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Graham Elliott

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.

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Cavanagh, Christopher L. & Elliott, Graham & Stock, James H., 1995. "Inference in Models with Nearly Integrated Regressors," Econometric Theory, Cambridge University Press, vol. 11(5), pages 1131-1147, October.

    Mentioned in:

    1. Some thoughts on the Reinhart and Rogoff debate
      by Gray in Pseudo-true News on 2013-04-24 10:06:23
  2. Elliott, Graham & Stock, James H., 1994. "Inference in Time Series Regression When the Order of Integration of a Regressor is Unknown," Econometric Theory, Cambridge University Press, vol. 10(3-4), pages 672-700, August.

    Mentioned in:

    1. Some thoughts on the Reinhart and Rogoff debate
      by Gray in Pseudo-true News on 2013-04-24 10:06:23

RePEc Biblio mentions

As found on the RePEc Biblio, the curated bibliography of Economics:
  1. G. Elliott & C. Granger & A. Timmermann (ed.), 2006. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 1, number 1.

    Mentioned in:

    1. > Econometrics > Forecasting
  2. G. Elliott & C. Granger & A. Timmermann (ed.), 2013. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 2, number 2.

    Mentioned in:

    1. > Econometrics > Forecasting

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-836, July.

    Mentioned in:

    1. ADF-GLS test in Wikipedia (English)

Working papers

  1. Graham Elliott & Nikolay Kudrin & Kaspar Wuthrich, 2019. "Detecting p-hacking," Papers 1906.06711, arXiv.org, revised May 2021.

    Cited by:

    1. Guido W. Imbens, 2021. "Statistical Significance, p-Values, and the Reporting of Uncertainty," Journal of Economic Perspectives, American Economic Association, vol. 35(3), pages 157-174, Summer.
    2. Josef Bajzik & Jan Janku & Simona Malovana & Klara Moravcova & Ngoc Anh Ngo, 2023. "Monetary Policy Has a Long-Lasting Impact on Credit: Evidence from 91 VAR Studies," Working Papers 2023/19, Czech National Bank.
    3. Simona Malovana & Martin Hodula & Zuzana Gric & Josef Bajzik, 2022. "Borrower-Based Macroprudential Measures and Credit Growth: How Biased is the Existing Literature?," Working Papers 2022/8, Czech National Bank.

  2. Timmermann, Allan & Elliott, Graham, 2016. "Forecasting in Economics and Finance," CEPR Discussion Papers 11354, C.E.P.R. Discussion Papers.

    Cited by:

    1. Andrii Babii & Xi Chen & Eric Ghysels & Rohit Kumar, 2020. "Binary Choice with Asymmetric Loss in a Data-Rich Environment: Theory and an Application to Racial Justice," Papers 2010.08463, arXiv.org, revised Nov 2021.
    2. Carstensen, Kai & Bachmann, Rüdiger & Schneider, Martin & Lautenbacher, Stefan, 2018. "Uncertainty is Change," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181572, Verein für Socialpolitik / German Economic Association.
    3. Anwen Yin, 2022. "Does the kitchen‐sink model work forecasting the equity premium?," International Review of Finance, International Review of Finance Ltd., vol. 22(1), pages 223-247, March.
    4. David I. Harvey & Stephen J. Leybourne & Yang Zu, 2024. "Tests for equal forecast accuracy under heteroskedasticity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(5), pages 850-869, August.
    5. Gibson, Heather D. & Hall, Stephen G. & Tavlas, George S., 2020. "Nonlinear forecast combinations: An example using euro-area real GDP growth," Journal of Economic Behavior & Organization, Elsevier, vol. 180(C), pages 579-589.
    6. Timo Dimitriadis & Andrew J. Patton & Patrick W. Schmidt, 2019. "Testing Forecast Rationality for Measures of Central Tendency," Papers 1910.12545, arXiv.org, revised Jul 2024.
    7. Qiu, Yue & Zheng, Yuchen, 2023. "Improving box office projections through sentiment analysis: Insights from regularization-based forecast combinations," Economic Modelling, Elsevier, vol. 125(C).
    8. Giovannelli, Alessandro & Massacci, Daniele & Soccorsi, Stefano, 2021. "Forecasting stock returns with large dimensional factor models," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 252-269.
    9. Boriss Siliverstovs & Daniel S. Wochner, 2021. "State‐dependent evaluation of predictive ability," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 547-574, April.
    10. Alexander, Carol & Han, Yang & Meng, Xiaochun, 2023. "Static and dynamic models for multivariate distribution forecasts: Proper scoring rule tests of factor-quantile versus multivariate GARCH models," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1078-1096.
    11. Hambuckers, J. & Ulm, M., 2023. "On the role of interest rate differentials in the dynamic asymmetry of exchange rates," Economic Modelling, Elsevier, vol. 129(C).
    12. , 2019. "The Contribution of Jump Signs and Activity to Forecasting Stock Price Volatility," Working Papers 1902, Federal Reserve Bank of Dallas, revised 17 Dec 2022.
    13. David A. Mascio & Frank J. Fabozzi & J. Kenton Zumwalt, 2021. "Market timing using combined forecasts and machine learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 1-16, January.
    14. Newell, Richard G. & Prest, Brian C. & Sexton, Steven, 2020. "The GDP Temperature Relationship: Implications for Climate Change Damages," RFF Working Paper Series 18-17, Resources for the Future.
    15. Elliot Beck & Damian Kozbur & Michael Wolf, 2023. "Hedging Forecast Combinations With an Application to the Random Forest," Papers 2308.15384, arXiv.org, revised Aug 2023.
    16. Lima, Luiz Renato & Meng, Fanning & Godeiro, Lucas, 2020. "Quantile forecasting with mixed-frequency data," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1149-1162.
    17. Yi-Ting Chen & Chu-An Liu, 2021. "Model Averaging for Asymptotically Optimal Combined Forecasts," IEAS Working Paper : academic research 21-A002, Institute of Economics, Academia Sinica, Taipei, Taiwan.
    18. Joseph Agyapong, 2021. "Application of Taylor Rule Fundamentals in Forecasting Exchange Rates," Economies, MDPI, vol. 9(2), pages 1-27, June.
    19. Sun, Yuying & Hong, Yongmiao & Wang, Shouyang & Zhang, Xinyu, 2023. "Penalized time-varying model averaging," Journal of Econometrics, Elsevier, vol. 235(2), pages 1355-1377.
    20. Xing, Li-Min & Zhang, Yue-Jun, 2022. "Forecasting crude oil prices with shrinkage methods: Can nonconvex penalty and Huber loss help?," Energy Economics, Elsevier, vol. 110(C).
    21. Gloria Gonzalez-Rivera & Vladimir Rodriguez-Caballero & Esther Ruiz, 2023. "Expecting the unexpected: Stressed scenarios for economic growth," Working Papers 202314, University of California at Riverside, Department of Economics.
    22. Hounyo, Ulrich & Lahiri, Kajal, 2023. "Estimating the variance of a combined forecast: Bootstrap-based approach," Journal of Econometrics, Elsevier, vol. 232(2), pages 445-468.
    23. Alessandro Casini, 2018. "Tests for Forecast Instability and Forecast Failure under a Continuous Record Asymptotic Framework," Papers 1803.10883, arXiv.org, revised Dec 2018.
    24. Rahul Deb & Mallesh M. Pai & Maher Said, 2017. "Evaluating Strategic Forecasters," Working Papers 17-02, New York University, Leonard N. Stern School of Business, Department of Economics.
    25. Francis X. Diebold & Minchul Shin & Boyuan Zhang, 2021. "On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates," Working Papers 21-06, Federal Reserve Bank of Philadelphia.
    26. Rebonato, Riccardo & Ronzani, Riccardo, 2021. "Is convexity efficiently priced? Evidence from international swap markets," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 392-413.
    27. Jiun-Hua Su, 2019. "Model Selection in Utility-Maximizing Binary Prediction," Papers 1903.00716, arXiv.org, revised Jul 2020.
    28. Algieri, Bernardina & Iania, Leonardo & Leccadito, Arturo & Meloni, Giulia, 2024. "Message in a bottle: Forecasting wine prices," Journal of Wine Economics, Cambridge University Press, vol. 19(1), pages 64-91, February.
    29. Graziano Moramarco, 2021. "Financial-cycle ratios and medium-term predictions of GDP: Evidence from the United States," Papers 2111.00822, arXiv.org, revised Jan 2024.
    30. 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.
    31. Andrii Babii & Eric Ghysels & Jonas Striaukas, 2023. "Econometrics of Machine Learning Methods in Economic Forecasting," Papers 2308.10993, arXiv.org.
    32. Marcin Dec, 2021. "From point through density valuation to individual risk assessment in the discounted cash flows method," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5621-5635, October.
    33. Bennedsen, Mikkel & Hillebrand, Eric & Koopman, Siem Jan, 2021. "Modeling, forecasting, and nowcasting U.S. CO2 emissions using many macroeconomic predictors," Energy Economics, Elsevier, vol. 96(C).
    34. Goodell, John W. & Kumar, Satish & Lim, Weng Marc & Pattnaik, Debidutta, 2021. "Artificial intelligence and machine learning in finance: Identifying foundations, themes, and research clusters from bibliometric analysis," Journal of Behavioral and Experimental Finance, Elsevier, vol. 32(C).
    35. Yin, Anwen, 2020. "Equity premium prediction and optimal portfolio decision with Bagging," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    36. Ari Hyytinen & Petri Rouvinen & Mika Pajarinen & Joosua Virtanen, 2023. "Ex Ante Predictability of Rapid Growth: A Design Science Approach," Entrepreneurship Theory and Practice, , vol. 47(6), pages 2465-2493, November.
    37. Dewangan, Chaman Lal & Singh, S.N. & Chakrabarti, S., 2020. "Combining forecasts of day-ahead solar power," Energy, Elsevier, vol. 202(C).
    38. Rui Fan & Stephen J. Taylor & Matteo Sandri, 2018. "Density forecast comparisons for stock prices, obtained from high‐frequency returns and daily option prices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(1), pages 83-103, January.
    39. Anna Borucka, 2023. "Seasonal Methods of Demand Forecasting in the Supply Chain as Support for the Company’s Sustainable Growth," Sustainability, MDPI, vol. 15(9), pages 1-21, April.
    40. Timothy Christensen & Hyungsik Roger Moon & Frank Schorfheide, 2020. "Robust Forecasting," PIER Working Paper Archive 20-038, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
      • Timothy Christensen & Hyungsik Roger Moon & Frank Schorfheide, 2020. "Robust Forecasting," Papers 2011.03153, arXiv.org, revised Dec 2020.
    41. Li Chen & Jiti Gao & Farshid Vahid, 2019. "Global Temperatures and Greenhouse Gases: A Common Features Approach," Monash Econometrics and Business Statistics Working Papers 23/19, Monash University, Department of Econometrics and Business Statistics.
    42. Lu, Xinjie & Ma, Feng & Xu, Jin & Zhang, Zehui, 2022. "Oil futures volatility predictability: New evidence based on machine learning models11All the authors contribute to the paper equally," International Review of Financial Analysis, Elsevier, vol. 83(C).
    43. Zhu, Yinchu & Timmermann, Allan, 2022. "Conditional rotation between forecasting models," Journal of Econometrics, Elsevier, vol. 231(2), pages 329-347.
    44. Timmermann, Allan & Zhu, Yinchu, 2021. "Conditional Rotation Between Forecasting Models," CEPR Discussion Papers 15917, C.E.P.R. Discussion Papers.
    45. 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.
    46. Dennis Kant & Andreas Pick & Jasper de Winter, 2022. "Nowcasting GDP using machine learning methods," Working Papers 754, DNB.
    47. Dungey, Mardi & Islam, Raisul & Volkov, Vladimir, 2019. "Crisis transmission: visualizing vulnerability," Working Papers 2019-07, University of Tasmania, Tasmanian School of Business and Economics.
    48. Hasumi, Ryo & Iiboshi, Hirokuni & Matsumae, Tatsuyoshi & Nakamura, Daisuke, 2019. "Does a financial accelerator improve forecasts during financial crises? Evidence from Japan with prediction-pooling methods," Journal of Asian Economics, Elsevier, vol. 60(C), pages 45-68.
    49. Islam, Raisul & Volkov, Vladimir, 2020. "Calm before the storm: an early warning approach before and during the COVID-19 crisis," Working Papers 2020-09, University of Tasmania, Tasmanian School of Business and Economics.
    50. Su, Jiun-Hua, 2021. "Model selection in utility-maximizing binary prediction," Journal of Econometrics, Elsevier, vol. 223(1), pages 96-124.
    51. Graziano Moramarco, 2021. "Regime-Switching Density Forecasts Using Economists' Scenarios," Papers 2110.13761, arXiv.org, revised Feb 2024.
    52. Marta Boczoń & Jean-François Richard, 2020. "Balanced Growth Approach to Tracking Recessions," Econometrics, MDPI, vol. 8(2), pages 1-35, April.
    53. Yu Jeffrey Hu & Jeroen Rombouts & Ines Wilms, 2023. "Fast Forecasting of Unstable Data Streams for On-Demand Service Platforms," Papers 2303.01887, arXiv.org, revised May 2024.
    54. Kieran Mc Morrow & Werner Roeger & Valerie Vandermeulen, 2017. "Evaluating Medium Term Forecasting Methods and their Implications for EU Output Gap Calculations," European Economy - Discussion Papers 070, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    55. Jeroen Rombouts & Marie Ternes & Ines Wilms, 2024. "Cross-Temporal Forecast Reconciliation at Digital Platforms with Machine Learning," Papers 2402.09033, arXiv.org, revised May 2024.
    56. Niu, Zibo & Wang, Chenlu & Zhang, Hongwei, 2023. "Forecasting stock market volatility with various geopolitical risks categories: New evidence from machine learning models," International Review of Financial Analysis, Elsevier, vol. 89(C).
    57. Jack Fosten & Daniel Gutknecht & Marc-Oliver Pohle, 2023. "Testing Quantile Forecast Optimality," Papers 2302.02747, arXiv.org, revised Oct 2023.
    58. Qin Zhang & He Ni & Hao Xu, 2023. "Forecasting models for the Chinese macroeconomy in a data‐rich environment: Evidence from large dimensional approximate factor models with mixed‐frequency data," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(1), pages 719-767, March.
    59. Zhang, Qin & Ni, He & Xu, Hao, 2023. "Nowcasting Chinese GDP in a data-rich environment: Lessons from machine learning algorithms," Economic Modelling, Elsevier, vol. 122(C).
    60. 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.
    61. Zhang, Hongwei & Zhao, Xinyi & Gao, Wang & Niu, Zibo, 2023. "The role of higher moments in predicting China's oil futures volatility: Evidence from machine learning models," Journal of Commodity Markets, Elsevier, vol. 32(C).
    62. Zhou, Weilun & Gao, Jiti & Harris, David & Kew, Hsein, 2024. "Semi-parametric single-index predictive regression models with cointegrated regressors," Journal of Econometrics, Elsevier, vol. 238(1).
    63. 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.
    64. Li, Jiang-Cheng & Leng, Na & Zhong, Guang-Yan & Wei, Yu & Peng, Jia-Sheng, 2020. "Safe marginal time of crude oil price via escape problem of econophysics," Chaos, Solitons & Fractals, Elsevier, vol. 133(C).
    65. Kothari, Pratik & O’Doherty, Michael S., 2023. "Job postings and aggregate stock returns," Journal of Financial Markets, Elsevier, vol. 64(C).
    66. Procasky, William J. & Yin, Anwen, 2023. "The impact of COVID-19 on the relative market efficiency and forecasting ability of credit derivative and equity markets," International Review of Financial Analysis, Elsevier, vol. 90(C).
    67. Kuangyu Wen, 2023. "A semiparametric spatio‐temporal model of crop yield trend and its implication to insurance rating," Agricultural Economics, International Association of Agricultural Economists, vol. 54(5), pages 662-673, September.
    68. Dichtl, Hubert & Drobetz, Wolfgang & Neuhierl, Andreas & Wendt, Viktoria-Sophie, 2021. "Data snooping in equity premium prediction," International Journal of Forecasting, Elsevier, vol. 37(1), pages 72-94.
    69. Kaiji Motegi & Xiaojing Cai & Shigeyuki Hamori & Haifeng Xu, 2020. "Moving average threshold heterogeneous autoregressive (MAT‐HAR) models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1035-1042, November.
    70. Adalberto Ospino Castro & Carlos Robles-Algar n & Rafael Pe a Gallardo, 2019. "Analysis of Energy Management and Financial Planning in the Implementation of PV Systems," International Journal of Energy Economics and Policy, Econjournals, vol. 9(4), pages 1-11.
    71. Anwen Yin, 2021. "Forecasting the Market Equity Premium: Does Nonlinearity Matter?," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 13(5), pages 1-9, May.
    72. Iania, Leonardo & Algieri, Bernardina & Leccadito, Arturo, 2022. "Forecasting total energy’s CO2 emissions," LIDAM Discussion Papers LFIN 2022003, Université catholique de Louvain, Louvain Finance (LFIN).
    73. Bennedsen, Mikkel & Lunde, Asger & Shephard, Neil & Veraart, Almut E.D., 2023. "Inference and forecasting for continuous-time integer-valued trawl processes," Journal of Econometrics, Elsevier, vol. 236(2).
    74. James Lightwood & Steve Anderson & Stanton A Glantz, 2020. "Predictive validation and forecasts of short-term changes in healthcare expenditure associated with changes in smoking behavior in the United States," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-18, January.
    75. Juan R. Hernández, 2024. "Covered interest parity: a forecasting approach to estimate the neutral band," BIS Working Papers 1206, Bank for International Settlements.
    76. Marcin Dec, 2019. "From point through density valuation to individual risk assessment in the discounted cash flows method," GRAPE Working Papers 35, GRAPE Group for Research in Applied Economics.
    77. Katarzyna Maciejowska & Bartosz Uniejewski & Rafa{l} Weron, 2022. "Forecasting Electricity Prices," Papers 2204.11735, arXiv.org.
    78. Arai, Natsuki, 2020. "Investigating the inefficiency of the CBO’s budgetary projections," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1290-1300.
    79. William J. Procasky & Anwen Yin, 2022. "Forecasting high‐yield equity and CDS index returns: Does observed cross‐market informational flow have predictive power?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(8), pages 1466-1490, August.

