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David I. Harvey

Not to be confused with: David Harvey

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Michael P. Clements & David I. Harvey, 2010. "Forecast encompassing tests and probability forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(6), pages 1028-1062.

    Mentioned in:

    1. Forecast encompassing tests and probability forecasts (Journal of Applied Econometrics 2010) in ReplicationWiki ()
  2. David Harvey & Paul Newbold, 2000. "Tests for multiple forecast encompassing," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 471-482.

    Mentioned in:

    1. Tests for multiple forecast encompassing (Journal of Applied Econometrics 2000) in ReplicationWiki ()

Working papers

  1. Harvey, David I & Leybourne, Stephen J & Taylor, AM Robert, 2021. "Simple Tests for Stock Return Predictability with Good Size and Power Properties," Essex Finance Centre Working Papers 29814, University of Essex, Essex Business School.

    Cited by:

    1. Christis Katsouris, 2023. "Structural Break Detection in Quantile Predictive Regression Models with Persistent Covariates," Papers 2302.05193, arXiv.org.
    2. Tassos Magdalinos & Katerina Petrova, 2022. "Uniform and Distribution-Free Inference with General Autoregressive Processes," Working Papers 1344, Barcelona School of Economics.
    3. Xiaosai Liao & Xinjue Li & Qingliang Fan, 2024. "Robust Inference for Multiple Predictive Regressions with an Application on Bond Risk Premia," Papers 2401.01064, arXiv.org.

  2. Harvey, David I & Leybourne, Stephen J & Sollis, Robert & Taylor, AM Robert, 2020. "Real-Time Detection of Regimes of Predictability in the U.S. Equity Premium," Essex Finance Centre Working Papers 27775, University of Essex, Essex Business School.

    Cited by:

    1. Rossi, Barbara & Odendahl, Florens & Sekhposyan, Tatevik, 2020. "Comparing Forecast Performance with State Dependence," CEPR Discussion Papers 15217, C.E.P.R. Discussion Papers.
    2. Florens Odendahl & Barbara Rossi & Tatevik Sekhposyan, 2021. "Evaluating Forecast Performance with State Dependence," Working Papers 1295, Barcelona School of Economics.
    3. Fan, Rui & Lee, Ji Hyung & Shin, Youngki, 2023. "Predictive quantile regression with mixed roots and increasing dimensions: The ALQR approach," Journal of Econometrics, Elsevier, vol. 237(2).
    4. Smith, Simon C., 2021. "International stock return predictability," International Review of Financial Analysis, Elsevier, vol. 78(C).
    5. Miriam Arden & Tiemen Woutersen, 2021. "A Balanced Portfolio Can Have a Higher Geometric Return Than the Risky Asset," JRFM, MDPI, vol. 14(9), pages 1-5, September.

  3. David Harvey & Stephen Leybourne & Yang Zu, 2018. "Testing explosive bubbles with time-varying volatility," Discussion Papers 18/05, University of Nottingham, Granger Centre for Time Series Econometrics.

    Cited by:

    1. Gil-Alana, Luis Alberiko & Dettoni, Robinson & Costamagna, Rodrigo & Valenzuela, Mario, 2019. "Rational bubbles in the real housing stock market: Empirical evidence from Santiago de Chile," Research in International Business and Finance, Elsevier, vol. 49(C), pages 269-281.
    2. Verena Monschang & Bernd Wilfling, 2019. "Sup-ADF-style bubble-detection methods under test," CQE Working Papers 7819, Center for Quantitative Economics (CQE), University of Muenster.
    3. Yang Hu, 2023. "A review of Phillips‐type right‐tailed unit root bubble detection tests," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 141-158, February.
    4. Stefan Richter & Weining Wang & Wei Biao Wu, 2018. "A supreme test for periodic explosive GARCH," Papers 1812.03475, arXiv.org.
    5. Stefan Richter & Weining Wang & Wei Biao Wu, 2023. "Testing for parameter change epochs in GARCH time series," The Econometrics Journal, Royal Economic Society, vol. 26(3), pages 467-491.
    6. Vicente Esteve & María A. Prats, 2022. "Testing explosive bubbles with time-varying volatility: The case of the Spanish public debt, 1850?2021," Working Papers 2205, Department of Applied Economics II, Universidad de Valencia.
    7. Zhang, Erhua & Wu, Jilin, 2020. "Adaptive estimation of AR∞ models with time-varying variances," Economics Letters, Elsevier, vol. 197(C).
    8. Skrobotov Anton, 2023. "Testing for explosive bubbles: a review," Dependence Modeling, De Gruyter, vol. 11(1), pages 1-26, January.
    9. Sam Astill & David I Harvey & Stephen J Leybourne & A M Robert Taylor & Yang Zu, 2023. "CUSUM-Based Monitoring for Explosive Episodes in Financial Data in the Presence of Time-Varying Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 21(1), pages 187-227.
    10. Yiu Lim Lui & Weilin Xiao & Jun Yu, 2021. "Mildly Explosive Autoregression with Anti‐persistent Errors," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(2), pages 518-539, April.
    11. Xuanling Yang & Dong Li & Ting Zhang, 2024. "A simple stochastic nonlinear AR model with application to bubble," Papers 2401.07038, arXiv.org.
    12. Esteve, Vicente & Prats, María A., 2023. "Testing explosive bubbles with time-varying volatility: The case of Spanish public debt," Finance Research Letters, Elsevier, vol. 51(C).
    13. Esteve, Vicente & Prats, María A., 2023. "Testing explosive bubbles with time-varying volatility: the case of Spanish public debt," LSE Research Online Documents on Economics 116980, London School of Economics and Political Science, LSE Library.

  4. Harvey, David I & Leybourne, Stephen J & Sollis, Robert & Taylor, AM Robert, 2018. "Detecting Regimes of Predictability in the U.S. Equity Premium," Essex Finance Centre Working Papers 23198, University of Essex, Essex Business School.

    Cited by:

    1. Sam Astill & David I. Harvey & Stephen J. Leybourne & Robert Sollis & A. M. Robert Taylor, 2018. "Real‐Time Monitoring for Explosive Financial Bubbles," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 863-891, November.

  5. David I. Harvey & Stephen J. Leybourne & Emily J. Whitehouse, 2017. "Forecast evaluation tests and negative long-run variance estimates in small samples," Discussion Papers 17/03, University of Nottingham, Granger Centre for Time Series Econometrics.

    Cited by:

    1. Lin, Yu & Lu, Qin & Tan, Bin & Yu, Yuanyuan, 2022. "Forecasting energy prices using a novel hybrid model with variational mode decomposition," Energy, Elsevier, vol. 246(C).
    2. Rubaszek, Michał & Karolak, Zuzanna & Kwas, Marek, 2020. "Mean-reversion, non-linearities and the dynamics of industrial metal prices. A forecasting perspective," Resources Policy, Elsevier, vol. 65(C).
    3. Arabinda Basistha & Richard Startz, 2023. "Measuring Persistent Global Economic Factors with Output, Commodity Price, and Commodity Currency Data," Working Papers 23-05, Department of Economics, West Virginia University.
    4. Galvao, Ana Beatriz & Owyang, Michael, 2020. "Forecasting Low Frequency Macroeconomic Events with High Frequency Data," EMF Research Papers 38, Economic Modelling and Forecasting Group.
    5. Zhou, Jin & Li, Haiqi & Zhong, Wanling, 2021. "A modified Diebold–Mariano test for equal forecast accuracy with clustered dependence," Economics Letters, Elsevier, vol. 207(C).
    6. Coroneo, Laura & Iacone, Fabrizio & Paccagnini, Alessia & Santos Monteiro, Paulo, 2023. "Testing the predictive accuracy of COVID-19 forecasts," International Journal of Forecasting, Elsevier, vol. 39(2), pages 606-622.
    7. Laura Coroneo & Fabrizio Iacone, 2020. "Comparing predictive accuracy in small samples using fixed‐smoothing asymptotics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(4), pages 391-409, June.
    8. Håvard Hungnes, 2020. "Equal predictability test for multi-step-ahead system forecasts invariant to linear transformations," Discussion Papers 931, Statistics Norway, Research Department.
    9. Galvao, Ana Beatriz & Garratt, Anthony & Mitchell, James, 2020. "Does Judgment Improve Macroeconomic Density Forecasts?," EMF Research Papers 33, Economic Modelling and Forecasting Group.
    10. Timo Dimitriadis & Xiaochun Liu & Julie Schnaitmann, 2020. "Encompassing Tests for Value at Risk and Expected Shortfall Multi-Step Forecasts based on Inference on the Boundary," Papers 2009.07341, arXiv.org.
    11. Rubaszek Michal & Karolak Zuzanna & Kwas Marek & Uddin Gazi Salah, 2020. "The role of the threshold effect for the dynamics of futures and spot prices of energy commodities," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(5), pages 1-20, December.
    12. Schlösser, Alexander, 2020. "Forecasting industrial production in Germany: The predictive power of leading indicators," Ruhr Economic Papers 838, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    13. Kwas, Marek & Paccagnini, Alessia & Rubaszek, Michał, 2021. "Common factors and the dynamics of industrial metal prices. A forecasting perspective," Resources Policy, Elsevier, vol. 74(C).
    14. Costantini, Mauro & Kunst, Robert M., 2021. "On using predictive-ability tests in the selection of time-series prediction models: A Monte Carlo evaluation," International Journal of Forecasting, Elsevier, vol. 37(2), pages 445-460.
    15. Hwee Kwan Chow & Yijie Fei & Daniel Han, 2023. "Forecasting GDP with many predictors in a small open economy: forecast or information pooling?," Empirical Economics, Springer, vol. 65(2), pages 805-829, August.
    16. Qin Lu & Jingwen Liao & Kechi Chen & Yanhui Liang & Yu Lin, 2024. "Predicting Natural Gas Prices Based on a Novel Hybrid Model with Variational Mode Decomposition," Computational Economics, Springer;Society for Computational Economics, vol. 63(2), pages 639-678, February.
    17. Wang, Lu & Ma, Feng & Liu, Jing & Yang, Lin, 2020. "Forecasting stock price volatility: New evidence from the GARCH-MIDAS model," International Journal of Forecasting, Elsevier, vol. 36(2), pages 684-694.

  6. Iliyan Georgiev & David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2017. "A bootstrap stationarity test for predictive regression invalidity," Discussion Papers 17/04, University of Nottingham, Granger Centre for Time Series Econometrics.

    Cited by:

    1. Giuseppe Cavaliere & Iliyan Georgiev, 2019. "Inference under random limit bootstrap measures," Papers 1911.12779, arXiv.org, revised Dec 2019.
    2. Yang, Bingduo & Long, Wei & Yang, Zihui, 2022. "Testing predictability of stock returns under possible bubbles," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 246-260.
    3. Demetrescu, Matei & Rodrigues, Paulo M.M., 2022. "Residual-augmented IVX predictive regression," Journal of Econometrics, Elsevier, vol. 227(2), pages 429-460.
    4. Demetrescu, Matei & Rodrigues, Paulo M.M. & Taylor, A.M. Robert, 2023. "Transformed regression-based long-horizon predictability tests," Journal of Econometrics, Elsevier, vol. 237(2).
    5. Georgiev, I & Harvey, DI & Leybourne, SJ & Taylor, AM, 2018. "Testing for Parameter Instability in Predictive Regression Models," Essex Finance Centre Working Papers 21162, University of Essex, Essex Business School.
    6. Paulo M.M. Rodrigues & Matei Demetrescu, 2019. "Testing for Episodic Predictability in Stock Returns," Working Papers w201906, Banco de Portugal, Economics and Research Department.
    7. Fukang Zhu & Mengya Liu & Shiqing Ling & Zongwu Cai, 2020. "Testing for Structural Change of Predictive Regression Model to Threshold Predictive Regression Model," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202021, University of Kansas, Department of Economics, revised Dec 2020.
    8. Xiaohui Liu & Yuzi Liu & Yao Rao & Fucai Lu, 2021. "A Unified test for the Intercept of a Predictive Regression Model," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(2), pages 571-588, April.
    9. Christis Katsouris, 2023. "Predictability Tests Robust against Parameter Instability," Papers 2307.15151, arXiv.org.

  7. Chrystalleni Aristidou & David Harvey & Stephen Leybourne, 2016. "The impact of the initial condition on covariate augmented unit root tests," Discussion Papers 16/01, University of Nottingham, Granger Centre for Time Series Econometrics.

    Cited by:

    1. Chrystalleni Aristidou & David Harvey & Stephen Leybourne, 2016. "The impact of the initial condition on covariate augmented unit root tests," Discussion Papers 16/01, University of Nottingham, Granger Centre for Time Series Econometrics.

  8. Sam Astill & David Harvey & Stephen Leybourne & Robert Taylor, 2016. "Tests for an end-of-sample bubble in financial time series," Discussion Papers 16/02, University of Nottingham, Granger Centre for Time Series Econometrics.

    Cited by:

    1. Gil-Alana, Luis Alberiko & Dettoni, Robinson & Costamagna, Rodrigo & Valenzuela, Mario, 2019. "Rational bubbles in the real housing stock market: Empirical evidence from Santiago de Chile," Research in International Business and Finance, Elsevier, vol. 49(C), pages 269-281.
    2. Sinelnikova-Muryleva, Elena & Skrobotov, Anton, 2017. "Testing time series for the bubbles (with application to Russian data)," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 46, pages 90-103.
    3. Sam Astill & David I. Harvey & Stephen J. Leybourne & Robert Sollis & A. M. Robert Taylor, 2018. "Real‐Time Monitoring for Explosive Financial Bubbles," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 863-891, November.
    4. Escobari, Diego & Garcia, Sergio & Mellado, Cristhian, 2017. "Identifying bubbles in Latin American equity markets: Phillips-Perron-based tests and linkages," Emerging Markets Review, Elsevier, vol. 33(C), pages 90-101.
    5. Moreira, Afonso M. & Martins, Luis F., 2020. "A new mechanism for anticipating price exuberance," International Review of Economics & Finance, Elsevier, vol. 65(C), pages 199-221.
    6. Astill, Sam & Taylor, A.M. Robert & Kellard, Neil & Korkos, Ioannis, 2023. "Using covariates to improve the efficacy of univariate bubble detection methods," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 342-366.
    7. Frank J. Fabozzi & Iason Kynigakis & Ekaterini Panopoulou & Radu S. Tunaru, 2020. "Detecting Bubbles in the US and UK Real Estate Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 60(4), pages 469-513, May.
    8. Sam Astill & David I Harvey & Stephen J Leybourne & A M Robert Taylor & Yang Zu, 2023. "CUSUM-Based Monitoring for Explosive Episodes in Financial Data in the Presence of Time-Varying Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 21(1), pages 187-227.
    9. Eiji Kurozumi, 2018. "Confidence Sets for the Date of a Structural Change at the End of a Sample," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 850-862, November.
    10. KUROZUMI, Eiji & 黒住, 英司, 2017. "Confidence Sets for the Date of a Mean Shift at the End of a Sample," Discussion Papers 2017-06, Graduate School of Economics, Hitotsubashi University.
    11. Christopher Lynch & Benjamin Mestel, 2019. "Change-Point Analysis Of Asset Price Bubbles With Power-Law Hazard Function," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 22(07), pages 1-24, November.

  9. David Harvey & Stephen Leybourne, 2014. "Confidence sets for the date of a break in level and trend when the order of integration is unknown," Discussion Papers 14/04, University of Nottingham, Granger Centre for Time Series Econometrics.

    Cited by:

    1. KUROZUMI, Eiji & 黒住, 英司 & SKROBOTOV, Anton, 2016. "Confidence Sets for the Break Date in Cointegrating Regressions," Discussion Papers 2016-07, Graduate School of Economics, Hitotsubashi University.
    2. Harvey, David I. & Leybourne, Stephen J., 2016. "Improving the length of confidence sets for the date of a break in level and trend when the order of integration is unknown," Economics Letters, Elsevier, vol. 145(C), pages 239-245.
    3. Skrobotov, Anton, 2020. "Survey on structural breaks and unit root tests," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 58, pages 96-141.
    4. Yicong Lin & Mingxuan Song, 2023. "Robust bootstrap inference for linear time-varying coefficient models: Some Monte Carlo evidence," Tinbergen Institute Discussion Papers 23-049/III, Tinbergen Institute.

  10. David I. Harvey & Stephen J. Leybourne, 2013. "Break date estimation for models with deterministic structural change," Discussion Papers 13/02, University of Nottingham, Granger Centre for Time Series Econometrics.

    Cited by:

    1. Anton Skrobotov, 2016. "On Trend Breaks and Initial Condition in Unit Root Testing," Working Papers 0097, Gaidar Institute for Economic Policy, revised 2016.
    2. Skrobotov, Anton (Скроботов, Антон), 2015. "About Trend, the Shift and the Initial Value in Testing of the Hypothesis of a Unit Root [О Тренде, Сдвиге И Начальном Значении В Тестировании Гипотезы О Наличии Единичного Корня]," Published Papers mak6, Russian Presidential Academy of National Economy and Public Administration.
    3. Harvey, David I. & Leybourne, Stephen J., 2015. "Confidence sets for the date of a break in level and trend when the order of integration is unknown," Journal of Econometrics, Elsevier, vol. 184(2), pages 262-279.
    4. Anton Skrobotov, 2012. "Bias Correction of KPSS Test with Structural Break for Reducing of Size Distortion," Working Papers 0043, Gaidar Institute for Economic Policy, revised 2013.
    5. Ioanna Konstantakopoulou, 2017. "The aggregate exports-GDP relation under the prism of infrequent trend breaks and multi-horizon causality," International Economics and Economic Policy, Springer, vol. 14(4), pages 661-689, October.
    6. Yiannis Karavias & Elias Tzavalis, 2014. "Testing for unit roots in panels with structural changes, spatial and temporal dependence when the time dimension is finite," Discussion Papers 14/03, University of Nottingham, Granger Centre for Time Series Econometrics.
    7. Harvey, David I. & Leybourne, Stephen J., 2016. "Improving the length of confidence sets for the date of a break in level and trend when the order of integration is unknown," Economics Letters, Elsevier, vol. 145(C), pages 239-245.
    8. Skrobotov, Anton, 2020. "Survey on structural breaks and unit root tests," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 58, pages 96-141.
    9. Yicong Lin & Mingxuan Song, 2023. "Robust bootstrap inference for linear time-varying coefficient models: Some Monte Carlo evidence," Tinbergen Institute Discussion Papers 23-049/III, Tinbergen Institute.

  11. David Harvey & Neil Kellard & Jakob Madsen & Mark Wohar, 2012. "Trends and Cycles in Real Commodity Prices: 1650-2010," CEH Discussion Papers 010, Centre for Economic History, Research School of Economics, Australian National University.

    Cited by:

    1. Gil-Alana, Luis A. & Aye, Goodness C. & Gupta, Rangan, 2015. "Trends and cycles in historical gold and silver prices," Journal of International Money and Finance, Elsevier, vol. 58(C), pages 98-109.
    2. Han, Liyan & Xu, Yang & Yin, Libo, 2017. "Does investor attention matter? The attention-return relation in gold futures market," Economics Discussion Papers 2017-37, Kiel Institute for the World Economy (IfW Kiel).
    3. Awaworyi-Churchill, Sefa & Inekwe, John & Ivanovski, Kris & Smyth, Russell, 2022. "Breaks, trends and correlations in commodity prices in the very long-run," Energy Economics, Elsevier, vol. 108(C).

  12. David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2011. "Robust methods for detecting multiple level breaks in autocorrelated time series," Discussion Papers 11/01, University of Nottingham, Granger Centre for Time Series Econometrics.

    Cited by:

    1. Matteo Mogliani, 2010. "Residual-based tests for cointegration and multiple deterministic structural breaks: A Monte Carlo study," PSE Working Papers halshs-00564897, HAL.
    2. Ghoshray Atanu & Kejriwal Mohitosh & Wohar Mark, 2014. "Breaks, trends and unit roots in commodity prices: a robust investigation," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(1), pages 23-40, February.
    3. Mohitosh Kejriwal & Pierre Perron, 2009. "A Sequential Procedure to Determine the Number of Breaks in Trend with an Integrated or Stationary Noise Component," Purdue University Economics Working Papers 1217, Purdue University, Department of Economics.
    4. Josep Lluís Carrion-I-Silvestre & María Dolores Gadea, 2016. "Bounds, Breaks and Unit Root Tests," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(2), pages 165-181, March.
    5. Claudio Morana, 2014. "Factor Vector Autoregressive Estimation of Heteroskedastic Persistent and Non Persistent Processes Subject to Structural Breaks," Working Papers 273, University of Milano-Bicocca, Department of Economics, revised May 2014.
    6. Mar'ia Jos'e Presno & Manuel Landajo & Paula Fern'andez Gonz'alez, 2024. "Stochastic convergence in per capita CO$_2$ emissions. An approach from nonlinear stationarity analysis," Papers 2402.00567, arXiv.org.
    7. Fabien Candau & Michaël Goujon & Jean-François Hoarau & Serge Rey, 2013. "Real exchange rate and competitiveness of an EU’s ultra-peripheral region: La Reunion Island," Working papers of CATT hal-01847942, HAL.
    8. Chambers, Marcus J. & Ercolani, Joanne S. & Taylor, A.M. Robert, 2014. "Testing for seasonal unit roots by frequency domain regression," Journal of Econometrics, Elsevier, vol. 178(P2), pages 243-258.
    9. Harvey, David I. & Leybourne, Stephen J., 2015. "Confidence sets for the date of a break in level and trend when the order of integration is unknown," Journal of Econometrics, Elsevier, vol. 184(2), pages 262-279.
    10. Anton Skrobotov, 2014. "A simple modification of the Busetti-Harvey stationarity tests with structural breaks at unknown time," Working Papers 0102, Gaidar Institute for Economic Policy, revised 2014.
    11. Paulo M.M. Rodrigues & Nuno Sobreira, 2013. "Characterizing economic growth paths based on new structural change tests," Working Papers w201313, Banco de Portugal, Economics and Research Department.
    12. Presno, María José & Landajo, Manuel & Fernández González, Paula, 2018. "Stochastic convergence in per capita CO2 emissions. An approach from nonlinear stationarity analysis," Energy Economics, Elsevier, vol. 70(C), pages 563-581.
    13. Mohitosh Kejriwal & Claude Lopez, 2013. "Unit Roots, Level Shifts, and Trend Breaks in Per Capita Output: A Robust Evaluation," Econometric Reviews, Taylor & Francis Journals, vol. 32(8), pages 892-927, November.
    14. Amélie Charles & Olivier Darné & Jean-François Hoarau, 2019. "How resilient is La Réunion in terms of international tourism attractiveness: an assessment from unit root tests with structural breaks from 1981-2015," Post-Print hal-02053296, HAL.
    15. David I. Harvey & Stephen J. Leybourne, 2013. "Break date estimation for models with deterministic structural change," Discussion Papers 13/02, University of Nottingham, Granger Centre for Time Series Econometrics.
    16. Josep Lluís Carrion-i-Silvestre & María Dolores Gadea, 2021. ""Detecting multiple level shifts in bounded time series"," IREA Working Papers 202115, University of Barcelona, Research Institute of Applied Economics, revised Jul 2021.
    17. Zerbo, Eléazar & Darné, Olivier, 2019. "On the stationarity of CO2 emissions in OECD and BRICS countries: A sequential testing approach," Energy Economics, Elsevier, vol. 83(C), pages 319-332.
    18. Skrobotov, Anton, 2020. "Survey on structural breaks and unit root tests," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 58, pages 96-141.
    19. Manuel Landajo & Mar'ia Jos'e Presno, 2024. "The prices of renewable commodities: A robust stationarity analysis," Papers 2402.01005, arXiv.org.
    20. Presno, María José & Landajo, Manuel & Fernández, Paula, 2012. "Non-renewable resource prices. A robust evaluation from the stationarity perspective," MPRA Paper 42523, University Library of Munich, Germany.
    21. Manuel Landajo & María José Presno, 2022. "The prices of renewable commodities: a robust stationarity analysis," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 66(2), pages 447-470, April.
    22. Josep Lluís Carrion-i-Silvestre & Maria Dolores Gadea, 2015. "Testing for multiple level shifts in I(0) and I(1) stochastic processes," EcoMod2015 8702, EcoMod.
    23. Ghoshray, A., 2018. "The Dynamic Properties of Natural Resource Prices," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277210, International Association of Agricultural Economists.
    24. Ghoshray, Atanu & Kejriwal, Mohitosh & Wohar, Mark E., 2011. "Breaking Trends and the Prebisch-Singer Hypothesis: A Further Investigation," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 120387, European Association of Agricultural Economists.
    25. Presno, María José & Landajo, Manuel & Fernández, Paula, 2014. "Non-renewable resource prices: A robust evaluation from the stationarity perspective," Resource and Energy Economics, Elsevier, vol. 36(2), pages 394-416.
    26. Josep Lluís Carrion‐i‐Silvestre & María Dolores Gadea, 2023. "Testing for multiple level shifts with an integrated or stationary noise component," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(6), pages 801-819, September.
    27. Paulo M. M. Rodrigues, 2013. "Recursive adjustment, unit root tests and structural breaks," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(1), pages 62-82, January.
    28. Sobreira, Nuno & Nunesz, Luis C. & Rodriguesz, Paulo M. M., 2012. "Neoclassical, semi-endogenous or endogenous growth theory? Evidence based on new structural change tests," Insper Working Papers wpe_291, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    29. Awaworyi Churchill, Sefa & Inekwe, John & Ivanovski, Kris & Smyth, Russell, 2020. "Stationarity properties of per capita CO2 emissions in the OECD in the very long-run: A replication and extension analysis," Energy Economics, Elsevier, vol. 90(C).
    30. Atanu Ghoshray & Issam Malki & Javier Ordóñez, 2022. "On the long-run dynamics of income and wealth inequality," Empirical Economics, Springer, vol. 62(2), pages 375-408, February.

  13. David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2011. "Unit root testing under a local break in trend," Discussion Papers 11/02, University of Nottingham, Granger Centre for Time Series Econometrics.

    Cited by:

    1. Anton Skrobotov, 2013. "Local Structural Trend Break in Stationarity Testing," Working Papers 0074, Gaidar Institute for Economic Policy, revised 2013.
    2. Anton Skrobotov, 2016. "On Trend Breaks and Initial Condition in Unit Root Testing," Working Papers 0097, Gaidar Institute for Economic Policy, revised 2016.
    3. Skrobotov, Anton (Скроботов, Антон), 2015. "About Trend, the Shift and the Initial Value in Testing of the Hypothesis of a Unit Root [О Тренде, Сдвиге И Начальном Значении В Тестировании Гипотезы О Наличии Единичного Корня]," Published Papers mak6, Russian Presidential Academy of National Economy and Public Administration.
    4. Marilena Furno, 2021. "Cointegration tests at the quantiles," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1087-1100, January.
    5. Anton Skrobotov, 2014. "A simple modification of the Busetti-Harvey stationarity tests with structural breaks at unknown time," Working Papers 0102, Gaidar Institute for Economic Policy, revised 2014.
    6. Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2013. "Testing for unit roots in the possible presence of multiple trend breaks using minimum Dickey–Fuller statistics," Journal of Econometrics, Elsevier, vol. 177(2), pages 265-284.
    7. Skrobotov, Anton, 2020. "Survey on structural breaks and unit root tests," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 58, pages 96-141.
    8. David Harris & Hsein Kew & A. M. Robert Taylor, 2020. "Level Shift Estimation in the Presence of Non-stationary Volatility with an Application to the Unit Root Testing Problem," Monash Econometrics and Business Statistics Working Papers 8/20, Monash University, Department of Econometrics and Business Statistics.
    9. Neil Kellard & Denise Osborn & Jerry Coakley & Giuseppe Cavaliere & David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2015. "Testing for Unit Roots Under Multiple Possible Trend Breaks and Non-Stationary Volatility Using Bootstrap Minimum Dickey–Fuller Statistics," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(5), pages 603-629, September.
    10. Meligkotsidou, Loukia & Tzavalis, Elias & Vrontos, Ioannis, 2017. "On Bayesian analysis and unit root testing for autoregressive models in the presence of multiple structural breaks," Econometrics and Statistics, Elsevier, vol. 4(C), pages 70-90.

  14. David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2009. "The impact of the initial condition on robust tests for a linear trend," Discussion Papers 09/03, University of Nottingham, Granger Centre for Time Series Econometrics.

    Cited by:

    1. Anton Skrobotov, 2016. "On Trend Breaks and Initial Condition in Unit Root Testing," Working Papers 0097, Gaidar Institute for Economic Policy, revised 2016.
    2. Skrobotov, Anton (Скроботов, Антон), 2015. "About Trend, the Shift and the Initial Value in Testing of the Hypothesis of a Unit Root [О Тренде, Сдвиге И Начальном Значении В Тестировании Гипотезы О Наличии Единичного Корня]," Published Papers mak6, Russian Presidential Academy of National Economy and Public Administration.
    3. Elliott, Graham, 2020. "Testing for a trend with persistent errors," University of California at San Diego, Economics Working Paper Series qt8qb0j5s7, Department of Economics, UC San Diego.
    4. Anton Skrobotov, 2015. "Trend and Initial Condition in Stationarity Tests: The Asymptotic Analysis," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(2), pages 254-273, April.
    5. Terence Mills, 2013. "Breaks and unit roots in global and hemispheric temperatures: an updated analysis," Climatic Change, Springer, vol. 118(3), pages 745-755, June.

  15. David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2009. "Robust methods for detecting multiple level breaks in autocorrelated time series [Revised to become No. 10/01 above]," Discussion Papers 09/01, University of Nottingham, Granger Centre for Time Series Econometrics.

    Cited by:

    1. Matteo Mogliani, 2010. "Residual-based tests for cointegration and multiple deterministic structural breaks: A Monte Carlo study," PSE Working Papers halshs-00564897, HAL.

  16. Giuseppe Cavaliere & David I. Harvey & Stephen J. Leybourne & A.M. Robert Taylor, 2008. "Testing for Unit Roots in the Presence of a Possible Break in Trend and Non-Stationary Volatility," CREATES Research Papers 2008-62, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Terence C. Mills, 2013. "Trends, cycles and structural breaks," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 3, pages 45-60, Edward Elgar Publishing.
    2. Balcombe, Kelvin & Fraser, Iain, 2017. "Do bubbles have an explosive signature in markov switching models?," Economic Modelling, Elsevier, vol. 66(C), pages 81-100.
    3. Anton Skrobotov, 2016. "On Trend Breaks and Initial Condition in Unit Root Testing," Working Papers 0097, Gaidar Institute for Economic Policy, revised 2016.
    4. Francesca Iorio & Stefano Fachin, 2014. "Savings and investments in the OECD: a panel cointegration study with a new bootstrap test," Empirical Economics, Springer, vol. 46(4), pages 1271-1300, June.
    5. Vitaly Pershin & Juan Carlos Molero & Fernando Pérez de Gracia, 2015. "Exploring the oil prices and exchange rates nexus in some African economies," Faculty Working Papers 01/15, School of Economics and Business Administration, University of Navarra.
    6. Sebastian Fossati, 2013. "Unit root testing with stationary covariates and a structural break in the trend function," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(3), pages 368-384, May.
    7. Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2009. "Unit Root Testing In Practice: Dealing With Uncertainty Over The Trend And Initial Condition," Econometric Theory, Cambridge University Press, vol. 25(3), pages 587-636, June.
    8. Niels Haldrup & Robinson Kruse & Timo Teräsvirta & Rasmus T. Varneskov, 2013. "Unit roots, non-linearities and structural breaks," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 4, pages 61-94, Edward Elgar Publishing.
    9. Russo, Emanuele & Foster-McGregor, Neil & Verspagen, Bart, 2019. "Characterizing growth instability: new evidence on unit roots and structural breaks in long run time series," MERIT Working Papers 2019-026, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    10. Apergis, Nicholas & Bowden, Nicholas & Payne, James E., 2015. "Downstream integration of natural gas prices across U.S. states: Evidence from deregulation regime shifts," Energy Economics, Elsevier, vol. 49(C), pages 82-92.
    11. Lajos Horváth & Piotr Kokoszka & Jeremy VanderDoes & Shixuan Wang, 2022. "Inference in functional factor models with applications to yield curves," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(6), pages 872-894, November.
    12. Mohitosh Kejriwal & Claude Lopez, 2013. "Unit Roots, Level Shifts, and Trend Breaks in Per Capita Output: A Robust Evaluation," Econometric Reviews, Taylor & Francis Journals, vol. 32(8), pages 892-927, November.
    13. Addison, Tony & Ghoshray, Atanu, 2023. "Discerning trends in international metal prices in the presence of nonstationary volatility," Resource and Energy Economics, Elsevier, vol. 71(C).
    14. Sven Otto, 2020. "Unit Root Testing with Slowly Varying Trends," Papers 2003.04066, arXiv.org, revised Aug 2020.
    15. Harris, David & Leybourne, Stephen J. & Taylor, A.M. Robert, 2016. "Tests of the co-integration rank in VAR models in the presence of a possible break in trend at an unknown point," Journal of Econometrics, Elsevier, vol. 192(2), pages 451-467.
    16. Górecki, Tomasz & Horváth, Lajos & Kokoszka, Piotr, 2018. "Change point detection in heteroscedastic time series," Econometrics and Statistics, Elsevier, vol. 7(C), pages 63-88.
    17. Skrobotov, Anton, 2020. "Survey on structural breaks and unit root tests," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 58, pages 96-141.
    18. David Harris & Hsein Kew & A. M. Robert Taylor, 2020. "Level Shift Estimation in the Presence of Non-stationary Volatility with an Application to the Unit Root Testing Problem," Monash Econometrics and Business Statistics Working Papers 8/20, Monash University, Department of Econometrics and Business Statistics.
    19. Husein, Jamal, 2020. "Current account sustainability for 21 African economies: Evidence based on nonlinear flexible Fourier stationarity and unit-root tests," MPRA Paper 100410, University Library of Munich, Germany.
    20. Dervis Kirikkaleli & Hasan Güngör, 2021. "Co-movement of commodity price indexes and energy price index: a wavelet coherence approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-18, December.
    21. Börger, Matthias & Schupp, Johannes, 2018. "Modeling trend processes in parametric mortality models," Insurance: Mathematics and Economics, Elsevier, vol. 78(C), pages 369-380.
    22. David I. Harvey, & Stephen J. Leybourne, & A. M. Robert Taylor, 2007. "Testing for a unit root when uncertain about the trend [Revised to become 07/03 above]," Discussion Papers 06/03, University of Nottingham, Granger Centre for Time Series Econometrics.
    23. Sun, Jingwei & Shi, Wendong, 2015. "Breaks, trends, and unit roots in spot prices for crude oil and petroleum products," Energy Economics, Elsevier, vol. 50(C), pages 169-177.
    24. Paulo M. M. Rodrigues, 2013. "Recursive adjustment, unit root tests and structural breaks," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(1), pages 62-82, January.
    25. Emanuele Russo & Neil Foster-McGregor, 2022. "Characterizing growth instability: new evidence on unit roots and structural breaks in countries’ long run trajectories," Journal of Evolutionary Economics, Springer, vol. 32(2), pages 713-756, April.
    26. Terence Mills, 2013. "Breaks and unit roots in global and hemispheric temperatures: an updated analysis," Climatic Change, Springer, vol. 118(3), pages 745-755, June.
    27. Aquino, Juan, 2019. "The Small Open Economy New-Keynesian Phillips Curve: Specification, Structural Breaks and Robustness," Working Papers 2019-019, Banco Central de Reserva del Perú.
    28. Sven Otto, 2021. "Unit root testing with slowly varying trends," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(1), pages 85-106, January.
    29. Neil Kellard & Denise Osborn & Jerry Coakley & Giuseppe Cavaliere & David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2015. "Testing for Unit Roots Under Multiple Possible Trend Breaks and Non-Stationary Volatility Using Bootstrap Minimum Dickey–Fuller Statistics," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(5), pages 603-629, September.
    30. Wang, Shaoping & Li, Yanglin & Wen, Kuangyu, 2021. "Recursive adjusted unit root tests under non-stationary volatility," Economics Letters, Elsevier, vol. 205(C).

  17. David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2008. "Seasonal unit root tests and the role of initial conditions," Discussion Papers 08/01, University of Nottingham, Granger Centre for Time Series Econometrics.

    Cited by:

    1. Anton Skrobotov, 2013. "On GLS-detrending for deterministic seasonality testing," Working Papers 0073, Gaidar Institute for Economic Policy, revised 2014.

  18. David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2008. "Testing for unit roots and the impact of quadratic trends, with an application to relative primary commodity prices," Discussion Papers 08/04, University of Nottingham, Granger Centre for Time Series Econometrics.

    Cited by:

    1. Georgios Bertsatos & Plutarchos Sakellaris & Mike G. Tsionas, 2022. "Extensions of the Pesaran, Shin and Smith (2001) bounds testing procedure," Empirical Economics, Springer, vol. 62(2), pages 605-634, February.
    2. Marcos Sanso-Navarro, 2011. "Broken trend stationarity of hours worked," Post-Print hal-00712742, HAL.
    3. Winkelried, Diego, 2015. "Unit Roots, Flexible Trends and the Prebisch-Singer Hypothesis," Working Papers 2015-007, Banco Central de Reserva del Perú.
    4. Winkelried, Diego, 2021. "Unit roots in real primary commodity prices? A meta-analysis of the Grilli and Yang data set," Journal of Commodity Markets, Elsevier, vol. 23(C).
    5. Ligang Liu & Andrew Tsang, 2008. "Pass‐through Effects of Global Commodity Prices on China's Inflation: An Empirical Investigation," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 16(6), pages 22-34, November.
    6. Yiannis Karavias & Elias Tzavalis, 2014. "Testing for unit roots in panels with structural changes, spatial and temporal dependence when the time dimension is finite," Discussion Papers 14/03, University of Nottingham, Granger Centre for Time Series Econometrics.
    7. Manuel Landajo & Mar'ia Jos'e Presno, 2024. "The prices of renewable commodities: A robust stationarity analysis," Papers 2402.01005, arXiv.org.
    8. Presno, María José & Landajo, Manuel & Fernández, Paula, 2012. "Non-renewable resource prices. A robust evaluation from the stationarity perspective," MPRA Paper 42523, University Library of Munich, Germany.
    9. Manuel Landajo & María José Presno, 2022. "The prices of renewable commodities: a robust stationarity analysis," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 66(2), pages 447-470, April.
    10. Westerlund, Joakim, 2013. "Simple unit root testing in generally trending data with an application to precious metal prices in Asia," Journal of Asian Economics, Elsevier, vol. 28(C), pages 12-27.
    11. Yamada, Hiroshi & Yoon, Gawon, 2014. "When Grilli and Yang meet Prebisch and Singer: Piecewise linear trends in primary commodity prices," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 193-207.
    12. Manuel Landajo & María José Presno & Paula Fernández González, 2021. "Stationarity in the Prices of Energy Commodities. A Nonparametric Approach," Energies, MDPI, vol. 14(11), pages 1-16, June.
    13. Presno, María José & Landajo, Manuel & Fernández, Paula, 2014. "Non-renewable resource prices: A robust evaluation from the stationarity perspective," Resource and Energy Economics, Elsevier, vol. 36(2), pages 394-416.
    14. Lan Cheng & Xuguang Simon Sheng, 2017. "Combination of “combinations of p values”," Empirical Economics, Springer, vol. 53(1), pages 329-350, August.
    15. Gonçalves, Thallis Macedo de Assis & Cerqueira, Luiz Fernando & Feijó, Carmem Aparecida, 2023. "Pass-through of exchange rate shocks in Brazil as a small open economy," Revista CEPAL, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), April.
    16. Westerlund, Joakim, 2015. "The effect of recursive detrending on panel unit root tests," Journal of Econometrics, Elsevier, vol. 185(2), pages 453-467.

  19. David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2008. "Testing for unit roots in the presence of uncertainty over both the trend and initial condition," Discussion Papers 08/03, University of Nottingham, Granger Centre for Time Series Econometrics.

    Cited by:

    1. David I. Harvey & Stephen J. Leybourne & Emily J. Whitehouse, 2017. "Testing for a unit root against ESTAR stationarity," Discussion Papers 17/02, University of Nottingham, Granger Centre for Time Series Econometrics.
    2. Anton Skrobotov, 2016. "On Trend Breaks and Initial Condition in Unit Root Testing," Working Papers 0097, Gaidar Institute for Economic Policy, revised 2016.
    3. Milda Norkute, 2015. "Can the sectoral New Keynesian Phillips curve explain inflation dynamics in the Euro Area?," Empirical Economics, Springer, vol. 49(4), pages 1191-1216, December.
    4. Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2012. "Testing for unit roots in the presence of uncertainty over both the trend and initial condition," Journal of Econometrics, Elsevier, vol. 169(2), pages 188-195.
    5. Skrobotov, Anton (Скроботов, Антон), 2015. "About Trend, the Shift and the Initial Value in Testing of the Hypothesis of a Unit Root [О Тренде, Сдвиге И Начальном Значении В Тестировании Гипотезы О Наличии Единичного Корня]," Published Papers mak6, Russian Presidential Academy of National Economy and Public Administration.
    6. Stephan Smeekes, 2013. "Detrending Bootstrap Unit Root Tests," Econometric Reviews, Taylor & Francis Journals, vol. 32(8), pages 869-891, November.
    7. Saeid Mahdavi & Joakim Westerlund, 2017. "Are state–local government expenditures converging? New evidence based on sequential unit root tests," Empirical Economics, Springer, vol. 53(2), pages 373-403, September.
    8. Niels Haldrup & Robinson Kruse & Timo Teräsvirta & Rasmus T. Varneskov, 2013. "Unit roots, non-linearities and structural breaks," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 4, pages 61-94, Edward Elgar Publishing.
    9. Smeekes, Stephan & Taylor, A.M. Robert, 2012. "Bootstrap Union Tests For Unit Roots In The Presence Of Nonstationary Volatility," Econometric Theory, Cambridge University Press, vol. 28(2), pages 422-456, April.
    10. Ghoshray, Atanu, 2021. "Are coffee farmers worse off in the long run?," 95th Annual Conference, March 29-30, 2021, Warwick, UK (Hybrid) 311084, Agricultural Economics Society - AES.
    11. Marques, André M. & Lima, Gilberto Tadeu, 2022. "Testing for Granger causality in quantiles between the wage share in income and productive capacity utilization," Structural Change and Economic Dynamics, Elsevier, vol. 62(C), pages 290-312.
    12. Sandberg, Rickard, 2016. "Trends, unit roots, structural changes, and time-varying asymmetries in U.S. macroeconomic data: the Stock and Watson data re-examined," Economic Modelling, Elsevier, vol. 52(PB), pages 699-713.
    13. Addison, Tony & Ghoshray, Atanu, 2023. "Discerning trends in international metal prices in the presence of nonstationary volatility," Resource and Energy Economics, Elsevier, vol. 71(C).
    14. Andre M. Marques & Gilberto Tadeu Lima, 2021. "Testing for Granger Causality in Quantiles Between the Wage Share and Capacity Utilization," Working Papers, Department of Economics 2021_03, University of São Paulo (FEA-USP).
    15. Giuseppe Cavaliere & Dimitris N. Politis & Anders Rahbek & Stephan Smeekes, 2015. "Recent developments in bootstrap methods for dependent data," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(3), pages 398-415, May.
    16. Anton Skrobotov, 2015. "Trend and Initial Condition in Stationarity Tests: The Asymptotic Analysis," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(2), pages 254-273, April.
    17. Ghoshray, Atanu, 2022. "Trends and persistence of farm-gate coffee prices around the world," 96th Annual Conference, April 4-6, 2022, K U Leuven, Belgium 321166, Agricultural Economics Society - AES.
    18. Smeekes, S., 2011. "Bootstrap sequential tests to determine the stationary units in a panel," Research Memorandum 003, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    19. Xu, Deyi & Sheraz, Muhammad & Hassan, Arshad & Sinha, Avik & Ullah, Saif, 2022. "Financial development, renewable energy and CO2 emission in G7 countries: New evidence from non-linear and asymmetric analysis," Energy Economics, Elsevier, vol. 109(C).
    20. Jeremy Nguyen & Jen-je Su, 2015. "Combining linear and nonlinear unit root tests with an application to PPP," Economics Bulletin, AccessEcon, vol. 35(4), pages 2796-2801.
    21. Su, Jen-Je & Nguyen, Jeremy K., 2013. "Alternative unit root testing strategies using the Fourier approximation," Economics Letters, Elsevier, vol. 121(1), pages 8-11.

  20. David Harris & David I. Harvey & Stephen J. Leybourne & Nikoloas D. Sakkas, 2008. "Local asymptotic power of the Im-Pesaran-Shin panel unit root test and the impact of initial observations," Discussion Papers 08/02, University of Nottingham, Granger Centre for Time Series Econometrics.

    Cited by:

    1. Becheri, I.G. & Drost, Feike C. & van den Akker, R., 2013. "Asymptotically UMP Panel Unit Root Tests," Discussion Paper 2013-017, Tilburg University, Center for Economic Research.
    2. Becheri, I.G. & Drost, Feike C. & van den Akker, R., 2013. "Asymptotically UMP Panel Unit Root Tests," Other publications TiSEM e34b7d23-8e53-4cea-ba69-5, Tilburg University, School of Economics and Management.
    3. Pedroni, Peter L. & Vogelsang, Timothy J. & Wagner, Martin & Westerlund, Joakim, 2015. "Nonparametric rank tests for non-stationary panels," Journal of Econometrics, Elsevier, vol. 185(2), pages 378-391.
    4. Kajal Lahiri & Zhongwen Liang & Huaming Peng, 2017. "The Local Power of the IPS Test with Both Initial Conditions and Incidental Trends," CESifo Working Paper Series 6313, CESifo.
    5. Yiannis Karavias & Elias Tzavalis, 2013. "The power performance of fixed-T panel unit root tests allowing for structural breaks," Discussion Papers 13/01, University of Nottingham, Granger Centre for Time Series Econometrics.
    6. Valerija Botric, 2013. "Output Convergence between Western Balkans and EU-15," Research in Economics and Business: Central and Eastern Europe, Tallinn School of Economics and Business Administration, Tallinn University of Technology, vol. 5(1).
    7. M. Hashem Pesaran & L. Vanessa Smith & Takashi Yamagata, 2008. "Panel Unit Root Tests in the Presence of a Multifactor Error Structure," CESifo Working Paper Series 2193, CESifo.
    8. Chingnun Lee & Jyh-Lin Wu & Lixiong Yang, 2016. "A Simple Panel Unit-Root Test with Smooth Breaks in the Presence of a Multifactor Error Structure," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(3), pages 365-393, June.
    9. Yiannis Karavias & Elias Tzavalis, 2012. "The local power of fixed-T panel unit root tests allowing for serially correlated errors," Discussion Papers 12/01, University of Nottingham, Granger Centre for Time Series Econometrics.
    10. Stauskas, Ovidijus, 2019. "On the Limit Theory of Mixed to Unity VARs: Panel Setting With Weakly Dependent Errors," Working Papers 2019:2, Lund University, Department of Economics.
    11. Yiannis Karavias & Elias Tzavalis, 2016. "Local Power of Fixed-T Panel Unit Root Tests With Serially Correlated Errors and Incidental Trends," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(2), pages 222-239, March.
    12. Joakim Westerlund & Jörg Breitung, 2013. "Lessons from a Decade of IPS and LLC," Econometric Reviews, Taylor & Francis Journals, vol. 32(5-6), pages 547-591, August.
    13. Westerlund, Joakim, 2015. "The power of PANIC," Journal of Econometrics, Elsevier, vol. 185(2), pages 495-509.
    14. Skrobotov, Anton (Скроботов, Антон) & Turuntseva, Marina (Турунцева, Марина), 2017. "Testing the Hypothesis of a Unit Root for Independent Panels [Тестирование Гипотезы О Наличии Единичного Корня Для Независимых Панелей]," Working Papers 021707, Russian Presidential Academy of National Economy and Public Administration.
    15. Westerlund, Joakim & Larsson, Rolf, 2012. "Testing for a unit root in a random coefficient panel data model," Journal of Econometrics, Elsevier, vol. 167(1), pages 254-273.

  21. David Harris & David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2007. "Testing for a unit root in the presence of a possible break in trend," Discussion Papers 07/04, University of Nottingham, Granger Centre for Time Series Econometrics.

    Cited by:

    1. Terence C. Mills, 2013. "Trends, cycles and structural breaks," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 3, pages 45-60, Edward Elgar Publishing.
    2. Anton Skrobotov, 2013. "Local Structural Trend Break in Stationarity Testing," Working Papers 0074, Gaidar Institute for Economic Policy, revised 2013.
    3. Balcombe, Kelvin & Fraser, Iain, 2017. "Do bubbles have an explosive signature in markov switching models?," Economic Modelling, Elsevier, vol. 66(C), pages 81-100.
    4. Basher, Syed Abul & Haug, Alfred A. & Sadorsky, Perry, 2011. "Oil prices, exchange rates and emerging stock markets," MPRA Paper 30140, University Library of Munich, Germany.
    5. Ghoshray Atanu & Kejriwal Mohitosh & Wohar Mark, 2014. "Breaks, trends and unit roots in commodity prices: a robust investigation," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(1), pages 23-40, February.
    6. Cavaliere, Giuseppe & Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2011. "Testing For Unit Roots In The Presence Of A Possible Break In Trend And Nonstationary Volatility," Econometric Theory, Cambridge University Press, vol. 27(5), pages 957-991, October.
    7. Francesca Iorio & Stefano Fachin, 2014. "Savings and investments in the OECD: a panel cointegration study with a new bootstrap test," Empirical Economics, Springer, vol. 46(4), pages 1271-1300, June.
    8. Vitaly Pershin & Juan Carlos Molero & Fernando Pérez de Gracia, 2015. "Exploring the oil prices and exchange rates nexus in some African economies," Faculty Working Papers 01/15, School of Economics and Business Administration, University of Navarra.
    9. David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2010. "Unit root testing under a local break in trend," Discussion Papers 10/05, University of Nottingham, Granger Centre for Time Series Econometrics.
    10. Skrobotov, Anton (Скроботов, Антон), 2015. "About Trend, the Shift and the Initial Value in Testing of the Hypothesis of a Unit Root [О Тренде, Сдвиге И Начальном Значении В Тестировании Гипотезы О Наличии Единичного Корня]," Published Papers mak6, Russian Presidential Academy of National Economy and Public Administration.
    11. Sebastian Fossati, 2013. "Unit root testing with stationary covariates and a structural break in the trend function," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(3), pages 368-384, May.
    12. Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2009. "Unit Root Testing In Practice: Dealing With Uncertainty Over The Trend And Initial Condition," Econometric Theory, Cambridge University Press, vol. 25(3), pages 587-636, June.
    13. Niels Haldrup & Robinson Kruse & Timo Teräsvirta & Rasmus T. Varneskov, 2013. "Unit roots, non-linearities and structural breaks," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 4, pages 61-94, Edward Elgar Publishing.
    14. Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2013. "Testing for unit roots in the possible presence of multiple trend breaks using minimum Dickey–Fuller statistics," Journal of Econometrics, Elsevier, vol. 177(2), pages 265-284.
    15. Russo, Emanuele & Foster-McGregor, Neil & Verspagen, Bart, 2019. "Characterizing growth instability: new evidence on unit roots and structural breaks in long run time series," MERIT Working Papers 2019-026, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    16. Josep Lluís Carrion-i-Silvestre & Dukpa Kim & Pierre Perron, 2007. "GLS-based unit root tests with multiple structural breaks both under the null and the alternative hypotheses," Boston University - Department of Economics - Working Papers Series wp2008-019, Boston University - Department of Economics.
    17. Apergis, Nicholas & Bowden, Nicholas & Payne, James E., 2015. "Downstream integration of natural gas prices across U.S. states: Evidence from deregulation regime shifts," Energy Economics, Elsevier, vol. 49(C), pages 82-92.
    18. Paulo M.M. Rodrigues & Nuno Sobreira, 2013. "Characterizing economic growth paths based on new structural change tests," Working Papers w201313, Banco de Portugal, Economics and Research Department.
    19. David I. Harvey & Stephen J. Leybourne & A.M. Robert Taylor, 2014. "Unit Root Testing under a Local Break in Trend using Partial Information on the Break Date," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(1), pages 93-111, February.
    20. Richard S. J. Tol & Francisco Estrada & Carlos Gay-García, 2012. "The persistence of shocks in GDP and the estimation of the potential economic costs of climate change," Working Paper Series 4312, Department of Economics, University of Sussex Business School.
    21. Mohitosh Kejriwal & Claude Lopez, 2013. "Unit Roots, Level Shifts, and Trend Breaks in Per Capita Output: A Robust Evaluation," Econometric Reviews, Taylor & Francis Journals, vol. 32(8), pages 892-927, November.
    22. Colin O’hare & Youwei Li, 2017. "Modelling mortality: are we heading in the right direction?," Applied Economics, Taylor & Francis Journals, vol. 49(2), pages 170-187, January.
    23. David I. Harvey & Stephen J. Leybourne, 2013. "Break date estimation for models with deterministic structural change," Discussion Papers 13/02, University of Nottingham, Granger Centre for Time Series Econometrics.
    24. Harris, David & Leybourne, Stephen J. & Taylor, A.M. Robert, 2016. "Tests of the co-integration rank in VAR models in the presence of a possible break in trend at an unknown point," Journal of Econometrics, Elsevier, vol. 192(2), pages 451-467.
    25. Skrobotov, Anton, 2020. "Survey on structural breaks and unit root tests," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 58, pages 96-141.
    26. David Harris & Hsein Kew & A. M. Robert Taylor, 2020. "Level Shift Estimation in the Presence of Non-stationary Volatility with an Application to the Unit Root Testing Problem," Monash Econometrics and Business Statistics Working Papers 8/20, Monash University, Department of Econometrics and Business Statistics.
    27. Husein, Jamal, 2020. "Current account sustainability for 21 African economies: Evidence based on nonlinear flexible Fourier stationarity and unit-root tests," MPRA Paper 100410, University Library of Munich, Germany.
    28. Ghoshray, Atanu & Kejriwal, Mohitosh & Wohar, Mark E., 2011. "Breaking Trends and the Prebisch-Singer Hypothesis: A Further Investigation," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 120387, European Association of Agricultural Economists.
    29. Börger, Matthias & Schupp, Johannes, 2018. "Modeling trend processes in parametric mortality models," Insurance: Mathematics and Economics, Elsevier, vol. 78(C), pages 369-380.
    30. David I. Harvey, & Stephen J. Leybourne, & A. M. Robert Taylor, 2007. "Testing for a unit root when uncertain about the trend [Revised to become 07/03 above]," Discussion Papers 06/03, University of Nottingham, Granger Centre for Time Series Econometrics.
    31. Pitarakis, Jean-Yves, 2014. "A joint test for structural stability and a unit root in autoregressions," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 577-587.
    32. Sun, Jingwei & Shi, Wendong, 2015. "Breaks, trends, and unit roots in spot prices for crude oil and petroleum products," Energy Economics, Elsevier, vol. 50(C), pages 169-177.
    33. Sobreira, Nuno & Nunesz, Luis C. & Rodriguesz, Paulo M. M., 2012. "Neoclassical, semi-endogenous or endogenous growth theory? Evidence based on new structural change tests," Insper Working Papers wpe_291, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    34. Emanuele Russo & Neil Foster-McGregor, 2022. "Characterizing growth instability: new evidence on unit roots and structural breaks in countries’ long run trajectories," Journal of Evolutionary Economics, Springer, vol. 32(2), pages 713-756, April.
    35. Pitarakis, Jean-Yves, 2011. "Joint Detection of Structural Change and Nonstationarity in Autoregressions," MPRA Paper 29189, University Library of Munich, Germany.
    36. Terence Mills, 2013. "Breaks and unit roots in global and hemispheric temperatures: an updated analysis," Climatic Change, Springer, vol. 118(3), pages 745-755, June.
    37. Atanu Ghoshray & Ashira Perera, 2016. "An Empirical Study of Commodity Prices after Sir Arthur Lewis," Manchester School, University of Manchester, vol. 84(4), pages 551-571, July.
    38. O'Hare, Colin & Li, Youwei, 2014. "Identifying structural breaks in stochastic mortality models," MPRA Paper 62994, University Library of Munich, Germany.
    39. Neil Kellard & Denise Osborn & Jerry Coakley & Giuseppe Cavaliere & David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2015. "Testing for Unit Roots Under Multiple Possible Trend Breaks and Non-Stationary Volatility Using Bootstrap Minimum Dickey–Fuller Statistics," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(5), pages 603-629, September.
    40. Wang, Shaoping & Li, Yanglin & Wen, Kuangyu, 2021. "Recursive adjusted unit root tests under non-stationary volatility," Economics Letters, Elsevier, vol. 205(C).

  22. David I. Harvey & Stephen J. Leybourne & Bin Xiao, 2007. "A powerful test for linearity when the order of integration is unknown," Discussion Papers 07/01, University of Nottingham, Granger Centre for Time Series Econometrics.

    Cited by:

    1. Solarin, Sakiru Adebola & Shahbaz, Muhammad & Hammoudeh, Shawkat, 2019. "Sustainable economic development in China: Modelling the role of hydroelectricity consumption in a multivariate framework," Energy, Elsevier, vol. 168(C), pages 516-531.
    2. Burak GÜRIŞ & İpek M. YURTTAGÜLER & Muhammed TIRAŞOĞLU, 2017. "Unemployment convergence analysis for Nordic countries: Evidence from linear and nonlinear unit root tests," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(1(610), S), pages 45-56, Spring.
    3. Juan Carlos Cuestas & Paulo José Regis, 2010. "Purchasing power parity in OECD countries: nonlinear unit root tests revisited," NBS Discussion Papers in Economics 2010/3, Economics, Nottingham Business School, Nottingham Trent University.
    4. Wahab, Bashir A. & Adewuyi, Adeolu O., 2021. "Analysis of major properties of metal prices using new methods: Structural breaks, non-linearity, stationarity and bubbles," Resources Policy, Elsevier, vol. 74(C).
    5. Yavuz, Nilgün Çil & Yilanci, Veli, 2012. "Testing For Nonlinearity In G7 Macroeconomic Time Series," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 69-79, September.
    6. Solarin, Sakiru Adebola & Lean, Hooi Hooi, 2016. "Are fluctuations in oil consumption permanent or transitory? Evidence from linear and nonlinear unit root tests," Energy Policy, Elsevier, vol. 88(C), pages 262-270.
    7. Burak Güriş & Burcu Yavuz Tiftikçigil & Muhammed Tıraşoğlu, 2017. "Testing for unemployment hysteresis in Turkey: evidence from nonlinear unit root tests," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(1), pages 35-46, January.
    8. Juan Carlos Cuestas & Dean Garratt, 2008. "Is real GDP per capita a stationary process? Smooth transitions, nonlinear trends and unit root testing," NBS Discussion Papers in Economics 2008/12, Economics, Nottingham Business School, Nottingham Trent University.
    9. Tiwari, Aviral Kumar & Albulescu, Claudiu Tiberiu, 2016. "Renewable-to-total electricity consumption ratio: Estimating the permanent or transitory fluctuations based on flexible Fourier stationarity and unit root tests," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1409-1427.
    10. Feyyaz Zeren & Filiz Konuk, 2013. "Testing The Random Walk Hypothesis For Emerging Markets: Evidence From Linear And Non-Linear Unit Root Tests," Romanian Economic Business Review, Romanian-American University, vol. 8(4), pages 61-71, december.
    11. neifar, malika, 2020. "Efficiency-Market Hypothesis: case of Tunisian and 6 ‎Asian stock markets ‎," MPRA Paper 103232, University Library of Munich, Germany.
    12. Mücahit Aydın, 2019. "Investigation of the Validity of Purchasing Power Parity Hypothesis with Fourier Unit Root Tests: The Case of Turkey," EKOIST Journal of Econometrics and Statistics, Istanbul University, Faculty of Economics, vol. 30(0), pages 35-48, June.
    13. Malika Neifar & Leila Gharbi, 2022. "Weak EMH and Canadian stock markets: evidence from linear and nonlinear unit root tests," Journal of Islamic Accounting and Business Research, Emerald Group Publishing Limited, vol. 14(4), pages 629-651, December.
    14. Erdas Mehmet Levent, 2019. "Validity of Weak-Form Market Efficiency in Central and Eastern European Countries (CEECs): Evidence from Linear and Nonlinear Unit Root Tests," Review of Economic Perspectives, Sciendo, vol. 19(4), pages 399-428, December.
    15. Yifei Cai & Cosimo Magazzino, 2019. "Are shocks to natural gas consumption transitory or permanent? A more powerful panel unit root test on the G7 countries," Natural Resources Forum, Blackwell Publishing, vol. 43(2), pages 111-120, May.
    16. Juan Carlos Cuestas & Luis A. Gil-Alana & Karl Taylor, 2012. "Inflation Convergence in Central and Eastern Europe with a View to Adopting the Euro," Working Papers 2012005, The University of Sheffield, Department of Economics.
    17. Zhang, Yue-Jun & Zhang, Han, 2023. "Volatility forecasting of crude oil futures market: Which structural change-based HAR models have better performance?," International Review of Financial Analysis, Elsevier, vol. 85(C).
    18. Mehmet Altuntaş & Emre Kılıç & Şevket Pazarcı & Alican Umut, 2022. "Borsa İstanbul Alt Endekslerinde Etkin Piyasa Hipotezinin Test Edilmesi: Fourier Kırılmalı ve Doğrusal Olmayan Birim Kök Testlerinden Kanıtlar," Journal of Research in Economics, Politics & Finance, Ersan ERSOY, vol. 7(1), pages 169-185.
    19. Paulo M.M. Rodrigues & A. M. Robert Taylor, 2009. "The Flexible Fourier Form and Local GLS De-trended Unit Root Tests," Working Papers w200919, Banco de Portugal, Economics and Research Department.
    20. Ayca Doganer, 2022. "Determining Unemployment Hysteresis in European Countries Using Linear and Nonlinear Unit Root Tests: The 1991-2020 Period," Istanbul Journal of Economics-Istanbul Iktisat Dergisi, Istanbul University, Faculty of Economics, vol. 72(72-2), pages 753-785, December.
    21. Yoon, Gawon, 2009. "It's all the miners' fault: On the nonlinearity in U.S. unemployment rates," Economic Modelling, Elsevier, vol. 26(6), pages 1449-1454, November.
    22. Chen, Shyh-Wei & Hsu, Chi-Sheng, 2016. "Threshold, smooth transition and mean reversion in inflation: New evidence from European countries," Economic Modelling, Elsevier, vol. 53(C), pages 23-36.
    23. Mehmet Hanefi Topal, 2020. "The Middle Income Trap: Theory and Empirical Evidence," Bogazici Journal, Review of Social, Economic and Administrative Studies, Bogazici University, Department of Economics, vol. 34(1), pages 51-75.
    24. Selahattin GÜRİŞ & Burak GÜRİŞ & Muhammed TIRAŞOĞLU, 2017. "Do military expenditures converge in NATO countries? Linear and nonlinear unit root test evidence," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(2(611), S), pages 237-248, Summer.
    25. Kassouri, Yacouba & Altıntaş, Halil, 2022. "The quantile dependence of the stock returns of “clean” and “dirty” firms on oil demand and supply shocks," Journal of Commodity Markets, Elsevier, vol. 28(C).
    26. Shahbaz, Muhammad & Khraief, Naceur & Mahalik, Mantu Kumar & Zaman, Khair Uz, 2014. "Are fluctuations in natural gas consumption per capita transitory? Evidence from time series and panel unit root tests," Energy, Elsevier, vol. 78(C), pages 183-195.
    27. Adewuyi, Adeolu O. & Wahab, Bashir A. & Adeboye, Olusegun S., 2020. "Stationarity of prices of precious and industrial metals using recent unit root methods: Implications for markets’ efficiency," Resources Policy, Elsevier, vol. 65(C).
    28. Chen, Shyh-Wei, 2014. "Smooth transition, non-linearity and current account sustainability: Evidence from the European countries," Economic Modelling, Elsevier, vol. 38(C), pages 541-554.
    29. Artur Silva Lopes & Gabriel Florin Zsurkis, 2019. "Are linear models really unuseful to describe business cycle data?," Applied Economics, Taylor & Francis Journals, vol. 51(22), pages 2355-2376, May.
    30. Aslan, Alper & Kum, Hakan, 2011. "The stationary of energy consumption for Turkish disaggregate data by employing linear and nonlinear unit root tests," Energy, Elsevier, vol. 36(7), pages 4256-4258.
    31. Lee, Chien-Chiang & Ranjbar, Omid & Lee, Chi-Chuan, 2021. "Testing the persistence of shocks on renewable energy consumption: Evidence from a quantile unit-root test with smooth breaks," Energy, Elsevier, vol. 215(PB).
    32. Yi‐Ting Peng & Tsangyao Chang & Omid Ranjbar, 2022. "Analyzing the degree of persistence of economic policy uncertainty using linear and non‐linear fourier quantile unit root tests," Manchester School, University of Manchester, vol. 90(4), pages 453-471, July.
    33. Esra ALP & Ünal SEVEN, 2019. "Türkiye Konut Piyasasında Etkinlik Analizi," Istanbul Business Research, Istanbul University Business School, vol. 48(1), pages 84-112, May.
    34. Neifar, Malika, 2020. "Multivariate GARCH Approaches: case of major sectorial Tunisian stock markets," MPRA Paper 99658, University Library of Munich, Germany.
    35. Murat Eren & Selim Basar & Bengu Tosun, 2022. "Dollarization and Risk Premium in a Risky Country: An Investigation on Turkiye," Istanbul Journal of Economics-Istanbul Iktisat Dergisi, Istanbul University, Faculty of Economics, vol. 72(72-2), pages 625-651, December.
    36. Yusuf TUNA & Ayca DOGANER & Guldenur CETIN, 2022. "Determining the Relationships Between Domestic Credits, Economic Growth and Inflation in Turkiye by Nonlinear Cointegration Analysis," Journal of BRSA Banking and Financial Markets, Banking Regulation and Supervision Agency, vol. 16(2), pages 173-187.
    37. neifar, malika, 2020. "Efficient Markets Hypothesis in Canada:‎ a comparative study between Islamic and Conventional stock markets ‎," MPRA Paper 103175, University Library of Munich, Germany.
    38. Khraief, Naceur & Shahbaz, Muhammad & Heshmati, Almas & Azam, Muhammad, 2020. "Are unemployment rates in OECD countries stationary? Evidence from univariate and panel unit root tests," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    39. Ghoshray, A., 2018. "The Dynamic Properties of Natural Resource Prices," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277210, International Association of Agricultural Economists.
    40. Aslan, Alper, 2011. "Does natural gas consumption follow a nonlinear path over time? Evidence from 50 US States," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(9), pages 4466-4469.
    41. Golpe, Antonio A. & Carmona, Monica & Congregado, Emilio, 2012. "Persistence in natural gas consumption in the US: An unobserved component model," Energy Policy, Elsevier, vol. 46(C), pages 594-600.
    42. Yunus Kilic & Mehmet Fatih Bugan, 2016. "The Efficient Market Hypothesis: Evidence from Turkey," International Journal of Academic Research in Business and Social Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Business and Social Sciences, vol. 6(10), pages 262-272, October.
    43. SAHIN, Emrah & GUNGOR, Selim & KARACA, Suleyman Serdar, 2020. "Empirical Analysis Of The Relationship Between Purchasing Managers Index And Bist Industrial Index Under Structural Breaks," Studii Financiare (Financial Studies), Centre of Financial and Monetary Research "Victor Slavescu", vol. 24(3), pages 6-22, September.
    44. Gozbasi, Onur & Kucukkaplan, Ilhan & Nazlioglu, Saban, 2014. "Re-examining the Turkish stock market efficiency: Evidence from nonlinear unit root tests," Economic Modelling, Elsevier, vol. 38(C), pages 381-384.
    45. Silva Lopes, Artur C. & Florin Zsurkis, Gabriel, 2015. "Revisiting non-linearities in business cycles around the world," MPRA Paper 65668, University Library of Munich, Germany.
    46. De Vita, Glauco & Trachanas, Emmanouil & Luo, Yun, 2018. "Revisiting the bi-directional causality between debt and growth: Evidence from linear and nonlinear tests," Journal of International Money and Finance, Elsevier, vol. 83(C), pages 55-74.
    47. Gawon Yoon, 2010. "Nonlinearity in real exchange rates: an approach with disaggregated data and a new linearity test," Applied Economics Letters, Taylor & Francis Journals, vol. 17(11), pages 1125-1132.
    48. Claudiu Tiberiu Albulescu & Aviral Kumar Tiwari & Phouphet Kyophilavong, 2021. "Nonlinearities and Chaos: A New Analysis of CEE Stock Markets," Mathematics, MDPI, vol. 9(7), pages 1-13, March.
    49. De Vita, Glauco & Trachanas, Emmanouil, 2016. "‘Nonlinear causality between crude oil price and exchange rate: A comparative study of China and India’ — A failed replication (negative Type 1 and Type 2)," Energy Economics, Elsevier, vol. 56(C), pages 150-160.
    50. Juan Carlos Cuestas & Luis A. Gil-Alana & Karl Taylor, 2016. "Inflation convergence in Central and Eastern Europe vs. the Eurozone: Non-linearities and long memory," Scottish Journal of Political Economy, Scottish Economic Society, vol. 63(5), pages 519-538, November.
    51. Shahbaz, Muhammad & Khraief, Naceur & Hammoudeh, Shawkat, 2019. "How Do Carbon Emissions Respond to Economic Shocks? Evidence from Low-, Middle- and High-Income Countries," MPRA Paper 93976, University Library of Munich, Germany, revised 15 May 2019.
    52. Saša Obradoviæ & Lela Ristiæ & Nemanja Lojanica, 2018. "Are unemployment rates stationary for SEE10 countries? Evidence from linear and nonlinear dynamics," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 36(2), pages 559-583.
    53. Kassouri, Yacouba, 2022. "Boom-bust cycles in oil consumption: The role of explosive bubbles and asymmetric adjustments," Energy Economics, Elsevier, vol. 111(C).
    54. Moosa, Imad A. & Ma, Ming, 2018. "Linear and Nonlinear Attractors in Purchasing Power Parity," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, vol. 71(2), pages 149-172.
    55. Liu, Donghui & Meng, Lingjie & Wang, Yudong, 2021. "The asymmetric effects of oil price changes on China’s exports: New evidence from a nonlinear autoregressive distributed lag model," Journal of Asian Economics, Elsevier, vol. 77(C).
    56. Durmuş Çağrı Yıldırım & Seda Yıldırım & Seyfettin Erdoğan & Işıl Demirtaş & Gualter Couto & Rui Alexandre Castanho, 2021. "Time-Varying Convergences of Environmental Footprint Levels between European Countries," Energies, MDPI, vol. 14(7), pages 1-15, March.
    57. Burhan Biçer & Almila Burgac Cil, 2023. "Symmetric and Asymmetric Dynamics of Output Gap and Inflation Relation for Turkish Economy," Prague Economic Papers, Prague University of Economics and Business, vol. 2023(5), pages 520-549.
    58. Lopes, Artur Silva & Zsurkis, Gabriel Florin, 2017. "Are linear models really unuseful to describe business cycle data?," Economics Discussion Papers 2017-5, Kiel Institute for the World Economy (IfW Kiel).
    59. Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "International Financial Markets," Post-Print halshs-02183053, HAL.