  3. Elliott, Graham & Müller, Ulrich K & Watson, Mark W, 2015. "Nearly Optimal Tests When a Nuisance Parameter Is Present Under the Null Hypothesis," University of California at San Diego, Economics Working Paper Series qt5jp0q0fx, Department of Economics, UC San Diego.

    Cited by:

    1. Werker, Bas J.M. & Zhou, Bo, 2022. "Semiparametric testing with highly persistent predictors," Journal of Econometrics, Elsevier, vol. 227(2), pages 347-370.
    2. Philipp Ketz & Adam McCloskey, 2021. "Short and Simple Confidence Intervals when the Directions of Some Effects are Known," Papers 2109.08222, arXiv.org.
    3. Gregory Fletcher Cox, 2024. "A Simple and Adaptive Confidence Interval when Nuisance Parameters Satisfy an Inequality," Papers 2409.09962, arXiv.org.
    4. Ulrich K. Müller & Andriy Norets, 2016. "Coverage Inducing Priors in Nonstandard Inference Problems," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(515), pages 1233-1241, July.
    5. Timothy Armstrong & Patrick M. Kline & Liyang Sun, 2024. "Adapting to Misspecification," NBER Working Papers 32906, National Bureau of Economic Research, Inc.
    6. Cui, Liyuan & Hong, Yongmiao & Li, Yingxing, 2021. "Solving Euler equations via two-stage nonparametric penalized splines," Journal of Econometrics, Elsevier, vol. 222(2), pages 1024-1056.
    7. Christis Katsouris, 2023. "Structural Break Detection in Quantile Predictive Regression Models with Persistent Covariates," Papers 2302.05193, arXiv.org.
    8. Humberto Moreira & Marcelo Moreira, 2016. "Optimal two-sided tests for instrumental variables regression with heteroskedastic and autocorrelated errors," CeMMAP working papers 25/16, Institute for Fiscal Studies.
    9. Alessandro Casini & Pierre Perron, 2020. "Continuous Record Laplace-based Inference about the Break Date in Structural Change Models," Boston University - Department of Economics - Working Papers Series WP2020-014, Boston University - Department of Economics.
    10. 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.
    11. Karthik Muralidharan & Mauricio Romero & Kaspar Wüthrich, 2020. "Factorial Designs, Model Selection, and (Incorrect) Inference in Randomized Experiments," CESifo Working Paper Series 8137, CESifo.
    12. Ulrich K. Müller & Mark W. Watson, 2021. "Spatial Correlation Robust Inference," Working Papers 2021-61, Princeton University. Economics Department..
    13. Kaspar Wuthrich & Ying Zhu, 2019. "Omitted variable bias of Lasso-based inference methods: A finite sample analysis," Papers 1903.08704, arXiv.org, revised Sep 2021.
    14. Yuya Sasaki & Yulong Wang, 2020. "Testing Finite Moment Conditions for the Consistency and the Root-N Asymptotic Normality of the GMM and M Estimators," Papers 2006.02541, arXiv.org, revised Sep 2020.
    15. James A. Duffy & Jerome R. Simons, 2020. "Cointegration without Unit Roots," Papers 2002.08092, arXiv.org, revised Apr 2023.
    16. Tetsuya Kaji, 2019. "Theory of Weak Identification in Semiparametric Models," Papers 1908.10478, arXiv.org, revised Aug 2020.
    17. 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.
    18. Hiroaki Kaido & Yi Zhang, 2019. "Robust likelihood ratio tests for incomplete economic models," CeMMAP working papers CWP68/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    19. Ulrich K. Müller & Mark W. Watson, 2015. "Low-Frequency Econometrics," NBER Working Papers 21564, National Bureau of Economic Research, Inc.
    20. Tom Boot & Andreas Pick, 2017. "A near optimal test for structural breaks when forecasting under square error loss," Tinbergen Institute Discussion Papers 17-039/III, Tinbergen Institute.
    21. Abhimanyu Gupta & Myung Hwan Seo, 2019. "Robust Inference on Infinite and Growing Dimensional Time Series Regression," Papers 1911.08637, arXiv.org, revised Apr 2023.
    22. 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).
    23. Liyu Dou & Ulrich K. Müller, 2021. "Generalized Local‐to‐Unity Models," Econometrica, Econometric Society, vol. 89(4), pages 1825-1854, July.
    24. Torben G. Andersen & Rasmus T. Varneskov, 2018. "Consistent Inference for Predictive Regressions in Persistent VAR Economies," CREATES Research Papers 2018-09, Department of Economics and Business Economics, Aarhus University.
    25. Kleibergen, Frank, 2021. "Efficient size correct subset inference in homoskedastic linear instrumental variables regression," Journal of Econometrics, Elsevier, vol. 221(1), pages 78-96.
    26. 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.
    27. Paulo M.M. Rodrigues & Matei Demetrescu, 2019. "Testing for Episodic Predictability in Stock Returns," Working Papers w201906, Banco de Portugal, Economics and Research Department.
    28. Chenchuan (Mark) Li & Ulrich K. Müller, 2021. "Linear regression with many controls of limited explanatory power," Quantitative Economics, Econometric Society, vol. 12(2), pages 405-442, May.
    29. Ulrich K. Müller & Mark W. Watson, 2018. "Long†Run Covariability," Econometrica, Econometric Society, vol. 86(3), pages 775-804, May.
    30. Adam McCloskey, 2012. "Bonferroni-Based Size-Correction for Nonstandard Testing Problems," Working Papers 2012-16, Brown University, Department of Economics.
    31. Yulong Wang & Zhijie Xiao, 2020. "Estimation and Inference about Tail Features with Tail Censored Data," Boston College Working Papers in Economics 994, Boston College Department of Economics.
    32. Bas Werker & Bo Zhou, 2020. "Semiparametric Testing with Highly Persistent Predictors," Papers 2009.08291, arXiv.org.
    33. Moreira, Humberto & Moreira, Marcelo J., 2019. "Optimal two-sided tests for instrumental variables regression with heteroskedastic and autocorrelated errors," Journal of Econometrics, Elsevier, vol. 213(2), pages 398-433.
    34. Ulrich K. Müller, 2020. "A More Robust t-Test," Working Papers 2020-32, Princeton University. Economics Department..
    35. Werker, Bas J.M. & Zhou, B., 2022. "Semiparametric testing with highly persistent predictors," Other publications TiSEM 2974ce9c-97c1-44cd-9331-0, Tilburg University, School of Economics and Management.
    36. Pavlidis, Efthymios G. & Vasilopoulos, Kostas, 2020. "Speculative bubbles in segmented markets: Evidence from Chinese cross-listed stocks," Journal of International Money and Finance, Elsevier, vol. 109(C).
    37. Xu Cheng & Winston Wei Dou & Zhipeng Liao, 2022. "Macro‐Finance Decoupling: Robust Evaluations of Macro Asset Pricing Models," Econometrica, Econometric Society, vol. 90(2), pages 685-713, March.
    38. Alessandro Casini & Pierre Perron, 2018. "Continuous Record Asymptotics for Change-Points Models," Papers 1803.10881, arXiv.org, revised Nov 2021.
    39. 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.
    40. Müller, Ulrich K. & Wang, Yulong, 2019. "Nearly weighted risk minimal unbiased estimation," Journal of Econometrics, Elsevier, vol. 209(1), pages 18-34.
    41. Demetrescu, Matei & Georgiev, Iliyan & Rodrigues, Paulo MM & Taylor, AM Robert, 2022. "Extensions to IVX Methods of Inference for Return Predictability," Essex Finance Centre Working Papers 29779, University of Essex, Essex Business School.
    42. Ulrich K. Müller & Mark W. Watson, 2022. "Spatial Correlation Robust Inference," Econometrica, Econometric Society, vol. 90(6), pages 2901-2935, November.
    43. Sebastian Calonico & Matias D. Cattaneo & Max H. Farrell, 2018. "Coverage Error Optimal Confidence Intervals for Local Polynomial Regression," Papers 1808.01398, arXiv.org, revised Jul 2021.
    44. M. Chudý & S. Karmakar & W. B. Wu, 2020. "Long-term prediction intervals of economic time series," Empirical Economics, Springer, vol. 58(1), pages 191-222, January.
    45. Efthymios G. Pavlidis & Ivan Paya & David A. Peel, 2018. "Using Market Expectations to Test for Speculative Bubbles in the Crude Oil Market," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(5), pages 833-856, August.
    46. William & C. Horrace & Yulong Wang, 2020. "Nonparametric Tests of Tail Behavior in Stochastic Frontier Models," Papers 2006.07780, arXiv.org.
    47. Torben G. Andersen & Rasmus T. Varneskov, 2021. "Consistent Inference for Predictive Regressions in Persistent Economic Systems," NBER Working Papers 28568, National Bureau of Economic Research, Inc.
    48. Chenchuan (Mark) Li & Ulrich K. Müller, 2020. "Linear Regression with Many Controls of Limited Explanatory Power," Working Papers 2020-57, Princeton University. Economics Department..
    49. Cavaliere, Giuseppe & Nielsen, Heino Bohn & Pedersen, Rasmus Søndergaard & Rahbek, Anders, 2022. "Bootstrap inference on the boundary of the parameter space, with application to conditional volatility models," Journal of Econometrics, Elsevier, vol. 227(1), pages 241-263.
    50. Yoonseok Lee & Yulong Wang, 2020. "Inference in Threshold Models," Center for Policy Research Working Papers 223, Center for Policy Research, Maxwell School, Syracuse University.
    51. 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.
    52. Philipp Ketz, 2018. "Subvector inference when the true parameter vector may be near or at the boundary," Post-Print halshs-01884381, HAL.
    53. 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.
    54. Zhou, Weilun & Gao, Jiti & Harris, David & Kew, Hsein, 2024. "Semi-parametric single-index predictive regression models with cointegrated regressors," Journal of Econometrics, Elsevier, vol. 238(1).
    55. Luther Yap, 2024. "Inference with Many Weak Instruments and Heterogeneity," Papers 2408.11193, arXiv.org, revised Sep 2024.
    56. Boot, Tom & Pick, Andreas, 2020. "Does modeling a structural break improve forecast accuracy?," Journal of Econometrics, Elsevier, vol. 215(1), pages 35-59.
    57. Ulrich K. Müller & Yulong Wang, 2017. "Fixed- Asymptotic Inference About Tail Properties," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(519), pages 1334-1343, July.
    58. Davide Viviano & Kaspar Wuthrich & Paul Niehaus, 2021. "A model of multiple hypothesis testing," Papers 2104.13367, arXiv.org, revised Apr 2024.
    59. Ulrich K. Mueller, 2020. "A More Robust t-Test," Papers 2007.07065, arXiv.org.
    60. Alex Maynard & Katsumi Shimotsu & Nina Kuriyama, 2023. "Inference in Predictive Quantile Regressions," Papers 2306.00296, arXiv.org, revised May 2024.
    61. Tuvaandorj, Purevdorj, 2020. "Regression discontinuity designs, white noise models, and minimax," Journal of Econometrics, Elsevier, vol. 218(2), pages 587-608.
    62. Kees Jan van Garderen & Noud van Giersbergen, 2020. "A Nearly Similar Powerful Test for Mediation," Papers 2012.11342, arXiv.org, revised Jan 2022.
    63. Dmitry Arkhangelsky & Vasily Korovkin, 2020. "On Policy Evaluation with Aggregate Time-Series Shocks," CERGE-EI Working Papers wp657, The Center for Economic Research and Graduate Education - Economics Institute, Prague.

  4. Elliott, Graham & Müller, Ulrich K, 2014. "Pre and post break parameter inference," University of California at San Diego, Economics Working Paper Series qt4j733246, Department of Economics, UC San Diego.

    Cited by:

    1. Ulrich K. Müller & Andriy Norets, 2016. "Coverage Inducing Priors in Nonstandard Inference Problems," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(515), pages 1233-1241, July.
    2. Tom Boot & Andreas Pick, 2017. "A near optimal test for structural breaks when forecasting under square error loss," Tinbergen Institute Discussion Papers 17-039/III, Tinbergen Institute.
    3. Hu, Junjie & López Cabrera, Brenda & Melzer, Awdesch, 2021. "Advanced statistical learning on short term load process forecasting," IRTG 1792 Discussion Papers 2021-020, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    4. Isaiah Andrews & Toru Kitagawa & Adam McCloskey, 2020. "Inference on winners," CeMMAP working papers CWP43/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Adam McCloskey, 2012. "Bonferroni-Based Size-Correction for Nonstandard Testing Problems," Working Papers 2012-16, Brown University, Department of Economics.
    6. Torben G. Andersen & Viktor Todorov & Bo Zhou, 2023. "Real-Time Detection of Local No-Arbitrage Violations," Papers 2307.10872, arXiv.org.
    7. Isaiah Andrews & Toru Kitagawa & Adam McCloskey, 2020. "Inference after Estimation of Breaks," CeMMAP working papers CWP34/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    8. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2024. "Forecasting the UK top 1% income share in a shifting world," Economica, London School of Economics and Political Science, vol. 91(363), pages 1047-1074, July.
    9. Song Shi & Vince Mangioni & Xin Janet Ge & Shanaka Herath & Fethi Rabhi & Rachida Ouysse, 2021. "House Price Forecasting from Investment Perspectives," Land, MDPI, vol. 10(10), pages 1-17, September.
    10. Boot, Tom & Pick, Andreas, 2020. "Does modeling a structural break improve forecast accuracy?," Journal of Econometrics, Elsevier, vol. 215(1), pages 35-59.
    11. Maxwell L. King & Sivagowry Sriananthakumar, 2015. "Point Optimal Testing: A Survey of the Post 1987 Literature," Monash Econometrics and Business Statistics Working Papers 5/15, Monash University, Department of Econometrics and Business Statistics.
    12. Tuvaandorj, Purevdorj, 2020. "Regression discontinuity designs, white noise models, and minimax," Journal of Econometrics, Elsevier, vol. 218(2), pages 587-608.

  5. Elliott, Graham & Gargano, Antonio & Timmermann, Allan, 2013. "Complete subset regressions," University of California at San Diego, Economics Working Paper Series qt1st3n7z7, Department of Economics, UC San Diego.