  23. David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2007. "Unit root testing in practice: dealing with uncertainty over the trend and initial condition," Discussion Papers 07/03, University of Nottingham, Granger Centre for Time Series Econometrics.

    Cited by:

    1. Michael Jansson & Morten Ø. Nielsen, 2009. "Nearly Efficient Likelihood Ratio Tests For Seasonal Unit Roots," Working Paper 1224, Economics Department, Queen's University.
    2. David I. Harvey & Stephen J. Leybourne & Emily J. Whitehouse, 2017. "Testing for a unit root against ESTAR stationarity," Discussion Papers 17/02, University of Nottingham, Granger Centre for Time Series Econometrics.
    3. David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2009. "The impact of the initial condition on robust tests for a linear trend," Discussion Papers 09/03, University of Nottingham, Granger Centre for Time Series Econometrics.
    4. Matei Demetrescu & Helmut Lütkepohl & Pentti Saikkonen, 2009. "Testing for the cointegrating rank of a vector autoregressive process with uncertain deterministic trend term," Econometrics Journal, Royal Economic Society, vol. 12(3), pages 414-435, November.
    5. Anton Skrobotov, 2016. "On Trend Breaks and Initial Condition in Unit Root Testing," Working Papers 0097, Gaidar Institute for Economic Policy, revised 2016.
    6. Patrick Marsh, 2019. "Properties of the power envelope for tests against both stationary and explosive alternatives: the effect of trends," Discussion Papers 19/03, University of Nottingham, Granger Centre for Time Series Econometrics.
    7. Michael Jansson & Morten Ørregaard Nielsen, 2012. "Nearly Efficient Likelihood Ratio Tests of the Unit Root Hypothesis," Econometrica, Econometric Society, vol. 80(5), pages 2321-2332, September.
    8. David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2011. "Testing for Unit Roots and the Impact of Quadratic Trends, with an Application to Relative Primary Commodity Prices," Econometric Reviews, Taylor & Francis Journals, vol. 30(5), pages 514-547, October.
    9. Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2012. "Testing for unit roots in the presence of uncertainty over both the trend and initial condition," Journal of Econometrics, Elsevier, vol. 169(2), pages 188-195.
    10. David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2010. "Unit root testing under a local break in trend," Discussion Papers 10/05, University of Nottingham, Granger Centre for Time Series Econometrics.
    11. Adel Bosch & Franz Ruch, 2012. "An Alternative Business Cycle Dating Procedure for South Africa," Working Papers 5210, South African Reserve Bank.
    12. Skrobotov, Anton (Скроботов, Антон), 2015. "About Trend, the Shift and the Initial Value in Testing of the Hypothesis of a Unit Root [О Тренде, Сдвиге И Начальном Значении В Тестировании Гипотезы О Наличии Единичного Корня]," Published Papers mak6, Russian Presidential Academy of National Economy and Public Administration.
    13. Stephan Smeekes, 2013. "Detrending Bootstrap Unit Root Tests," Econometric Reviews, Taylor & Francis Journals, vol. 32(8), pages 869-891, November.
    14. Kajal Lahiri & Zhongwen Liang & Huaming Peng, 2017. "The Local Power of the IPS Test with Both Initial Conditions and Incidental Trends," CESifo Working Paper Series 6313, CESifo.
    15. Born Benjamin & Demetrescu Matei, 2015. "Recursive Adjustment for General Deterministic Components and Improved Cointegration Rank Tests," Journal of Time Series Econometrics, De Gruyter, vol. 7(2), pages 143-179, July.
    16. Silva Lopes, Artur, 2021. "Non-convergent incomes with a new DF-Fourier test: most likely you go your way (and I'll go mine)," MPRA Paper 120171, University Library of Munich, Germany, revised 09 Oct 2023.
    17. Qiankun Zhou & Jun Yu, 2010. "Asymptotic Distributions of the Least Squares Estimator for Diffusion Processes," Working Papers 20-2010, Singapore Management University, School of Economics.
    18. Anna Bykhovskaya & Peter C. B. Phillips, 2017. "Point Optimal Testing with Roots That Are Functionally Local to Unity," Cowles Foundation Discussion Papers 2107, Cowles Foundation for Research in Economics, Yale University.
    19. Natalia Bailey & Liudas Giraitis, 2015. "Spectral Approach to Parameter-Free Unit Root Testing," Working Papers 746, Queen Mary University of London, School of Economics and Finance.
    20. David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2011. "Robust methods for detecting multiple level breaks in autocorrelated time series," Discussion Papers 11/01, University of Nottingham, Granger Centre for Time Series Econometrics.
    21. Niels Haldrup & Robinson Kruse & Timo Teräsvirta & Rasmus T. Varneskov, 2013. "Unit roots, non-linearities and structural breaks," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 4, pages 61-94, Edward Elgar Publishing.
    22. Silva Lopes, Artur, 2016. "A simple proposal to improve the power of income convergence tests," Economics Letters, Elsevier, vol. 138(C), pages 92-95.
    23. David I. Harvey & Stephen J. Leybourne & Yang Zu, 2019. "Testing explosive bubbles with time-varying volatility," Econometric Reviews, Taylor & Francis Journals, vol. 38(10), pages 1131-1151, November.
    24. Phillips, Peter C.B. & Magdalinos, Tassos, 2009. "Unit Root And Cointegrating Limit Theory When Initialization Is In The Infinite Past," Econometric Theory, Cambridge University Press, vol. 25(6), pages 1682-1715, December.
    25. Smeekes, Stephan & Taylor, A.M. Robert, 2012. "Bootstrap Union Tests For Unit Roots In The Presence Of Nonstationary Volatility," Econometric Theory, Cambridge University Press, vol. 28(2), pages 422-456, April.
    26. Shelef, Amit, 2016. "A Gini-based unit root test," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 763-772.
    27. Maican, Florin G. & Sweeney, Richard J., 2013. "Rejection Probabilities for a Battery of Unit-Root Tests," Working Papers in Economics 568, University of Gothenburg, Department of Economics.
    28. Razvan Pascalau & Junsoo Lee & Saban Nazlioglu & Yan (Olivia) Lu, 2022. "Johansen‐type cointegration tests with a Fourier function," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(5), pages 828-852, September.
    29. Franz Ruch & Stan du Plessis, 2015. "SecondRound Effects from Food and Energy Prices an SBVAR approach," Working Papers 7008, South African Reserve Bank.
    30. Chevillon, Guillaume, 2013. "Robust Cointegration Testing in the Presence of Weak Trends, with an Application to the Human Origin of Global Warming," ESSEC Working Papers WP1320, ESSEC Research Center, ESSEC Business School.
    31. David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2009. "Robust methods for detecting multiple level breaks in autocorrelated time series [Revised to become No. 10/01 above]," Discussion Papers 09/01, University of Nottingham, Granger Centre for Time Series Econometrics.
    32. Karsten Reichold, 2022. "A Residuals-Based Nonparametric Variance Ratio Test for Cointegration," Papers 2211.06288, arXiv.org, revised Dec 2022.
    33. Hugo Ferrer-Pérez & María-Isabel Ayuda & Antonio Aznar, 2019. "Improving the Performance of a Long-Run Variance Ratio Test for a Unit Root," The Japanese Economic Review, Springer, vol. 70(2), pages 258-274, June.
    34. Sandberg, Rickard, 2016. "Trends, unit roots, structural changes, and time-varying asymmetries in U.S. macroeconomic data: the Stock and Watson data re-examined," Economic Modelling, Elsevier, vol. 52(PB), pages 699-713.
    35. Meng, Ming & Lee, Hyejin & Cho, Myeong Hyeon & Lee, Junsoo, 2013. "Impacts of the initial observation on unit root tests using recursive demeaning and detrending procedures," Economics Letters, Elsevier, vol. 120(2), pages 195-199.
    36. Fathali Firoozi & Donald Lien, 2016. "A Modified ADF Test for Geometric ARMA Processes," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 15(2), pages 173-179, December.
    37. Addison, Tony & Ghoshray, Atanu, 2023. "Discerning trends in international metal prices in the presence of nonstationary volatility," Resource and Energy Economics, Elsevier, vol. 71(C).
    38. Cho, Cheol-Keun & Amsler, Christine & Schmidt, Peter, 2015. "A test of the null of integer integration against the alternative of fractional integration," Journal of Econometrics, Elsevier, vol. 187(1), pages 217-237.
    39. Samuel Brien & Michael Jansson & Morten Ørregaard Nielsen, 2022. "Nearly Efficient Likelihood Ratio Tests of a Unit Root in an Autoregressive Model of Arbitrary Order," Working Paper 1429, Economics Department, Queen's University.
    40. Pierre Perron & Gabriel Rodríguez, "undated". "Residuals-based Tests for Cointegration with GLS Detrended Data," Boston University - Department of Economics - Working Papers Series wp2015-017, Boston University - Department of Economics, revised 19 Oct 2015.
    41. Silva Lopes, Artur C., 2021. "Most likely you go your way (and I'll go mine): non-convergent incomes with a new DF-Fourier test," MPRA Paper 107676, University Library of Munich, Germany, revised 19 Mar 2021.
    42. Anton Skrobotov, 2015. "Trend and Initial Condition in Stationarity Tests: The Asymptotic Analysis," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(2), pages 254-273, April.
    43. Martin C. Arnold & Christoph Hanck, 2019. "On Combining Evidence from Heteroskedasticity Robust Panel Unit Root Tests in Pooled Regressions," JRFM, MDPI, vol. 12(3), pages 1-22, July.
    44. Ke-Li Xu & Jui-Chung Yang, 2015. "Towards Uniformly Efficient Trend Estimation Under Weak/Strong Correlation and Non-stationary Volatility," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(1), pages 63-86, March.
    45. Smeekes, S., 2011. "Bootstrap sequential tests to determine the stationary units in a panel," Research Memorandum 003, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    46. Chevillon, Guillaume, 2012. "Local-Explosive Approximations to Null Distributions of the Johansen Cointegration Test, with an Application to Cyclical Concordance in the Euro Area," ESSEC Working Papers WP1210, ESSEC Research Center, ESSEC Business School.
    47. Anton Skrobotov, 2013. "Double Unit Roots Testing, GLS-detrending and Uncertainty over the Initial Conditions," Working Papers 0083, Gaidar Institute for Economic Policy, revised 2013.
    48. Richard Crump & Gopi Shah Goda & Kevin Mumford, 2010. "Fertility and the Personal Exemption: Comment," NBER Working Papers 15984, National Bureau of Economic Research, Inc.
    49. Mehdi Hosseinkouchack & Uwe Hassler, 2016. "Powerful Unit Root Tests Free of Nuisance Parameters," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(4), pages 533-554, July.
    50. Lan Cheng & Xuguang Simon Sheng, 2017. "Combination of “combinations of p values”," Empirical Economics, Springer, vol. 53(1), pages 329-350, August.
    51. Jeremy Nguyen & Jen-je Su, 2015. "Combining linear and nonlinear unit root tests with an application to PPP," Economics Bulletin, AccessEcon, vol. 35(4), pages 2796-2801.
    52. Ahlgren, Niklas & Juselius, Mikael, 2009. "Tests for Cointegration Rank and the Initial Condition," Working Papers 539, Hanken School of Economics.
    53. Chrystalleni Aristidou & David Harvey & Stephen Leybourne, 2016. "The impact of the initial condition on covariate augmented unit root tests," Discussion Papers 16/01, University of Nottingham, Granger Centre for Time Series Econometrics.
    54. Paulo M. M. Rodrigues, 2013. "Recursive adjustment, unit root tests and structural breaks," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(1), pages 62-82, January.
    55. Heon Lee, 2021. "Money Creation and Banking: Theory and Evidence," Papers 2109.15096, arXiv.org.
    56. Nishi, Mikihito & 西, 幹仁 & Kurozumi, Eiji & 黒住, 英司, 2022. "Stochastic Local and Moderate Departures from a Unit Root and Its Application to Unit Root Testing," Discussion Papers 2022-02, Graduate School of Economics, Hitotsubashi University.
    57. Christian Bayer & Christoph Hanck, 2013. "Combining non-cointegration tests," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(1), pages 83-95, January.
    58. Su, Jen-Je & Nguyen, Jeremy K., 2013. "Alternative unit root testing strategies using the Fourier approximation," Economics Letters, Elsevier, vol. 121(1), pages 8-11.
    59. Harvey, David I. & Leybourne, Stephen J., 2014. "Asymptotic behaviour of tests for a unit root against an explosive alternative," Economics Letters, Elsevier, vol. 122(1), pages 64-68.
    60. Wang, Shaoping & Li, Yanglin & Wen, Kuangyu, 2021. "Recursive adjusted unit root tests under non-stationary volatility," Economics Letters, Elsevier, vol. 205(C).
    61. Arturas Juodis & Yiannis Karavias, 2019. "Partially heterogeneous tests for Granger non-causality in panel data," Bank of Lithuania Working Paper Series 59, Bank of Lithuania.
    62. Meligkotsidou, Loukia & Tzavalis, Elias & Vrontos, Ioannis, 2017. "On Bayesian analysis and unit root testing for autoregressive models in the presence of multiple structural breaks," Econometrics and Statistics, Elsevier, vol. 4(C), pages 70-90.
    63. Christoph Hanck, 2012. "Multiple unit root tests under uncertainty over the initial condition: some powerful modifications," Statistical Papers, Springer, vol. 53(3), pages 767-774, August.
    64. Silva Lopes, Artur, 2020. "Revisiting income convergence with DF-Fourier tests: old evidence with a new test," MPRA Paper 102208, University Library of Munich, Germany.
    65. Anna Bykhovskaya & Vadim Gorin, 2020. "Cointegration in large VARs," Papers 2006.14179, arXiv.org, revised Dec 2021.
    66. Amsler Christine & Schmidt Peter & Vogelsang Timothy J, 2009. "The KPSS Test Using Fixed-b Critical Values: Size and Power in Highly Autocorrelated Time Series," Journal of Time Series Econometrics, De Gruyter, vol. 1(1), pages 1-44, December.

  24. Clements, Michael P & Harvey, David I, 2006. "Forecast Encompassing Tests and Probability Forecasts," The Warwick Economics Research Paper Series (TWERPS) 774, University of Warwick, Department of Economics.

    Cited by:

    1. Clements, Michael P., 2008. "Explanations of the inconsistencies in survey respondents'forecasts," The Warwick Economics Research Paper Series (TWERPS) 870, University of Warwick, Department of Economics.
    2. Cepni, Oguzhan & Clements, Michael P., 2024. "How local is the local inflation factor? Evidence from emerging European countries," International Journal of Forecasting, Elsevier, vol. 40(1), pages 160-183.
    3. David G. McMillan & Mark E. Wohar, 2010. "Stock return predictability and dividend-price ratio: a nonlinear approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 15(4), pages 351-365.
    4. Tsyplakov, Alexander, 2014. "Theoretical guidelines for a partially informed forecast examiner," MPRA Paper 55017, University Library of Munich, Germany.
    5. Turgut Kisinbay & Chikako Baba, 2011. "Predicting Recessions: A New Approach for Identifying Leading Indicators and Forecast Combinations," IMF Working Papers 2011/235, International Monetary Fund.
    6. Guizzardi, Andrea & Stacchini, Annalisa, 2015. "Real-time forecasting regional tourism with business sentiment surveys," Tourism Management, Elsevier, vol. 47(C), pages 213-223.
    7. Rodrigues, Bruno Dore & Stevenson, Maxwell J., 2013. "Takeover prediction using forecast combinations," International Journal of Forecasting, Elsevier, vol. 29(4), pages 628-641.
    8. Kajal Lahiri & Huaming Peng & Yongchen Zhao, 2013. "Testing the Value of Probability Forecasts for Calibrated Combining," Discussion Papers 13-02, University at Albany, SUNY, Department of Economics.
    9. Xiao, Liye & Wang, Jianzhou & Hou, Ru & Wu, Jie, 2015. "A combined model based on data pre-analysis and weight coefficients optimization for electrical load forecasting," Energy, Elsevier, vol. 82(C), pages 524-549.
    10. Lahiri, Kajal & Wang, J. George, 2013. "Evaluating probability forecasts for GDP declines using alternative methodologies," International Journal of Forecasting, Elsevier, vol. 29(1), pages 175-190.
    11. Michael P. Clements, 2014. "Long-Run Restrictions and Survey Forecasts of Output, Consumption and Investment," ICMA Centre Discussion Papers in Finance icma-dp2014-02, Henley Business School, University of Reading.
    12. Timmermann, Allan, 2006. "Forecast Combinations," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 4, pages 135-196, Elsevier.
    13. Stahl, Dale O., 2018. "Assessing the forecast performance of models of choice," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 73(C), pages 86-92.
    14. Timo Dimitriadis & Xiaochun Liu & Julie Schnaitmann, 2020. "Encompassing Tests for Value at Risk and Expected Shortfall Multi-Step Forecasts based on Inference on the Boundary," Papers 2009.07341, arXiv.org.
    15. Oliver Hülsewig & Johannes Mayr & Stéphane Sorbe, 2007. "Assessing the Forecast Properties of the CESifo World Economic Climate Indicator: Evidence for the Euro Area," ifo Working Paper Series 46, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    16. Michael P. Clements, 2011. "An Empirical Investigation of the Effects of Rounding on the SPF Probabilities of Decline and Output Growth Histograms," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 43(1), pages 207-220, February.
    17. Michał Rubaszek & Paweł Skrzypczyński & Grzegorz Koloch, 2010. "Forecasting the Polish Zloty with Non-Linear Models," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 2(2), pages 151-167, March.
    18. Dimitriadis, Timo & Schnaitmann, Julie, 2021. "Forecast encompassing tests for the expected shortfall," International Journal of Forecasting, Elsevier, vol. 37(2), pages 604-621.
    19. Michael P. Clements, 2020. "Are Some Forecasters’ Probability Assessments of Macro Variables Better Than Those of Others?," Econometrics, MDPI, vol. 8(2), pages 1-16, May.
    20. Rendon-Sanchez, Juan F. & de Menezes, Lilian M., 2019. "Structural combination of seasonal exponential smoothing forecasts applied to load forecasting," European Journal of Operational Research, Elsevier, vol. 275(3), pages 916-924.
    21. Clements, Michael P., 2008. "Consensus and uncertainty: Using forecast probabilities of output declines," International Journal of Forecasting, Elsevier, vol. 24(1), pages 76-86.
    22. Timo Dimitriadis & Julie Schnaitmann, 2019. "Forecast Encompassing Tests for the Expected Shortfall," Papers 1908.04569, arXiv.org, revised Aug 2020.
    23. Lu Wang & Shan Li & Chao Liang, 2024. "Exploring the impact of oil security attention on oil volatility: A new perspective," International Finance, Wiley Blackwell, vol. 27(1), pages 61-80, April.

  25. David I. Harvey, & Stephen J. Leybourne, & A. M. Robert Taylor, 2006. "A simple, robust and powerful test of the trend hypothesis," Discussion Papers 06/01, University of Nottingham, Granger Centre for Time Series Econometrics.

    Cited by:

    1. Jesús Otero & Ana María Iregui, 2011. "The Long-Run Behaviour of the Terms of Trade between Primary Commodities and Manufactures: A Panel Data Approach," WIDER Working Paper Series wp-2011-071, World Institute for Development Economic Research (UNU-WIDER).
    2. Ivan Petzev & Andreas Schrimpf & Alexander F. Wagner, 2015. "Has the Pricing of Stocks Become More Global?," Swiss Finance Institute Research Paper Series 15-48, Swiss Finance Institute, revised Apr 2016.
    3. David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2009. "The impact of the initial condition on robust tests for a linear trend," Discussion Papers 09/03, University of Nottingham, Granger Centre for Time Series Econometrics.
    4. Ghoshray, Atanu, 2011. "A reexamination of trends in primary commodity prices," Journal of Development Economics, Elsevier, vol. 95(2), pages 242-251, July.
    5. Ghoshray Atanu & Kejriwal Mohitosh & Wohar Mark, 2014. "Breaks, trends and unit roots in commodity prices: a robust investigation," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(1), pages 23-40, February.
    6. Yannick LE PEN & Benoît SEVI, 2008. "On the non-convergence of energy intensities: evidence from a pair-wise econometric approach," Cahiers du CREDEN (CREDEN Working Papers) 08.12.79, CREDEN (Centre de Recherche en Economie et Droit de l'Energie), Faculty of Economics, University of Montpellier 1.
    7. Le Pen, Yannick, 2011. "A pair-wise approach to output convergence between European regions," Economic Modelling, Elsevier, vol. 28(3), pages 955-964, May.
    8. Xu, Ke-Li, 2016. "Multivariate trend function testing with mixed stationary and integrated disturbances," Journal of Multivariate Analysis, Elsevier, vol. 147(C), pages 38-57.
    9. David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2011. "Testing for Unit Roots and the Impact of Quadratic Trends, with an Application to Relative Primary Commodity Prices," Econometric Reviews, Taylor & Francis Journals, vol. 30(5), pages 514-547, October.
    10. Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2012. "Testing for unit roots in the presence of uncertainty over both the trend and initial condition," Journal of Econometrics, Elsevier, vol. 169(2), pages 188-195.
    11. Xu, Ke-Li, 2012. "Robustifying multivariate trend tests to nonstationary volatility," Journal of Econometrics, Elsevier, vol. 169(2), pages 147-154.
    12. Pierre Perron & Tomoyoshi Yabu, 2007. "Estimating Deterministic Trend with an Integrated or Stationary Noise Component," Boston University - Department of Economics - Working Papers Series WP2007-020, Boston University - Department of Economics.
    13. Jiawen Xu & Pierre Perron, 2013. "Robust testing of time trend and mean with unknown integration order errors Frequency (and Other) Contaminations," Boston University - Department of Economics - Working Papers Series 2013-006, Boston University - Department of Economics.
    14. Elliott, Graham, 2020. "Testing for a trend with persistent errors," University of California at San Diego, Economics Working Paper Series qt8qb0j5s7, Department of Economics, UC San Diego.
    15. Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2009. "Unit Root Testing In Practice: Dealing With Uncertainty Over The Trend And Initial Condition," Econometric Theory, Cambridge University Press, vol. 25(3), pages 587-636, June.
    16. Harvey, David I. & Leybourne, Stephen J., 2015. "Confidence sets for the date of a break in level and trend when the order of integration is unknown," Journal of Econometrics, Elsevier, vol. 184(2), pages 262-279.
    17. McCulloch, J. Huston, 2016. "Moment Ratio estimation of autoregressive/unit root parameters and autocorrelation-consistent standard errors," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 712-733.
    18. Alessandro Casini & Pierre Perron, 2018. "Structural Breaks in Time Series," Boston University - Department of Economics - Working Papers Series WP2019-02, Boston University - Department of Economics.
    19. Niels Haldrup & Robinson Kruse & Timo Teräsvirta & Rasmus T. Varneskov, 2013. "Unit roots, non-linearities and structural breaks," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 4, pages 61-94, Edward Elgar Publishing.
    20. Yeonwoo Rho & Xiaofeng Shao, 2015. "Inference for Time Series Regression Models With Weakly Dependent and Heteroscedastic Errors," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(3), pages 444-457, July.
    21. Arezki, Rabah & Hadri, Kaddour & Loungani, Prakash & Rao, Yao, 2014. "Testing the Prebisch–Singer hypothesis since 1650: Evidence from panel techniques that allow for multiple breaks," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 208-223.
    22. Mohsen Bahmani-Oskooee & Tsangyao Chang & Zahra (Mila) Elmi & Omid Ranjbar, 2018. "Re-testing Prebisch–Singer hypothesis: new evidence using Fourier quantile unit root test," Applied Economics, Taylor & Francis Journals, vol. 50(4), pages 441-454, January.
    23. Tristan Jourde, 2022. "The Rising Interconnectedness of the Insurance Sector," Working papers 857, Banque de France.
    24. Sungju Chun & Pierre Perron, 2013. "Comparisons of robust tests for shifts in trend with an application to trend deviations of real exchange rates in the long run," Applied Economics, Taylor & Francis Journals, vol. 45(24), pages 3512-3528, August.
    25. Harvey David I & Leybourne Stephen J & Xiao Bin, 2008. "A Powerful Test for Linearity When the Order of Integration is Unknown," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(3), pages 1-24, September.
    26. Mohitosh Kejriwal & Claude Lopez, 2013. "Unit Roots, Level Shifts, and Trend Breaks in Per Capita Output: A Robust Evaluation," Econometric Reviews, Taylor & Francis Journals, vol. 32(8), pages 892-927, November.
    27. Rabah Arezki & Kaddour Hadri & Prakash Loungani & Yao Rao, 2013. "Breaking the Dynamic of Relative Primary Commodity Prices in Levels and Volatilities since 1650," Economics Working Papers 13-02, Queen's Management School, Queen's University Belfast.
    28. Pötscher, Benedikt M. & Preinerstorfer, David, 2017. "Further Results on Size and Power of Heteroskedasticity and Autocorrelation Robust Tests, with an Application to Trend Testing," MPRA Paper 81053, University Library of Munich, Germany.
    29. Addison, Tony & Ghoshray, Atanu, 2023. "Discerning trends in international metal prices in the presence of nonstationary volatility," Resource and Energy Economics, Elsevier, vol. 71(C).
    30. Kaddour Hadri, 2010. "What Can We Learn From Primary Commodity Prices Series Which Is Useful To Policymakers In Resource-Rich Countries?," Economics Working Papers 10-07, Queen's Management School, Queen's University Belfast.
    31. Skrobotov, Anton, 2020. "Survey on structural breaks and unit root tests," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 58, pages 96-141.
    32. Astill, Sam & Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2014. "Robust tests for a linear trend with an application to equity indices," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 168-185.
    33. Anton Skrobotov, 2015. "Trend and Initial Condition in Stationarity Tests: The Asymptotic Analysis," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(2), pages 254-273, April.
    34. Ke-Li Xu & Jui-Chung Yang, 2015. "Towards Uniformly Efficient Trend Estimation Under Weak/Strong Correlation and Non-stationary Volatility," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(1), pages 63-86, March.
    35. Harvey, David I. & Kellard, Neil M. & Madsen, Jakob B. & Wohar, Mark E., 2017. "Long-Run Commodity Prices, Economic Growth, and Interest Rates: 17th Century to the Present Day," World Development, Elsevier, vol. 89(C), pages 57-70.
    36. Chevillon, Guillaume, 2012. "Local-Explosive Approximations to Null Distributions of the Johansen Cointegration Test, with an Application to Cyclical Concordance in the Euro Area," ESSEC Working Papers WP1210, ESSEC Research Center, ESSEC Business School.
    37. George Kapetanios & Zacharias Psaradakis, 2016. "Semiparametric Sieve-Type Generalized Least Squares Inference," Econometric Reviews, Taylor & Francis Journals, vol. 35(6), pages 951-985, June.
    38. Ghoshray, Atanu & Kejriwal, Mohitosh & Wohar, Mark E., 2011. "Breaking Trends and the Prebisch-Singer Hypothesis: A Further Investigation," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 120387, European Association of Agricultural Economists.
    39. David I. Harvey, & Stephen J. Leybourne, & A. M. Robert Taylor, 2007. "Testing for a unit root when uncertain about the trend [Revised to become 07/03 above]," Discussion Papers 06/03, University of Nottingham, Granger Centre for Time Series Econometrics.
    40. Liu, Guannan & Yao, Shuang, 2020. "A robust test for predictability with unknown persistence," Economics Letters, Elsevier, vol. 189(C).
    41. Skrobotov, Anton, 2022. "On robust testing for trend," Economics Letters, Elsevier, vol. 212(C).
    42. David Harvey & Neil Kellard & Jakob Madsen & Mark Wohar, 2012. "Trends and Cycles in Real Commodity Prices: 1650-2010," CEH Discussion Papers 010, Centre for Economic History, Research School of Economics, Australian National University.
    43. Rapach, David E. & Ringgenberg, Matthew C. & Zhou, Guofu, 2016. "Short interest and aggregate stock returns," Journal of Financial Economics, Elsevier, vol. 121(1), pages 46-65.
    44. Yang, Yang & Wang, Shaoping, 2017. "Two simple tests of the trend hypothesis under time-varying variance," Economics Letters, Elsevier, vol. 156(C), pages 123-128.
    45. Fernandez, Viviana, 2012. "Trends in real commodity prices: How real is real?," Resources Policy, Elsevier, vol. 37(1), pages 30-47.
    46. Tristan Jourde, 2022. "The rising interconnectedness of the insurance sector," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 89(2), pages 397-425, June.

  26. David I. Harvey & Stephen J. Leybourne & A.M. Robert Taylor, 2006. "Simple, Robust and Powerful Tests of the Breaking Trend Hypothesis," Discussion Papers 06/11, University of Nottingham, School of Economics.

    Cited by:

    1. Jesús Otero & Ana María Iregui, 2011. "The Long-Run Behaviour of the Terms of Trade between Primary Commodities and Manufactures: A Panel Data Approach," WIDER Working Paper Series wp-2011-071, World Institute for Development Economic Research (UNU-WIDER).
    2. Matteo Mogliani, 2010. "Residual-based tests for cointegration and multiple deterministic structural breaks: A Monte Carlo study," PSE Working Papers halshs-00564897, HAL.
    3. Anton Skrobotov, 2013. "Local Structural Trend Break in Stationarity Testing," Working Papers 0074, Gaidar Institute for Economic Policy, revised 2013.
    4. Marcos Sanso-Navarro, 2011. "Broken trend stationarity of hours worked," Post-Print hal-00712742, HAL.
    5. Anton Skrobotov, 2016. "On Trend Breaks and Initial Condition in Unit Root Testing," Working Papers 0097, Gaidar Institute for Economic Policy, revised 2016.
    6. Ghoshray Atanu & Kejriwal Mohitosh & Wohar Mark, 2014. "Breaks, trends and unit roots in commodity prices: a robust investigation," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(1), pages 23-40, February.
    7. Mohitosh Kejriwal & Pierre Perron, 2009. "A Sequential Procedure to Determine the Number of Breaks in Trend with an Integrated or Stationary Noise Component," Purdue University Economics Working Papers 1217, Purdue University, Department of Economics.
    8. Mohitosh Kejriwal & Xuewen Yu & Pierre Perron, 2020. "Bootstrap Procedures for Detecting Multiple Persistence Shifts in Heteroskedastic Time Series," Boston University - Department of Economics - Working Papers Series WP2020-009, Boston University - Department of Economics.
    9. Xu, Ke-Li, 2016. "Multivariate trend function testing with mixed stationary and integrated disturbances," Journal of Multivariate Analysis, Elsevier, vol. 147(C), pages 38-57.
    10. Fabien Candau & Michaël Goujon & Jean-François Hoarau & Serge Rey, 2013. "Real exchange rate and competitiveness of an EU’s ultra-peripheral region: La Reunion Island," Working papers of CATT hal-01847942, HAL.
    11. David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2010. "Unit root testing under a local break in trend," Discussion Papers 10/05, University of Nottingham, Granger Centre for Time Series Econometrics.
    12. Vogelsang, Timothy & Nawaz, Nasreen, 2015. "Estimation and Inference of Linear Trend Slope Ratios with an Application to Global Temperature Data," MPRA Paper 117435, University Library of Munich, Germany.
    13. Paraskevi Salamaliki, 2015. "Economic Policy Uncertainty and Economic Activity: A Focus on Infrequent Structural Shifts," Working Paper Series of the Department of Economics, University of Konstanz 2015-08, Department of Economics, University of Konstanz.
    14. Skrobotov, Anton (Скроботов, Антон), 2015. "About Trend, the Shift and the Initial Value in Testing of the Hypothesis of a Unit Root [О Тренде, Сдвиге И Начальном Значении В Тестировании Гипотезы О Наличии Единичного Корня]," Published Papers mak6, Russian Presidential Academy of National Economy and Public Administration.
    15. Eiji Kurozumi, 2012. "Testing for Multiple Structural Changes with Non-Homogeneous Regressors," Global COE Hi-Stat Discussion Paper Series gd11-227, Institute of Economic Research, Hitotsubashi University.
    16. Seong Yeon Chang & Pierre Perron, 2016. "Inference on a Structural Break in Trend with Fractionally Integrated Errors," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(4), pages 555-574, July.
    17. Mario Gómez Aguirre & José Carlos A. Rodríguez Chávez, 2012. "Análisis de la paridad del poder de compra: evidencia empírica entre México y Estados Unidos," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, vol. 27(1), pages 169-207.
    18. Harvey, David I. & Leybourne, Stephen J., 2015. "Confidence sets for the date of a break in level and trend when the order of integration is unknown," Journal of Econometrics, Elsevier, vol. 184(2), pages 262-279.
    19. David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2011. "Robust methods for detecting multiple level breaks in autocorrelated time series," Discussion Papers 11/01, University of Nottingham, Granger Centre for Time Series Econometrics.
    20. Anton Skrobotov, 2014. "A simple modification of the Busetti-Harvey stationarity tests with structural breaks at unknown time," Working Papers 0102, Gaidar Institute for Economic Policy, revised 2014.
    21. Alessandro Casini & Pierre Perron, 2018. "Structural Breaks in Time Series," Boston University - Department of Economics - Working Papers Series WP2019-02, Boston University - Department of Economics.
    22. Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2013. "Testing for unit roots in the possible presence of multiple trend breaks using minimum Dickey–Fuller statistics," Journal of Econometrics, Elsevier, vol. 177(2), pages 265-284.
    23. Noguera, José, 2013. "Oil prices: Breaks and trends," Energy Economics, Elsevier, vol. 37(C), pages 60-67.
    24. Arezki, Rabah & Hadri, Kaddour & Loungani, Prakash & Rao, Yao, 2014. "Testing the Prebisch–Singer hypothesis since 1650: Evidence from panel techniques that allow for multiple breaks," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 208-223.
    25. Paulo M.M. Rodrigues & Nuno Sobreira, 2013. "Characterizing economic growth paths based on new structural change tests," Working Papers w201313, Banco de Portugal, Economics and Research Department.
    26. David Harris & David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2007. "Testing for a unit root in the presence of a possible break in trend," Discussion Papers 07/04, University of Nottingham, Granger Centre for Time Series Econometrics.
    27. Mohitosh Kejriwal & Claude Lopez, 2013. "Unit Roots, Level Shifts, and Trend Breaks in Per Capita Output: A Robust Evaluation," Econometric Reviews, Taylor & Francis Journals, vol. 32(8), pages 892-927, November.
    28. David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2009. "Robust methods for detecting multiple level breaks in autocorrelated time series [Revised to become No. 10/01 above]," Discussion Papers 09/01, University of Nottingham, Granger Centre for Time Series Econometrics.
    29. Rabah Arezki & Kaddour Hadri & Prakash Loungani & Yao Rao, 2013. "Breaking the Dynamic of Relative Primary Commodity Prices in Levels and Volatilities since 1650," Economics Working Papers 13-02, Queen's Management School, Queen's University Belfast.
    30. Ioanna Konstantakopoulou, 2017. "The aggregate exports-GDP relation under the prism of infrequent trend breaks and multi-horizon causality," International Economics and Economic Policy, Springer, vol. 14(4), pages 661-689, October.
    31. F. Peters & J. P. Mackenbach & W. J. Nusselder, 2016. "Does the Impact of the Tobacco Epidemic Explain Structural Changes in the Decline of Mortality?," European Journal of Population, Springer;European Association for Population Studies, vol. 32(5), pages 687-702, December.
    32. David I. Harvey & Stephen J. Leybourne, 2013. "Break date estimation for models with deterministic structural change," Discussion Papers 13/02, University of Nottingham, Granger Centre for Time Series Econometrics.
    33. Kaddour Hadri, 2010. "What Can We Learn From Primary Commodity Prices Series Which Is Useful To Policymakers In Resource-Rich Countries?," Economics Working Papers 10-07, Queen's Management School, Queen's University Belfast.
    34. Skrobotov, Anton, 2020. "Survey on structural breaks and unit root tests," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 58, pages 96-141.
    35. Sobreira, Nuno & Nunes, Luis C., 2012. "Tests for Multiple Breaks in the Trend with Stationary or Integrated Shocks," Insper Working Papers wpe_290, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    36. David Harris & Hsein Kew & A. M. Robert Taylor, 2020. "Level Shift Estimation in the Presence of Non-stationary Volatility with an Application to the Unit Root Testing Problem," Monash Econometrics and Business Statistics Working Papers 8/20, Monash University, Department of Econometrics and Business Statistics.
    37. Harvey, David I. & Kellard, Neil M. & Madsen, Jakob B. & Wohar, Mark E., 2017. "Long-Run Commodity Prices, Economic Growth, and Interest Rates: 17th Century to the Present Day," World Development, Elsevier, vol. 89(C), pages 57-70.
    38. Christensen, Bent Jesper & Kruse, Robinson & Sibbertsen, Philipp, 2013. "A unified framework for testing in the linear regression model under unknown order of fractional integration," Hannover Economic Papers (HEP) dp-519, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    39. Iacone, Fabrizio & Leybourne, Stephen J. & Robert Taylor, A.M., 2013. "Testing for a break in trend when the order of integration is unknown," Journal of Econometrics, Elsevier, vol. 176(1), pages 30-45.
    40. Jingjing Yang, 2017. "Consistency of Trend Break Point Estimator with Underspecified Break Number," Econometrics, MDPI, vol. 5(1), pages 1-19, January.
    41. Ghoshray, Atanu & Kejriwal, Mohitosh & Wohar, Mark E., 2011. "Breaking Trends and the Prebisch-Singer Hypothesis: A Further Investigation," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 120387, European Association of Agricultural Economists.
    42. Börger, Matthias & Schupp, Johannes, 2018. "Modeling trend processes in parametric mortality models," Insurance: Mathematics and Economics, Elsevier, vol. 78(C), pages 369-380.
    43. Paulo M. M. Rodrigues, 2013. "Recursive adjustment, unit root tests and structural breaks," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(1), pages 62-82, January.
    44. Sobreira, Nuno & Nunesz, Luis C. & Rodriguesz, Paulo M. M., 2012. "Neoclassical, semi-endogenous or endogenous growth theory? Evidence based on new structural change tests," Insper Working Papers wpe_291, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    45. Emanuele Russo & Neil Foster-McGregor, 2022. "Characterizing growth instability: new evidence on unit roots and structural breaks in countries’ long run trajectories," Journal of Evolutionary Economics, Springer, vol. 32(2), pages 713-756, April.
    46. Wei, Wei & Zhang, Wan-Li & Wen, Jun & Wang, Jun-Sheng, 2020. "TFP growth in Chinese cities: The role of factor-intensity and industrial agglomeration," Economic Modelling, Elsevier, vol. 91(C), pages 534-549.
    47. David Harvey & Neil Kellard & Jakob Madsen & Mark Wohar, 2012. "Trends and Cycles in Real Commodity Prices: 1650-2010," CEH Discussion Papers 010, Centre for Economic History, Research School of Economics, Australian National University.
    48. Rapach, David E. & Ringgenberg, Matthew C. & Zhou, Guofu, 2016. "Short interest and aggregate stock returns," Journal of Financial Economics, Elsevier, vol. 121(1), pages 46-65.
    49. Atanu Ghoshray & Ashira Perera, 2016. "An Empirical Study of Commodity Prices after Sir Arthur Lewis," Manchester School, University of Manchester, vol. 84(4), pages 551-571, July.
    50. Yang, Yang & Wang, Shaoping, 2017. "Two simple tests of the trend hypothesis under time-varying variance," Economics Letters, Elsevier, vol. 156(C), pages 123-128.
    51. Atanu Ghoshray & Issam Malki & Javier Ordóñez, 2022. "On the long-run dynamics of income and wealth inequality," Empirical Economics, Springer, vol. 62(2), pages 375-408, February.
    52. Fernandez, Viviana, 2012. "Trends in real commodity prices: How real is real?," Resources Policy, Elsevier, vol. 37(1), pages 30-47.
    53. Tristan Jourde, 2022. "The rising interconnectedness of the insurance sector," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 89(2), pages 397-425, June.

  27. David Harvey & Stephen Leybourne & A M Robert Taylor, 2005. "On Robust Trend Function Hypothesis Testing," Discussion Papers 05-07, Department of Economics, University of Birmingham.

    Cited by:

    1. David I. Harvey & Stephen J. Leybourne & Lisa Xiao, 2009. "Testing for nonlinear trends when the order of integration is unknown," Discussion Papers 09/04, University of Nottingham, Granger Centre for Time Series Econometrics.

  28. Robert Taylor & Stephen Leybourne & David Harvey, 2004. "Modified Tests for a Change in Persistence," Econometric Society 2004 Australasian Meetings 64, Econometric Society.

    Cited by:

    1. Pang, Tianxiao & Tai-Leung Chong, Terence & Zhang, Danna & Liang, Yanling, 2018. "Structural Change In Nonstationary Ar(1) Models," Econometric Theory, Cambridge University Press, vol. 34(5), pages 985-1017, October.
    2. Eiji Kurozumi, 2005. "Detection of Structural Change in the Long‐run Persistence in a Univariate Time Series," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(2), pages 181-206, April.
    3. Mohitosh Kejriwal, 2020. "A Robust Sequential Procedure for Estimating the Number of Structural Changes in Persistence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(3), pages 669-685, June.
    4. Otavio Ribeiro de Medeiros and Vitor Leone, 2012. "Multiple Changes in Persistence vs. Explosive Behaviour: The Dotcom Bubble," NBS Discussion Papers in Economics 2012/02, Economics, Nottingham Business School, Nottingham Trent University.
    5. Roy Cerqueti & Mauro Costantini & Luciano Gutierrez, 2009. "New panel tests to assess inflation persistence," Working Papers 54-2009, Macerata University, Department of Finance and Economic Sciences, revised Oct 2009.
    6. Cerqueti, Roy & Costantini, Mauro & Gutierrez, Luciano, 2007. "Change in persistence tests for panels," Economics & Statistics Discussion Papers esdp07040, University of Molise, Department of Economics.
    7. Zsolt Darvas & Balázs Varga, 2013. "Inflation Persistence in Central and Eastern European Countries," Working Papers 1302, Department of Mathematical Economics and Economic Analysis, Corvinus University of Budapest, revised Jul 2013.
    8. Mohitosh Kejriwal & Xuewen Yu & Pierre Perron, 2020. "Bootstrap Procedures for Detecting Multiple Persistence Shifts in Heteroskedastic Time Series," Boston University - Department of Economics - Working Papers Series WP2020-009, Boston University - Department of Economics.
    9. Cerqueti, Roy & Costantini, Mauro & Gutierrez, Luciano, 2008. "Change in persistence tests for panels: An update and some new results," Economics & Statistics Discussion Papers esdp08043, University of Molise, Department of Economics.
    10. Chen, Wei & Huang, Zhuo & Yi, Yanping, 2015. "Is there a structural change in the persistence of WTI–Brent oil price spreads in the post-2010 period?," Economic Modelling, Elsevier, vol. 50(C), pages 64-71.
    11. Paulo M.M. Rodrigues & Gabriel Zsurkis, 2019. "A reexamination of inflation persistence dynamics in OECD countries: A new approach," Working Papers w201909, Banco de Portugal, Economics and Research Department.
    12. A. M. Robert Taylor, 2005. "Fluctuation Tests for a Change in Persistence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(2), pages 207-230, April.
    13. Assaf, Ata & Bhandari, Avishek & Charif, Husni & Demir, Ender, 2022. "Multivariate long memory structure in the cryptocurrency market: The impact of COVID-19," International Review of Financial Analysis, Elsevier, vol. 82(C).
    14. Taipalus, Katja, 2012. "Signaling asset price bubbles with time-series methods," Bank of Finland Research Discussion Papers 7/2012, Bank of Finland.
    15. Ahmad Hassan Ahmad & Eric J. Pentecost, 2020. "Testing the ‘Fear of Floating’ Hypothesis: A Statistical Analysis for Eight African Countries," Open Economies Review, Springer, vol. 31(2), pages 407-430, April.
    16. Uwe Hassler & Jan Scheithauer, 2011. "Detecting changes from short to long memory," Statistical Papers, Springer, vol. 52(4), pages 847-870, November.
    17. Demetrescu, Matei & Rodrigues, Paulo M.M., 2022. "Residual-augmented IVX predictive regression," Journal of Econometrics, Elsevier, vol. 227(2), pages 429-460.
    18. Juan Carlos Cuestas & Carlyn Dobson, 2011. "Inflation persistence: Implication for a monetary union in the Caribbean," Working Papers 2011017, The University of Sheffield, Department of Economics.
    19. Paulo M.M. Rodrigues & Antonio Rubia, 2011. "A Class of Robust Tests in Augmented Predictive Regressions," Working Papers w201126, Banco de Portugal, Economics and Research Department.
    20. Eyal Dvir & Kenneth S. Rogoff, 2009. "Three Epochs of Oil," NBER Working Papers 14927, National Bureau of Economic Research, Inc.
    21. Pedro Bação, 2006. "The Performance of Structural Change Tests," Quality & Quantity: International Journal of Methodology, Springer, vol. 40(4), pages 611-628, August.
    22. Giorgio Canarella & Stephen M. Miller & Stephen K. Pollard, 2014. "Unemployment Rate Hysteresis and the Great Recession: Exploring the Metropolitan Evidence," Working Papers 1403, University of Nevada, Las Vegas , Department of Economics.
    23. Daniel Chiquiar & Antonio Noriega & Manuel Ramos-Francia, 2010. "A time-series approach to test a change in inflation persistence: the Mexican experience," Applied Economics, Taylor & Francis Journals, vol. 42(24), pages 3067-3075.
    24. Georgios KOURETAS & Mark E. WOHAR, 2010. "The Dynamics of Inflation: A Study of a Large Number of Countries," EcoMod2010 259600096, EcoMod.
    25. A H Ahmad & E J Pentecost, 2011. "Exchange Rate Regime Verification: An Alternative Method of Testing for Regime Changes," Department of Economics Working Papers 22748, University of Bath, Department of Economics.
    26. Simeon Coleman & Vitor Leone, 2015. "An investigation of regime shifts in UK commercial property returns: a time series analysis," Applied Economics, Taylor & Francis Journals, vol. 47(60), pages 6479-6492, December.
    27. Martins, Luis F. & Rodrigues, Paulo M.M., 2014. "Testing for persistence change in fractionally integrated models: An application to world inflation rates," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 502-522.
    28. Leone, Vitor & de Medeiros, Otavio Ribeiro, 2015. "Signalling the Dotcom bubble: A multiple changes in persistence approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 55(C), pages 77-86.
    29. Dergiades, Theologos & Kaufmann, Robert K. & Panagiotidis, Theodore, 2016. "Long-run changes in radiative forcing and surface temperature: The effect of human activity over the last five centuries," Journal of Environmental Economics and Management, Elsevier, vol. 76(C), pages 67-85.
    30. Pang, Tianxiao & Du, Lingjie & Chong, Terence Tai-Leung, 2021. "Estimating multiple breaks in nonstationary autoregressive models," Journal of Econometrics, Elsevier, vol. 221(1), pages 277-311.
    31. Evžen Kocenda & Balázs Varga, 2017. "The Impact of Monetary Strategies on Inflation Persistence," CESifo Working Paper Series 6306, CESifo.
    32. Antonio Noriega & Carlos Capistrán & Manuel Ramos-Francia, 2013. "On the dynamics of inflation persistence around the world," Empirical Economics, Springer, vol. 44(3), pages 1243-1265, June.
    33. Christis Katsouris, 2023. "Break-Point Date Estimation for Nonstationary Autoregressive and Predictive Regression Models," Papers 2308.13915, arXiv.org.
    34. Górecki, Tomasz & Horváth, Lajos & Kokoszka, Piotr, 2018. "Change point detection in heteroscedastic time series," Econometrics and Statistics, Elsevier, vol. 7(C), pages 63-88.
    35. Halunga, Andreea G. & Osborn, Denise R. & Sensier, Marianne, 2009. "Changes in the order of integration of US and UK inflation," Economics Letters, Elsevier, vol. 102(1), pages 30-32, January.
    36. Petrenko, Victoria (Петренко, ВИктория) & Skrobotov, Anton (Скроботов, Антон) & Turuntseva, Maria (Турунцева, Мария), 2016. "Testing of Changes in Persistence and Their Effect on the Forecasting Quality [Тестирование Изменения Инерционности И Влияние На Качество Прогнозов]," Working Papers 542, Russian Presidential Academy of National Economy and Public Administration.
    37. C.S. Bos & S.J. Koopman & M. Ooms, 2007. "Long Memory Modelling of Inflation with Stochastic Variance and Structural Breaks," Tinbergen Institute Discussion Papers 07-099/4, Tinbergen Institute.
    38. Simeon Coleman & Kavita Sirichand, 2014. "Investigating Multiple Changes in Persistence in International Yields," Discussion Paper Series 2014_04, Department of Economics, Loughborough University, revised Jul 2014.
    39. Taipalus, Katja, 2012. "Detecting asset price bubbles with time-series methods," Bank of Finland Scientific Monographs, Bank of Finland, volume 0, number sm2012_047.
    40. Xiao Han & Nikolaos Sakkas & Jo Danbolt & Arman Eshraghi, 2022. "Persistence of investor sentiment and market mispricing," The Financial Review, Eastern Finance Association, vol. 57(3), pages 617-640, August.
    41. Kruse, Yves Robinson & Kaufmann, Hendrik, 2015. "Bias-corrected estimation in mildly explosive autoregressions," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112897, Verein für Socialpolitik / German Economic Association.
    42. Noriega Antonio E. & Ramos Francia Manuel, 2008. "A Note on the Dynamics of Persistence in US Inflation," Working Papers 2008-12, Banco de México.
    43. Rodrigues, Paulo M.M. & Sibbertsen, Philipp & Voges, Michelle, 2019. "Testing for breaks in the cointegrating relationship: On the stability of government bond markets' equilibrium," Hannover Economic Papers (HEP) dp-656, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    44. Juan Carlos Cuestas & Carlyn Ramlogan-Dobson, 2013. "Convergence of Inflationary Shocks: Evidence from the Caribbean," The World Economy, Wiley Blackwell, vol. 36(9), pages 1229-1243, September.
    45. Noriega, Antonio E. & Ramos-Francia, Manuel, 2009. "The dynamics of persistence in US inflation," Economics Letters, Elsevier, vol. 105(2), pages 168-172, November.
    46. Uwe Hassler & Jan Scheithauer, 2008. "On Critical Values of Tests against a Change in Persistence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(5), pages 705-710, October.
    47. Daiqing Xi & Tianxiao Pang, 2021. "Estimating multiple breaks in mean sequentially with fractionally integrated errors," Statistical Papers, Springer, vol. 62(1), pages 451-494, February.
    48. Park, Cheolbeom, 2010. "When does the dividend-price ratio predict stock returns?," Journal of Empirical Finance, Elsevier, vol. 17(1), pages 81-101, January.
    49. Rob Ackrill and Simeon Coleman, 2012. "Inflation dynamics in central and eastern European countries," NBS Discussion Papers in Economics 2012/01, Economics, Nottingham Business School, Nottingham Trent University.
    50. Cook, Steven & Fosten, Jack, 2019. "Replicating rockets and feathers," Energy Economics, Elsevier, vol. 82(C), pages 139-151.
    51. Simeon Coleman Author name: Vitor Leone, 2012. "Time-series characteristics of UK commercial property returns: Testing for multiple changes in persistence," NBS Discussion Papers in Economics 2012/03, Economics, Nottingham Business School, Nottingham Trent University.
    52. Jorge Belaire-Franch, 2019. "A note on the evidence of inflation persistence around the world," Empirical Economics, Springer, vol. 56(5), pages 1477-1487, May.
    53. Hendrik Kaufmannz & Robinson Kruse, 2013. "Bias-corrected estimation in potentially mildly explosive autoregressive models," CREATES Research Papers 2013-10, Department of Economics and Business Economics, Aarhus University.
    54. Roy Cerqueti & Mauro Costantini & Luciano Gutierrez & Joakim Westerlund, 2019. "Panel stationary tests against changes in persistence," Statistical Papers, Springer, vol. 60(4), pages 1079-1100, August.
    55. Zhanshou Chen & Yanting Xiao & Fuxiao Li, 2021. "Monitoring memory parameter change-points in long-memory time series," Empirical Economics, Springer, vol. 60(5), pages 2365-2389, May.
    56. Hans KREMERS & Andreas LOESCHEL, 2010. "The Strategic Implications of Setting Border Tax Adjustments," EcoMod2010 259600097, EcoMod.
    57. Lajos Horváth & William Pouliot & Shixuan Wang, 2017. "Detecting at-Most-m Changes in Linear Regression Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(4), pages 552-590, July.
    58. Li, Fuxiao & Tian, Zheng & Xiao, Yanting & Chen, Zhanshou, 2015. "Variance change-point detection in panel data models," Economics Letters, Elsevier, vol. 126(C), pages 140-143.
    59. Luis F. Martins & Paulo M. M. Rodrigues, 2022. "Tests for segmented cointegration: an application to US governments budgets," Empirical Economics, Springer, vol. 63(2), pages 567-600, August.
    60. Assaf, Ata & Mokni, Khaled & Yousaf, Imran & Bhandari, Avishek, 2023. "Long memory in the high frequency cryptocurrency markets using fractal connectivity analysis: The impact of COVID-19," Research in International Business and Finance, Elsevier, vol. 64(C).
    61. Chen, Zhanshou & Jin, Zi & Tian, Zheng & Qi, Peiyan, 2012. "Bootstrap testing multiple changes in persistence for a heavy-tailed sequence," Computational Statistics & Data Analysis, Elsevier, vol. 56(7), pages 2303-2316.
    62. Mohamed Bouabidi, 2022. "The Tunisian exchange rate regime: Is it really floating?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4684-4704, October.

Articles

  1. David I. Harvey & Stephen J. Leybourne & Robert Sollis & A.M. Robert Taylor, 2021. "Real‐time detection of regimes of predictability in the US equity premium," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(1), pages 45-70, January.
    See citations under working paper version above.
  2. Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2021. "Simple tests for stock return predictability with good size and power properties," Journal of Econometrics, Elsevier, vol. 224(1), pages 198-214.
    See citations under working paper version above.
  3. Harvey, David I. & Leybourne, Stephen J. & Whitehouse, Emily J., 2020. "Date-stamping multiple bubble regimes," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 226-246.

    Cited by:

    1. Yang, Bingduo & Long, Wei & Yang, Zihui, 2022. "Testing predictability of stock returns under possible bubbles," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 246-260.
    2. Lajos Horváth & Hemei Li & Zhenya Liu, 2021. "How to identify the different phases of stock market bubbles statistically?," Post-Print hal-03511435, HAL.
    3. Skrobotov Anton, 2023. "Testing for explosive bubbles: a review," Dependence Modeling, De Gruyter, vol. 11(1), pages 1-26, January.
    4. Eiji Kurozumi & Anton Skrobotov, 2021. "On the asymptotic behavior of bubble date estimators," Papers 2110.04500, arXiv.org, revised Sep 2022.

  4. Harvey, David I. & Leybourne, Stephen J. & Zu, Yang, 2020. "Sign-Based Unit Root Tests For Explosive Financial Bubbles In The Presence Of Deterministically Time-Varying Volatility," Econometric Theory, Cambridge University Press, vol. 36(1), pages 122-169, February.

    Cited by:

    1. Jean-Louis Bago & Koffi Akakpo & Imad Rherrad & Ernest Ouédraogo, 2021. "Volatility Spillover and International Contagion of Housing Bubbles," JRFM, MDPI, vol. 14(7), pages 1-14, June.
    2. Verena Monschang & Bernd Wilfling, 2019. "Sup-ADF-style bubble-detection methods under test," CQE Working Papers 7819, Center for Quantitative Economics (CQE), University of Muenster.
    3. Eiji Kurozumi & Anton Skrobotov & Alexey Tsarev, 2020. "Time-Transformed Test for the Explosive Bubbles under Non-stationary Volatility," Papers 2012.13937, arXiv.org, revised Nov 2021.
    4. Eiji Kurozumi & Anton Skrobotov, 2023. "Improving the accuracy of bubble date estimators under time-varying volatility," Papers 2306.02977, arXiv.org.
    5. Vicente Esteve & María A. Prats, 2022. "Testing explosive bubbles with time-varying volatility: The case of the Spanish public debt, 1850?2021," Working Papers 2205, Department of Applied Economics II, Universidad de Valencia.
    6. Sam Astill & David I Harvey & Stephen J Leybourne & A M Robert Taylor & Yang Zu, 2023. "CUSUM-Based Monitoring for Explosive Episodes in Financial Data in the Presence of Time-Varying Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 21(1), pages 187-227.
    7. Xuanling Yang & Dong Li & Ting Zhang, 2024. "A simple stochastic nonlinear AR model with application to bubble," Papers 2401.07038, arXiv.org.
    8. Shuping Shi & Peter C. B. Phillips, 2022. "Econometric Analysis of Asset Price Bubbles," Cowles Foundation Discussion Papers 2331, Cowles Foundation for Research in Economics, Yale University.
    9. Aktham Maghyereh & Hussein Abdoh, 2022. "Can news-based economic sentiment predict bubbles in precious metal markets?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-29, December.
    10. Esteve, Vicente & Prats, María A., 2023. "Testing explosive bubbles with time-varying volatility: The case of Spanish public debt," Finance Research Letters, Elsevier, vol. 51(C).
    11. Esteve, Vicente & Prats, María A., 2023. "Testing explosive bubbles with time-varying volatility: the case of Spanish public debt," LSE Research Online Documents on Economics 116980, London School of Economics and Political Science, LSE Library.

  5. Iliyan Georgiev & David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2019. "A Bootstrap Stationarity Test for Predictive Regression Invalidity," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(3), pages 528-541, July.
    See citations under working paper version above.
  6. David I. Harvey & Stephen J. Leybourne & Yang Zu, 2019. "Testing explosive bubbles with time-varying volatility," Econometric Reviews, Taylor & Francis Journals, vol. 38(10), pages 1131-1151, November.
    See citations under working paper version above.
  7. Sam Astill & David I. Harvey & Stephen J. Leybourne & Robert Sollis & A. M. Robert Taylor, 2018. "Real‐Time Monitoring for Explosive Financial Bubbles," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 863-891, November.

    Cited by:

    1. Gil-Alana, Luis Alberiko & Dettoni, Robinson & Costamagna, Rodrigo & Valenzuela, Mario, 2019. "Rational bubbles in the real housing stock market: Empirical evidence from Santiago de Chile," Research in International Business and Finance, Elsevier, vol. 49(C), pages 269-281.
    2. Judith Eidenberger & Vanessa Redak & Eva Ubl, 2019. "Who puts our financial system at risk? A methodological approach to identify banks with potential significant negative effects on financial stability," Financial Stability Report, Oesterreichische Nationalbank (Austrian Central Bank), issue 37, pages 57-72.
    3. Eiji Kurozumi, 2021. "Asymptotic Behavior of Delay Times of Bubble Monitoring Tests," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(3), pages 314-337, May.
    4. Tomás Caravello & Zacharias Psaradakis & Martín Sola, 2021. "Rational Bubbles: Too Many to be True?," Department of Economics Working Papers 2021_06, Universidad Torcuato Di Tella.
    5. Sam Astill & David I Harvey & Stephen J Leybourne & A M Robert Taylor & Yang Zu, 2023. "CUSUM-Based Monitoring for Explosive Episodes in Financial Data in the Presence of Time-Varying Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 21(1), pages 187-227.
    6. Shobande Olatunji Abdul & Shodipe Oladimeji Tomiwa, 2020. "Re-Evaluation of World Population Figures: Politics and Forecasting Mechanics," Economics and Business, Sciendo, vol. 34(1), pages 104-125, February.

  8. Georgiev, Iliyan & Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2018. "Testing for parameter instability in predictive regression models," Journal of Econometrics, Elsevier, vol. 204(1), pages 101-118.

    Cited by:

    1. Christis Katsouris, 2023. "Structural Break Detection in Quantile Predictive Regression Models with Persistent Covariates," Papers 2302.05193, arXiv.org.
    2. Mohitosh Kejriwal & Xuewen Yu & Pierre Perron, 2020. "Bootstrap Procedures for Detecting Multiple Persistence Shifts in Heteroskedastic Time Series," Boston University - Department of Economics - Working Papers Series WP2020-009, Boston University - Department of Economics.
    3. Torben G. Andersen & Rasmus T. Varneskov, 2021. "Testing for Parameter Instability and Structural Change in Persistent Predictive Regressions," NBER Working Papers 28570, National Bureau of Economic Research, Inc.
    4. Cai, Zongwu & Juhl, Ted, 2023. "The distribution of rolling regression estimators," Journal of Econometrics, Elsevier, vol. 235(2), pages 1447-1463.
    5. Paulo M.M. Rodrigues & Matei Demetrescu, 2019. "Testing for Episodic Predictability in Stock Returns," Working Papers w201906, Banco de Portugal, Economics and Research Department.
    6. Otilia Boldea & Adriana Cornea-Madeira & Alastair R. Hall, 2018. "Bootstrapping Structural Change Tests," Papers 1811.04125, arXiv.org.
    7. Yanbo Liu & Peter C.B. Phillips, 2021. "Robust Inference with Stochastic Local Unit Root Regressors in Predictive Regressions," Cowles Foundation Discussion Papers 2305, Cowles Foundation for Research in Economics, Yale University.
    8. Fukang Zhu & Mengya Liu & Shiqing Ling & Zongwu Cai, 2020. "Testing for Structural Change of Predictive Regression Model to Threshold Predictive Regression Model," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202021, University of Kansas, Department of Economics, revised Dec 2020.
    9. Xiaohui Liu & Yuzi Liu & Yao Rao & Fucai Lu, 2021. "A Unified test for the Intercept of a Predictive Regression Model," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(2), pages 571-588, April.
    10. Christis Katsouris, 2023. "Limit Theory under Network Dependence and Nonstationarity," Papers 2308.01418, arXiv.org, revised Aug 2023.
    11. Anibal Emiliano Da Silva Neto & Jesús Gonzalo & Jean‐Yves Pitarakis, 2021. "Uncovering Regimes in Out of Sample Forecast Errors from Predictive Regressions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(3), pages 713-741, June.
    12. Tu, Yundong & Xie, Xinling, 2023. "Penetrating sporadic return predictability," Journal of Econometrics, Elsevier, vol. 237(1).
    13. Gonzalo, Jesús & Pitarakis, Jean-Yves, 2019. "Predictive Regressions," UC3M Working papers. Economics 28554, Universidad Carlos III de Madrid. Departamento de Economía.
    14. Zongwu Cai & Ted Juhl, 2020. "The Distribution Of Rolling Regression Estimators," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202218, University of Kansas, Department of Economics, revised Dec 2022.
    15. Christis Katsouris, 2023. "Bootstrapping Nonstationary Autoregressive Processes with Predictive Regression Models," Papers 2307.14463, arXiv.org.
    16. Christis Katsouris, 2023. "Predictability Tests Robust against Parameter Instability," Papers 2307.15151, arXiv.org.
    17. Mikihito Nishi, 2023. "Testing for Stationary or Persistent Coefficient Randomness in Predictive Regressions," Papers 2309.04926, arXiv.org, revised Jan 2024.

  9. Harvey, David I. & Kellard, Neil M. & Madsen, Jakob B. & Wohar, Mark E., 2017. "Long-Run Commodity Prices, Economic Growth, and Interest Rates: 17th Century to the Present Day," World Development, Elsevier, vol. 89(C), pages 57-70.

    Cited by:

    1. Abbas, Syed Kanwar & Lan, Hao, 2020. "Commodity price pass-through and inflation regimes," Energy Economics, Elsevier, vol. 92(C).
    2. Winkelried, Diego, 2021. "Unit roots in real primary commodity prices? A meta-analysis of the Grilli and Yang data set," Journal of Commodity Markets, Elsevier, vol. 23(C).
    3. Ghoshray, Atanu, 2019. "Do international primary commodity prices exhibit asymmetric adjustment?," Journal of Commodity Markets, Elsevier, vol. 14(C), pages 40-50.
    4. Juncal Cunado & Luis A. Gil-Alana & Rangan Gupta, 2018. "Persistence in Trends and Cycles of Gold and Silver Prices: Evidence from Historical Data," Working Papers 201816, University of Pretoria, Department of Economics.
    5. Makhlouf, Yousef & Kellard, Neil M. & Vinogradov, Dmitri, 2017. "Child mortality, commodity price volatility and the resource curse," Social Science & Medicine, Elsevier, vol. 178(C), pages 144-156.
    6. Ge, Yiqing & Tang, Ke, 2020. "Commodity prices and GDP growth," International Review of Financial Analysis, Elsevier, vol. 71(C).
    7. Yasmeen Idilbi-Bayaa & Mahmoud Qadan, 2021. "Forecasting Commodity Prices Using the Term Structure," JRFM, MDPI, vol. 14(12), pages 1-39, December.
    8. Yousef Makhlouf, 2023. "Trends in Income Inequality: Evidence from Developing and Developed Countries," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 165(1), pages 213-243, January.
    9. Gray, Rowena & Narciso, Gaia & Tortorici, Gaspare, 2019. "Globalization, agricultural markets and mass migration: Italy, 1881–1912," Explorations in Economic History, Elsevier, vol. 74(C).
    10. Christophe Gouel & Qingyin Ma & John Stachurski, 2023. "Interest Rate Dynamics and Commodity Prices," Papers 2308.07577, arXiv.org.
    11. Jair N. Ojeda-Joya & Oscar Jaulin-Mendez & Juan C. Bustos-Peláez, 2019. "The Interdependence Between Commodity-Price and GDP Cycles: A Frequency-Domain Approach," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 47(3), pages 275-292, September.
    12. Yves Jégourel, 2017. "Tendances et cyclicité du prix des matières premières (partie 1) : le débat sur l’hypothèse de Prebisch-Singer," Policy briefs 1729, Policy Center for the New South.
    13. Saidi, Samir & Mani, Venkatesh & Mefteh, Haifa & Shahbaz, Muhammad & Akhtar, Pervaiz, 2020. "Dynamic linkages between transport, logistics, foreign direct Investment, and economic growth: Empirical evidence from developing countries," Transportation Research Part A: Policy and Practice, Elsevier, vol. 141(C), pages 277-293.
    14. Fernandez, Viviana, 2019. "Assessing cycles of mine production and prices of industrial metals," Resources Policy, Elsevier, vol. 63(C), pages 1-1.
    15. Awaworyi-Churchill, Sefa & Inekwe, John & Ivanovski, Kris & Smyth, Russell, 2022. "Breaks, trends and correlations in commodity prices in the very long-run," Energy Economics, Elsevier, vol. 108(C).
    16. Infante-Amate, Juan & Krausmann, Fridolin, 2019. "Trade, Ecologically Unequal Exchange and Colonial Legacy: The Case of France and its Former Colonies (1962–2015)," Ecological Economics, Elsevier, vol. 156(C), pages 98-109.
    17. Fernandez, Viviana, 2019. "A readily computable commodity price index: 1900–2016," Finance Research Letters, Elsevier, vol. 31(C).
    18. Umair Kashif & Junguo Shi & Snovia Naseem & Muhammad Ayaz & Rehan Sohail Butt & Waris Ali Khan & Mamdouh Abdulaziz Saleh Al-Faryan, 2023. "Do agricultural commodity prices asymmetrically affect the performance of value-added agriculture? Evidence from Pakistan using a NARDL model," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-9, December.

  10. Harvey, David I. & Leybourne, Stephen J. & Whitehouse, Emily J., 2017. "Forecast evaluation tests and negative long-run variance estimates in small samples," International Journal of Forecasting, Elsevier, vol. 33(4), pages 833-847.
    See citations under working paper version above.
  11. Aristidou Chrystalleni & Harvey David I. & Leybourne Stephen J., 2017. "The Impact of the Initial Condition on Covariate Augmented Unit Root Tests," Journal of Time Series Econometrics, De Gruyter, vol. 9(1), pages 1-23, January.
    See citations under working paper version above.
  12. Harvey, David I. & Leybourne, Stephen J. & Sollis, Robert, 2017. "Improving the accuracy of asset price bubble start and end date estimators," Journal of Empirical Finance, Elsevier, vol. 40(C), pages 121-138.

    Cited by:

    1. Pang, Tianxiao & Tai-Leung Chong, Terence & Zhang, Danna & Liang, Yanling, 2018. "Structural Change In Nonstationary Ar(1) Models," Econometric Theory, Cambridge University Press, vol. 34(5), pages 985-1017, October.
    2. Potrykus, Marcin, 2023. "Investing in wine, precious metals and G-7 stock markets – A co-occurrence analysis for price bubbles," International Review of Financial Analysis, Elsevier, vol. 87(C).
    3. Yang Hu, 2023. "A review of Phillips‐type right‐tailed unit root bubble detection tests," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 141-158, February.
    4. Harvey, David I. & Leybourne, Stephen J. & Whitehouse, Emily J., 2020. "Date-stamping multiple bubble regimes," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 226-246.
    5. Sinelnikova-Muryleva, Elena & Skrobotov, Anton, 2017. "Testing time series for the bubbles (with application to Russian data)," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 46, pages 90-103.
    6. Eiji Kurozumi & Anton Skrobotov, 2023. "Improving the accuracy of bubble date estimators under time-varying volatility," Papers 2306.02977, arXiv.org.
    7. Sam Astill & David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2017. "Tests for an end-of-sample bubble in financial time series," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 651-666, October.
    8. David I. Harvey & Stephen J. Leybourne & Yang Zu, 2019. "Testing explosive bubbles with time-varying volatility," Econometric Reviews, Taylor & Francis Journals, vol. 38(10), pages 1131-1151, November.
    9. Sam Astill & David I. Harvey & Stephen J. Leybourne & Robert Sollis & A. M. Robert Taylor, 2018. "Real‐Time Monitoring for Explosive Financial Bubbles," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 863-891, November.
    10. Lajos Horváth & Hemei Li & Zhenya Liu, 2021. "How to identify the different phases of stock market bubbles statistically?," Post-Print hal-03511435, HAL.
    11. Pang, Tianxiao & Du, Lingjie & Chong, Terence Tai-Leung, 2021. "Estimating multiple breaks in nonstationary autoregressive models," Journal of Econometrics, Elsevier, vol. 221(1), pages 277-311.
    12. Moreira, Afonso M. & Martins, Luis F., 2020. "A new mechanism for anticipating price exuberance," International Review of Economics & Finance, Elsevier, vol. 65(C), pages 199-221.
    13. Astill, Sam & Taylor, A.M. Robert & Kellard, Neil & Korkos, Ioannis, 2023. "Using covariates to improve the efficacy of univariate bubble detection methods," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 342-366.
    14. Eiji Kurozumi & Anton Skrobotov, 2023. "On the asymptotic behavior of bubble date estimators," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(4), pages 359-373, July.
    15. Skrobotov Anton, 2023. "Testing for explosive bubbles: a review," Dependence Modeling, De Gruyter, vol. 11(1), pages 1-26, January.
    16. Andria C. Evripidou & David I. Harvey & Stephen J. Leybourne & Robert Sollis, 2022. "Testing for Co‐explosive Behaviour in Financial Time Series," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(3), pages 624-650, June.
    17. Bouri, Elie & Shahzad, Syed Jawad Hussain & Roubaud, David, 2019. "Co-explosivity in the cryptocurrency market," Finance Research Letters, Elsevier, vol. 29(C), pages 178-183.
    18. Whitehouse, E. J. & Harvey, D. I. & Leybourne, S. J., 2022. "Real-time monitoring of bubbles and crashes," Working Papers 2022007, The University of Sheffield, Department of Economics.
    19. Kruse, Robinson & Kaufmann, Hendrik & Wegener, Christoph, 2018. "Bias-corrected estimation for speculative bubbles in stock prices," Economic Modelling, Elsevier, vol. 73(C), pages 354-364.
    20. Bellón, Carlos & Figuerola-Ferretti, Isabel, 2022. "Bubbles in Ethereum," Finance Research Letters, Elsevier, vol. 46(PB).
    21. Theodosios Perifanis, 2019. "Detecting West Texas Intermediate (WTI) Prices’ Bubble Periods," Energies, MDPI, vol. 12(14), pages 1-16, July.
    22. Eiji Kurozumi & Anton Skrobotov, 2021. "On the asymptotic behavior of bubble date estimators," Papers 2110.04500, arXiv.org, revised Sep 2022.
    23. Lajos Horv'ath & Lorenzo Trapani, 2023. "Real-time monitoring with RCA models," Papers 2312.11710, arXiv.org.

  13. Sam Astill & David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2017. "Tests for an end-of-sample bubble in financial time series," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 651-666, October.
    See citations under working paper version above.
  14. Harvey, David I. & Leybourne, Stephen J. & Sollis, Robert & Taylor, A.M. Robert, 2016. "Tests for explosive financial bubbles in the presence of non-stationary volatility," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 548-574.

    Cited by:

    1. Jean-Louis Bago & Koffi Akakpo & Imad Rherrad & Ernest Ouédraogo, 2021. "Volatility Spillover and International Contagion of Housing Bubbles," JRFM, MDPI, vol. 14(7), pages 1-14, June.
    2. Wang, Shaoping & Feng, Hao & Gao, Da, 2023. "Testing for short explosive bubbles: A case of Brent oil futures price," Finance Research Letters, Elsevier, vol. 52(C).
    3. Verena Monschang & Bernd Wilfling, 2019. "Sup-ADF-style bubble-detection methods under test," CQE Working Papers 7819, Center for Quantitative Economics (CQE), University of Muenster.
    4. Gomis-Porqueras, Pedro & Shi, Shuping & Tan, David, 2020. "Gold as a Financial Instrument," MPRA Paper 102782, University Library of Munich, Germany.
    5. Yang Hu, 2023. "A review of Phillips‐type right‐tailed unit root bubble detection tests," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 141-158, February.
    6. Figuerola-Ferretti, Isabel & McCrorie, J. Roderick & Paraskevopoulos, Ioannis, 2020. "Mild explosivity in recent crude oil prices," Energy Economics, Elsevier, vol. 87(C).
    7. Fantazzini, Dean, 2016. "The Oil Price Crash in 2014/15: Was There a (Negative) Financial Bubble?," MPRA Paper 72094, University Library of Munich, Germany.
    8. Eiji Kurozumi & Anton Skrobotov & Alexey Tsarev, 2020. "Time-Transformed Test for the Explosive Bubbles under Non-stationary Volatility," Papers 2012.13937, arXiv.org, revised Nov 2021.
    9. Harvey, David I. & Leybourne, Stephen J. & Whitehouse, Emily J., 2020. "Date-stamping multiple bubble regimes," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 226-246.
    10. Cretí, Anna & Joëts, Marc, 2017. "Multiple bubbles in the European Union Emission Trading Scheme," Energy Policy, Elsevier, vol. 107(C), pages 119-130.
    11. Pedersen, Thomas Quistgaard & Schütte, Erik Christian Montes, 2020. "Testing for explosive bubbles in the presence of autocorrelated innovations," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 207-225.
    12. Sinelnikova-Muryleva, Elena & Skrobotov, Anton, 2017. "Testing time series for the bubbles (with application to Russian data)," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 46, pages 90-103.
    13. Floro, Danvee, 2019. "Testing the predictive ability of house price bubbles for macroeconomic performance: A meta-analytic approach," International Review of Financial Analysis, Elsevier, vol. 62(C), pages 164-181.
    14. Eiji Kurozumi & Anton Skrobotov, 2023. "Improving the accuracy of bubble date estimators under time-varying volatility," Papers 2306.02977, arXiv.org.
    15. Shuping Shi & Peter C.B. Phillips, 2020. "Diagnosing Housing Fever with an Econometric Thermometer," Cowles Foundation Discussion Papers 2248, Cowles Foundation for Research in Economics, Yale University.
    16. Figuerola-Ferretti, Isabel & McCrorie, J. Roderick, 2016. "The shine of precious metals around the global financial crisis," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 717-738.
    17. Basse, Tobias & Klein, Tony & Vigne, Samuel A. & Wegener, Christoph, 2021. "U.S. stock prices and the dot.com-bubble: Can dividend policy rescue the efficient market hypothesis?," Journal of Corporate Finance, Elsevier, vol. 67(C).
    18. Zeren Feyyaz & Yilanci Veli, 2019. "Are there Multiple Bubbles in the Stock Markets? Further Evidence from Selected Countries," Ekonomika (Economics), Sciendo, vol. 98(1), pages 81-95, June.
    19. Zhuo Chen & Bo Yan & Hanwen Kang, 2023. "Price bubbles of agricultural commodities: evidence from China’s futures market," Empirical Economics, Springer, vol. 64(1), pages 195-222, January.
    20. Li, Yanglin & Wang, Shaoping & Zhao, Qing, 2021. "When does the stock market recover from a crisis?," Finance Research Letters, Elsevier, vol. 39(C).
    21. Sam Astill & David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2017. "Tests for an end-of-sample bubble in financial time series," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 651-666, October.
    22. David I. Harvey & Stephen J. Leybourne & Yang Zu, 2019. "Testing explosive bubbles with time-varying volatility," Econometric Reviews, Taylor & Francis Journals, vol. 38(10), pages 1131-1151, November.
    23. H. Peter Boswijk & Giuseppe Cavaliere & Anders Rahbek & Iliyan Georgiev, 2021. "Bootstrapping Non-Stationary Stochastic Volatility," Papers 2101.03562, arXiv.org.
    24. Sam Astill & David I. Harvey & Stephen J. Leybourne & Robert Sollis & A. M. Robert Taylor, 2018. "Real‐Time Monitoring for Explosive Financial Bubbles," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 863-891, November.
    25. Yan, Lei & Irwin, Scott H. & Sanders, Dwight R., 2018. "Mapping algorithms, agricultural futures, and the relationship between commodity investment flows and crude oil futures prices," Energy Economics, Elsevier, vol. 72(C), pages 486-504.
    26. Escobari, Diego & Garcia, Sergio & Mellado, Cristhian, 2017. "Identifying bubbles in Latin American equity markets: Phillips-Perron-based tests and linkages," Emerging Markets Review, Elsevier, vol. 33(C), pages 90-101.
    27. Hu, Yang & Oxley, Les, 2017. "Are there bubbles in exchange rates? Some new evidence from G10 and emerging market economies," Economic Modelling, Elsevier, vol. 64(C), pages 419-442.
    28. Ramit Sawhney & Shivam Agarwal & Vivek Mittal & Paolo Rosso & Vikram Nanda & Sudheer Chava, 2022. "Cryptocurrency Bubble Detection: A New Stock Market Dataset, Financial Task & Hyperbolic Models," Papers 2206.06320, arXiv.org.
    29. Lajos Horváth & Hemei Li & Zhenya Liu, 2021. "How to identify the different phases of stock market bubbles statistically?," Post-Print hal-03511435, HAL.
    30. Oladosu, Gbadebo, 2022. "Bubbles in US gasoline prices: Assessing the role of hurricanes and anti–price gouging laws," Journal of Commodity Markets, Elsevier, vol. 27(C).
    31. Peter C. B. Phillips & Shuping Shi, 2019. "Detecting Financial Collapse and Ballooning Sovereign Risk," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 81(6), pages 1336-1361, December.
    32. Ajmi, Ahdi Noomen & Hammoudeh, Shawkat & Mokni, Khaled, 2021. "Detection of bubbles in WTI, brent, and Dubai oil prices: A novel double recursive algorithm," Resources Policy, Elsevier, vol. 70(C).
    33. Pang, Tianxiao & Du, Lingjie & Chong, Terence Tai-Leung, 2021. "Estimating multiple breaks in nonstationary autoregressive models," Journal of Econometrics, Elsevier, vol. 221(1), pages 277-311.
    34. Grabowski, Wojciech & Welfe, Aleksander, 2020. "The Tobit cointegrated vector autoregressive model: An application to the currency market," Economic Modelling, Elsevier, vol. 89(C), pages 88-100.
    35. Eray Gemici & Muslum Polat & Remzi Gök & Muhammad Asif Khan & Mohammed Arshad Khan & Yunus Kilic, 2023. "Do Bubbles in the Bitcoin Market Impact Stock Markets? Evidence From 10 Major Stock Markets," SAGE Open, , vol. 13(2), pages 21582440231, June.
    36. Gharib, Cheima & Mefteh-Wali, Salma & Serret, Vanessa & Ben Jabeur, Sami, 2021. "Impact of COVID-19 pandemic on crude oil prices: Evidence from Econophysics approach," Resources Policy, Elsevier, vol. 74(C).
    37. Moreira, Afonso M. & Martins, Luis F., 2020. "A new mechanism for anticipating price exuberance," International Review of Economics & Finance, Elsevier, vol. 65(C), pages 199-221.
    38. Pan, Wei-Fong, 2018. "Sentiment and asset price bubble in the precious metals markets," Finance Research Letters, Elsevier, vol. 26(C), pages 106-111.
    39. Kristoffer Pons Bertelsen, 2019. "Comparing Tests for Identification of Bubbles," CREATES Research Papers 2019-16, Department of Economics and Business Economics, Aarhus University.
    40. Steenkamp, Daan, 2018. "Explosiveness in G11 currencies," Economic Modelling, Elsevier, vol. 68(C), pages 388-408.
    41. Lajos Horváth & Curtis Miller & Gregory Rice, 2021. "Detecting early or late changes in linear models with heteroscedastic errors," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(2), pages 577-609, June.
    42. Hu, Yang & Oxley, Les, 2018. "Bubble contagion: Evidence from Japan’s asset price bubble of the 1980-90s," Journal of the Japanese and International Economies, Elsevier, vol. 50(C), pages 89-95.
    43. Astill, Sam & Taylor, A.M. Robert & Kellard, Neil & Korkos, Ioannis, 2023. "Using covariates to improve the efficacy of univariate bubble detection methods," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 342-366.
    44. Lui, Yiu Lim & Phillips, Peter C.B. & Yu, Jun, 2024. "Robust testing for explosive behavior with strongly dependent errors," Journal of Econometrics, Elsevier, vol. 238(2).
    45. Xiaojie Xu, 2020. "Corn Cash Price Forecasting," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(4), pages 1297-1320, August.
    46. Eiji Kurozumi, 2021. "Asymptotic Behavior of Delay Times of Bubble Monitoring Tests," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(3), pages 314-337, May.
    47. Meng, Bo & Vijh, Anand M., 2021. "Stock merger activity and industry performance," Journal of Banking & Finance, Elsevier, vol. 129(C).
    48. Chen, Shyh-Wei & Wu, An-Chi, 2018. "Is there a bubble component in government debt? New international evidence," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 467-486.
    49. Andria C. Evripidou & David I. Harvey & Stephen J. Leybourne & Robert Sollis, 2022. "Testing for Co‐explosive Behaviour in Financial Time Series," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(3), pages 624-650, June.
    50. Tomás Caravello & Zacharias Psaradakis & Martín Sola, 2021. "Rational Bubbles: Too Many to be True?," Department of Economics Working Papers 2021_06, Universidad Torcuato Di Tella.
    51. Sam Astill & David I Harvey & Stephen J Leybourne & A M Robert Taylor & Yang Zu, 2023. "CUSUM-Based Monitoring for Explosive Episodes in Financial Data in the Presence of Time-Varying Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 21(1), pages 187-227.
    52. Yongheng Deng & Eric Girardin & Roselyne Joyeux & Shuping Shi, 2017. "Did bubbles migrate from the stock to the housing market in China between 2005 and 2010?," Pacific Economic Review, Wiley Blackwell, vol. 22(3), pages 276-292, August.
    53. Whitehouse, E. J. & Harvey, D. I. & Leybourne, S. J., 2022. "Real-time monitoring of bubbles and crashes," Working Papers 2022007, The University of Sheffield, Department of Economics.
    54. Canepa Alessandra, 2022. "Small Sample Adjustment for Hypotheses Testing on Cointegrating Vectors," Journal of Time Series Econometrics, De Gruyter, vol. 14(1), pages 51-85, January.
    55. Wang, Xichen & Yan, Ji (Karena) & Yan, Cheng & Gozgor, Giray, 2021. "Emerging stock market exuberance and international short-term flows," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
    56. Lajos Horvath & Lorenzo Trapani, 2021. "Changepoint detection in random coefficient autoregressive models," Papers 2104.13440, arXiv.org.
    57. Alexakis, Christos & Bagnarosa, Guillaume & Dowling, Michael, 2017. "Do cointegrated commodities bubble together? the case of hog, corn, and soybean," Finance Research Letters, Elsevier, vol. 23(C), pages 96-102.
    58. Hu, Yang & Oxley, Les, 2018. "Do 18th century ‘bubbles’ survive the scrutiny of 21st century time series econometrics?," Economics Letters, Elsevier, vol. 162(C), pages 131-134.
    59. Assaf, Ata, 2018. "Testing for bubbles in the art markets: An empirical investigation," Economic Modelling, Elsevier, vol. 68(C), pages 340-355.
    60. Shuping Shi & Peter C. B. Phillips, 2022. "Econometric Analysis of Asset Price Bubbles," Cowles Foundation Discussion Papers 2331, Cowles Foundation for Research in Economics, Yale University.
    61. Liu, Tie-Ying & Lee, Chien-Chiang, 2021. "Global convergence of inflation rates," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    62. Aktham Maghyereh & Hussein Abdoh, 2022. "Can news-based economic sentiment predict bubbles in precious metal markets?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-29, December.
    63. Esteve, Vicente & Prats, María A., 2023. "Testing explosive bubbles with time-varying volatility: The case of Spanish public debt," Finance Research Letters, Elsevier, vol. 51(C).
    64. Neil Kellard & Denise Osborn & Jerry Coakley & Isabel Figuerola-Ferretti & Christopher L. Gilbert & J. Roderick McCrorie, 2015. "Testing for Mild Explosivity and Bubbles in LME Non-Ferrous Metals Prices," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(5), pages 763-782, September.
    65. Demir, Ender & Gozgor, Giray & Sari, Emre, 2018. "Dynamics of the Turkish paintings market: A comprehensive empirical study," Emerging Markets Review, Elsevier, vol. 36(C), pages 180-194.
    66. Akcora, Begum & Kandemir Kocaaslan, Ozge, 2023. "Price bubbles in the European natural gas market between 2011 and 2020," Resources Policy, Elsevier, vol. 80(C).
    67. Esteve, Vicente & Prats, María A., 2023. "Testing explosive bubbles with time-varying volatility: the case of Spanish public debt," LSE Research Online Documents on Economics 116980, London School of Economics and Political Science, LSE Library.

  15. Sam Astill & David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2015. "Robust and Powerful Tests for Nonlinear Deterministic Components," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(6), pages 780-799, December.

    Cited by:

    1. Winkelried, Diego, 2015. "Unit Roots, Flexible Trends and the Prebisch-Singer Hypothesis," Working Papers 2015-007, Banco Central de Reserva del Perú.
    2. Enders Walter & Jones Paul, 2016. "Grain prices, oil prices, and multiple smooth breaks in a VAR," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(4), pages 399-419, September.
    3. Atanu Ghoshray & Madhavi Pundit, 2021. "Economic growth in China and its impact on international commodity prices," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2776-2789, April.
    4. Pierre Perron & Mototsugu Shintaniz & Tomoyoshi Yabu, 2020. "Trigonometric Trend Regressions of Unknown Frequencies with Stationary or Integrated Noise," Boston University - Department of Economics - Working Papers Series WP2020-012, Boston University - Department of Economics.
    5. Takamitsu Kurita & Mototsugu Shintani, 2023. "Johansen Test with Fourier-Type Smooth Nonlinear Trends in Cointegrating Relations," CIRJE F-Series CIRJE-F-1216, CIRJE, Faculty of Economics, University of Tokyo.
    6. Pierre Perron & Mototsugu Shintani & Tomoyoshi Yabu, 2015. "Testing for Flexible Nonlinear Trends with an Integrated or Stationary Noise Component," Vanderbilt University Department of Economics Working Papers 15-00001, Vanderbilt University Department of Economics.

  16. David I. Harvey & Stephen J. Leybourne & Robert Sollis, 2015. "Recursive Right-Tailed Unit Root Tests for an Explosive Asset Price Bubble," Journal of Financial Econometrics, Oxford University Press, vol. 13(1), pages 166-187.

    Cited by:

    1. Wang, Shaoping & Feng, Hao & Gao, Da, 2023. "Testing for short explosive bubbles: A case of Brent oil futures price," Finance Research Letters, Elsevier, vol. 52(C).
    2. Sinelnikova-Muryleva, Elena & Skrobotov, Anton, 2017. "Testing time series for the bubbles (with application to Russian data)," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 46, pages 90-103.
    3. Figuerola-Ferretti, Isabel & McCrorie, J. Roderick, 2016. "The shine of precious metals around the global financial crisis," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 717-738.
    4. Zhao, Zhao & Wen, Huwei & Li, Ke, 2021. "Identifying bubbles and the contagion effect between oil and stock markets: New evidence from China," Economic Modelling, Elsevier, vol. 94(C), pages 780-788.
    5. Benjamin Beckers, 2015. "The Real-Time Predictive Content of Asset Price Bubbles for Macro Forecasts," Discussion Papers of DIW Berlin 1496, DIW Berlin, German Institute for Economic Research.
    6. Escobari, Diego & Garcia, Sergio & Mellado, Cristhian, 2017. "Identifying bubbles in Latin American equity markets: Phillips-Perron-based tests and linkages," Emerging Markets Review, Elsevier, vol. 33(C), pages 90-101.
    7. Akanksha Jalan & Roman Matkovskyy & Valerio Potì, 2022. "Shall the winning last? A study of recent bubbles and persistence," Post-Print hal-03603161, HAL.
    8. Pang, Tianxiao & Du, Lingjie & Chong, Terence Tai-Leung, 2021. "Estimating multiple breaks in nonstationary autoregressive models," Journal of Econometrics, Elsevier, vol. 221(1), pages 277-311.
    9. Moreira, Afonso M. & Martins, Luis F., 2020. "A new mechanism for anticipating price exuberance," International Review of Economics & Finance, Elsevier, vol. 65(C), pages 199-221.
    10. Eiji Kurozumi, 2021. "Asymptotic Behavior of Delay Times of Bubble Monitoring Tests," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(3), pages 314-337, May.
    11. Skrobotov Anton, 2023. "Testing for explosive bubbles: a review," Dependence Modeling, De Gruyter, vol. 11(1), pages 1-26, January.
    12. Sam Astill & David I Harvey & Stephen J Leybourne & A M Robert Taylor & Yang Zu, 2023. "CUSUM-Based Monitoring for Explosive Episodes in Financial Data in the Presence of Time-Varying Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 21(1), pages 187-227.
    13. Alexakis, Christos & Bagnarosa, Guillaume & Dowling, Michael, 2017. "Do cointegrated commodities bubble together? the case of hog, corn, and soybean," Finance Research Letters, Elsevier, vol. 23(C), pages 96-102.
    14. Marco R. Barassi & Nicola Spagnolo & Yuqian Zhao, 2018. "Fractional Integration Versus Structural Change: Testing the Convergence of $$\hbox {CO}_{2}$$ CO 2 Emissions," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 71(4), pages 923-968, December.
    15. KIRKPINAR, Aysegul & ERER, Elif & ERER, Deniz, 2019. "Is There A Rational Bubble In Bist 100 And Sector Indices?," Studii Financiare (Financial Studies), Centre of Financial and Monetary Research "Victor Slavescu", vol. 23(3), pages 21-33, September.
    16. Christopher Lynch & Benjamin Mestel, 2019. "Change-Point Analysis Of Asset Price Bubbles With Power-Law Hazard Function," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 22(07), pages 1-24, November.
    17. Nishi, Mikihito & 西, 幹仁 & Kurozumi, Eiji & 黒住, 英司, 2022. "Stochastic Local and Moderate Departures from a Unit Root and Its Application to Unit Root Testing," Discussion Papers 2022-02, Graduate School of Economics, Hitotsubashi University.

  17. Neil Kellard & Denise Osborn & Jerry Coakley & Giuseppe Cavaliere & David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2015. "Testing for Unit Roots Under Multiple Possible Trend Breaks and Non-Stationary Volatility Using Bootstrap Minimum Dickey–Fuller Statistics," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(5), pages 603-629, September.

    Cited by:

    1. Rickard Sandberg, 2018. "Unit Root Testing in Multiple Smooth Break Models with Nonlinear Dynamics," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 942-952, November.
    2. Skrobotov, Anton, 2020. "Survey on structural breaks and unit root tests," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 58, pages 96-141.
    3. Mustafa Akpinar & Nejat Yumusak, 2016. "Year Ahead Demand Forecast of City Natural Gas Using Seasonal Time Series Methods," Energies, MDPI, vol. 9(9), pages 1-17, September.

  18. Harvey, David I. & Leybourne, Stephen J., 2015. "Confidence sets for the date of a break in level and trend when the order of integration is unknown," Journal of Econometrics, Elsevier, vol. 184(2), pages 262-279.
    See citations under working paper version above.
  19. Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2014. "On infimum Dickey–Fuller unit root tests allowing for a trend break under the null," Computational Statistics & Data Analysis, Elsevier, vol. 78(C), pages 235-242.

    Cited by:

    1. Xue-hua Zhao & Xu Chen, 2015. "Auto Regressive and Ensemble Empirical Mode Decomposition Hybrid Model for Annual Runoff Forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(8), pages 2913-2926, June.
    2. Polbin, Andrey & Fokin, Nikita, 2020. "Modeling the dynamics of import in the Russian Federation using the error correction model," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 59, pages 88-112.

  20. Harvey, David I. & Leybourne, Stephen J., 2014. "Asymptotic behaviour of tests for a unit root against an explosive alternative," Economics Letters, Elsevier, vol. 122(1), pages 64-68.

    Cited by:

    1. Patrick Marsh, 2019. "Properties of the power envelope for tests against both stationary and explosive alternatives: the effect of trends," Discussion Papers 19/03, University of Nottingham, Granger Centre for Time Series Econometrics.
    2. Sinelnikova-Muryleva, Elena & Skrobotov, Anton, 2017. "Testing time series for the bubbles (with application to Russian data)," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 46, pages 90-103.
    3. Skrobotov Anton, 2023. "Testing for explosive bubbles: a review," Dependence Modeling, De Gruyter, vol. 11(1), pages 1-26, January.
    4. Anton Skrobotov, 2013. "Double Unit Roots Testing, GLS-detrending and Uncertainty over the Initial Conditions," Working Papers 0083, Gaidar Institute for Economic Policy, revised 2013.
    5. Kruse, Robinson & Kaufmann, Hendrik & Wegener, Christoph, 2018. "Bias-corrected estimation for speculative bubbles in stock prices," Economic Modelling, Elsevier, vol. 73(C), pages 354-364.

  21. David I. Harvey & Stephen J. Leybourne, 2014. "Break Date Estimation for Models with Deterministic Structural Change," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(5), pages 623-642, October.
    See citations under working paper version above.
  22. David I. Harvey & Stephen J. Leybourne & A.M. Robert Taylor, 2014. "Unit Root Testing under a Local Break in Trend using Partial Information on the Break Date," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(1), pages 93-111, February.

    Cited by:

    1. Anton Skrobotov, 2016. "On Trend Breaks and Initial Condition in Unit Root Testing," Working Papers 0097, Gaidar Institute for Economic Policy, revised 2016.
    2. Skrobotov, Anton (Скроботов, Антон), 2015. "About Trend, the Shift and the Initial Value in Testing of the Hypothesis of a Unit Root [О Тренде, Сдвиге И Начальном Значении В Тестировании Гипотезы О Наличии Единичного Корня]," Published Papers mak6, Russian Presidential Academy of National Economy and Public Administration.
    3. K. Moses Tule & O. Taiwo Ajilore, 2016. "On the stability of the money multiplier in Nigeria: Co-integration analyses with regime shifts in banking system liquidity," Cogent Economics & Finance, Taylor & Francis Journals, vol. 4(1), pages 1187780-118, December.
    4. Skrobotov, Anton, 2020. "Survey on structural breaks and unit root tests," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 58, pages 96-141.

  23. Sam Astill & David I. Harvey & A. M. Robert Taylor, 2013. "A bootstrap test for additive outliers in non-stationary time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(4), pages 454-465, July.

    Cited by:

    1. V. A. Reisen & C. Lévy-Leduc & M. Bourguignon & H. Boistard, 2017. "Robust Dickey–Fuller tests based on ranks for time series with additive outliers," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 80(1), pages 115-131, January.
    2. Alanya-Beltran, Willy, 2022. "Unit roots in lower-bounded series with outliers," Economic Modelling, Elsevier, vol. 115(C).

  24. Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2013. "Testing for unit roots in the possible presence of multiple trend breaks using minimum Dickey–Fuller statistics," Journal of Econometrics, Elsevier, vol. 177(2), pages 265-284.

    Cited by:

    1. Anton Skrobotov, 2013. "Local Structural Trend Break in Stationarity Testing," Working Papers 0074, Gaidar Institute for Economic Policy, revised 2013.
    2. Liddle, Brantley & Messinis, George, 2014. "Revisiting carbon Kuznets curves with endogenous breaks modeling: Evidence of decoupling and saturation (but few inverted-Us) for individual OECD countries," MPRA Paper 59566, University Library of Munich, Germany.
    3. Charles Yuji Horioka & Akiko Terada-Hagiwara, 2016. "The Impact of Pre-marital Sex Ratios on Household Saving in Two Asian Countries: The Competitive Saving Motive Revisited," NBER Working Papers 22412, National Bureau of Economic Research, Inc.
    4. Parewangi, Andi M. Alfian & Iskandar, Azwar, 2020. "The Nexus of Islamic Finance and Poverty," Hitotsubashi Journal of Economics, Hitotsubashi University, vol. 61(2), pages 111-139, December.
    5. Rickard Sandberg, 2018. "Unit Root Testing in Multiple Smooth Break Models with Nonlinear Dynamics," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 942-952, November.
    6. Paraskevi Salamaliki, 2015. "Economic Policy Uncertainty and Economic Activity: A Focus on Infrequent Structural Shifts," Working Paper Series of the Department of Economics, University of Konstanz 2015-08, Department of Economics, University of Konstanz.
    7. Horioka, Charles Yuji & Terada-Hagiwara, Akiko, 2016. "The Impact of Sex Ratios before Marriage on Household Saving in Two Asian Countries: The Competitive Saving Motive Revisited," ADB Economics Working Paper Series 494, Asian Development Bank.
    8. Esteve García, Vicente & Navarro Ibáñez, Manuel & Prats Albentosa, María Asuncíon, 2017. "The present value model of U.S. stock prices revisited: Long-run evidence with structural breaks, 1871-2012," Economics Discussion Papers 2017-93, Kiel Institute for the World Economy (IfW Kiel).
    9. Harvey, David I. & Leybourne, Stephen J., 2015. "Confidence sets for the date of a break in level and trend when the order of integration is unknown," Journal of Econometrics, Elsevier, vol. 184(2), pages 262-279.
    10. Vicente Esteve & Cecilio Tamarit, 2018. "Public debt and economic growth in Spain, 1851–2013," Cliometrica, Springer;Cliometric Society (Association Francaise de Cliométrie), vol. 12(2), pages 219-249, May.
    11. Russo, Emanuele & Foster-McGregor, Neil & Verspagen, Bart, 2019. "Characterizing growth instability: new evidence on unit roots and structural breaks in long run time series," MERIT Working Papers 2019-026, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    12. Bashir Olayinka Kolawole, 2021. "Fiscal Stability and Macroeconomic Environment in Nigeria: A Further Assessment," Theory Methodology Practice (TMP), Faculty of Economics, University of Miskolc, vol. 17(02), pages 53-66.
    13. Ioanna Konstantakopoulou, 2017. "The aggregate exports-GDP relation under the prism of infrequent trend breaks and multi-horizon causality," International Economics and Economic Policy, Springer, vol. 14(4), pages 661-689, October.
    14. Manveer Kaur Mangat & Erhard Reschenhofer, 2020. "Frequency-Domain Evidence for Climate Change," Econometrics, MDPI, vol. 8(3), pages 1-15, July.
    15. Mariam Camarero & Alejandro Muñoz & Cecilio Tamarit, 2021. "50 Years of Capital Mobility in the Eurozone: Breaking the Feldstein-Horioka Puzzle," Open Economies Review, Springer, vol. 32(5), pages 867-905, November.
    16. Harvey, David I. & Leybourne, Stephen J., 2016. "Improving the length of confidence sets for the date of a break in level and trend when the order of integration is unknown," Economics Letters, Elsevier, vol. 145(C), pages 239-245.
    17. Marina Faďoš & Mária Bohdalová, 2019. "Unemployment gender inequality: evidence from the 27 European Union countries," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 9(3), pages 349-371, September.
    18. Skrobotov, Anton, 2020. "Survey on structural breaks and unit root tests," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 58, pages 96-141.
    19. Esteve, Vicente & Navarro-Ibáñez, Manuel & Prats, María A., 2020. "Stock prices, dividends, and structural changes in the long-term: The case of U.S," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    20. Yannick Hoga, 2022. "Quantifying the data-dredging bias in structural break tests," Statistical Papers, Springer, vol. 63(1), pages 143-155, February.
    21. Ana Lourdes Morones Carrillo, 2016. "Crecimiento económico en México: restricción por la balanza de pagos," Ensayos Revista de Economia, Universidad Autonoma de Nuevo Leon, Facultad de Economia, vol. 0(1), pages 39-58, May.
    22. Martha Ofelia Lobo Rodriguez & Carlos Alberto Flores Sanchez & Duniesky Feito Madrigal & Jorge Quiroz Felix, 2016. "An Econometric Analysis Of The Demand For Tourism In Mexico, Un Analisis Econometrico De La Demanda De Turismo En Mexico," Revista Internacional Administracion & Finanzas, The Institute for Business and Finance Research, vol. 9(3), pages 61-70.
    23. Atanu Ghoshray & Mercedes Monfort & Javier Ordóñez, 2020. "Economic integration and the distribution of income in Europe: A between country analysis," Working Papers 2020/11, Economics Department, Universitat Jaume I, Castellón (Spain).
    24. Lajos Horváth & Gregory Rice, 2014. "Extensions of some classical methods in change point analysis," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(2), pages 219-255, June.
    25. Liddle, Brantley & Messinis, George, 2014. "Revisiting sulfur Kuznets curves with endogenous breaks modeling: Substantial evidence of inverted-Us/Vs for individual OECD countries," MPRA Paper 59565, University Library of Munich, Germany.
    26. De Vita, Glauco & Trachanas, Emmanouil, 2016. "‘Nonlinear causality between crude oil price and exchange rate: A comparative study of China and India’ — A failed replication (negative Type 1 and Type 2)," Energy Economics, Elsevier, vol. 56(C), pages 150-160.
    27. Emanuele Russo & Neil Foster-McGregor, 2022. "Characterizing growth instability: new evidence on unit roots and structural breaks in countries’ long run trajectories," Journal of Evolutionary Economics, Springer, vol. 32(2), pages 713-756, April.
    28. Ricardo Quineche & Gabriel Rodríguez, 2017. "Selecting the Lag Length for the M GLS Unit Root Tests with Structural Change: A Warning Note for Practitioners Based on Simulations," Econometrics, MDPI, vol. 5(2), pages 1-10, April.
    29. Martin B. Schmidt, 2021. "On the evolution of athlete anthropometric measurements: racial integration, expansion, and steroids," Empirical Economics, Springer, vol. 61(6), pages 3419-3443, December.
    30. Neil Kellard & Denise Osborn & Jerry Coakley & Giuseppe Cavaliere & David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2015. "Testing for Unit Roots Under Multiple Possible Trend Breaks and Non-Stationary Volatility Using Bootstrap Minimum Dickey–Fuller Statistics," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(5), pages 603-629, September.
    31. Atanu Ghoshray & Issam Malki & Javier Ordóñez, 2022. "On the long-run dynamics of income and wealth inequality," Empirical Economics, Springer, vol. 62(2), pages 375-408, February.
    32. Meligkotsidou, Loukia & Tzavalis, Elias & Vrontos, Ioannis, 2017. "On Bayesian analysis and unit root testing for autoregressive models in the presence of multiple structural breaks," Econometrics and Statistics, Elsevier, vol. 4(C), pages 70-90.
    33. Eléazar Zerbo, 2015. "What determines the long-run growth in Sub-Saharan Africa? Exploring the role of energy, trade openness and financial development in six countries," Working Papers hal-01238524, HAL.

  25. Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2012. "Unit root testing under a local break in trend," Journal of Econometrics, Elsevier, vol. 167(1), pages 140-167.
    See citations under working paper version above.
  26. Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2012. "Testing for unit roots in the presence of uncertainty over both the trend and initial condition," Journal of Econometrics, Elsevier, vol. 169(2), pages 188-195.
    See citations under working paper version above.
  27. Harvey, David I. & Leybourne, Stephen J., 2012. "An infimum coefficient unit root test allowing for an unknown break in trend," Economics Letters, Elsevier, vol. 117(1), pages 298-302.

    Cited by:

    1. Skrobotov, Anton (Скроботов, Антон), 2015. "About Trend, the Shift and the Initial Value in Testing of the Hypothesis of a Unit Root [О Тренде, Сдвиге И Начальном Значении В Тестировании Гипотезы О Наличии Единичного Корня]," Published Papers mak6, Russian Presidential Academy of National Economy and Public Administration.
    2. David I. Harvey & Stephen J. Leybourne & A.M. Robert Taylor, 2014. "Unit Root Testing under a Local Break in Trend using Partial Information on the Break Date," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(1), pages 93-111, February.
    3. Skrobotov, Anton, 2020. "Survey on structural breaks and unit root tests," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 58, pages 96-141.

  28. Clements, Michael P. & Harvey, David I., 2011. "Combining probability forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 208-223.

    Cited by:

    1. Shaun P Vahey & Elizabeth C Wakerly, 2013. "Moving towards probability forecasting," BIS Papers chapters, in: Bank for International Settlements (ed.), Globalisation and inflation dynamics in Asia and the Pacific, volume 70, pages 3-8, Bank for International Settlements.
    2. Pauwels, Laurent & Vasnev, Andrey, 2013. "Forecast combination for U.S. recessions with real-time data," Working Papers 2013-05, University of Sydney Business School, Discipline of Business Analytics.
    3. Ruben Loaiza-Maya & Gael M. Martin & David T. Frazier & Worapree Maneesoonthorn & Andres Ramirez Hassan, 2020. "Optimal probabilistic forecasts: When do they work?," Monash Econometrics and Business Statistics Working Papers 33/20, Monash University, Department of Econometrics and Business Statistics.
    4. Lyon, Aidan & Wintle, Bonnie C. & Burgman, Mark, 2015. "Collective wisdom: Methods of confidence interval aggregation," Journal of Business Research, Elsevier, vol. 68(8), pages 1759-1767.
    5. Bentes, Sonia R. & Menezes, Rui, 2013. "On the predictability of realized volatility using feasible GLS," Journal of Asian Economics, Elsevier, vol. 28(C), pages 58-66.
    6. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2012. "Combination schemes for turning point predictions," Working Paper 2012/04, Norges Bank.
    7. Qian, Wei & Rolling, Craig A. & Cheng, Gang & Yang, Yuhong, 2022. "Combining forecasts for universally optimal performance," International Journal of Forecasting, Elsevier, vol. 38(1), pages 193-208.
    8. Ruben Loaiza‐Maya & Gael M. Martin & David T. Frazier, 2021. "Focused Bayesian prediction," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 517-543, August.
    9. Pablo Pincheira, 2012. "Are Forecast Combinations Efficient?," Working Papers Central Bank of Chile 661, Central Bank of Chile.
    10. Cristina Conflitti & Christine De Mol & Domenico Giannone, 2012. "Optimal Combination of Survey Forecasts," Working Papers ECARES ECARES 2012-023, ULB -- Universite Libre de Bruxelles.
    11. Stephen Hora & Erim Kardeş, 2015. "Calibration, sharpness and the weighting of experts in a linear opinion pool," Annals of Operations Research, Springer, vol. 229(1), pages 429-450, June.
    12. Fabian Krüger & Ingmar Nolte, 2011. "Disagreement, Uncertainty and the True Predictive Density," Working Paper Series of the Department of Economics, University of Konstanz 2011-43, Department of Economics, University of Konstanz.
    13. Pirschel, Inske, 2016. "Forecasting euro area recessions in real-time," Kiel Working Papers 2020, Kiel Institute for the World Economy (IfW Kiel).
    14. Rodrigues, Bruno Dore & Stevenson, Maxwell J., 2013. "Takeover prediction using forecast combinations," International Journal of Forecasting, Elsevier, vol. 29(4), pages 628-641.
    15. Kajal Lahiri & Huaming Peng & Yongchen Zhao, 2013. "Testing the Value of Probability Forecasts for Calibrated Combining," Discussion Papers 13-02, University at Albany, SUNY, Department of Economics.
    16. Frederik Kunze, 2020. "Predicting exchange rates in Asia: New insights on the accuracy of survey forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 313-333, March.
    17. Svetlana Makarova, 2014. "Risk and Uncertainty: Macroeconomic Perspective," UCL SSEES Economics and Business working paper series 129, UCL School of Slavonic and East European Studies (SSEES).
    18. Laurent L. Pauwels & Andrey L. Vasnev, 2017. "Forecast combination for discrete choice models: predicting FOMC monetary policy decisions," Empirical Economics, Springer, vol. 52(1), pages 229-254, February.
    19. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    20. Pablo Pincheira-Brown & Andrea Bentancor & Nicolás Hardy, 2023. "An Inconvenient Truth about Forecast Combinations," Mathematics, MDPI, vol. 11(18), pages 1-24, September.
    21. Pirschel, Inske, 2015. "Forecasting Euro Area Recessions in real-time with a mixed-frequency Bayesian VAR," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113031, Verein für Socialpolitik / German Economic Association.
    22. Bermejo Mancera, Miguel Ángel & Peña, Daniel & Sánchez, Ismael, 2011. "Densidad de predicción basada en momentos condicionados y máxima entropía : aplicación a la predicción de potencia eólica," DES - Working Papers. Statistics and Econometrics. WS ws111813, Universidad Carlos III de Madrid. Departamento de Estadística.
    23. Trapero, Juan R. & Cardós, Manuel & Kourentzes, Nikolaos, 2019. "Quantile forecast optimal combination to enhance safety stock estimation," International Journal of Forecasting, Elsevier, vol. 35(1), pages 239-250.
    24. Lee, Seohyun, 2017. "Three essays on uncertainty: real and financial effects of uncertainty shocks," MPRA Paper 83617, University Library of Munich, Germany.
    25. Michael P. Clements, 2020. "Are Some Forecasters’ Probability Assessments of Macro Variables Better Than Those of Others?," Econometrics, MDPI, vol. 8(2), pages 1-16, May.
    26. Giovanni De Luca & Alfonso Carfora, 2014. "Predicting U.S. recessions through a combination of probability forecasts," Empirical Economics, Springer, vol. 46(1), pages 127-144, February.

  29. Ahmad, A.H. & Harvey, David I. & Pentecost, Eric J., 2011. "Exchange rate regime verification: An alternative method of testing for regime changes," Economics Letters, Elsevier, vol. 113(1), pages 96-98, October.

    Cited by:

    1. Ahmad Hassan Ahmad & Eric J. Pentecost, 2020. "Testing the ‘Fear of Floating’ Hypothesis: A Statistical Analysis for Eight African Countries," Open Economies Review, Springer, vol. 31(2), pages 407-430, April.
    2. Ahmad, A.H. & Pentecost, Eric J., 2012. "Identifying aggregate supply and demand shocks in small open economies: Empirical evidence from African countries," International Review of Economics & Finance, Elsevier, vol. 21(1), pages 272-291.
    3. Muhammad Ali Nasir & Muhammad Shahbaz & Trinh Thi Mai & Moade Shubita, 2021. "Development of Vietnamese stock market: Influence of domestic macroeconomic environment and regional markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1435-1458, January.
    4. Ahmad Ahmad & Olalekan Aworinde, 2015. "Structural breaks and twin deficits hypothesis in African countries," Economic Change and Restructuring, Springer, vol. 48(1), pages 1-35, February.
    5. A H Ahmad & Eric J Pentecost, 2012. "The Current Account and Real Exchange Rate Dynamics in African Countries," Department of Economics Working Papers 4/12, University of Bath, Department of Economics.
    6. Ahmad, Ahmad Hassan & Pentecost, Eric J. & Stack, Marie M., 2023. "Foreign aid, debt interest repayments and Dutch disease effects in a real exchange rate model for African countries," Economic Modelling, Elsevier, vol. 126(C).
    7. Mohamed Bouabidi, 2022. "The Tunisian exchange rate regime: Is it really floating?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4684-4704, October.

  30. Cavaliere, Giuseppe & Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2011. "Testing For Unit Roots In The Presence Of A Possible Break In Trend And Nonstationary Volatility," Econometric Theory, Cambridge University Press, vol. 27(5), pages 957-991, October.
    See citations under working paper version above.
  31. David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2011. "Testing for Unit Roots and the Impact of Quadratic Trends, with an Application to Relative Primary Commodity Prices," Econometric Reviews, Taylor & Francis Journals, vol. 30(5), pages 514-547, October.
    See citations under working paper version above.
  32. Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2010. "Robust methods for detecting multiple level breaks in autocorrelated time series," Journal of Econometrics, Elsevier, vol. 157(2), pages 342-358, August.
    See citations under working paper version above.
  33. David I. Harvey & Stephen J. Leybourne & Lisa Xiao, 2010. "Testing for nonlinear deterministic components when the order of integration is unknown," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(5), pages 379-391, September.

    Cited by:

    1. Pierre Perron & Mototsugu Shintaniz & Tomoyoshi Yabu, 2020. "Trigonometric Trend Regressions of Unknown Frequencies with Stationary or Integrated Noise," Boston University - Department of Economics - Working Papers Series WP2020-012, Boston University - Department of Economics.
    2. Christensen, Bent Jesper & Kruse, Robinson & Sibbertsen, Philipp, 2013. "A unified framework for testing in the linear regression model under unknown order of fractional integration," Hannover Economic Papers (HEP) dp-519, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    3. Takamitsu Kurita & Mototsugu Shintani, 2023. "Johansen Test with Fourier-Type Smooth Nonlinear Trends in Cointegrating Relations," CIRJE F-Series CIRJE-F-1216, CIRJE, Faculty of Economics, University of Tokyo.
    4. Pierre Perron & Mototsugu Shintani & Tomoyoshi Yabu, 2015. "Testing for Flexible Nonlinear Trends with an Integrated or Stationary Noise Component," Vanderbilt University Department of Economics Working Papers 15-00001, Vanderbilt University Department of Economics.

  34. Harris, David & Harvey, David I. & Leybourne, Stephen J. & Sakkas, Nikolaos D., 2010. "Local Asymptotic Power Of The Im-Pesaran-Shin Panel Unit Root Test And The Impact Of Initial Observations," Econometric Theory, Cambridge University Press, vol. 26(1), pages 311-324, February.
    See citations under working paper version above.
  35. David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2010. "The impact of the initial condition on robust tests for a linear trend," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(4), pages 292-302, July.
    See citations under working paper version above.
  36. Michael P. Clements & David I. Harvey, 2010. "Forecast encompassing tests and probability forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(6), pages 1028-1062.
    See citations under working paper version above.
  37. David I. Harvey & Neil M. Kellard & Jakob B. Madsen & Mark E. Wohar, 2010. "The Prebisch-Singer Hypothesis: Four Centuries of Evidence," The Review of Economics and Statistics, MIT Press, vol. 92(2), pages 367-377, May.

    Cited by:

    1. Jesús Otero & Ana María Iregui, 2011. "The Long-Run Behaviour of the Terms of Trade between Primary Commodities and Manufactures: A Panel Data Approach," WIDER Working Paper Series wp-2011-071, World Institute for Development Economic Research (UNU-WIDER).
    2. Rabah Arezki & Daniel Lederman & Hongyan Zhao, 2011. "The Relative Volatility of Commodity Prices: A Reappraisal," Working Papers 660, Economic Research Forum, revised 12 Jan 2011.
    3. Enders, Walter & Holt, Matthew T., 2011. "Breaks, bubbles, booms, and busts: the evolution of primary commodity price fundamentals," MPRA Paper 31461, University Library of Munich, Germany.
    4. Chiara Casoli & Riccardo (Jack) Lucchetti, 2022. "Permanent-Transitory decomposition of cointegrated time series via dynamic factor models, with an application to commodity prices [Commodity-price comovement and global economic activity]," The Econometrics Journal, Royal Economic Society, vol. 25(2), pages 494-514.
    5. Winkelried, Diego, 2015. "Unit Roots, Flexible Trends and the Prebisch-Singer Hypothesis," Working Papers 2015-007, Banco Central de Reserva del Perú.
    6. József Popp & Judit Oláh & Mária Farkas Fekete & Zoltán Lakner & Domicián Máté, 2018. "The Relationship Between Prices of Various Metals, Oil and Scarcity," Energies, MDPI, vol. 11(9), pages 1-19, September.
    7. Caselli, Francesco & Tesei, Andrea, 2016. "Resource windfalls, political regimes and political stability," LSE Research Online Documents on Economics 64587, London School of Economics and Political Science, LSE Library.
    8. Trofimov, Ivan D., 2018. "Income terms of trade and economic convergence: Evidence from Latin America," MPRA Paper 87598, University Library of Munich, Germany.
    9. Ghoshray Atanu & Kejriwal Mohitosh & Wohar Mark, 2014. "Breaks, trends and unit roots in commodity prices: a robust investigation," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(1), pages 23-40, February.
    10. Carpantier, Jean-François, 2021. "Anything but gold - The golden constant revisited," Journal of Commodity Markets, Elsevier, vol. 24(C).
    11. Pierre JACQUET & Alexis ATLANI & Marwan LISSER, 2017. "Policy responses to terms of trade shocks," Working Papers P205, FERDI.
    12. Giovanni Federico & Antonio Tena‐Junguito, 2017. "Lewis revisited: tropical polities competing on the world market, 1830–1938," Economic History Review, Economic History Society, vol. 70(4), pages 1244-1267, November.
    13. Lin, Justin Yifu & Rosenblatt, David, 2012. "Shifting patterns of economic growth and rethinking development," Policy Research Working Paper Series 6040, The World Bank.
    14. Ourens, Guzmán, 2017. "Uneven growth in the extensive margin: explaining the lag of agricultural economies," CEPREMAP Working Papers (Docweb) 1704, CEPREMAP.
    15. Winkelried, Diego, 2021. "Unit roots in real primary commodity prices? A meta-analysis of the Grilli and Yang data set," Journal of Commodity Markets, Elsevier, vol. 23(C).
    16. Ghoshray, Atanu, 2019. "Do international primary commodity prices exhibit asymmetric adjustment?," Journal of Commodity Markets, Elsevier, vol. 14(C), pages 40-50.
    17. Winkelried, Diego, 2016. "Piecewise linear trends and cycles in primary commodity prices," Journal of International Money and Finance, Elsevier, vol. 64(C), pages 196-213.
    18. Md. Rabiul Islam, 2010. "Quality-adjusted Human Capital and Productivity Growth," Monash Economics Working Papers 48-10, Monash University, Department of Economics.
    19. Kim, Hyeongwoo & Zhang, Yunxiao, 2020. "Investigating properties of commodity price responses to real and nominal shocks," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    20. Joseph P. Byrne & Giorgio Fazio & Norbert Fiess, 2010. "Primary commodity prices: co-movements, common factors and fundamentals," Working Papers 2010_27, Business School - Economics, University of Glasgow.
    21. Cesar A. Hidalgo, 2022. "The Policy Implications of Economic Complexity," Papers in Evolutionary Economic Geography (PEEG) 2230, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Nov 2022.
    22. Juncal Cunado & Luis A. Gil-Alana & Rangan Gupta, 2018. "Persistence in Trends and Cycles of Gold and Silver Prices: Evidence from Historical Data," Working Papers 201816, University of Pretoria, Department of Economics.
    23. Makhlouf, Yousef & Kellard, Neil M. & Vinogradov, Dmitri, 2017. "Child mortality, commodity price volatility and the resource curse," Social Science & Medicine, Elsevier, vol. 178(C), pages 144-156.
    24. Jean-François Carpantier, 2019. "Commodity Prices In Empirical Research," LIDAM Discussion Papers IRES 2020021, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
    25. Frederick van der Ploeg, 2011. "Natural Resources: Curse or Blessing?," Journal of Economic Literature, American Economic Association, vol. 49(2), pages 366-420, June.
    26. Diego Daruich & William Easterly & Ariell Reshef, 2019. "The surprising instability of export specializations," PSE-Ecole d'économie de Paris (Postprint) halshs-02875089, HAL.
    27. Caselli, Francesco & Tesei, Andrea, 2011. "Resource windfalls, political regimes, and political stability," LSE Research Online Documents on Economics 121753, London School of Economics and Political Science, LSE Library.
    28. Aguirre, Alvaro, 2019. "Rebellions, Technical Change, and the Early Development of Political Institutions in Latin America," Journal of Comparative Economics, Elsevier, vol. 47(1), pages 65-89.
    29. Ranjan Aneja & Arjun, 2022. "Impact of Terms of Trade on GDP in the Context of Prebisch–Singer Theorem: Evidence from Egypt and Guinea," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 34(5), pages 2561-2575, October.
    30. Yves Jégourel, 2018. "Tendances et cyclicité du prix des matières premières (partie 2) : le super-cycle des matières premières en question," Policy briefs 1824, Policy Center for the New South.
    31. Tony Addison & Atanu Ghoshray & Michalis P. Stamatogiannis, 2016. "Agricultural Commodity Price Shocks and Their Effect on Growth in Sub-Saharan Africa," Journal of Agricultural Economics, Wiley Blackwell, vol. 67(1), pages 47-61, February.
    32. Jeffrey A. Frankel, 2011. "A Solution to Fiscal Procyclicality: The Structural Budget Institutions Pioneered by Chile," NBER Working Papers 16945, National Bureau of Economic Research, Inc.
    33. Oglend, Atle & Selland Kleppe, Tore, 2016. "How regular are directional movements in commodity and asset prices? A Wald test," Journal of Empirical Finance, Elsevier, vol. 38(PA), pages 290-306.
    34. Arezki,Rabah & van der Ploeg,Frederick & Toscani,Frederik, 2018. "The shifting natural wealth of nations : the role of market orientation," Policy Research Working Paper Series 8520, The World Bank.
    35. Atanu Ghoshray & Madhavi Pundit, 2021. "Economic growth in China and its impact on international commodity prices," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2776-2789, April.
    36. Filippo Bontadini, 2019. "Trade Specialisation and Performance in Global Value Chains," SPRU Working Paper Series 2019-10, SPRU - Science Policy Research Unit, University of Sussex Business School.
    37. Ipsen, Leonhard & Aminian, Armin & Schulz-Gebhard, Jan, 2023. "Stress-testing inflation exposure: Systemically significant prices and asymmetric shock propagation in the EU28," BERG Working Paper Series 188, Bamberg University, Bamberg Economic Research Group.
    38. Arezki, Rabah & Hadri, Kaddour & Loungani, Prakash & Rao, Yao, 2014. "Testing the Prebisch–Singer hypothesis since 1650: Evidence from panel techniques that allow for multiple breaks," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 208-223.
    39. V. V. Chari & Lawrence J. Christiano, 2014. "The Optimal Extraction of Exhaustible Resources," Economic Policy Paper 14-5, Federal Reserve Bank of Minneapolis.
    40. Mohsen Bahmani-Oskooee & Tsangyao Chang & Zahra (Mila) Elmi & Omid Ranjbar, 2018. "Re-testing Prebisch–Singer hypothesis: new evidence using Fourier quantile unit root test," Applied Economics, Taylor & Francis Journals, vol. 50(4), pages 441-454, January.
    41. Débora Machado Nunes, 2024. "Imperialism in the Financial Capital Era: Forgotten Contributions from Marxist Dependency Theory," Review of Radical Political Economics, Union for Radical Political Economics, vol. 56(1), pages 5-22, March.
    42. David S. Jacks, 2013. "From Boom to Bust: A Typology of Real Commodity Prices in the Long Run," NBER Working Papers 18874, National Bureau of Economic Research, Inc.
    43. Konstantin M. Wacker, 2011. "Do multinationals beat down developing countries' export prices? The impact of FDI on net barter terms of trade," Ibero America Institute for Econ. Research (IAI) Discussion Papers 211, Ibero-America Institute for Economic Research.
    44. Cécile Couharde & Vincent Geronimi & Armand Taranco, 2012. "Les hausses récentes des cours des matières premières traduisent-elles l'entrée dans un régime de prix plus élevés?," Post-Print hal-01385858, HAL.
    45. Carmignani, Fabrizio, 2013. "Development outcomes, resource abundance, and the transmission through inequality," Resource and Energy Economics, Elsevier, vol. 35(3), pages 412-428.
    46. Thomas H.W. Ziesemer, 2014. "Country terms of trade: trends, unit roots, over-differencing, endogeneity, time dummies, and heterogeneity," International Review of Applied Economics, Taylor & Francis Journals, vol. 28(6), pages 767-796, September.
    47. Yifei Cai & Tolga Omay, 2022. "Using Double Frequency in Fourier Dickey–Fuller Unit Root Test," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 445-470, February.
    48. Fabrizio Carmignani & Abdur Chowdhury, 2012. "The Geographical Dimension of the Development Effects of Natural Resources," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 52(4), pages 479-498, August.
    49. Bloch, Harry & Sapsford, David, 2012. "The Malthusian Paradox: Declining Food Prices in the Very Long Run," 2012 Conference (56th), February 7-10, 2012, Fremantle, Australia 124240, Australian Agricultural and Resource Economics Society.
    50. Pierre JACQUET & Alexis ATLANI & Marwan LISSER, 2017. "Policy responses to terms of trade shocks," Working Papers P205, FERDI.
    51. Rabah Arezki & Kaddour Hadri & Prakash Loungani & Yao Rao, 2013. "Breaking the Dynamic of Relative Primary Commodity Prices in Levels and Volatilities since 1650," Economics Working Papers 13-02, Queen's Management School, Queen's University Belfast.
    52. John T. Cuddington & Grant Nülle, 2013. "Variable Long-Term Trends in Mineral Prices: The Ongoing Tug-of-War between Exploration, Depletion, and Technological Change," Working Papers 2013-02, Colorado School of Mines, Division of Economics and Business.
    53. Frankel, Jeffrey A., 2011. "A Solution to Overoptimistic Forecasts and Fiscal Procyclicality: The Structural Budget Institutions Pioneered by Chile," Scholarly Articles 4723209, Harvard Kennedy School of Government.
    54. Alex Braithwaite & Niheer Dasandi & David Hudson, 2016. "Does poverty cause conflict? Isolating the causal origins of the conflict trap," Conflict Management and Peace Science, Peace Science Society (International), vol. 33(1), pages 45-66, February.
    55. Addison, Tony & Ghoshray, Atanu, 2023. "Discerning trends in international metal prices in the presence of nonstationary volatility," Resource and Energy Economics, Elsevier, vol. 71(C).
    56. Lee Robinson & Alice Nicole Sindzingre, 2012. "China’s Ambiguous Impacts on Commodity-Dependent Countries: the Example of Sub-Saharan Africa (with a Focus on Zambia)," Working Papers hal-04141046, HAL.
    57. Bernhard G. Gunter & Valeria Vargas Sejas, 2017. "Free Falling Terms of Trade Despite Industrialization: The Case of Bangladesh," Bangladesh Development Research Working Paper Series (BDRWPS) BDRWPS No. 33, Bangladesh Development Research Center (BDRC).
    58. Lehecka, Georg V., 2013. "Have food and financial markets integrated? An empirical assessment on aggregate data," 53rd Annual Conference, Berlin, Germany, September 25-27, 2013 156108, German Association of Agricultural Economists (GEWISOLA).
    59. Hassler, J. & Krusell, P. & Smith, A.A., 2016. "Environmental Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 1893-2008, Elsevier.
    60. Lehecka, G., 2014. "Have food and financial markets integrated? An empirical assessment on aggregate data," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 49, March.
    61. Erten, Bilge & Ocampo, José Antonio, 2013. "Super Cycles of Commodity Prices Since the Mid-Nineteenth Century," World Development, Elsevier, vol. 44(C), pages 14-30.
    62. Fabrizio Carmignani & Abdur Chowdhury, 2011. "The Development Effects Of Natural Resources: A Geographical Dimension," William Davidson Institute Working Papers Series wp1022, William Davidson Institute at the University of Michigan.
    63. Herzer, Dierk, 2009. "Cross-country heterogeneity and the trade-income relationship," Proceedings of the German Development Economics Conference, Frankfurt a.M. 2009 13, Verein für Socialpolitik, Research Committee Development Economics.
    64. Hany Fahmy, 2021. "A Reappraisal of the Prebisch-Singer Hypothesis Using Wavelets Analysis," JRFM, MDPI, vol. 14(7), pages 1-17, July.
    65. Yu Ri Kim, 2019. "Does aid for trade diversify the export structure of recipient countries?," The World Economy, Wiley Blackwell, vol. 42(9), pages 2684-2722, September.
    66. Ben-Salha, Ousama & Dachraoui, Hajer & Sebri, Maamar, 2021. "Natural resource rents and economic growth in the top resource-abundant countries: A PMG estimation," Resources Policy, Elsevier, vol. 74(C).
    67. Murat ASLAN & Saban NAZLIOGLU, 2018. "Do International Relative Commodity Prices Support the Prebisch-Singer Hypothesis? A Nonlinear Panel Unit Root Testing," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 76-92, December.
    68. Harvey, David I. & Kellard, Neil M. & Madsen, Jakob B. & Wohar, Mark E., 2017. "Long-Run Commodity Prices, Economic Growth, and Interest Rates: 17th Century to the Present Day," World Development, Elsevier, vol. 89(C), pages 57-70.
    69. Byrne, Joseph P & Sakemoto, Ryuta & Xu, Bing, 2017. "Commodity Price Co-movement: Heterogeneity and the Time Varying Impact of Fundamentals," MPRA Paper 80791, University Library of Munich, Germany.
    70. Wanling Huang & André Varella Mollick & Khoa Huu Nguyen, 2017. "Dynamic responses and tail-dependence among commodities, the US real interest rate and the dollar," Empirical Economics, Springer, vol. 53(3), pages 959-997, November.
    71. John E. Tilton, 2012. "The Terms Of Trade Debate and the Policy Implications for Primary Product Producers," Working Papers 2012-11, Colorado School of Mines, Division of Economics and Business.
    72. Yamada, Hiroshi & Yoon, Gawon, 2014. "When Grilli and Yang meet Prebisch and Singer: Piecewise linear trends in primary commodity prices," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 193-207.
    73. Fernandez, Viviana, 2015. "Commodity price excess co-movement from a historical perspective: 1900–2010," Energy Economics, Elsevier, vol. 49(C), pages 698-710.
    74. Ghoshray, Atanu & Kejriwal, Mohitosh & Wohar, Mark E., 2011. "Breaking Trends and the Prebisch-Singer Hypothesis: A Further Investigation," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 120387, European Association of Agricultural Economists.
    75. Byrne, Joseph P & Fazio, Giorgio & Fiess, Norbert, 2010. "Optimism and commitment: An elementary theory of bargaining and war," SIRE Discussion Papers 2010-102, Scottish Institute for Research in Economics (SIRE).
    76. Boris Petkov, 2018. "Natural Resource Abundance: Is it a Blessing or is it a Curse," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 43(3), pages 25-56, September.
    77. Lee Robinson & Alice Nicole Sindzingre, 2012. "China’s Ambiguous Impacts on Commodity-Dependent Countries: the Example of Sub-Saharan Africa (with a Focus on Zambia)," EconomiX Working Papers 2012-39, University of Paris Nanterre, EconomiX.
    78. Ghoshray, Atanu, 2015. "A robust estimation of the terms of trade between the United Kingdom and British India, 1858–1947," Economic Modelling, Elsevier, vol. 51(C), pages 53-57.
    79. Foo, Nam & Bloch, Harry & Salim, Ruhul, 2018. "The optimisation rule for investment in mining projects," Resources Policy, Elsevier, vol. 55(C), pages 123-132.
    80. Opa Kapijimpanga, 2023. "Debt Sustainability in the Context of African Dependency and Underdevelopment," Development, Palgrave Macmillan;Society for International Deveopment, vol. 66(3), pages 251-259, December.
    81. Awaworyi-Churchill, Sefa & Inekwe, John & Ivanovski, Kris & Smyth, Russell, 2022. "Breaks, trends and correlations in commodity prices in the very long-run," Energy Economics, Elsevier, vol. 108(C).
    82. Jalil Khodaparast Shirazi & Vahid Mohamad Taghvaee & Mohamad Nasiri & Abbas Assari Arani, 2020. "Sustainable development and openness in oil-exporting countries: green growth and brown growth," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 9(1), pages 1-19, December.
    83. Chuku Chuku & Paul Middleditch, 2016. "Characterizing monetary and fiscal policy rules and interactions when commodity prices matter," Centre for Growth and Business Cycle Research Discussion Paper Series 222, Economics, The University of Manchester.
    84. Gregor Schwerhoff & Martin Stuermer, 2015. "Non-renewable resources, extraction technology, and endogenous growth," Working Papers 1506, Federal Reserve Bank of Dallas.
    85. Titus Isaiah Zayone & Shida Rastegari Henneberry & Riza Radmehr, 2020. "Effects of Agricultural, Manufacturing, and Mineral Exports on Angola’s Economic Growth," Energies, MDPI, vol. 13(6), pages 1-17, March.
    86. Konstantin M. Wacker, 2011. "The Impact of Foreign Direct Investment on Developing Countries' Terms of Trade," WIDER Working Paper Series wp-2011-006, World Institute for Development Economic Research (UNU-WIDER).
    87. Fernandez, Viviana, 2019. "A readily computable commodity price index: 1900–2016," Finance Research Letters, Elsevier, vol. 31(C).
    88. Sabna Ali & Syed Mansoob Murshed & Elissaios Papyrakis, 2023. "Oil, export diversification and economic growth in Sudan: evidence from a VAR model," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 36(1), pages 77-96, January.
    89. Spinola, Danilo, 2020. "Uneven development and the balance of payments constrained model: Terms of trade, economic cycles, and productivity catching-up," Structural Change and Economic Dynamics, Elsevier, vol. 54(C), pages 220-232.
    90. Schaffartzik, Anke & Mayer, Andreas & Eisenmenger, Nina & Krausmann, Fridolin, 2016. "Global patterns of metal extractivism, 1950–2010: Providing the bones for the industrial society's skeleton," Ecological Economics, Elsevier, vol. 122(C), pages 101-110.
    91. Idris Abdullahi Abdulqadir, 2022. "The nonlinearity of exchange rate pass‐through on currency invoice: A quantile, generalized method of moments and threshold effect‐test from sub‐Sahara African economies," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 1473-1494, January.
    92. Atanu Ghoshray, 2013. "Dynamic Persistence of Primary Commodity Prices," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 95(1), pages 153-164.
    93. Peter Wells & Thaisa Faro, 2011. "Eco‐efficiency, self‐sufficiency and sustainability in transport: The limits for Brazilian sugarcane ethanol policy," Natural Resources Forum, Blackwell Publishing, vol. 35(1), pages 21-31, February.
    94. Bernhard Tröster & Karin Küblböck, 2020. "Unprecedented but not Unpredictable: Effects of the COVID-19 Crisis on Commodity-Dependent Countries," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 32(5), pages 1430-1449, December.
    95. Iyke, Bernard Njindan & Ho, Sin-Yu, 2021. "Stock return predictability over four centuries: The role of commodity returns," Finance Research Letters, Elsevier, vol. 40(C).
    96. Anke Schaffartzik & Melanie Pichler, 2017. "Extractive Economies in Material and Political Terms: Broadening the Analytical Scope," Sustainability, MDPI, vol. 9(7), pages 1-17, June.
    97. Fernandez, Viviana, 2014. "Linear and non-linear causality between price indices and commodity prices," Resources Policy, Elsevier, vol. 41(C), pages 40-51.
    98. Skrobotov, Anton, 2022. "On robust testing for trend," Economics Letters, Elsevier, vol. 212(C).
    99. Shouvik Chakraborty & Prabirjit Sarkar, 2020. "From The Classical Economists To Empiricists: A Review Of The Terms Of Trade Controversy," Journal of Economic Surveys, Wiley Blackwell, vol. 34(5), pages 1111-1133, December.
    100. Tarlok Singh, 2023. "Do terms of trade affect economic growth? Robust evidence from India," Economics of Transition and Institutional Change, John Wiley & Sons, vol. 31(2), pages 491-521, April.
    101. Konstantin M. Wacker, 2016. "Do Multinationals Deteriorate Developing Countries' Export Prices? The Impact of FDI on Net Barter Terms of Trade," The World Economy, Wiley Blackwell, vol. 39(12), pages 1974-1999, December.
    102. Rebelo, Sérgio & Krusell, Per & Bornstein, Gideon, 2017. "Lags, Costs and Shocks: An Equilibrium Model of the Oil Industry," CEPR Discussion Papers 12047, C.E.P.R. Discussion Papers.
    103. Bleaney,Michael Francis & Halland,Havard, 2016. "Do resource-rich countries suffer from a lack of fiscal discipline ?," Policy Research Working Paper Series 7552, The World Bank.
    104. Paul Alagidede, 2012. "Trends And Cycles In The Net Barter Terms Of Trade For Sub-Saharan Africa's Primary Commodity Exporters," Journal of Developing Areas, Tennessee State University, College of Business, vol. 46(2), pages 213-229, July-Dece.
    105. David Harvey & Neil Kellard & Jakob Madsen & Mark Wohar, 2012. "Trends and Cycles in Real Commodity Prices: 1650-2010," CEH Discussion Papers 010, Centre for Economic History, Research School of Economics, Australian National University.
    106. Atanu Ghoshray & Ashira Perera, 2016. "An Empirical Study of Commodity Prices after Sir Arthur Lewis," Manchester School, University of Manchester, vol. 84(4), pages 551-571, July.
    107. Georg V. Lehecka, 2014. "Have food and financial markets integrated?," Applied Economics, Taylor & Francis Journals, vol. 46(18), pages 2087-2095, June.
    108. Islam, Md. Rabiul & Madsen, Jakob B. & Raschky, Paul A., 2015. "Gold and silver mining in the 16th and 17th centuries, land titles and agricultural productivity," European Journal of Political Economy, Elsevier, vol. 39(C), pages 150-166.
    109. Yang, Yang & Wang, Shaoping, 2017. "Two simple tests of the trend hypothesis under time-varying variance," Economics Letters, Elsevier, vol. 156(C), pages 123-128.
    110. Gideon Bornstein & Per Krusell & Sergio Rebelo, 2017. "A World Equilibrium Model of the Oil Market," NBER Working Papers 23423, National Bureau of Economic Research, Inc.
    111. Nazlioglu, Saban & Kucukkaplan, Ilhan & Kilic, Emre & Altuntas, Mehmet, 2022. "Financial market integration of emerging markets: Heavy tails, structural shifts, nonlinearity, and asymmetric persistence," Research in International Business and Finance, Elsevier, vol. 62(C).
    112. Fernandez, Viviana, 2012. "Trends in real commodity prices: How real is real?," Resources Policy, Elsevier, vol. 37(1), pages 30-47.