    Cited by:

    1. Adriano S. Koshiyama & Nikan Firoozye & Philip Treleaven, 2019. "A derivatives trading recommendation system: The mid‐curve calendar spread case," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 26(2), pages 83-103, April.
    2. Kourentzes, Nikolaos & Trapero, Juan R. & Barrow, Devon K., 2020. "Optimising forecasting models for inventory planning," International Journal of Production Economics, Elsevier, vol. 225(C).
    3. Byron Botha & Rulof Burger & Kevin Kotze & Neil Rankin & Daan Steenkamp, 2022. "Big data forecasting of South African inflation," School of Economics Macroeconomic Discussion Paper Series 2022-03, School of Economics, University of Cape Town.
    4. Exterkate, Peter & Groenen, Patrick J.F. & Heij, Christiaan & van Dijk, Dick, 2016. "Nonlinear forecasting with many predictors using kernel ridge regression," International Journal of Forecasting, Elsevier, vol. 32(3), pages 736-753.
    5. Chen, Qitong & Hong, Yongmiao & Li, Haiqi, 2024. "Time-varying forecast combination for factor-augmented regressions with smooth structural changes," Journal of Econometrics, Elsevier, vol. 240(1).
    6. Moritz Meister & Annekatrin Niebuhr & Jan Cornelius Peters & Johannes Stiller, 2023. "Local attributes and migration balance – evidence for different age and skill groups from a machine learning approach," Regional Science Policy & Practice, Wiley Blackwell, vol. 15(4), pages 794-825, May.
    7. Koop, Gary & Korobilis, Dimitris & Pettenuzzo, Davide, 2019. "Bayesian compressed vector autoregressions," Journal of Econometrics, Elsevier, vol. 210(1), pages 135-154.
    8. Buncic, Daniel & Piras, Gion Donat, 2014. "Heterogeneous Agents, the Financial Crisis and Exchange Rate Predictability," Economics Working Paper Series 1436, University of St. Gallen, School of Economics and Political Science, revised Oct 2015.
    9. Ioannis Kyriakou & Parastoo Mousavi & Jens Perch Nielsen & Michael Scholz, 2021. "Forecasting benchmarks of long-term stock returns via machine learning," Annals of Operations Research, Springer, vol. 297(1), pages 221-240, February.
    10. 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.
    11. David A. Mascio & Frank J. Fabozzi & J. Kenton Zumwalt, 2021. "Market timing using combined forecasts and machine learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 1-16, January.
    12. Timmermann, Allan & Pettenuzzo, Davide & Gargano, Antonio, 2014. "Bond Return Predictability: Economic Value and Links to the Macroeconomy," CEPR Discussion Papers 10104, C.E.P.R. Discussion Papers.
    13. Olivier Fortin-Gagnon & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2018. "A Large Canadian Database for Macroeconomic Analysis," CIRANO Working Papers 2018s-25, CIRANO.
    14. Scholz, Michael & Nielsen, Jens Perch & Sperlich, Stefan, 2015. "Nonparametric prediction of stock returns based on yearly data: The long-term view," Insurance: Mathematics and Economics, Elsevier, vol. 65(C), pages 143-155.
    15. Barbara Rossi, 2019. "Forecasting in the presence of instabilities: How do we know whether models predict well and how to improve them," Economics Working Papers 1711, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2021.
    16. Yi-Ting Chen & Chu-An Liu, 2021. "Model Averaging for Asymptotically Optimal Combined Forecasts," IEAS Working Paper : academic research 21-A002, Institute of Economics, Academia Sinica, Taipei, Taiwan.
    17. Victor DeMiguel & Javier Gil-Bazo & Francisco J. Nogales & André A. P. Santos, 2021. "Can machine learning help to select portfolios of mutual funds?," Economics Working Papers 1772, Department of Economics and Business, Universitat Pompeu Fabra.
    18. Cheng, Xu & Hansen, Bruce E., 2015. "Forecasting with factor-augmented regression: A frequentist model averaging approach," Journal of Econometrics, Elsevier, vol. 186(2), pages 280-293.
    19. Goulet Coulombe, Philippe & Leroux, Maxime & Stevanovic, Dalibor & Surprenant, Stéphane, 2021. "Macroeconomic data transformations matter," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1338-1354.
    20. 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).
    21. Timmermann, Allan, 2018. "Forecasting Methods in Finance," CEPR Discussion Papers 12692, C.E.P.R. Discussion Papers.
    22. Daniel Borup & Bent Jesper Christensen & Nicolaj N. Mühlbach & Mikkel S. Nielsen, 2020. "Targeting predictors in random forest regression," CREATES Research Papers 2020-03, Department of Economics and Business Economics, Aarhus University.
    23. Hounyo, Ulrich & Lahiri, Kajal, 2023. "Estimating the variance of a combined forecast: Bootstrap-based approach," Journal of Econometrics, Elsevier, vol. 232(2), pages 445-468.
    24. 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.
    25. Joshua C.C. Chan & Eric Eisenstat & Chenghan Hou & Gary Koop, 2018. "Composite likelihood methods for large Bayesian VARs with stochastic volatility," CAMA Working Papers 2018-26, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    26. John Cotter & Emmanuel Eyiah-Donkor & Valerio Potì, 2023. "Commodity futures return predictability and intertemporal asset pricing," Post-Print hal-04192933, HAL.
    27. Aslanidis, Nektarios, & Christiansen, Charlotte & Cipollini, Andrea & Bons -- Models matemàtics, 2018. "Predicting Bond Betas using Macro-Finance Variables," Working Papers 2072/306546, Universitat Rovira i Virgili, Department of Economics.
    28. Sainan Jin & Valentina Corradi & Norman Swanson, 2015. "Robust Forecast Comparison," Departmental Working Papers 201502, Rutgers University, Department of Economics.
    29. Cheng, Tingting & Jiang, Shan & Zhao, Albert Bo & Jia, Zhimin, 2023. "Complete subset averaging methods in corporate bond return prediction," Finance Research Letters, Elsevier, vol. 54(C).
    30. Araujo, Gustavo Silva & Gaglianone, Wagner Piazza, 2023. "Machine learning methods for inflation forecasting in Brazil: New contenders versus classical models," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 4(2).
    31. Kurov, Alexander & Sancetta, Alessio & Strasser, Georg & Wolfe, Marketa Halova, 2019. "Price Drift Before U.S. Macroeconomic News: Private Information about Public Announcements?," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 54(1), pages 449-479, February.
    32. Antoine Mandel & Amir Sani, 2016. "Learning Time-Varying Forecast Combinations," Documents de travail du Centre d'Economie de la Sorbonne 16036, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    33. Felipe Leal & Carlos Molina & Eduardo Zilberman, 2020. "Proyección de la Inflación en Chile con Métodos de Machine Learning," Working Papers Central Bank of Chile 860, Central Bank of Chile.
    34. Joscha Beckmann & Rainer Schüssler, 2014. "Forecasting Exchange Rates under Model and Parameter Uncertainty," CQE Working Papers 3214, Center for Quantitative Economics (CQE), University of Muenster.
    35. Antoine Mandel & Amir Sani, 2017. "A Machine Learning Approach to the Forecast Combination Puzzle," Working Papers halshs-01317974, HAL.
    36. Wen, Danyan & Liu, Li & Wang, Yudong & Zhang, Yaojie, 2022. "Forecasting crude oil market returns: Enhanced moving average technical indicators," Resources Policy, Elsevier, vol. 76(C).
    37. Yaojie Zhang & Yudong Wang & Feng Ma, 2021. "Forecasting US stock market volatility: How to use international volatility information," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 733-768, August.
    38. Koo, Bonsoo & Anderson, Heather M. & Seo, Myung Hwan & Yao, Wenying, 2020. "High-dimensional predictive regression in the presence of cointegration," Journal of Econometrics, Elsevier, vol. 219(2), pages 456-477.
    39. Donghua Wang & Tianhui Fang, 2022. "Forecasting Crude Oil Prices with a WT-FNN Model," Energies, MDPI, vol. 15(6), pages 1-21, March.
    40. Garcia, Márcio G.P. & Medeiros, Marcelo C. & Vasconcelos, Gabriel F.R., 2017. "Real-time inflation forecasting with high-dimensional models: The case of Brazil," International Journal of Forecasting, Elsevier, vol. 33(3), pages 679-693.
    41. Zhifeng Dai & Tingyu Li & Mi Yang, 2022. "Forecasting stock return volatility: The role of shrinkage approaches in a data‐rich environment," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(5), pages 980-996, August.
    42. 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.
    43. Scholz, Michael & Sperlich, Stefan & Nielsen, Jens Perch, 2016. "Nonparametric long term prediction of stock returns with generated bond yields," Insurance: Mathematics and Economics, Elsevier, vol. 69(C), pages 82-96.
    44. DeMiguel, Victor & Gil-Bazo, Javier & Nogales, Francisco J. & Santos, André A.P., 2023. "Machine learning and fund characteristics help to select mutual funds with positive alpha," Journal of Financial Economics, Elsevier, vol. 150(3).
    45. Maxime Leroux & Rachidi Kotchoni & Dalibor Stevanovic, 2017. "Forecasting economic activity in data-rich environment," Working Papers hal-04141668, HAL.
    46. Chen, Bin & Maung, Kenwin, 2023. "Time-varying forecast combination for high-dimensional data," Journal of Econometrics, Elsevier, vol. 237(2).
    47. Sagaert, Yves R. & Aghezzaf, El-Houssaine & Kourentzes, Nikolaos & Desmet, Bram, 2018. "Tactical sales forecasting using a very large set of macroeconomic indicators," European Journal of Operational Research, Elsevier, vol. 264(2), pages 558-569.
    48. 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.
    49. Seojeong Lee & Youngki Shin, 2021. "Complete subset averaging with many instruments," The Econometrics Journal, Royal Economic Society, vol. 24(2), pages 290-314.
    50. Boot, Tom & Nibbering, Didier, 2019. "Forecasting using random subspace methods," Journal of Econometrics, Elsevier, vol. 209(2), pages 391-406.
    51. Xu Cheng & Bruce E. Hansen, 2012. "Forecasting with Factor-Augmented Regression: A Frequentist Model Averaging Approach, Second Version," PIER Working Paper Archive 13-061, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 03 Sep 2013.
    52. Yanhui Chen & Ailing Feng & Shun Chen & Jackson Jinhong Mi, 2024. "Forecasting the containerized freight index with AIS data: A novel information combination method based on gray incidence analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(3), pages 802-815, April.
    53. Lyócsa, Štefan & Todorova, Neda & Výrost, Tomáš, 2021. "Predicting risk in energy markets: Low-frequency data still matter," Applied Energy, Elsevier, vol. 282(PA).
    54. Liu, Chu-An, 2013. "Distribution Theory of the Least Squares Averaging Estimator," MPRA Paper 54201, University Library of Munich, Germany.
    55. M. Chudý & S. Karmakar & W. B. Wu, 2020. "Long-term prediction intervals of economic time series," Empirical Economics, Springer, vol. 58(1), pages 191-222, January.
    56. Beckmann, Joscha & Schüssler, Rainer, 2016. "Forecasting exchange rates under parameter and model uncertainty," Journal of International Money and Finance, Elsevier, vol. 60(C), pages 267-288.
    57. Elliott, Graham & Gargano, Antonio & Timmermann, Allan, 2015. "Complete subset regressions with large-dimensional sets of predictors," Journal of Economic Dynamics and Control, Elsevier, vol. 54(C), pages 86-110.
    58. Korobilis, Dimitris, 2018. "Machine Learning Macroeconometrics A Primer," Essex Finance Centre Working Papers 22666, University of Essex, Essex Business School.
    59. Roberto Casarin & Daniel Felix Ahelegbey & Monica Billio, 2014. "Sparse Graphical Vector Autoregression: A Bayesian Approach," Working Papers 2014:29, Department of Economics, University of Venice "Ca' Foscari".
    60. Lee, Ji Hyung & Shin, Youngki, 2023. "Complete Subset Averaging For Quantile Regressions," Econometric Theory, Cambridge University Press, vol. 39(1), pages 146-188, February.
    61. Zhentao Shi & Liangjun Su & Tian Xie, 2020. "L2-Relaxation: With Applications to Forecast Combination and Portfolio Analysis," Papers 2010.09477, arXiv.org, revised Aug 2022.
    62. Philippe Goulet Coulombe, 2020. "To Bag is to Prune," Papers 2008.07063, arXiv.org, revised Sep 2024.
    63. Jordan, Steven J. & Vivian, Andrew & Wohar, Mark E., 2016. "Can commodity returns forecast Canadian sector stock returns?," International Review of Economics & Finance, Elsevier, vol. 41(C), pages 172-188.
    64. Magnus, Jan R. & Vasnev, Andrey L., 2015. "Interpretation and use of sensitivity in econometrics, illustrated with forecast combinations," International Journal of Forecasting, Elsevier, vol. 31(3), pages 769-781.
    65. Daniele Bianchi & Kenichiro McAlinn, 2018. "Large-Scale Dynamic Predictive Regressions," Papers 1803.06738, arXiv.org.
    66. Zhao, Albert Bo & Cheng, Tingting, 2022. "Stock return prediction: Stacking a variety of models," Journal of Empirical Finance, Elsevier, vol. 67(C), pages 288-317.
    67. Wang, Yudong & Hao, Xianfeng & Wu, Chongfeng, 2021. "Forecasting stock returns: A time-dependent weighted least squares approach," Journal of Financial Markets, Elsevier, vol. 53(C).
    68. Rachidi Kotchoni & Maxime Leroux & Dalibor Stevanovic, 2019. "Macroeconomic Forecast Accuracy in data-rich environment," Post-Print hal-02435757, HAL.
    69. Seema Narayan & Russell Smyth, 2015. "The Financial Econometrics of Price Discovery and Predictability," Monash Economics Working Papers 06-15, Monash University, Department of Economics.
    70. Dennis Kant & Andreas Pick & Jasper de Winter, 2022. "Nowcasting GDP using machine learning methods," Working Papers 754, DNB.
    71. Seojeong Lee & Youngki Shin, 2018. "Optimal Estimation with Complete Subsets of Instruments," Department of Economics Working Papers 2018-15, McMaster University.
    72. Eraslan, Sercan & Schröder, Maximilian, 2023. "Nowcasting GDP with a pool of factor models and a fast estimation algorithm," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1460-1476.
    73. 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.
    74. 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.
    75. Wang, Yunqi & Zhou, Ti, 2023. "Out-of-sample equity premium prediction: The role of option-implied constraints," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 199-226.
    76. Rama K. Malladi, 2024. "Benchmark Analysis of Machine Learning Methods to Forecast the U.S. Annual Inflation Rate During a High-Decile Inflation Period," Computational Economics, Springer;Society for Computational Economics, vol. 64(1), pages 335-375, July.
    77. Wang, Yudong & Liu, Li & Ma, Feng & Diao, Xundi, 2018. "Momentum of return predictability," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 141-156.
    78. Christian Brownlees & Geert Mesters, 2017. "Detecting Granular Time Series in Large Panels," Working Papers 991, Barcelona School of Economics.
    79. Anwen Yin, 2024. "Predictive model averaging with parameter instability and heteroskedasticity," Bulletin of Economic Research, Wiley Blackwell, vol. 76(2), pages 418-442, April.
    80. Zhang, Yaojie & Wei, Yu & Zhang, Yi & Jin, Daxiang, 2019. "Forecasting oil price volatility: Forecast combination versus shrinkage method," Energy Economics, Elsevier, vol. 80(C), pages 423-433.
    81. Kartikay Gupta & Niladri Chatterjee, 2021. "Stocks Recommendation from Large Datasets Using Important Company and Economic Indicators," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 28(4), pages 667-689, December.
    82. Medeiros, Marcelo C. & Vasconcelos, Gabriel F.R., 2016. "Forecasting macroeconomic variables in data-rich environments," Economics Letters, Elsevier, vol. 138(C), pages 50-52.
    83. 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.
    84. 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).
    85. Hao, Xianfeng & Zhao, Yuyang & Wang, Yudong, 2020. "Forecasting the real prices of crude oil using robust regression models with regularization constraints," Energy Economics, Elsevier, vol. 86(C).
    86. Chu‐An Liu & Biing‐Shen Kuo, 2016. "Model averaging in predictive regressions," Econometrics Journal, Royal Economic Society, vol. 19(2), pages 203-231, June.
    87. Risse, Marian & Ohl, Ludwig, 2017. "Using dynamic model averaging in state space representation with dynamic Occam’s window and applications to the stock and gold market," Journal of Empirical Finance, Elsevier, vol. 44(C), pages 158-176.
    88. Chen, Xingyi & Li, Haiqi & Zhang, Jing, 2023. "Complete subset averaging approach for high-dimensional generalized linear models," Economics Letters, Elsevier, vol. 226(C).
    89. Philippe Goulet Coulombe, 2021. "To Bag is to Prune," Working Papers 21-03, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Jun 2021.
    90. Jiun-Hua Su, 2021. "No-Regret Forecasting with Egalitarian Committees," Papers 2109.13801, arXiv.org.
    91. Qiu, Yue, 2021. "Complete subset least squares support vector regression," Economics Letters, Elsevier, vol. 200(C).
    92. Costa, Alexandre Bonnet R. & Ferreira, Pedro Cavalcanti G. & Gaglianone, Wagner P. & Guillén, Osmani Teixeira C. & Issler, João Victor & Lin, Yihao, 2021. "Machine learning and oil price point and density forecasting," Energy Economics, Elsevier, vol. 102(C).
    93. Anthony Garratt & Ivan Petrella, 2022. "Commodity prices and inflation risk," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(2), pages 392-414, March.
    94. Elliott, Graham & Timmermann, Allan G, 2016. "Forecasting in Economics and Finance," University of California at San Diego, Economics Working Paper Series qt6z55v472, Department of Economics, UC San Diego.
    95. Matthias Pelster & Johannes Vilsmeier, 2018. "The determinants of CDS spreads: evidence from the model space," Review of Derivatives Research, Springer, vol. 21(1), pages 63-118, April.
    96. Allan Timmermann, 2018. "Forecasting Methods in Finance," Annual Review of Financial Economics, Annual Reviews, vol. 10(1), pages 449-479, November.
    97. Gargano, Antonio & Timmermann, Allan, 2014. "Forecasting commodity price indexes using macroeconomic and financial predictors," International Journal of Forecasting, Elsevier, vol. 30(3), pages 825-843.
    98. Pelster, Matthias & Vilsmeier, Johannes, 2016. "The determinants of CDS spreads: Evidence from the model space," Discussion Papers 43/2016, Deutsche Bundesbank.
    99. Risse, Marian, 2019. "Combining wavelet decomposition with machine learning to forecast gold returns," International Journal of Forecasting, Elsevier, vol. 35(2), pages 601-615.
    100. 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.
    101. Carlos Henrique Dias Cordeiro de Castro & Fernando Antonio Lucena Aiube, 2023. "Forecasting inflation time series using score‐driven dynamic models and combination methods: The case of Brazil," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 369-401, March.
    102. Adriano Soares Koshiyama & Nick Firoozye & Philip Treleaven, 2018. "A Machine Learning-based Recommendation System for Swaptions Strategies," Papers 1810.02125, arXiv.org.
    103. Erik Christian Montes Schütte, 2018. "In Search of a Job: Forecasting Employment Growth in the US using Google Trends," CREATES Research Papers 2018-25, Department of Economics and Business Economics, Aarhus University.
    104. Sabaj, Ernil & Kahveci, Mustafa, 2018. "Forecasting tax revenues in an emerging economy: The case of Albania," MPRA Paper 84404, University Library of Munich, Germany.
    105. Ioannis D. Vrontos & John Galakis & Ekaterini Panopoulou & Spyridon D. Vrontos, 2024. "Forecasting GDP growth: The economic impact of COVID‐19 pandemic," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(4), pages 1042-1086, July.
    106. Joscha Beckmann & Rainer Schüssler, 2014. "Forecasting Equity Premia using Bayesian Dynamic Model Averaging," CQE Working Papers 2914, Center for Quantitative Economics (CQE), University of Muenster.