  38. Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2009. "Rejoinder," Econometric Theory, Cambridge University Press, vol. 25(3), pages 658-667, June.

    Cited by:

    1. Smeekes, Stephan & Taylor, A.M. Robert, 2012. "Bootstrap Union Tests For Unit Roots In The Presence Of Nonstationary Volatility," Econometric Theory, Cambridge University Press, vol. 28(2), pages 422-456, April.

  39. Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2009. "Unit Root Testing In Practice: Dealing With Uncertainty Over The Trend And Initial Condition," Econometric Theory, Cambridge University Press, vol. 25(3), pages 587-636, June.
    See citations under working paper version above.
  40. Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2009. "Simple, Robust, And Powerful Tests Of The Breaking Trend Hypothesis," Econometric Theory, Cambridge University Press, vol. 25(4), pages 995-1029, August.
    See citations under working paper version above.
  41. Harris, David & Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2009. "Testing For A Unit Root In The Presence Of A Possible Break In Trend," Econometric Theory, Cambridge University Press, vol. 25(6), pages 1545-1588, December.
    See citations under working paper version above.
  42. David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2008. "Seasonal unit root tests and the role of initial conditions," Econometrics Journal, Royal Economic Society, vol. 11(3), pages 409-442, November.
    See citations under working paper version above.
  43. Harvey David I & Leybourne Stephen J & Xiao Bin, 2008. "A Powerful Test for Linearity When the Order of Integration is Unknown," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(3), pages 1-24, September.
    See citations under working paper version above.
  44. Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2007. "A simple, robust and powerful test of the trend hypothesis," Journal of Econometrics, Elsevier, vol. 141(2), pages 1302-1330, December.
    See citations under working paper version above.
  45. David I. Harvey & Stephen J. Leybourne, 2007. "Testing for time series linearity," Econometrics Journal, Royal Economic Society, vol. 10(1), pages 149-165, March.

    Cited by:

    1. Juan Carlos Cuestas & Paulo José Regis, 2010. "Purchasing power parity in OECD countries: nonlinear unit root tests revisited," NBS Discussion Papers in Economics 2010/3, Economics, Nottingham Business School, Nottingham Trent University.
    2. Wahab, Bashir A. & Adewuyi, Adeolu O., 2021. "Analysis of major properties of metal prices using new methods: Structural breaks, non-linearity, stationarity and bubbles," Resources Policy, Elsevier, vol. 74(C).
    3. Jean-François Verne, 2022. "Forecast the inflation rate in Lebanon: The use of the artificial neural networks method," Economics Bulletin, AccessEcon, vol. 42(4), pages 1798-1810.
    4. Mario Cerrato & Hyunsok Kim & Ronald MacDonald, 2010. "Microstructure order flow: statistical and economic evaluation of nonlinear forecasts," Working Papers 2010_30, Business School - Economics, University of Glasgow.
    5. Juan Carlos Cuestas & Dean Garratt, 2008. "Is real GDP per capita a stationary process? Smooth transitions, nonlinear trends and unit root testing," NBS Discussion Papers in Economics 2008/12, Economics, Nottingham Business School, Nottingham Trent University.
    6. Mario Cerrato & Hyunsok Kim & Ronald Macdonald, 2010. "Three-Regime Asymmetric STAR Modeling and Exchange Rate Reversion," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(7), pages 1447-1467, October.
    7. Cheung, Yin-Wong (ed.), 2012. "The Evolving Role of China in the Global Economy," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262018234, December.
    8. Dilem Yildirim & Ralf Becker & Denise R Osborn, 2009. "Bootstrap Unit Root Tests for Nonlinear Threshold Models," Economics Discussion Paper Series 0915, Economics, The University of Manchester.
    9. Lingxiang Zhang, 2020. "Linearity tests and stochastic trend under the STAR framework," Statistical Papers, Springer, vol. 61(6), pages 2271-2282, December.
    10. David O. Cushman & Glauco De Vita & Emmanouil Trachanas, 2023. "Is the Fisher effect asymmetric? Cointegration analysis and expectations measurement," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 3727-3748, October.
    11. Listorti, Giulia & Esposti, Roberto, 2012. "Horizontal Price Transmission in Agricultural Markets: Fundamental Concepts and Open Empirical Issues," Bio-based and Applied Economics Journal, Italian Association of Agricultural and Applied Economics (AIEAA), vol. 1(1), pages 1-28, April.
    12. Giorgio d'Agostino & Luca Pieroni & J Paul Dunne, 2009. "Optimal Military Spending in the US: A Time Series Analysis," Working Papers 0903, Department of Accounting, Economics and Finance, Bristol Business School, University of the West of England, Bristol.
    13. Erdas Mehmet Levent, 2019. "Validity of Weak-Form Market Efficiency in Central and Eastern European Countries (CEECs): Evidence from Linear and Nonlinear Unit Root Tests," Review of Economic Perspectives, Sciendo, vol. 19(4), pages 399-428, December.
    14. d'Agostino, Giorgio & Daddi, Pierluigi & Pieroni, Luca & Steinbrueck, Eric, 2014. "Does military spending stimulate growth? An empirical investigation in Italy," MPRA Paper 58290, University Library of Munich, Germany.
    15. Mario Cerrato & Hyunsok Kim & Ronald MacDonald, 2008. "3-Regime symmetric STAR modeling and exchange rate reversion," Working Papers 2009_05, Business School - Economics, University of Glasgow, revised Feb 2009.
    16. Harvey David I & Leybourne Stephen J & Xiao Bin, 2008. "A Powerful Test for Linearity When the Order of Integration is Unknown," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(3), pages 1-24, September.
    17. Ana Romão & Ricardo Barradas, 2024. "Macroeconomic determinants of households' indebtedness in Portugal: What really matters in the era of financialisation?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(1), pages 383-401, January.
    18. Ayca Doganer, 2022. "Determining Unemployment Hysteresis in European Countries Using Linear and Nonlinear Unit Root Tests: The 1991-2020 Period," Istanbul Journal of Economics-Istanbul Iktisat Dergisi, Istanbul University, Faculty of Economics, vol. 72(72-2), pages 753-785, December.
    19. Yoon, Gawon, 2009. "It's all the miners' fault: On the nonlinearity in U.S. unemployment rates," Economic Modelling, Elsevier, vol. 26(6), pages 1449-1454, November.
    20. Selahattin GÜRİŞ & Burak GÜRİŞ & Muhammed TIRAŞOĞLU, 2017. "Do military expenditures converge in NATO countries? Linear and nonlinear unit root test evidence," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(2(611), S), pages 237-248, Summer.
    21. E Pavlidis & I Paya & D Peel, 2009. "Real Exchange Rates and Time-Varying Trade Costs," Working Papers 600537, Lancaster University Management School, Economics Department.
    22. Shahbaz, Muhammad & Khraief, Naceur & Mahalik, Mantu Kumar & Zaman, Khair Uz, 2014. "Are fluctuations in natural gas consumption per capita transitory? Evidence from time series and panel unit root tests," Energy, Elsevier, vol. 78(C), pages 183-195.
    23. Greenidge, Kevin & Drakes, Lisa & Craigwell, Roland, 2011. "A Note on Causality between Debt and Sovereign Credit Ratings using Panel Tests," MPRA Paper 40931, University Library of Munich, Germany.
    24. Elena-Ivona DUMITRESCU & Christophe HURLIN & Jaouad MADKOUR, 2011. "Testing Interval Forecasts: A New GMM-based Test," LEO Working Papers / DR LEO 1549, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    25. Yusuf TUNA & Ayca DOGANER & Guldenur CETIN, 2022. "Determining the Relationships Between Domestic Credits, Economic Growth and Inflation in Turkiye by Nonlinear Cointegration Analysis," Journal of BRSA Banking and Financial Markets, Banking Regulation and Supervision Agency, vol. 16(2), pages 173-187.
    26. Gawon Yoon, 2010. "On the performance of a nonparametric measure of convergence towards purchasing power parity in the presence of linearity," Applied Economics Letters, Taylor & Francis Journals, vol. 17(14), pages 1389-1396.
    27. Hendrik Kaufmann & Robinson Kruse & Philipp Sibbertsen, 2012. "On tests for linearity against STAR models with deterministic trends," CREATES Research Papers 2012-20, Department of Economics and Business Economics, Aarhus University.
    28. Christensen, Bent Jesper & Kruse, Robinson & Sibbertsen, Philipp, 2013. "A unified framework for testing in the linear regression model under unknown order of fractional integration," Hannover Economic Papers (HEP) dp-519, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    29. Jinzhao Chen, 2012. "Crisis, Capital Controls and Covered Interest Parity: Evidence from China in Transformation," Working Papers halshs-00660654, HAL.
    30. Bob Nobay & Ivan Paya & David A. Peel, 2010. "Inflation Dynamics in the U.S.: Global but Not Local Mean Reversion," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(1), pages 135-150, February.
    31. Khraief, Naceur & Shahbaz, Muhammad & Heshmati, Almas & Azam, Muhammad, 2020. "Are unemployment rates in OECD countries stationary? Evidence from univariate and panel unit root tests," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    32. Ghoshray, A., 2018. "The Dynamic Properties of Natural Resource Prices," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277210, International Association of Agricultural Economists.
    33. Aslan, Alper, 2011. "Does natural gas consumption follow a nonlinear path over time? Evidence from 50 US States," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(9), pages 4466-4469.
    34. Gawon Yoon, 2010. "Nonlinearity in real exchange rates: an approach with disaggregated data and a new linearity test," Applied Economics Letters, Taylor & Francis Journals, vol. 17(11), pages 1125-1132.
    35. De Vita, Glauco & Trachanas, Emmanouil, 2016. "‘Nonlinear causality between crude oil price and exchange rate: A comparative study of China and India’ — A failed replication (negative Type 1 and Type 2)," Energy Economics, Elsevier, vol. 56(C), pages 150-160.
    36. Saša Obradoviæ & Lela Ristiæ & Nemanja Lojanica, 2018. "Are unemployment rates stationary for SEE10 countries? Evidence from linear and nonlinear dynamics," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 36(2), pages 559-583.
    37. E Pavlidis & I Paya & D Peel, 2009. "Forecasting the Real Exchange Rate using a Long Span of Data. A Rematch: Linear vs Nonlinear," Working Papers 601190, Lancaster University Management School, Economics Department.
    38. Liu, Donghui & Meng, Lingjie & Wang, Yudong, 2021. "The asymmetric effects of oil price changes on China’s exports: New evidence from a nonlinear autoregressive distributed lag model," Journal of Asian Economics, Elsevier, vol. 77(C).
    39. Roland Craigwell & Allan Wright, 2011. "Foreign direct investment and corruption in developing economies: Evidence from linear and non-linear panel Granger causality tests," Economics Bulletin, AccessEcon, vol. 31(3), pages 2272-2283.
    40. Elena Ivona Dumitrescu & Christophe Hurlin & Jaouad Madkour, 2013. "Testing Interval Forecasts: a GMM-Based Approach," Post-Print hal-01385898, HAL.
    41. Mikko Myrskylä & Joshua Goldstein, 2013. "Probabilistic Forecasting Using Stochastic Diffusion Models, With Applications to Cohort Processes of Marriage and Fertility," Demography, Springer;Population Association of America (PAA), vol. 50(1), pages 237-260, February.

  46. Harvey David I & Leybourne Stephen J & Taylor A.M. Robert, 2006. "On Robust Trend Function Hypothesis Testing," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(1), pages 1-27, March.
    See citations under working paper version above.
  47. David I. Harvey & Stephen J. Leybourne, 2006. "Power of a Unit‐Root Test and the Initial Condition," Journal of Time Series Analysis, Wiley Blackwell, vol. 27(5), pages 739-752, September.

    Cited by:

    1. Anton Skrobotov, 2016. "On Trend Breaks and Initial Condition in Unit Root Testing," Working Papers 0097, Gaidar Institute for Economic Policy, revised 2016.
    2. Lau, Chi Keung Marco & Suvankulov, Farrukh & Su, Yongyang & Chau, Frankie, 2012. "Some cautions on the use of nonlinear panel unit root tests: Evidence from a modified series-specific non-linear panel unit-root test," Economic Modelling, Elsevier, vol. 29(3), pages 810-816.
    3. Skrobotov, Anton (Скроботов, Антон), 2015. "About Trend, the Shift and the Initial Value in Testing of the Hypothesis of a Unit Root [О Тренде, Сдвиге И Начальном Значении В Тестировании Гипотезы О Наличии Единичного Корня]," Published Papers mak6, Russian Presidential Academy of National Economy and Public Administration.
    4. Westerlund, Joakim, 2014. "Pooled panel unit root tests and the effect of past initialization," Working Papers fe_2014_06, Deakin University, Department of Economics.
    5. Hugo Ferrer-Pérez & María-Isabel Ayuda & Antonio Aznar, 2019. "Improving the Performance of a Long-Run Variance Ratio Test for a Unit Root," The Japanese Economic Review, Springer, vol. 70(2), pages 258-274, June.
    6. Sven Otto, 2020. "Unit Root Testing with Slowly Varying Trends," Papers 2003.04066, arXiv.org, revised Aug 2020.
    7. Kerry Patterson & Michael A. Thornton, 2013. "A review of econometric concepts and methods for empirical macroeconomics," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 2, pages 4-42, Edward Elgar Publishing.
    8. Skrobotov, Anton, 2020. "Survey on structural breaks and unit root tests," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 58, pages 96-141.
    9. Anton Skrobotov, 2013. "Double Unit Roots Testing, GLS-detrending and Uncertainty over the Initial Conditions," Working Papers 0083, Gaidar Institute for Economic Policy, revised 2013.
    10. Meligkotsidou, Loukia & Tzavalis, Elias & Vrontos, Ioannis, 2017. "On Bayesian analysis and unit root testing for autoregressive models in the presence of multiple structural breaks," Econometrics and Statistics, Elsevier, vol. 4(C), pages 70-90.

  48. Harvey, David I. & van Dijk, Dick, 2006. "Sample size, lag order and critical values of seasonal unit root tests," Computational Statistics & Data Analysis, Elsevier, vol. 50(10), pages 2734-2751, June.

    Cited by:

    1. Tomás del Barrio Castro & Andrii Bodnar & Andreu Sansó Rosselló, 2015. "Numerical Distribution Functions for Seasonal Unit Root Tests with OLS and GLS Detrending," DEA Working Papers 73, Universitat de les Illes Balears, Departament d'Economía Aplicada.
    2. Díaz-Emparanza, Ignacio & Moral, M. Paz, 2014. "Numerical distribution functions for seasonal stability tests," Statistics & Probability Letters, Elsevier, vol. 86(C), pages 44-49.
    3. Sebastian Kripfganz & Daniel C. Schneider, 2020. "Response Surface Regressions for Critical Value Bounds and Approximate p‐values in Equilibrium Correction Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(6), pages 1456-1481, December.
    4. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521817707.
    5. Jesús Otero & Jeremy Smith, 2012. "Response surface models for the Leybourne unit root tests and lag order dependence," Computational Statistics, Springer, vol. 27(3), pages 473-486, September.
    6. Pui Sun Tam, 2013. "Finite-sample distribution of the augmented Dickey--Fuller test with lag optimization," Applied Economics, Taylor & Francis Journals, vol. 45(24), pages 3495-3511, August.
    7. Jesús Otero & Jeremy Smith, 2013. "Response Surface Estimates of the Cross-Sectionally Augmented IPS Tests for Panel Unit Roots," Computational Economics, Springer;Society for Computational Economics, vol. 41(1), pages 1-9, January.
    8. Díaz-Emparanza Herrero, Ignacio, 2011. "Numerical Distribution Functions for Seasonal Unit Root Tests," BILTOKI 1134-8984, Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística).
    9. Gabriel Pons, 2006. "Testing Monthly Seasonal Unit Roots With Monthly and Quarterly Information," Journal of Time Series Analysis, Wiley Blackwell, vol. 27(2), pages 191-209, March.
    10. Peter Sephton, 2008. "Critical values of the augmented fractional Dickey–Fuller test," Empirical Economics, Springer, vol. 35(3), pages 437-450, November.
    11. Nazlioglu, Saban & Lee, Junsoo, 2020. "Response surface estimates of the LM unit root tests," Economics Letters, Elsevier, vol. 192(C).
    12. Díaz-Emparanza Herrero, Ignacio & Moral Zuazo, María Paz, 2013. "Seasonal Stability Tests in gretl. An Application to International Tourism Data," BILTOKI 1134-8984, Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística).

  49. Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2006. "Modified tests for a change in persistence," Journal of Econometrics, Elsevier, vol. 134(2), pages 441-469, October.
    See citations under working paper version above.
  50. David I. Harvey & Stephen J. Leybourne, 2005. "On testing for unit roots and the initial observation," Econometrics Journal, Royal Economic Society, vol. 8(1), pages 97-111, March.

    Cited by:

    1. David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2009. "The impact of the initial condition on robust tests for a linear trend," Discussion Papers 09/03, University of Nottingham, Granger Centre for Time Series Econometrics.
    2. Anton Skrobotov, 2016. "On Trend Breaks and Initial Condition in Unit Root Testing," Working Papers 0097, Gaidar Institute for Economic Policy, revised 2016.
    3. Skrobotov, Anton (Скроботов, Антон), 2015. "About Trend, the Shift and the Initial Value in Testing of the Hypothesis of a Unit Root [О Тренде, Сдвиге И Начальном Значении В Тестировании Гипотезы О Наличии Единичного Корня]," Published Papers mak6, Russian Presidential Academy of National Economy and Public Administration.
    4. Kajal Lahiri & Zhongwen Liang & Huaming Peng, 2017. "The Local Power of the IPS Test with Both Initial Conditions and Incidental Trends," CESifo Working Paper Series 6313, CESifo.
    5. Yiannis Karavias & Elias Tzavalis, 2013. "The power performance of fixed-T panel unit root tests allowing for structural breaks," Discussion Papers 13/01, University of Nottingham, Granger Centre for Time Series Econometrics.
    6. Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2009. "Unit Root Testing In Practice: Dealing With Uncertainty Over The Trend And Initial Condition," Econometric Theory, Cambridge University Press, vol. 25(3), pages 587-636, June.
    7. Shelef, Amit, 2016. "A Gini-based unit root test," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 763-772.
    8. Yiannis Karavias & Elias Tzavalis, 2017. "Local power of panel unit root tests allowing for structural breaks," Econometric Reviews, Taylor & Francis Journals, vol. 36(10), pages 1123-1156, November.
    9. Meng, Ming & Lee, Hyejin & Cho, Myeong Hyeon & Lee, Junsoo, 2013. "Impacts of the initial observation on unit root tests using recursive demeaning and detrending procedures," Economics Letters, Elsevier, vol. 120(2), pages 195-199.
    10. Sven Otto, 2020. "Unit Root Testing with Slowly Varying Trends," Papers 2003.04066, arXiv.org, revised Aug 2020.
    11. Kerry Patterson & Michael A. Thornton, 2013. "A review of econometric concepts and methods for empirical macroeconomics," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 2, pages 4-42, Edward Elgar Publishing.
    12. Skrobotov, Anton, 2020. "Survey on structural breaks and unit root tests," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 58, pages 96-141.
    13. Elliott, Graham & Muller, Ulrich K., 2006. "Minimizing the impact of the initial condition on testing for unit roots," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 285-310.
    14. David Harris & David I. Harvey & Stephen J. Leybourne & Nikoloas D. Sakkas, 2008. "Local asymptotic power of the Im-Pesaran-Shin panel unit root test and the impact of initial observations," Discussion Papers 08/02, University of Nottingham, Granger Centre for Time Series Econometrics.
    15. Anton Skrobotov, 2013. "Double Unit Roots Testing, GLS-detrending and Uncertainty over the Initial Conditions," Working Papers 0083, Gaidar Institute for Economic Policy, revised 2013.
    16. David I. Harvey & Stephen J. Leybourne & Nikolaos D. Sakkas, 2008. "Panel root tests and the impact of initial observations," Discussion Papers 06/02, University of Nottingham, Granger Centre for Time Series Econometrics.
    17. Ahlgren, Niklas & Juselius, Mikael, 2009. "Tests for Cointegration Rank and the Initial Condition," Working Papers 539, Hanken School of Economics.
    18. David I. Harvey, & Stephen J. Leybourne, & A. M. Robert Taylor, 2007. "Testing for a unit root when uncertain about the trend [Revised to become 07/03 above]," Discussion Papers 06/03, University of Nottingham, Granger Centre for Time Series Econometrics.
    19. Chrystalleni Aristidou & David Harvey & Stephen Leybourne, 2016. "The impact of the initial condition on covariate augmented unit root tests," Discussion Papers 16/01, University of Nottingham, Granger Centre for Time Series Econometrics.
    20. Paulo M. M. Rodrigues, 2013. "Recursive adjustment, unit root tests and structural breaks," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(1), pages 62-82, January.
    21. Yaya, OlaOluwa Simon & Gil-Alana, Luis Alberiko & Carcel, Hector, 2015. "Testing fractional persistence and non-linearities in the natural gas market: An application of non-linear deterministic terms based on Chebyshev polynomials in time," Energy Economics, Elsevier, vol. 52(PA), pages 240-245.
    22. Sven Otto, 2021. "Unit root testing with slowly varying trends," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(1), pages 85-106, January.

  51. David Harvey & Terence Mills, 2005. "Evidence for common features in G7 macroeconomic time series," Applied Economics, Taylor & Francis Journals, vol. 37(2), pages 165-175.

    Cited by:

    1. Zhichao Guo & Yuanhua Feng & Xiangyong Tan, 2011. "Impact of China's accession to WTO and the financial crisis on China's exports to Germany," Working Papers CIE 36, Paderborn University, CIE Center for International Economics.
    2. Guo, Zhichao & Feng, Yuanhua, 2013. "Modeling of the impact of the financial crisis and China's accession to WTO on China's exports to Germany," Economic Modelling, Elsevier, vol. 31(C), pages 474-483.
    3. Blonigen, Bruce A. & Piger, Jeremy & Sly, Nicholas, 2014. "Comovement in GDP trends and cycles among trading partners," Journal of International Economics, Elsevier, vol. 94(2), pages 239-247.
    4. Guo, Zhichao & Feng, Yuanhua & Tan, Xiangyong, 2011. "Short- and long-term impact of remarkable economic events on the growth causes of China–Germany trade in agri-food products," Economic Modelling, Elsevier, vol. 28(6), pages 2359-2368.
    5. Zhichao Guo & Yuanhua Feng & Thomas Gries, 2015. "Changes of China’s agri-food exports to Germany caused by its accession to WTO and the 2008 financial crisis," China Agricultural Economic Review, Emerald Group Publishing Limited, vol. 7(2), pages 262-279, May.
    6. Willie Lahari, 2011. "Assessing Business Cycle Synchronisation - Prospects for a Pacific Islands Currency Union," Working Papers 1110, University of Otago, Department of Economics, revised Oct 2011.
    7. Chen, Xiaoshan & Mills, Terence C., 2009. "Evaluating growth cycle synchronisation in the EU," Economic Modelling, Elsevier, vol. 26(2), pages 342-351, March.
    8. David Griffiths, 2007. "Forecasting income shares: are mean-reversion assumptions appropriate?," Applied Economics, Taylor & Francis Journals, vol. 39(21), pages 2699-2711.
    9. Fernandez, Viviana, 2006. "Does domestic cooperation lead to business-cycle convergence and financial linkages?," The Quarterly Review of Economics and Finance, Elsevier, vol. 46(3), pages 369-396, July.

  52. David I. Harvey & Paul Newbold, 2005. "Forecast Encompassing and Parameter Estimation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(s1), pages 815-835, December.

    Cited by:

    1. Garratt, Anthony & Lee, Kevin & Mise, Emi & Shields, Kalvinder, 2009. "Real time representation of the UK output gap in the presence of model uncertainty," International Journal of Forecasting, Elsevier, vol. 25(1), pages 81-102.
    2. Kourentzes, Nikolaos & Barrow, Devon & Petropoulos, Fotios, 2019. "Another look at forecast selection and combination: Evidence from forecast pooling," International Journal of Production Economics, Elsevier, vol. 209(C), pages 226-235.
    3. Bedri Kamil Onur Taş, 2016. "Does the Federal Reserve have Private Information about its Future Actions?," Economica, London School of Economics and Political Science, vol. 83(331), pages 498-517, July.
    4. Huiyu Huang & Tae-Hwy Lee, 2010. "To Combine Forecasts or to Combine Information?," Econometric Reviews, Taylor & Francis Journals, vol. 29(5-6), pages 534-570.
    5. Chrystalleni Aristidou & Kevin Lee & Kalvinder Shields, 2015. "Real-Time Data should be used in Forecasting Output Growth and Recessionary Events in the US," Discussion Papers 2015/13, University of Nottingham, Centre for Finance, Credit and Macroeconomics (CFCM).
    6. Vasyl Golosnoy & Yarema Okhrin, 2015. "Using information quality for volatility model combinations," Quantitative Finance, Taylor & Francis Journals, vol. 15(6), pages 1055-1073, June.
    7. Garratt, Anthony & Lee, Kevin, 2010. "Investing under model uncertainty: Decision based evaluation of exchange rate forecasts in the US, UK and Japan," Journal of International Money and Finance, Elsevier, vol. 29(3), pages 403-422, April.

  53. David I. Harvey & Terence C. Mills, 2004. "Tests for Stationarity in Series with Endogenously Determined Structural Change," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(5), pages 863-894, December.

    Cited by:

    1. Costantini, Mauro & Sen, Amit, 2016. "A simple testing procedure for unit root and model specification," Computational Statistics & Data Analysis, Elsevier, vol. 102(C), pages 37-54.
    2. Chun- Yu Ho & Dan Li, 2007. "Rising Regional Inequality in China:Policy Regimes and Structural Changes," Boston University - Department of Economics - Working Papers Series WP2007-013, Boston University - Department of Economics.
    3. D., Ivan, 2017. "Stability of the labour shares: evidence from OECD economies," MPRA Paper 79822, University Library of Munich, Germany.
    4. Joseph P. Byrne & Roger Perman, 2006. "Unit Roots and Structural Breaks: A Survey of the Literature," Working Papers 2006_10, Business School - Economics, University of Glasgow.
    5. Brittle, Shane, 2009. "Ricardian Equivalence and the Efficacy of Fiscal Policy in Australia," Economics Working Papers wp09-10, School of Economics, University of Wollongong, NSW, Australia.
    6. Landajo, Manuel & Presno, María José, 2010. "Nonparametric pseudo-Lagrange multiplier stationarity testing," MPRA Paper 25659, University Library of Munich, Germany.
    7. Ivan D. Trofimov, 2019. "Stability of Labour Shares: Evidence from OECD Economies," South-Eastern Europe Journal of Economics, Association of Economic Universities of South and Eastern Europe and the Black Sea Region, vol. 17(1), pages 57-89.
    8. María Presno & Manuel Landajo, 2010. "Computation of limiting distributions in stationarity testing with a generic trend," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 71(2), pages 165-183, March.
    9. Manuel Landajo & María José Presno, 2010. "Stationarity testing under nonlinear models. Some asymptotic results," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(5), pages 392-405, September.
    10. Peter Sephton, 2017. "Finite Sample Critical Values of the Generalized KPSS Stationarity Test," Computational Economics, Springer;Society for Computational Economics, vol. 50(1), pages 161-172, June.
    11. Alper Kara & Dilem Yildirim & G. Ipek Tunc, 2023. "Market efficiency in non-renewable resource markets: evidence from stationarity tests with structural changes," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 36(2), pages 279-290, June.
    12. Alper Kara & Dilem Yıldırım & Gül İpek Tunç, 2021. "Market Efficiency In Non-Renewable Resource Markets: Evidence From Stationarity Tests With Structural Changes," ERC Working Papers 2103, ERC - Economic Research Center, Middle East Technical University, revised Apr 2021.
    13. Noriega Antonio E. & Rodríguez-Pérez Cid Alonso, 2011. "Stationarity, structural breaks, and economic growth in Mexico: 1895-2008," Working Papers 2011-11, Banco de México.

  54. Harvey, David I. & Newbold, Paul, 2003. "The non-normality of some macroeconomic forecast errors," International Journal of Forecasting, Elsevier, vol. 19(4), pages 635-653.

    Cited by:

    1. João Henrique Gonçalves Mazzeu & Esther Ruiz & Helena Veiga, 2018. "Uncertainty And Density Forecasts Of Arma Models: Comparison Of Asymptotic, Bayesian, And Bootstrap Procedures," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 388-419, April.
    2. BRATU SIMIONESCU, Mihaela, 2012. "Two Quantitative Forecasting Methods For Macroeconomic Indicators In Czech Republic," Annals of Spiru Haret University, Economic Series, Universitatea Spiru Haret, vol. 3(1), pages 71-87.
    3. Timur Hulagu & Saygin Sahinoz, 2012. "Is Disagreement a Good Proxy for Inflation Uncertainty? Evidence from Turkey," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 12(1), pages 53-62.
    4. Kajal Lahiri & Xuguang Sheng, 2008. "Measuring Forecast Uncertainty by Disagreement: The Missing Link," ifo Working Paper Series 60, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    5. Pascual, Lorenzo & Romo, Juan & Ruiz, Esther, 2005. "Bootstrap prediction intervals for power-transformed time series," International Journal of Forecasting, Elsevier, vol. 21(2), pages 219-235.
    6. Krkoska, Libor & Teksoz, Utku, 2009. "How reliable are forecasts of GDP growth and inflation for countries with limited coverage?," Economic Systems, Elsevier, vol. 33(4), pages 376-388, December.
    7. Tara Sinclair & Herman O. Stekler & Warren Carnow, 2012. "A New Approach For Evaluating Economic Forecasts," Working Papers 2012-2, The George Washington University, Institute for International Economic Policy.
    8. Marian Vavra, 2018. "Assessing Distributional Properties of Forecast Errors," Working and Discussion Papers WP 3/2018, Research Department, National Bank of Slovakia.
    9. Krkoska, Libor & Teksoz, Utku, 2007. "Accuracy of GDP growth forecasts for transition countries: Ten years of forecasting assessed," International Journal of Forecasting, Elsevier, vol. 23(1), pages 29-45.
    10. Timur Hulagu & Saygin Sahinoz, 2011. "Enflasyon Belirsizligi ve Beklentilerdeki Uyusmazlik," CBT Research Notes in Economics 1104, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    11. Gonçalves Mazzeu, Joao Henrique & Ruiz Ortega, Esther & Veiga, Helena, 2015. "Model uncertainty and the forecast accuracy of ARMA models: A survey," DES - Working Papers. Statistics and Econometrics. WS ws1508, Universidad Carlos III de Madrid. Departamento de Estadística.
    12. Bonga-Bonga, Lumengo & Mwamba, Muteba, 2015. "A multivariate model for the prediction of stock returns in an emerging market: A comparison of parametric and non-parametric models," MPRA Paper 62028, University Library of Munich, Germany.
    13. Kontogeorgos, Georgios & Lambrias, Kyriacos, 2019. "An analysis of the Eurosystem/ECB projections," Working Paper Series 2291, European Central Bank.
    14. Víctor López-Pérez, 2017. "Do professional forecasters behave as if they believed in the New Keynesian Phillips Curve for the euro area?," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 44(1), pages 147-174, February.
    15. Fresoli, Diego & Ruiz, Esther & Pascual, Lorenzo, 2015. "Bootstrap multi-step forecasts of non-Gaussian VAR models," International Journal of Forecasting, Elsevier, vol. 31(3), pages 834-848.
    16. Tito Nícias Teixeira da Silva Filho, 2013. "Banks, Asset Management or Consultancies' Inflation Forecasts: is there a better forecaster out there?," Working Papers Series 310, Central Bank of Brazil, Research Department.

  55. Terence C. Mills & David I. Harvey, 2003. "Modelling trends in central England temperatures," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(1), pages 35-47.

    Cited by:

    1. Changli He & Jian Kang & Timo Teräsvirta & Shuhua Zhang, 2019. "Long monthly temperature series and the Vector Seasonal Shifting Mean and Covariance Autoregressive model," CREATES Research Papers 2019-18, Department of Economics and Business Economics, Aarhus University.
    2. Gadea Rivas, María Dolores & Gonzalo, Jesús, 2017. "Trends in distributional characteristics : Existence of global warming," UC3M Working papers. Economics 24121, Universidad Carlos III de Madrid. Departamento de Economía.
    3. Jewson Stephen & Penzer Jeremy, 2006. "Estimating Trends in Weather Series: Consequences for Pricing Derivatives," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(3), pages 1-17, September.
    4. Terence C. Mills, 2012. "Semi-parametric modelling of temperature records," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(2), pages 361-383, May.
    5. Tommaso Proietti & Eric Hillebrand, 2017. "Seasonal changes in central England temperatures," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(3), pages 769-791, June.
    6. Changli He & Jian Kang & Timo Teräsvirta & Shuhua Zhang, 2018. "The Shifting Seasonal Mean Autoregressive Model and Seasonality in the Central England Monthly Temperature Series, 1772-2016," CREATES Research Papers 2018-15, Department of Economics and Business Economics, Aarhus University.

  56. David I. Harvey & Terence C. Mills, 2003. "A Note On Busetti–Harvey Tests For Stationarity In Series With Structural Breaks," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(2), pages 159-164, March.

    Cited by:

    1. Anton Skrobotov, 2013. "Local Structural Trend Break in Stationarity Testing," Working Papers 0074, Gaidar Institute for Economic Policy, revised 2013.
    2. Anton Skrobotov, 2012. "Bias Correction of KPSS Test with Structural Break for Reducing of Size Distortion," Working Papers 0043, Gaidar Institute for Economic Policy, revised 2013.
    3. Su, Chi-Wei & Tsangyao, Chang & Chang, Hsu-Ling, 2011. "Purchasing power parity for fifteen Latin American countries: Stationary test with a Fourier function," International Review of Economics & Finance, Elsevier, vol. 20(4), pages 839-845, October.
    4. Jerome Geyer‐Klingeberg & Andreas W. Rathgeber, 2021. "Determinants of the WTI‐Brent price spread revisited," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(5), pages 736-757, May.
    5. Anton Skrobotov, 2012. "Bias Correction of KPSS Test with Structural Break for Reducing of Size Distortion - in Russian," Working Papers 0044, Gaidar Institute for Economic Policy, revised 2012.
    6. Skrobotov, Anton, 2020. "Survey on structural breaks and unit root tests," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 58, pages 96-141.

  57. David Harvey & Stephen Leybourne & Paul Newbold, 2003. "How great are the great ratios?," Applied Economics, Taylor & Francis Journals, vol. 35(2), pages 163-177.

    Cited by:

    1. Cliff L. F. Attfield & Jonathan R. W. Temple, 2006. "Balanced growth and the great ratios: new evidence for the US and UK," Centre for Growth and Business Cycle Research Discussion Paper Series 75, Economics, The University of Manchester.
    2. Kapetanios, George & Millard, Stephen & Petrova, Katerina & Price, Simon, 2019. "Time-varying cointegration and the UK great ratios," Bank of England working papers 789, Bank of England.
    3. Ivan D. Trofimov, 2017. "Capital Productivity In Industrialised Economies: Evidence From Error-Correction Model And Lagrange Multiplier Tests," Economic Annals, Faculty of Economics and Business, University of Belgrade, vol. 62(215), pages 53-80, October –.
    4. Chang, Juin-Jen & Lin, Chang-Ching & Lin, Hsieh-Yu, 2016. "Great ratios and international openness," International Review of Economics & Finance, Elsevier, vol. 41(C), pages 110-121.
    5. Menyah, Kojo & Wolde-Rufael, Yemane, 2010. "Energy consumption, pollutant emissions and economic growth in South Africa," Energy Economics, Elsevier, vol. 32(6), pages 1374-1382, November.
    6. M.S.Rafiq, 2006. "Great Ratios, Balanced Growth and Stochastic Trends: Evidence for the Euro Area," Discussion Paper Series 2006_20, Department of Economics, Loughborough University.
    7. Hong Li & Vince Daly, 2009. "Testing the balanced growth hypothesis: evidence from China," Empirical Economics, Springer, vol. 37(1), pages 185-200, September.
    8. Herzer, Dierk & Kemper, Niels & Zamparelli, Luca, 2009. "Balanced growth and structural breaks: Evidence for Germany," MPRA Paper 14944, University Library of Munich, Germany.
    9. Don Harding, 2020. "Econometric Foundations of the Great Ratios of Economics," Centre of Policy Studies/IMPACT Centre Working Papers g-300, Victoria University, Centre of Policy Studies/IMPACT Centre.
    10. Ekaterina Ponomareva & Alexandra Bozhechkova & Alexandr Knobel, 2012. "Factors of Economic Growth," Published Papers 172, Gaidar Institute for Economic Policy, revised 2013.
    11. Luca Zamparelli, 2011. "Induced Innovation, Endogenous Growth, and Income Distribution: a Model along Classical Lines," Working Papers CELEG 1102, Dipartimento di Economia e Finanza, LUISS Guido Carli.
    12. M.S.Rafiq, 2006. "Business Cycle Moderation - Good Policies or Good Luck: Evidence and Explanations for the Euro Area," Discussion Paper Series 2006_21, Department of Economics, Loughborough University.
    13. Claude Lopez & Javier Reyes, 2009. "Stationary properties of the real interest rate and the per-capita consumption growth rate: empirical evidence for theoretical arguments," Applied Economics, Taylor & Francis Journals, vol. 41(13), pages 1643-1651.
    14. Kapetanios, George & Millard, Stephen & Petrova, Katerina & Price, Simon, 2020. "Time-varying cointegration with an application to the UK Great Ratios," Economics Letters, Elsevier, vol. 193(C).
    15. Diego Romero-Avila, 2008. "A confirmatory analysis of the unit root hypothesis for OECD consumption-income ratios," Applied Economics, Taylor & Francis Journals, vol. 40(17), pages 2271-2278.
    16. Camarero, Mariam & Picazo-Tadeo, Andrés J. & Tamarit, Cecilio, 2008. "Is the environmental performance of industrialized countries converging? A 'SURE' approach to testing for convergence," Ecological Economics, Elsevier, vol. 66(4), pages 653-661, July.
    17. Trofimov, Ivan D., 2017. "Capital productivity in industrialized economies: evidence from error-correction model and Lagrange Multiplier tests," MPRA Paper 81655, University Library of Munich, Germany.
    18. Arjun & Bibhuti Ranjan Mishra, 2024. "Testing the Balanced Growth Hypothesis in the Presence of Structural Breaks: Evidence from Developed and Developing Countries," Prague Economic Papers, Prague University of Economics and Business, vol. 2024(1), pages 1-35.
    19. Holmes, Mark J. & Shen, Xin, 2013. "A note on the average propensity to consume, wealth and threshold adjustment," Economic Modelling, Elsevier, vol. 35(C), pages 309-313.
    20. Romero-Ávila, Diego, 2009. "Are OECD consumption-income ratios stationary after all?," Economic Modelling, Elsevier, vol. 26(1), pages 107-117, January.
    21. Mark J. HOLMES & Xin SHEN, 2015. "On Wealth Volatility, Asymmetries And The Average Propensity To Consume In The United States," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 15(1), pages 69-78.

  58. David Harvey & Terence Mills, 2002. "Unit roots and double smooth transitions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 29(5), pages 675-683.

    Cited by:

    1. He, Changli & Sandberg, Rickard, 2005. "Dickey-Fuller Type of Tests against Nonlinear Dynamic Models," SSE/EFI Working Paper Series in Economics and Finance 580, Stockholm School of Economics.
    2. Li, Yushu & Shukur, Ghazi, 2009. "Testing for Unit Root against LSTAR model – wavelet improvements under GARCH distortion," Working Paper Series in Economics and Institutions of Innovation 184, Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies.
    3. Rickard Sandberg, 2018. "Unit Root Testing in Multiple Smooth Break Models with Nonlinear Dynamics," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 942-952, November.
    4. Francisco Estrada & Pierre Perron, "undated". "Detection and attribution of climate change through econometric methods," Boston University - Department of Economics - Working Papers Series 2013-015, Boston University - Department of Economics.
    5. Dukpa Kim & Tatsushi Oka & Francisco Estrada & Pierre Perron, 2017. "Inference Related to Common Breaks in a Multivariate System with Joined Segmented Trends with Applications to Global and Hemispheric Temperatures," Boston University - Department of Economics - Working Papers Series WP2018-015, Boston University - Department of Economics, revised Apr 2018.
    6. Holt, Matthew T. & Teräsvirta, Timo, 2020. "Global hemispheric temperatures and co-shifting: A vector shifting-mean autoregressive analysis," Journal of Econometrics, Elsevier, vol. 214(1), pages 198-215.
    7. Richard S. J. Tol & Francisco Estrada & Carlos Gay-García, 2012. "The persistence of shocks in GDP and the estimation of the potential economic costs of climate change," Working Paper Series 4312, Department of Economics, University of Sussex Business School.
    8. Paraskevi Salamaliki & Ioannis Venetis, 2014. "Smooth transition trends and labor force participation rates in the United States," Empirical Economics, Springer, vol. 46(2), pages 629-652, March.
    9. Xie, Zixiong & Chen, Shyh-Wei & Hsieh, Chun-Kuei, 2021. "Facing up to the polysemy of purchasing power parity: New international evidence," Economic Modelling, Elsevier, vol. 98(C), pages 247-265.
    10. Sandberg, Rickard, 2016. "Trends, unit roots, structural changes, and time-varying asymmetries in U.S. macroeconomic data: the Stock and Watson data re-examined," Economic Modelling, Elsevier, vol. 52(PB), pages 699-713.
    11. He, Changli & Sandberg, Rickard, 2005. "Testing for Unit Roots in Nonlinear Dynamic Heterogeneous Panels," SSE/EFI Working Paper Series in Economics and Finance 582, Stockholm School of Economics.
    12. Hepsag, Aycan, 2017. "New unit root tests with two smooth breaks and nonlinear adjustment," MPRA Paper 83353, University Library of Munich, Germany.
    13. Terence C. Mills, 2012. "Semi-parametric modelling of temperature records," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(2), pages 361-383, May.
    14. Robert Sollis, 2005. "Evidence on purchasing power parity from univariate models: the case of smooth transition trend‐stationarity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(1), pages 79-98, January.
    15. Robert Sollis, 2005. "Evidence on purchasing power parity from univariate models: the case of smooth transition trend-stationarity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(1), pages 79-98.
    16. Chen, Shyh-Wei & Wu, An-Chi, 2018. "Is there a bubble component in government debt? New international evidence," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 467-486.
    17. Saumitra N. Bhaduri & Ashwin Andrew Samuel, 2009. "International Equity Market Integration," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 8(1), pages 45-66, April.
    18. Changli He & Rickard Sandberg, 2006. "Dickey–Fuller Type of Tests against Nonlinear Dynamic Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(s1), pages 835-861, December.
    19. Xie, Zixiong & Chen, Shyh-Wei & Wu, An-Chi, 2019. "Asymmetric adjustment, non-linearity and housing price bubbles: New international evidence," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    20. Terence Mills & Kerry Patterson, 2013. "Carmichael's Arctan Trend: Precursor of Smooth Transition Functions," Economics Discussion Papers em-dp2013-06, Department of Economics, University of Reading.
    21. Chen, Shyh-Wei & Xie, Zixiong, 2017. "Asymmetric adjustment and smooth breaks in dividend yields: Evidence from international stock markets," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 339-354.
    22. Terence C. Mills & David I. Harvey, 2003. "Modelling trends in central England temperatures," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(1), pages 35-47.
    23. Terence C. Mills, 2007. "Time series modelling of two millennia of northern hemisphere temperatures: long memory or shifting trends?," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 170(1), pages 83-94, January.
    24. Noriega Antonio E. & Rodríguez-Pérez Cid Alonso, 2011. "Stationarity, structural breaks, and economic growth in Mexico: 1895-2008," Working Papers 2011-11, Banco de México.

  59. Harvey, David I. & Leybourne, Stephen J. & Newbold, Paul, 2002. "Seasonal unit root tests with seasonal mean shifts," Economics Letters, Elsevier, vol. 76(2), pages 295-302, July.

    Cited by:

    1. Luis C. Nunes & Paulo M. M. Rodrigues, 2011. "On LM‐type tests for seasonal unit roots in the presence of a break in trend," Journal of Time Series Analysis, Wiley Blackwell, vol. 32(2), pages 108-134, March.
    2. Soo-Bin Jeong & Bong-Hwan Kim & Tae-Hwan Kim & Hyung-Ho Moon, 2017. "Unit Root Tests In The Presence Of Multiple Breaks In Variance," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 62(02), pages 345-361, June.
    3. Taipalus, Katja, 2012. "Signaling asset price bubbles with time-series methods," Bank of Finland Research Discussion Papers 7/2012, Bank of Finland.
    4. Niels Haldrup & Robinson Kruse & Timo Teräsvirta & Rasmus T. Varneskov, 2013. "Unit roots, non-linearities and structural breaks," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 4, pages 61-94, Edward Elgar Publishing.
    5. Virtanen, Timo & Tölö, Eero & Virén, Matti & Taipalus, Katja, 2016. "Use of unit root methods in early warning of financial crises," Bank of Finland Research Discussion Papers 27/2016, Bank of Finland.
    6. Herwartz, Helmut & Maxand, Simone & Walle, Yabibal M., 2017. "Heteroskedasticity-robust unit root testing for trending panels," University of Göttingen Working Papers in Economics 314, University of Goettingen, Department of Economics.
    7. B. da Silva Lopes, Artur C., 2005. "Finite sample effects of pure seasonal mean shifts on Dickey-Fuller tests," MPRA Paper 125, University Library of Munich, Germany, revised May 2006.
    8. Artur C. B. Da Silva Lopes, 2008. "Finite Sample Effects Of Pure Seasonal Mean Shifts On Dickey–Fuller Tests: A Simulation Study," Manchester School, University of Manchester, vol. 76(5), pages 528-538, September.
    9. Sven Otto, 2020. "Unit Root Testing with Slowly Varying Trends," Papers 2003.04066, arXiv.org, revised Aug 2020.
    10. Helmut Herwartz & Yabibal M. Walle, 2018. "A powerful wild bootstrap diagnosis of panel unit roots under linear trends and time-varying volatility," Computational Statistics, Springer, vol. 33(1), pages 379-411, March.
    11. Narayan, Paresh Kumar & Popp, Stephan, 2011. "An application of a new seasonal unit root test to inflation," International Review of Economics & Finance, Elsevier, vol. 20(4), pages 707-716, October.
    12. Skrobotov, Anton, 2020. "Survey on structural breaks and unit root tests," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 58, pages 96-141.
    13. Shaen Corbet & John W. Goodell & Samet Gunay & Kerem Kaskaloglu, 2023. "Are DeFi tokens a separate asset class from conventional cryptocurrencies?," Annals of Operations Research, Springer, vol. 322(2), pages 609-630, March.
    14. Joo-Yeon Hyun & Hyeong Ho Mun & Tae-Hwan Kim & Jinook Jeong, 2010. "The effect of a variance shift on the Breusch-Godfrey's LM test," Applied Economics Letters, Taylor & Francis Journals, vol. 17(4), pages 399-404.
    15. Funke, Michael & Tsang, Andrew & Zhu, Linxu, 2018. "Not all cities are alike: House price heterogeneity and the design of macro-prudential policies in China," BOFIT Discussion Papers 18/2018, Bank of Finland Institute for Emerging Economies (BOFIT).
    16. Popp, Stephan, 2007. "Modified seasonal unit root test with seasonal level shifts at unknown time," Economics Letters, Elsevier, vol. 97(2), pages 111-117, November.
    17. Hao Jin & Si Zhang & Jinsuo Zhang, 2017. "Spurious regression due to neglected of non-stationary volatility," Computational Statistics, Springer, vol. 32(3), pages 1065-1081, September.
    18. Mendez Parra, Maximiliano, 2015. "Seasonal Unit Roots and Structural Breaks in agricultural time series: Monthly exports and domestic supply in Argentina," MPRA Paper 63831, University Library of Munich, Germany, revised 06 Apr 2015.
    19. Westerlund, Joakim & Costantini, Mauro & Narayan, Paresh & Popp, Stephan, 2009. "Seasonal Unit Root Tests for Trending and Breaking Series with Application to Industrial Production," Working Papers in Economics 377, University of Gothenburg, Department of Economics.
    20. Virtanen, Timo & Tölö, Eero & Virén, Matti & Taipalus, Katja, 2017. "Use of unit root methods in early warning of financial crises," ESRB Working Paper Series 45, European Systemic Risk Board.
    21. D. Ventosa-Santaul a & M. G -Zald & F. H. Wallace, 2015. "The real exchange rate, regime changes and volatility shifts," Applied Economics, Taylor & Francis Journals, vol. 47(24), pages 2445-2454, May.
    22. Tomás Barrio & Mariam Camarero & Cecilio Tamarit, 2019. "Testing for Periodic Integration with a Changing Mean," Computational Economics, Springer;Society for Computational Economics, vol. 54(1), pages 45-75, June.

  60. Harvey, David I. & Mills, Terence C., 2002. "Common features in UK sectoral output," Economic Modelling, Elsevier, vol. 19(1), pages 91-104, January.

    Cited by:

    1. Christoph Schleicher & Francisco Barillas, 2005. "Common Trends and Common Cycles in Canadian Sectoral Output," Computing in Economics and Finance 2005 214, Society for Computational Economics.
    2. Harvey, David I. & Mills, Terence C., 2005. "Corrigendum to ''Common features in UK sectoral output'': [Economic Modelling 19 (2002) 91-104]," Economic Modelling, Elsevier, vol. 22(1), pages 207-211, January.
    3. Mills, Terence C. & Crafts, Nicholas F. R., 2004. "Sectoral output trends and cycles in Victorian Britain," Economic Modelling, Elsevier, vol. 21(2), pages 217-232, March.
    4. Narayan, Paresh Kumar & Thuraisamy, Kannan S., 2013. "Common trends and common cycles in stock markets," Economic Modelling, Elsevier, vol. 35(C), pages 472-476.

  61. David I. Harvey & Stephen J. Leybourne & Paul Newbold, 2001. "Innovational Outlier Unit Root Tests With an Endogenously Determined Break in Level," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 63(5), pages 559-575, December.

    Cited by:

    1. Kojo Menyah & Yemane Wolde-Rufael, 2012. "Wagner'S Law Revisited: A Note From South Africa," South African Journal of Economics, Economic Society of South Africa, vol. 80(2), pages 200-208, June.
    2. Junsoo Lee & Mark C. Strazicich, 2004. "Minimum LM Unit Root Test with One Structural Break," Working Papers 04-17, Department of Economics, Appalachian State University.
    3. David I. Harvey & Terence C. Mills, 2004. "Tests for Stationarity in Series with Endogenously Determined Structural Change," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(5), pages 863-894, December.
    4. Seong Yeon Chang & Pierre Perron, 2017. "Fractional Unit Root Tests Allowing for a Structural Change in Trend under Both the Null and Alternative Hypotheses," Econometrics, MDPI, vol. 5(1), pages 1-26, January.
    5. Amélie Charles & Olivier Darné, 2012. "Trends and random walks in macroeconomic time series: A reappraisal," Post-Print hal-00956937, HAL.
    6. Kim, Dukpa & Perron, Pierre, 2009. "Unit root tests allowing for a break in the trend function at an unknown time under both the null and alternative hypotheses," Journal of Econometrics, Elsevier, vol. 148(1), pages 1-13, January.
    7. Skrobotov, Anton, 2020. "Survey on structural breaks and unit root tests," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 58, pages 96-141.
    8. Popp, Stephan, 2007. "Identification of the true break date in innovational outlier unit root tests," IBES Diskussionsbeiträge 152, University of Duisburg-Essen, Institute of Business and Economic Studie (IBES).
    9. Josep Lluís Carrion‐i‐Silvestre & María Dolores Gadea, 2023. "Testing for multiple level shifts with an integrated or stationary noise component," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(6), pages 801-819, September.
    10. Popp, Stephan, 2007. "Modified seasonal unit root test with seasonal level shifts at unknown time," Economics Letters, Elsevier, vol. 97(2), pages 111-117, November.
    11. Mendez Parra, Maximiliano, 2015. "Seasonal Unit Roots and Structural Breaks in agricultural time series: Monthly exports and domestic supply in Argentina," MPRA Paper 63831, University Library of Munich, Germany, revised 06 Apr 2015.
    12. Banerjee, Anindya & Urga, Giovanni, 2005. "Modelling structural breaks, long memory and stock market volatility: an overview," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 1-34.
    13. Narayan, Paresh & Popp, Stephan, 2009. "A new unit root test with two structural breaks in level and slope at unknown time," Working Papers eco_2009_11, Deakin University, Department of Economics.
    14. Méndez Parra, Maximiliano, 2015. "Futures prices, trade and domestic supply of agricultural commodities," Economics PhD Theses 0115, Department of Economics, University of Sussex Business School.
    15. Luis C. Nunes, 2004. "LM-Type tests for a Unit Root Allowing for a Break in Trend," Econometric Society 2004 Australasian Meetings 190, Econometric Society.
    16. Harvey, David I. & Leybourne, Stephen J. & Newbold, Paul, 2002. "Seasonal unit root tests with seasonal mean shifts," Economics Letters, Elsevier, vol. 76(2), pages 295-302, July.
    17. Michael Princ, 2016. "Structural Distress Index: Structural Break Analysis of the Czech and Polish Stock Markets," European Financial and Accounting Journal, Prague University of Economics and Business, vol. 2016(3), pages 125-137.

  62. David I. Harvey & Stephen J. Leybourne & Paul Newbold, 2001. "Analysis of a panel of UK macroeconomic forecasts," Econometrics Journal, Royal Economic Society, vol. 4(1), pages 37-55.

    Cited by:

    1. Capistrán, Carlos & López-Moctezuma, Gabriel, 2014. "Forecast revisions of Mexican inflation and GDP growth," International Journal of Forecasting, Elsevier, vol. 30(2), pages 177-191.
    2. Jonas Dovern & Ulrich Fritsche & Jiri Slacalek, 2012. "Disagreement Among Forecasters in G7 Countries," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1081-1096, November.
    3. Jan-Egbert Sturm & Timo Wollmershäuser, 2008. "The Stress of Having a Single Monetary Policy in Europe," KOF Working papers 08-190, KOF Swiss Economic Institute, ETH Zurich.
    4. Kajal Lahiri & Gultekin Isiklar, 2010. "Estimating International Transmission of Shocks Using GDP Forecasts: India and Its Trading Partners," Discussion Papers 10-06, University at Albany, SUNY, Department of Economics.
    5. Jordi Pons-Novell, 2004. "Behavioural biases among interest rate forecasters?," Applied Economics Letters, Taylor & Francis Journals, vol. 11(5), pages 319-321.
    6. Isiklar, Gultekin & Lahiri, Kajal, 2007. "How far ahead can we forecast? Evidence from cross-country surveys," International Journal of Forecasting, Elsevier, vol. 23(2), pages 167-187.
    7. Gultekin Isiklar, 2004. "On aggregation bias in fixed-event forecast efficiency tests," Econometrics 0412011, University Library of Munich, Germany, revised 28 Dec 2004.
    8. Masahiro Ashiya, 2006. "Testing the rationality of forecast revisions made by the IMF and the OECD," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(1), pages 25-36.
    9. Isengildina, Olga & Irwin, Scott H. & Good, Darrel L., 2004. "Does The Market Anticipate Smoothing In Usda Crop Production Forecasts?," 2004 Annual meeting, August 1-4, Denver, CO 20145, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    10. Ager, Philipp & Kappler, Marcus & Osterloh, Steffen, 2007. "The Accuracy and Efficiency of the Consensus Forecasts: A Further Application and Extension of the Pooled Approach," ZEW Discussion Papers 07-058, ZEW - Leibniz Centre for European Economic Research.
    11. Stefan Günnel & Karl-Heinz Tödter, 2009. "Does Benford’s Law hold in economic research and forecasting?," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 36(3), pages 273-292, August.
    12. Chen, Qiwei & Costantini, Mauro & Deschamps, Bruno, 2016. "How accurate are professional forecasts in Asia? Evidence from ten countries," International Journal of Forecasting, Elsevier, vol. 32(1), pages 154-167.
    13. Harvey, David I. & Newbold, Paul, 2003. "The non-normality of some macroeconomic forecast errors," International Journal of Forecasting, Elsevier, vol. 19(4), pages 635-653.
    14. Gultekin Isiklar & Kajal Lahiri & Prakash Loungani, 2006. "How quickly do forecasters incorporate news? Evidence from cross‐country surveys," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(6), pages 703-725, September.
    15. Iregui, Ana María & Núñez, Héctor M. & Otero, Jesús, 2021. "Testing the efficiency of inflation and exchange rate forecast revisions in a changing economic environment," Journal of Economic Behavior & Organization, Elsevier, vol. 187(C), pages 290-314.
    16. Bruno Deschamps & Christos Ioannidis, 2014. "The Efficiency of Multivariate Macroeconomic Forecasts," Manchester School, University of Manchester, vol. 82(5), pages 509-523, September.
    17. Jonas Dovern & Johannes Weisser, 2009. "Accuracy, Unbiasedness and Efficiency of Professional Macroeconomic Forecasts: An empirical Comparison for the G7," Jena Economics Research Papers 2009-091, Friedrich-Schiller-University Jena.
    18. Jordi Pons-Novell, 2003. "Strategic bias, herding behaviour and economic forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(1), pages 67-77.
    19. Jordi Pons-Novell, 2006. "An analysis of a panel of Spanish GDP forecasts," Applied Economics, Taylor & Francis Journals, vol. 38(11), pages 1287-1292.
    20. Deschamps, Bruno & Ioannidis, Christos, 2013. "Can rational stubbornness explain forecast biases?," Journal of Economic Behavior & Organization, Elsevier, vol. 92(C), pages 141-151.
    21. Xiao, Jinzhi & Lence, Sergio H. & Hart, Chad, 2014. "Usda And Private Analysts' Forecasts Of Ending Stocks: How Good Are They?," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170642, Agricultural and Applied Economics Association.
    22. Lahiri, Kajal & Sheng, Xuguang, 2008. "Evolution of forecast disagreement in a Bayesian learning model," Journal of Econometrics, Elsevier, vol. 144(2), pages 325-340, June.

  63. David Harvey & Paul Newbold, 2000. "Tests for multiple forecast encompassing," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 471-482.

    Cited by:

    1. Christopher Gibbs, 2015. "Forecast Combination, Non-linear Dynamics, and the Macroeconomy," Discussion Papers 2015-05, School of Economics, The University of New South Wales.
    2. Manfredo, Mark R. & Sanders, Dwight R., 2003. "Minimum Variance Hedging And The Encompassing Principle: Assessing The Effectiveness Of Futures Hedges," 2003 Annual meeting, July 27-30, Montreal, Canada 22247, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    3. Kirstin Hubrich & Kenneth D. West, 2008. "Forecast Evaluation of Small Nested Model Sets," NBER Working Papers 14601, National Bureau of Economic Research, Inc.
    4. Kannika Duangnate & James W. Mjelde, 2020. "Prequential forecasting in the presence of structure breaks in natural gas spot markets," Empirical Economics, Springer, vol. 59(5), pages 2363-2384, November.
    5. Bentes, Sonia R. & Menezes, Rui, 2013. "On the predictability of realized volatility using feasible GLS," Journal of Asian Economics, Elsevier, vol. 28(C), pages 58-66.
    6. Curto, José Dias & Serrasqueiro, Pedro, 2022. "Averaging financial ratios," Finance Research Letters, Elsevier, vol. 48(C).
    7. Khalaf, Lynda & Saunders, Charles J., 2017. "Monte Carlo forecast evaluation with persistent data," International Journal of Forecasting, Elsevier, vol. 33(1), pages 1-10.
    8. Bessler, David & Kibriya, Shahriar & Chen, Junyi & Price, Ed, 2014. "On Forecasting Conflict in Sudan: 2009-2012," MPRA Paper 60069, University Library of Munich, Germany.
    9. Roccazzella, Francesco & Candelon, Bertrand, 2022. "Should we care about ECB inflation expectations?," LIDAM Discussion Papers LFIN 2022004, Université catholique de Louvain, Louvain Finance (LFIN).
    10. El-Shagi, Makram, 2011. "Inflation expectations: Does the market beat econometric forecasts?," The North American Journal of Economics and Finance, Elsevier, vol. 22(3), pages 298-319.
    11. Saša ŽIKOVIÆ & Randall K. FILER, 2013. "Ranking of VaR and ES Models: Performance in Developed and Emerging Markets," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(4), pages 327-359, August.
    12. Becker, Ralf & Clements, Adam E. & White, Scott I., 2006. "On the informational efficiency of S&P500 implied volatility," The North American Journal of Economics and Finance, Elsevier, vol. 17(2), pages 139-153, August.
    13. Gunter, Ulrich & Önder, Irem, 2016. "Forecasting city arrivals with Google Analytics," Annals of Tourism Research, Elsevier, vol. 61(C), pages 199-212.
    14. Siliverstovs, B. & van Dijk, D.J.C., 2003. "Forecasting industrial production with linear, nonlinear, and structural change models," Econometric Institute Research Papers EI 2003-16, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    15. Costantini, Mauro & Gunter, Ulrich & Kunst, Robert M., 2012. "Forecast Combination Based on Multiple Encompassing Tests in a Macroeconomic DSGE-VAR System," Economics Series 292, Institute for Advanced Studies.
    16. Rapach, David E. & Strauss, Jack K., 2012. "Forecasting US state-level employment growth: An amalgamation approach," International Journal of Forecasting, Elsevier, vol. 28(2), pages 315-327.
    17. Bos, Charles S. & Franses, Philip Hans & Ooms, Marius, 2002. "Inflation, forecast intervals and long memory regression models," International Journal of Forecasting, Elsevier, vol. 18(2), pages 243-264.
    18. Daniel Andrés Jaimes Cárdenas & jair Ojeda Joya, 2010. "Reglas de Taylor y previsibilidad fuera de muestra de la tasa de cambio en Latinoamérica," Borradores de Economia 7308, Banco de la Republica.
    19. Renee van Eyden & Goodness C. Aye & Rangan Gupta, 2012. "Predictive Ability of Competing Models for South Africa’s Fixed Business Non- Residential Investment Spending," Working Papers 201229, University of Pretoria, Department of Economics.
    20. David I. Harvey & Stephen J. Leybourne & Emily J. Whitehouse, 2017. "Forecast evaluation tests and negative long-run variance estimates in small samples," Discussion Papers 17/03, University of Nottingham, Granger Centre for Time Series Econometrics.
    21. Frommel, Michael & MacDonald, Ronald & Menkhoff, Lukas, 2005. "Markov switching regimes in a monetary exchange rate model," Economic Modelling, Elsevier, vol. 22(3), pages 485-502, May.
    22. Becker, Ralf & Clements, Adam E. & White, Scott I., 2007. "Does implied volatility provide any information beyond that captured in model-based volatility forecasts?," Journal of Banking & Finance, Elsevier, vol. 31(8), pages 2535-2549, August.
    23. Franses, Ph.H.B.F., 2008. "Model selection for forecast combination," Econometric Institute Research Papers EI 2008-11, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    24. Duangnate, Kannika & Mjelde, James W., 2017. "Comparison of data-rich and small-scale data time series models generating probabilistic forecasts: An application to U.S. natural gas gross withdrawals," Energy Economics, Elsevier, vol. 65(C), pages 411-423.
    25. Christian Gourieroux & Wei Liu, 2009. "Control and Out‐of‐Sample Validation of Dependent Risks," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 76(3), pages 683-707, September.
    26. Harvey, David I. & Newbold, Paul, 2003. "The non-normality of some macroeconomic forecast errors," International Journal of Forecasting, Elsevier, vol. 19(4), pages 635-653.
    27. José Dias Curto & João Tomaz & José Castro Pinto, 2009. "A new approach to bad news effects on volatility: the multiple-sign-volume sensitive regime EGARCH model (MSV-EGARCH)," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 8(1), pages 23-36, April.
    28. Håvard Hungnes, 2020. "Equal predictability test for multi-step-ahead system forecasts invariant to linear transformations," Discussion Papers 931, Statistics Norway, Research Department.
    29. Pedro Pires Ribeiro & José Dias Curto, 2018. "How do zero-coupon inflation swaps predict inflation rates in the euro area? Evidence of efficiency and accuracy on 1-year contracts," Empirical Economics, Springer, vol. 54(4), pages 1451-1475, June.
    30. Costantini, Mauro & Pappalardo, Carmine, 2010. "A hierarchical procedure for the combination of forecasts," International Journal of Forecasting, Elsevier, vol. 26(4), pages 725-743, October.
    31. Zijun Wang, 2010. "Directed graphs, information structure and forecast combinations: an empirical examination of US unemployment rates," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(4), pages 353-366.
    32. Bentes, Sónia R., 2015. "A comparative analysis of the predictive power of implied volatility indices and GARCH forecasted volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 105-112.
    33. Antonis Michis, 2012. "Monitoring Forecasting Combinations with Semiparametric Regression Models," Working Papers 2012-2, Central Bank of Cyprus.
    34. Mark E. Wohar & David E. Rapach, 2007. "Forecasting the recent behavior of US business fixed investment spending: an analysis of competing models This is a significantly revised version of our previous paper, 'Forecasting US Business Fixed ," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(1), pages 33-51.
    35. Anthony H. Tu & Cathy Yi-Hsuan Chen, 2016. "What Derives the Bond Portfolio Value-at-Risk: Information Roles of Macroeconomic and Financial Stress Factors," SFB 649 Discussion Papers SFB649DP2016-006, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    36. Timo Dimitriadis & Xiaochun Liu & Julie Schnaitmann, 2020. "Encompassing Tests for Value at Risk and Expected Shortfall Multi-Step Forecasts based on Inference on the Boundary," Papers 2009.07341, arXiv.org.
    37. Sanders, Dwight R. & Manfredo, Mark R. & Boris, Keith, 2009. "Evaluating information in multiple horizon forecasts: The DOE's energy price forecasts," Energy Economics, Elsevier, vol. 31(2), pages 189-196.
    38. Şener, Emrah & Baronyan, Sayad & Ali Mengütürk, Levent, 2012. "Ranking the predictive performances of value-at-risk estimation methods," International Journal of Forecasting, Elsevier, vol. 28(4), pages 849-873.
    39. Daniel Andrés Jaimes Cárdenas & Jair Ojeda Joya, 2010. "Reglas de Taylor y previsibilidad fuera de muestra de la tasa de cambio en Latinoamérica," Borradores de Economia 619, Banco de la Republica de Colombia.
    40. David Bessler & Zijun Wang, 2012. "D-separation, forecasting, and economic science: a conjecture," Theory and Decision, Springer, vol. 73(2), pages 295-314, August.
    41. Sanders, Dwight R. & Manfredo, Mark R., 2004. "Predicting Pork Supplies: An Application of Multiple Forecast Encompassing," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 36(3), pages 605-615, December.
    42. Dimitriadis, Timo & Schnaitmann, Julie, 2021. "Forecast encompassing tests for the expected shortfall," International Journal of Forecasting, Elsevier, vol. 37(2), pages 604-621.
    43. Mauro Costantini & Ulrich Gunter & Robert M. Kunst, 2017. "Forecast Combinations in a DSGE‐VAR Lab," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(3), pages 305-324, April.
    44. Clements, Michael P. & Harvey, David I., 2011. "Combining probability forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 208-223.
    45. Håvard Hungnes, 2018. "Encompassing tests for evaluating multi-step system forecasts invariant to linear transformations," Discussion Papers 871, Statistics Norway, Research Department.
    46. Glynn Tonsor & Ted Schroeder, 2011. "Multivariate forecasting of a commodity portfolio: application to cattle feeding margins and risk," Applied Economics, Taylor & Francis Journals, vol. 43(11), pages 1329-1339.
    47. Timo Dimitriadis & Julie Schnaitmann, 2019. "Forecast Encompassing Tests for the Expected Shortfall," Papers 1908.04569, arXiv.org, revised Aug 2020.
    48. Sanders, Dwight R. & Manfredo, Mark R., 2002. "Usda Production Forecasts For Pork, Beef, And Broilers: An Evaluation," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 27(1), pages 1-14, July.
    49. Joseph, Andreas & Kalamara, Eleni & Kapetanios, George & Potjagailo, Galina & Chakraborty, Chiranjit, 2021. "Forecasting UK inflation bottom up," Bank of England working papers 915, Bank of England, revised 27 Sep 2022.
    50. Manfredo, Mark R. & Richards, Timothy J., 2005. "Hedging Yield with Weather Derivatives: A Role for Options," 2005 Annual meeting, July 24-27, Providence, RI 19369, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    51. Manfredo, Mark R. & Sanders, Dwight R., 2004. "Forecast Encompassing And Futures Market Efficiency: The Case Of Milk Futures," 2004 Annual meeting, August 1-4, Denver, CO 20267, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    52. Sanders, Dwight R. & Manfredo, Mark R., 2004. "Comparing Hedging Effectiveness: An Application of the Encompassing Principle," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 29(1), pages 1-14, April.

  64. Harvey, David I & Leybourne, Stephen J & Newbold, Paul, 1998. "Tests for Forecast Encompassing," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 254-259, April.

    Cited by:

    1. Brent Meyer & Guhan Venkatu, 2012. "Trimmed-mean inflation statistics: just hit the one in the middle," Working Papers (Old Series) 1217, Federal Reserve Bank of Cleveland.
    2. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    3. David Rapach & Jack Strauss, 2010. "Bagging or Combining (or Both)? An Analysis Based on Forecasting U.S. Employment Growth," Econometric Reviews, Taylor & Francis Journals, vol. 29(5-6), pages 511-533.
    4. Mario Porqueddu & Fabrizio Venditti, 2012. "Do food commodity prices have asymmetric effects on Euro-Area inflation?," Temi di discussione (Economic working papers) 878, Bank of Italy, Economic Research and International Relations Area.
    5. Christos Bouras & Christina Christou & Rangan Gupta & Keagile Lesame, 2020. "Forecasting State- and MSA-Level Housing Returns of the US: The Role of Mortgage Default Risks," Working Papers 202037, University of Pretoria, Department of Economics.
    6. Norman R. Swanson & Nii Ayi Armah, 2011. "Predictive Inference Under Model Misspecification with an Application to Assessing the Marginal Predictive Content of Money for Output," Departmental Working Papers 201103, Rutgers University, Department of Economics.
    7. João Valle e Azevedo & Ana Pereira, 2008. "Approximating and Forecasting Macroeconomic Signals in Real-Time," Working Papers w200819, Banco de Portugal, Economics and Research Department.
    8. Thorsten Egelkraut & Philip Garcia & Bruce Sherrick, 2007. "Options-based forecasts of futures prices in the presence of limit moves," Applied Economics, Taylor & Francis Journals, vol. 39(2), pages 145-152.
    9. Julien Champagne & Guillaume Poulin‐Bellisle & Rodrigo Sekkel, 2020. "Introducing the Bank of Canada staff economic projections database," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 114-129, January.
    10. Siddhartha S. Bora & Ani L. Katchova & Todd H. Kuethe, 2023. "The accuracy and informativeness of agricultural baselines," American Journal of Agricultural Economics, John Wiley & Sons, vol. 105(4), pages 1116-1148, August.
    11. Bergman, U. Michael & Hansson, Jesper, 1999. "Real Exchange Rates and Switching Regimes," Working Papers 1999:4, Lund University, Department of Economics, revised 08 Jun 2000.
    12. Breitung Jörg, 2008. "Assessing the Rationality of Survey Expectations: The Probability Approach," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 228(5-6), pages 630-643, October.
    13. Snowberg, Erik & Wolfers, Justin & Zitzewitz, Eric, 2012. "Prediction Markets for Economic Forecasting," IZA Discussion Papers 6720, Institute of Labor Economics (IZA).
    14. Robert Lehmann, 2016. "Economic Growth and Business Cycle Forecasting at the Regional Level," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 65.
    15. Galvão, Ana Beatriz, 2013. "Changes in predictive ability with mixed frequency data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 395-410.
    16. Xi Dong & Yan Li & David E. Rapach & Guofu Zhou, 2022. "Anomalies and the Expected Market Return," Journal of Finance, American Finance Association, vol. 77(1), pages 639-681, February.
    17. Manfredo, Mark R. & Sanders, Dwight R., 2003. "Minimum Variance Hedging And The Encompassing Principle: Assessing The Effectiveness Of Futures Hedges," 2003 Annual meeting, July 27-30, Montreal, Canada 22247, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    18. Amélie Charles & Olivier Darné & Jae H. Kim, 2022. "Stock return predictability: Evaluation based on interval forecasts," Bulletin of Economic Research, Wiley Blackwell, vol. 74(2), pages 363-385, April.
    19. Francesco D’Amuri & Juri Marcucci, 2010. "“Google it!”Forecasting the US Unemployment Rate with a Google Job Search index," Working Papers 2010.31, Fondazione Eni Enrico Mattei.
    20. Thomas A. Knetsch, 2004. "Evaluating the German Inventory Cycle – Using Data from the Ifo Business Survey," CESifo Working Paper Series 1202, CESifo.
    21. Goodness C. Aye & Stephen M. Miller & Rangan Gupta & Mehmet Balcilar, 2013. "Forecasting the US Real Private Residential Fixed Investment Using Large Number of Predictors," Working Papers 201348, University of Pretoria, Department of Economics.
    22. Jondeau, Eric & Zhang, Qunzi & Zhu, Xiaoneng, 2019. "Average skewness matters," Journal of Financial Economics, Elsevier, vol. 134(1), pages 29-47.
    23. Pierre-Olivier Gourinchas & Hélène Rey, 2007. "International Financial Adjustment," Journal of Political Economy, University of Chicago Press, vol. 115(4), pages 665-703, August.
    24. Qin, Duo & He, Xinhua, 2012. "Modelling the impact of aggregate financial shocks external to the Chinese economy," BOFIT Discussion Papers 25/2012, Bank of Finland Institute for Emerging Economies (BOFIT).
    25. Theologos Dergiades & Apostolos Dasilas, 2010. "Modelling and forecasting mobile telecommunication services: the case of Greece," Applied Economics Letters, Taylor & Francis Journals, vol. 17(18), pages 1823-1828.
    26. Fildes, Robert & Stekler, Herman, 2002. "The state of macroeconomic forecasting," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 435-468, December.
    27. Todd E. Clark & Michael W. McCracken, 2001. "Evaluating long-horizon forecasts," Research Working Paper RWP 01-14, Federal Reserve Bank of Kansas City.
    28. Massimiliano Kaucic, 2009. "Predicting EU Energy Industry Excess Returns on EU Market Index via a Constrained Genetic Algorithm," Computational Economics, Springer;Society for Computational Economics, vol. 34(2), pages 173-193, September.
    29. Kieran Burgess & Nicholas Rohde, 2013. "Can Exchange Rates Forecast Commodity Prices? Recent Evidence using Australian Data," Economics Bulletin, AccessEcon, vol. 33(1), pages 511-518.
    30. Constantin Burgi, 2016. "What Do We Lose When We Average Expectations?," Working Papers 2016-013, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    31. Faria, Gonçalo & Verona, Fabio, 2017. "Forecasting the equity risk premium with frequency-decomposed predictors," Bank of Finland Research Discussion Papers 1/2017, Bank of Finland.
    32. Todd E. Clark, 2004. "Can out-of-sample forecast comparisons help prevent overfitting?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(2), pages 115-139.
    33. Dai, Zhifeng & Kang, Jie & Hu, Yangli, 2021. "Efficient predictability of oil price: The role of number of IPOs and U.S. dollar index," Resources Policy, Elsevier, vol. 74(C).
    34. Michael P. Clements & Philip Hans Franses & Norman R. Swanson, 2003. "Forecasting economic and financial time-series with non-linear models," Departmental Working Papers 200309, Rutgers University, Department of Economics.
    35. Manabu Asai & Michael McAleer & Marcelo C. Medeiros, 2011. "Modelling and Forecasting Noisy Realized Volatility," KIER Working Papers 758, Kyoto University, Institute of Economic Research.
    36. Mönch, Emanuel & Stein, Tobias, 2021. "Equity premium predictability over the business cycle," Discussion Papers 25/2021, Deutsche Bundesbank.
    37. Hyung, N. & Franses, Ph.H.B.F., 2001. "Structural breaks and long memory in US inflation rates: do they matter for forecasting?," Econometric Institute Research Papers EI 2001-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    38. Goodhead, Robert & Kolb, Benedikt, 2018. "Monetary policy communication shocks and the macroeconomy," Discussion Papers 46/2018, Deutsche Bundesbank.
    39. Zhenni Ding & Huayou Chen & Ligang Zhou, 2023. "Using shapely values to define subgroups of forecasts for combining," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 905-923, July.
    40. Mawuli Segnon & Stelios Bekiros, 2020. "Forecasting volatility in bitcoin market," Annals of Finance, Springer, vol. 16(3), pages 435-462, September.
    41. Giancarlo Bruno, 2008. "Forecasting Using Functional Coefficients Autoregressive Models," ISAE Working Papers 98, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
    42. Christian Schulz, 2007. "Forecasting economic growth for Estonia : application of common factor methodologies," Bank of Estonia Working Papers 2007-09, Bank of Estonia, revised 04 Sep 2007.
    43. Paul Hubert, 2015. "Revisiting the greenbook's relative forecasting performance," Post-Print hal-01087522, HAL.
    44. Martin Lettau & Sydney C. Ludvigson, 1999. "Consumption, aggregate wealth and expected stock returns," Staff Reports 77, Federal Reserve Bank of New York.
    45. Stavroula Yfanti & Georgios Chortareas & Menelaos Karanasos & Emmanouil Noikokyris, 2022. "A three‐dimensional asymmetric power HEAVY model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 2737-2761, July.
    46. Eliana González, 2010. "Bayesian Model Averaging. An Application to Forecast Inflation in Colombia," Borradores de Economia 7015, Banco de la Republica.
    47. Elena Andreou & Eric Ghysels & Andros Kourtellos, 2010. "Should macroeconomic forecasters use daily financial data and how?," University of Cyprus Working Papers in Economics 09-2010, University of Cyprus Department of Economics.
    48. Koeda, Junko, 2013. "Endogenous monetary policy shifts and the term structure: Evidence from Japanese government bond yields," Journal of the Japanese and International Economies, Elsevier, vol. 29(C), pages 170-188.
    49. Cerrato, Mario & Sarantis, Nicholas & Saunders, Alex, 2010. "An investigation of customer order flow in the foreign exchange market," SIRE Discussion Papers 2010-11, Scottish Institute for Research in Economics (SIRE).
    50. Timo Teräsvirta & Dick van Dijk & Marcelo Cunha Medeiros, 2004. "Linear models, smooth transition autoregressions and neural networks for forecasting macroeconomic time series: A reexamination," Textos para discussão 485, Department of Economics PUC-Rio (Brazil).
    51. Clark, Todd & McCracken, Michael, 2013. "Advances in Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1107-1201, Elsevier.
    52. Eric Jondeau & Xuewu Wang & Zhipeng Yan & Qunzi Zhang, 2020. "Skewness and index futures return," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(11), pages 1648-1664, November.
    53. Catherine L. Kling & Raymond W. Arritt & Gray Calhoun & David A. Keiser, 2016. "Research Needs and Challenges in the FEW System: Coupling Economic Models with Agronomic, Hydrologic, and Bioenergy Models for Sustainable Food, Energy, and Water Systems," Center for Agricultural and Rural Development (CARD) Publications 16-wp563, Center for Agricultural and Rural Development (CARD) at Iowa State University.
    54. Rafal Weron, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," HSC Research Reports HSC/14/07, Hugo Steinhaus Center, Wroclaw University of Technology.
    55. Mills, Terence C. & Pepper, Gordon T., 1999. "Assessing the forecasters: an analysis of the forecasting records of the Treasury, the London Business School and the National Institute," International Journal of Forecasting, Elsevier, vol. 15(3), pages 247-257, July.
    56. Kaufmann, Daniel & Scheufele, Rolf, 2017. "Business tendency surveys and macroeconomic fluctuations," International Journal of Forecasting, Elsevier, vol. 33(4), pages 878-893.
    57. David Bivin, 2005. "Gauging the performance of the linear-quadratic inventory model," Applied Economics, Taylor & Francis Journals, vol. 37(11), pages 1215-1231.
    58. Bentes, Sonia R. & Menezes, Rui, 2013. "On the predictability of realized volatility using feasible GLS," Journal of Asian Economics, Elsevier, vol. 28(C), pages 58-66.
    59. Héctor Mauricio Nunez Amortegui, 2005. "Una evaluación de los pronósticos de inflación en Colombia bajo el esquema de inflación objetivo," Revista de Economía del Rosario, Universidad del Rosario, December.
    60. Nowotarski, Jakub & Weron, Rafał, 2018. "Recent advances in electricity price forecasting: A review of probabilistic forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1548-1568.
    61. Dandan Liu, 2011. "Learning and Estimation of the New Keynesian Phillips Curve Models," Southern Economic Journal, John Wiley & Sons, vol. 78(2), pages 382-396, October.
    62. Gomez, Miguel I. & Gonzalez, Eliana & Melo, Luis F. & Torres, Jose L., 2006. "Forecasting Food Price Inflation, Challenges for Central Banks in Developing Countries using an Inflation Targeting Framework: the Case of Colombia," 2006 Annual meeting, July 23-26, Long Beach, CA 21181, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    63. Boriss Siliverstovs, 2011. "The Real-Time Predictive Content of the KOF Economic Barometer," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 147(III), pages 353-375, September.
    64. Ruipeng Liu & Rangan Gupta, 2020. "Investors' Uncertainty and Forecasting Stock Market Volatility," Working Papers 202090, University of Pretoria, Department of Economics.
    65. Guillaume Chevillon, 2007. "Direct Multi‐Step Estimation And Forecasting," Journal of Economic Surveys, Wiley Blackwell, vol. 21(4), pages 746-785, September.
    66. Amélie Charles & Olivier Darné & Jae H. Kim, 2016. "Stock Return Predictability: Evaluation based on prediction intervals," Working Papers hal-01295037, HAL.
    67. Tierney, Heather L.R., 2010. "Real-Time Data Revisions and the PCE Measure of Inflation," MPRA Paper 22387, University Library of Munich, Germany, revised Apr 2010.
    68. Maxym Kryshko & Frank Schorfheide & Keith Sill, 2008. "DSGE model-based forecasting of non-modelled variables," Working Papers 08-17, Federal Reserve Bank of Philadelphia.
    69. Segnon, Mawuli & Lux, Thomas & Gupta, Rangan, 2015. "Modeling and Forecasting Carbon Dioxide Emission Allowance Spot Price Volatility: Multifractal vs. GARCH-type Volatility Models," FinMaP-Working Papers 46, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    70. Katja Drechsel & Dr. Rolf Scheufele, 2012. "Bottom-up or Direct? Forecasting German GDP in a Data-rich Environment," Working Papers 2012-16, Swiss National Bank.
    71. Boucher, Christophe, 2006. "Stock prices-inflation puzzle and the predictability of stock market returns," Economics Letters, Elsevier, vol. 90(2), pages 205-212, February.
    72. Sarantis, Nicholas, 2006. "On the short-term predictability of exchange rates: A BVAR time-varying parameters approach," Journal of Banking & Finance, Elsevier, vol. 30(8), pages 2257-2279, August.
    73. Wang, Rudan & Morley, Bruce & Stamatogiannis, Michalis P., 2019. "Forecasting the exchange rate using nonlinear Taylor rule based models," International Journal of Forecasting, Elsevier, vol. 35(2), pages 429-442.
    74. Camila Figueroa & Michael Pedersen, 2017. "Forecasting Demand for Denominations of Chilean Coins and Banknotes," Working Papers Central Bank of Chile 799, Central Bank of Chile.
    75. Pincheira, Pablo M. & West, Kenneth D., 2016. "A comparison of some out-of-sample tests of predictability in iterated multi-step-ahead forecasts," Research in Economics, Elsevier, vol. 70(2), pages 304-319.
    76. Biao Guo & Hai Lin, 2020. "Volatility and jump risk in option returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(11), pages 1767-1792, November.
    77. Daniel L. Thornton, 2005. "Predictions of short-term rates and the expectations hypothesis of the term structure of interest rates," Working Papers 2004-010, Federal Reserve Bank of St. Louis.
    78. Franses, Ph.H.B.F. & van Dijk, D.J.C., 2001. "The forecasting performance of various models for seasonality and nonlinearity for quarterly industrial production," Econometric Institute Research Papers EI 2001-14, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    79. Luciana Juvenal & Ivan Petrella, 2012. "Speculation in the oil market," Economic Synopses, Federal Reserve Bank of St. Louis.
    80. Michael P. Clements & David I. Harvey, 2010. "Forecast encompassing tests and probability forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(6), pages 1028-1062.
    81. Junko Koeda, 2010. "How Does Yield Curve Predict GDP Growth? A Macro-Finance Approach Revisited," CARF F-Series CARF-F-237, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo, revised Jan 2011.
    82. Saša ŽIKOVIÆ & Randall K. FILER, 2013. "Ranking of VaR and ES Models: Performance in Developed and Emerging Markets," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(4), pages 327-359, August.
    83. Magnus Kvåle Helliesen & Håvard Hungnes & Terje Skjerpen, 2022. "Revisions in the Norwegian National Accounts: accuracy, unbiasedness and efficiency in preliminary figures," Empirical Economics, Springer, vol. 62(3), pages 1079-1121, March.
    84. Amit Goyal & Ivo Welch, 2002. "Predicting the Equity Premium With Dividend Ratios," NBER Working Papers 8788, National Bureau of Economic Research, Inc.
    85. Bergman, U. Michael & Hansson, Jesper, 2005. "Real exchange rates and switching regimes," Journal of International Money and Finance, Elsevier, vol. 24(1), pages 121-138, February.
    86. Brand, Claus & Reimers, Hans-Eggert & Seitz, Franz, 2003. "Forecasting real GDP: what role for narrow money?," Working Paper Series 254, European Central Bank.
    87. Hai Lin & Chunchi Wu & Guofu Zhou, 2018. "Forecasting Corporate Bond Returns with a Large Set of Predictors: An Iterated Combination Approach," Management Science, INFORMS, vol. 64(9), pages 4218-4238, September.
    88. Daniel Borup & Erik Christian Montes Schütte, 2019. "In search of a job: Forecasting employment growth using Google Trends," CREATES Research Papers 2019-13, Department of Economics and Business Economics, Aarhus University.
    89. Ruan, Qingsong & Wang, Zilin & Zhou, Yaping & Lv, Dayong, 2020. "A new investor sentiment indicator (ISI) based on artificial intelligence: A powerful return predictor in China," Economic Modelling, Elsevier, vol. 88(C), pages 47-58.
    90. Robert Lehmann & Klaus Wohlrabe, 2013. "Forecasting gross value-added at the regional level: Are sectoral disaggregated predictions superior to direct ones?," ifo Working Paper Series 171, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    91. Heinisch, Katja, 2016. "A real-time analysis on the importance of hard and soft data for nowcasting German GDP," VfS Annual Conference 2016 (Augsburg): Demographic Change 145864, Verein für Socialpolitik / German Economic Association.
    92. Altug, Sumru & Çakmaklı, Cem, 2015. "Forecasting Inflation using Survey Expectations and Target Inflation: Evidence for Brazil and Turkey," CEPR Discussion Papers 10419, C.E.P.R. Discussion Papers.
    93. Lu, Fei & Ma, Feng & Guo, Qiang, 2023. "Less is more? New evidence from stock market volatility predictability," International Review of Financial Analysis, Elsevier, vol. 89(C).
    94. Ricardo M. Sousa, 2005. "Consumption, (Dis) Aggregate Wealth and Asset Returns," NIPE Working Papers 9/2005, NIPE - Universidade do Minho.
    95. Chatterjee, Ujjal K., 2015. "Bank liquidity creation and asset market liquidity," Journal of Financial Stability, Elsevier, vol. 18(C), pages 139-153.
    96. Lu, Xinjie & Ma, Feng & Wang, Tianyang & Wen, Fenghua, 2023. "International stock market volatility: A data-rich environment based on oil shocks," Journal of Economic Behavior & Organization, Elsevier, vol. 214(C), pages 184-215.
    97. Evelyn V. Colino & Scott H. Irwin, 2010. "Outlook vs. Futures: Three Decades of Evidence in Hog and Cattle Markets," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 92(1), pages 1-15.
    98. Pablo Pincheira, 2012. "Are Forecast Combinations Efficient?," Working Papers Central Bank of Chile 661, Central Bank of Chile.
    99. Rangan Gupta & Patrick T. Kanda & Mampho P. Modise & Alessia Paccagnini, 2015. "DSGE model-based forecasting of modelled and nonmodelled inflation variables in South Africa," Applied Economics, Taylor & Francis Journals, vol. 47(3), pages 207-221, January.
    100. Clements, Adam & Liao, Yin, 2017. "Forecasting the variance of stock index returns using jumps and cojumps," International Journal of Forecasting, Elsevier, vol. 33(3), pages 729-742.
    101. Duo Qin & Sophie van Huellen & Qing Chao Wang & Thanos Moraitis, 2022. "Algorithmic Modelling of Financial Conditions for Macro Predictive Purposes: Pilot Application to USA Data," Econometrics, MDPI, vol. 10(2), pages 1-22, April.
    102. Forni, Mario & Gambetti, Luca, 2011. "Testing for Sufficient Information in Structural VARs," CEPR Discussion Papers 8209, C.E.P.R. Discussion Papers.
    103. Turgut Kisinbay & Chikako Baba, 2011. "Predicting Recessions: A New Approach for Identifying Leading Indicators and Forecast Combinations," IMF Working Papers 2011/235, International Monetary Fund.
    104. Rui HAO, 2007. "Sources of income differences across Chinese provinces during the reform period: a development accounting exercise," Working Papers 200723, CERDI.
    105. Fischer, B. & Lenza, M. & Pill, H. & Reichlin, L., 2009. "Monetary analysis and monetary policy in the euro area 1999-2006," Journal of International Money and Finance, Elsevier, vol. 28(7), pages 1138-1164, November.
    106. Daniel Roash & Tanya Suhoy, 2019. "Sentiment Indicators Based on a Short Business Tendency Survey," Bank of Israel Working Papers 2019.11, Bank of Israel.
    107. Javier Giner & Sandra Morini & Rafael Rosillo, 2016. "Optimal Prediction Periods for New and Old Volatility Indexes in USA and German Markets," Computational Economics, Springer;Society for Computational Economics, vol. 47(4), pages 527-549, April.
    108. Wang, Yudong & Pan, Zhiyuan & Liu, Li & Wu, Chongfeng, 2019. "Oil price increases and the predictability of equity premium," Journal of Banking & Finance, Elsevier, vol. 102(C), pages 43-58.
    109. Guglielmo Maria Caporale & Menelaos Karanasos & Stavroula Yfanti, 2024. "Macro‐financial linkages in the high‐frequency domain: Economic fundamentals and the Covid‐induced uncertainty channel in US and UK financial markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(2), pages 1581-1608, April.
    110. Siliverstovs, B. & van Dijk, D.J.C., 2003. "Forecasting industrial production with linear, nonlinear, and structural change models," Econometric Institute Research Papers EI 2003-16, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    111. Paul Hubert, 2010. "Monetary policy, imperfect information and the expectations channel [Politique monétaire,information imparfaite et canal des anticipations]," SciencePo Working papers Main tel-04095385, HAL.
    112. Liu, Dandan & Smith, Julie K., 2014. "Inflation forecasts and core inflation measures: Where is the information on future inflation?," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(1), pages 133-137.
    113. Luiz Renato Lima & Lucas Lúcio Godeiro, 2023. "Equity‐premium prediction: Attention is all you need," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(1), pages 105-122, January.
    114. Alberto Baffigi & Roberto Golinelli & Giuseppe Parigi, 2002. "Real-time GDP forecasting in the euro area," Temi di discussione (Economic working papers) 456, Bank of Italy, Economic Research and International Relations Area.
    115. Lin, Qi, 2018. "Technical analysis and stock return predictability: An aligned approach," Journal of Financial Markets, Elsevier, vol. 38(C), pages 103-123.
    116. Buncic, Daniel & Tischhauser, Martin, 2015. "Macroeconomic Factors and Equity Premium Predictability," Economics Working Paper Series 1522, University of St. Gallen, School of Economics and Political Science.
    117. Kilian, Lutz & Inoue, Atsushi, 2002. "In-Sample or Out-of-Sample Tests of Predictability: Which One Should We Use?," CEPR Discussion Papers 3671, C.E.P.R. Discussion Papers.
    118. Rapach, David E. & Wohar, Mark E., 2006. "The out-of-sample forecasting performance of nonlinear models of real exchange rate behavior," International Journal of Forecasting, Elsevier, vol. 22(2), pages 341-361.
    119. Bryant, Henry L. & Haigh, Michael S., 2001. "Estimating Actual Bid-Ask Spreads In Commodity Futures Markets," 2001 Annual meeting, August 5-8, Chicago, IL 20707, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    120. Dr. Sandra Hanslin Grossmann & Dr. Rolf Scheufele, 2016. "Foreign PMIs: A reliable indicator for exports?," Working Papers 2016-01, Swiss National Bank.
    121. Pincheira, Pablo & Hardy, Nicolas, 2018. "Forecasting Base Metal Prices with Commodity Currencies," MPRA Paper 83564, University Library of Munich, Germany.
    122. Christian Conrad, 2007. "Non-negativity Conditions for the Hyperbolic GARCH Model," KOF Working papers 07-162, KOF Swiss Economic Institute, ETH Zurich.
    123. Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2019. "Forecasting the KOSPI200 spot volatility using various volatility measures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 156-166.
    124. Costantini, Mauro & Gunter, Ulrich & Kunst, Robert M., 2012. "Forecast Combination Based on Multiple Encompassing Tests in a Macroeconomic DSGE-VAR System," Economics Series 292, Institute for Advanced Studies.
    125. Stephan Jank, 2015. "Changes in the Composition of Publicly Traded Firms: Implications for the Dividend-Price Ratio and Return Predictability," Management Science, INFORMS, vol. 61(6), pages 1362-1377, June.
    126. Rapach, David E. & Strauss, Jack K., 2012. "Forecasting US state-level employment growth: An amalgamation approach," International Journal of Forecasting, Elsevier, vol. 28(2), pages 315-327.
    127. Bos, Charles S. & Franses, Philip Hans & Ooms, Marius, 2002. "Inflation, forecast intervals and long memory regression models," International Journal of Forecasting, Elsevier, vol. 18(2), pages 243-264.
    128. Todd E. Clark & Michael McCracken, 1999. "Tests of Equal Forecast Accuracy and Encompassing for Nested Models," Computing in Economics and Finance 1999 1241, Society for Computational Economics.
    129. Antonio Bassanetti & Michele Caivano & Alberto Locarno, 2010. "Modelling Italian potential output and the output gap," Temi di discussione (Economic working papers) 771, Bank of Italy, Economic Research and International Relations Area.
    130. Liu, Ruipeng & Lux, Thomas, 2017. "Generalized Method of Moment estimation of multivariate multifractal models," Economic Modelling, Elsevier, vol. 67(C), pages 136-148.
    131. Katja Heinisch & Rolf Scheufele, 2019. "Should Forecasters Use Real‐Time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence," German Economic Review, Verein für Socialpolitik, vol. 20(4), pages 170-200, November.
    132. Clark, Todd E. & West, Kenneth D., 2006. "Using out-of-sample mean squared prediction errors to test the martingale difference hypothesis," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 155-186.
    133. Hoang, Khoa & Cannavan, Damien & Huang, Ronghong & Peng, Xiaowen, 2021. "Predicting stock returns with implied cost of capital: A partial least squares approach," Journal of Financial Markets, Elsevier, vol. 53(C).
    134. Martens, Martin & van Dijk, Dick, 2007. "Measuring volatility with the realized range," Journal of Econometrics, Elsevier, vol. 138(1), pages 181-207, May.
    135. Hai Lin & Daniel Quill & Henk Berkman, 2016. "Information diffusion and the predictability of New Zealand stock market returns," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 56(3), pages 749-785, September.
    136. Eliana González & Miguel I. Gómez & Luis F. Melo & José Luis Torres, 2006. "Forecasting Food Price Inflation in Developing Countries with Inflation Targeting Regimes: the Colombian Case," Borradores de Economia 2735, Banco de la Republica.
    137. Zhang, Yaojie & Ma, Feng & Wang, Yudong, 2019. "Forecasting crude oil prices with a large set of predictors: Can LASSO select powerful predictors?," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 97-117.
    138. Dean Croushore & Simon van Norden, 2017. "Fiscal Surprises at the FOMC," CIRANO Working Papers 2017s-09, CIRANO.
    139. Conrad, Christian & Karanasos, Menelaos & Zeng, Ning, 2011. "Multivariate fractionally integrated APARCH modeling of stock market volatility: A multi-country study," Journal of Empirical Finance, Elsevier, vol. 18(1), pages 147-159, January.
    140. Zhao, Yang & Li, Jianping & Yu, Lean, 2017. "A deep learning ensemble approach for crude oil price forecasting," Energy Economics, Elsevier, vol. 66(C), pages 9-16.
    141. Jordan, Steven J. & Vivian, Andrew & Wohar, Mark E., 2014. "Sticky prices or economically-linked economies: The case of forecasting the Chinese stock market," Journal of International Money and Finance, Elsevier, vol. 41(C), pages 95-109.
    142. Chen, Long, 2009. "On the reversal of return and dividend growth predictability: A tale of two periods," Journal of Financial Economics, Elsevier, vol. 92(1), pages 128-151, April.
    143. Carstensen, Kai, 2007. "Is core money growth a good and stable inflation predictor in the euro area?," Kiel Working Papers 1318, Kiel Institute for the World Economy (IfW Kiel).
    144. Rafal Weron & Florian Ziel, 2018. "Electricity price forecasting," HSC Research Reports HSC/18/08, Hugo Steinhaus Center, Wroclaw University of Technology.
    145. Renee van Eyden & Goodness C. Aye & Rangan Gupta, 2012. "Predictive Ability of Competing Models for South Africa’s Fixed Business Non- Residential Investment Spending," Working Papers 201229, University of Pretoria, Department of Economics.
    146. Pincheira Brown, Pablo & Hardy, Nicolás, 2019. "Forecasting base metal prices with the Chilean exchange rate," Resources Policy, Elsevier, vol. 62(C), pages 256-281.
    147. Forni, Mario & Gambetti, Luca, 2014. "Sufficient information in structural VARs," Journal of Monetary Economics, Elsevier, vol. 66(C), pages 124-136.
    148. Hubrich, Kirstin & Granziera, Eleonora & Moon, Hyungsik Roger, 2013. "A predictability test for a small number of nested models," Working Paper Series 1580, European Central Bank.
    149. Zhu, Yanjian & Zhu, Xiaoneng, 2014. "European business cycles and stock return predictability," Finance Research Letters, Elsevier, vol. 11(4), pages 446-453.
    150. Bonham, Carl & Gangnes, Byron & Zhou, Ting, 2009. "Modeling tourism: A fully identified VECM approach," International Journal of Forecasting, Elsevier, vol. 25(3), pages 531-549, July.
    151. Boriss Siliverstovs & Konstantin A. Kholodilin, 2006. "On Selection of Components for a Diffusion Index Model: It's not the Size, It's How You Use It," Discussion Papers of DIW Berlin 598, DIW Berlin, German Institute for Economic Research.
    152. Kishor, N. Kundan, 2011. "Data revisions in India: Implications for monetary policy," Journal of Asian Economics, Elsevier, vol. 22(2), pages 164-173, April.
    153. Guo, Yangli & Ma, Feng & Li, Haibo & Lai, Xiaodong, 2022. "Oil price volatility predictability based on global economic conditions," International Review of Financial Analysis, Elsevier, vol. 82(C).
    154. Gelper, Sarah & Croux, Christophe, 2007. "Multivariate out-of-sample tests for Granger causality," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3319-3329, April.
    155. Chen, Shiu-Sheng & Chou, Yu-Hsi, 2015. "Revisiting the relationship between exchange rates and fundamentals," Journal of Macroeconomics, Elsevier, vol. 46(C), pages 1-22.
    156. He, Mengxi & Zhang, Yaojie & Wen, Danyan & Wang, Yudong, 2021. "Forecasting crude oil prices: A scaled PCA approach," Energy Economics, Elsevier, vol. 97(C).
    157. David I. Harvey & Stephen J. Leybourne & Emily J. Whitehouse, 2017. "Forecast evaluation tests and negative long-run variance estimates in small samples," Discussion Papers 17/03, University of Nottingham, Granger Centre for Time Series Econometrics.
    158. Todd E. Clark & Kenneth D. West, 2005. "Using Out-of-Sample Mean Squared Prediction Errors to Test the Martingale Difference," NBER Technical Working Papers 0305, National Bureau of Economic Research, Inc.
    159. Erlandsson, Ulf, 2002. "Regime Switches in Swedish Interest Rates," Working Papers 2002:5, Lund University, Department of Economics, revised 04 Mar 2005.
    160. Marshall, Ben R. & Nguyen, Nhut H. & Visaltanachoti, Nuttawat, 2021. "Beta estimation in New Zealand," Pacific-Basin Finance Journal, Elsevier, vol. 70(C).
    161. Carmine Pappalardo & Gianfranco Piras, 2004. "Vector-Autoregression Approach to Forecast Italian Imports," ISAE Working Papers 42, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
    162. Bessec Marie & Bouabdallah Othman, 2005. "What Causes The Forecasting Failure of Markov-Switching Models? A Monte Carlo Study," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(2), pages 1-24, June.
    163. Turgut Kısınbay, 2010. "Predictive ability of asymmetric volatility models at medium-term horizons," Applied Economics, Taylor & Francis Journals, vol. 42(30), pages 3813-3829.
    164. Christophe Boucher & Bertrand Maillet & Thierry Michel, 2008. "Do misalignments predict aggregated stock-market volatility?," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00307783, HAL.
    165. A. Girardi & R. Golinelli & C. Pappalardo, 2014. "The Role of Indicator Selection in Nowcasting Euro Area GDP in Pseudo Real Time," Working Papers wp919, Dipartimento Scienze Economiche, Universita' di Bologna.
    166. Khoa Hoang & Robert Faff, 2021. "Is the ex‐ante equity risk premium always positive? Evidence from a new conditional expectations model," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(1), pages 95-124, March.
    167. Morales-Arias, Leonardo & Moura, Guilherme V., 2013. "Adaptive forecasting of exchange rates with panel data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 493-509.
    168. Li, Yan & Ng, David T. & Swaminathan, Bhaskaran, 2013. "Predicting market returns using aggregate implied cost of capital," Journal of Financial Economics, Elsevier, vol. 110(2), pages 419-436.
    169. Brent Meyer & Saeed Zaman, 2016. "The Usefulness of the Median CPI in Bayesian VARs Used for Macroeconomic Forecasting and Policy," FRB Atlanta Working Paper 2016-13, Federal Reserve Bank of Atlanta.
    170. David Harvey & Paul Newbold, 2000. "Tests for multiple forecast encompassing," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 471-482.
    171. Nima Zarrabi & Stuart Snaith & Jerry Coakley, 2022. "Exchange rate forecasting using economic models and technical trading rules," The European Journal of Finance, Taylor & Francis Journals, vol. 28(10), pages 997-1018, July.
    172. Morales-Arias, Leonardo & Moura, Guilherme V., 2010. "A conditionally heteroskedastic global inflation model," Kiel Working Papers 1666, Kiel Institute for the World Economy (IfW Kiel).
    173. Ali Dib & Mohamed Gammoudi & Kevin Moran, 2006. "Forecasting Canadian Time Series With the New-Keynesian Model," Working Papers Central Bank of Chile 382, Central Bank of Chile.
    174. Martin Martens & Dick van Dijk & Michiel de Pooter, 2004. "Modeling and Forecasting S&P 500 Volatility: Long Memory, Structural Breaks and Nonlinearity," Tinbergen Institute Discussion Papers 04-067/4, Tinbergen Institute.
    175. Clark, Todd E. & McCracken, Michael W., 2005. "The power of tests of predictive ability in the presence of structural breaks," Journal of Econometrics, Elsevier, vol. 124(1), pages 1-31, January.
    176. Lin, Hai & Wang, Junbo & Wu, Chunchi, 2014. "Predictions of corporate bond excess returns," Journal of Financial Markets, Elsevier, vol. 21(C), pages 123-152.
    177. Sbrana, Giacomo & Silvestrini, Andrea & Venditti, Fabrizio, 2017. "Short-term inflation forecasting: The M.E.T.A. approach," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1065-1081.
    178. Becker, Ralf & Clements, Adam E. & White, Scott I., 2007. "Does implied volatility provide any information beyond that captured in model-based volatility forecasts?," Journal of Banking & Finance, Elsevier, vol. 31(8), pages 2535-2549, August.
    179. Nombulelo Gumata & Alain Kabundi & Eliphas Ndou, 2013. "Important channels of transmission of monetary policy shock in South Africa," Working Papers 6021, South African Reserve Bank.
    180. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    181. Odusami, Babatunde Olatunji, 2010. "To consume or not: How oil prices affect the comovement of consumption and aggregate wealth," Energy Economics, Elsevier, vol. 32(4), pages 857-867, July.
    182. Ming-Chih Lee & Chien-Liang Chiu & Wan-Hsiu Cheng, 2007. "Enhancing Forecast Accuracy By Using Long Estimation Periods," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 1(2), pages 1-9.
    183. Yang-Ho Park, 2019. "Information in Yield Spread Trades," Finance and Economics Discussion Series 2019-025, Board of Governors of the Federal Reserve System (U.S.).
    184. Faias, José Afonso, 2023. "Predicting the equity risk premium using the smooth cross-sectional tail risk: The importance of correlation," Journal of Financial Markets, Elsevier, vol. 63(C).
    185. Tierney, Heather L.R., 2013. "Forecasting and Tracking Real-Time Data Revisions in Inflation Persistence," MPRA Paper 53374, University Library of Munich, Germany, revised Nov 2013.
    186. van Dijk, D.J.C. & Franses, Ph.H.B.F., 2003. "Selecting a Nonlinear Time Series Model using Weighted Tests of Equal Forecast Accuracy," Econometric Institute Research Papers EI 2003-10, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    187. Zhang, Yaojie & Zeng, Qing & Ma, Feng & Shi, Benshan, 2019. "Forecasting stock returns: Do less powerful predictors help?," Economic Modelling, Elsevier, vol. 78(C), pages 32-39.
    188. Yang, Zihui & Zhao, Yongliang, 2014. "Energy consumption, carbon emissions, and economic growth in India: Evidence from directed acyclic graphs," Economic Modelling, Elsevier, vol. 38(C), pages 533-540.
    189. Konstantin A. Kholodilin & Boriss Siliverstovs & Stefan Kooths, 2007. "A Dynamic Panel Data Approach to the Forecasting of the GDP of German Länder," Discussion Papers of DIW Berlin 664, DIW Berlin, German Institute for Economic Research.
    190. Zhi Da & Ravi Jagannathan & Jianfeng Shen, 2014. "Growth Expectations, Dividend Yields, and Future Stock Returns," NBER Working Papers 20651, National Bureau of Economic Research, Inc.
    191. Mésonnier, J-S., 2006. "The Reliability of Macroeconomic Forecasts based on Real Interest Rate Gap Estimates in Real Time: an Assessment for the Euro Area," Working papers 157, Banque de France.
    192. Massimo Guidolin & Daniel L. Thornton, 2010. "Predictions of short-term rates and the expectations hypothesis," Working Papers 2010-013, Federal Reserve Bank of St. Louis.
    193. Hindrayanto, Irma & Koopman, Siem Jan & Ooms, Marius, 2010. "Exact maximum likelihood estimation for non-stationary periodic time series models," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2641-2654, November.
    194. Döhrn, Roland & Schmidt, Christoph M. & Zimmermann, Tobias, 2008. "Inflation Forecasting with Inflation Sentiment Indicators," Ruhr Economic Papers 80, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    195. de Albuquerquemello, Vinícius Phillipe & de Medeiros, Rennan Kertlly & da Nóbrega Besarria, Cássio & Maia, Sinézio Fernandes, 2018. "Forecasting crude oil price: Does exist an optimal econometric model?," Energy, Elsevier, vol. 155(C), pages 578-591.
    196. Curran, Declan & Funke, Michael, 2006. "Taking the temperature: forecasting GDP growth for mainland in China," BOFIT Discussion Papers 6/2006, Bank of Finland Institute for Emerging Economies (BOFIT).
    197. Tae-Hwy Lee & Yiyao Wang, 2019. "Evaluation of the Survey of Professional Forecasters in the Greenbook’s Loss Function," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 17(2), pages 345-360, June.
    198. Namwon Hyung & Clive W.J. Granger, 2008. "Linking series generated at different frequencies This work is part of a PhD dissertation presented at the University of California, San Diego (1999)," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(2), pages 95-108.
    199. Zhang, Yaojie & Wang, Yudong, 2023. "Forecasting crude oil futures market returns: A principal component analysis combination approach," International Journal of Forecasting, Elsevier, vol. 39(2), pages 659-673.
    200. Christian Gourieroux & Wei Liu, 2009. "Control and Out‐of‐Sample Validation of Dependent Risks," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 76(3), pages 683-707, September.
    201. Michael W. McCracken & Todd E. Clark, 2003. "The Predictive Content of the Output Gap for Inflation: Resolving In-Sample and Out-of-Sample Evidence," Computing in Economics and Finance 2003 183, Society for Computational Economics.
    202. Rapach, David E. & Wohar, Mark E. & Rangvid, Jesper, 2005. "Macro variables and international stock return predictability," International Journal of Forecasting, Elsevier, vol. 21(1), pages 137-166.
    203. Shi, Qi, 2023. "The RP-PCA factors and stock return predictability: An aligned approach," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    204. Chen, Jian & Jiang, Fuwei & Li, Hongyi & Xu, Weidong, 2016. "Chinese stock market volatility and the role of U.S. economic variables," Pacific-Basin Finance Journal, Elsevier, vol. 39(C), pages 70-83.
    205. Moser, Gabriel & Rumler, Fabio & Scharler, Johann, 2007. "Forecasting Austrian inflation," Economic Modelling, Elsevier, vol. 24(3), pages 470-480, May.
    206. Li, Zhao-Chen & Xie, Chi & Zeng, Zhi-Jian & Wang, Gang-Jin & Zhang, Ting, 2023. "Forecasting global stock market volatilities in an uncertain world," International Review of Financial Analysis, Elsevier, vol. 85(C).
    207. Colino, Evelyn V. & Irwin, Scott H. & Garcia, Philip & Etienne, Xiaoli, 2012. "Composite and Outlook Forecast Accuracy," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 37(2), pages 1-19, August.
    208. Thomas B. Götz & Alain Hecq & Jean‐Pierre Urbain, 2014. "Forecasting Mixed‐Frequency Time Series with ECM‐MIDAS Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(3), pages 198-213, April.
    209. Harvey, David I. & Newbold, Paul, 2003. "The non-normality of some macroeconomic forecast errors," International Journal of Forecasting, Elsevier, vol. 19(4), pages 635-653.
    210. Claudiu Tiberiu Albulescu & Dominique Pépin, 2018. "Monetary Integration, Money-Demand Stability, and the Role of Monetary Overhang in Forecasting Inflation in CEE Countries," Post-Print hal-01720319, HAL.
    211. Abbate, Angela & Marcellino, Massimiliano, 2016. "Point, interval and density forecasts of exchange rates with time-varying parameter models," Discussion Papers 19/2016, Deutsche Bundesbank.
    212. Rothman, P. & van Dijk, D.J.C. & Franses, Ph.H.B.F., 1999. "A multivariate STAR analysis of the relationship between money and output," Econometric Institute Research Papers EI 9945-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    213. David Hendry & Michael P. Clements, 2001. "Pooling of Forecasts," Economics Papers 2002-W9, Economics Group, Nuffield College, University of Oxford.
    214. Pablo Pincheira & Nicolás Hardy & Felipe Muñoz, 2021. "“Go Wild for a While!”: A New Test for Forecast Evaluation in Nested Models," Mathematics, MDPI, vol. 9(18), pages 1-28, September.
    215. Brooks, Chris & Burke, Simon P. & Stanescu, Silvia, 2016. "Finite sample weighting of recursive forecast errors," International Journal of Forecasting, Elsevier, vol. 32(2), pages 458-474.
    216. Håvard Hungnes, 2020. "Equal predictability test for multi-step-ahead system forecasts invariant to linear transformations," Discussion Papers 931, Statistics Norway, Research Department.
    217. Qunzi Zhang, 2021. "One hundred years of rare disaster concerns and commodity prices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(12), pages 1891-1915, December.
    218. Henryk Gurgul & Łukasz Lach, 2011. "The Nexus between Improvements in Economic Freedom and Growth: Evidence from CEE Countries in Transition," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 3(3), pages 133-168, September.
    219. Miller, Thomas W. & Rapach, David E., 2013. "An intra-week efficiency analysis of bookie-quoted NFL betting lines in NYC," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 10-23.
    220. Michael P. Clements, 2014. "Long-Run Restrictions and Survey Forecasts of Output, Consumption and Investment," ICMA Centre Discussion Papers in Finance icma-dp2014-02, Henley Business School, University of Reading.
    221. Ildeberta Abreu, 2011. "International organisations’ vs. private analysts’ forecasts: an evaluation," Working Papers w201120, Banco de Portugal, Economics and Research Department.
    222. Chen-Yin Kuo, 2017. "Is the accuracy of stock value forecasting relevant to industry factors or firm-specific factors? An empirical study of the Ohlson model," Review of Quantitative Finance and Accounting, Springer, vol. 49(1), pages 195-225, July.
    223. Gerdesmeier Dieter & Roffia Barbara & Reimers Hans-Eggert, 2017. "Forecasting Euro Area Inflation Using Single-Equation and Multivariate VAR–Models," Folia Oeconomica Stetinensia, Sciendo, vol. 17(2), pages 19-34, December.
    224. Gebka, Bartosz & Wohar, Mark E., 2019. "Stock return distribution and predictability: Evidence from over a century of daily data on the DJIA index," International Review of Economics & Finance, Elsevier, vol. 60(C), pages 1-25.
    225. Boriss Siliverstovs, 2013. "Do business tendency surveys help in forecasting employment?: A real-time evidence for Switzerland," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2013(2), pages 129-151.
    226. Döhrn, Roland & Barabas, György & Gebhardt, Heinz & Middendorf, Torge & Schäfer, Günter & Zimmermann, Tobias, 2008. "Die wirtschaftliche Entwicklung im Inland: Konjunktur im Zwischentief," RWI Konjunkturberichte, RWI - Leibniz-Institut für Wirtschaftsforschung, vol. 59(1), pages 31-82.
    227. Kai Carstensen & Jan Hagen & Oliver Hossfeld & Abelardo Salazar Neaves, 2008. "Money Demand Stability and Inflation Prediction in the Four Largest EMU Countries," ifo Working Paper Series 61, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    228. Pincheira, Pablo & Hardy, Nicolás & Muñoz, Felipe, 2021. ""Go wild for a while!": A new asymptotically Normal test for forecast evaluation in nested models," MPRA Paper 105368, University Library of Munich, Germany.
    229. Bruneau, C. & De Bandt, O. & Flageollet, A. & Michaux, E., 2003. "Forecasting Inflation using Economic Indicators: the Case of France," Working papers 101, Banque de France.
    230. Pincheira-Brown, Pablo & Selaive, Jorge & Nolazco, Jose Luis, 2019. "Forecasting inflation in Latin America with core measures," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1060-1071.
    231. Segnon, Mawuli & Lux, Thomas & Gupta, Rangan, 2017. "Modeling and forecasting the volatility of carbon dioxide emission allowance prices: A review and comparison of modern volatility models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 692-704.
    232. Abhyankar, Abhay & Klinkowska, Olga & Lee, Soyeon, 2015. "Consumption risk and the cross-section of government bond returns," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 180-200.
    233. Costantini, Mauro & Pappalardo, Carmine, 2010. "A hierarchical procedure for the combination of forecasts," International Journal of Forecasting, Elsevier, vol. 26(4), pages 725-743, October.
    234. Konstantin A. Kholodilin & Boriss Siliverstovs, 2017. "Think national, forecast local: a case study of 71 German urban housing markets," Applied Economics, Taylor & Francis Journals, vol. 49(42), pages 4271-4297, September.
    235. Kirsten Thompson & Renee van Eyden & Rangan Gupta, 2013. "Testing the Out-of-Sample Forecasting Ability of a Financial Conditions Index for South Africa," Working Papers 201383, University of Pretoria, Department of Economics.
    236. Mihaela Simionescu, 2014. "What Type Of Social Capital Is Engaged By The French Dairy Stockbreeders? A Characterization Through Their Professional Identities," Romanian Journal of Regional Science, Romanian Regional Science Association, vol. 8(1), pages 87-102, JUNE.
    237. Chen, Nan-Kuang & Chen, Shiu-Sheng & Chou, Yu-Hsi, 2013. "Further evidence on bear market predictability: The role of the external finance premium," MPRA Paper 49093, University Library of Munich, Germany.
    238. Schumacher Christian & Dreger Christian, 2004. "Estimating Large-Scale Factor Models for Economic Activity in Germany: Do They Outperform Simpler Models? / Die Schätzung von großen Faktormodellen für die deutsche Volkswirtschaft: Übertreffen sie ei," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 224(6), pages 731-750, December.
    239. Bentes, Sónia R., 2015. "A comparative analysis of the predictive power of implied volatility indices and GARCH forecasted volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 105-112.
    240. Greg Tkacz & Carolyn Wilkins, 2008. "Linear and threshold forecasts of output and inflation using stock and housing prices," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(2), pages 131-151.
    241. David Iselin & Boriss Siliverstovs, 2013. "Using Newspapers for Tracking the Business Cycle," KOF Working papers 13-337, KOF Swiss Economic Institute, ETH Zurich.
    242. Panopoulou, Ekaterini & Souropanis, Ioannis, 2019. "The role of technical indicators in exchange rate forecasting," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 197-221.
    243. Zhang, Yaojie & Ma, Feng & Zhu, Bo, 2019. "Intraday momentum and stock return predictability: Evidence from China," Economic Modelling, Elsevier, vol. 76(C), pages 319-329.
    244. Luis C. Nunes, 2005. "Nowcasting quarterly GDP growth in a monthly coincident indicator model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(8), pages 575-592.
    245. Murat Midiliç, 2020. "Estimation of STAR–GARCH Models with Iteratively Weighted Least Squares," Computational Economics, Springer;Society for Computational Economics, vol. 55(1), pages 87-117, January.
    246. Antonis Michis, 2012. "Monitoring Forecasting Combinations with Semiparametric Regression Models," Working Papers 2012-2, Central Bank of Cyprus.
    247. West, Kenneth D., 2006. "Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 3, pages 99-134, Elsevier.
    248. Marczak, Martyna & Proietti, Tommaso, 2015. "Outlier Detection in Structural Time Series Models: the Indicator Saturation Approach," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113137, Verein für Socialpolitik / German Economic Association.
    249. Maio, Paulo, 2016. "Cross-sectional return dispersion and the equity premium," Journal of Financial Markets, Elsevier, vol. 29(C), pages 87-109.
    250. Yu, Deshui & Huang, Difang, 2023. "Cross-sectional uncertainty and expected stock returns," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 321-340.
    251. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    252. Mark E. Wohar & David E. Rapach, 2007. "Forecasting the recent behavior of US business fixed investment spending: an analysis of competing models This is a significantly revised version of our previous paper, 'Forecasting US Business Fixed ," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(1), pages 33-51.
    253. Jordan, Steven J. & Vivian, Andrew & Wohar, Mark E., 2017. "Forecasting market returns: bagging or combining?," International Journal of Forecasting, Elsevier, vol. 33(1), pages 102-120.
    254. Rangan Gupta & Mampho P. Modise & Josine Uwilingiye, 2011. "Out-of-Sample Equity Premium Predictability in South Africa: Evidence from a Large Number of Predictors," Working Papers 201122, University of Pretoria, Department of Economics.
    255. Reimers, Hans-Eggert, 2002. "Analysing Divisia Aggregates for the Euro Area," Discussion Paper Series 1: Economic Studies 2002,13, Deutsche Bundesbank.
    256. Pablo Pincheira-Brown & Andrea Bentancor & Nicolás Hardy, 2023. "An Inconvenient Truth about Forecast Combinations," Mathematics, MDPI, vol. 11(18), pages 1-24, September.
    257. Venditti, Fabrizio, 2013. "From oil to consumer energy prices: How much asymmetry along the way?," Energy Economics, Elsevier, vol. 40(C), pages 468-473.
    258. Liu, Dandan & Jansen, Dennis W., 2007. "Macroeconomic forecasting using structural factor analysis," International Journal of Forecasting, Elsevier, vol. 23(4), pages 655-677.
    259. Dandan Liu & Dennis Jansen, 2011. "Does a factor Phillips curve help? An evaluation of the predictive power for U.S. inflation," Empirical Economics, Springer, vol. 40(3), pages 807-826, May.
    260. Xiaojie Xu, 2020. "Corn Cash Price Forecasting," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(4), pages 1297-1320, August.
    261. Pan, Zheyao & Chan, Kam Fong, 2018. "A new government bond volatility index predictor for the U.S. equity premium," Pacific-Basin Finance Journal, Elsevier, vol. 50(C), pages 200-215.
    262. Akhter Faroque & William Veloce & Jean-Francois Lamarche, 2008. "The impact of structural breaks on the stability of the out-of-sample predictive content of financial variables for Canada's real GDP growth: An encompassing approach," Working Papers 0803, Brock University, Department of Economics.
    263. Christopher J. Neely & David E. Rapach & Jun Tu & Guofu Zhou, 2010. "Out-of-sample equity premium prediction: economic fundamentals vs. moving-average rules," Working Papers 2010-008, Federal Reserve Bank of St. Louis.
    264. Elliott, Graham & Gargano, Antonio & Timmermann, Allan, 2013. "Complete subset regressions," Journal of Econometrics, Elsevier, vol. 177(2), pages 357-373.
    265. Fabio Busetti & Juri Marcucci & Giovanni Veronese, 2009. "Comparing forecast accuracy: A Monte Carlo investigation," Temi di discussione (Economic working papers) 723, Bank of Italy, Economic Research and International Relations Area.
    266. Andrew B. Martinez, 2020. "Extracting Information from Different Expectations," Working Papers 2020-008, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    267. Brent Meyer & Murat Tasci, 2015. "Lessons for forecasting unemployment in the United States: use flow rates, mind the trend," FRB Atlanta Working Paper 2015-1, Federal Reserve Bank of Atlanta.
    268. Riane de Bruyn & Rangan Gupta & Lardo stander, 2011. "Testing the Monetary Model for Exchange Rate Determination in South Africa: Evidence from 101 Years of Data," Working Papers 201134, University of Pretoria, Department of Economics.
    269. Anthony H. Tu & Cathy Yi-Hsuan Chen, 2016. "What Derives the Bond Portfolio Value-at-Risk: Information Roles of Macroeconomic and Financial Stress Factors," SFB 649 Discussion Papers SFB649DP2016-006, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    270. Nicholas Taylor, 2008. "The predictive value of temporally disaggregated volatility: evidence from index futures markets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(8), pages 721-742.
    271. Ma, Feng & Guo, Yangli & Chevallier, Julien & Huang, Dengshi, 2022. "Macroeconomic attention, economic policy uncertainty, and stock volatility predictability," International Review of Financial Analysis, Elsevier, vol. 84(C).
    272. Barnhart, Scott W. & Giannetti, Antoine, 2009. "Negative earnings, positive earnings and stock return predictability: An empirical examination of market timing," Journal of Empirical Finance, Elsevier, vol. 16(1), pages 70-86, January.
    273. Hüfner Felix P. & Schröder Michael, 2002. "Prognosegehalt von ifo-Geschäftserwartungen und ZEW-Konjunkturerwartungen: Ein ökonometrischer Vergleich / Forecasting German industrial Production: An Econometric Comparison of ifo- and ZEW-Business ," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 222(3), pages 316-336, June.
    274. Egelkraut, Thorsten M. & Garcia, Philip & Irwin, Scott H. & Good, Darrel L., 2002. "An Evaluation Of Crop Forecast Accuracy For Corn And Soybeans: Usda And Private Information Services," 2002 Conference, April 22-23, 2002, St. Louis, Missouri 19068, NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    275. Perez-Rodriguez, Jorge V. & Torra, Salvador & Andrada-Felix, Julian, 2005. "STAR and ANN models: forecasting performance on the Spanish "Ibex-35" stock index," Journal of Empirical Finance, Elsevier, vol. 12(3), pages 490-509, June.
    276. Tae-Hwy Lee & Yiyao Wang, 2015. "Finding SPF Percentiles Closest to Greenbook," Working Papers 201503, University of California at Riverside, Department of Economics.
    277. Hammerschmid, Regina & Lohre, Harald, 2018. "Regime shifts and stock return predictability," International Review of Economics & Finance, Elsevier, vol. 56(C), pages 138-160.
    278. Coble, David & Pincheira, Pablo, 2017. "Nowcasting Building Permits with Google Trends," MPRA Paper 76514, University Library of Munich, Germany.
    279. Naik, Prasad A., 2015. "Marketing Dynamics: A Primer on Estimation and Control," Foundations and Trends(R) in Marketing, now publishers, vol. 9(3), pages 175-266, December.
    280. Atanasov, Victoria, 2018. "World output gap and global stock returns," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 181-197.
    281. Atsushi Inoue & Barbara Rossi, 2011. "Out-of-sample forecast tests robust to the choice of window size," Working Papers 11-31, Federal Reserve Bank of Philadelphia.
    282. Kenneth S. Rogoff & Vania Stavrakeva, 2008. "The Continuing Puzzle of Short Horizon Exchange Rate Forecasting," NBER Working Papers 14071, National Bureau of Economic Research, Inc.
    283. Nicholas Apergis & Ghassen El Montasser & Emmanuel Owusu-Sekyere & Ahdi N. Ajmi & Rangan Gupta, 2014. "Dutch Disease Effect of Oil Rents on Agriculture Value Added in MENA Countries," Working Papers 201408, University of Pretoria, Department of Economics.
    284. Christian Schulz, 2008. "Forecasting economic activity for Estonia : The application of dynamic principal component analyses," Bank of Estonia Working Papers 2008-02, Bank of Estonia, revised 30 Oct 2008.
    285. Konstantins Benkovskis, 2008. "Short-Term Forecasts of Latvia's Real Gross Domestic Product Growth Using Monthly Indicators," Working Papers 2008/05, Latvijas Banka.
    286. Abdoulaye Sy & Catherine Araujo-Bonjean & Marie-Eliette Dury & Nourddine Azzaoui & Arnaud Guillin, 2021. "An Extreme Value Mixture model to assess drought hazard in West Africa," Working Papers hal-03297023, HAL.
    287. Rudan Wang & Bruce Morley & Javier Ordóñez, 2015. "The Taylor Rule, Wealth Effects and the Exchange Rate," Working Papers 2015/08, Economics Department, Universitat Jaume I, Castellón (Spain).
    288. Taylor, Nicholas, 2008. "Can idiosyncratic volatility help forecast stock market volatility?," International Journal of Forecasting, Elsevier, vol. 24(3), pages 462-479.
    289. Rainer Schulz & Axel Werwatz, 2008. "House Prices and Replacement Cost: A Micro-Level Analysis," SFB 649 Discussion Papers SFB649DP2008-013, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    290. Tannura, Michael A. & Irwin, Scott H. & Good, Darrel L., 2008. "Weather, Technology, and Corn and Soybean Yields in the U.S. Corn Belt," Marketing and Outlook Research Reports 37501, University of Illinois at Urbana-Champaign, Department of Agricultural and Consumer Economics.
    291. Bordignon, Silvano & Bunn, Derek W. & Lisi, Francesco & Nan, Fany, 2013. "Combining day-ahead forecasts for British electricity prices," Energy Economics, Elsevier, vol. 35(C), pages 88-103.
    292. Raffaella Giacomini & Barbara Rossi, 2013. "Forecasting in macroeconomics," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 17, pages 381-408, Edward Elgar Publishing.
    293. Giancarlo Bruno, 2009. "Non-linear relation between industrial production and business surveys data," ISAE Working Papers 119, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
    294. Rapach, David E. & Wohar, Mark E., 2006. "In-sample vs. out-of-sample tests of stock return predictability in the context of data mining," Journal of Empirical Finance, Elsevier, vol. 13(2), pages 231-247, March.
    295. Kothari, Pratik & O’Doherty, Michael S., 2023. "Job postings and aggregate stock returns," Journal of Financial Markets, Elsevier, vol. 64(C).
    296. Francis X. Diebold & Glenn D. Rudebusch, 2001. "Five questions about business cycles," Economic Review, Federal Reserve Bank of San Francisco, pages 1-15.
    297. Awartani, Basel M.A. & Corradi, Valentina, 2005. "Predicting the volatility of the S&P-500 stock index via GARCH models: the role of asymmetries," International Journal of Forecasting, Elsevier, vol. 21(1), pages 167-183.
    298. Zhang, Li & Li, Yan & Yu, Sixin & Wang, Lu, 2023. "Risk transmission of El Niño-induced climate change to regional Green Economy Index," Economic Analysis and Policy, Elsevier, vol. 79(C), pages 860-872.
    299. Todd E. Clark & Michael W. McCracken, 2010. "Reality checks and nested forecast model comparisons," Working Papers 2010-032, Federal Reserve Bank of St. Louis.
    300. Tian, Guangning & Peng, Yuchao & Meng, Yuhao, 2023. "Forecasting crude oil prices in the COVID-19 era: Can machine learn better?," Energy Economics, Elsevier, vol. 125(C).
    301. Lu, Fei & Ma, Feng, 2023. "Cross-sectional uncertainty and stock market volatility: New evidence," Finance Research Letters, Elsevier, vol. 57(C).
    302. Claus Brand & Hans-Eggert Reimers & Franz Seitz, 2003. "Narrow Money and the Business Cycle: Theoretical aspects and euro area evdence," Macroeconomics 0303012, University Library of Munich, Germany.
    303. Colino, Evelyn V. & Irwin, Scott H. & Garcia, Philip, 2008. "How Much Can Outlook Forecasts be Improved? An Application to the U.S. Hog Market," 2008 Conference, April 21-22, 2008, St. Louis, Missouri 37620, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    304. Liu, Xiaochun, 2019. "On tail fatness of macroeconomic dynamics," Journal of Macroeconomics, Elsevier, vol. 62(C).
    305. El-Shagi, Makram, 2009. "Inflation Expectations: Does the Market Beat Professional Forecasts?," IWH Discussion Papers 16/2009, Halle Institute for Economic Research (IWH).
    306. Reimers Hans-Eggert, 2003. "Does Money Include Information for Prices in the Euro Area? / Enthält Geld Informationen für die Preisentwicklung im Eurowährungsgebiet?," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 223(5), pages 581-602, October.
    307. Luis Fernando Melo & Héctor Núñez, 2004. "Combinación de Pronósticos de la Inflación en Presencia de cambios Estructurales," Borradores de Economia 286, Banco de la Republica de Colombia.
    308. Ana-Maria Fuertes & Elena Kalotychou & Natasa Todorovic, 2015. "Daily volume, intraday and overnight returns for volatility prediction: profitability or accuracy?," Review of Quantitative Finance and Accounting, Springer, vol. 45(2), pages 251-278, August.
    309. Baffigi, Alberto & Golinelli, Roberto & Parigi, Giuseppe, 2004. "Bridge models to forecast the euro area GDP," International Journal of Forecasting, Elsevier, vol. 20(3), pages 447-460.
    310. Hai Lin & Xinyuan Tao & Junbo Wang & Chunchi Wu, 2020. "Credit Spreads, Business Conditions, and Expected Corporate Bond Returns," JRFM, MDPI, vol. 13(2), pages 1-34, January.
    311. David Bessler & Zijun Wang, 2012. "D-separation, forecasting, and economic science: a conjecture," Theory and Decision, Springer, vol. 73(2), pages 295-314, August.
    312. Etienne, Xiaoli L. & Farhangdoost, Sara & Hoffman, Linwood A. & Adam, Brian D., 2023. "Forecasting the U.S. season-average farm price of corn: Derivation of an alternative futures-based forecasting model," Journal of Commodity Markets, Elsevier, vol. 30(C).
    313. Trecroci, Carmine & Vega, Juan Luis, 2000. "The information content of M3 for future inflation," Working Paper Series 33, European Central Bank.
    314. Paul Hubert, 2010. "Monetary Policy, Imperfect Information and the Expectations Channel," Sciences Po publications info:hdl:2441/f4rshpf3v1u, Sciences Po.
    315. Wang, Jiqian & He, Xiaofeng & Ma, Feng & Li, Pan, 2022. "Uncertainty and oil volatility: Evidence from shrinkage method," Resources Policy, Elsevier, vol. 75(C).
    316. Sousa, Ricardo M. & Vivian, Andrew & Wohar, Mark E., 2016. "Predicting asset returns in the BRICS: The role of macroeconomic and fundamental predictors," International Review of Economics & Finance, Elsevier, vol. 41(C), pages 122-143.
    317. Noha Emara, 2014. "Predictive Ability of Three Different Estimates of “Cay†to Excess Stock Returns – A Comparative Study for South Africa and USA," European Research Studies Journal, European Research Studies Journal, vol. 0(1), pages 3-18.
    318. Ali Dib & Kevin Moran, 2005. "Forecasting with the New-Keynesian Model: An Experiment with Canadian Data," Computing in Economics and Finance 2005 235, Society for Computational Economics.
    319. Catherine L. Kling & Raymond W. Arritt & Gray Calhoun & David A. Keiser, 2017. "Integrated Assessment Models of the Food, Energy, and Water Nexus: A Review and an Outline of Research Needs," Annual Review of Resource Economics, Annual Reviews, vol. 9(1), pages 143-163, October.
    320. Kontogeorgos, Georgios & Lambrias, Kyriacos, 2019. "An analysis of the Eurosystem/ECB projections," Working Paper Series 2291, European Central Bank.
    321. Narayan, Paresh Kumar & Sharma, Susan Sunila, 2015. "Is carbon emissions trading profitable?," Economic Modelling, Elsevier, vol. 47(C), pages 84-92.
    322. Allison Zhou & Carl Bonham & Byron Gangnes, 2007. "Modeling the supply and demand for tourism: a fully identified VECM approach," Working Papers 200717, University of Hawaii at Manoa, Department of Economics.
    323. Wang, Xiaoqian & Hyndman, Rob J. & Li, Feng & Kang, Yanfei, 2023. "Forecast combinations: An over 50-year review," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1518-1547.
    324. Cao, Zhen & Han, Liyan & Wei, Xinbei & Zhang, Qunzi, 2022. "Fear in commodity return prediction," Finance Research Letters, Elsevier, vol. 46(PB).
    325. Tan, Xueping & Sirichand, Kavita & Vivian, Andrew & Wang, Xinyu, 2022. "Forecasting European carbon returns using dimension reduction techniques: Commodity versus financial fundamentals," International Journal of Forecasting, Elsevier, vol. 38(3), pages 944-969.
    326. Xu Chong Bo & Jianlei Han & Yin Liao & Jing Shi & Wu Yan, 2021. "Do outliers matter? The predictive ability of average skewness on market returns using robust skewness measures," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(3), pages 3977-4006, September.
    327. Arora Siddharth & Little Max A. & McSharry Patrick E., 2013. "Nonlinear and nonparametric modeling approaches for probabilistic forecasting of the US gross national product," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(4), pages 395-420, September.
    328. M. Karanasos & S. Yfanti & J. Hunter, 2022. "Emerging stock market volatility and economic fundamentals: the importance of US uncertainty spillovers, financial and health crises," Annals of Operations Research, Springer, vol. 313(2), pages 1077-1116, June.
    329. Christian Dreger & Dieter Gerdesmeier & Barbara Roffia, 2016. "Re-vitalizing Money Demand in the Euro Area: Still Valid at the Zero Lower Bound," Discussion Papers of DIW Berlin 1606, DIW Berlin, German Institute for Economic Research.
    330. Strauss, Jack, 2013. "Does housing drive state-level job growth? Building permits and consumer expectations forecast a state’s economic activity," Journal of Urban Economics, Elsevier, vol. 73(1), pages 77-93.
    331. Dean Croushore & Simon van Norden, 2018. "Fiscal Forecasts at the FOMC: Evidence from the Greenbooks," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 933-945, December.
    332. Dimitriadis, Timo & Schnaitmann, Julie, 2021. "Forecast encompassing tests for the expected shortfall," International Journal of Forecasting, Elsevier, vol. 37(2), pages 604-621.
    333. Fuertes, Ana-Maria & Izzeldin, Marwan & Kalotychou, Elena, 2009. "On forecasting daily stock volatility: The role of intraday information and market conditions," International Journal of Forecasting, Elsevier, vol. 25(2), pages 259-281.
    334. Rui Hao, 2011. "Sources of income differences across Chinese provinces during the reform period: a development accounting exercise," CERDI Working papers halshs-00557001, HAL.
    335. Emara, Noha, 2014. "Predictive ability of three different estimates of “cay” to excess stock returns - A comparative study South Africa & U.S. -," MPRA Paper 68684, University Library of Munich, Germany.
    336. Luis Fernando Melo Velandia & Héctor M. Núñez Amortegui, 2004. "Combinación de pronósticos de la inflación en presencia de cambios estructurales," Borradores de Economia 2153, Banco de la Republica.
    337. Jaime Casassus & Freddy Higuera, 2011. "Stock Return Predictability and Oil Prices," Documentos de Trabajo 406, Instituto de Economia. Pontificia Universidad Católica de Chile..
    338. Murat Midilic, 2016. "Estimation Of Star-Garch Models With Iteratively Weighted Least Squares," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 16/918, Ghent University, Faculty of Economics and Business Administration.
    339. Mauro Costantini & Ulrich Gunter & Robert M. Kunst, 2017. "Forecast Combinations in a DSGE‐VAR Lab," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(3), pages 305-324, April.
    340. Brent Meyer & Saeed Zaman, 2013. "It’s not just for inflation: The usefulness of the median CPI in BVAR forecasting," Working Papers (Old Series) 1303, Federal Reserve Bank of Cleveland.
    341. Andrea Carriero & Raffaella Giacomini, 2011. "How useful are no-arbitrage restrictions for forecasting the term structure of interest rates?," Post-Print hal-00844809, HAL.
    342. Hüfner, Felix P. & Schröder, Michael, 2001. "Unternehmens- versus Analystenbefragungen: Zum Prognosegehalt von ifo-Geschäftserwartungen und ZEW-Konjunkturerwartungen," ZEW Discussion Papers 01-04, ZEW - Leibniz Centre for European Economic Research.
    343. Rapach, David E. & Wohar, Mark E., 2002. "Testing the monetary model of exchange rate determination: new evidence from a century of data," Journal of International Economics, Elsevier, vol. 58(2), pages 359-385, December.
    344. Dreger, Christian & Schumacher, Christian, 2002. "Estimating large-scale factor models for economic activity in Germany: Do they outperform simpler models?," HWWA Discussion Papers 199, Hamburg Institute of International Economics (HWWA).
    345. Hongwei Zhang & Qiang He & Ben Jacobsen & Fuwei Jiang, 2020. "Forecasting stock returns with model uncertainty and parameter instability," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(5), pages 629-644, August.
    346. Clements, Michael P. & Harvey, David I., 2011. "Combining probability forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 208-223.
    347. Chue, Timothy K. & Xu, Jin Karen, 2022. "Profitability, asset investment, and aggregate stock returns," Journal of Banking & Finance, Elsevier, vol. 143(C).
    348. Wegener, Christian & von Nitzsch, Rüdiger & Cengiz, Cetin, 2010. "An advanced perspective on the predictability in hedge fund returns," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2694-2708, November.
    349. Kishor N. Kundan, 2010. "The Superiority of Greenbook Forecasts and the Role of Recessions," NBP Working Papers 74, Narodowy Bank Polski.
    350. You, Yu & Liu, Xiaochun, 2020. "Forecasting short-run exchange rate volatility with monetary fundamentals: A GARCH-MIDAS approach," Journal of Banking & Finance, Elsevier, vol. 116(C).
    351. Håvard Hungnes, 2018. "Encompassing tests for evaluating multi-step system forecasts invariant to linear transformations," Discussion Papers 871, Statistics Norway, Research Department.
    352. Hans-Eggert Reimers, 2003. "Does Money Include Information for Output in the Euro Area?," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 139(II), pages 231-252, June.
    353. Ryan Ratcliff, 2010. "Predicting nominal exchange rate movements using skewness information from options prices," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 15(1), pages 75-92.
    354. Heather L. R. Tierney, 2019. "Forecasting with the Nonparametric Exclusion-from-Core Inflation Persistence Model Using Real-Time Data," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 25(1), pages 39-63, February.
    355. Anella Munro, 2005. "UIP, Expectations and the Kiwi," Reserve Bank of New Zealand Discussion Paper Series DP2005/05, Reserve Bank of New Zealand.
    356. Ekaterini Panopoulou & Sotiria Plastira, 2014. "Fama French factors and US stock return predictability," Journal of Asset Management, Palgrave Macmillan, vol. 15(2), pages 110-128, April.
    357. Todd E. Clark & Michael W. McCracken, 2002. "Forecast-based model selection in the presence of structural breaks," Research Working Paper RWP 02-05, Federal Reserve Bank of Kansas City.
    358. Hassani, Hossein & Heravi, Saeed & Zhigljavsky, Anatoly, 2009. "Forecasting European industrial production with singular spectrum analysis," International Journal of Forecasting, Elsevier, vol. 25(1), pages 103-118.
    359. Jean-Stéphane MESONNIER, 2007. "The predictive content of the real interest rate gap for macroeconomic variables in the euro area," Money Macro and Finance (MMF) Research Group Conference 2006 102, Money Macro and Finance Research Group.
    360. Robert Sollis, 2005. "Predicting returns and volatility with macroeconomic variables: evidence from tests of encompassing," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(3), pages 221-231.
    361. Glynn Tonsor & Ted Schroeder, 2011. "Multivariate forecasting of a commodity portfolio: application to cattle feeding margins and risk," Applied Economics, Taylor & Francis Journals, vol. 43(11), pages 1329-1339.
    362. Charles Harvie & Hyeon‐Seung Huh, 2009. "A New Measure Of Us Potential Output, Inflation Forecasts, And Monetary Policy Rules," Manchester School, University of Manchester, vol. 77(5), pages 611-631, September.
    363. Maurício Yoshinori Une & Marcelo Savino Portugal, 2005. "Can fear beat hope? A story of GARCH-in-Mean-Level effects for Emerging Market Country Risks," Econometrics 0509006, University Library of Munich, Germany.
    364. Dudek, Sławomir, 2008. "Consumer Survey Data and short-term forecasting of households consumption expenditures in Poland," MPRA Paper 19818, University Library of Munich, Germany.
    365. Wei Wei & Leonhard Held, 2014. "Calibration tests for count data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(4), pages 787-805, December.
    366. Dladla, Pholile & Malikane, Christopher, 2019. "Stock return predictability: Evidence from a structural model," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 412-424.
    367. Dreger, Christian & Wolters, Jürgen, 2014. "Money demand and the role of monetary indicators in forecasting euro area inflation," International Journal of Forecasting, Elsevier, vol. 30(2), pages 303-312.
    368. Sanders, Dwight R. & Manfredo, Mark R., 2002. "Usda Production Forecasts For Pork, Beef, And Broilers: An Evaluation," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 27(1), pages 1-14, July.
    369. Xianfeng Hao & Yudong Wang, 2023. "Cloud cover and expected oil returns," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-10, December.
    370. Mathias Hoffmann, 2014. "The Consumption–Income Ratio, Entrepreneurial Risk, and the U.S. Stock Market," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 46(6), pages 1259-1292, September.
    371. Rosario Dell'Aquila & Elvezio Ronchetti, 2004. "Robust tests of predictive accuracy," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(2), pages 161-184.
    372. Wang, Zijun & Bessler, David A, 2002. "The Homogeneity Restriction and Forecasting Performance of VAR-Type Demand Systems: An Empirical Examination of US Meat Consumption," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 21(3), pages 193-206, April.
    373. Jiang, Fuwei & Lee, Joshua & Martin, Xiumin & Zhou, Guofu, 2019. "Manager sentiment and stock returns," Journal of Financial Economics, Elsevier, vol. 132(1), pages 126-149.
    374. Franken, Jason R.V. & Irwin, Scott H. & Garcia, Philip, 2021. "Biodiesel hedging under binding renewable fuel standard mandates," Energy Economics, Elsevier, vol. 96(C).
    375. Lu Wang & Shan Li & Chao Liang, 2024. "Exploring the impact of oil security attention on oil volatility: A new perspective," International Finance, Wiley Blackwell, vol. 27(1), pages 61-80, April.
    376. Dick van Dijk & Philip Hans Franses & Michael P. Clements & Jeremy Smith, 2003. "On SETAR non-linearity and forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(5), pages 359-375.
    377. Rapach, David E. & Ringgenberg, Matthew C. & Zhou, Guofu, 2016. "Short interest and aggregate stock returns," Journal of Financial Economics, Elsevier, vol. 121(1), pages 46-65.
    378. Marshall, Ben R. & Nguyen, Hung T. & Nguyen, Nhut H. & Visaltanachoti, Nuttawat, 2021. "Country governance and international equity returns," Journal of Banking & Finance, Elsevier, vol. 122(C).
    379. Yaojie Zhang & Feng Ma & Chao Liang & Yi Zhang, 2021. "Good variance, bad variance, and stock return predictability," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4410-4423, July.
    380. Shiu-Sheng Chen, 2005. "A note on in-sample and out-of-sample tests for Granger causality," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(6), pages 453-464.
    381. Wang, Zijun & Bessler, David A., 2004. "Forecasting performance of multivariate time series models with full and reduced rank: an empirical examination," International Journal of Forecasting, Elsevier, vol. 20(4), pages 683-695.
    382. Park, Yang-Ho, 2022. "Spread position as a leading economic indicator," Journal of Financial Markets, Elsevier, vol. 59(PA).
    383. Manfredo, Mark R. & Richards, Timothy J., 2005. "Hedging Yield with Weather Derivatives: A Role for Options," 2005 Annual meeting, July 24-27, Providence, RI 19369, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    384. Manfredo, Mark R. & Sanders, Dwight R., 2004. "Forecast Encompassing And Futures Market Efficiency: The Case Of Milk Futures," 2004 Annual meeting, August 1-4, Denver, CO 20267, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    385. NICOLAE Simona & GRIGORE George-Eduard & MUȘETESCU Radu-Cristian, 2022. "The Use of GARCH Autoregressive Models in Estimating and Forecasting the Crude Oil Volatility," European Journal of Interdisciplinary Studies, Bucharest Economic Academy, issue 01, March.
    386. Bryant, Henry L. & Haigh, Michael S., 2002. "Bid-Ask Spreads In Commodity Futures Markets," Working Papers 28587, University of Maryland, Department of Agricultural and Resource Economics.
    387. Huang, Henry H. & Wang, Kent & Wang, Zhanglong, 2016. "A test of efficiency for the S&P 500 index option market using the generalized spectrum method," Journal of Banking & Finance, Elsevier, vol. 64(C), pages 52-70.
    388. Mawuli Segnon & Stelios Bekiros, 2019. "Forecasting Volatility in Cryptocurrency Markets," CQE Working Papers 7919, Center for Quantitative Economics (CQE), University of Muenster.
    389. Ghonghadze, Jaba & Lux, Thomas, 2016. "Bringing an elementary agent-based model to the data: Estimation via GMM and an application to forecasting of asset price volatility," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 1-19.
    390. Byron Botha & Tim Olds & Geordie Reid & Daan Steenkamp & Rossouw van Jaarsveld, 2021. "Nowcasting South African gross domestic product using a suite of statistical models," South African Journal of Economics, Economic Society of South Africa, vol. 89(4), pages 526-554, December.
    391. Duo Qin & Qingchao Wang, 2016. "Predictive Macro-Impacts of PLS-based Financial Conditions Indices: An Application to the USA," Working Papers 201, Department of Economics, SOAS University of London, UK.
    392. Sanders, Dwight R. & Manfredo, Mark R., 2004. "Comparing Hedging Effectiveness: An Application of the Encompassing Principle," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 29(1), pages 1-14, April.
    393. Lin, Qi & Lin, Xi, 2021. "Cash conversion cycle and aggregate stock returns," Journal of Financial Markets, Elsevier, vol. 52(C).