  6. Timmermann, Allan & Elliott, Graham, 2007. "Economic Forecasting," CEPR Discussion Papers 6158, C.E.P.R. Discussion Papers.

    Cited by:

    1. von der Gracht, Heiko A. & Hommel, Ulrich & Prokesch, Tobias & Wohlenberg, Holger, 2016. "Testing weighting approaches for forecasting in a Group Wisdom Support System environment," Journal of Business Research, Elsevier, vol. 69(10), pages 4081-4094.
    2. Andrii Babii & Xi Chen & Eric Ghysels & Rohit Kumar, 2020. "Binary Choice with Asymmetric Loss in a Data-Rich Environment: Theory and an Application to Racial Justice," Papers 2010.08463, arXiv.org, revised Nov 2021.
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    188. Rizwan Raheem AHMED & Dalia STREIMIKIENE & Saghir Pervaiz GHAURI & Muhammad AQIL, 2021. "Forecasting Inflation by Using the Sub-Groups of both CPI and WPI: Evidence from Auto Regression (AR) and ARIMA Models," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 144-161, June.
    189. Zhou, Weilun & Gao, Jiti & Harris, David & Kew, Hsein, 2024. "Semi-parametric single-index predictive regression models with cointegrated regressors," Journal of Econometrics, Elsevier, vol. 238(1).
    190. Gneiting, Tilmann, 2011. "Quantiles as optimal point forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 197-207.
    191. Kaya, Huseyin, 2013. "Forecasting the yield curve and the role of macroeconomic information in Turkey," Economic Modelling, Elsevier, vol. 33(C), pages 1-7.
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    193. 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.
    194. Mr. Allan Timmermann, 2006. "An Evaluation of the World Economic Outlook Forecasts," IMF Working Papers 2006/059, International Monetary Fund.
    195. Xiaoye Jin, 2022. "Evaluating the predictive power of intraday technical trading in China's crude oil market," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(7), pages 1416-1432, November.
    196. David Schröder, 2020. "The role of market efficiency on implied cost of capital estimates: an international perspective," Annals of Finance, Springer, vol. 16(4), pages 463-499, December.
    197. Procasky, William J. & Yin, Anwen, 2023. "The impact of COVID-19 on the relative market efficiency and forecasting ability of credit derivative and equity markets," International Review of Financial Analysis, Elsevier, vol. 90(C).
    198. 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.
    199. Meub, Lukas & Proeger, Till & Bizer, Kilian & Spiwoks, Markus, 2015. "Strategic coordination in forecasting – An experimental study," Finance Research Letters, Elsevier, vol. 13(C), pages 155-162.
    200. 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.
    201. Bizer, Kilian & Meub, Lukas & Proeger, Till & Spiwoks, Markus, 2014. "Strategic coordination in forecasting: An experimental study," University of Göttingen Working Papers in Economics 195, University of Goettingen, Department of Economics.
    202. Kuangyu Wen, 2023. "A semiparametric spatio‐temporal model of crop yield trend and its implication to insurance rating," Agricultural Economics, International Association of Agricultural Economists, vol. 54(5), pages 662-673, September.
    203. Dichtl, Hubert & Drobetz, Wolfgang & Neuhierl, Andreas & Wendt, Viktoria-Sophie, 2021. "Data snooping in equity premium prediction," International Journal of Forecasting, Elsevier, vol. 37(1), pages 72-94.
    204. 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.
    205. Kaiji Motegi & Xiaojing Cai & Shigeyuki Hamori & Haifeng Xu, 2020. "Moving average threshold heterogeneous autoregressive (MAT‐HAR) models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1035-1042, November.
    206. Leonard I. Nakamura & Tom Stark, 2007. "Mismeasured personal saving and the permanent income hypothesis," Working Papers 07-8, Federal Reserve Bank of Philadelphia.
    207. Komunjer, Ivana, 2013. "Quantile Prediction," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 961-994, Elsevier.
    208. Todd E. Clark & Taisuke Nakata, 2006. "The trend growth rate of employment : past, present, and future," Economic Review, Federal Reserve Bank of Kansas City, vol. 91(Q I), pages 43-85.
    209. Nicolas Sirven & Brigitte Santos-Eggimann & Jacques Spagnoli, 2008. "Comparability of Health Care Responsiveness in Europe using anchoring vignettes from SHARE," Working Papers DT15, IRDES institut for research and information in health economics, revised Sep 2008.
    210. McKenzie, Jordi, 2011. "Mean absolute percentage error and bias in economic forecasting," Economics Letters, Elsevier, vol. 113(3), pages 259-262.
    211. Laura Veldkamp & Anna Orlik, 2014. "Uncertainty Shocks and the Role of the Black Swan," 2014 Meeting Papers 275, Society for Economic Dynamics.
    212. Anwen Yin, 2021. "Forecasting the Market Equity Premium: Does Nonlinearity Matter?," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 13(5), pages 1-9, May.
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    214. Iania, Leonardo & Algieri, Bernardina & Leccadito, Arturo, 2022. "Forecasting total energy’s CO2 emissions," LIDAM Discussion Papers LFIN 2022003, Université catholique de Louvain, Louvain Finance (LFIN).
    215. Bennedsen, Mikkel & Lunde, Asger & Shephard, Neil & Veraart, Almut E.D., 2023. "Inference and forecasting for continuous-time integer-valued trawl processes," Journal of Econometrics, Elsevier, vol. 236(2).
    216. Jari Hännikäinen, 2015. "Zero lower bound, unconventional monetary policy and indicator properties of interest rate spreads," Review of Financial Economics, John Wiley & Sons, vol. 26(1), pages 47-54, September.
    217. Harun Özkan & M. Yazgan, 2015. "Is forecasting inflation easier under inflation targeting?," Empirical Economics, Springer, vol. 48(2), pages 609-626, March.
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    227. Arai, Natsuki, 2020. "Investigating the inefficiency of the CBO’s budgetary projections," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1290-1300.
    228. Aysun, Uluc & Wright, Cardel, 2024. "A two-step dynamic factor modelling approach for forecasting inflation in small open economies," Emerging Markets Review, Elsevier, vol. 62(C).
    229. William J. Procasky & Anwen Yin, 2022. "Forecasting high‐yield equity and CDS index returns: Does observed cross‐market informational flow have predictive power?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(8), pages 1466-1490, August.

  7. Timmermann, Allan & Elliott, Graham, 2004. "Optimal Forecast Combination Under Regime Switching," CEPR Discussion Papers 4649, C.E.P.R. Discussion Papers.

    Cited by:

    1. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    2. Krüger Fabian & Pohlmeier Winfried & Mokinski Frieder, 2011. "Combining Survey Forecasts and Time Series Models: The Case of the Euribor," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 63-81, February.
    3. Mehmet Pinar & Thanasis Stengos & M. Ege Yazgan, 2018. "Quantile forecast combination using stochastic dominance," Empirical Economics, Springer, vol. 55(4), pages 1717-1755, December.
    4. Benavides, Guillermo & Capistrán, Carlos, 2012. "Forecasting exchange rate volatility: The superior performance of conditional combinations of time series and option implied forecasts," Journal of Empirical Finance, Elsevier, vol. 19(5), pages 627-639.
    5. Chen, Qitong & Hong, Yongmiao & Li, Haiqi, 2024. "Time-varying forecast combination for factor-augmented regressions with smooth structural changes," Journal of Econometrics, Elsevier, vol. 240(1).
    6. Davide Pettenuzzo & Francesco Ravazzolo, 2014. "Optimal portfolio choice under decision-based model combinations," Working Paper 2014/15, Norges Bank.
    7. Favero, Carlo A. & Milani, Fabio, 2005. "Parameter Instability, Model Uncertainty and the Choice of Monetary Policy," CEPR Discussion Papers 4909, C.E.P.R. Discussion Papers.
    8. Barrow, Devon K. & Kourentzes, Nikolaos, 2016. "Distributions of forecasting errors of forecast combinations: Implications for inventory management," International Journal of Production Economics, Elsevier, vol. 177(C), pages 24-33.
    9. Valentina Corradi & Norman Swanson, 2013. "A Survey of Recent Advances in Forecast Accuracy Comparison Testing, with an Extension to Stochastic Dominance," Departmental Working Papers 201309, Rutgers University, Department of Economics.
    10. Carlos Capistrán & Allan Timmermann, 2008. "Forecast Combination With Entry and Exit of Experts," CREATES Research Papers 2008-55, Department of Economics and Business Economics, Aarhus University.
    11. Barbara Rossi, 2019. "Forecasting in the presence of instabilities: How do we know whether models predict well and how to improve them," Economics Working Papers 1711, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2021.
    12. Jakub Nowotarski, 2013. "Short-term forecasting of electricity spot prices using model averaging (Krótkoterminowe prognozowanie spotowych cen energii elektrycznej z wykorzystaniem uśredniania modeli)," HSC Research Reports HSC/13/17, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    13. Sun, Yuying & Hong, Yongmiao & Wang, Shouyang & Zhang, Xinyu, 2023. "Penalized time-varying model averaging," Journal of Econometrics, Elsevier, vol. 235(2), pages 1355-1377.
    14. Guérin, Pierre & Leiva-Leon, Danilo, 2017. "Model averaging in Markov-switching models: Predicting national recessions with regional data," Economics Letters, Elsevier, vol. 157(C), pages 45-49.
    15. Lees, Kirdan & Matheson, Troy & Smith, Christie, 2011. "Open economy forecasting with a DSGE-VAR: Head to head with the RBNZ published forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 512-528.
    16. Georgios Papadopoulos & Dionysios Chionis & Nikolaos P. Rachaniotis, 2018. "Macro-financial linkages during tranquil and crisis periods: evidence from stressed economies," Risk Management, Palgrave Macmillan, vol. 20(2), pages 142-166, May.
    17. Martinez-Martin Jaime & Morris Richard & Onorante Luca & Piersanti Fabio Massimo, 2024. "Merging Structural and Reduced-Form Models for Forecasting," The B.E. Journal of Macroeconomics, De Gruyter, vol. 24(1), pages 399-437, January.
    18. Antoine Mandel & Amir Sani, 2016. "Learning Time-Varying Forecast Combinations," Documents de travail du Centre d'Economie de la Sorbonne 16036, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    19. Antoine Mandel & Amir Sani, 2017. "A Machine Learning Approach to the Forecast Combination Puzzle," Working Papers halshs-01317974, HAL.
    20. Eo, Yunjong & Kang, Kyu Ho, 2020. "The effects of conventional and unconventional monetary policy on forecasting the yield curve," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    21. Aiolfi Marco & Capistrán Carlos & Timmermann Allan, 2010. "Forecast Combinations," Working Papers 2010-04, Banco de México.
    22. Marcus Cobb, 2009. "Forecasting Chilean Inflation From Disaggregate Components," Working Papers Central Bank of Chile 545, Central Bank of Chile.
    23. A.S.M. Arroyo & A. de Juan Fern¨¢ndez, 2014. "Split-then-Combine Method for out-of-sample Combinations of Forecasts," Journal of Business Administration Research, Journal of Business Administration Research, Sciedu Press, vol. 3(1), pages 19-37, April.
    24. George Athanasopoulos & Rob J Hyndman & Nikolaos Kourentzes & Fotios Petropoulos, 2015. "Forecasting with Temporal Hierarchies," Monash Econometrics and Business Statistics Working Papers 16/15, Monash University, Department of Econometrics and Business Statistics.
    25. Norman Swanson & Valentina Corradi, 2006. "Nonparametric Bootstrap Procedures for Predictive Inference Based on Recursive Estimation Schemes," Departmental Working Papers 200618, Rutgers University, Department of Economics.
    26. Zhe Huang & Franck Martin, 2017. "Optimal pairs trading strategies in a cointegration framework," Working Papers halshs-01566803, HAL.
    27. Rianne Legerstee & Philip Hans Franses, 2010. "Does Disagreement amongst Forecasters have Predictive Value?," Tinbergen Institute Discussion Papers 10-088/4, Tinbergen Institute.
    28. Bin Chen & Kenwin Maung, 2020. "Time-varying Forecast Combination for High-Dimensional Data," Papers 2010.10435, arXiv.org.
    29. Chen, Bin & Maung, Kenwin, 2023. "Time-varying forecast combination for high-dimensional data," Journal of Econometrics, Elsevier, vol. 237(2).
    30. Mehmet Pinar & Thanasis Stengos & M. Ege Yazgan, 2012. "Is there an Optimal Forecast Combination? A Stochastic Dominance Approach to Forecast Combination Puzzle," Working Paper series 17_12, Rimini Centre for Economic Analysis.
    31. Lima, Luiz Renato Regis de Oliveira & Issler, João Victor, 2007. "A panel data approach to economic forecasting: the bias-corrected average forecast," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 650, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    32. Giacomini, Raffaella & Rossi, Barbara, 2008. "Forecast Comparisons in Unstable Environments," Working Papers 08-04, Duke University, Department of Economics.
    33. Lyócsa, Štefan & Todorova, Neda & Výrost, Tomáš, 2021. "Predicting risk in energy markets: Low-frequency data still matter," Applied Energy, Elsevier, vol. 282(PA).
    34. Elena Andreou & Eric Ghysels & Constantinos Kourouyiannis, 2012. "Robust volatility forecasts in the presence of structural breaks," University of Cyprus Working Papers in Economics 08-2012, University of Cyprus Department of Economics.
    35. Gaglianone, Wagner Piazza & Issler, João Victor, 2019. "Microfounded forecasting," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 813, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    36. Yongchen Zhao, 2021. "The robustness of forecast combination in unstable environments: a Monte Carlo study of advanced algorithms," Empirical Economics, Springer, vol. 61(1), pages 173-199, July.
    37. Krüger, Fabian & Nolte, Ingmar, 2016. "Disagreement versus uncertainty: Evidence from distribution forecasts," Journal of Banking & Finance, Elsevier, vol. 72(S), pages 172-186.
    38. Rachidi Kotchoni & Maxime Leroux & Dalibor Stevanovic, 2019. "Macroeconomic Forecast Accuracy in data-rich environment," Post-Print hal-02435757, HAL.
    39. Kenwin Maung, 2021. "Estimating high-dimensional Markov-switching VARs," Papers 2107.12552, arXiv.org.
    40. Valentina Corradi & Norman Swanson, 2004. "Bootstrap Procedures for Recursive Estimation Schemes With Applications to Forecast Model Selection," Departmental Working Papers 200418, Rutgers University, Department of Economics.
    41. Timmermann, Allan & Guidolin, Massimo, 2007. "Forecasts of US Short-term Interest Rates: A Flexible Forecast Combination Approach," CEPR Discussion Papers 6188, C.E.P.R. Discussion Papers.
    42. Steff De Visscher & Markus Eberhardt & Gerdie Everaert, 2017. "Measuring productivity and absorptive capacity evolution," Discussion Papers 2017-11, University of Nottingham, GEP.
    43. Daniel Borup & Martin Thyrsgaard, 2017. "Statistical tests for equal predictive ability across multiple forecasting methods," CREATES Research Papers 2017-19, Department of Economics and Business Economics, Aarhus University.
    44. Ayadi, Mohamed A. & Lazrak, Skander & Liao, Yusui & Welch, Robert, 2018. "Performance of fixed-income mutual funds with regime-switching models," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 217-231.
    45. 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.
    46. Sylvia Kaufmann, 2016. "Hidden Markov models in time series, with applications in economics," Working Papers 16.06, Swiss National Bank, Study Center Gerzensee.
    47. Chen Zhuo & Yang Yuhong, 2007. "Time Series Models for Forecasting: Testing or Combining?," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 11(1), pages 1-37, March.