  65. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.

    Cited by:

    1. Michal Rubaszek & Pawel Skrzypczynski, 2007. "Can a simple DSGE model outperform Professional Forecasters?," Working Papers 5, Department of Applied Econometrics, Warsaw School of Economics.
    2. Carlos, Thiago Carlomagno & Marçal, Emerson Fernandes, 2013. "Forecasting Brazilian inflation by its aggregate and disaggregated data: a test of predictive power by forecast horizon," Textos para discussão 346, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    3. Frédérick Demers & Annie De Champlain, 2005. "Forecasting Core Inflation in Canada: Should We Forecast the Aggregate or the Components?," Staff Working Papers 05-44, Bank of Canada.
    4. Bekiros, Stelios & Marcellino, Massimiliano, 2013. "The multiscale causal dynamics of foreign exchange markets," Journal of International Money and Finance, Elsevier, vol. 33(C), pages 282-305.
    5. Li, Li & Kang, Yanfei & Li, Feng, 2023. "Bayesian forecast combination using time-varying features," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1287-1302.
    6. Pesaran, M.H. & Pick, A., 2008. "Forecasting Random Walks Under Drift Instability," Cambridge Working Papers in Economics 0814, Faculty of Economics, University of Cambridge.
    7. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2012. "Time-varying Combinations of Predictive Densities using Nonlinear Filtering," Tinbergen Institute Discussion Papers 12-118/III, Tinbergen Institute.
    8. A. ISLAS & Víctor M. GUERRERO & Eliud SILVA, 2019. "Forecasting Remittances to Mexico with a Multi-State Markov-Switching Model Applied to the Trend with Controlled Smoothness," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 38-56, March.
    9. Mahua Barari & Nityananda Sarkar & Srikanta Kundu & Kushal Banik Chowdhury, 2014. "Forecasting House Prices in the United States with Multiple Structural Breaks," International Econometric Review (IER), Econometric Research Association, vol. 6(1), pages 1-23, April.
    10. Roberto Golinelli & Giuseppe Parigi, 2003. "What is this thing called confidence? A comparative analysis of consumer confidence indices in eight major countries," Temi di discussione (Economic working papers) 484, Bank of Italy, Economic Research and International Relations Area.
    11. Ayinde, Taofeek O. & Olaniran, Abeeb O. & Abolade, Onomeabure C. & Ogbonna, Ahamuefula Ephraim, 2023. "Technology shocks - Gold market connection: Is the effect episodic to business cycle behaviour?," Resources Policy, Elsevier, vol. 84(C).
    12. Thorsten Egelkraut & Philip Garcia & Bruce Sherrick, 2007. "Options-based forecasts of futures prices in the presence of limit moves," Applied Economics, Taylor & Francis Journals, vol. 39(2), pages 145-152.
    13. Guillaume Chevillon, 2006. "Multi-step Forecasting in Unstable Economies: Robustness Issues in the Presence of Location Shifts," Economics Series Working Papers 257, University of Oxford, Department of Economics.
    14. Poledna, Sebastian & Miess, Michael Gregor & Hommes, Cars & Rabitsch, Katrin, 2023. "Economic forecasting with an agent-based model," European Economic Review, Elsevier, vol. 151(C).
    15. Nicolas Chanut & Mario Marcel & Carlos Medel, 2018. "Can Economic Perception Surveys Improve Macroeconomic Forecasting in Chile?," Working Papers Central Bank of Chile 824, Central Bank of Chile.
    16. Constantin Bürgi, 2023. "How to Deal With Missing Observations in Surveys of Professional Forecasters," CESifo Working Paper Series 10203, CESifo.
    17. Kelly Burns & Imad Moosa, 2017. "Demystifying the Meese–Rogoff puzzle: structural breaks or measures of forecasting accuracy?," Applied Economics, Taylor & Francis Journals, vol. 49(48), pages 4897-4910, October.
    18. Siddhartha S. Bora & Ani L. Katchova & Todd H. Kuethe, 2023. "The accuracy and informativeness of agricultural baselines," American Journal of Agricultural Economics, John Wiley & Sons, vol. 105(4), pages 1116-1148, August.
    19. Trapani, Lorenzo & Urga, Giovanni, 2009. "Optimal forecasting with heterogeneous panels: A Monte Carlo study," International Journal of Forecasting, Elsevier, vol. 25(3), pages 567-586, July.
    20. Behrendt, Simon & Schweikert, Karsten, 2021. "A Note on Adaptive Group Lasso for Structural Break Time Series," Econometrics and Statistics, Elsevier, vol. 17(C), pages 156-172.
    21. Wang, Yi & Von Krannichfeldt, Leandro & Zufferey, Thierry & Toubeau, Jean-François, 2021. "Short-term nodal voltage forecasting for power distribution grids: An ensemble learning approach," Applied Energy, Elsevier, vol. 304(C).
    22. Carlo Altavilla & Matteo Ciccarelli, 2006. "Inflation Forecasts, Monetary Policy and Unemployment Dynamics: Evidence from the US and the Euro Area," Discussion Papers 7_2006, D.E.S. (Department of Economic Studies), University of Naples "Parthenope", Italy.
    23. Aleksandra Górna & Alicja Szabelska-Beręsewicz & Marek Wieruszewski & Monika Starosta-Grala & Zygmunt Stanula & Anna Kożuch & Krzysztof Adamowicz, 2023. "Predicting Post-Production Biomass Prices," Energies, MDPI, vol. 16(8), pages 1-16, April.
    24. Mehmet Balcilar & NICO KATZKE & Rangan Gupta, 2015. "Do Precious Metal Prices Help in Forecasting South African Inflation?," Working Papers 15-05, Eastern Mediterranean University, Department of Economics.
    25. Cepni, Oguzhan & Clements, Michael P., 2024. "How local is the local inflation factor? Evidence from emerging European countries," International Journal of Forecasting, Elsevier, vol. 40(1), pages 160-183.
    26. Silva, Emmanuel Sirimal & Ghodsi, Zara & Ghodsi, Mansi & Heravi, Saeed & Hassani, Hossein, 2017. "Cross country relations in European tourist arrivals," Annals of Tourism Research, Elsevier, vol. 63(C), pages 151-168.
    27. Marchetti, D.J. & Parigi, G., 1998. "Energy Consumption, Survey Data and the Prediction of Industrial Production in Italy," Papers 342, Banca Italia - Servizio di Studi.
    28. Bonato, Matteo & Gkillas, Konstantinos & Gupta, Rangan & Pierdzioch, Christian, 2021. "A note on investor happiness and the predictability of realized volatility of gold," Finance Research Letters, Elsevier, vol. 39(C).
    29. Silva, Emmanuel Sirimal & Hassani, Hossein & Heravi, Saeed & Huang, Xu, 2019. "Forecasting tourism demand with denoised neural networks," Annals of Tourism Research, Elsevier, vol. 74(C), pages 134-154.
    30. Hamid Baghestani, 2011. "A directional analysis of Federal Reserve predictions of growth in unit labor costs and productivity," International Review of Applied Economics, Taylor & Francis Journals, vol. 25(3), pages 303-311.
    31. Robert Lehmann, 2016. "Economic Growth and Business Cycle Forecasting at the Regional Level," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 65.
    32. Aye, Goodness C. & Balcilar, Mehmet & Gupta, Rangan & Majumdar, Anandamayee, 2015. "Forecasting aggregate retail sales: The case of South Africa," International Journal of Production Economics, Elsevier, vol. 160(C), pages 66-79.
    33. Antipa, Pamfili & Barhoumi, Karim & Brunhes-Lesage, Véronique & Darné, Olivier, 2012. "Nowcasting German GDP: A comparison of bridge and factor models," Journal of Policy Modeling, Elsevier, vol. 34(6), pages 864-878.
    34. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2015. "Realtime nowcasting with a Bayesian mixed frequency model with stochastic volatility," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(4), pages 837-862, October.
    35. Verena Monschang & Mark Trede & Bernd Wilfling, 2023. "Multi-horizon uniform superior predictive ability revisited: A size-exploiting and consistent test," CQE Working Papers 10623, Center for Quantitative Economics (CQE), University of Muenster.
    36. Alia Afzal & Philipp Sibbertsen, 2021. "Modeling fractional cointegration between high and low stock prices in Asian countries," Empirical Economics, Springer, vol. 60(2), pages 661-682, February.
    37. Yuchen Zhang & Shigeyuki Hamori, 2020. "The Predictability of the Exchange Rate When Combining Machine Learning and Fundamental Models," JRFM, MDPI, vol. 13(3), pages 1-16, March.
    38. Jin Shang & Shigeyuki Hamori, 2023. "Do Large Datasets or Hybrid Integrated Models Outperform Simple Ones in Predicting Commodity Prices and Foreign Exchange Rates?," JRFM, MDPI, vol. 16(6), pages 1-25, June.
    39. Thomas A. Knetsch, 2004. "Evaluating the German Inventory Cycle – Using Data from the Ifo Business Survey," CESifo Working Paper Series 1202, CESifo.
    40. Thomas Hasenzagl & Filippo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2022. "A Model of the Fed's View on Inflation," The Review of Economics and Statistics, MIT Press, vol. 104(4), pages 686-704, October.
    41. Nima Nonejad, 2021. "Should crude oil price volatility receive more attention than the price of crude oil? An empirical investigation via a large‐scale out‐of‐sample forecast evaluation of US macroeconomic data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 769-791, August.
    42. Barbaglia, Luca & Frattarolo, Lorenzo & Onorante, Luca & Pericoli, Filippo Maria & Ratto, Marco & Tiozzo Pezzoli, Luca, 2022. "Testing big data in a big crisis: Nowcasting under COVID-19," Working Papers 2022-06, Joint Research Centre, European Commission.
    43. Goodness C. Aye & Stephen M. Miller & Rangan Gupta & Mehmet Balcilar, 2013. "Forecasting the US Real Private Residential Fixed Investment Using Large Number of Predictors," Working Papers 201348, University of Pretoria, Department of Economics.
    44. Xuan, Chunji & Kim, Chang-Jin, 2020. "Structural breaks in the mean of dividend-price ratios: Implications of learning on stock return predictability," Japan and the World Economy, Elsevier, vol. 55(C).
    45. Stelios D. Bekiros & Alessia Paccagnini, 2014. "Estimating point and density forecasts for the US economy with a factor-augmented vector autoregressive DSGE model," Open Access publications 10197/7588, School of Economics, University College Dublin.
    46. Gabriel Pino & J. D. Tena & Antoni Espasa, 2016. "Geographical disaggregation of sectoral inflation. Econometric modelling of the Euro area and Spanish economies," Applied Economics, Taylor & Francis Journals, vol. 48(9), pages 799-815, February.
    47. Catherine Doz & Laurent Ferrara & Pierre-Alain Pionnier, 2020. "Business cycle dynamics after the Great Recession: An extended Markov-Switching Dynamic Factor Model," OECD Statistics Working Papers 2020/01, OECD Publishing.
    48. Raïsa Basselier & David Antonio Liedo & Geert Langenus, 2018. "Nowcasting Real Economic Activity in the Euro Area: Assessing the Impact of Qualitative Surveys," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(1), pages 1-46, April.
    49. Fildes, Robert & Stekler, Herman, 2002. "The state of macroeconomic forecasting," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 435-468, December.
    50. Li, Hengyun & Hu, Mingming & Li, Gang, 2020. "Forecasting tourism demand with multisource big data," Annals of Tourism Research, Elsevier, vol. 83(C).
    51. Christophe Boucher & Bertrand Maillet, 2012. "Prévoir sans persistance," Post-Print hal-01386006, HAL.
    52. Aktham Maghyereh & Hussein Abdoh, 2022. "Global financial crisis versus COVID‐19: Evidence from sentiment analysis," International Finance, Wiley Blackwell, vol. 25(2), pages 218-248, August.
    53. Koop, G & Korobilis, D, 2018. "Forecasting with High-Dimensional Panel VARs," Essex Finance Centre Working Papers 21329, University of Essex, Essex Business School.
    54. Chris Florakis & Gianluigi Giorgioni & Alexandros Kostakis & Costas Milas, 2012. "The Impact of Stock Market Illiquidity on Real UK GDP Growth," Working Paper series 65_12, Rimini Centre for Economic Analysis.
    55. Costas Milas & Jesus Otero & Theodore Panagiotidis, 2001. "Forecasting the spot prices of various coffee types using linear and non-linear error correction models," Borradores de Investigación 2737, Universidad del Rosario.
    56. Caruso, Alberto, 2018. "Nowcasting with the help of foreign indicators: The case of Mexico," Economic Modelling, Elsevier, vol. 69(C), pages 160-168.
    57. Dong, Yunxuan & Wang, Jing & Xiao, Ling & Fu, Tonglin, 2021. "Short-term wind speed time series forecasting based on a hybrid method with multiple objective optimization for non-convex target," Energy, Elsevier, vol. 215(PB).
    58. Donato Ceci & Orest Prifti & Andrea Silvestrini, 2024. "Nowcasting Italian GDP growth: a Factor MIDAS approach," Temi di discussione (Economic working papers) 1446, Bank of Italy, Economic Research and International Relations Area.
    59. Gkillas, Konstantinos & Gupta, Rangan & Pierdzioch, Christian, 2020. "Forecasting realized oil-price volatility: The role of financial stress and asymmetric loss," Journal of International Money and Finance, Elsevier, vol. 104(C).
    60. Mehmet Balcilar & Rangan Gupta & Anandamayee Majumdar & Stephen M. Miller, 2015. "Was the recent downturn in US real GDP predictable?," Applied Economics, Taylor & Francis Journals, vol. 47(28), pages 2985-3007, June.
    61. Constantin Burgi, 2016. "What Do We Lose When We Average Expectations?," Working Papers 2016-013, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    62. Hassani, Hossein & Silva, Emmanuel Sirimal & Gupta, Rangan & Das, Sonali, 2018. "Predicting global temperature anomaly: A definitive investigation using an ensemble of twelve competing forecasting models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 121-139.
    63. Hollstein, Fabian, 2020. "Estimating beta: The international evidence," Journal of Banking & Finance, Elsevier, vol. 121(C).
    64. Aaronson, Daniel & Brave, Scott A. & Butters, R. Andrew & Fogarty, Michael & Sacks, Daniel W. & Seo, Boyoung, 2022. "Forecasting unemployment insurance claims in realtime with Google Trends," International Journal of Forecasting, Elsevier, vol. 38(2), pages 567-581.
    65. Matteo Bonato & Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2020. "Investor Happiness and Predictability of the Realized Volatility of Oil Price," Working Papers 202009, University of Pretoria, Department of Economics.
    66. Marie Bessec, 2013. "Short‐Term Forecasts of French GDP: A Dynamic Factor Model with Targeted Predictors," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(6), pages 500-511, September.
    67. Marian Vavra, 2015. "On a Bootstrap Test for Forecast Evaluations," Working and Discussion Papers WP 5/2015, Research Department, National Bank of Slovakia.
    68. Giampiero M. Gallo & Edoardo Otranto, 2012. "Realized Volatility and Change of Regimes," Econometrics Working Papers Archive 2012_02, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Jul 2012.
    69. Bauwens, Luc & Sucarrat, Genaro, 2008. "General to specific modelling of exchange rate volatility : a forecast evaluation," UC3M Working papers. Economics we081810, Universidad Carlos III de Madrid. Departamento de Economía.
    70. Michael P. Clements & Philip Hans Franses & Norman R. Swanson, 2003. "Forecasting economic and financial time-series with non-linear models," Departmental Working Papers 200309, Rutgers University, Department of Economics.
    71. Guglielmo Maria Caporale & Juncal Cunado & Luis A. Gil-Alana, 2008. "Modelling Long-Run Trends and Cycles in Financial Time Series Data," CESifo Working Paper Series 2330, CESifo.
    72. Elizondo Rocío, 2013. "Forecasting the Term Structure of Interest Rates in Mexico Using an Affine Model," Working Papers 2013-03, Banco de México.
    73. Isabel Figuerola‐Ferretti & Alejandro Rodríguez & Eduardo Schwartz, 2021. "Oil price analysts' forecasts," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(9), pages 1351-1374, September.
    74. Carlo Altavilla & Paul De Grauwe, 2006. "Forecasting and Combining Competing Models of Exchange Rate Determination," CESifo Working Paper Series 1747, CESifo.
    75. Elie Bouri & Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2021. "Forecasting Realized Volatility of Bitcoin: The Role of the Trade War," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 29-53, January.
    76. Ali B. Barlas & Seda Guler Mert & Berk Orkun Isa & Alvaro Ortiz & Tomasa Rodrigo & Baris Soybilgen & Ege Yazgan, 2024. "Big data financial transactions and GDP nowcasting: The case of Turkey," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 227-248, March.
    77. Kuo‐Hsuan Chin, 2022. "Forecast evaluation of DSGE models: Linear and nonlinear likelihood," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1099-1130, September.
    78. Alberto Fuertes & Simón Sosvilla-Rivero, 2019. "“Forecasting emerging market currencies: Are inflation expectations useful?”," IREA Working Papers 201918, University of Barcelona, Research Institute of Applied Economics, revised Oct 2019.
    79. Carl Bonham & Peter Fuleky & James Jones & Ashley Hirashima, 2015. "Nowcasting Tourism Industry Performance Using High Frequency Covariates," Working Papers 2015-13R, University of Hawaii Economic Research Organization, University of Hawaii at Manoa, revised Jul 2016.
    80. Caroline Jardet & Baptiste Meunier, 2022. "Nowcasting world GDP growth with high‐frequency data," Post-Print hal-03647097, HAL.
    81. Arthur Thomas & Olivier Massol & Benoît Sévi, 2020. "How are Day-Ahead Prices Informative for Predicting the Next Day’s Consumption of Natural Gas ?," Working Papers hal-03178474, HAL.
    82. Dr. Marco Huwiler & Daniel Kaufmann, 2013. "Combining disaggregate forecasts for inflation: The SNB's ARIMA model," Economic Studies 2013-07, Swiss National Bank.
    83. Tim Janke & Florian Steinke, 2019. "Forecasting the Price Distribution of Continuous Intraday Electricity Trading," Energies, MDPI, vol. 12(22), pages 1-14, November.
    84. Li, Wei & Becker, Denis Mike, 2021. "Day-ahead electricity price prediction applying hybrid models of LSTM-based deep learning methods and feature selection algorithms under consideration of market coupling," Energy, Elsevier, vol. 237(C).
    85. Mizen, Paul & Tsoukas, Serafeim, 2012. "Forecasting US bond default ratings allowing for previous and initial state dependence in an ordered probit model," International Journal of Forecasting, Elsevier, vol. 28(1), pages 273-287.
    86. Chen, Xiaoshan & MacDonald, Ronald, 2014. "Measuring the Euro-Dollar Permanent Equilibrium Exchange Rate using the Unobserved Components Model," Stirling Economics Discussion Papers 2014-12, University of Stirling, Division of Economics.
    87. Rumler, Fabio & Valderrama, Maria Teresa, 2010. "Comparing the New Keynesian Phillips Curve with time series models to forecast inflation," The North American Journal of Economics and Finance, Elsevier, vol. 21(2), pages 126-144, August.
    88. Adediran, Idris A. & Swaray, Raymond, 2023. "Carbon trading amidst global uncertainty: The role of policy and geopolitical uncertainty," Economic Modelling, Elsevier, vol. 123(C).
    89. Duncan, Roberto & Martínez-García, Enrique, 2019. "New perspectives on forecasting inflation in emerging market economies: An empirical assessment," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1008-1031.
    90. Xu, Xiaojie, 2014. "Causality and Price Discovery in U.S. Corn Markets: An Application of Error Correction Modeling and Directed Acyclic Graphs," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 169806, Agricultural and Applied Economics Association.
    91. Florian Eckert & Rob J Hyndman & Anastasios Panagiotelis, 2019. "Forecasting Swiss Exports Using Bayesian Forecast Reconciliation," Monash Econometrics and Business Statistics Working Papers 14/19, Monash University, Department of Econometrics and Business Statistics.
    92. Christopher McDonald & Craig Thamotheram & Shaun P. Vahey & Elizabeth C. Wakerly, 2016. "Assessing the economic value of probabilistic forecasts in the presence of an inflation target," CAMA Working Papers 2016-40, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    93. Oleksandr Castello & Marina Resta, 2023. "A Machine-Learning-Based Approach for Natural Gas Futures Curve Modeling," Energies, MDPI, vol. 16(12), pages 1-22, June.
    94. Luis A. Gil-Alana & James Payne & David Loomis, 2010. "Does energy consumption by the US electric power secto exhibit long memory behaviour?," Faculty Working Papers 04/10, School of Economics and Business Administration, University of Navarra.
    95. Angelos Kanas, 2008. "Modeling regime transition in stock index futures markets and forecasting implications," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(8), pages 649-669.
    96. Xiaojie Xu, 2017. "The rolling causal structure between the Chinese stock index and futures," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 31(4), pages 491-509, November.
    97. Cubadda, Gianluca & Guardabascio, Barbara, 2012. "A medium-N approach to macroeconomic forecasting," Economic Modelling, Elsevier, vol. 29(4), pages 1099-1105.
    98. Fabio Gobbi, 2021. "Evaluating Forecasts from State-Dependent Autoregressive Models for US GDP Growth Rate. Comparison with Alternative Approaches," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 11(6), pages 1-7.
    99. Moonsoo Park & Yanhong Jin & Alan Love, 2011. "Dynamic and contemporaneous causality in a supply chain: an application of the US beef industry," Applied Economics, Taylor & Francis Journals, vol. 43(30), pages 4785-4801.
    100. GIOT, Pierre & PETITJEAN, Mikael, 2005. "Dynamic asset allocation between stocks and bonds using the Bond-Equity Yield Ratio," LIDAM Discussion Papers CORE 2005010, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    101. GIOT, Pierre & PETITJEAN, Mikael, 2007. "The information content of the Bond-Equity Yield Ratio: Better than a random walk?," LIDAM Reprints CORE 1982, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    102. Kuo-Hsuan Chin, 2019. "Fiscal Stimulus on Bayesian DSGE Models," Prague Economic Papers, Prague University of Economics and Business, vol. 2019(6), pages 688-708.
    103. Parigi, Giuseppe & Golinelli, Roberto, 2005. "Short-Run Italian GDP Forecasting and Real-Time Data," CEPR Discussion Papers 5302, C.E.P.R. Discussion Papers.
    104. Nicoletta Pashourtidou & Christos Papamichael & Charalampos Karagiannakis, 2018. "Forecasting economic activity in sectors of the Cypriot economy," Cyprus Economic Policy Review, University of Cyprus, Economics Research Centre, vol. 12(2), pages 24-66, December.
    105. Dora Borbély & Carsten-Patrick Meier, 2003. "Zum Konjunkturverbund zwischen der EU und den Beitrittsländern," Vierteljahrshefte zur Wirtschaftsforschung / Quarterly Journal of Economic Research, DIW Berlin, German Institute for Economic Research, vol. 72(4), pages 492-509.
    106. Pym Manopimoke & Vorada Limjaroenrat, 2016. "Trend Inflation Estimates for Thailand from Disaggregated Data," PIER Discussion Papers 51, Puey Ungphakorn Institute for Economic Research.
    107. Golosnoy, Vasyl & Gribisch, Bastian & Seifert, Miriam Isabel, 2019. "Exponential smoothing of realized portfolio weights," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 222-237.
    108. Maria Caporale, Guglielmo & A. Gil-Alana, Luis, 2011. "Multi-Factor Gegenbauer Processes and European Inflation Rates," Journal of Economic Integration, Center for Economic Integration, Sejong University, vol. 26, pages 386-409.
    109. Proietti, Tommaso & Lütkepohl, Helmut, 2013. "Does the Box–Cox transformation help in forecasting macroeconomic time series?," International Journal of Forecasting, Elsevier, vol. 29(1), pages 88-99.
    110. M. Marzo & P. Zagaglia, 2007. "Domestic political constraints to foreign aid effectiveness," Working Papers 599, Dipartimento Scienze Economiche, Universita' di Bologna.
    111. Heinen, Florian & Sibbertsen, Philipp & Kruse, Robinson, 2009. "Forecasting long memory time series under a break in persistence," Hannover Economic Papers (HEP) dp-433, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    112. Cem Cakmakli & Yasin Simsek, 2023. "Bridging the Covid-19 Data and the Epidemiological Model using Time-Varying Parameter SIRD Model," Papers 2301.13692, arXiv.org.
    113. Xiaoshan Chen & Ronald MacDonald, 2010. "Revisiting the Dollar-Euro Permanent Equilibrium Exchange Rate: Evidence from Multivariate Unobserved Components Models," Working Papers 2010_16, Business School - Economics, University of Glasgow.
    114. Tallman, Ellis W. & Zaman, Saeed, 2020. "Combining survey long-run forecasts and nowcasts with BVAR forecasts using relative entropy," International Journal of Forecasting, Elsevier, vol. 36(2), pages 373-398.
    115. Xiaojie Xu, 2017. "Short-run price forecast performance of individual and composite models for 496 corn cash markets," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(14), pages 2593-2620, October.
    116. Maximo Camacho & Marcos Dal Bianco & Gabriel Perez Quiros, 2012. "Short-run forecasting of the euro-dollar exchange rate with economic fundamentals," Working Papers 1201, BBVA Bank, Economic Research Department.
    117. Timo Teräsvirta & Dick van Dijk & Marcelo Cunha Medeiros, 2004. "Linear models, smooth transition autoregressions and neural networks for forecasting macroeconomic time series: A reexamination," Textos para discussão 485, Department of Economics PUC-Rio (Brazil).
    118. Demirer, Riza & Gkillas, Konstantinos & Gupta, Rangan & Pierdzioch, Christian, 2019. "Time-varying risk aversion and realized gold volatility," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    119. Vargas, Gregorio A., 2006. "An Asymmetric Block Dynamic Conditional Correlation Multivariate GARCH Model," MPRA Paper 189, University Library of Munich, Germany, revised Aug 2006.
    120. Chen, Yanhui & Zhang, Chuan & He, Kaijian & Zheng, Aibing, 2018. "Multi-step-ahead crude oil price forecasting using a hybrid grey wave model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 501(C), pages 98-110.
    121. Beckmann, Joscha & Czudaj, Robert L., 2020. "Fundamental determinants of exchange rate expectations," VfS Annual Conference 2020 (Virtual Conference): Gender Economics 224617, Verein für Socialpolitik / German Economic Association.
    122. Clark, Todd & McCracken, Michael, 2013. "Advances in Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1107-1201, Elsevier.
    123. Johanna Garnitz & Robert Lehmann & Klaus Wohlrabe, 2019. "Forecasting GDP all over the world using leading indicators based on comprehensive survey data," Applied Economics, Taylor & Francis Journals, vol. 51(54), pages 5802-5816, November.
    124. Andreas Karatahansopoulos & Georgios Sermpinis & Jason Laws & Christian Dunis, 2014. "Modelling and Trading the Greek Stock Market with Gene Expression and Genetic Programing Algorithms," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(8), pages 596-610, December.
    125. Elena Angelini & Gonzalo Camba‐Mendez & Domenico Giannone & Lucrezia Reichlin & Gerhard Rünstler, 2011. "Short‐term forecasts of euro area GDP growth," Econometrics Journal, Royal Economic Society, vol. 14(1), pages 25-44, February.
    126. Nikoleta Anesti & Ana Beatriz Galvão & Silvia Miranda‐Agrippino, 2022. "Uncertain Kingdom: Nowcasting Gross Domestic Product and its revisions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 42-62, January.
    127. Anna Sznajderska & Alfred A. Haug, 2023. "Bayesian VARs of the U.S. economy before and during the pandemic," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 13(2), pages 211-236, June.
    128. Konstantin S. Rybak, 2023. "Анализ Важности Глобальных Факторов Для Наукастинга Ввп," Russian Economic Development (in Russian), Gaidar Institute for Economic Policy, issue 12, pages 18-23, December.
    129. Mills, Terence C. & Pepper, Gordon T., 1999. "Assessing the forecasters: an analysis of the forecasting records of the Treasury, the London Business School and the National Institute," International Journal of Forecasting, Elsevier, vol. 15(3), pages 247-257, July.
    130. Breitung, Jörg & Knüppel, Malte, 2018. "How far can we forecast? Statistical tests of the predictive content," Discussion Papers 07/2018, Deutsche Bundesbank.
    131. Michael Pedersen, 2024. "Judgment in macroeconomic output growth predictions: Efficiency, accuracy and persistence," Papers 2404.04105, arXiv.org.
    132. Michael Funke & Aaron Mehrotra & Hao Yu, 2015. "Tracking Chinese CPI inflation in real time," Empirical Economics, Springer, vol. 48(4), pages 1619-1641, June.
    133. Michael D. Bauer & Glenn D. Rudebusch, 2020. "Interest Rates under Falling Stars," American Economic Review, American Economic Association, vol. 110(5), pages 1316-1354, May.
    134. Héctor Mauricio Nunez Amortegui, 2005. "Una evaluación de los pronósticos de inflación en Colombia bajo el esquema de inflación objetivo," Revista de Economía del Rosario, Universidad del Rosario, December.
    135. Klaus Abberger & Michael Graff & Boriss Siliverstovs & Jan-Egbert Sturm, 2014. "The KOF Economic Barometer, Version 2014," KOF Working papers 14-353, KOF Swiss Economic Institute, ETH Zurich.
    136. Hinterlang, Natascha, 2020. "Predicting monetary policy using artificial neural networks," Discussion Papers 44/2020, Deutsche Bundesbank.
    137. Meyler, Aidan & Grothe, Magdalena, 2015. "Inflation forecasts: Are market-based and survey-based measures informative?," Working Paper Series 1865, European Central Bank.
    138. Buncic, Daniel, 2009. "Understanding forecast failure in ESTAR models of real exchange rates," MPRA Paper 13121, University Library of Munich, Germany.
    139. Ilias Lekkos & Costas Milas & Theodore Panagiotidis, 2007. "Forecasting interest rate swap spreads using domestic and international risk factors: evidence from linear and non-linear models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(8), pages 601-619.
    140. Boriss Siliverstovs, 2011. "The Real-Time Predictive Content of the KOF Economic Barometer," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 147(III), pages 353-375, September.
    141. Maximo Camacho, 2002. "Nonlinear stochastic trends and economic fluctuations," Computing in Economics and Finance 2002 274, Society for Computational Economics.
    142. McAleer, Michael & Medeiros, Marcelo C., 2008. "A multiple regime smooth transition Heterogeneous Autoregressive model for long memory and asymmetries," Journal of Econometrics, Elsevier, vol. 147(1), pages 104-119, November.
    143. Olivier Darne & Amelie Charles, 2020. "Nowcasting GDP growth using data reduction methods: Evidence for the French economy," Economics Bulletin, AccessEcon, vol. 40(3), pages 2431-2439.
    144. Guillaume Chevillon, 2007. "Direct Multi‐Step Estimation And Forecasting," Journal of Economic Surveys, Wiley Blackwell, vol. 21(4), pages 746-785, September.
    145. Nikolay Robinzonov & Klaus Wohlrabe, 2010. "Freedom of Choice in Macroeconomic Forecasting ," CESifo Economic Studies, CESifo Group, vol. 56(2), pages 192-220, June.
    146. Hakan Kara & Pinar Ozlu & Deren Unalmis, 2015. "Turkiye icin Finansal Kosullar Endeksi," Working Papers 1513, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    147. Nonejad, Nima, 2019. "Forecasting aggregate equity return volatility using crude oil price volatility: The role of nonlinearities and asymmetries," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    148. Juncal Cuñado & Luis A. Gil-Alaña, 2007. "Tourism in the Canary Islands: Forecasting Using Several Seasonal Time Series Models," Faculty Working Papers 02/07, School of Economics and Business Administration, University of Navarra.
    149. Berrisch, Jonathan & Pappert, Sven & Ziel, Florian & Arsova, Antonia, 2023. "Modeling volatility and dependence of European carbon and energy prices," Finance Research Letters, Elsevier, vol. 52(C).
    150. Łukasz Lenart & Agnieszka Leszczyńska-Paczesna, 2016. "Do market prices improve the accuracy of inflation forecasting in Poland? A disaggregated approach," Bank i Kredyt, Narodowy Bank Polski, vol. 47(5), pages 365-394.
    151. Elisa Jorge-González & Enrique González-Dávila & Raquel Martín-Rivero & Domingo Lorenzo-Díaz, 2020. "Univariate and multivariate forecasting of tourism demand using state-space models," Tourism Economics, , vol. 26(4), pages 598-621, June.
    152. Konstantin Kholodilin, 2014. "Business confidence and forecasting of housing prices and rents in large German cities," ERSA conference papers ersa14p9, European Regional Science Association.
    153. Edda Claus, 2011. "Seven Leading Indexes of New Zealand Employment," The Economic Record, The Economic Society of Australia, vol. 87(276), pages 76-89, March.
    154. Chortareas, Georgios & Jiang, Ying & Nankervis, John. C., 2011. "Forecasting exchange rate volatility using high-frequency data: Is the euro different?," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1089-1107, October.
    155. Suleman Sarwar & Ghazala Aziz & Daniel Balsalobre-Lorente, 2023. "Forecasting Accuracy of Traditional Regression, Machine Learning, and Deep Learning: A Study of Environmental Emissions in Saudi Arabia," Sustainability, MDPI, vol. 15(20), pages 1-22, October.
    156. Costas Milas & Ruthira Naraidoo, 2009. "Financial Market Conditions, Real Time, Nonlinearity and European Central Bank Monetary Policy: In-Sample and Out-of-Sample Assessment," Working Paper series 42_09, Rimini Centre for Economic Analysis.
    157. Jeronymo Marcondes Pinto & Jennifer L. Castle, 2022. "Machine Learning Dynamic Switching Approach to Forecasting in the Presence of Structural Breaks," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 18(2), pages 129-157, July.
    158. Oguzhan Cepni & Riza Demirer & Rangan Gupta & Christian Pierdzioch, 2019. "Time-Varying Risk Aversion and the Predictability of Bond Premia," Working Papers 201906, University of Pretoria, Department of Economics.
    159. Koop, Gary & Korobilis, Dimitris & Pettenuzzo, Davide, 2019. "Bayesian compressed vector autoregressions," Journal of Econometrics, Elsevier, vol. 210(1), pages 135-154.
    160. Scott Brave & R. Andrew Butters & Alejandro Justiniano, 2016. "Forecasting Economic Activity with Mixed Frequency Bayesian VARs," Working Paper Series WP-2016-5, Federal Reserve Bank of Chicago.
    161. Schiff, Aaron & Phillips, Peter, 2000. "Forecasting New Zealand's Real GDP," Working Papers 186, Department of Economics, The University of Auckland.
    162. Edward S. Knotek & Saeed Zaman, 2014. "Nowcasting U.S. Headline and Core Inflation," Working Papers (Old Series) 1403, Federal Reserve Bank of Cleveland.
    163. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2020. "No-Arbitrage Priors, Drifting Volatilities, and the Term Structure of Interest Rates," Working Papers 20-27, Federal Reserve Bank of Cleveland.
    164. Lechner, Sandra & Nolte, Ingmar, 2007. "Customer trading in the foreign exchange market empirical evidence from an internet trading platform," CoFE Discussion Papers 07/03, University of Konstanz, Center of Finance and Econometrics (CoFE).
    165. Kasai, Ndahiriwe & Naraidoo, Ruthira, 2011. "Evaluating the forecasting performance of linear and nonlinear monetary policy rules for South Africa," MPRA Paper 40699, University Library of Munich, Germany.
    166. Fildes, Robert & Wei, Yingqi & Ismail, Suzilah, 2011. "Evaluating the forecasting performance of econometric models of air passenger traffic flows using multiple error measures," International Journal of Forecasting, Elsevier, vol. 27(3), pages 902-922.
    167. Bekkerman, Anton & Brester, Gary W. & Taylor, Mykel, 2016. "Forecasting a Moving Target: The Roles of Quality and Timing for Determining Northern U.S. Wheat Basis," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 41(1), pages 1-17, January.
    168. Marcelo Cunha Medeiros & Álvaro Veiga & Carlos Eduardo Pedreira, 2000. "Modelling exchange rates: smooth transitions, neural networks, and linear models," Textos para discussão 432, Department of Economics PUC-Rio (Brazil).
    169. Hirashima, Ashley & Jones, James & Bonham, Carl S. & Fuleky, Peter, 2017. "Forecasting in a Mixed Up World: Nowcasting Hawaii Tourism," Annals of Tourism Research, Elsevier, vol. 63(C), pages 191-202.
    170. Malte Knüppel & Guido Schultefrankenfeld, 2017. "Interest rate assumptions and predictive accuracy of central bank forecasts," Empirical Economics, Springer, vol. 53(1), pages 195-215, August.
    171. Milas, Costas & Rothman, Philip, 2008. "Out-of-sample forecasting of unemployment rates with pooled STVECM forecasts," International Journal of Forecasting, Elsevier, vol. 24(1), pages 101-121.
    172. Christopher Martin & Costas Milas, 2007. "Testing the Opportunistic Approach to Monetary Policy," Keele Economics Research Papers KERP 2007/02, Centre for Economic Research, Keele University.
    173. Sarantis, Nicholas, 2006. "On the short-term predictability of exchange rates: A BVAR time-varying parameters approach," Journal of Banking & Finance, Elsevier, vol. 30(8), pages 2257-2279, August.
    174. Yun, Jaeho, 2019. "Bond risk premia in a small open economy with volatile capital flows: The case of Korea," Journal of International Money and Finance, Elsevier, vol. 93(C), pages 223-243.
    175. Beatriz Vaz de Melo Mendes & Victor Bello Accioly, 2017. "Improving (E)GARCH forecasts with robust realized range measures: Evidence from international markets," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 41(4), pages 631-658, October.
    176. Kruse, Robinson & Leschinski, Christian & Will, Michael, 2016. "Comparing Predictive Accuracy under Long Memory - With an Application to Volatility Forecasting," Hannover Economic Papers (HEP) dp-571, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    177. Ahmad, Saad & Civelli, Andrea, 2016. "Globalization and inflation: A threshold investigation," Journal of Macroeconomics, Elsevier, vol. 48(C), pages 283-304.
    178. Marco J. Lombardi & Francesco Ravazzolo, 2012. "Oil price density forecasts: exploring the linkages with stock markets," Working Paper 2012/24, Norges Bank.
    179. Frédérique Bec & Annabelle de Gaye, 2019. "Le modèle autorégressif autorégressif à seuil avec effet rebond : Une application aux rendements boursiers français et américains ," Working Papers hal-02014663, HAL.
    180. Duarte, Pablo & Süßmuth, Bernd, 2018. "Implementing an approximate dynamic factor model to nowcast GDP using sensitivity analysis," Working Papers 152, University of Leipzig, Faculty of Economics and Management Science.
    181. Götz, Thomas B. & Knetsch, Thomas A., 2019. "Google data in bridge equation models for German GDP," International Journal of Forecasting, Elsevier, vol. 35(1), pages 45-66.
    182. Easaw, Joshy Z. & Heravi, Saeed M., 2004. "Evaluating consumer sentiments as predictors of UK household consumption behavior: Are they accurate and useful?," International Journal of Forecasting, Elsevier, vol. 20(4), pages 671-681.
    183. Fiszeder, Piotr & Fałdziński, Marcin & Molnár, Peter, 2019. "Range-based DCC models for covariance and value-at-risk forecasting," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 58-76.
    184. Salisu, Afees A. & Bouri, Elie & Gupta, Rangan, 2022. "Out-of-sample predictability of gold market volatility: The role of US Nonfarm Payroll," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 482-488.
    185. Rita Pimentel & Morten Risstad & Sjur Westgaard, 2022. "Predicting interest rate distributions using PCA & quantile regression," Digital Finance, Springer, vol. 4(4), pages 291-311, December.
    186. Andrejs Bessonovs & Olegs Krasnopjorovs, 2020. "Short-Term Inflation Projections Model and Its Assessment in Latvia," Working Papers 2020/01, Latvijas Banka.
    187. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    188. Daniel L. Thornton, 2005. "Predictions of short-term rates and the expectations hypothesis of the term structure of interest rates," Working Papers 2004-010, Federal Reserve Bank of St. Louis.
    189. Franses, Ph.H.B.F. & van Dijk, D.J.C., 2001. "The forecasting performance of various models for seasonality and nonlinearity for quarterly industrial production," Econometric Institute Research Papers EI 2001-14, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    190. Colino, Evelyn V. & Irwin, Scott H. & Garcia, Philip, 2009. "Do Composite Procedures Really Improve the Accuracy of Outlook Forecasts?," 2009 Conference, April 20-21, 2009, St. Louis, Missouri 53052, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    191. No, Sung Chul & Salassi, Michael E., 2006. "Dynamic Analysis and Forecasts of Rough Rice Price under Government Price Support Program: An Application of Bayesian VAR," 2006 Annual Meeting, February 5-8, 2006, Orlando, Florida 35279, Southern Agricultural Economics Association.
    192. Kopnova, Elena & Rodionova, Liliya, 2020. "Globalization and socio-economic development in Russia," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 60, pages 80-101.
    193. Gerhard Fenz & Martin Spitzer, 2006. "An Unobserved Components Model to Forecast Austrian GDP," Working Papers 119, Oesterreichische Nationalbank (Austrian Central Bank).
    194. Konstantin Kuck & Karsten Schweikert, 2021. "Forecasting Baden‐Württemberg's GDP growth: MIDAS regressions versus dynamic mixed‐frequency factor models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 861-882, August.
    195. Taufiq Choudhry & Hao Wu, 2008. "Forecasting ability of GARCH vs Kalman filter method: evidence from daily UK time-varying beta," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(8), pages 670-689.
    196. Camila Epprecht & Dominique Guegan & Álvaro Veiga & Joel Correa da Rosa, 2017. "Variable selection and forecasting via automated methods for linear models: LASSO/adaLASSO and Autometrics," Post-Print halshs-00917797, HAL.
    197. Grabowski, Szymon, 2008. "What does a financial system say about future economic growth?," MPRA Paper 11560, University Library of Munich, Germany.
    198. Baghestani, Hamid, 2009. "Survey evidence on forecast accuracy of U.S. term spreads," Review of Financial Economics, Elsevier, vol. 18(3), pages 156-162, August.
    199. Carlos Cañizares Martínez & Gabe J. de Bondt & Arne Gieseck, 2023. "Forecasting housing investment," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(3), pages 543-565, April.
    200. Caio Vigo Pereira, 2020. "Portfolio Efficiency with High-Dimensional Data as Conditioning Information," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202015, University of Kansas, Department of Economics, revised Sep 2020.
    201. Marshall, Andrew & Maulana, Tubagus & Tang, Leilei, 2009. "The estimation and determinants of emerging market country risk and the dynamic conditional correlation GARCH model," International Review of Financial Analysis, Elsevier, vol. 18(5), pages 250-259, December.
    202. Hubrich, Kirstin, 2005. "Forecasting euro area inflation: Does aggregating forecasts by HICP component improve forecast accuracy?," International Journal of Forecasting, Elsevier, vol. 21(1), pages 119-136.
    203. Amit Goyal & Ivo Welch, 2002. "Predicting the Equity Premium With Dividend Ratios," NBER Working Papers 8788, National Bureau of Economic Research, Inc.
    204. Ubilava, David & Helmers, C Gustav, 2012. "Forecasting ENSO with a smooth transition autoregressive model," MPRA Paper 36890, University Library of Munich, Germany.
    205. Minchul Shin & Molin Zhong, 2015. "Does Realized Volatility Help Bond Yield Density Prediction?," Finance and Economics Discussion Series 2015-115, Board of Governors of the Federal Reserve System (U.S.).
    206. Robert Lehmann & Klaus Wohlrabe, 2012. "Forecasting GDP at the Regional Level with Many Predictors," CESifo Working Paper Series 3956, CESifo.
    207. Jiao, Xiaoying & Li, Gang & Chen, Jason Li, 2020. "Forecasting international tourism demand: a local spatiotemporal model," Annals of Tourism Research, Elsevier, vol. 83(C).
    208. Hännikäinen Jari, 2016. "The shadow rate as a predictor of real activity and inflation: Evidence from a data-rich environment," Working Papers 1606, Tampere University, Faculty of Management and Business, Economics.
    209. Maximo Camacho & Rafael Domenech, 2010. "MICA-BBVA: A Factor Model of Economic and Financial Indicators for Short-term GDP Forecasting," Working Papers 1021, BBVA Bank, Economic Research Department.
    210. Brand, Claus & Reimers, Hans-Eggert & Seitz, Franz, 2003. "Forecasting real GDP: what role for narrow money?," Working Paper Series 254, European Central Bank.
    211. Carstensen, Kai & Wohlrabe, Klaus & Ziegler, Christina, 2011. "Predictive ability of business cycle indicators under test: A case study for the Euro area industrial production," Munich Reprints in Economics 19953, University of Munich, Department of Economics.
    212. Robert Lehmann & Klaus Wohlrabe, 2013. "Forecasting gross value-added at the regional level: Are sectoral disaggregated predictions superior to direct ones?," ifo Working Paper Series 171, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    213. Rodrigo Sekkel, 2014. "Balance Sheets of Financial Intermediaries: Do They Forecast Economic Activity?," Staff Working Papers 14-40, Bank of Canada.
    214. Kennan,J., 2001. "Uniqueness of positive fixed points for increasing concave functions on Rn : an elementary result," Working papers 2, Wisconsin Madison - Social Systems.
    215. Robert Lehmann, 2023. "READ-GER: Introducing German Real-Time Regional Accounts Data for Revision Analysis and Nowcasting," CESifo Working Paper Series 10315, CESifo.
    216. Chao Zhang & Xingyue Pu & Mihai Cucuringu & Xiaowen Dong, 2023. "Graph Neural Networks for Forecasting Multivariate Realized Volatility with Spillover Effects," Papers 2308.01419, arXiv.org.
    217. Hwee Kwan Chow & Keen Meng Choy, 2004. "Forecasting the Global Electronics Cycle with Leading Indicators: A VAR Approach," Working Papers 16-2004, Singapore Management University, School of Economics.
    218. Heinisch, Katja & Lindner, Axel, 2021. "Economic sentiment: Disentangling private information from public knowledge," IWH Discussion Papers 15/2021, Halle Institute for Economic Research (IWH).
    219. Hampel, Katharina & Kunz, Marcus & Schanne, Norbert & Wapler, Rüdiger & Weyh, Antje, 2007. "Regional employment forecasts with spatial interdependencies," IAB-Discussion Paper 200702, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    220. Kajal Lahiri & George Monokroussos, 2011. "Nowcasting US GDP: The role of ISM Business Surveys," Discussion Papers 11-01, University at Albany, SUNY, Department of Economics.
    221. Edward S. Knotek & Saeed Zaman, 2017. "Financial Nowcasts and Their Usefulness in Macroeconomic Forecasting," Working Papers (Old Series) 1702, Federal Reserve Bank of Cleveland.
    222. Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman K. van Dijk, 2013. "Parallel Sequential Monte Carlo for Efficient Density Combination: The Deco Matlab Toolbox," CREATES Research Papers 2013-09, Department of Economics and Business Economics, Aarhus University.
    223. Hanan Naser, 2015. "Estimating and forecasting Bahrain quarterly GDP growth using simple regression and factor-based methods," Empirical Economics, Springer, vol. 49(2), pages 449-479, September.
    224. G. Boero & E. Marrocu, 2002. "The performance of Setar Models: a regime conditional evaluation of point, interval and density forecasts," Working Paper CRENoS 200208, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    225. Romulo A. Chumacero, 2004. "Forecasting Chilean Industrial Production and Sales with Automated Procedures," Computing in Economics and Finance 2004 112, Society for Computational Economics.
    226. Skrove Falch, Nina & Nymoen, Ragnar, 2011. "The accuracy of a forecast targeting central bank," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 5, pages 1-36.
    227. Salisu, Afees A. & Ogbonna, Ahamuefula E. & Lasisi, Lukman & Olaniran, Abeeb, 2022. "Geopolitical risk and stock market volatility in emerging markets: A GARCH – MIDAS approach," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    228. Pedregal, Diego J. & Pérez, Javier J., 2010. "Should quarterly government finance statistics be used for fiscal surveillance in Europe?," International Journal of Forecasting, Elsevier, vol. 26(4), pages 794-807, October.
    229. Cubadda, Gianluca & Guardabascio, Barbara & Hecq, Alain, 2017. "A vector heterogeneous autoregressive index model for realized volatility measures," International Journal of Forecasting, Elsevier, vol. 33(2), pages 337-344.
    230. Evelyn V. Colino & Scott H. Irwin, 2010. "Outlook vs. Futures: Three Decades of Evidence in Hog and Cattle Markets," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 92(1), pages 1-15.
    231. Mehmet Balcilar & Rangan Gupta & Stephen M. Miller, 2012. "The Out-of-Sample Forecasting Performance of Non-Linear Models of Regional Housing Prices in the US," Working papers 2012-12, University of Connecticut, Department of Economics.
    232. Gao, Yuyang & Wang, Jianzhou & Yang, Hufang, 2022. "A multi-component hybrid system based on predictability recognition and modified multi-objective optimization for ultra-short-term onshore wind speed forecasting," Renewable Energy, Elsevier, vol. 188(C), pages 384-401.
    233. Song, Haiyan & Li, Gang & Witt, Stephen F. & Athanasopoulos, George, 2011. "Forecasting tourist arrivals using time-varying parameter structural time series models," International Journal of Forecasting, Elsevier, vol. 27(3), pages 855-869.
    234. Baghestani, Hamid, 2011. "Federal Reserve and private forecasts of growth in investment," Journal of Economics and Business, Elsevier, vol. 63(4), pages 290-305, July.
    235. Wei Kuang, 2021. "Conditional covariance matrix forecast using the hybrid exponentially weighted moving average approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1398-1419, December.
    236. Halkos, George E. & Tsirivis, Apostolos S., 2019. "Effective energy commodity risk management: Econometric modeling of price volatility," Economic Analysis and Policy, Elsevier, vol. 63(C), pages 234-250.
    237. Li, Mengheng & Koopman, Siem Jan & Lit, Rutger & Petrova, Desislava, 2020. "Long-term forecasting of El Niño events via dynamic factor simulations," Journal of Econometrics, Elsevier, vol. 214(1), pages 46-66.
    238. Havranek, Tomas & Zeynalov, Ayaz, 2018. "Forecasting Tourist Arrivals: Google Trends Meets Mixed Frequency Data," MPRA Paper 90205, University Library of Munich, Germany.
    239. Juan Antolin-Diaz & Thomas Drechsel & Ivan Petrella, 2014. "Tracking the Slowdown in Long-Run GDP Growth," Discussion Papers 1604, Centre for Macroeconomics (CFM), revised Jan 2016.
    240. Afees A. Salisu & Rangan Gupta & Sayar Karmakar & Sonali Das, 2021. "Forecasting Output Growth of Advanced Economies Over Eight Centuries: The Role of Gold Market Volatility as a Proxy of Global Uncertainty," Working Papers 202133, University of Pretoria, Department of Economics.
    241. Huang, Tao & Fildes, Robert & Soopramanien, Didier, 2019. "Forecasting retailer product sales in the presence of structural change," European Journal of Operational Research, Elsevier, vol. 279(2), pages 459-470.
    242. Xiaojie Xu, 2019. "Price dynamics in corn cash and futures markets: cointegration, causality, and forecasting through a rolling window approach," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 33(2), pages 155-181, June.
    243. Robert Gausden & Mohammad Hasan, 2022. "A reappraisal of Katona’s adaptive theory of consumer behaviour using U.K. data," Manchester School, University of Manchester, vol. 90(2), pages 122-143, March.
    244. Massimiliano Marzo & Paolo Zagaglia, 2010. "Volatility forecasting for crude oil futures," Applied Economics Letters, Taylor & Francis Journals, vol. 17(16), pages 1587-1599.
    245. Pami Dua & Lokendra Kumawat, 2005. "Modelling and Forecasting Seasonality in Indian Macroeconomic Time Series," Working papers 136, Centre for Development Economics, Delhi School of Economics.
    246. Duo Qin & Sophie van Huellen & Qing Chao Wang & Thanos Moraitis, 2022. "Algorithmic Modelling of Financial Conditions for Macro Predictive Purposes: Pilot Application to USA Data," Econometrics, MDPI, vol. 10(2), pages 1-22, April.
    247. Malley, Jim & Philippopoulos, Apostolis & Woitek, Ulrich, 2007. "Electoral uncertainty, fiscal policy and macroeconomic fluctuations," Journal of Economic Dynamics and Control, Elsevier, vol. 31(3), pages 1051-1080, March.
    248. Caporin, Massimiliano & Costola, Michele & Garibal, Jean-Charles & Maillet, Bertrand, 2022. "Systemic risk and severe economic downturns: A targeted and sparse analysis," Journal of Banking & Finance, Elsevier, vol. 134(C).
    249. Verena Monschang & Bernd Wilfling, 2022. "A procedure for upgrading linear-convex combination forecasts with an application to volatility prediction," CQE Working Papers 9722, Center for Quantitative Economics (CQE), University of Muenster.
    250. Schmidt, Torsten & Vosen, Simeon, 2010. "A monthly consumption indicator for Germany based on internet search query data," Ruhr Economic Papers 208, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    251. Helmut Herwartz, 2011. "Forecast accuracy and uncertainty in applied econometrics: a recommendation of specific-to-general predictor selection," Empirical Economics, Springer, vol. 41(2), pages 487-510, October.
    252. Albis, Manuel Leonard F. & Mapa, Dennis S., 2014. "Bayesian Averaging of Classical Estimates in Asymmetric Vector Autoregressive (AVAR) Models," MPRA Paper 55902, University Library of Munich, Germany.
    253. T.S. Tuang Buansing & Amos Golan & Aman Ullah, 2019. "Information-Theoretic Approach for Forecasting Interval-Valued SP500 Daily Returns," Working Papers 201922, University of California at Riverside, Department of Economics.
    254. Lord Mensah, 2013. "The Behavior of Beta in the 19th Century," Accounting and Finance Research, Sciedu Press, vol. 2(4), pages 1-34, November.
    255. Ding, Yishan, 2018. "A novel decompose-ensemble methodology with AIC-ANN approach for crude oil forecasting," Energy, Elsevier, vol. 154(C), pages 328-336.
    256. Goulas, Lambros & Skiadopoulos, George, 2012. "Are freight futures markets efficient? Evidence from IMAREX," International Journal of Forecasting, Elsevier, vol. 28(3), pages 644-659.
    257. Kuusela, Annika & Hännikäinen, Jari, 2017. "What do the shadow rates tell us about future inflation?," MPRA Paper 80542, University Library of Munich, Germany.
    258. Peng Chen & Andrew Vivian & Cheng Ye, 2022. "Forecasting carbon futures price: a hybrid method incorporating fuzzy entropy and extreme learning machine," Annals of Operations Research, Springer, vol. 313(1), pages 559-601, June.
    259. Camilla Muglia & Luca Santabarbara & Stefano Grassi, 2019. "Is Bitcoin a Relevant Predictor of Standard & Poor’s 500?," JRFM, MDPI, vol. 12(2), pages 1-10, May.
    260. Oscar Claveria & Enric Monte & Salvador Torra, 2016. "Modelling cross-dependencies between Spain’s regional tourism markets with an extension of the Gaussian process regression model," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 7(3), pages 341-357, August.
    261. Lombardi, Marco J. & Ravazzolo, Francesco, 2016. "On the correlation between commodity and equity returns: Implications for portfolio allocation," Journal of Commodity Markets, Elsevier, vol. 2(1), pages 45-57.
    262. Bekiros, Stelios D. & Paccagnini, Alessia, 2015. "Macroprudential Policy And Forecasting Using Hybrid Dsge Models With Financial Frictions And State Space Markov-Switching Tvp-Vars," Macroeconomic Dynamics, Cambridge University Press, vol. 19(7), pages 1565-1592, October.
    263. Rubaszek, Michal & Skrzypczynski, Pawel, 2008. "On the forecasting performance of a small-scale DSGE model," International Journal of Forecasting, Elsevier, vol. 24(3), pages 498-512.
    264. Bloznelis, Daumantas, 2017. "Hedging under square loss," MPRA Paper 83442, University Library of Munich, Germany.
    265. Viviana Fernandez, 2008. "Traditional versus novel forecasting techniques: how much do we gain?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(7), pages 637-648.
    266. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2012. "Common drifting volatility in large Bayesian VARs," Working Papers (Old Series) 1206, Federal Reserve Bank of Cleveland.
    267. Afees A. Salisu & Riza Demirer & Rangan Gupta, 2023. "Technological Shocks and Stock Market Volatility Over a Century: A GARCH-MIDAS Approach," Working Papers 202308, University of Pretoria, Department of Economics.
    268. António Rua & Miguel de Carvalho, 2014. "Real-time nowcasting the US output gap: Singular spectrum analysis at work," Working Papers w201416, Banco de Portugal, Economics and Research Department.
    269. Rangan Gupta & Christian Pierdzioch & Afees A. Salisu, 2020. "Oil-Price Uncertainty and the U.K. Unemployment Rate: A Forecasting Experiment with Random Forests Using 150 Years of Data," Working Papers 202095, University of Pretoria, Department of Economics.
    270. Siliverstovs, B. & van Dijk, D.J.C., 2003. "Forecasting industrial production with linear, nonlinear, and structural change models," Econometric Institute Research Papers EI 2003-16, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    271. Benner Joachim & Meier Carsten-Patrick, 2004. "Prognosegüte alternativer Früh Indikatoren für die Konjunktur in Deutschland / Forecasting Performance of Alternative Indicators for the German Economy," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 224(6), pages 639-652, December.
    272. Tiago E. Pratas & Filipe R. Ramos & Lihki Rubio, 2023. "Forecasting bitcoin volatility: exploring the potential of deep learning," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 13(2), pages 285-305, June.
    273. Mogliani, Matteo & Darné, Olivier & Pluyaud, Bertrand, 2017. "The new MIBA model: Real-time nowcasting of French GDP using the Banque de France's monthly business survey," Economic Modelling, Elsevier, vol. 64(C), pages 26-39.
    274. Nonejad, Nima, 2022. "Forecasting crude oil price volatility out-of-sample using news-based geopolitical risk index: What forms of nonlinearity help improve forecast accuracy the most?," Finance Research Letters, Elsevier, vol. 46(PA).
    275. Yaojie Zhang & Yudong Wang & Feng Ma & Yu Wei, 2022. "To jump or not to jump: momentum of jumps in crude oil price volatility prediction," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-31, December.
    276. Korobilis, Dimitris, 2017. "Quantile regression forecasts of inflation under model uncertainty," International Journal of Forecasting, Elsevier, vol. 33(1), pages 11-20.
    277. Chunming Yuan, 2008. "Forecasting Exchange Rates: The Multi-State Markov-Switching Model with Smoothing," UMBC Economics Department Working Papers 09-115, UMBC Department of Economics, revised 01 Nov 2009.
    278. Alberto Baffigi & Roberto Golinelli & Giuseppe Parigi, 2002. "Real-time GDP forecasting in the euro area," Temi di discussione (Economic working papers) 456, Bank of Italy, Economic Research and International Relations Area.
    279. Bryan Campbell & Steve Murphy, 2006. "The Recent Performance of the Canadian Forecasting Industry," Canadian Public Policy, University of Toronto Press, vol. 32(1), pages 23-40, March.
    280. Kilian, Lutz & Inoue, Atsushi, 2002. "In-Sample or Out-of-Sample Tests of Predictability: Which One Should We Use?," CEPR Discussion Papers 3671, C.E.P.R. Discussion Papers.
    281. Roque Montero & Javier García-Cicco, 2012. "Modelo y Pronóstico del Precio del Cobre: Un Enfoque de Cambio de Regímenes," Notas de Investigación Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 15(2), pages 099-116, August.
    282. Korobilis, Dimitris & Pettenuzzo, Davide, 2019. "Adaptive hierarchical priors for high-dimensional vector autoregressions," Journal of Econometrics, Elsevier, vol. 212(1), pages 241-271.
    283. Olivier BIAU & Angela D´ELIA, 2010. "A Non-Balanced Survey-Based Indicator to Track Industrial Production," EcoMod2010 259600028, EcoMod.
    284. Nicoletta Pashourtidou, 2022. "Survey-derived proxies for uncertainty: the case of Cyprus," Cyprus Economic Policy Review, University of Cyprus, Economics Research Centre, vol. 16(2), pages 27-56, December.
    285. Cappiello, Lorenzo & De Santis, Roberto A., 2005. "Explaining exchange rate dynamics: the uncovered equity return parity condition," Working Paper Series 529, European Central Bank.
    286. Mayr, Johannes, 2010. "Forecasting Macroeconomic Aggregates," Munich Dissertations in Economics 11140, University of Munich, Department of Economics.
    287. Rapach, David E. & Wohar, Mark E., 2006. "The out-of-sample forecasting performance of nonlinear models of real exchange rate behavior," International Journal of Forecasting, Elsevier, vol. 22(2), pages 341-361.
    288. Konstantinidi, Eirini & Skiadopoulos, George, 2011. "Are VIX futures prices predictable? An empirical investigation," International Journal of Forecasting, Elsevier, vol. 27(2), pages 543-560.
    289. Mingzhe Wei & Georgios Sermpinis & Charalampos Stasinakis, 2023. "Forecasting and trading Bitcoin with machine learning techniques and a hybrid volatility/sentiment leverage," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 852-871, July.
    290. Sandra Eickmeier & Wolfgang Lemke & Massimiliano Marcellino, 2015. "Classical time varying factor-augmented vector auto-regressive models—estimation, forecasting and structural analysis," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(3), pages 493-533, June.
    291. Christian Conrad, 2007. "Non-negativity Conditions for the Hyperbolic GARCH Model," KOF Working papers 07-162, KOF Swiss Economic Institute, ETH Zurich.
    292. Dimitrios P. Louzis, 2017. "Macroeconomic and credit forecasts during the Greek crisis using Bayesian VARs," Empirical Economics, Springer, vol. 53(2), pages 569-598, September.
    293. Hansson, Jesper & Jansson, Per & Lof, Marten, 2005. "Business survey data: Do they help in forecasting GDP growth?," International Journal of Forecasting, Elsevier, vol. 21(2), pages 377-389.
    294. Allayioti, Anastasia & Venditti, Fabrizio, 2024. "The role of comovement and time-varying dynamics in forecasting commodity prices," Working Paper Series 2901, European Central Bank.
    295. Brave, Scott A. & Butters, R. Andrew & Justiniano, Alejandro, 2019. "Forecasting economic activity with mixed frequency BVARs," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1692-1707.
    296. Halkos, George & Tzirivis, Apostolos, 2018. "Effective energy commodities’ risk management: Econometric modeling of price volatility," MPRA Paper 90781, University Library of Munich, Germany.
    297. Taylor, Mark & Clarida, Richard & Sarno, Lucio & Valente, Giorgio, 2002. "The Out-of-Sample Success of Term Structure Models as Exchange Rate Predictors: A Step Beyond," CEPR Discussion Papers 3281, C.E.P.R. Discussion Papers.
    298. Charalampos Stasinakis & Georgios Sermpinis & Konstantinos Theofilatos & Andreas Karathanasopoulos, 2016. "Forecasting US Unemployment with Radial Basis Neural Networks, Kalman Filters and Support Vector Regressions," Computational Economics, Springer;Society for Computational Economics, vol. 47(4), pages 569-587, April.
    299. Giacomini, Raffaella & White, Halbert, 2003. "Tests of Conditional Predictive Ability," University of California at San Diego, Economics Working Paper Series qt5jk0j5jh, Department of Economics, UC San Diego.
    300. Maximo Camacho, 2004. "Vector smooth transition regression models for US GDP and the composite index of leading indicators," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(3), pages 173-196.
    301. Marcelo Fernandes & Marcelo Cunha Medeiros & MArcelo Scharth, 2007. "Modeling and predicting the CBOE market volatility index," Textos para discussão 548, Department of Economics PUC-Rio (Brazil).
    302. Oscar Claveria, 2021. "On the Aggregation of Survey-Based Economic Uncertainty Indicators Between Different Agents and Across Variables," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(1), pages 1-26, April.
    303. Wenzel, Lars & Wolf, André, 2013. "Short-term forecasting with business surveys: Evidence for German IHK data at federal state level," HWWI Research Papers 140, Hamburg Institute of International Economics (HWWI).
    304. Todd E. Clark & Michael McCracken, 1999. "Tests of Equal Forecast Accuracy and Encompassing for Nested Models," Computing in Economics and Finance 1999 1241, Society for Computational Economics.
    305. McCracken, Michael W., 2004. "Parameter estimation and tests of equal forecast accuracy between non-nested models," International Journal of Forecasting, Elsevier, vol. 20(3), pages 503-514.
    306. Croushore, D., 2002. "Comments on 'The state of macroeconomic forecasting'," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 483-489, December.
    307. Tesi Aliaj & Milos Ciganovic & Massimiliano Tancioni, 2023. "Nowcasting inflation with Lasso‐regularized vector autoregressions and mixed frequency data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(3), pages 464-480, April.
    308. Manfredo, Mark R. & Sanders, Dwight R., 2004. "The Value of Public Price Forecasts: Additional Evidence in the Live Hog Market," Journal of Agribusiness, Agricultural Economics Association of Georgia, vol. 22(2), pages 1-13.
    309. Hwee Kwan Chow & Keen Meng Choy, 2009. "Analyzing and Forecasting Business Cycles in a Small Open Economy : A Dynamic Factor Model for Singapore," Macroeconomics Working Papers 22074, East Asian Bureau of Economic Research.
    310. Heinisch, Katja & Lindner, Axel, 2018. "For how long do IMF forecasts of world economic growth stay up-to-date?," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, issue Latest ar, pages 1-6.
    311. Matteo Mogliani, 2019. "Bayesian MIDAS penalized regressions: estimation, selection, and prediction," Working papers 713, Banque de France.
    312. Zhou, Huimin & Dang, Yaoguo & Yang, Yingjie & Wang, Junjie & Yang, Shaowen, 2023. "An optimized nonlinear time-varying grey Bernoulli model and its application in forecasting the stock and sales of electric vehicles," Energy, Elsevier, vol. 263(PC).
    313. Christian Glocker & Philipp Wegmueller, 2020. "Business cycle dating and forecasting with real-time Swiss GDP data," Empirical Economics, Springer, vol. 58(1), pages 73-105, January.
    314. Hector H. Sandoval & Anita N. Walsh, 2021. "The role of consumer confidence in forecasting consumption, evidence from Florida," Southern Economic Journal, John Wiley & Sons, vol. 88(2), pages 757-788, October.
    315. Dean Croushore & Simon van Norden, 2017. "Fiscal Surprises at the FOMC," CIRANO Working Papers 2017s-09, CIRANO.
    316. Conrad, Christian & Karanasos, Menelaos & Zeng, Ning, 2011. "Multivariate fractionally integrated APARCH modeling of stock market volatility: A multi-country study," Journal of Empirical Finance, Elsevier, vol. 18(1), pages 147-159, January.
    317. Juan D. Borrero & Jesus Mariscal, 2022. "Predicting Time SeriesUsing an Automatic New Algorithm of the Kalman Filter," Mathematics, MDPI, vol. 10(16), pages 1-13, August.
    318. Klaus Abberger, 2006. "Qualitative Business Surveys in Manufacturing and Industrial Production - What can be Learned from Industry Branch Results?," ifo Working Paper Series 31, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    319. Martin, Ian & Kremens, Lukas, 2017. "The Quanto Theory of Exchange Rates," CEPR Discussion Papers 11970, C.E.P.R. Discussion Papers.
    320. Reichenbacher, Michael & Schuster, Philipp, 2022. "Size-adapted bond liquidity measures and their asset pricing implications," Journal of Financial Economics, Elsevier, vol. 146(2), pages 425-443.
    321. Michael S. Smith & Shaun P. Vahey, 2016. "Asymmetric Forecast Densities for U.S. Macroeconomic Variables from a Gaussian Copula Model of Cross-Sectional and Serial Dependence," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(3), pages 416-434, July.
    322. Jakub Micha'nk'ow & {L}ukasz Kwiatkowski & Janusz Morajda, 2023. "Combining Deep Learning and GARCH Models for Financial Volatility and Risk Forecasting," Papers 2310.01063, arXiv.org.
    323. Afees A. Salisu & Christian Pierdzioch & Rangan Gupta & David Gabauer, 2021. "Forecasting Stock-Market Tail Risk and Connectedness in Advanced Economies Over a Century: The Role of Gold-to-Silver and Gold-to-Platinum Price Ratios," Working Papers 202161, University of Pretoria, Department of Economics.
    324. Daniel Aaronson & Scott A. Brave & Michael Fogarty & Ezra Karger & Spencer D. Krane, 2021. "Tracking U.S. Consumers in Real Time with a New Weekly Index of Retail Trade," Working Paper Series WP-2021-05, Federal Reserve Bank of Chicago, revised 18 Jun 2021.
    325. Imene Mootamri & Mohamed Boutahar & Anne Peguin-Feissolle, 2008. "A fractionally integrated exponential STAR model applied to the US real effective exchange rate," Post-Print halshs-00390134, HAL.
    326. Ferrara, L. & Marcellino, M. & Mogliani, M., 2012. "Macroeconomic forecasting during the Great Recession: The return of non-linearity?," Working papers 383, Banque de France.
    327. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    328. Eduardo Caro & Jesús Juan, 2020. "Short-Term Load Forecasting for Spanish Insular Electric Systems," Energies, MDPI, vol. 13(14), pages 1-26, July.
    329. Das, Sudeepa & Sahu, Tirath Prasad & Janghel, Rekh Ram, 2022. "Oil and gold price prediction using optimized fuzzy inference system based extreme learning machine," Resources Policy, Elsevier, vol. 79(C).
    330. Renee van Eyden & Goodness C. Aye & Rangan Gupta, 2012. "Predictive Ability of Competing Models for South Africa’s Fixed Business Non- Residential Investment Spending," Working Papers 201229, University of Pretoria, Department of Economics.
    331. Qin, Duo & Cagas, Marie Anne & Ducanes, Geoffrey & Magtibay-Ramos, Nedelyn & Quising, Pilipinas, 2008. "Automatic leading indicators versus macroeconometric structural models: A comparison of inflation and GDP growth forecasting," International Journal of Forecasting, Elsevier, vol. 24(3), pages 399-413.
    332. Michael K. Adjemian & Valentina G. Bruno & Michel A. Robe, 2020. "Incorporating Uncertainty into USDA Commodity Price Forecasts," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(2), pages 696-712, March.
    333. Boriss Siliverstovs & Konstantin A. Kholodilin, 2006. "On Selection of Components for a Diffusion Index Model: It's not the Size, It's How You Use It," Discussion Papers of DIW Berlin 598, DIW Berlin, German Institute for Economic Research.
    334. Trapletti, Adrian & Geyer, Alois & Leisch, Friedrich, 2002. "Forecasting Exchange Rates Using Cointegration Models and Inra-day Data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 21(3), pages 151-166, April.
    335. Guizzardi, Andrea & Stacchini, Annalisa, 2015. "Real-time forecasting regional tourism with business sentiment surveys," Tourism Management, Elsevier, vol. 47(C), pages 213-223.
    336. Christina Anderl & Guglielmo Maria Caporale, 2023. "Forecasting inflation with a zero lower bound or negative interest rates: Evidence from point and density forecasts," Manchester School, University of Manchester, vol. 91(3), pages 171-232, June.
    337. Dahmene, Meriam & Boughrara, Adel & Slim, Skander, 2021. "Nonlinearity in stock returns: Do risk aversion, investor sentiment and, monetary policy shocks matter?," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 676-699.
    338. Irac, D. & Sédillot, F., 2002. "Short-Run Assessment of French Economic Activity Using OPTIM," Working papers 88, Banque de France.
    339. Sanders, Dwight R. & Manfredo, Mark R. & Boris, Keith, 2008. "Accuracy and efficiency in the U.S. Department of Energy's short-term supply forecasts," Energy Economics, Elsevier, vol. 30(3), pages 1192-1207, May.
    340. Racine Ly & Fousseini Traore & Khadim Dia, 2021. "Forecasting Commodity Prices Using Long Short-Term Memory Neural Networks," Papers 2101.03087, arXiv.org, revised Jan 2021.
    341. Kilponen, Juha & Verona, Fabio, 2016. "Testing the Q theory of investment in the frequency domain," Bank of Finland Research Discussion Papers 32/2016, Bank of Finland.
    342. Artur Tarassow, 2017. "Forecasting growth of U.S. aggregate and household-sector M2 after 2000 using economic uncertainty measures," Macroeconomics and Finance Series 201702, University of Hamburg, Department of Socioeconomics.
    343. Marcel Scharth & Marcelo Cunha Medeiros, 2006. "Asymmetric effects and long memory in the volatility of Dow Jones stocks," Textos para discussão 532, Department of Economics PUC-Rio (Brazil).
    344. David I. Harvey & Stephen J. Leybourne & Emily J. Whitehouse, 2017. "Forecast evaluation tests and negative long-run variance estimates in small samples," Discussion Papers 17/03, University of Nottingham, Granger Centre for Time Series Econometrics.
    345. Sonja Tilly & Giacomo Livan, 2021. "Macroeconomic forecasting with statistically validated knowledge graphs," Papers 2104.10457, arXiv.org.
    346. Li, Tenghui & Liu, Xiaolei & Lin, Zi & Morrison, Rory, 2022. "Ensemble offshore Wind Turbine Power Curve modelling – An integration of Isolation Forest, fast Radial Basis Function Neural Network, and metaheuristic algorithm," Energy, Elsevier, vol. 239(PD).
    347. Ulrich Fritsche & Artur Tarassow, 2017. "Vergleichende Evaluation der Konjunkturprognosen des Instituts für Makroökonomie und Konjunkturforschung an der Hans-Böckler-Stiftung für den Zeitraum 2005-2014," IMK Studies 54-2017, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
    348. Post, Thierry & Karabatı, Selçuk & Arvanitis, Stelios, 2019. "Robust optimization of forecast combinations," International Journal of Forecasting, Elsevier, vol. 35(3), pages 910-926.
    349. Dean Croushore & Stephanie M. Wilshusen, 2020. "Forecasting Consumption Spending Using Credit Bureau Data," Working Papers 20-22, Federal Reserve Bank of Philadelphia.
    350. Knut Are Aastveit & Tørres G. Trovik, 2008. "Estimating the output gap in real time: A factor model approach," Working Paper 2008/23, Norges Bank.
    351. Jiadong Tong & Zijun Wang & Jian Yang, 2016. "Information Flow Between Forward and Spot Markets: Evidence From the Chinese Renminbi," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(7), pages 695-718, July.
    352. Carmine Pappalardo & Gianfranco Piras, 2004. "Vector-Autoregression Approach to Forecast Italian Imports," ISAE Working Papers 42, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
    353. Rangvid, Jesper, 2006. "Output and expected returns," Journal of Financial Economics, Elsevier, vol. 81(3), pages 595-624, September.
    354. Sarat Chandra Nayak & Bijan Bihari Misra, 2019. "A chemical-reaction-optimization-based neuro-fuzzy hybrid network for stock closing price prediction," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 5(1), pages 1-34, December.
    355. Roccazzella, Francesco & Gambetti, Paolo & Vrins, Frédéric, 2021. "Optimal and robust combination of forecasts via constrained optimization and shrinkage," LIDAM Reprints LFIN 2021014, Université catholique de Louvain, Louvain Finance (LFIN).
    356. Li, Xin & Ma, Jian & Wang, Shouyang & Zhang, Xun, 2015. "How does Google search affect trader positions and crude oil prices?," Economic Modelling, Elsevier, vol. 49(C), pages 162-171.
    357. Martin Baumgaertner & Jens Klose, 2018. "Forecasting Exchange Rates with Commodity Prices - A Global Country Analysis," MAGKS Papers on Economics 201812, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    358. Felix Haase & Matthias Neuenkirch, 2020. "Predictability of Bull and Bear Markets: A New Look at Forecasting Stock Market Regimes (and Returns) in the US," Research Papers in Economics 2020-01, University of Trier, Department of Economics.
    359. Berneburg, Marian, 2003. "Composite Leading Indicators der amerikanischen Wirtschaft - Prognosegüte des Conference Board und des OECD Ansatzes im Vergleich," IWH Discussion Papers 172/2003, Halle Institute for Economic Research (IWH).
    360. Gallo, Giampiero M. & Otranto, Edoardo, 2015. "Forecasting realized volatility with changing average levels," International Journal of Forecasting, Elsevier, vol. 31(3), pages 620-634.
    361. Tom Stark and Dean Croushore, 2001. "Forecasting with a Real-Time Data Set for Macroeconomists," Computing in Economics and Finance 2001 258, Society for Computational Economics.
    362. Bumho Son & Yunyoung Lee & Seongwan Park & Jaewook Lee, 2023. "Forecasting global stock market volatility: The impact of volatility spillover index in spatial‐temporal graph‐based model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1539-1559, November.
    363. Darné, O. & Brunhes-Lesage, V., 2007. "L’Indicateur Synthétique Mensuel d’Activité (ISMA) : une révision," Working papers 171, Banque de France.
    364. A. Girardi & R. Golinelli & C. Pappalardo, 2014. "The Role of Indicator Selection in Nowcasting Euro Area GDP in Pseudo Real Time," Working Papers wp919, Dipartimento Scienze Economiche, Universita' di Bologna.
    365. Oliver Hülsewig & Johannes Mayr & Timo Wollmershäuser, 2008. "Forecasting Euro Area Real GDP: Optimal Pooling of Information," CESifo Working Paper Series 2371, CESifo.
    366. Máximo Camacho & Gabriel Pérez-Quirós, 2005. "Jump-and-rest effect of U.S. business cycles," Working Papers 0507, Banco de España.
    367. Guglielmo Caporale & Luis Gil-Alana, 2016. "Persistence and cyclical dependence in the monthly euribor rate," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 40(1), pages 157-171, January.
    368. Camacho, Maximo, 2005. "Markov-switching stochastic trends and economic fluctuations," Journal of Economic Dynamics and Control, Elsevier, vol. 29(1-2), pages 135-158, January.
    369. Morales-Arias, Leonardo & Moura, Guilherme V., 2013. "Adaptive forecasting of exchange rates with panel data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 493-509.
    370. Haiyan Song & Egon Smeral & Gang Li & Jason L. Chen, 2008. "Tourism Forecasting: Accuracy of Alternative Econometric Models Revisited," WIFO Working Papers 326, WIFO.
    371. Giorgio Canarella & Luis A. Gil-Alana & Rangan Gupta & Stephen M. Miller, 2020. "Modeling US historical time-series prices and inflation using alternative long-memory approaches," Empirical Economics, Springer, vol. 58(4), pages 1491-1511, April.
    372. Chalmovianský, Jakub & Porqueddu, Mario & Sokol, Andrej, 2020. "Weigh(t)ing the basket: aggregate and component-based inflation forecasts for the euro area," Working Paper Series 2501, European Central Bank.
    373. Philipp Wegmüller & Christian Glocker, 2023. "US weekly economic index: Replication and extension," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(6), pages 977-985, September.
    374. Robert Lehmann & Magnus Reif, 2021. "Predicting the German Economy: Headline Survey Indices Under Test," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(2), pages 215-232, November.
    375. Javier Pórtoles & Camino González & Javier M. Moguerza, 2018. "Electricity Price Forecasting with Dynamic Trees: A Benchmark Against the Random Forest Approach," Energies, MDPI, vol. 11(6), pages 1-21, June.
    376. David Harvey & Paul Newbold, 2000. "Tests for multiple forecast encompassing," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 471-482.
    377. Ahmed, Ali & Granberg, Mark & Troster, Victor & Uddin, Gazi Salah, 2020. "Asymmetric Dynamics between Uncertainty and Unemployment Flows in the United States," LiU Working Papers in Economics 7, Linköping University, Division of Economics, Department of Management and Engineering.
    378. Fernandez, Viviana, 2007. "Wavelet- and SVM-based forecasts: An analysis of the U.S. metal and materials manufacturing industry," Resources Policy, Elsevier, vol. 32(1-2), pages 80-89.
    379. Federico D'Amario & Milos Ciganovic, 2022. "Forecasting Cryptocurrencies Log-Returns: a LASSO-VAR and Sentiment Approach," Papers 2210.00883, arXiv.org.
    380. Gamber, Edward N. & Smith, Julie K. & McNamara, Dylan C., 2014. "Where is the Fed in the distribution of forecasters?," Journal of Policy Modeling, Elsevier, vol. 36(2), pages 296-312.
    381. Rodríguez-Vargas, Adolfo, 2020. "Forecasting Costa Rican inflation with machine learning methods," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 1(1).
    382. Morales-Arias, Leonardo & Moura, Guilherme V., 2010. "A conditionally heteroskedastic global inflation model," Kiel Working Papers 1666, Kiel Institute for the World Economy (IfW Kiel).
    383. da Veiga, Bernardo & Chan, Felix & McAleer, Michael, 2008. "Evaluating the impact of market reforms on Value-at-Risk forecasts of Chinese A and B shares," Pacific-Basin Finance Journal, Elsevier, vol. 16(4), pages 453-475, September.
    384. Branimir Jovanovic & Magdalena Petrovska, 2010. "Forecasting Macedonian GDP: Evaluation of different models for short-term forecasting," Working Papers 2010-02, National Bank of the Republic of North Macedonia, revised Aug 2010.
    385. Ali Dib & Mohamed Gammoudi & Kevin Moran, 2006. "Forecasting Canadian Time Series With the New-Keynesian Model," Working Papers Central Bank of Chile 382, Central Bank of Chile.
    386. Kjetil Martinsen & Francesco Ravazzolo & Fredrik Wulfsberg, 2011. "Forecasting macroeconomic variables using disaggregate survey data," Working Paper 2011/04, Norges Bank.
    387. Javier J. Pérez, 2005. "Early-warning tools to forecast General Government deficit in the euro area: the role of intra-annual fiscal Indicators," Economic Working Papers at Centro de Estudios Andaluces E2005/14, Centro de Estudios Andaluces.
    388. Edward N. Gamber (CBO), 2017. "Did Treasury Debt Markets Anticipate the Persistent Decline in Long-Term Interest Rates?: Working Paper 2017-07," Working Papers 53153, Congressional Budget Office.
    389. Guy Chapda Nana & Bruno Larue, 2014. "Imposing curvature conditions on flexible functional forms for GNP functions," Empirical Economics, Springer, vol. 47(4), pages 1411-1440, December.
    390. Stankevich, Ivan, 2023. "Application of Markov-Switching MIDAS models to nowcasting of GDP and its components," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 70, pages 122-143.
    391. Anindya Banerjee & Bill Russell, 2006. "A markup model for forecasting inflation for the euro area," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(7), pages 495-511.
    392. Becker, Ralf & Clements, Adam E. & White, Scott I., 2007. "Does implied volatility provide any information beyond that captured in model-based volatility forecasts?," Journal of Banking & Finance, Elsevier, vol. 31(8), pages 2535-2549, August.
    393. Kitlinski, Tobias & Schmidt, Torsten, 2011. "The Forecasting Performance of an Estimated Medium Run Model," Ruhr Economic Papers 301, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    394. Wilms, Ines & Rombouts, Jeroen & Croux, Christophe, 2021. "Multivariate volatility forecasts for stock market indices," International Journal of Forecasting, Elsevier, vol. 37(2), pages 484-499.
    395. Christophe Boucher & Bertrand Maillet, 2012. "Prévoir sans persistance," Documents de travail du Centre d'Economie de la Sorbonne 12001, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    396. Paul Corrigan & Hélène Desgagnés & José Dorich & Vadym Lepetyuk & Wataru Miyamoto & Yang Zhang, 2021. "ToTEM III: The Bank of Canada’s Main DSGE Model for Projection and Policy Analysis," Technical Reports 119, Bank of Canada.
    397. Martin Nordström, 2020. "A forecast evaluation of the Riksbank's policy‐rate projections," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 49(3), September.
    398. Xu Xiaojie, 2018. "Using Local Information to Improve Short-Run Corn Price Forecasts," Journal of Agricultural & Food Industrial Organization, De Gruyter, vol. 16(1), pages 1-15, January.
    399. Fabian Krüger & Todd E. Clark & Francesco Ravazzolo, 2017. "Using Entropic Tilting to Combine BVAR Forecasts With External Nowcasts," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(3), pages 470-485, July.
    400. Glocker, Christian & Kaniovski, Serguei, 2020. "Structural modeling and forecasting using a cluster of dynamic factor models," MPRA Paper 101874, University Library of Munich, Germany.
    401. C.J.M. Kool & D.L. Thornton, 2012. "How Effective Is Central Bank Forward Guidance?," Working Papers 12-05, Utrecht School of Economics.
    402. Robledo, Carlos W. & Zapata, Hector O. & McCracken, Michael, 2001. "New Mse Tests For Evaluating Forecasting Performance: Empirics And Bootstrap," 2001 Annual meeting, August 5-8, Chicago, IL 20686, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    403. Tierney, Heather L.R., 2013. "Forecasting and Tracking Real-Time Data Revisions in Inflation Persistence," MPRA Paper 53374, University Library of Munich, Germany, revised Nov 2013.
    404. Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2018. "Forecasting (Good and Bad) Realized Exchange-Rate Volatility: Is there a Role for Realized Skewness and Kurtosis?," Working Papers 201879, University of Pretoria, Department of Economics.
    405. Salisu, Afees A. & Gupta, Rangan & Pierdzioch, Christian, 2022. "Predictability of tail risks of Canada and the U.S. Over a Century: The role of spillovers and oil tail Risks☆," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    406. Domenico Di Gangi & Giacomo Bormetti & Fabrizio Lillo, 2022. "Score Driven Generalized Fitness Model for Sparse and Weighted Temporal Networks," Papers 2202.09854, arXiv.org, revised Mar 2022.
    407. Ebru Caglayan Akay & Sinem Guler Kangalli Uyar, 2016. "Determining the Functional Form of Relationships between Oil Prices and Macroeconomic Variables: The Case of Mexico, Indonesia, South Korea, Turkey Countries," International Journal of Economics and Financial Issues, Econjournals, vol. 6(3), pages 880-891.
    408. van Dijk, D.J.C. & Franses, Ph.H.B.F., 2003. "Selecting a Nonlinear Time Series Model using Weighted Tests of Equal Forecast Accuracy," Econometric Institute Research Papers EI 2003-10, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    409. Claudio Detotto & Edoardo Otranto, 2010. "Does Crime Affect Economic Growth?," Post-Print hal-01972848, HAL.
    410. Cătălin Stărică & Clive Granger, 2005. "Nonstationarities in Stock Returns," The Review of Economics and Statistics, MIT Press, vol. 87(3), pages 503-522, August.
    411. Gkillas, Konstantinos & Gupta, Rangan & Pierdzioch, Christian, 2020. "Forecasting realized gold volatility: Is there a role of geopolitical risks?," Finance Research Letters, Elsevier, vol. 35(C).
    412. Arnaud Mehl, 2009. "The Yield Curve as a Predictor and Emerging Economies," Open Economies Review, Springer, vol. 20(5), pages 683-716, November.
    413. Hartmann, Matthias & Herwartz, Helmut & Ulm, Maren, 2017. "A comparative assessment of alternative ex ante measures of inflation uncertainty," International Journal of Forecasting, Elsevier, vol. 33(1), pages 76-89.
    414. Daniel Grenouilleau, 2006. "The Stacked Leading Indicators Dynamic Factor Model: A Sensitivity Analysis of Forecast Accuracy using Bootstrapping," European Economy - Economic Papers 2008 - 2015 249, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    415. Konstantin A. Kholodilin & Boriss Siliverstovs & Stefan Kooths, 2007. "A Dynamic Panel Data Approach to the Forecasting of the GDP of German Länder," Discussion Papers of DIW Berlin 664, DIW Berlin, German Institute for Economic Research.
    416. Hossein Hassani & Abdol S. Soofi & Anatoly Zhigljavsky, 2013. "Predicting inflation dynamics with singular spectrum analysis," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 176(3), pages 743-760, June.
    417. Ankargren Sebastian & Unosson Måns & Yang Yukai, 2020. "A Flexible Mixed-Frequency Vector Autoregression with a Steady-State Prior," Journal of Time Series Econometrics, De Gruyter, vol. 12(2), pages 1-41, July.
    418. Salisu, Afees A. & Olaniran, Abeeb & Tchankam, Jean Paul, 2022. "Oil tail risk and the tail risk of the US Dollar exchange rates," Energy Economics, Elsevier, vol. 109(C).
    419. Aubry, Mathilde & Renou-Maissant, Patricia, 2014. "Semiconductor industry cycles: Explanatory factors and forecasting," Economic Modelling, Elsevier, vol. 39(C), pages 221-231.
    420. Massimo Guidolin & Daniel L. Thornton, 2010. "Predictions of short-term rates and the expectations hypothesis," Working Papers 2010-013, Federal Reserve Bank of St. Louis.
    421. Zidong An & João Tovar Jalles, 2020. "On the Performance of US Fiscal Forecasts: Government vs. Private Information," Working Papers REM 2020/0130, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    422. Grimme, Christian & Lehmann, Robert & Noeller, Marvin, 2021. "Forecasting imports with information from abroad," Economic Modelling, Elsevier, vol. 98(C), pages 109-117.
    423. Hossein Hassani & Emmanuel Sirimal Silva, 2015. "A Kolmogorov-Smirnov Based Test for Comparing the Predictive Accuracy of Two Sets of Forecasts," Econometrics, MDPI, vol. 3(3), pages 1-20, August.
    424. Mohammadi, M. & Rezakhah, S. & Modarresi, N., 2020. "Semi-Lévy driven continuous-time GARCH process," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 557(C).
    425. Clementrs, Michael P. & Smith, Jeremy, 1997. "A Monte Carlo study of the forecasting performance of empirical SETAR models," Economic Research Papers 268734, University of Warwick - Department of Economics.
    426. Bahar Şen Doğan & Murat Midiliç, 2019. "Forecasting Turkish real GDP growth in a data-rich environment," Empirical Economics, Springer, vol. 56(1), pages 367-395, January.
    427. Carriero, Andrea & Mumtaz, Haroon & Theophilopoulou, Angeliki, 2015. "Macroeconomic information, structural change, and the prediction of fiscal aggregates," International Journal of Forecasting, Elsevier, vol. 31(2), pages 325-348.
    428. Czudaj, Robert L., 2022. "Heterogeneity of beliefs and information rigidity in the crude oil market: Evidence from survey data," European Economic Review, Elsevier, vol. 143(C).
    429. Eduard Baitinger, 2021. "Forecasting asset returns with network‐based metrics: A statistical and economic analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(7), pages 1342-1375, November.
    430. Zongwu Cai & Jiazi Chen & Linlin Niu, 2021. "A Semiparametric Model for Bond Pricing with Life Cycle Fundamental," Working Papers 2021-01-06, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    431. Christiana Anaxagorou & Nicoletta Pashourtidou, 2022. "Forecasting economic activity using preselected predictors: the case of Cyprus," Cyprus Economic Policy Review, University of Cyprus, Economics Research Centre, vol. 16(1), pages 11-36, June.
    432. Kichian, Maral & Rumler, Fabio, 2014. "Forecasting Canadian inflation: A semi-structural NKPC approach," Economic Modelling, Elsevier, vol. 43(C), pages 183-191.
    433. Götz, T.B. & Hecq, A.W. & Urbain, J.R.Y.J., 2014. "Combining distributions of real-time forecasts: An application to U.S. growth," Research Memorandum 027, Maastricht University, Graduate School of Business and Economics (GSBE).
    434. Zied Ftiti & Fredj Jawadi, 2019. "Forecasting Inflation Uncertainty in the United States and Euro Area," Computational Economics, Springer;Society for Computational Economics, vol. 54(1), pages 455-476, June.
    435. Rangan Gupta & Yuvana Jaichand & Christian Pierdzioch & Reneé van Eyden, 2023. "Realized Stock-Market Volatility of the United States and the Presidential Approval Rating," Mathematics, MDPI, vol. 11(13), pages 1-27, July.
    436. Rui Liu, 2019. "Forecasting Bond Risk Premia with Unspanned Macroeconomic Information," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 9(01), pages 1-62, March.
    437. Aslanidis, Nektarios & Cipollini, Andrea, 2010. "Leading indicator properties of US high-yield credit spreads," Journal of Macroeconomics, Elsevier, vol. 32(1), pages 145-156, March.
    438. Yongchen Zhao, 2015. "Robustness of Forecast Combination in Unstable Environment: A Monte Carlo Study of Advanced Algorithms," Working Papers 2015-04, Towson University, Department of Economics, revised Mar 2020.
    439. Marie Bessec & Julien Fouquau & Sophie Méritet, 2014. "Forecasting electricity spot prices using time-series models with a double temporal segmentation," Post-Print hal-01502835, HAL.
    440. Christian Gourieroux & Wei Liu, 2009. "Control and Out‐of‐Sample Validation of Dependent Risks," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 76(3), pages 683-707, September.
    441. Zhang, Kefei & Cao, Hua & Thé, Jesse & Yu, Hesheng, 2022. "A hybrid model for multi-step coal price forecasting using decomposition technique and deep learning algorithms," Applied Energy, Elsevier, vol. 306(PA).
    442. Cobb, Marcus P A, 2018. "Improving Underlying Scenarios for Aggregate Forecasts: A Multi-level Combination Approach," MPRA Paper 88593, University Library of Munich, Germany.
    443. Moser, Gabriel & Rumler, Fabio & Scharler, Johann, 2007. "Forecasting Austrian inflation," Economic Modelling, Elsevier, vol. 24(3), pages 470-480, May.
    444. Bernardini, Emmanuela & Cubadda, Gianluca, 2015. "Macroeconomic forecasting and structural analysis through regularized reduced-rank regression," International Journal of Forecasting, Elsevier, vol. 31(3), pages 682-691.
    445. Vijverberg, Chu-Ping C., 2009. "A time deformation model and its time-varying autocorrelation: An application to US unemployment data," International Journal of Forecasting, Elsevier, vol. 25(1), pages 128-145.
    446. Roberto S. Mariano & Suleyman Ozmucur, 2021. "Predictive Performance of Mixed-Frequency Nowcasting and Forecasting Models (with Application to Philippine Inflation and GDP Growth)," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 383-400, December.
    447. William D. Larson & Tara M. Sinclair, 2020. "Nowcasting unemployment insurance claims in the time of COVID-19," CAMA Working Papers 2020-63, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    448. Lindner, Axel & Heinisch, Katja, 2019. "Economic Sentiment in Europe: Disentangling Private Information from Public Knowledge," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203501, Verein für Socialpolitik / German Economic Association.
    449. Bhatia, Kushagra & Mittal, Rajat & Varanasi, Jyothi & Tripathi, M.M., 2021. "An ensemble approach for electricity price forecasting in markets with renewable energy resources," Utilities Policy, Elsevier, vol. 70(C).
    450. Mayer, Walter J. & Madden, Gary & Dang, Xin, 2014. "Can measures of broadband infrastructure improve predictions of economic growth?," 20th ITS Biennial Conference, Rio de Janeiro 2014: The Net and the Internet - Emerging Markets and Policies 106875, International Telecommunications Society (ITS).
    451. Colino, Evelyn V. & Irwin, Scott H. & Garcia, Philip & Etienne, Xiaoli, 2012. "Composite and Outlook Forecast Accuracy," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 37(2), pages 1-19, August.
    452. Hassani, Hossein & Silva, Emmanuel Sirimal & Antonakakis, Nikolaos & Filis, George & Gupta, Rangan, 2017. "Forecasting accuracy evaluation of tourist arrivals," Annals of Tourism Research, Elsevier, vol. 63(C), pages 112-127.
    453. Gunter, Ulrich & Zekan, Bozana, 2021. "Forecasting air passenger numbers with a GVAR model," Annals of Tourism Research, Elsevier, vol. 89(C).
    454. Ekaterina Abramova & Derek Bunn, 2020. "Forecasting the Intra-Day Spread Densities of Electricity Prices," Energies, MDPI, vol. 13(3), pages 1-31, February.