  8. Elliott, Graham & Jansson, Michael & Pesavento, Elena, 2004. "Optimal Power for Testing Potential Cointegrating Vectors with Known," University of California at San Diego, Economics Working Paper Series qt2bv7n071, Department of Economics, UC San Diego.

    Cited by:

    1. Elliott, Graham & Jansson, Michael, 2000. "Testing for Unit Roots with Stationary Covariances," Department of Economics, Working Paper Series qt47k7z69n, Department of Economics, Institute for Business and Economic Research, UC Berkeley.

  9. Allan Timmermann & Graham Elliott & Ivana Komunjer, 2004. "Biases in Macroeconomic Forecasts: Irrationality or Asymmetric Loss?," Econometric Society 2004 North American Summer Meetings 601, Econometric Society.

    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. Pesaran, M. Hashem & Weale, Martin, 2006. "Survey Expectations," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 14, pages 715-776, Elsevier.
    3. Ivana Komunjer & Michael T. Owyang, 2012. "Multivariate Forecast Evaluation and Rationality Testing," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1066-1080, November.
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    143. Elliott, Graham & Timmermann, Allan G, 2016. "Forecasting in Economics and Finance," University of California at San Diego, Economics Working Paper Series qt6z55v472, Department of Economics, UC San Diego.
    144. Lee, Tae-Hwy & Yang, Yang, 2006. "Bagging binary and quantile predictors for time series," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 465-497.
    145. Sergey V. Smirnov & Daria A. Avdeeva, 2016. "Wishful Bias in Predicting Us Recessions: Indirect Evidence," HSE Working papers WP BRP 135/EC/2016, National Research University Higher School of Economics.
    146. 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.
    147. Jonsson, Thomas & Österholm, Pär, 2011. "The forecasting properties of survey-based wage-growth expectations," Economics Letters, Elsevier, vol. 113(3), pages 276-281.
    148. Conrad, Christian & Lahiri, Kajal, 2024. "Heterogeneous Expectations among Professional Forecasters," Working Papers 0754, University of Heidelberg, Department of Economics.
    149. Döpke, Jörg & Müller, Karsten & Tegtmeier, Lars, 2018. "The economic value of business cycle forecasts for potential investors – Evidence from Germany," Research in International Business and Finance, Elsevier, vol. 46(C), pages 445-461.
    150. Pedro Henrique Melo Albuquerque & Yaohao Peng & João Pedro Fontoura da Silva, 2022. "Making the whole greater than the sum of its parts: A literature review of ensemble methods for financial time series forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(8), pages 1701-1724, December.
    151. Jörg Döpke & Ulrich Fritsche & Christian Pierdzioch, 2015. "Predicting Recessions in Germany With Boosted Regression Trees," Macroeconomics and Finance Series 201505, University of Hamburg, Department of Socioeconomics.
    152. Kröger, Sabine & Pierrot, Thibaud, 2019. "What point of a distribution summarises point predictions?," Discussion Papers, Research Unit: Market Behavior SP II 2019-212, WZB Berlin Social Science Center.
    153. Tsuchiya, Yoichi, 2016. "Asymmetric loss and rationality of Chinese renminbi forecasts: An implication for the trade between China and the US," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 44(C), pages 116-127.
    154. Anmol Bhandari & Jaroslav Borovicka & Paul Ho, 2019. "Survey Data and Subjective Beliefs in Business Cycle Models," Working Paper 19-14, Federal Reserve Bank of Richmond.
    155. Tsuchiya, Yoichi, 2012. "Evaluating Japanese corporate executives’ forecasts under an asymmetric loss function," Economics Letters, Elsevier, vol. 116(3), pages 601-603.
    156. P. Schanbacher, 2014. "Measuring and adjusting for overconfidence," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 37(2), pages 423-452, October.
    157. Sergey V. Smirnov, 2014. "Predicting US Recessions: Does a Wishful Bias Exist?," HSE Working papers WP BRP 77/EC/2014, National Research University Higher School of Economics.
    158. Hamid Baghestani, 2013. "Evaluating Federal Reserve predictions of growth in consumer spending," Applied Economics, Taylor & Francis Journals, vol. 45(13), pages 1637-1646, May.
    159. Dean Croushore, 2012. "Forecast bias in two dimensions," Working Papers 12-9, Federal Reserve Bank of Philadelphia.
    160. Fildes, Robert, 2015. "Forecasters and rationality—A comment on Fritsche et al., Forecasting the Brazilian Real and Mexican Peso: Asymmetric loss, forecast rationality and forecaster herding," International Journal of Forecasting, Elsevier, vol. 31(1), pages 140-143.
    161. Young Bin Ahn & Yoichi Tsuchiya, 2022. "Consumer’s perceived and expected inflation in Japan—irrationality or asymmetric loss?," Empirical Economics, Springer, vol. 63(3), pages 1247-1292, September.

  10. Elliott, Graham & Muller, Ulrich K., 2004. "Confidence Sets for the Date of a Single Break in Linear Time Series Regressions," University of California at San Diego, Economics Working Paper Series qt9hf4j4c2, Department of Economics, UC San Diego.

    Cited by:

    1. David Hendry & Lea Schneider & Jason E. Smerdon, 2016. "Detecting Volcanic Eruptions in Temperature Reconstructions by Designed Break-Indicator Saturation," Economics Series Working Papers 780, University of Oxford, Department of Economics.
    2. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    3. Boldea, Otilia & Hall, Alastair R., 2013. "Estimation and inference in unstable nonlinear least squares models," Journal of Econometrics, Elsevier, vol. 172(1), pages 158-167.
    4. Abi Morshed, Alaa & Andreou, E. & Boldea, Otilia, 2016. "Structural Break Tests Robust to Regression Misspecification," Discussion Paper 2016-019, Tilburg University, Center for Economic Research.
    5. Ulrich K. Müller & Andriy Norets, 2016. "Coverage Inducing Priors in Nonstandard Inference Problems," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(515), pages 1233-1241, July.
    6. João Pedro Pereira & Vasco Pesquita & Paulo M. M. Rodrigues & António Rua, 2019. "Market integration and the persistence of electricity prices," Empirical Economics, Springer, vol. 57(5), pages 1495-1514, November.
    7. Yamamoto, Yohei & 山本, 庸平, 2014. "A Modified Confidence Set for the Structural Break Date in Linear Regression Models," Discussion Papers 2014-08, Graduate School of Economics, Hitotsubashi University.
    8. Alessandro Casini & Pierre Perron, 2020. "Continuous Record Laplace-based Inference about the Break Date in Structural Change Models," Boston University - Department of Economics - Working Papers Series WP2020-014, Boston University - Department of Economics.
    9. Gloria Gonzalez-Rivera & Yingying Sun, 2016. "Density Forecast Evaluation in Unstable Environments," Working Papers 201606, University of California at Riverside, Department of Economics.
    10. Haiqiang Chen, "undated". "Robust Estimation and Inference for Threshold Models with Integrated Regressors," Working Papers 2013-12-02, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    11. 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.
    12. Alessandro Casini & Pierre Perron, 2018. "Generalized Laplace Inference in Multiple Change-Points Models," Papers 1803.10871, arXiv.org, revised Jan 2021.
    13. Tom Boot & Andreas Pick, 2017. "A near optimal test for structural breaks when forecasting under square error loss," Tinbergen Institute Discussion Papers 17-039/III, Tinbergen Institute.
    14. Hu, Junjie & López Cabrera, Brenda & Melzer, Awdesch, 2021. "Advanced statistical learning on short term load process forecasting," IRTG 1792 Discussion Papers 2021-020, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    15. 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.
    16. Abhimanyu Gupta & Myung Hwan Seo, 2019. "Robust Inference on Infinite and Growing Dimensional Time Series Regression," Papers 1911.08637, arXiv.org, revised Apr 2023.
    17. Jose Manuel Campa & Linda S. Goldberg & Jose M. Gonzalez-Minguez, 2005. "Exchange rate pass-through to import prices in the Euro area," Staff Reports 219, Federal Reserve Bank of New York.
    18. Isaiah Andrews & Toru Kitagawa & Adam McCloskey, 2020. "Inference on winners," CeMMAP working papers CWP43/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    19. Eo, Yunjong & Morley, James C., 2008. "Likelihood-Based Confidence Sets for the Timing of Structural Breaks," MPRA Paper 10372, University Library of Munich, Germany.
    20. Seong Yeon Chang & Pierre Perron, 2013. "A Comparison of Alternative Methods to Construct Confidence Intervals for the Estimate of a Break Date in Linear Regression Models," Boston University - Department of Economics - Working Papers Series wp2015-010, Boston University - Department of Economics, revised 11 Oct 2015.
    21. KUROZUMI, Eiji & 黒住, 英司 & YAMAMOTO, Yohei & 山本, 庸平, 2015. "Confidence Sets for the Break Date Based on Optimal Tests," Discussion Papers 2015-01, Graduate School of Economics, Hitotsubashi University.
    22. Oka, Tatsushi & Qu, Zhongjun, 2011. "Estimating structural changes in regression quantiles," Journal of Econometrics, Elsevier, vol. 162(2), pages 248-267, June.
    23. Linda S. Goldberg & Michael W. Klein, 2007. "Establishing Credibility: Evolving Perceptions of the European Central Bank," The Institute for International Integration Studies Discussion Paper Series iiisdp194, IIIS.
    24. 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.
    25. Zongwu Cai & Seong Yeon Chang, 2018. "A New Test In A Predictive Regression with Structural Breaks," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201811, University of Kansas, Department of Economics, revised Dec 2018.
    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. Elliott, Graham & Müller, Ulrich K, 2014. "Pre and post break parameter inference," University of California at San Diego, Economics Working Paper Series qt4j733246, Department of Economics, UC San Diego.
    28. Tayanagi, Toshikazu & 田柳, 俊和 & Kurozumi, Eiji & 黒住, 英司, 2022. "In-fill asymptotic distribution of the change point estimator when estimating breaks one at a time," Discussion Papers 2022-03, Graduate School of Economics, Hitotsubashi University.
    29. Skrobotov, Anton, 2021. "Structural breaks in cointegration models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 63, pages 117-141.
    30. 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.
    31. Alessandro Casini & Pierre Perron, 2018. "Continuous Record Asymptotics for Change-Points Models," Papers 1803.10881, arXiv.org, revised Nov 2021.
    32. Jiang, Liang & Wang, Xiaohu & Yu, Jun, 2018. "New distribution theory for the estimation of structural break point in mean," Journal of Econometrics, Elsevier, vol. 205(1), pages 156-176.
    33. 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.
    34. Alastair R. Hall & Denise R. Osborn & Nikolaos Sakkas, 2017. "The asymptotic behaviour of the residual sum of squares in models with multiple break points," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 667-698, October.
    35. Isaiah Andrews & Toru Kitagawa & Adam McCloskey, 2020. "Inference after Estimation of Breaks," CeMMAP working papers CWP34/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    36. Hirano, Keisuke & Wright, Jonathan H., 2022. "Analyzing cross-validation for forecasting with structural instability," Journal of Econometrics, Elsevier, vol. 226(1), pages 139-154.
    37. Marmer, Vadim & Shneyerov, Artyom, 2008. "Quantile-Based Nonparametric Inference for First-Price Auctions," Microeconomics.ca working papers marmer-08-01-17-12-16-12, Vancouver School of Economics, revised 16 May 2013.
    38. Eo, Yunjong & Morley, James, 2011. "Likelihood-Ratio-Based Confidence Sets for the Timing of Structural Breaks," Working Papers 2011-07, University of Sydney, School of Economics, revised Feb 2014.
    39. Yaein Baek, 2018. "Estimation of a Structural Break Point in Linear Regression Models," Papers 1811.03720, arXiv.org, revised Jun 2020.
    40. 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.
    41. Yoonseok Lee & Yulong Wang, 2020. "Inference in Threshold Models," Center for Policy Research Working Papers 223, Center for Policy Research, Maxwell School, Syracuse University.
    42. Alessandro Casini & Taosong Deng & Pierre Perron, 2021. "Theory of Low Frequency Contamination from Nonstationarity and Misspecification: Consequences for HAR Inference," Papers 2103.01604, arXiv.org, revised Sep 2024.
    43. Gregory Cox, 2022. "A Generalized Argmax Theorem with Applications," Papers 2209.08793, arXiv.org.
    44. Yao Rao & Brendan McCabe, 2018. "Structural Change and the Problem of Phantom Break Locations," Working Papers 20185, University of Liverpool, Department of Economics.
    45. 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.
    46. Gantungalag Altansukh & Denise R. Osborn, 2022. "Using structural break inference for forecasting time series," Empirical Economics, Springer, vol. 63(1), pages 1-41, July.
    47. Song Shi & Vince Mangioni & Xin Janet Ge & Shanaka Herath & Fethi Rabhi & Rachida Ouysse, 2021. "House Price Forecasting from Investment Perspectives," Land, MDPI, vol. 10(10), pages 1-17, September.
    48. 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.
    49. Boot, Tom & Pick, Andreas, 2020. "Does modeling a structural break improve forecast accuracy?," Journal of Econometrics, Elsevier, vol. 215(1), pages 35-59.
    50. Tuvaandorj, Purevdorj, 2020. "Regression discontinuity designs, white noise models, and minimax," Journal of Econometrics, Elsevier, vol. 218(2), pages 587-608.

  11. Timmermann, Allan & Elliott, Graham & Komunjer, Ivana, 2003. "Estimating Loss Function Parameters," CEPR Discussion Papers 3821, C.E.P.R. Discussion Papers.

    Cited by:

    1. Martin Skitmore & Franco K. T. Cheung, 2007. "Explorations in specifying construction price forecast loss functions," Construction Management and Economics, Taylor & Francis Journals, vol. 25(5), pages 449-465.
    2. Graham Elliott & Ivana Komunjer & Allan Timmermann, 2008. "Biases in Macroeconomic Forecasts: Irrationality or Asymmetric Loss?," Journal of the European Economic Association, MIT Press, vol. 6(1), pages 122-157, March.
    3. Stan Hurn & Ralf Becker, 2006. "Testing for nonlinearity in mean in the presence of heteroskedasticity," Stan Hurn Discussion Papers 2006-02, School of Economics and Finance, Queensland University of Technology.
    4. Siliverstovs, Boriss & Engsted, Tom & Haldrup, Niels, 2002. "Long-Run Forecasting in Multicointegrated Systems," Finance Working Papers 02-14, University of Aarhus, Aarhus School of Business, Department of Business Studies.
    5. Basu, Sudipta & Markov, Stanimir, 2004. "Loss function assumptions in rational expectations tests on financial analysts' earnings forecasts," Journal of Accounting and Economics, Elsevier, vol. 38(1), pages 171-203, December.
    6. Yang Yang & Tae-Hwy Lee, 2004. "Bagging Binary Predictors for Time Series," Econometric Society 2004 Far Eastern Meetings 512, Econometric Society.
    7. Lee, Tae-Hwy & Yang, Yang, 2006. "Bagging binary and quantile predictors for time series," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 465-497.
    8. Allan Timmermann & Andrew J. Patton, 2004. "Properties of Optimal Forecasts," Econometric Society 2004 North American Winter Meetings 234, Econometric Society.
    9. Adrian Pagan & Hashem Pesaran, 2007. "Econometric Analysis of Structural Systems with Permanent and Transitory Shocks. Working paper #7," NCER Working Paper Series 7, National Centre for Econometric Research.
    10. Pedro Henrique Melo Albuquerque & Yaohao Peng & João Pedro Fontoura da Silva, 2022. "Making the whole greater than the sum of its parts: A literature review of ensemble methods for financial time series forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(8), pages 1701-1724, December.
    11. Alexander, Marcus & Christakis, Nicholas A., 2008. "Bias and asymmetric loss in expert forecasts: A study of physician prognostic behavior with respect to patient survival," Journal of Health Economics, Elsevier, vol. 27(4), pages 1095-1108, July.

  12. Elliott, Graham & Timmermann, Allan, 2002. "Optimal Forecast Combination Under General Loss Functions and Forecast Error Distributions," University of California at San Diego, Economics Working Paper Series qt15r9t2q2, Department of Economics, UC San Diego.

    Cited by:

    1. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    2. 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.
    3. Carlos Capistrán-Carmona, 2005. "Bias in Federal Reserve Inflation Forecasts: Is the Federal Reserve Irrational or Just Cautious?," Computing in Economics and Finance 2005 127, Society for Computational Economics.
    4. Aretz, Kevin & Bartram, Söhnke M. & Pope, Peter F., 2011. "Asymmetric Loss Functions and the Rationality of Expected Stock Returns," MPRA Paper 47343, University Library of Munich, Germany.
    5. Mehmet Pinar & Thanasis Stengos & M. Ege Yazgan, 2018. "Quantile forecast combination using stochastic dominance," Empirical Economics, Springer, vol. 55(4), pages 1717-1755, December.
    6. Jiang Wu & Jianzhong Zhou & Lu Chen & Lei Ye, 2015. "Coupling Forecast Methods of Multiple Rainfall–Runoff Models for Improving the Precision of Hydrological Forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(14), pages 5091-5108, November.
    7. Golosnoy, Vasyl & Hamid, Alain & Okhrin, Yarema, 2014. "The empirical similarity approach for volatility prediction," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 321-329.
    8. Cecilia Frale & Libero Monteforte, "undated". "FaMIDAS: A Mixed Frequency Factor Model with MIDAS structure," Working Papers 3, Department of the Treasury, Ministry of the Economy and of Finance.
    9. Barrow, Devon K. & Kourentzes, Nikolaos, 2016. "Distributions of forecasting errors of forecast combinations: Implications for inventory management," International Journal of Production Economics, Elsevier, vol. 177(C), pages 24-33.
    10. Giacomini, Raffaella & Komunjer, Ivana, 2002. "Evaluation and Combination of Conditional Quantile Forecasts," University of California at San Diego, Economics Working Paper Series qt4n99t4wz, Department of Economics, UC San Diego.
    11. Jan R. Magnus & Wendun Wang & Xinyu Zhang, 2016. "Weighted-Average Least Squares Prediction," Econometric Reviews, Taylor & Francis Journals, vol. 35(6), pages 1040-1074, June.
    12. Patton, Andrew J. & Timmermann, Allan, 2007. "Properties of optimal forecasts under asymmetric loss and nonlinearity," Journal of Econometrics, Elsevier, vol. 140(2), pages 884-918, October.
    13. Wagner Piazza Gaglianone & Luiz Renato Lima, 2014. "Constructing Optimal Density Forecasts From Point Forecast Combinations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(5), pages 736-757, August.
    14. Matteo Iacopini & Francesco Ravazzolo & Luca Rossini, 2020. "Proper scoring rules for evaluating asymmetry in density forecasting," Working Papers No 06/2020, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    15. Heather M. Anderson & Farshid Vahid, 2005. "Nonlinear Correlograms and Partial Autocorrelograms," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(s1), pages 957-982, December.
    16. Valentina Corradi & Norman Swanson, 2013. "A Survey of Recent Advances in Forecast Accuracy Comparison Testing, with an Extension to Stochastic Dominance," Departmental Working Papers 201309, Rutgers University, Department of Economics.
    17. Todd E. Clark & Michael W. McCracken, 2004. "Improving forecast accuracy by combining recursive and rolling forecasts," Research Working Paper RWP 04-10, Federal Reserve Bank of Kansas City.
    18. Jakub Nowotarski, 2013. "Short-term forecasting of electricity spot prices using model averaging (Krótkoterminowe prognozowanie spotowych cen energii elektrycznej z wykorzystaniem uśredniania modeli)," HSC Research Reports HSC/13/17, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    19. Xing, Li-Min & Zhang, Yue-Jun, 2022. "Forecasting crude oil prices with shrinkage methods: Can nonconvex penalty and Huber loss help?," Energy Economics, Elsevier, vol. 110(C).
    20. Coshall, John T. & Charlesworth, Richard, 2011. "A management orientated approach to combination forecasting of tourism demand," Tourism Management, Elsevier, vol. 32(4), pages 759-769.
    21. Jana Eklund & Sune Karlsson, 2007. "Forecast Combination and Model Averaging Using Predictive Measures," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 329-363.
    22. Demetrescu, Matei & Hacioglu Hoke, Sinem, 2018. "Predictive regressions under asymmetric loss: factor augmentation and model selection," Bank of England working papers 723, Bank of England.
    23. 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.
    24. Barbara Będowska-Sójka, 2018. "Is intraday data useful for forecasting VaR? The evidence from EUR/PLN exchange rate," Risk Management, Palgrave Macmillan, vol. 20(4), pages 326-346, November.
    25. Aiolfi, Marco & Timmermann, Allan, 2006. "Persistence in forecasting performance and conditional combination strategies," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 31-53.
    26. Sainan Jin & Valentina Corradi & Norman Swanson, 2015. "Robust Forecast Comparison," Departmental Working Papers 201502, Rutgers University, Department of Economics.
    27. Timmermann, Allan & Elliott, Graham, 2007. "Economic Forecasting," CEPR Discussion Papers 6158, C.E.P.R. Discussion Papers.
    28. Viviano, Davide & Bradic, Jelena, 2023. "Synthetic Learner: Model-free inference on treatments over time," Journal of Econometrics, Elsevier, vol. 234(2), pages 691-713.
    29. Ekaterina V. Astafyeva & Maria Yu. Turuntseva, 2023. "Analysis of Opportunities to Improve the Quality of Natural Resource Price by Combining Forecasts Resulting from Methods Based on Regression Estimates of Weights [Анализ Возможностей Улучшения Каче," Russian Economic Development, Gaidar Institute for Economic Policy, issue 12, pages 24-33, December.
    30. Wei, Xiaoqiao & Yang, Yuhong, 2012. "Robust forecast combinations," Journal of Econometrics, Elsevier, vol. 166(2), pages 224-236.
    31. Heijmans, Roweno J.R.K. & Gerlagh, Reyer, 2019. "Regulating Global Externalities," Other publications TiSEM 9a0a6f7a-f8d0-4495-8aed-4, Tilburg University, School of Economics and Management.
    32. Norman R. Swanson & Weiqi Xiong, 2018. "Big data analytics in economics: What have we learned so far, and where should we go from here?," Canadian Journal of Economics, Canadian Economics Association, vol. 51(3), pages 695-746, August.
    33. Xu, Yexiao, 2004. "Small levels of predictability and large economic gains," Journal of Empirical Finance, Elsevier, vol. 11(2), pages 247-275, March.
    34. Aiolfi Marco & Capistrán Carlos & Timmermann Allan, 2010. "Forecast Combinations," Working Papers 2010-04, Banco de México.
    35. Massimo Guidolin, 2011. "Markov Switching Models in Empirical Finance," Working Papers 415, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    36. Marco Aiolfi & Carlo Ambrogio Favero, "undated". "Model Uncertainty, Thick Modelling and the predictability of Stock Returns," Working Papers 221, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    37. 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.
    38. Todd E. Clark & Michael W. McCracken, 2009. "Combining Forecasts from Nested Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(3), pages 303-329, June.
    39. Cheng, Gang & Yang, Yuhong, 2015. "Forecast combination with outlier protection," International Journal of Forecasting, Elsevier, vol. 31(2), pages 223-237.
    40. Sancetta, A., 2007. "Online Forecast Combination for Dependent Heterogeneous Data," Cambridge Working Papers in Economics 0718, Faculty of Economics, University of Cambridge.
    41. George Athanasopoulos & Rob J Hyndman & Nikolaos Kourentzes & Fotios Petropoulos, 2015. "Forecasting with Temporal Hierarchies," Monash Econometrics and Business Statistics Working Papers 16/15, Monash University, Department of Econometrics and Business Statistics.
    42. Norman Swanson & Valentina Corradi, 2006. "Nonparametric Bootstrap Procedures for Predictive Inference Based on Recursive Estimation Schemes," Departmental Working Papers 200618, Rutgers University, Department of Economics.
    43. Massimiliano Giacalone, 2022. "Optimal forecasting accuracy using Lp-norm combination," METRON, Springer;Sapienza Università di Roma, vol. 80(2), pages 187-230, August.
    44. Sancetta, A. & Satchell, S.E., 2004. "Cost of Capital and Regulator’s Preferences: Investigation into a new method of estimating regulatory bias," Cambridge Working Papers in Economics 0441, Faculty of Economics, University of Cambridge.
    45. Martin Baumgärtner & Jens Klose, 2019. "Forecasting exchange rates with commodity prices—a global country analysis," The World Economy, Wiley Blackwell, vol. 42(9), pages 2546-2565, September.
    46. Massimo Guidolin & Carrie Fangzhou Na, 2007. "The economic and statistical value of forecast combinations under regime switching: an application to predictable U.S. returns," Working Papers 2006-059, Federal Reserve Bank of St. Louis.
    47. Gneiting, Tilmann, 2011. "Quantiles as optimal point forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 197-207, April.
    48. Alessandro Riboni & Francisco Ruge-Murcia, 2020. "The Power of the Federal Reserve Chair," Cahiers de recherche 20-2020, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    49. Chanont Banternghansa & Michael W. McCracken, 2010. "Real-time forecast averaging with ALFRED," Working Papers 2010-033, Federal Reserve Bank of St. Louis.
    50. Lima, Luiz Renato Regis de Oliveira & Issler, João Victor, 2007. "A panel data approach to economic forecasting: the bias-corrected average forecast," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 650, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    51. Elena Andreou & Eric Ghysels & Constantinos Kourouyiannis, 2012. "Robust volatility forecasts in the presence of structural breaks," University of Cyprus Working Papers in Economics 08-2012, University of Cyprus Department of Economics.
    52. Gaglianone, Wagner Piazza & Issler, João Victor, 2019. "Microfounded forecasting," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 813, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    53. Clements, Michael P. & Harvey, David I., 2011. "Combining probability forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 208-223, April.
    54. Xiaohong Chen & Yanqin Fan, 2004. "Estimation and Model Selection of Semiparametric Copula-Based Multivariate Dynamic Models under Copula Misspecification," Vanderbilt University Department of Economics Working Papers 0419, Vanderbilt University Department of Economics, revised Sep 2004.
    55. Magnus, J.R. & Wang, W. & Zhang, Xinyu, 2012. "WALS Prediction," Discussion Paper 2012-043, Tilburg University, Center for Economic Research.
    56. Heijmans, Roweno J.R.K. & Gerlagh, Reyer, 2019. "Regulating Global Externalities," Discussion Paper 2019-001, Tilburg University, Center for Economic Research.
    57. Qing Zhou & Robert Faff, 2017. "The complementary role of cross-sectional and time-series information in forecasting stock returns," Australian Journal of Management, Australian School of Business, vol. 42(1), pages 113-139, February.
    58. Taylor, James W., 2020. "Forecast combinations for value at risk and expected shortfall," International Journal of Forecasting, Elsevier, vol. 36(2), pages 428-441.
    59. 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).
    60. Wagner Piazza Gaglianone & João Victor Issler & Silvia Maria Matos, 2017. "Applying a microfounded-forecasting approach to predict Brazilian inflation," Empirical Economics, Springer, vol. 53(1), pages 137-163, August.
    61. Laborda, Ricardo, 2018. "Optimal combination of currency strategies," The North American Journal of Economics and Finance, Elsevier, vol. 43(C), pages 129-140.
    62. Valentina Corradi & Norman Swanson, 2004. "Bootstrap Procedures for Recursive Estimation Schemes With Applications to Forecast Model Selection," Departmental Working Papers 200418, Rutgers University, Department of Economics.
    63. Luke Hartigan, 2016. "Alternative HAC Covariance Matrix Estimators with Improved Finite Sample Properties," Discussion Papers 2016-06, School of Economics, The University of New South Wales.
    64. Elena Andreou & Constantinos Kourouyiannis & Andros Kourtellos, 2012. "Volatility Forecast Combinations using Asymmetric Loss Functions," University of Cyprus Working Papers in Economics 07-2012, University of Cyprus Department of Economics.
    65. Xinyu Zhang & Alan T. K. Wan & Sherry Z. Zhou, 2011. "Focused Information Criteria, Model Selection, and Model Averaging in a Tobit Model With a Nonzero Threshold," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 132-142, June.
    66. Chotikapanich, D. & Griffiths, W.E. & Rao, D.S.P., 2001. "Averaging Income Distributions," Department of Economics - Working Papers Series 798, The University of Melbourne.
    67. Gneiting, Tilmann, 2011. "Quantiles as optimal point forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 197-207.
    68. 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.
    69. Ulrich Gunter & Irem Önder & Egon Smeral, 2020. "Are Combined Tourism Forecasts Better at Minimizing Forecasting Errors?," Forecasting, MDPI, vol. 2(3), pages 1-19, June.
    70. Egorov, Alexei V. & Hong, Yongmiao & Li, Haitao, 2006. "Validating forecasts of the joint probability density of bond yields: Can affine models beat random walk?," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 255-284.
    71. Gary Cornwall & Jeff Chen & Beau Sauley, 2021. "Standing on the Shoulders of Machine Learning: Can We Improve Hypothesis Testing?," Papers 2103.01368, arXiv.org.
    72. Matei Demetrescu, 2007. "Optimal forecast intervals under asymmetric loss," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(4), pages 227-238.
    73. Andrea Carriero & Raffaella Giacomini, 2011. "How useful are no-arbitrage restrictions for forecasting the term structure of interest rates?," Post-Print hal-00844809, HAL.
    74. John Galbraith & Greg Tkacz, 2007. "How Far Can Forecasting Models Forecast? Forecast Content Horizons for Some Important Macroeconomic Variables," Staff Working Papers 07-1, Bank of Canada.
    75. Kocięcki, Andrzej & Kolasa, Marcin & Rubaszek, Michał, 2012. "A Bayesian method of combining judgmental and model-based density forecasts," Economic Modelling, Elsevier, vol. 29(4), pages 1349-1355.
    76. Zongwu Cai & Chaoqun Ma & Xianhua Mi, 2020. "Realized Volatility Forecasting Based on Dynamic Quantile Model Averaging," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202016, University of Kansas, Department of Economics, revised Sep 2020.
    77. Capistrán Carlos, 2007. "Optimality Tests for Multi-Horizon Forecasts," Working Papers 2007-14, Banco de México.
    78. Kevin Aretz & David Peel, 2007. "Some implications of a quartic loss function," Economics Bulletin, AccessEcon, vol. 7(13), pages 1-7.
    79. Alexander, Marcus & Christakis, Nicholas A., 2008. "Bias and asymmetric loss in expert forecasts: A study of physician prognostic behavior with respect to patient survival," Journal of Health Economics, Elsevier, vol. 27(4), pages 1095-1108, July.
    80. Sancetta, Alessio, 2007. "Online forecast combinations of distributions: Worst case bounds," Journal of Econometrics, Elsevier, vol. 141(2), pages 621-651, December.
    81. Magnus, J.R. & Wang, W. & Zhang, Xinyu, 2012. "WALS Prediction," Other publications TiSEM 7715e942-b446-4985-8216-f, Tilburg University, School of Economics and Management.

  13. Ulrich K. Müller & Graham Elliott, 2001. "Tests for Unit Roots and the Initial Observation," University of St. Gallen Department of Economics working paper series 2002 2002-02, Department of Economics, University of St. Gallen.

    Cited by:

    1. Ulrich K. Müller, 2002. "Size and Power of Tests for Stationarity in Highly Autocorrelated Time Series," University of St. Gallen Department of Economics working paper series 2002 2002-26, Department of Economics, University of St. Gallen.
    2. Muller, Ulrich K., 2005. "Size and power of tests of stationarity in highly autocorrelated time series," Journal of Econometrics, Elsevier, vol. 128(2), pages 195-213, October.

  14. Elliott, Graham & STOCK, JAMES H, 2000. "Confidence Intervals for Autoregressive Coefficients Near One," University of California at San Diego, Economics Working Paper Series qt6ww3p59v, Department of Economics, UC San Diego.