    455. Naraidoo, Ruthira & Paya, Ivan, 2012. "Forecasting monetary policy rules in South Africa," International Journal of Forecasting, Elsevier, vol. 28(2), pages 446-455.
    456. Yan-Leung Cheung & Yin-Wong Cheung & Alan T. K. Wan, 2009. "A High-Low Model of Daily Stock Price Ranges," Working Papers 032009, Hong Kong Institute for Monetary Research.
    457. Michiel D. de Pooter & Francesco Ravazzolo & Dick van Dijk, 2007. "Predicting the Term Structure of Interest Rates: Incorporating Parameter Uncertainty, Model Uncertainty and Macroeconomic Information," Tinbergen Institute Discussion Papers 07-028/4, Tinbergen Institute.
    458. Jonathan Berrisch & Florian Ziel, 2023. "Multivariate Probabilistic CRPS Learning with an Application to Day-Ahead Electricity Prices," Papers 2303.10019, arXiv.org, revised Feb 2024.
    459. Nuray Tosunoğlu & Hilal Abacı & Gizem Ateş & Neslihan Saygılı Akkaya, 2023. "Artificial neural network analysis of the day of the week anomaly in cryptocurrencies," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-24, December.
    460. N. Alemohammad & S. Rezakhah & S. H. Alizadeh, 2020. "Markov switching asymmetric GARCH model: stability and forecasting," Statistical Papers, Springer, vol. 61(3), pages 1309-1333, June.
    461. Lelo de Larrea Alejandra, 2020. "Forecast Comparison of the Term Structure of Interest Rates of Mexico for Different Specifications of the Affine Model," Working Papers 2020-01, Banco de México.
    462. Marie-Hélène Gagnon & Gabriel Power & Dominique Toupin, 2018. "Forecasting International Index Returns using Option-implied Variables," Cahiers de recherche 1807, Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques.
    463. Adrian Marek Burda & Blazej Mazur & Mateusz Pawel Pipien, 2017. "Forecasting EUR/PLN Exchange Rate: the Role of Purchasing Power Parity Hypothesis in ESTVEC Models," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 17, pages 97-114.
    464. Mr. Willy A Hoffmaister & Mr. Jens R Clausen, 2010. "Cyclical Behavior of Inventories and Growth Projections Recent Evidence From Europe and the United States," IMF Working Papers 2010/212, International Monetary Fund.
    465. Olivier Darne, 2008. "Using business survey in industrial and services sector to nowcast GDP growth:The French case," Economics Bulletin, AccessEcon, vol. 3(32), pages 1-8.
    466. Pesaran, M.H. & Assenmacher-Wesche, K., 2007. "Assessing forecast uncertainties in a VECX* model for Switzerland: an exercise in forecast combination across models and observation windows," Cambridge Working Papers in Economics 0746, Faculty of Economics, University of Cambridge.
    467. Harvey, David I. & Newbold, Paul, 2003. "The non-normality of some macroeconomic forecast errors," International Journal of Forecasting, Elsevier, vol. 19(4), pages 635-653.
    468. Claudiu Tiberiu Albulescu & Dominique Pépin, 2018. "Monetary Integration, Money-Demand Stability, and the Role of Monetary Overhang in Forecasting Inflation in CEE Countries," Post-Print hal-01720319, HAL.
    469. Foroni, Claudia & Marcellino, Massimiliano, 2014. "A comparison of mixed frequency approaches for nowcasting Euro area macroeconomic aggregates," International Journal of Forecasting, Elsevier, vol. 30(3), pages 554-568.
    470. Veress, Aron & Kaiser, Lars, 2017. "Forecasting quality of professionals: Does affiliation matter?," The Quarterly Review of Economics and Finance, Elsevier, vol. 66(C), pages 159-168.
    471. Barakchian , Seyed Mahdi & Bayat , Saeed & Karami , Hooman, 2013. "Common Factors of CPI Sub-aggregates and Forecast of Inflation," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 8(4), pages 1-17, October.
    472. Nippala, Veera & Sinivuori, Taina, 2023. "Forecasting private investment in Finland using Q-theory and frequency decomposition," BoF Economics Review 3/2023, Bank of Finland.
    473. Johanna Posch & Fabio Rumler, 2015. "Semi‐Structural Forecasting of UK Inflation Based on the Hybrid New Keynesian Phillips Curve," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(2), pages 145-162, March.
    474. Camila Figueroa S. & Michael Pedersen, 2019. "A system for forecasting Chilean cash demand – the role of forecast combinations," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 22(2), pages 040-068, August.
    475. Rothman, P. & van Dijk, D.J.C. & Franses, Ph.H.B.F., 1999. "A multivariate STAR analysis of the relationship between money and output," Econometric Institute Research Papers EI 9945-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    476. M. Mogliani & T. Ferrière, 2016. "Rationality of announcements, business cycle asymmetry, and predictability of revisions. The case of French GDP," Working papers 600, Banque de France.
    477. Hamid Baghestani & Barry Poulson, 2012. "Federal Reserve forecasts of nonfarm payroll employment across different political regimes," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 39(3), pages 280-289, July.
    478. Marie Diron, 2008. "Short-term forecasts of euro area real GDP growth: an assessment of real-time performance based on vintage data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(5), pages 371-390.
    479. Nikita Medvedev & Zhiguang Wang, 2022. "Multistep forecast of the implied volatility surface using deep learning," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(4), pages 645-667, April.
    480. Jun Lu & Shao Yi, 2022. "Reducing overestimating and underestimating volatility via the augmented blending-ARCH model," Papers 2203.12456, arXiv.org.
    481. Garciga, Christian & Knotek II, Edward S., 2019. "Forecasting GDP growth with NIPA aggregates: In search of core GDP," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1814-1828.
    482. Siroos Khademalomoom & Paresh Kumar Narayan & Susan Sunila Sharma, 2019. "Higher Moments and Exchange Rate Behavior," The Financial Review, Eastern Finance Association, vol. 54(1), pages 201-229, February.
    483. Takami, Marcelo Yoshio & Tabak, Benjamin Miranda, 2008. "Interest rate option pricing and volatility forecasting: An application to Brazil," Chaos, Solitons & Fractals, Elsevier, vol. 38(3), pages 755-763.
    484. Camila Figueroa S. & Michael Pedersen, 2019. "Extracting information on economic activity from business and consumer surveys in an emerging economy (Chile)," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 22(3), pages 098-131, December.
    485. Marcelo Sánchez, 2011. "Oil shocks and endogenous markups: results from an estimated euro area DSGE model," International Economics and Economic Policy, Springer, vol. 8(3), pages 247-273, September.
    486. Jimmy Ran & Jan P. Voon & Guangzhong Li, 2010. "How Do Oil Price Shocks Affect A Small Non‐Oil Producing Economy? Evidence From Hong Kong," Pacific Economic Review, Wiley Blackwell, vol. 15(2), pages 263-280, May.
    487. Guglielmo Maria Caporale & Luis A. Gil-Alana, 2007. "Long Run and Cyclical Dynamics in the US Stock Market," CESifo Working Paper Series 2046, CESifo.
    488. Christopher G. Gibbs & Andrey L. Vasnev, 2017. "Conditionally Optimal Weights and Forward-Looking Approaches to Combining Forecasts," Discussion Papers 2017-10, School of Economics, The University of New South Wales.
    489. Jean-Philippe Cayen & Simon van Norden, 2002. "La fiabilité des estimations de l'écart de production au Canada," Staff Working Papers 02-10, Bank of Canada.
    490. Chen, Haiqiang & Chong, Terence Tai Leung & She, Yingni, 2013. "A Principal Component Approach to Measuring Investor Sentiment in China," MPRA Paper 54150, University Library of Munich, Germany.
    491. Khoshrou, Abdolrahman & Pauwels, Eric J., 2019. "Short-term scenario-based probabilistic load forecasting: A data-driven approach," Applied Energy, Elsevier, vol. 238(C), pages 1258-1268.
    492. Brooks, Chris & Burke, Simon P. & Stanescu, Silvia, 2016. "Finite sample weighting of recursive forecast errors," International Journal of Forecasting, Elsevier, vol. 32(2), pages 458-474.
    493. Perry Sadorsky & Michael D. McKenzie, 2008. "Power transformation models and volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(7), pages 587-606.
    494. Chow, Hwee Kwan & Choy, Keen Meng, 2006. "Forecasting the global electronics cycle with leading indicators: A Bayesian VAR approach," International Journal of Forecasting, Elsevier, vol. 22(2), pages 301-315.
    495. Laura Coroneo & Fabrizio Iacone, 2020. "Comparing predictive accuracy in small samples using fixed‐smoothing asymptotics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(4), pages 391-409, June.
    496. Håvard Hungnes, 2020. "Equal predictability test for multi-step-ahead system forecasts invariant to linear transformations," Discussion Papers 931, Statistics Norway, Research Department.
    497. Milas, Costas & Naraidoo, Ruthira, 2012. "Financial conditions and nonlinearities in the European Central Bank (ECB) reaction function: In-sample and out-of-sample assessment," Computational Statistics & Data Analysis, Elsevier, vol. 56(1), pages 173-189, January.
    498. Luis Eduardo Arango & Luz Adriana Flórez, 2004. "Expectativas De Actividad Económica En Colombia Y Estructura A Plazo: Un Poco Más De Evidencia," Revista ESPE - Ensayos Sobre Política Económica, Banco de la República, vol. 22(47), pages 126-160, December.
    499. Mikhail Gareev, 2020. "Use of Machine Learning Methods to Forecast Investment in Russia," Russian Journal of Money and Finance, Bank of Russia, vol. 79(1), pages 35-56, March.
    500. Ling Tang & Chengyuan Zhang & Tingfei Li & Ling Li, 2021. "A novel BEMD-based method for forecasting tourist volume with search engine data," Tourism Economics, , vol. 27(5), pages 1015-1038, August.
    501. Fabian Hollstein & Marcel Prokopczuk & Chardin Wese Simen, 2020. "The Conditional Capital Asset Pricing Model Revisited: Evidence from High-Frequency Betas," Management Science, INFORMS, vol. 66(6), pages 2474-2494, June.
    502. Perez, Javier J., 2007. "Leading indicators for euro area government deficits," International Journal of Forecasting, Elsevier, vol. 23(2), pages 259-275.
    503. Kajal Lahiri & George Monokroussos & Yongchen Zhao, 2016. "Forecasting Consumption: the Role of Consumer Confidence in Real Time with many Predictors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1254-1275, November.
    504. Branimir, Jovanovic & Magdalena, Petrovska, 2010. "Forecasting Macedonian GDP: Evaluation of different models for short-term forecasting," MPRA Paper 43162, University Library of Munich, Germany.
    505. Ildeberta Abreu, 2011. "International organisations’ vs. private analysts’ forecasts: an evaluation," Working Papers w201120, Banco de Portugal, Economics and Research Department.
    506. Herrera, Gabriel Paes & Constantino, Michel & Tabak, Benjamin Miranda & Pistori, Hemerson & Su, Jen-Je & Naranpanawa, Athula, 2019. "Long-term forecast of energy commodities price using machine learning," Energy, Elsevier, vol. 179(C), pages 214-221.
    507. Joan Paredes & Javier J. Pérez & Gabriel Perez Quiros, 2023. "Fiscal targets. A guide to forecasters?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 472-492, June.
    508. Christophe Boucher & Bertrand Maillet, 2011. "Detrending Persistent Predictors," Post-Print halshs-00587775, HAL.
    509. Sucarrat, Genaro, 2009. "Forecast Evaluation of Explanatory Models of Financial Variability," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 3, pages 1-33.
    510. Warne, Anders, 2023. "DSGE model forecasting: rational expectations vs. adaptive learning," Working Paper Series 2768, European Central Bank.
    511. Schinke-Nendza, A. & von Loeper, F. & Osinski, P. & Schaumann, P. & Schmidt, V. & Weber, C., 2021. "Probabilistic forecasting of photovoltaic power supply — A hybrid approach using D-vine copulas to model spatial dependencies," Applied Energy, Elsevier, vol. 304(C).
    512. Saranya, K. & Prasanna, P. Krishna, 2018. "Estimating stochastic volatility with jumps and asymmetry in Asian markets," Finance Research Letters, Elsevier, vol. 25(C), pages 145-153.
    513. Herman Stekler & Yongchen Zhao, 2016. "Predicting U.S. Business Cycle Turning Points Using Real-Time Diffusion Indexes Based on a Large Data Set," Working Papers 2016-15, Towson University, Department of Economics, revised Sep 2016.
    514. Mark R. Manfredo & Dwight R. Sanders, 2004. "The forecasting performance of implied volatility from live cattle options contracts: Implications for agribusiness risk management," Agribusiness, John Wiley & Sons, Ltd., vol. 20(2), pages 217-230.
    515. Cao, Liangyue & Soofi, Abdol S., 1999. "Nonlinear deterministic forecasting of daily dollar exchange rates," International Journal of Forecasting, Elsevier, vol. 15(4), pages 421-430, October.
    516. Douglas G. Santos & Flavio A. Ziegelmann, 2014. "Volatility Forecasting via MIDAS, HAR and their Combination: An Empirical Comparative Study for IBOVESPA," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(4), pages 284-299, July.
    517. Steffen Henzel, 2008. "Learning Trend Inflation – Can Signal Extraction Explain Survey Forecasts?," ifo Working Paper Series 55, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    518. Zhou, Feite & Huang, Zhehao & Zhang, Changhong, 2022. "Carbon price forecasting based on CEEMDAN and LSTM," Applied Energy, Elsevier, vol. 311(C).
    519. Daniel Buncic, 2008. "A Note on Long Horizon Forecasts of Nonlinear Models of Real Exchange Rates: Comments on Rapach and Wohar (2006)," Discussion Papers 2008-02, School of Economics, The University of New South Wales.
    520. Edward N. Gamber & Julie K. Smith, 2007. "Are the Fed’s Inflation Forecasts Still Superior to the Private Sector’s?," Working Papers 2007-002, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting, revised Jul 2008.
    521. Medel, Carlos A., 2015. "A Critical Review of Posch, J. and F. Rumler (2015), 'Semi-Structural Forecasting of UK Inflation Based on the Hybrid New Keynesian Phillips Curve,' Journal of Forecasting 34(2): 145-62," MPRA Paper 65665, University Library of Munich, Germany.
    522. Peter Carr & Liuren Wu, 2023. "Decomposing Long Bond Returns: A Decentralized Theory," Review of Finance, European Finance Association, vol. 27(3), pages 997-1026.
    523. Riccardo Corradini, 2019. "A Set of State–Space Models at a High Disaggregation Level to Forecast Italian Industrial Production," J, MDPI, vol. 2(4), pages 1-53, November.
    524. Krzysztof Drachal, 2022. "Forecasting the Crude Oil Spot Price with Bayesian Symbolic Regression," Energies, MDPI, vol. 16(1), pages 1-29, December.
    525. Yelland, Phillip M., 2010. "Bayesian forecasting of parts demand," International Journal of Forecasting, Elsevier, vol. 26(2), pages 374-396, April.
    526. Truong Ngoc Cuong & Sam-Sang You & Le Ngoc Bao Long & Hwan-Seong Kim, 2022. "Seaport Resilience Analysis and Throughput Forecast Using a Deep Learning Approach: A Case Study of Busan Port," Sustainability, MDPI, vol. 14(21), pages 1-25, October.
    527. Barış Soybilgen & M. Ege Yazgan & Hüseyin Kaya, 2023. "Nowcasting Turkish Food Inflation Using Daily Online Prices," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 19(2), pages 171-190, September.
    528. Ilias Lekkos & Costas Milas & Theodore Panagiotidis, 2005. "On the predictability of common risk factors in the US and UK interest rate swap markets: Evidence from non-linear and linear models," Discussion Paper Series 2005_9, Department of Economics, Loughborough University, revised Sep 2005.
    529. Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna & Mark E. Wohar, 2021. "Uncertainty and Predictability of Real Housing Returns in the United Kingdom: A Regional Analysis," Working Papers 202102, University of Pretoria, Department of Economics.
    530. Tseng, Tseng-Chan & Lee, Chien-Chiang & Chen, Mei-Ping, 2015. "Volatility forecast of country ETF: The sequential information arrival hypothesis," Economic Modelling, Elsevier, vol. 47(C), pages 228-234.
    531. Daniel Grenouilleau, 2004. "A sorted leading indicators dynamic (SLID) factor model for short-run euro-area GDP forecasting," European Economy - Economic Papers 2008 - 2015 219, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    532. Avino, Davide & Nneji, Ogonna, 2014. "Are CDS spreads predictable? An analysis of linear and non-linear forecasting models," International Review of Financial Analysis, Elsevier, vol. 34(C), pages 262-274.
    533. Matthieu Lemoine & Gian Luigi Mazzi & Paola Monperrus-Veroni & Frédéric Reynes, 2008. "Real time estimation of potential output and output gap for the euro-area: comparing production function with unobserved components and SVAR approaches," Documents de Travail de l'OFCE 2008-34, Observatoire Francais des Conjonctures Economiques (OFCE).
    534. Croushore, Dean, 2005. "Do consumer-confidence indexes help forecast consumer spending in real time?," The North American Journal of Economics and Finance, Elsevier, vol. 16(3), pages 435-450, December.
    535. Costantini, Mauro & Pappalardo, Carmine, 2010. "A hierarchical procedure for the combination of forecasts," International Journal of Forecasting, Elsevier, vol. 26(4), pages 725-743, October.
    536. Mouratidis, Kostas, 2008. "Evaluating currency crises: A Bayesian Markov switching approach," Journal of Macroeconomics, Elsevier, vol. 30(4), pages 1688-1711, December.
    537. Paolo Zagaglia, 2013. "Forecasting Long-Term Interest Rates with a General-Equilibrium Model of the Euro Area: What Role for Liquidity Services of Bonds?," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 20(4), pages 383-430, November.
    538. Smets, Frank & Warne, Anders & Wouters, Rafael, 2014. "Professional forecasters and real-time forecasting with a DSGE model," International Journal of Forecasting, Elsevier, vol. 30(4), pages 981-995.
    539. Konstantin A. Kholodilin & Boriss Siliverstovs, 2017. "Think national, forecast local: a case study of 71 German urban housing markets," Applied Economics, Taylor & Francis Journals, vol. 49(42), pages 4271-4297, September.
    540. Todd E. Clark & Taeyoung Doh, 2011. "A Bayesian evaluation of alternative models of trend inflation," Working Papers (Old Series) 1134, Federal Reserve Bank of Cleveland.
    541. Wagner Piazza Gaglianone & Jaqueline Terra Moura Marins, 2014. "Risk Assessment of the Brazilian FX Rate," Working Papers Series 344, Central Bank of Brazil, Research Department.
    542. Kostas Andriosopoulos & Nikos Nomikos, 2012. "Risk management in the energy markets and Value-at-Risk modelling: a Hybrid approach," RSCAS Working Papers 2012/47, European University Institute.
    543. George B. Tawadros, 2013. "The information content of the Reserve Bank of Australia's inflation forecasts," Applied Economics, Taylor & Francis Journals, vol. 45(5), pages 623-628, February.
    544. Kholodilin, Konstantin A. & Yao, Vincent W., 2005. "Measuring and predicting turning points using a dynamic bi-factor model," International Journal of Forecasting, Elsevier, vol. 21(3), pages 525-537.
    545. Laura Coroneo & Fabrizio Iacone, 2015. "Comparing predictive accuracy in small samples," Discussion Papers 15/15, Department of Economics, University of York.
    546. Patrick T. kanda & Mehmet Balcilar & Pejman Bahramian & Rangan Gupta, 2014. "Forecasting South African Inflation Using Non-Linear Models: A Weighted Loss-Based Evaluation," Working Papers 201416, University of Pretoria, Department of Economics.
    547. Dimitar EFTIMOSKI, 2019. "Improving Short-Term Forecasting of Macedonian GDP: Comparing the Factor Model with the Macroeconomic Structural Equation Model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 32-53, June.
    548. Silvia Muzzioli, 2013. "The Forecasting Performance of Corridor Implied Volatility in the Italian Market," Computational Economics, Springer;Society for Computational Economics, vol. 41(3), pages 359-386, March.
    549. Afees A. Salisu & Rangan Gupta & Elie Bouri, 2022. "Testing the Forecasting Power of Global Economic Conditions for the Volatility of International REITs using a GARCH-MIDAS Approach," Working Papers 202211, University of Pretoria, Department of Economics.
    550. Mayr, Johannes & Ulbricht, Dirk, 2015. "Log versus level in VAR forecasting: 42 million empirical answers—Expect the unexpected," Economics Letters, Elsevier, vol. 126(C), pages 40-42.
    551. Supraja Malladi & Qiqi Lu, 2023. "Intervention Time Series Analysis and Forecasting of Organ Donor Transplants in the US during the COVID-19 Era," Forecasting, MDPI, vol. 5(1), pages 1-27, February.
    552. De Gooijer, Jan G. & Vidiella-i-Anguera, Antoni, 2004. "Forecasting threshold cointegrated systems," International Journal of Forecasting, Elsevier, vol. 20(2), pages 237-253.
    553. Kirstin Hubrich & David F. Hendry, 2005. "Forecasting Aggregates by Disaggregates," Computing in Economics and Finance 2005 270, Society for Computational Economics.
    554. Claudio Monteiro & L. Alfredo Fernandez-Jimenez & Ignacio J. Ramirez-Rosado, 2020. "Predictive Trading Strategy for Physical Electricity Futures," Energies, MDPI, vol. 13(14), pages 1-24, July.
    555. Hendry, David F. & Hubrich, Kirstin, 2006. "Forecasting economic aggregates by disaggregates," Working Paper Series 589, European Central Bank.
    556. Gonzalo Calvo & Miguel Ricaurte, 2012. "Indicadores Sintéticos para la Proyección de Imacec en Chile," Working Papers Central Bank of Chile 656, Central Bank of Chile.
    557. Lei Lei Song, 2003. "The Role of the Unit of Analysis in Tax Policy Reform Evaluations," Melbourne Institute Working Paper Series wp2003n29, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    558. Schumacher Christian & Dreger Christian, 2004. "Estimating Large-Scale Factor Models for Economic Activity in Germany: Do They Outperform Simpler Models? / Die Schätzung von großen Faktormodellen für die deutsche Volkswirtschaft: Übertreffen sie ei," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 224(6), pages 731-750, December.
    559. Meredith Beechey & P�r Österholm, 2014. "Policy interest-rate expectations in Sweden: a forecast evaluation," Applied Economics Letters, Taylor & Francis Journals, vol. 21(14), pages 984-991, September.
    560. M. Mucciardi & E. Otranto, 2016. "A Flexible Specification of Space–Time AutoRegressive Models," Working Paper CRENoS 201608, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    561. Greg Tkacz & Carolyn Wilkins, 2008. "Linear and threshold forecasts of output and inflation using stock and housing prices," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(2), pages 131-151.
    562. Ulrich Gunter & Irem Önder & Stefan Gindl, 2019. "Exploring the predictive ability of LIKES of posts on the Facebook pages of four major city DMOs in Austria," Tourism Economics, , vol. 25(3), pages 375-401, May.
    563. Marco Maffezzoli, "undated". "Non-Walrasian Labor Markets and Real Business Cycles," Working Papers 167, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    564. Oguzhan Cepni & Rangan Gupta & Yigit Onay, 2022. "The role of investor sentiment in forecasting housing returns in China: A machine learning approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(8), pages 1725-1740, December.
    565. David Iselin & Boriss Siliverstovs, 2013. "Using Newspapers for Tracking the Business Cycle," KOF Working papers 13-337, KOF Swiss Economic Institute, ETH Zurich.
    566. Liu, Wei & Semeyutin, Artur & Lau, Chi Keung Marco & Gozgor, Giray, 2020. "Forecasting Value-at-Risk of Cryptocurrencies with RiskMetrics type models," Research in International Business and Finance, Elsevier, vol. 54(C).
    567. Mathijs Cosemans & Rik Frehen & Peter C. Schotman & Rob Bauer, 2016. "Estimating Security Betas Using Prior Information Based on Firm Fundamentals," The Review of Financial Studies, Society for Financial Studies, vol. 29(4), pages 1072-1112.
    568. Ran, Jimmy & Voon, Jan P. & Li, Guangzhong, 2008. "Effects of foreign currency component in monetary aggregates on money neutrality," Economics Letters, Elsevier, vol. 99(3), pages 435-438, June.
    569. Krzysztof Drachal & Michał Pawłowski, 2024. "Forecasting Selected Commodities’ Prices with the Bayesian Symbolic Regression," IJFS, MDPI, vol. 12(2), pages 1-56, March.
    570. Fernando Moraes & Rodrigo De-Losso, 2020. "Risk Factor Centrality and the Cross-Section of Expected Returns," Working Papers, Department of Economics 2020_17, University of São Paulo (FEA-USP).
    571. Gabe J. Bondt, 2019. "A PMI-Based Real GDP Tracker for the Euro Area," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 15(2), pages 147-170, December.
    572. Zhou, Jian, 2013. "Conditional market beta for REITs: A comparison of modeling techniques," Economic Modelling, Elsevier, vol. 30(C), pages 196-204.
    573. Rybacki Jakub, 2020. "Are the European Commission's forecasts of public finances better than those of national governments?," Central European Economic Journal, Sciendo, vol. 7(54), pages 101-109, January.
    574. Marcos à lvarez-Díaz & Manuel González-Gómez & María Soledad Otero-Giráldez, 2019. "Estimating the economic impact of a political conflict on tourism: The case of the Catalan separatist challenge," Tourism Economics, , vol. 25(1), pages 34-50, February.
    575. Brückbauer, Frank, 2022. "Do financial market experts know their theory? New evidence from survey data," ZEW Discussion Papers 20-092, ZEW - Leibniz Centre for European Economic Research, revised 2022.
    576. Döhrn, Roland, 2019. "Comparing forecast accuracy in small samples," Ruhr Economic Papers 833, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    577. Mr. Mikhail Golosov & Mr. John R King, 2002. "Tax Revenue Forecasts in IMF-Supported Programs," IMF Working Papers 2002/236, International Monetary Fund.
    578. Marcin Kolasa & Michał Rubaszek & Paweł Skrzypczyński, 2012. "Putting the New Keynesian DSGE Model to the Real‐Time Forecasting Test," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(7), pages 1301-1324, October.
    579. Hitesh Doshi & Kris Jacobs & Rui Liu, 2021. "Information in the Term Structure: A Forecasting Perspective," Management Science, INFORMS, vol. 67(8), pages 5255-5277, August.
    580. Artis, Michael & Marcellino, Massimiliano & Galvão, Ana Beatriz, 2003. "The Transmission Mechanism in a Changing World," CEPR Discussion Papers 4014, C.E.P.R. Discussion Papers.
    581. Al-Zoubi, Haitham A., 2019. "Bond and option prices with permanent shocks," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 272-290.
    582. Hilliard, Jimmy E. & Hilliard, Jitka, 2019. "A jump-diffusion model for pricing and hedging with margined options: An application to Brent crude oil contracts," Journal of Banking & Finance, Elsevier, vol. 98(C), pages 137-155.
    583. Ruthira Naraidoo & Ivan Paya, 2010. "Forecasting Monetary Rules in South Africa," Working Papers 201007, University of Pretoria, Department of Economics.
    584. Veiga, Helena, 2006. "Volatility forecasts: a continuous time model versus discrete time models," DES - Working Papers. Statistics and Econometrics. WS ws062509, Universidad Carlos III de Madrid. Departamento de Estadística.
    585. Logan Rangasamy, 2009. "Inflation Persistence And Core Inflation: The Case Of South Africa," South African Journal of Economics, Economic Society of South Africa, vol. 77(3), pages 430-444, September.
    586. Hassani, Hossein & Webster, Allan & Silva, Emmanuel Sirimal & Heravi, Saeed, 2015. "Forecasting U.S. Tourist arrivals using optimal Singular Spectrum Analysis," Tourism Management, Elsevier, vol. 46(C), pages 322-335.
    587. Silvia Muzzioli, 2010. "Towards a volatility index for the Italian stock market," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 10091, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    588. Weng, Futian & Zhang, Hongwei & Yang, Cai, 2021. "Volatility forecasting of crude oil futures based on a genetic algorithm regularization online extreme learning machine with a forgetting factor: The role of news during the COVID-19 pandemic," Resources Policy, Elsevier, vol. 73(C).
    589. Mark E. Wohar & David E. Rapach, 2007. "Forecasting the recent behavior of US business fixed investment spending: an analysis of competing models This is a significantly revised version of our previous paper, 'Forecasting US Business Fixed ," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(1), pages 33-51.
    590. Konstantin A., Kholodilin, 2003. "Identifying and Forecasting the Turns of the Japanese Business Cycle," LIDAM Discussion Papers IRES 2003008, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
    591. Anthony Garratt & Shaun P. Vahey & Ynuyi Zhang, 2018. "Real-time Forecast Combinations for the Oil Price," National Institute of Economic and Social Research (NIESR) Discussion Papers 494, National Institute of Economic and Social Research.
    592. Steffen Henzel, 2015. "Forecasting Accuracy of the Ifo Business Survey – Influence of New Seasonal Adjustment with X-13ARIMA-SEATS," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 68(01), pages 59-63, January.
    593. Olivier BIAU & Angela D´ELIA, 2010. "Euro Area GDP Forecast Using Large Survey Dataset - A Random Forest Approach," EcoMod2010 259600029, EcoMod.
    594. Fukuda, Kosei, 2006. "Monitoring unit root and multiple structural changes: An information criterion approach," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 71(2), pages 121-130.
    595. Reimers, Hans-Eggert, 2002. "Analysing Divisia Aggregates for the Euro Area," Discussion Paper Series 1: Economic Studies 2002,13, Deutsche Bundesbank.
    596. Magnus Reif, 2018. "Macroeconomic Uncertainty and Forecasting Macroeconomic Aggregates," ifo Working Paper Series 265, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    597. George Chouliarakis, 2009. "Coping With Uncertainty: Historical And Real‐Time Estimates Of The Natural Unemployment Rate And The Uk Monetary Policy," Manchester School, University of Manchester, vol. 77(4), pages 479-511, July.
    598. Silvia Muzzioli, 2011. "Corridor implied volatility and the variance risk premium in the Italian market," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0030, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    599. Christopher G. Gibbs, 2015. "Overcoming the Forecast Combination Puzzle: Lessons from the Time-Varying Effciency of Phillips Curve Forecasts of U.S. Inflation," Discussion Papers 2015-09, School of Economics, The University of New South Wales.
    600. Michael H. Breitner & Christian Dunis & Hans-Jörg Mettenheim & Christopher Neely & Georgios Sermpinis & Georgios Sermpinis & Charalampos Stasinakis & Konstantinos Theofilatos & Andreas Karathanasopoul, 2014. "Inflation and Unemployment Forecasting with Genetic Support Vector Regression," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(6), pages 471-487, September.
    601. Yucheng Yang & Yue Pang & Guanhua Huang & Weinan E, 2020. "The Knowledge Graph for Macroeconomic Analysis with Alternative Big Data," Papers 2010.05172, arXiv.org.
    602. Bou-Hamad, Imad & Jamali, Ibrahim, 2020. "Forecasting financial time-series using data mining models: A simulation study," Research in International Business and Finance, Elsevier, vol. 51(C).
    603. Garcés Díaz Daniel, 2016. "Changes in Inflation Predictability in Major Latin American Countries," Working Papers 2016-20, Banco de México.
    604. Baghestani, Hamid, 2010. "How well do experts predict interbank loan rates and spreads?," Economics Letters, Elsevier, vol. 109(1), pages 4-6, October.
    605. Angela He & Alan Wan, 2009. "Predicting daily highs and lows of exchange rates: a cointegration analysis," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(11), pages 1191-1204.
    606. Sandra Bilek-Steindl & Thomas Url, 2022. "Nowcasting and monitoring SDG 8," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 49(2), pages 313-345, May.
    607. Sharma, Udayan & Karmakar, Madhusudan, 2023. "Measuring minimum variance hedging effectiveness: Traditional vs. sophisticated models," International Review of Financial Analysis, Elsevier, vol. 87(C).
    608. Ángel Cuevas & Ramiro Ledo & Enrique M. Quilis, 2021. "Seasonal adjustment of the Spanish sales daily data," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 12(4), pages 687-708, December.
    609. Manzan, Sebastiano & Westerhoff, Frank H., 2007. "Heterogeneous expectations, exchange rate dynamics and predictability," Journal of Economic Behavior & Organization, Elsevier, vol. 64(1), pages 111-128, September.
    610. Marta Banbura & Andries van Vlodrop, 2018. "Forecasting with Bayesian Vector Autoregressions with Time Variation in the Mean," Tinbergen Institute Discussion Papers 18-025/IV, Tinbergen Institute.
    611. Xiaojie Xu, 2020. "Corn Cash Price Forecasting," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(4), pages 1297-1320, August.
    612. Christian Grimme & Robert Lehmann & Marvin Nöller, 2018. "ifo Import Climate – a First Lead Indicator for Forecasting German Imports," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 71(12), pages 27-32, June.
    613. Nonejad, Nima, 2020. "Crude oil price changes and the United Kingdom real gross domestic product growth rate: An out-of-sample investigation," The Journal of Economic Asymmetries, Elsevier, vol. 21(C).
    614. Ricardo P. Masini & Marcelo C. Medeiros & Eduardo F. Mendes, 2023. "Machine learning advances for time series forecasting," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 76-111, February.
    615. Annari de Waal & Renee van Eyden & Rangan Gupta, 2013. "Do we need a global VAR model to forecast inflation and output in South Africa?," Working Papers 201346, University of Pretoria, Department of Economics.
    616. Krzysztof Drachal & Daniel González Cortés, 2022. "Estimation of Lockdowns’ Impact on Well-Being in Selected Countries: An Application of Novel Bayesian Methods and Google Search Queries Data," IJERPH, MDPI, vol. 20(1), pages 1-24, December.
    617. Björn Fastrich & Peter Winker, 2014. "Combining Forecasts with Missing Data: Making Use of Portfolio Theory," Computational Economics, Springer;Society for Computational Economics, vol. 44(2), pages 127-152, August.
    618. Zied Ftiti & Kais Tissaoui & Sahbi Boubaker, 2022. "On the relationship between oil and gas markets: a new forecasting framework based on a machine learning approach," Annals of Operations Research, Springer, vol. 313(2), pages 915-943, June.
    619. Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2024. "Business applications and state‐level stock market realized volatility: A forecasting experiment," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 456-472, March.
    620. Lan Bai & Xiafei Li & Yu Wei & Guiwu Wei, 2022. "Does crude oil futures price really help to predict spot oil price? New evidence from density forecasting," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3694-3712, July.
    621. Ullrich Heilemann & Karsten Müller, 2018. "Wenig Unterschiede – Zur Treffsicherheit Internationaler Prognosen und Prognostiker [Few differences—on the accuracy of international forecasts and forecaster]," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 12(3), pages 195-233, December.
    622. Constantin Burgi, 2015. "Can A Subset Of Forecasters Beat The Simple Average In The Spf?," Working Papers 2015-001, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    623. Apostolos Ampountolas, 2021. "Modeling and Forecasting Daily Hotel Demand: A Comparison Based on SARIMAX, Neural Networks, and GARCH Models," Forecasting, MDPI, vol. 3(3), pages 1-16, August.
    624. Karsten Müller, 2022. "German forecasters’ narratives: How informative are German business cycle forecast reports?," Empirical Economics, Springer, vol. 62(5), pages 2373-2415, May.
    625. Antonio Marsi, 2023. "Predicting European stock returns using machine learning," SN Business & Economics, Springer, vol. 3(7), pages 1-25, July.
    626. Renyuan Shao & Brian Roe, 2003. "The design and pricing of fixed‐ and moving‐window contracts: An application of Asian‐Basket option pricing methods to the hog‐finishing sector," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 23(11), pages 1047-1073, November.
    627. Afees A. Salisu & Christian Pierdzioch & Rangan Gupta & Renee van Eyden, 2021. "Climate Risks and U.S. Stock-Market Tail Risks: A Forecasting Experiment Using over a Century of Data," Working Papers 202165, University of Pretoria, Department of Economics.
    628. Fabio Busetti & Juri Marcucci & Giovanni Veronese, 2009. "Comparing forecast accuracy: A Monte Carlo investigation," Temi di discussione (Economic working papers) 723, Bank of Italy, Economic Research and International Relations Area.
    629. Seong, Byeongchan, 2020. "Smoothing and forecasting mixed-frequency time series with vector exponential smoothing models," Economic Modelling, Elsevier, vol. 91(C), pages 463-468.
    630. Sihle Kubheka, 2023. "South African inflation modelling using bootstrapped long short-term memory methods," SN Business & Economics, Springer, vol. 3(7), pages 1-11, July.
    631. Hüfner Felix P. & Schröder Michael, 2002. "Prognosegehalt von ifo-Geschäftserwartungen und ZEW-Konjunkturerwartungen: Ein ökonometrischer Vergleich / Forecasting German industrial Production: An Econometric Comparison of ifo- and ZEW-Business ," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 222(3), pages 316-336, June.
    632. Christos Katris & Manolis G. Kavussanos, 2021. "Time series forecasting methods for the Baltic dry index," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1540-1565, December.
    633. Goodness C. Aye & Mehmet Balcilar & Adél Bosch & Rangan Gupta & Francois Stofberg, 2013. "The out-of-sample forecasting performance of non-linear models of real exchange rate behaviour: The case of the South African Rand," European Journal of Comparative Economics, Cattaneo University (LIUC), vol. 10(1), pages 121-148, April.
    634. Egelkraut, Thorsten M. & Garcia, Philip & Irwin, Scott H. & Good, Darrel L., 2002. "An Evaluation Of Crop Forecast Accuracy For Corn And Soybeans: Usda And Private Information Services," 2002 Conference, April 22-23, 2002, St. Louis, Missouri 19068, NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    635. Hossein Hassani & Emmanuel Sirimal Silva & Rangan Gupta & Mawuli K. Segnon, 2015. "Forecasting the price of gold," Applied Economics, Taylor & Francis Journals, vol. 47(39), pages 4141-4152, August.
    636. Xiaojie Xu & Yun Zhang, 2022. "Commodity price forecasting via neural networks for coffee, corn, cotton, oats, soybeans, soybean oil, sugar, and wheat," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 29(3), pages 169-181, July.
    637. Marcus Cobb, 2009. "Forecasting Chilean Inflation From Disaggregate Components," Working Papers Central Bank of Chile 545, Central Bank of Chile.
    638. Atsushi Inoue & Barbara Rossi, 2011. "Out-of-sample forecast tests robust to the choice of window size," Working Papers 11-31, Federal Reserve Bank of Philadelphia.
    639. Guglielmo Maria Caporale & Luis A. Gil-Alana, 2012. "Persistence and Cycles in the US Federal Funds Rate," CESifo Working Paper Series 4035, CESifo.
    640. Nikolay Robinzonov & Gerhard Tutz & Torsten Hothorn, 2012. "Boosting techniques for nonlinear time series models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 96(1), pages 99-122, January.
    641. Christian Glocker & Serguei Kaniovski, 2020. "Macroeconometric Forecasting Using a Cluster of Dynamic Factor Models," WIFO Working Papers 614, WIFO.
    642. Kalamara, Eleni & Turrell, Arthur & Redl, Chris & Kapetanios, George & Kapadia, Sujit, 2020. "Making text count: economic forecasting using newspaper text," Bank of England working papers 865, Bank of England.
    643. Rangan Gupta & Sayar Karmakar & Christian Pierdzioch, 2022. "Safe Havens, Machine Learning, and the Sources of Geopolitical Risk: A Forecasting Analysis Using Over a Century of Data," Working Papers 202201, University of Pretoria, Department of Economics.
    644. Oliver Hülsewig & Johannes Mayr & Stéphane Sorbe, 2007. "Assessing the Forecast Properties of the CESifo World Economic Climate Indicator: Evidence for the Euro Area," ifo Working Paper Series 46, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    645. Kavussanos, Manolis G. & Dimitrakopoulos, Dimitris N., 2011. "Market risk model selection and medium-term risk with limited data: Application to ocean tanker freight markets," International Review of Financial Analysis, Elsevier, vol. 20(5), pages 258-268.
    646. Zuzana Rakovska, 2020. "Composite Survey Sentiment as a Predictor of Future Market Returns: Evidence for German Equity Indices," Working Papers 2020/13, Czech National Bank.
    647. Konstantins Benkovskis, 2008. "Short-Term Forecasts of Latvia's Real Gross Domestic Product Growth Using Monthly Indicators," Working Papers 2008/05, Latvijas Banka.
    648. Hélène Erkel-Rousse, 2006. "Les enquêtes de conjoncture : de l'analyse conjoncturelle aux études structurelles," Économie et Statistique, Programme National Persée, vol. 395(1), pages 3-11.
    649. He, Angela W.W. & Kwok, Jerry T.K. & Wan, Alan T.K., 2010. "An empirical model of daily highs and lows of West Texas Intermediate crude oil prices," Energy Economics, Elsevier, vol. 32(6), pages 1499-1506, November.
    650. Morita, Hiroshi & 森田, 裕史, 2019. "Forecasting Public Investment Using Daily Stock Returns," Discussion paper series HIAS-E-88, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    651. Stefan Sauer & Klaus Wohlrabe, 2020. "ifo Handbuch der Konjunkturumfragen," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 88.
    652. Afees A. Salisu & Wenting Liao & Rangan Gupta & Oguzhan Cepni, 2023. "Economic Conditions and Predictability of US Stock Returns Volatility: Local Factor versus National Factor in a GARCH-MIDAS Model," Working Papers 202323, University of Pretoria, Department of Economics.
    653. Afees A. Salisu & Ahamuefula E. Ogbonna & Rangan Gupta & Elie Bouri, 2023. "Energy-Related Uncertainty and International Stock Market Volatility," Working Papers 202336, University of Pretoria, Department of Economics.
    654. Kanas, Angelos & Vasiliou, Dimitrios & Eriotis, Nikolaos, 2012. "Revisiting bank profitability: A semi-parametric approach," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(4), pages 990-1005.
    655. Poncela, Pilar & Rodríguez, Julio & Sánchez-Mangas, Rocío & Senra, Eva, 2011. "Forecast combination through dimension reduction techniques," International Journal of Forecasting, Elsevier, vol. 27(2), pages 224-237.
    656. Mittnik, Stefan & Robinzonov, Nikolay & Spindler, Martin, 2015. "Stock market volatility: Identifying major drivers and the nature of their impact," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 1-14.
    657. Groen, Jan J.J. & Kapetanios, George, 2016. "Revisiting useful approaches to data-rich macroeconomic forecasting," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 221-239.
    658. Kosei Fukuda, 2005. "Forecasting economic time series with measurement error," Applied Economics Letters, Taylor & Francis Journals, vol. 12(15), pages 923-927.
    659. Pamela Jervis, 2007. "Inflation Compensation and Its Components in Chile," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 10(2), pages 27-56, August.
    660. Balcilar, Mehmet & Gupta, Rangan & van Eyden, Reneé & Thompson, Kirsten & Majumdar, Anandamayee, 2018. "Comparing the forecasting ability of financial conditions indices: The case of South Africa," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 245-259.
    661. António Rua, 2011. "A wavelet approach for factor‐augmented forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(7), pages 666-678, November.
    662. Garratt, Anthony & Petrella, Ivan & Zhang, Yunyi, 2022. "Asymmetry and Interdependence when Evaluating U.S. Energy Information Administration Forecasts," MPRA Paper 115559, University Library of Munich, Germany.
    663. Helmut Lütkepohl & Fang Xu, 2009. "The Role of the Log Transformation in Forecasting Economic Variables," CESifo Working Paper Series 2591, CESifo.
    664. David I. Harvey & Stephen J. Leybourne & Robert Sollis & A.M. Robert Taylor, 2021. "Real‐time detection of regimes of predictability in the US equity premium," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(1), pages 45-70, January.
    665. Francis X. Diebold & Glenn D. Rudebusch, 2001. "Five questions about business cycles," Economic Review, Federal Reserve Bank of San Francisco, pages 1-15.
    666. Kim, Myung Suk, 2018. "Impacts of supply and demand factors on declining oil prices," Energy, Elsevier, vol. 155(C), pages 1059-1065.
    667. Jonathan H. Wright, 2015. "Comment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(1), pages 12-13, January.
    668. Roy Batchelor, 2001. "How useful are the forecasts of intergovernmental agencies? The IMF and OECD versus the consensus," Applied Economics, Taylor & Francis Journals, vol. 33(2), pages 225-235.
    669. Milena Hoyos & Mario Galindo, 2011. "Comparación de los modelos SETAR y STAR para el índice de empleo industrial colombiano," Documentos de Trabajo, Escuela de Economía 8347, Universidad Nacional de Colombia, FCE, CID.
    670. Célérier, C., 2009. "Forecasting inflation in France," Working papers 262, Banque de France.
    671. Richard D. F. Harris & Murat Mazibas, 2022. "A component Markov regime‐switching autoregressive conditional range model," Bulletin of Economic Research, Wiley Blackwell, vol. 74(2), pages 650-683, April.
    672. Karlyn Mitchell & Douglas K. Pearce, 2004. "Professional Forecasts of Interest Rates and Exchange Rates: Evidence from the Wall Street Journal's Panel of Economists," Working Paper Series 004, North Carolina State University, Department of Economics.
    673. Rianne Legerstee & Philip Hans Franses, 2015. "Does Disagreement Amongst Forecasters Have Predictive Value?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(4), pages 290-302, July.
    674. Gaglianone, Wagner Piazza & Marins, Jaqueline Terra Moura, 2017. "Evaluation of exchange rate point and density forecasts: An application to Brazil," International Journal of Forecasting, Elsevier, vol. 33(3), pages 707-728.
    675. Claus Brand & Hans-Eggert Reimers & Franz Seitz, 2003. "Narrow Money and the Business Cycle: Theoretical aspects and euro area evdence," Macroeconomics 0303012, University Library of Munich, Germany.
    676. Marie Diron & Maria Cruz Manzano & Thomas Westermann, 2005. "Forecasting aggregate investment in the euro area: do indicators of financial conditions help?," BIS Papers chapters, in: Bank for International Settlements (ed.), Investigating the relationship between the financial and real economy, volume 22, pages 206-27, Bank for International Settlements.
    677. Luetkepohl Helmut & Xu Fang, 2011. "Forecasting Annual Inflation with Seasonal Monthly Data: Using Levels versus Logs of the Underlying Price Index," Journal of Time Series Econometrics, De Gruyter, vol. 3(1), pages 1-23, February.
    678. Colino, Evelyn V. & Irwin, Scott H. & Garcia, Philip, 2008. "How Much Can Outlook Forecasts be Improved? An Application to the U.S. Hog Market," 2008 Conference, April 21-22, 2008, St. Louis, Missouri 37620, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    679. Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2024. "Forecasting Growth-at-Risk of the United States: Housing Price versus Housing Sentiment or Attention," Working Papers 202401, University of Pretoria, Department of Economics.
    680. Petrella, Ivan & Drechsel, Thomas & Antolin-Diaz, Juan, 2014. "Following the Trend: Tracking GDP when Long-Run Growth is Uncertain," CEPR Discussion Papers 10272, C.E.P.R. Discussion Papers.
    681. Alex Ilek, 2007. "Aggregation versus Disaggregation - What can we learn from it?," Bank of Israel Working Papers 2007.02b, Bank of Israel.
    682. L. De Charsonville & F. Ferrière & C. Jardet, 2017. "MAPI: Model for Analysis and Projection of Inflation in France," Working papers 637, Banque de France.
    683. Tommaso PROIETTI & Alberto MUSSO & Thomas WESTERMANN, 2002. "Estimating Potential Output and the Output Gap for the Euro Area: a Model-Based Production Function Approach," Economics Working Papers ECO2002/09, European University Institute.
    684. Şener, Emrah & Baronyan, Sayad & Ali Mengütürk, Levent, 2012. "Ranking the predictive performances of value-at-risk estimation methods," International Journal of Forecasting, Elsevier, vol. 28(4), pages 849-873.
    685. Gagnon, Marie-Hélène & Power, Gabriel J. & Toupin, Dominique, 2023. "The sum of all fears: Forecasting international returns using option-implied risk measures," Journal of Banking & Finance, Elsevier, vol. 146(C).
    686. Julie K. Smith, 2012. "PCE inflation and core inflation," Working Papers 1203, Federal Reserve Bank of Dallas.
    687. Reimers Hans-Eggert, 2003. "Does Money Include Information for Prices in the Euro Area? / Enthält Geld Informationen für die Preisentwicklung im Eurowährungsgebiet?," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 223(5), pages 581-602, October.
    688. David Ubilava, 2022. "A comparison of multistep commodity price forecasts using direct and iterated smooth transition autoregressive methods," Agricultural Economics, International Association of Agricultural Economists, vol. 53(5), pages 687-701, September.
    689. Radchenko, Peter & Vasnev, Andrey L. & Wang, Wendun, 2023. "Too similar to combine? On negative weights in forecast combination," International Journal of Forecasting, Elsevier, vol. 39(1), pages 18-38.
    690. Luis Fernando Melo & Héctor Núñez, 2004. "Combinación de Pronósticos de la Inflación en Presencia de cambios Estructurales," Borradores de Economia 286, Banco de la Republica de Colombia.
    691. Mahmut Gunay, 2016. "Forecasting Turkish GDP Growth with Financial Variables and Confidence Indicators," CBT Research Notes in Economics 1614, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    692. Croushore Dean, 2010. "An Evaluation of Inflation Forecasts from Surveys Using Real-Time Data," The B.E. Journal of Macroeconomics, De Gruyter, vol. 10(1), pages 1-32, May.
    693. de Mendonça, Helder Ferreira & Simão Filho, José & Abreu, Vanessa Castro, 2023. "Central bank’s forecasts and lack of transparency: An assessment of the effect on private expectations in a large emerging economy," Economic Systems, Elsevier, vol. 47(2).
    694. Gilles Mourre & Michael Thiel, 2006. "Monitoring short-term labour cost developments in the European Union: which indicators to trust?," European Economy - Economic Papers 2008 - 2015 258, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    695. Timo Teräsvirta & Marcelo C. Medeiros & Gianluigi Rech, 2006. "Building neural network models for time series: a statistical approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(1), pages 49-75.
    696. Juan Tenorio & Wilder Perez, 2024. "Monthly GDP nowcasting with Machine Learning and Unstructured Data," Papers 2402.04165, arXiv.org.
    697. Abbritti, Mirko & Carcel, Hector & Gil-Alana, Luis & Moreno, Antonio, 2023. "Term premium in a fractionally cointegrated yield curve," Journal of Banking & Finance, Elsevier, vol. 149(C).
    698. Baffigi, Alberto & Golinelli, Roberto & Parigi, Giuseppe, 2004. "Bridge models to forecast the euro area GDP," International Journal of Forecasting, Elsevier, vol. 20(3), pages 447-460.
    699. Angelos Kanas & Panagiotis D. Zervopoulos, 2020. "Systemic risk-shifting in U.S. commercial banking," Review of Quantitative Finance and Accounting, Springer, vol. 54(2), pages 517-539, February.
    700. Döhrn, Roland, 2013. "Transportation Data as a Tool for Nowcasting Economic Activity – The German Road Pricing System as an Example," Ruhr Economic Papers 395, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    701. Pami Dua & Nishita Raje & Satyananda Sahoo, 2008. "Forecasting Interest Rates in India," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 2(1), pages 1-41, March.
    702. Pablo Pincheira, 2010. "A Real Time Evaluation of the Central Bank of Chile GDP Growth Forecasts," Working Papers Central Bank of Chile 556, Central Bank of Chile.
    703. Etienne, Xiaoli L. & Farhangdoost, Sara & Hoffman, Linwood A. & Adam, Brian D., 2023. "Forecasting the U.S. season-average farm price of corn: Derivation of an alternative futures-based forecasting model," Journal of Commodity Markets, Elsevier, vol. 30(C).
    704. Guzman, Giselle C., 2010. "An inflation expectations horserace," MPRA Paper 36511, University Library of Munich, Germany.
    705. Afees A. Salisu & Riza Demirer & Rangan Gupta, 2022. "Policy Uncertainty and Stock Market Volatility Revisited: The Predictive Role of Signal Quality," Working Papers 202232, University of Pretoria, Department of Economics.
    706. Georgios Chortareas & John Nankervis & Ying Jiang, 2007. "Forecasting Exchange Rate Volatility with High Frequency Data: Is the Euro Different?," Money Macro and Finance (MMF) Research Group Conference 2006 79, Money Macro and Finance Research Group.
    707. Erhard RESCHENHOFER & Thomas STARK, 2019. "Forecasting the Yield Curve with Dynamic Factors," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 101-113, March.
    708. Teräsvirta, Timo, 2005. "Forecasting economic variables with nonlinear models," SSE/EFI Working Paper Series in Economics and Finance 598, Stockholm School of Economics, revised 29 Dec 2005.
    709. Till Weigt & Bernd Wilfling, 2021. "An approach to increasing forecast‐combination accuracy through VAR error modeling," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(4), pages 686-699, July.
    710. Halužan, Marko & Verbič, Miroslav & Zorić, Jelena, 2020. "Performance of alternative electricity price forecasting methods: Findings from the Greek and Hungarian power exchanges," Applied Energy, Elsevier, vol. 277(C).
    711. Duarte, Claudia & Rua, Antonio, 2007. "Forecasting inflation through a bottom-up approach: How bottom is bottom?," Economic Modelling, Elsevier, vol. 24(6), pages 941-953, November.
    712. Hakeem‐Ur Rehman & Guohua Wan & Raza Rafique, 2023. "A hybrid approach with step‐size aggregation to forecasting hierarchical time series," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(1), pages 176-192, January.
    713. Aspremont Alexandre & Ben Arous Simon & Bricongne Jean-Charles & Lietti Benjamin & Meunier Baptiste, 2023. "Satellites Turn “Concrete”: Tracking Cement with Satellite Data and Neural Networks," Working papers 916, Banque de France.
    714. Barhoumi, K. & Brunhes-Lesage, V. & Ferrara, L. & Pluyaud, B. & Rouvreau, B. & Darné, O., 2008. "OPTIM: a quarterly forecasting tool for French GDP," Quarterly selection of articles - Bulletin de la Banque de France, Banque de France, issue 13, pages 31-47, Autumn.
    715. Wu, Yih-Jiuan, 1998. "Exchange rate forecasting: an application of radial basis function neural networks," ISU General Staff Papers 1998010108000013540, Iowa State University, Department of Economics.
    716. Giampiero M. Gallo & Edoardo Otranto, 2014. "Forecasting Realized Volatility with Changes of Regimes," Econometrics Working Papers Archive 2014_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Feb 2014.
    717. Michał Rubaszek & Paweł Skrzypczyński & Grzegorz Koloch, 2010. "Forecasting the Polish Zloty with Non-Linear Models," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 2(2), pages 151-167, March.
    718. Faust, Jon & Wright, Jonathan H., 2013. "Forecasting Inflation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 2-56, Elsevier.
    719. Osman, Mohammad & Jean Louis, Rosmy & Balli, Faruk, 2008. "Output gap and inflation nexus: the case of United Arab Emirates," MPRA Paper 34006, University Library of Munich, Germany, revised 2009.
    720. Ying Wang & Jianzhou Wang & Hongmin Li & Hufang Yang & Zhiwu Li, 2022. "Multi‐step air quality index forecasting via data preprocessing, sequence reconstruction, and improved multi‐objective optimization algorithm," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(7), pages 1483-1511, November.
    721. Ali Dib & Kevin Moran, 2005. "Forecasting with the New-Keynesian Model: An Experiment with Canadian Data," Computing in Economics and Finance 2005 235, Society for Computational Economics.
    722. Andrew Vivian, 2005. "The Equity Premium: 101 years of Empirical Evidence from the UK," Money Macro and Finance (MMF) Research Group Conference 2005 92, Money Macro and Finance Research Group.
    723. Michael Clements, 2006. "Evaluating the survey of professional forecasters probability distributions of expected inflation based on derived event probability forecasts," Empirical Economics, Springer, vol. 31(1), pages 49-64, March.
    724. Feng Zhao & Guofu Zhou & Xiaoneng Zhu, 2021. "Unspanned Global Macro Risks in Bond Returns," Management Science, INFORMS, vol. 67(12), pages 7825-7843, December.
    725. Kontogeorgos, Georgios & Lambrias, Kyriacos, 2019. "An analysis of the Eurosystem/ECB projections," Working Paper Series 2291, European Central Bank.
    726. Tao Chen & Liang Wu & Isabel Kit-Ming Yan, 2013. "On the Use of International Commodity Futures Spread for Forecasting China's Net Imports of Commodities," The World Economy, Wiley Blackwell, vol. 36(7), pages 861-879, July.
    727. Stephen McKnight & Alexander Mihailov & Fabio Rumler, 2018. "NKPC-Based Inflation Forecasts with a Time-Varying Trend," Serie documentos de trabajo del Centro de Estudios Económicos 2018-05, El Colegio de México, Centro de Estudios Económicos.
    728. Prüser, Jan, 2023. "Data-based priors for vector error correction models," International Journal of Forecasting, Elsevier, vol. 39(1), pages 209-227.
    729. Nima Nonejad, 2020. "A detailed look at crude oil price volatility prediction using macroeconomic variables," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1119-1141, November.
    730. Diogo M. F. Izidio & Paulo S. G. de Mattos Neto & Luciano Barbosa & João F. L. de Oliveira & Manoel Henrique da Nóbrega Marinho & Guilherme Ferretti Rissi, 2021. "Evolutionary Hybrid System for Energy Consumption Forecasting for Smart Meters," Energies, MDPI, vol. 14(7), pages 1-19, March.
    731. Lahiri, Kajal & Yang, Liu, 2013. "Forecasting Binary Outcomes," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1025-1106, Elsevier.
    732. Ulrich Gunter, 2019. "Estimating and forecasting with a two-country DSGE model of the Euro area and the USA: the merits of diverging interest-rate rules," Empirical Economics, Springer, vol. 56(4), pages 1283-1323, April.
    733. Benner, Joachim & Meier, Carsten-Patrick, 2005. "Was leisten Stimmungsindikatoren für die Prognose des realen Bruttoinlandsprodukts in Deutschland? Eine Echtzeit-Analyse," Open Access Publications from Kiel Institute for the World Economy 3725, Kiel Institute for the World Economy (IfW Kiel).
    734. Carlos Fonseca Marinheiro, 2010. "Fiscal sustainability and the accuracy of macroeconomic forecasts: do supranational forecasts rather than government forecasts make a difference?," GEMF Working Papers 2010-07, GEMF, Faculty of Economics, University of Coimbra.
    735. Robert Gausden & Mohammad S. Hasan, 2016. "Would information on consumer confidence have helped to predict UK household expenditure during the recent economic crisis?," Applied Economics, Taylor & Francis Journals, vol. 48(18), pages 1695-1709, April.
    736. Meng, Fanyi & Liu, Li, 2019. "Analyzing the economic sources of oil price volatility: An out-of-sample perspective," Energy, Elsevier, vol. 177(C), pages 476-486.
    737. Drachal, Krzysztof, 2018. "Comparison between Bayesian and information-theoretic model averaging: Fossil fuels prices example," Energy Economics, Elsevier, vol. 74(C), pages 208-251.
    738. Lei Lei Song, 2005. "Do underlying measures of inflation outperform headline rates? Evidence from Australian data," Applied Economics, Taylor & Francis Journals, vol. 37(3), pages 339-345.
    739. Wegmüller, Philipp & Glocker, Christian & Guggia, Valentino, 2023. "Weekly economic activity: Measurement and informational content," International Journal of Forecasting, Elsevier, vol. 39(1), pages 228-243.
    740. Claudia Godbout & Jocelyn Jacob, 2010. "Le pouvoir de prévision des indices PMI," Discussion Papers 10-3, Bank of Canada.
    741. Eirini Konstantinidi & Gkaren Papazian & George Skiadopoulos, 2015. "Modeling the Dynamics of Temperature with a View to Weather Derivatives," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 17, pages 511-544, World Scientific Publishing Co. Pte. Ltd..
    742. Min Liu & Chien‐Chiang Lee & Wei‐Chong Choo, 2021. "An empirical study on the role of trading volume and data frequency in volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 792-816, August.
    743. Cobb, Marcus P A, 2017. "Forecasting Economic Aggregates Using Dynamic Component Grouping," MPRA Paper 81585, University Library of Munich, Germany.
    744. Qi, Lingzhi & Li, Xixi & Wang, Qiang & Jia, Suling, 2023. "fETSmcs: Feature-based ETS model component selection," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1303-1317.
    745. Guillaume Chevillon, 2004. "A Comparison of Multi-step GDP Forecasts for South Africa," Documents de Travail de l'OFCE 2004-13, Observatoire Francais des Conjonctures Economiques (OFCE).
    746. Fabio Moneta, 2005. "Does the Yield Spread Predict Recessions in the Euro Area?," International Finance, Wiley Blackwell, vol. 8(2), pages 263-301, August.
    747. Mariano, Roberto S. & Preve, Daniel, 2012. "Statistical tests for multiple forecast comparison," Journal of Econometrics, Elsevier, vol. 169(1), pages 123-130.
    748. Çepni, Oğuzhan & Guney, I. Ethem & Gupta, Rangan & Wohar, Mark E., 2020. "The role of an aligned investor sentiment index in predicting bond risk premia of the U.S," Journal of Financial Markets, Elsevier, vol. 51(C).
    749. Döhrn, Roland & Barabas, György & Gebhardt, Heinz & Kitlinski, Tobias & Micheli, Martin & Schmidt, Torsten & Vosen, Simeon & Zimmermann, Lina, 2010. "Die wirtschaftliche Entwicklung im Inland: Aufschwung verliert an Fahrt," RWI Konjunkturberichte, RWI - Leibniz-Institut für Wirtschaftsforschung, vol. 61(2), pages 37-82.
    750. Simon Hirsch & Florian Ziel, 2022. "Simulation-based Forecasting for Intraday Power Markets: Modelling Fundamental Drivers for Location, Shape and Scale of the Price Distribution," Papers 2211.13002, arXiv.org.
    751. Salisu, Afees & Raheem, Ibrahim & Vo, Xuan, 2021. "Assessing the safe haven property of the gold market during COVID-19 pandemic," MPRA Paper 105353, University Library of Munich, Germany.
    752. Nonejad, Nima, 2020. "A comprehensive empirical analysis of the predictive impact of the price of crude oil on aggregate equity return volatility," Journal of Commodity Markets, Elsevier, vol. 20(C).
    753. Gharsallah, Sofian & Sucarrat, Genaro, 2019. "Hvor presise er prognosene i Nasjonalbudsjettet? [How precise are the forecasts of the Norwegian national budget?]," MPRA Paper 96850, University Library of Munich, Germany.
    754. Ullrich Heilemann & Herman Stekler, 2010. "Perspectives on Evaluating Macroeconomic Forecasts," Working Papers 2010-002, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    755. Riza Demirer & Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2022. "Risk aversion and the predictability of crude oil market volatility: A forecasting experiment with random forests," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 73(8), pages 1755-1767, August.
    756. Christos Papamichael & Nicoletta Pashourtidou, 2016. "The Role of Survey Data in the Construction of Short-term GDP Growth Forecasts," Cyprus Economic Policy Review, University of Cyprus, Economics Research Centre, vol. 10(2), pages 77-109, December.
    757. Jan G. de Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Tinbergen Institute Discussion Papers 05-068/4, Tinbergen Institute.
    758. Yang, Ke & Tian, Fengping & Chen, Langnan & Li, Steven, 2017. "Realized volatility forecast of agricultural futures using the HAR models with bagging and combination approaches," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 276-291.
    759. Karim Barhoumi & Olivier Darné & Laurent Ferrara, 2010. "Are disaggregate data useful for factor analysis in forecasting French GDP?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 132-144.
    760. Constantin Bürgi & Tara M. Sinclair, 2015. "A Nonparametric Approach to Identifying a Subset of Forecasters that Outperforms the Simple Average," Working Papers 2015-006, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    761. Zhang, Yishuo & Li, Gang & Muskat, Birgit & Vu, Huy Quan & Law, Rob, 2021. "Predictivity of tourism demand data," Annals of Tourism Research, Elsevier, vol. 89(C).
    762. Claire Giordano & Marco Marinucci & Andrea Silvestrini, 2022. "Assessing the usefulness of survey‐based data in forecasting firms' capital formation: Evidence from Italy," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 491-513, April.
    763. Siva R Venna & Satya Katragadda & Vijay Raghavan & Raju Gottumukkala, 2021. "River Stage Forecasting using Enhanced Partial Correlation Graph," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(12), pages 4111-4126, September.
    764. Hüfner, Felix P. & Schröder, Michael, 2001. "Unternehmens- versus Analystenbefragungen: Zum Prognosegehalt von ifo-Geschäftserwartungen und ZEW-Konjunkturerwartungen," ZEW Discussion Papers 01-04, ZEW - Leibniz Centre for European Economic Research.
    765. Wenjuan Chen & Dieter Nautz, 2015. "The Information Content of Monetary Statistics for the Great Recession: Evidence from Germany," SFB 649 Discussion Papers SFB649DP2015-027, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    766. Dreger, Christian & Schumacher, Christian, 2002. "Estimating large-scale factor models for economic activity in Germany: Do they outperform simpler models?," HWWA Discussion Papers 199, Hamburg Institute of International Economics (HWWA).
    767. Eliana González, 2011. "Forecasting With Many Predictors. An Empirical Comparison," Borradores de Economia 7996, Banco de la Republica.
    768. Sabine Stephan, 2005. "German Exports to the Euro Area - A Cointegration Approach," IMK Working Paper 06-2005, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
    769. Hinrichs, Nils & Kolbe, Jens & Werwatz, Axel, 2020. "AVM and high dimensional data: Do ridge, the lasso or the elastic net provide an "automated" solution?," FORLand Working Papers 22 (2020), Humboldt University Berlin, DFG Research Unit 2569 FORLand "Agricultural Land Markets – Efficiency and Regulation".
    770. Fernando Moraes & Rodrigo De-Losso, 2020. "Risk Factors’ CPDAG Roots and the Cross-Section of Expected Returns," Working Papers, Department of Economics 2020_18, University of São Paulo (FEA-USP).
    771. Isengildina-Massa, Olga & Sharp, Julia L., 2013. "Interval Forecast Comparison," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150791, Agricultural and Applied Economics Association.
    772. Javier García-Cicco & Roque Montero, 2011. "Modeling Copper Price: A Regime-Switching Approach," Working Papers Central Bank of Chile 613, Central Bank of Chile.
    773. Claire Giordano & Marco Marinucci & Andrea Silvestrini, 2021. "Forecasting corporate capital accumulation in Italy: the role of survey-based information," Questioni di Economia e Finanza (Occasional Papers) 596, Bank of Italy, Economic Research and International Relations Area.
    774. González-Astudillo, Manuel & Baquero, Daniel, 2019. "A nowcasting model for Ecuador: Implementing a time-varying mean output growth," Economic Modelling, Elsevier, vol. 82(C), pages 250-263.
    775. Cem Çakmakli & Hamza Dem I˙rcani & Sumru Altug, 2021. "Modelling of Economic and Financial Conditions for Real‐Time Prediction of Recessions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(3), pages 663-685, June.
    776. Lamichhane, Sabhyata & Mei, Bin & Siry, Jacek, 2023. "Forecasting pine sawtimber stumpage prices: A comparison between a time series hybrid model and an artificial neural network," Forest Policy and Economics, Elsevier, vol. 154(C).
    777. Marcos Álvarez-Díaz, 2020. "Is it possible to accurately forecast the evolution of Brent crude oil prices? An answer based on parametric and nonparametric forecasting methods," Empirical Economics, Springer, vol. 59(3), pages 1285-1305, September.
    778. Johannes Mayr & Dirk Ulbricht, 2007. "Log versus level in VAR forecasting: 16 Million empirical answers - expect the unexpected," ifo Working Paper Series 42, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    779. Ekşi Ozan & Taş Bedri Kamil Onur & Orman Cüneyt, 2017. "Has the forecasting performance of the Federal Reserve’s Greenbooks changed over time?," The B.E. Journal of Macroeconomics, De Gruyter, vol. 17(2), pages 1-25, June.
    780. Clements, Michael P. & Harvey, David I., 2011. "Combining probability forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 208-223.
    781. Melisso Boschi & Alessandro Girardi, 2005. "Euro Area inflation: long-run determinants and short-run dynamics," ISAE Working Papers 60, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
    782. Florackis, Chris & Giorgioni, Gianluigi & Kostakis, Alexandros & Milas, Costas, 2014. "On stock market illiquidity and real-time GDP growth," Journal of International Money and Finance, Elsevier, vol. 44(C), pages 210-229.
    783. Matthieu LEMOINE & Odile CHAGNY, 2005. "Estimating the potential output of the euro area with a semi-structural multivariate Hodrick-Prescott filter," Computing in Economics and Finance 2005 344, Society for Computational Economics.
    784. Andrey Zubarev & Daniil Lomonosov & Konstantin Rybak, 2022. "Estimation of the Impact of Global Shocks on the Russian Economy and GDP Nowcasting Using a Factor Model," Russian Journal of Money and Finance, Bank of Russia, vol. 81(2), pages 49-78, June.
    785. Abel Rodríguez Tirado & Marcelo Delajara & Federico Hernández Álvarez, 2016. "Nowcasting Mexico’s Short-Term GDP Growth in Real-Time: A Factor Model versus Professional Forecasters," Economía Journal, The Latin American and Caribbean Economic Association - LACEA, vol. 0(Fall 2016), pages 167-182, October.
    786. Håvard Hungnes, 2018. "Encompassing tests for evaluating multi-step system forecasts invariant to linear transformations," Discussion Papers 871, Statistics Norway, Research Department.
    787. Hans-Eggert Reimers, 2003. "Does Money Include Information for Output in the Euro Area?," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 139(II), pages 231-252, June.
    788. Heather L. R. Tierney, 2019. "Forecasting with the Nonparametric Exclusion-from-Core Inflation Persistence Model Using Real-Time Data," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 25(1), pages 39-63, February.
    789. Donya Rahmani & Saeed Heravi & Hossein Hassani & Mansi Ghodsi, 2016. "Forecasting time series with structural breaks with Singular Spectrum Analysis, using a general form of recurrent formula," Papers 1605.02188, arXiv.org.
    790. Marcos Álvarez-Díaz & Manuel González-Gómez & María Soledad Otero-Giráldez, 2018. "Forecasting International Tourism Demand Using a Non-Linear Autoregressive Neural Network and Genetic Programming," Forecasting, MDPI, vol. 1(1), pages 1-17, September.
    791. Tseng Tseng-Chan & Chung Huimin & Huang Chin-Sheng, 2009. "Modeling Jump and Continuous Components in the Volatility of Oil Futures," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(3), pages 1-30, May.
    792. Weber, Anke, 2007. "Heterogeneous expectations, learning and European inflation dynamics," Discussion Paper Series 1: Economic Studies 2007,16, Deutsche Bundesbank.
    793. Knetsch, Thomas A., 2006. "Forecasting the price of crude oil via convenience yield predictions," Discussion Paper Series 1: Economic Studies 2006,12, Deutsche Bundesbank.
    794. Victor Bello Accioly & Beatriz Vaz de Melo Mendes, 2016. "Assessing the Impact of the Realized Range on the (E)GARCH Volatility: Evidence from Brazil," Brazilian Business Review, Fucape Business School, vol. 13(2), pages 1-26, March.
    795. Nataliia Ostapenko, 2022. "Do output gap estimates improve inflation forecasts in Slovakia?," Working and Discussion Papers WP 4/2022, Research Department, National Bank of Slovakia.
    796. Abounoori, Esmaiel & Elmi, Zahra (Mila) & Nademi, Younes, 2016. "Forecasting Tehran stock exchange volatility; Markov switching GARCH approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 445(C), pages 264-282.
    797. Hossein Hassani & Jan Coreman & Saeed Heravi & Joshy Easaw, 2018. "Forecasting Inflation Rate: Professional Against Academic, Which One is More Accurate," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 16(3), pages 631-646, September.
    798. Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87.
    799. Choi, Hwan-sik & Kiefer, Nicholas M., 2006. "Robust Model Selection in Dynamic Models with an Application to Comparing Predictive Accuracy," Working Papers 06-09, Cornell University, Center for Analytic Economics.
    800. Hassani, Hossein & Heravi, Saeed & Zhigljavsky, Anatoly, 2009. "Forecasting European industrial production with singular spectrum analysis," International Journal of Forecasting, Elsevier, vol. 25(1), pages 103-118.
    801. den Reijer, Ard H.J., 2011. "Regional and sectoral dynamics of the Dutch staffing labor cycle," Economic Modelling, Elsevier, vol. 28(4), pages 1826-1837, July.
    802. Costas Milas & Phil Rothman, 2005. "Multivariate STAR Unemployment Rate Forecasts," Econometrics 0502010, University Library of Munich, Germany.
    803. Cecilia Frale & Stefano Grassi & Massimiliano Marcellino & Gianluigi Mazzi & Tommaso Proietti, 2013. "EuroMInd-C: a Disaggregate Monthly Indicator of Economic Activity for the Euro Area and member countries," CEIS Research Paper 287, Tor Vergata University, CEIS, revised 01 Oct 2013.
    804. Konstantinidi, Eirini & Skiadopoulos, George & Tzagkaraki, Emilia, 2008. "Can the evolution of implied volatility be forecasted? Evidence from European and US implied volatility indices," Journal of Banking & Finance, Elsevier, vol. 32(11), pages 2401-2411, November.
    805. Tseng‐Chan Tseng & Hung‐Cheng Lai & Jih‐Kuang Chen, 2022. "Impacts of relatively rational and irrational investor sentiment on realized volatility," Asian Economic Journal, East Asian Economic Association, vol. 36(4), pages 458-478, December.
    806. Chan, Felix & Pauwels, Laurent L., 2018. "Some theoretical results on forecast combinations," International Journal of Forecasting, Elsevier, vol. 34(1), pages 64-74.
    807. Greg Tkacz & Carolyn A. Wilkins, 2006. "Linear and Threshold Forecasts of Output and Inflation with Stock and Housing Prices," Staff Working Papers 06-25, Bank of Canada.
    808. Sánchez, Marcelo, 2008. "Oil shocks and endogenous markups: results from an estimated euro area DSGE model," Working Paper Series 860, European Central Bank.
    809. Bonnier, Jean-Baptiste, 2022. "Forecasting crude oil volatility with exogenous predictors: As good as it GETS?," Energy Economics, Elsevier, vol. 111(C).
    810. E Pavlidis & I Paya & D Peel, 2009. "Forecasting the Real Exchange Rate using a Long Span of Data. A Rematch: Linear vs Nonlinear," Working Papers 601190, Lancaster University Management School, Economics Department.
    811. Dimitrios P. Louzis, 2019. "Steady‐state modeling and macroeconomic forecasting quality," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(2), pages 285-314, March.
    812. Jae‐Yun Jun & Victor Lebreton & Yves Rakotondratsimba, 2021. "Forecasting negative yield‐curve distributions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 367-386, April.
    813. Kurz-Kim, Jeong-Ryeol, 2018. "A note on the predictive power of survey data in nowcasting euro area GDP," Discussion Papers 10/2018, Deutsche Bundesbank.
    814. Zhang, Yagang & Zhang, Jinghui & Yu, Leyi & Pan, Zhiya & Feng, Changyou & Sun, Yiqian & Wang, Fei, 2022. "A short-term wind energy hybrid optimal prediction system with denoising and novel error correction technique," Energy, Elsevier, vol. 254(PC).
    815. Pami Dua & Rajiv Ranjan, 2011. "Modelling and Forecasting the Indian Re/US Dollar Exchange Rate," Working papers 197, Centre for Development Economics, Delhi School of Economics.
    816. Giovanni De Luca & Alfonso Carfora, 2014. "Predicting U.S. recessions through a combination of probability forecasts," Empirical Economics, Springer, vol. 46(1), pages 127-144, February.
    817. Mateusz Sumorek & Adam Idzkowski, 2023. "Time Series Forecasting for Energy Production in Stand-Alone and Tracking Photovoltaic Systems Based on Historical Measurement Data," Energies, MDPI, vol. 16(17), pages 1-23, September.
    818. Becker, Janis & Hollstein, Fabian & Prokopczuk, Marcel & Sibbertsen, Philipp, 2019. "The Memory of Beta Factors," Hannover Economic Papers (HEP) dp-661, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    819. Chapda Nana, Guy & Larue, Bruno, 2012. "Imposing Curvature Conditions on Flexible Functional Forms to GNP Functions," Working Papers 123308, University of Laval, Center for Research on the Economics of the Environment, Agri-food, Transports and Energy (CREATE).
    820. Julius Stakenas, 2015. "Forecasting Lithuanian Inflation," Bank of Lithuania Working Paper Series 17, Bank of Lithuania.
    821. Wink Junior, Marcos Vinício & Pereira, Pedro Luiz Valls, 2011. "Modeling and Forecasting of Realized Volatility: Evidence from Brazil," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 31(2), December.
    822. Dreger, Christian & Wolters, Jürgen, 2014. "Money demand and the role of monetary indicators in forecasting euro area inflation," International Journal of Forecasting, Elsevier, vol. 30(2), pages 303-312.
    823. António Rua, 2016. "A wavelet-based multivariate multiscale approach for forecasting," Working Papers w201612, Banco de Portugal, Economics and Research Department.
    824. Arim Jin & Dahan Lee & Jong-Bae Park & Jae Hyung Roh, 2023. "Day-Ahead Electricity Market Price Forecasting Considering the Components of the Electricity Market Price; Using Demand Decomposition, Fuel Cost, and the Kernel Density Estimation," Energies, MDPI, vol. 16(7), pages 1-19, April.
    825. Martin Gonzalez-Rozada & Martin sola & Constantino Hevia & Fabio Spagnolo, 2012. "Estimating and Forecasting the Yield Curve Using a Markov Switching Dynamic Nelson and Siegel Model," Department of Economics Working Papers 2012-07, Universidad Torcuato Di Tella.
    826. Jeffrey S. Racine & Christopher F. Parmeter, 2012. "Data-Driven Model Evaluation: A Test for Revealed Performance," Department of Economics Working Papers 2012-13, McMaster University.
    827. Hollstein, Fabian & Prokopczuk, Marcel & Wese Simen, Chardin, 2017. "How to Estimate Beta?," Hannover Economic Papers (HEP) dp-617, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    828. Kertlly de Medeiros, Rennan & da Nóbrega Besarria, Cássio & Pitta de Jesus, Diego & Phillipe de Albuquerquemello, Vinicius, 2022. "Forecasting oil prices: New approaches," Energy, Elsevier, vol. 238(PC).
    829. Xiaojie Xu, 2018. "Cointegration and price discovery in US corn cash and futures markets," Empirical Economics, Springer, vol. 55(4), pages 1889-1923, December.
    830. Hess, Dieter & Orbe, Sebastian, 2011. "Irrationality or efficiency of macroeconomic survey forecasts? Implications from the anchoring bias test," CFR Working Papers 11-13, University of Cologne, Centre for Financial Research (CFR).
    831. Luis Ceballos S. & Mario González F., 2012. "Indicador de Condiciones Económicas," Notas de Investigación Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 15(1), pages 105-117, April.
    832. Pawel M. Krolikowski & Kurt G. Lunsford, 2024. "Advance layoff notices and aggregate job loss," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(3), pages 462-480, April.
    833. Ekaterina Abramova & Derek Bunn, 2020. "Forecasting the Intra-Day Spread Densities of Electricity Prices," Papers 2002.10566, arXiv.org.
    834. Hamid Baghestani, 2009. "A Comparison of U.S. Housing Starts Forecasts," Economics Bulletin, AccessEcon, vol. 29(4), pages 2525-2530.
    835. Hollstein, Fabian & Prokopczuk, Marcel & Wese Simen, Chardin, 2019. "Estimating beta: Forecast adjustments and the impact of stock characteristics for a broad cross-section," Journal of Financial Markets, Elsevier, vol. 44(C), pages 91-118.
    836. Vermeulen, Philip, 2014. "An evaluation of business survey indices for short-term forecasting: Balance method versus Carlson–Parkin method," International Journal of Forecasting, Elsevier, vol. 30(4), pages 882-897.
    837. Silva, Emmanuel Sirimal & Hassani, Hossein, 2022. "‘Modelling’ UK tourism demand using fashion retail sales," Annals of Tourism Research, Elsevier, vol. 95(C).
    838. Agnieszka Przybylska-Mazur, 2014. "Selected Tests Comparing the Accuracy of Inflation Rate Forecasts Constructed by Different Methods," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 15(2), pages 299-308, March.
    839. Rosario Dell'Aquila & Elvezio Ronchetti, 2004. "Robust tests of predictive accuracy," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(2), pages 161-184.
    840. Thomas C. Chiang & Zhuo Qiao & Wing-Keung Wong, 2010. "New evidence on the relation between return volatility and trading volume," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(5), pages 502-515.
    841. Wang, Zijun & Bessler, David A, 2002. "The Homogeneity Restriction and Forecasting Performance of VAR-Type Demand Systems: An Empirical Examination of US Meat Consumption," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 21(3), pages 193-206, April.
    842. Santino Del Fava & Rangan Gupta & Christian Pierdzioch & Lavinia Rognone, 2023. "Forecasting International Financial Stress: The Role of Climate Risks," Working Papers 202329, University of Pretoria, Department of Economics.
    843. Chang, Kuang-Liang, 2010. "House price dynamics, conditional higher-order moments, and density forecasts," Economic Modelling, Elsevier, vol. 27(5), pages 1029-1039, September.
    844. Laurent Ferrara & Thomas Raffinot, 2008. "A non-parametric method to nowcast the Euro Area IPI," Post-Print halshs-00275769, HAL.
    845. David Happersberger & Harald Lohre & Ingmar Nolte, 2020. "Estimating portfolio risk for tail risk protection strategies," European Financial Management, European Financial Management Association, vol. 26(4), pages 1107-1146, September.
    846. Wolfgang Nierhaus & Timo Wollmershäuser, 2016. "ifo Konjunkturumfragen und Konjunkturanalyse: Band II," ifo Forschungsberichte, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 72.
    847. Jawadi, Fredj & Namouri, Hela & Ftiti, Zied, 2018. "An analysis of the effect of investor sentiment in a heterogeneous switching transition model for G7 stock markets," Journal of Economic Dynamics and Control, Elsevier, vol. 91(C), pages 469-484.
    848. Jan Prüser & Florian Huber, 2024. "Nonlinearities in macroeconomic tail risk through the lens of big data quantile regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(2), pages 269-291, March.
    849. Zongwu Cai & Jiazi Chen & Linlin Liu, 2021. "Estimating Impact of Age Distribution on Bond Pricing: A Semiparametric Functional Data Analysis Approach," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202102, University of Kansas, Department of Economics, revised Jan 2021.
    850. Dick van Dijk & Philip Hans Franses & Michael P. Clements & Jeremy Smith, 2003. "On SETAR non-linearity and forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(5), pages 359-375.
    851. Aparicio, Diego & Bertolotto, Manuel I., 2020. "Forecasting inflation with online prices," International Journal of Forecasting, Elsevier, vol. 36(2), pages 232-247.
    852. Bernd Süssmuth, 2022. "The mutual predictability of Bitcoin and web search dynamics," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 435-454, April.
    853. Chuntian Cheng & Bin Luo & Shumin Miao & Xinyu Wu, 2016. "Mid-Term Electricity Market Clearing Price Forecasting with Sparse Data: A Case in Newly-Reformed Yunnan Electricity Market," Energies, MDPI, vol. 9(10), pages 1-22, October.
    854. Dean Croushore & Katherine Marsten, 2016. "Do GDP Forecasts Respond Efficiently to Changes in Interest Rates?," Working Papers 16-17, Federal Reserve Bank of Philadelphia.
    855. Afees A. Salisu & Ahamuefula E.Oghonna & Rangan Gupta & Oguzhan Cepni, 2024. "Energy Market Uncertainties and US State-Level Stock Market Volatility: A GARCH-MIDAS Approach," Working Papers 202409, University of Pretoria, Department of Economics.
    856. Wang, Zijun & Khan, M. Moosa, 2017. "Market states and the risk-return tradeoff," The Quarterly Review of Economics and Finance, Elsevier, vol. 65(C), pages 314-327.
    857. Bai, Yun & Li, Xixi & Yu, Hao & Jia, Suling, 2022. "Crude oil price forecasting incorporating news text," International Journal of Forecasting, Elsevier, vol. 38(1), pages 367-383.
    858. Harris, Richard D.F. & Yilmaz, Fatih, 2010. "Estimation of the conditional variance-covariance matrix of returns using the intraday range," International Journal of Forecasting, Elsevier, vol. 26(1), pages 180-194, January.
    859. Leopoldo Catania & Alessandra Luati & Pierluigi Vallarino, 2021. "Economic vulnerability is state dependent," CREATES Research Papers 2021-09, Department of Economics and Business Economics, Aarhus University.
    860. Olivier Biau & Hélène Erkel-Rousse & Nicolas Ferrari, 2006. "Réponses individuelles aux enquêtes de conjoncture et prévision de la production manufacturière," Économie et Statistique, Programme National Persée, vol. 395(1), pages 91-116.
    861. Helmut Herwartz & Konstantin A. Kholodilin, 2014. "Uncertainty of Macroeconomic Forecasters and the Prediction of Stock Market Bubbles," Discussion Papers of DIW Berlin 1405, DIW Berlin, German Institute for Economic Research.
    862. Sermpinis, Georgios & Stasinakis, Charalampos & Dunis, Christian, 2014. "Stochastic and genetic neural network combinations in trading and hybrid time-varying leverage effects," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 30(C), pages 21-54.
    863. Wang, Zijun & Bessler, David A., 2004. "Forecasting performance of multivariate time series models with full and reduced rank: an empirical examination," International Journal of Forecasting, Elsevier, vol. 20(4), pages 683-695.
    864. Naser, Hanan, 2016. "Estimating and forecasting the real prices of crude oil: A data rich model using a dynamic model averaging (DMA) approach," Energy Economics, Elsevier, vol. 56(C), pages 75-87.
    865. Orhan Altuğ Karabiber & George Xydis, 2019. "Electricity Price Forecasting in the Danish Day-Ahead Market Using the TBATS, ANN and ARIMA Methods," Energies, MDPI, vol. 12(5), pages 1-29, March.
    866. Stéphanie Guichard & Elena Rusticelli, 2011. "A Dynamic Factor Model for World Trade Growth," OECD Economics Department Working Papers 874, OECD Publishing.
    867. Sanders, Dwight R. & Manfredo, Mark R., 2003. "USDA Livestock Price Forecasts: A Comprehensive Evaluation," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 28(2), pages 1-19, August.
    868. Tom Stark, 2000. "Does current-quarter information improve quarterly forecasts for the U.S. economy?," Working Papers 00-2, Federal Reserve Bank of Philadelphia.
    869. De Pace, Pierangelo & Weber, Kyle D., 2016. "The time-varying leading properties of the high yield spread in the United States," International Journal of Forecasting, Elsevier, vol. 32(1), pages 203-230.
    870. Lu, Hongfang & Ma, Xin & Ma, Minda, 2021. "A hybrid multi-objective optimizer-based model for daily electricity demand prediction considering COVID-19," Energy, Elsevier, vol. 219(C).
    871. Manfredo, Mark R. & Sanders, Dwight R., 2004. "Forecast Encompassing And Futures Market Efficiency: The Case Of Milk Futures," 2004 Annual meeting, August 1-4, Denver, CO 20267, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    872. Morita, Hiroshi, 2022. "Forecasting GDP growth using stock returns in Japan: A factor-augmented MIDAS approach," Discussion paper series HIAS-E-118, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    873. Hamid Baghestani, 2009. "Survey evidence on forecast accuracy of U.S. term spreads," Review of Financial Economics, John Wiley & Sons, vol. 18(3), pages 156-162, August.
    874. Garratt, Anthony & Petrella, Ivan & Zhang, Yunyi, 2022. "Asymmetry and Interdependence when Evaluating U.S. Energy Information Agency Forecasts," MPRA Paper 114325, University Library of Munich, Germany.
    875. Herrera, Gabriel Paes & Constantino, Michel & Su, Jen-Je & Naranpanawa, Athula, 2023. "The use of ICTs and income distribution in Brazil: A machine learning explanation using SHAP values," Telecommunications Policy, Elsevier, vol. 47(8).
    876. Jakub Rybacki, 2019. "Does Forward Guidance Matter in Small Open Economies? Examples from Europe," Econometric Research in Finance, SGH Warsaw School of Economics, Collegium of Economic Analysis, vol. 4(1), pages 1-26, June.
    877. Dbouk, Wassim & Jamali, Ibrahim, 2018. "Predicting daily oil prices: Linear and non-linear models," Research in International Business and Finance, Elsevier, vol. 46(C), pages 149-165.
    878. Ekaterina Abramova & Derek Bunn, 2019. "Estimating Dynamic Conditional Spread Densities to Optimise Daily Storage Trading of Electricity," Papers 1903.06668, arXiv.org.
    879. Wang, Yudong & Ma, Feng & Wei, Yu & Wu, Chongfeng, 2016. "Forecasting realized volatility in a changing world: A dynamic model averaging approach," Journal of Banking & Finance, Elsevier, vol. 64(C), pages 136-149.
    880. Benner, Joachim & Meier, Carsten-Patrick, 2003. "Prognosegüte alternativer Frühindikatoren für die Konjunktur in Deutschland," Kiel Working Papers 1139, Kiel Institute for the World Economy (IfW Kiel).
    881. Nolte, Ingmar & Pohlmeier, Winfried, 2007. "Using forecasts of forecasters to forecast," International Journal of Forecasting, Elsevier, vol. 23(1), pages 15-28.
    882. Konstantin S. Rybak, 2023. "Evaluating the Role of Global Factors in GDP Nowcasting [Анализ Важности Глобальных Факторов Для Наукастинга Ввп]," Russian Economic Development, Gaidar Institute for Economic Policy, issue 12, pages 18-23, December.
    883. Guzman, Giselle C., 2011. "The case for higher frequency inflation expectations," MPRA Paper 36656, University Library of Munich, Germany.
    884. Jing-Zhi Huang & Zhan Shi, 2023. "Machine-Learning-Based Return Predictors and the Spanning Controversy in Macro-Finance," Management Science, INFORMS, vol. 69(3), pages 1780-1804, March.
    885. Tom Stark, 2014. "Real-time performance of GDPplus and alternative model-based measures of GDP: 2005—2014," Research Rap Special Report, Federal Reserve Bank of Philadelphia, issue Nov.
    886. G. Kontogeorgos & K. Lambrias, 2022. "Evaluating the Eurosystem/ECB staff macroeconomic projections: The first 20 years," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 213-229, March.
    887. Sergio Iván Prada & Julio C. Alonso & Julián Fernández, 2019. "Exchange rate pass-through into consumer healthcare prices in Colombia," Revista Cuadernos de Economia, Universidad Nacional de Colombia, FCE, CID, vol. 38(77), pages 523-550, July.
    888. Ray Barrell, 1999. "Employment Security and European Labour Demand: A Panel Study Across 16 Industries," National Institute of Economic and Social Research (NIESR) Discussion Papers 148, National Institute of Economic and Social Research.
    889. Claveria, Oscar & Monte, Enric & Torra, Salvador, 2020. "Economic forecasting with evolved confidence indicators," Economic Modelling, Elsevier, vol. 93(C), pages 576-585.
    890. Xiaojie Xu & Yun Zhang, 2022. "Forecasting the total market value of a shares traded in the Shenzhen stock exchange via the neural network," Economics Bulletin, AccessEcon, vol. 42(3), pages 1266-1279.
    891. Elizaveta Golovanova & Andrey Zubarev, 2021. "Forecasting Aggregate Retail Sales with Google Trends," Russian Journal of Money and Finance, Bank of Russia, vol. 80(4), pages 50-73, December.
    892. Oscar Claveria & Enric Monte & Salvador Torra, 2021. ""Nowcasting and forecasting GDP growth with machine-learning sentiment indicators"," IREA Working Papers 202103, University of Barcelona, Research Institute of Applied Economics, revised Feb 2021.
    893. Hinterlang, Natascha, 2019. "Predicting Monetary Policy Using Artificial Neural Networks," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203503, Verein für Socialpolitik / German Economic Association.
    894. Sollis, Robert, 2008. "U.S. dollar real exchange rates: Nonlinearity revisited," Journal of International Money and Finance, Elsevier, vol. 27(4), pages 516-528, June.
    895. Loïc Maréchal, 2021. "Do economic variables forecast commodity futures volatility?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(11), pages 1735-1774, November.
    896. Troster, Victor & Bouri, Elie & Roubaud, David, 2019. "A quantile regression analysis of flights-to-safety with implied volatilities," Resources Policy, Elsevier, vol. 62(C), pages 482-495.
    897. Giuseppe Parigi & Roberto Golinelli, 2007. "The use of monthly indicators to forecast quarterly GDP in the short run: an application to the G7 countries," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(2), pages 77-94.
    898. Jordi Maas, 2014. "Forecasting inflation using time-varying Bayesian model averaging," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 68(3), pages 149-182, August.
    899. Nonejad, Nima, 2020. "Crude oil price volatility and equity return predictability: A comparative out-of-sample study," International Review of Financial Analysis, Elsevier, vol. 71(C).
    900. Vogt Gerit, 2007. "Analyse der Prognoseeigenschaften von ifo-Konjunkturindikatoren unter Echtzeitbedingungen / The Forecasting Performance of ifo-indicators Under Real-time Conditions," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 227(1), pages 87-101, February.
    901. Christophe Boucher & Bertrand Maillet, 2012. "Prévoir sans persistance," Post-Print halshs-00662771, HAL.
    902. Clements, Michael P. & Galvao, Ana Beatriz, 2004. "A comparison of tests of nonlinear cointegration with application to the predictability of US interest rates using the term structure," International Journal of Forecasting, Elsevier, vol. 20(2), pages 219-236.
    903. Chen, Xiaoshan & MacDonald, Ronald, 2015. "Measuring the dollar–euro permanent equilibrium exchange rate using the unobserved components model," Journal of International Money and Finance, Elsevier, vol. 53(C), pages 20-35.
    904. Taufiq Choudhry & Hao Wu, 2009. "Forecasting the weekly time-varying beta of UK firms: GARCH models vs. Kalman filter method," The European Journal of Finance, Taylor & Francis Journals, vol. 15(4), pages 437-444.
    905. Kappler, Marcus, 2007. "Projecting the Medium-Term: Outcomes and Errors for GDP Growth," ZEW Discussion Papers 07-068, ZEW - Leibniz Centre for European Economic Research.
    906. McCracken,M.W. & West,K.D., 2001. "Inference about predictive ability," Working papers 14, Wisconsin Madison - Social Systems.
    907. Herrera, Gabriel Paes & Constantino, Michel & Su, Jen-Je & Naranpanawa, Athula, 2022. "Renewable energy stocks forecast using Twitter investor sentiment and deep learning," Energy Economics, Elsevier, vol. 114(C).

Chapters

  1. Michael P. Clements & David I. Harvey, 2009. "Forecast Combination and Encompassing," Palgrave Macmillan Books, in: Terence C. Mills & Kerry Patterson (ed.), Palgrave Handbook of Econometrics, chapter 4, pages 169-198, Palgrave Macmillan.

    Cited by:

    1. Narayan Kundan Kishor, 2021. "Forecasting real‐time economic activity using house prices and credit conditions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(2), pages 213-227, March.
    2. David I. Harvey & Stephen J. Leybourne & Emily J. Whitehouse, 2017. "Forecast evaluation tests and negative long-run variance estimates in small samples," Discussion Papers 17/03, University of Nottingham, Granger Centre for Time Series Econometrics.
    3. McMillan, David G., 2019. "Stock return predictability: Using the cyclical component of the price ratio," Research in International Business and Finance, Elsevier, vol. 48(C), pages 228-242.
    4. Timo Dimitriadis & Xiaochun Liu & Julie Schnaitmann, 2020. "Encompassing Tests for Value at Risk and Expected Shortfall Multi-Step Forecasts based on Inference on the Boundary," Papers 2009.07341, arXiv.org.
    5. Bordignon, Silvano & Bunn, Derek W. & Lisi, Francesco & Nan, Fany, 2013. "Combining day-ahead forecasts for British electricity prices," Energy Economics, Elsevier, vol. 35(C), pages 88-103.
    6. Hyun Hak Kim, 2013. "Forecasting Macroeconomic Variables Using Data Dimension Reduction Methods: The Case of Korea," Working Papers 2013-26, Economic Research Institute, Bank of Korea.
    7. Ulrich Gunter, 2021. "Improving Hotel Room Demand Forecasts for Vienna across Hotel Classes and Forecast Horizons: Single Models and Combination Techniques Based on Encompassing Tests," Forecasting, MDPI, vol. 3(4), pages 1-36, November.
    8. Carlos Fonseca Marinheiro, 2010. "Fiscal sustainability and the accuracy of macroeconomic forecasts: do supranational forecasts rather than government forecasts make a difference?," GEMF Working Papers 2010-07, GEMF, Faculty of Economics, University of Coimbra.
    9. Clements, Michael P. & Harvey, David I., 2011. "Combining probability forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 208-223.
    10. Fuentes, Julieta & Poncela, Pilar & Rodríguez, Julio, 2014. "Selecting and combining experts from survey forecasts," DES - Working Papers. Statistics and Econometrics. WS ws140905, Universidad Carlos III de Madrid. Departamento de Estadística.
    11. Timo Dimitriadis & Julie Schnaitmann, 2019. "Forecast Encompassing Tests for the Expected Shortfall," Papers 1908.04569, arXiv.org, revised Aug 2020.
    12. David G. McMillan, 2021. "Predicting GDP growth with stock and bond markets: Do they contain different information?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3651-3675, July.

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