    Cited by:

    1. Ulrich K. Müller & Andriy Norets, 2016. "Coverage Inducing Priors in Nonstandard Inference Problems," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(515), pages 1233-1241, July.
    2. Andrews, Donald W.K. & Guggenberger, Patrik, 2012. "Asymptotics for LS, GLS, and feasible GLS statistics in an AR(1) model with conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 169(2), pages 196-210.
    3. Thabo M. Mokoena & Gupta, R. & Van Eyden, R., 2009. "Half-Life Deviations from PPP in the South African Development Community (SADC)," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 9(1).
    4. Lopez, Claude & Murray, Chris & Papell, David, 2009. "Median-Unbiased Estimation in DF-GLS Regressions and the PPP Puzzle," MPRA Paper 26091, University Library of Munich, Germany.
    5. Donald W. K. Andrews & Patrik Guggenberger, 2008. "Asymptotics for stationary very nearly unit root processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(1), pages 203-212, January.
    6. Pesavento, Elena & Rossi, Barbara, 2005. "Do Technology Shocks Drive Hours Up Or Down? A Little Evidence From An Agnostic Procedure," Macroeconomic Dynamics, Cambridge University Press, vol. 9(4), pages 478-488, September.
    7. Rossi, Barbara & Pesavento, Elena, 2003. "Small Sample Confidence Intervals for Multivariate Impulse Response Functions at Long Horizons," Working Papers 03-19, Duke University, Department of Economics.
    8. Liyu Dou & Ulrich K. Müller, 2021. "Generalized Local‐to‐Unity Models," Econometrica, Econometric Society, vol. 89(4), pages 1825-1854, July.
    9. Rossi, Barbara, 2005. "Confidence Intervals for Half-Life Deviations From Purchasing Power Parity," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 432-442, October.
    10. Barbara Rossi & Elena Pesavento, 2004. "Do Technology Shocks Drive Hours Up or Down?," Econometric Society 2004 North American Summer Meetings 96, Econometric Society.
    11. Broda, Simon & Paolella, Marc S. & Carstensen, Kai, 2007. "Bias-adjusted estimation in the ARX(1) model," Munich Reprints in Economics 19992, University of Munich, Department of Economics.
    12. Firouz Fallahi & Gabriel Rodríguez, 2011. "Persistence of Unemployment in the Canadian Provinces," International Regional Science Review, , vol. 34(4), pages 438-458, October.
    13. Chambers, MJ, 2013. "The Calculation of Some Limiting Distributions Arising in Near-Integrated Models with GLS Detrending," Economics Discussion Papers 8975, University of Essex, Department of Economics.
    14. Donald W. K. Andrews & Patrik Guggenberger, 2014. "A Conditional-Heteroskedasticity-Robust Confidence Interval for the Autoregressive Parameter," The Review of Economics and Statistics, MIT Press, vol. 96(2), pages 376-381, May.
    15. John Y. Campbell & Motohiro Yogo, 2002. "Efficient Tests of Stock Return Predictability," Harvard Institute of Economic Research Working Papers 1972, Harvard - Institute of Economic Research.
    16. Donald W.K. Andrews & Patrik Guggenberger, 2007. "Hybrid and Size-Corrected Subsample Methods," Cowles Foundation Discussion Papers 1606, Cowles Foundation for Research in Economics, Yale University.
    17. 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.
    18. Donald W.K. Andrews & Xu Cheng & Patrik Guggenberger, 2011. "Generic Results for Establishing the Asymptotic Size of Confidence Sets and Tests," Cowles Foundation Discussion Papers 1813, Cowles Foundation for Research in Economics, Yale University.
    19. Ulrich K. Müller & Mark W. Watson, 2020. "Low-Frequency Analysis of Economic Time Series," Working Papers 2020-13, Princeton University. Economics Department..
    20. Pitarakis, Jean-Yves, 2019. "Predictive Regressions," UC3M Working papers. Economics 28554, Universidad Carlos III de Madrid. Departamento de Economía.
    21. Jean Imbs & Haroon Mumtaz & Morton O. Ravn & Helene Rey, 2002. "PPP Strikes Back: Aggregation and the Real Exchange Rate," NBER Working Papers 9372, National Bureau of Economic Research, Inc.
    22. Yu-chin Chen & Kenneth Rogoff, 2006. "Are the Commodity Currencies an Exception to the Rule?," Working Papers UWEC-2006-28, University of Washington, Department of Economics, revised Mar 2012.
    23. Peter C.B. Phillips, 2012. "On Confidence Intervals for Autoregressive Roots and Predictive Regression," Cowles Foundation Discussion Papers 1879, Cowles Foundation for Research in Economics, Yale University.
    24. Kang, Natasha & Marmer, Vadim, 2020. "Modeling Long Cycles," Economics working papers vadim_marmer-2020-3, Vancouver School of Economics, revised 26 Oct 2020.
    25. Muller, Ulrich K., 2005. "Size and power of tests of stationarity in highly autocorrelated time series," Journal of Econometrics, Elsevier, vol. 128(2), pages 195-213, October.
    26. Kiviet, Jan F. & Niemczyk, Jerzy, 2007. "The asymptotic and finite sample distributions of OLS and simple IV in simultaneous equations," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3296-3318, April.
    27. Kittel, Bernhard & Winner, Hannes, 2002. "How reliable is pooled analysis in political economy? The globalization welfare state nexus revisited," MPIfG Discussion Paper 02/3, Max Planck Institute for the Study of Societies.
    28. Jardet, C. & Monfort, A. & Pegoraro, F., 2009. "No-arbitrage Near-Cointegrated VAR(p) Term Structure Models, Term Premia and GDP Growth," Working papers 234, Banque de France.
    29. Ronald W. Butler & Marc S. Paolella, 2017. "Autoregressive Lag—Order Selection Using Conditional Saddlepoint Approximations," Econometrics, MDPI, vol. 5(3), pages 1-33, September.
    30. 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.
    31. Pradeep Agrawal, 2014. "The Role of Exports in India's Economic Growth," IEG Working Papers 345 JEL Classification: O, Institute of Economic Growth.

  15. Elliott, Graham, 1999. "Estimating Restricted Cointegrating Vectors," University of California at San Diego, Economics Working Paper Series qt5sr55716, Department of Economics, UC San Diego.

    Cited by:

    1. Richard G. Anderson & Hailong Qian & Robert H. Rasche, 2006. "Analysis of panel vector error correction models using maximum likelihood, the bootstrap, and canonical-correlation estimators," Working Papers 2006-050, Federal Reserve Bank of St. Louis.
    2. Atle Oglend, Morten E. Lindbäck, and Petter Osmundsen, 2015. "Shale Gas Boom Affecting the Relationship Between LPG and Oil Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    3. Peter Reinhard Hansen, 2000. "Structural Changes in the Cointegrated Vector Autoregressive Model," Working Papers 2000-20, Brown University, Department of Economics.
    4. H. Peter Boswijk & Jurgen A. Doornik, 2004. "Identifying, estimating and testing restricted cointegrated systems: An overview," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 58(4), pages 440-465, November.
    5. Lindback, Morten & Osmundsen, Petter & Øglend, Atle, 2013. "Shale Gas and the Relationship between U.S. Natural Gas, Liquified Petroleum Gases and Oil Market," UiS Working Papers in Economics and Finance 2013/5, University of Stavanger.
    6. Considine, Timothy J., 2018. "Estimating concave substitution possibilities with non-stationary data using the dynamic linear logit demand model," Economic Modelling, Elsevier, vol. 72(C), pages 22-30.

  16. Graham Elliott & Takatoshi Ito, 1998. "Heterogeneous Expectations and Tests of Efficiency in the Yen/Dollar Forward Exchange rate Market," Discussion Paper Series a347, Institute of Economic Research, Hitotsubashi University.

    Cited by:

    1. Pesaran, M. Hashem & Weale, Martin, 2006. "Survey Expectations," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 14, pages 715-776, Elsevier.
    2. Reitz, Stefan & Rülke, Jan & Stadtmann, Georg, 2012. "Nonlinear Expectations in Speculative Markets," VfS Annual Conference 2012 (Goettingen): New Approaches and Challenges for the Labor Market of the 21st Century 62045, Verein für Socialpolitik / German Economic Association.
    3. Li, Xue & Liu, Yanghui & Li, Hanxu & Li, Jie, 2021. "Onshore spot and offshore forward markets for RMB: Evidence from the “8.11” exchange rate regime reform," China Economic Review, Elsevier, vol. 67(C).
    4. Rime, Dagfinn & Sarno, Lucio & Sojli, Elvira, 2010. "Exchange rate forecasting, order flow and macroeconomic information," Journal of International Economics, Elsevier, vol. 80(1), pages 72-88, January.
    5. Michel Beine & Agnes Bénassy-Quéré & Ronald MacDonald, 2007. "The impact of Central Bank intervention on exchange rate forecasts heterogeneity," ULB Institutional Repository 2013/10423, ULB -- Universite Libre de Bruxelles.
    6. Stijn Claessens & M Ayhan Kose, 2018. "Frontiers of macrofinancial linkages," BIS Papers, Bank for International Settlements, number 95.
    7. Reitz, Stefan & Rülke, Jan-Christoph & Stadtmann, Georg, 2012. "Nonlinear expectations in speculative markets: Evidence from the ECB survey of professional forecasters," Discussion Papers 311, European University Viadrina Frankfurt (Oder), Department of Business Administration and Economics.
    8. Jongen, R. & Muller, A. & Verschoor, W.F.C., 2012. "Using survey data to resolve the exchange risk exposure puzzle: Evidence from U.S. multinational firms," Journal of International Money and Finance, Elsevier, vol. 31(2), pages 148-169.
    9. Ken Miyajima, 2013. "Foreign exchange intervention and expectation in emerging economies," BIS Working Papers 414, Bank for International Settlements.
    10. Reitz Stefan & Rülke Jan-Christoph & Stadtmann Georg, 2010. "Regressive Oil Price Expectations Toward More Fundamental Values of the Oil Price," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 230(4), pages 454-466, August.
    11. Ken Miyajima & Carlos Montoro, 2013. "Impact of foreign exchange interventions on exchange rate expectations," BIS Papers chapters, in: Bank for International Settlements (ed.), Sovereign risk: a world without risk-free assets?, volume 73, pages 39-54, Bank for International Settlements.
    12. Philippe Bacchetta & Eric van Wincoop, 2003. "Can Information Heterogeneity Explain the Exchange Rate Determination Puzzle?," Working Papers 03.02, Swiss National Bank, Study Center Gerzensee.
    13. Beckmann, Joscha & Czudaj, Robert, 2017. "Exchange rate expectations since the financial crisis: Performance evaluation and the role of monetary policy and safe haven," Journal of International Money and Finance, Elsevier, vol. 74(C), pages 283-300.
    14. Pierdzioch, Christian & Rülke, Jan-Christoph & Stadtmann, Georg, 2011. "Forecasting U.S. car sales and car registrations in Japan: Rationality, accuracy and herding," Japan and the World Economy, Elsevier, vol. 23(4), pages 253-258.
    15. Michel Beine & Agnès Bénassy-Quéré & Hélène Colas, 2003. "Imitation Amongst Exchange-Rate Forecasters: Evidence from Survey Data," Working Papers 2003-08, CEPII research center.
    16. Jongen, Ron & Verschoor, Willem F.C. & Wolff, Christian C.P., 2011. "Time-variation in term premia: International survey-based evidence," Journal of International Money and Finance, Elsevier, vol. 30(4), pages 605-622, June.
    17. Sager, Michael & Taylor, Mark P., 2014. "Generating currency trading rules from the term structure of forward foreign exchange premia," Journal of International Money and Finance, Elsevier, vol. 44(C), pages 230-250.
    18. Fisher, Eric O'N., 2006. "The forward premium in a model with heterogeneous prior beliefs," Journal of International Money and Finance, Elsevier, vol. 25(1), pages 48-70, February.
    19. Pierdzioch, Christian & Rülke, Jan Christoph & Stadtmann, Georg, 2012. "Housing starts in Canada, Japan, and the United States: Do forecasters herd?," Discussion Papers 320, European University Viadrina Frankfurt (Oder), Department of Business Administration and Economics.
    20. Richard H. Cohen & Carl Bonham, 2007. "Specifying the Forecast Generating Process for Exchange Rate Survey Forecasts," Working Papers 200718, University of Hawaii at Manoa, Department of Economics.
    21. Jan Christoph Ruelke & Christian Pierdzioch & Georg Stadtmann, 2011. "On the Internal Consistency of Short-Term, Medium-Term, and Long-Term Oil Price Forecasts," Post-Print hal-00708542, HAL.
    22. Frenkel, Michael & Rülke, Jan-Christoph & Stadtmann, Georg, 2009. "Two currencies, one model? Evidence from the Wall Street Journal forecast poll," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 19(4), pages 588-596, October.
    23. Ron Jongen & Willem F.C. Verschoor & Christian C.P. Wolff, 2008. "Foreign Exchange Rate Expectations: Survey And Synthesis," Journal of Economic Surveys, Wiley Blackwell, vol. 22(1), pages 140-165, February.
    24. Andrade, Sandro C. & Kohlscheen, Emanuel, 2010. "Pessimistic Foreign Investors and Turmoil in Emerging Markets : The Case of Brazil in 2002," The Warwick Economics Research Paper Series (TWERPS) 926, University of Warwick, Department of Economics.
    25. Francesca Pancotto & Giuseppe Pignataro & Davide Raggi, 2015. "Social Learning and Higher Order Beliefs: A Structural Model of Exchange Rates Dynamics," LEM Papers Series 2015/24, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    26. Reitz, Stefan & Stadtmann, Georg & Taylor, Mark P., 2010. "The effects of Japanese interventions on FX-forecast heterogeneity," Economics Letters, Elsevier, vol. 108(1), pages 62-64, July.
    27. MacDonald, Ronald & Menkhoff, Lukas & Rebitzky, Rafael R., 2009. "Exchange rate forecasters’ performance: evidence of skill?," SIRE Discussion Papers 2009-10, Scottish Institute for Research in Economics (SIRE).
    28. mamatzakis, e & Christodoulakis, G, 2013. "Behavioural Asymmetries in the G7 Foreign Exchange Market," MPRA Paper 51615, University Library of Munich, Germany.
    29. Frenkel, Michael & Lis, Eliza M. & Rülke, Jan-Christoph, 2011. "Has the economic crisis of 2007-2009 changed the expectation formation process in the Euro area?," Economic Modelling, Elsevier, vol. 28(4), pages 1808-1814, July.
    30. Hommes, Cars, 2011. "The heterogeneous expectations hypothesis: Some evidence from the lab," Journal of Economic Dynamics and Control, Elsevier, vol. 35(1), pages 1-24, January.
    31. Christian Dreger & Georg Stadtmann, 2008. "What drives heterogeneity in foreign exchange rate expectations: insights from a new survey," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 13(4), pages 360-367.
    32. Michael Melvin & John Prins & Duncan Shand, 2013. "Forecasting Exchange Rates: An Investor Perspective," CESifo Working Paper Series 4238, CESifo.
    33. Pasquale Della Corte & Lucio Sarno & Giulia Sestieri, 2012. "The Predictive Information Content of External Imbalances for Exchange Rate Returns: How Much Is It Worth?," The Review of Economics and Statistics, MIT Press, vol. 94(1), pages 100-115, February.
    34. Fritsche, Ulrich & Pierdzioch, Christian & Rülke, Jan-Christoph & Stadtmann, Georg, 2015. "Forecasting the Brazilian real and the Mexican peso: Asymmetric loss, forecast rationality, and forecaster herding," International Journal of Forecasting, Elsevier, vol. 31(1), pages 130-139.
    35. Park, Cheolbeom & Park, Sookyung, 2017. "Can monetary policy cause the uncovered interest parity puzzle?," Japan and the World Economy, Elsevier, vol. 41(C), pages 34-44.
    36. Reitz, Stefan & Ruelke, Jan & Stadtmann, Georg, 2009. "Are oil-price-forecasters finally right? -- Regressive expectations towards more fundamental values of the oil price," MPRA Paper 15607, University Library of Munich, Germany.
    37. Christian Pierdzioch & Jan-Christoph Rülke & Georg Stadtmann, 2012. "Exchange-rate forecasts and asymmetric loss: empirical evidence for the yen/dollar exchange rate," Applied Economics Letters, Taylor & Francis Journals, vol. 19(18), pages 1759-1763, December.
    38. Kose, M. Ayhan & Claessens, Stijn, 2017. "Asset Prices and Macroeconomic Outcomes: A Survey," CEPR Discussion Papers 12460, C.E.P.R. Discussion Papers.
    39. Michael Frenkel & Jan Christoph Rülke & Lilli Zimmermann, 2011. "Do Current Account Forecasters Herd? – Evidence from the Euro Area and the G7 Countries," WHU Working Paper Series - Economics Group 11-01, WHU - Otto Beisheim School of Management.
    40. Jan-Christoph Rülke, 2012. "Are central bank projections rational?," Applied Economics Letters, Taylor & Francis Journals, vol. 19(13), pages 1257-1263, September.
    41. Ronald MacDonald & Lukas Menkhoff & Rafael R. Rebitzky, 2009. "Exchange rate forecasters’ performance: evidence of skill?," Working Papers 2009_13, Business School - Economics, University of Glasgow.
    42. Domenico Colucci & Vincenzo Valori, 2008. "Asset Price Dynamics When Behavioural Heterogeneity Varies," Computational Economics, Springer;Society for Computational Economics, vol. 32(1), pages 3-20, September.
    43. Dick, Christian D. & MacDonald, Ronald & Menkhoff, Lukas, 2014. "Exchange rate forecasts and expected fundamentals," Kiel Working Papers 1974, Kiel Institute for the World Economy (IfW Kiel).
    44. Francesca Pancotto & Filippo Maria Pericoli & Marco Pistagnesi, 2013. "Inefficiency in Survey Exchange Rates Forecasts," Center for Economic Research (RECent) 090, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
    45. Lukas Menkhoff & Rafael R. Rebitzky & Michael Schröder, 2008. "Heterogeneity in Exchange Rate Expectations: Evidence on the Chartist-Fundamentalist Approach," CESifo Working Paper Series 2502, CESifo.
    46. Hamid Baghestani, 2010. "Evaluating Blue Chip forecasts of the trade-weighted dollar exchange rate," Applied Financial Economics, Taylor & Francis Journals, vol. 20(24), pages 1879-1889.
    47. Menkhoff, Lukas & Rebitzky, Rafael & Schröder, Michael, 2005. "Do Dollar Forecasters Believe too Much in PPP?," Hannover Economic Papers (HEP) dp-321, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    48. Bak, Yuhyeon & Park, Cheolbeom, 2022. "Exchange rate predictability, risk premiums, and predictive system," Economic Modelling, Elsevier, vol. 116(C).
    49. Bernhard O. Ishioro, 2014. "The Dynamics Of Exchange Rate Expectations Formation: The Nigerian Perspective," Economic Thought and Practice, Department of Economics and Business, University of Dubrovnik, vol. 23(2), pages 431-460, december.
    50. Koske, Isabell & Stadtmann, Georg, 2009. "Exchange rate expectations: The role of person specific forward looking variables," Economics Letters, Elsevier, vol. 105(3), pages 221-223, December.
    51. Tai, Chung-Ching & Chen, Shu-Heng & Yang, Lee-Xieng, 2018. "Cognitive ability and earnings performance: Evidence from double auction market experiments," Journal of Economic Dynamics and Control, Elsevier, vol. 91(C), pages 409-440.
    52. Christian Wolff & Ron Jongen & Willem F.C. Verschoor & Remco C.J. Zwinkels, 2009. "Dispersion of Beliefs in the Foreign Exchange Market," LSF Research Working Paper Series 09-01, Luxembourg School of Finance, University of Luxembourg.
    53. Eun, Cheol S. & Sabherwal, Sanjiv, 2002. "Forecasting exchange rates: Do banks know better?," Global Finance Journal, Elsevier, vol. 13(2), pages 195-215.
    54. Peter G. Szilagyi & Jonathan A. Batten, 2006. "Arbitrage, Covered Interest Parity and Long-Term Dependence between the US Dollar and the Yen," The Institute for International Integration Studies Discussion Paper Series iiisdp128, IIIS.
    55. Acedański, Jan, 2017. "Heterogeneous expectations and the distribution of wealth," Journal of Macroeconomics, Elsevier, vol. 53(C), pages 162-175.
    56. Audretsch, David B. & Stadtmann, Georg, 2005. "Biases in FX-forecasts: Evidence from panel data," Global Finance Journal, Elsevier, vol. 16(1), pages 99-111, August.
    57. Chortareas, Georgios & Jitmaneeroj, Boonlert & Wood, Andrew, 2012. "Forecast rationality and monetary policy frameworks: Evidence from UK interest rate forecasts," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(1), pages 209-231.
    58. Carl Bonham & Richard Cohen & Shigeyuki Abe, 2006. "The Rationality and Heterogeneity of Survey Forecasts of the Yen-Dollar Exchange Rate: A Reexamination," Working Papers 200611, University of Hawaii at Manoa, Department of Economics.
    59. Philippe Bacchetta & Eric van Wincoop, 2005. "Can Information Heterogeneity Explain the Exchange Rate Determination?," FAME Research Paper Series rp155, International Center for Financial Asset Management and Engineering.
    60. Beber, Alessandro & Fabbri, Daniela, 2012. "Who times the foreign exchange market? Corporate speculation and CEO characteristics," Journal of Corporate Finance, Elsevier, vol. 18(5), pages 1065-1087.
    61. Jan-Christoph Rülke, 2011. "Are central bank projections rational?," WHU Working Paper Series - Economics Group 11-05, WHU - Otto Beisheim School of Management.
    62. F. Pancotto & G. Pignataro & D. Raggi, 2014. "Higher order beliefs and the dynamics of exchange rates," Working Papers wp957, Dipartimento Scienze Economiche, Universita' di Bologna.
    63. Kearney, Fearghal & Cummins, Mark & Murphy, Finbarr, 2019. "Using extracted forward rate term structure information to forecast foreign exchange rates," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 1-14.
    64. Christian Dreger & Georg Stadtmann, 2006. "What Drives Heterogeneity in Foreign Exchange Rate Expectations: Deep Insights from a New Survey," Discussion Papers of DIW Berlin 624, DIW Berlin, German Institute for Economic Research.
    65. Bokhyeon Baik & Cheolbeom Park, 2003. "Dispersion of analysts' expectations and the cross-section of stock returns," Applied Financial Economics, Taylor & Francis Journals, vol. 13(11), pages 829-839.
    66. Batten, Jonathan A. & Szilagyi, Peter G., 2007. "Covered interest parity arbitrage and temporal long-term dependence between the US dollar and the Yen," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 376(C), pages 409-421.
    67. Michael Frenkel & Matthias Mauch & Jan-Christoph Rülke, 2017. "Forecaster Rationality and Expectation Formation in Foreign Exchange Markets: Do Emerging Markets Differ from Industrialized Economies?," WHU Working Paper Series - Economics Group 17-04, WHU - Otto Beisheim School of Management.
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    1. Peter F. Christoffersen & Francis X. Diebold, 2006. "Financial Asset Returns, Direction-of-Change Forecasting, and Volatility Dynamics," Management Science, INFORMS, vol. 52(8), pages 1273-1287, August.
    2. Katarzyna Dąbrowska-Gruszczyńska & Marcin Gruszczyński, 2009. "The introduction of the euro in the perspective of accession and the challenges of absorption," Ekonomia journal, Faculty of Economic Sciences, University of Warsaw, vol. 22.
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    4. Marcin Gruszczyński, 2007. "Repression versus free and controlled market. Research into the (weak) effectiveness of the Polish foreign currency (US dollar/zloty) market over the years 1983–1989 and 1991–2006," Ekonomia journal, Faculty of Economic Sciences, University of Warsaw, vol. 19.
    5. Peter Christoffersen & Francis X. Diebold, 2002. "Financial Asset Returns, Market Timing, and Volatility Dynamics," CIRANO Working Papers 2002s-02, CIRANO.
    6. Sonia Pangusión Espinosa., "undated". "Testing Uncovered Interest Rate Parity: The Spanish case," Studies on the Spanish Economy 128, FEDEA.
    7. Sergey V. Chernenko, 2004. "The information content of forward and futures prices: market expectations and the price of risk," International Finance Discussion Papers 808, Board of Governors of the Federal Reserve System (U.S.).

  18. Elliott, Graham & Fatás, Antonio, 1995. "International Business Cycles and the Dynamics of the Current Account," CEPR Discussion Papers 1280, C.E.P.R. Discussion Papers.

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    7. Fratzscher, Marcel & Müller, Gernot J. & Bussière, Matthieu, 2005. "Productivity shocks, budget deficits and the current account," Working Paper Series 509, European Central Bank.
    8. Diego Winkelried & José Enrique Gutierrez, 2015. "Regional Inflation Dynamics and Inflation Targeting. The Case of Peru," Journal of Applied Economics, Taylor & Francis Journals, vol. 18(2), pages 199-224, November.
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    1. Giuseppe Ferrero & Andrea Nobili, 2009. "Futures Contract Rates as Monetary Policy Forecasts," International Journal of Central Banking, International Journal of Central Banking, vol. 5(2), pages 109-145, June.
    2. Marques, André M. & Lima, Gilberto Tadeu & Troster, Victor, 2017. "Unemployment persistence in OECD countries after the Great Recession," Economic Modelling, Elsevier, vol. 64(C), pages 105-116.
    3. Muhammad Shahbaz & Ilhan Ozturk & Amjad Ali, 2015. "Electricity Consumption and Economic Growth Causality Revisited: Evidence from Turkey," Bulletin of Energy Economics (BEE), The Economics and Social Development Organization (TESDO), vol. 3(4), pages 176-193, December.
    4. Gupta, Kartick, 2017. "Do economic and societal factors influence the financial performance of alternative energy firms?," Energy Economics, Elsevier, vol. 65(C), pages 172-182.
    5. Karasoy, Alper, 2022. "Is innovative technology a solution to Japan's long-run energy insecurity? Dynamic evidence from the linear and nonlinear methods," Technology in Society, Elsevier, vol. 70(C).
    6. Mohsen Bahmani‐Oskooee & Tsangyao Chang & Farhang Niroomand & Omid Ranjbar, 2020. "Fourier nonlinear quantile unit root test and PPP in Africa," Bulletin of Economic Research, Wiley Blackwell, vol. 72(4), pages 451-481, October.
    7. Shank, Corey A. & Vianna, Andre C., 2016. "Are US-Dollar-Hedged-ETF investors aggressive on exchange rates? A panel VAR approach," Research in International Business and Finance, Elsevier, vol. 38(C), pages 430-438.
    8. Stephen M. Miller & Luis F. Martins & Rangan Gupta, 2014. "A Time-Varying Approach of the US Welfare Cost of Inflation," Working papers 2014-11, University of Connecticut, Department of Economics.
    9. Nautz, Dieter & Strohsal, Till & Netšunajev, Aleksei, 2019. "The Anchoring Of Inflation Expectations In The Short And In The Long Run," Macroeconomic Dynamics, Cambridge University Press, vol. 23(5), pages 1959-1977, July.
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    2710. Solarin Sakiru Adebola & Jauhari Dahalan, 2012. "An Empirical Analysis of Stock Markets Integration in Selected African Countries," EuroEconomica, Danubius University of Galati, issue 2(31), pages 166-177, May.
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    2714. Caner Demir & Suleyman Emre Ozcan, 2023. "The Asymmetric Relationship Among Industrial Production, Capacity Utilization Rate, and Producer Prices in Türkiye: The Nonlinear ARDL Model Approach," Journal of Economic Policy Researches, Istanbul University, Faculty of Economics, vol. 10(2), pages 525-543, July.
    2715. Chatziantoniou, Ioannis & Gabauer, David & Gupta, Rangan, 2023. "Integration and risk transmission in the market for crude oil: New evidence from a time-varying parameter frequency connectedness approach," Resources Policy, Elsevier, vol. 84(C).
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    2718. Hoque, Mohammad Enamul & Billah, Mabruk & Alam, Md Rafayet & Tiwari, Aviral Kumar, 2024. "Gold-backed cryptocurrencies: A hedging tool against categorical and regional financial stress," Global Finance Journal, Elsevier, vol. 60(C).
    2719. Amr Sadek HOSNY, 2014. "Is Monetary Policy in Egypt Backward or Forward-Looking?," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 14(2).
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    2721. Constantine Alexandrakis, 2014. "Technological change and the U.S. real interest rate," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 38(4), pages 672-686, October.
    2722. Baotai Wang & Ajit Dayanandan, 2006. "Unit Root Tests of Canadian Poverty Measures," Economics Bulletin, AccessEcon, vol. 9(2), pages 1-7.
    2723. Gary Tian Gang, 2008. "Equity Market Price Interactions Between China and the Other Markets Within the Chinese States Equity Markets," Multinational Finance Journal, Multinational Finance Journal, vol. 12(1-2), pages 105-126, March-Jun.
    2724. Gabauer, David, 2021. "Dynamic measures of asymmetric & pairwise connectedness within an optimal currency area: Evidence from the ERM I system," Journal of Multinational Financial Management, Elsevier, vol. 60(C).
    2725. Beyer, Andreas & Dewald, William G. & Haug, Alfred A., 2009. "Structural breaks, cointegration and the Fisher effect," Working Paper Series 1013, European Central Bank.
    2726. Meshach Jesse Aziakpono, 2008. "Financial And Monetary Autonomy And Interdependence Between South Africa And The Other Sacu Countries," South African Journal of Economics, Economic Society of South Africa, vol. 76(2), pages 189-211, June.
    2727. Jason W. Miller, 2018. "ARIMA Time Series Models for Full Truckload Transportation Prices," Forecasting, MDPI, vol. 1(1), pages 1-14, September.
    2728. Joakim Westerlund, 2015. "Rethinking the Univariate Approach to Panel Unit Root Testing: Using Covariates to Resolve the Incidental Trend Problem," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(3), pages 430-443, July.
    2729. Abdulkadir Abdulrashid Rafindadi & Zarinah Yusof, 2014. "An Econometric Estimation and Prediction of the Effects of Nominal Devaluation on Real Devaluation: Does the Marshal-Lerner (M-L) Assumptions Fits in Nigeria?," International Journal of Economics and Financial Issues, Econjournals, vol. 4(4), pages 819-835.
    2730. Dimitris A. Georgoutsos & Petros Migiakis, 2010. "European sovereign bond spreads: monetary unification, market conditions and financial integration," Working Papers 115, Bank of Greece.
    2731. Eduard Baumöhl & Štefan Lyócsa & Tomáš Výrost, 2011. "Volatility Regimes in Macroeconomic Time Series: The Case of the Visegrad Group," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 61(6), pages 530-544, December.
    2732. Sokhanvar, Amin & Çiftçioğlu, Serhan & Lee, Chien-Chiang, 2023. "The effect of energy price shocks on commodity currencies during the war in Ukraine," Resources Policy, Elsevier, vol. 82(C).
    2733. Andrew Coleman & John Landon-Lane, 2007. "Housing Markets and Migration in New Zealand, 1962-2006," Reserve Bank of New Zealand Discussion Paper Series DP2007/12, Reserve Bank of New Zealand.
    2734. Abu N.M. Wahid & Mohammad Salahuddin & Abdullah M. Noman, 2010. "Savings and investment in South Asia," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 37(6), pages 658-666, November.
    2735. Raslan Alzuabi & Mustafa Caglayan & Kostas Mouratidis, 2021. "The risk‐taking channel in the United States: A GVAR approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5826-5849, October.
    2736. Ikeno, Hidehiro, 2014. "Pairwise tests of convergence of Japanese local price levels," International Review of Economics & Finance, Elsevier, vol. 31(C), pages 232-248.
    2737. Ghassan, Hassan B., 2001. "Estimation Robuste des Equations d’Importation à Contamination Ponctuelle [Robust estimation of the Equations of Punctual contaminated Imports]," MPRA Paper 56429, University Library of Munich, Germany, revised 28 Sep 2001.
    2738. Zhou, Weilun & Gao, Jiti & Harris, David & Kew, Hsein, 2024. "Semi-parametric single-index predictive regression models with cointegrated regressors," Journal of Econometrics, Elsevier, vol. 238(1).
    2739. Yaya Keho, 2024. "Does Budget Deficit Crowd Out Private Investment? Cote d’Ivoire As A Focus," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 16(2), pages 1-86, February.
    2740. 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.
    2741. Lau, Evan & Baharumshah, Ahmad Zubaidi & Haw, Chan Tze, 2006. "Current account: mean-reverting or random walk behavior?," Japan and the World Economy, Elsevier, vol. 18(1), pages 90-107, January.
    2742. Halicioglu, Ferda & Andrés, Antonio R. & Yamamura, Eiji, 2012. "Modeling crime in Japan," Economic Modelling, Elsevier, vol. 29(5), pages 1640-1645.
    2743. Javed Ahmad Bhat & Sajad Ahmad Bhat & Waseem Ahmad Parray, 2025. "Nonlinearity in exchange rate pass-through across BRICS: Role of business cycle and inflation," International Economics and Economic Policy, Springer, vol. 22(1), pages 1-32, February.
    2744. Filippo Beltrami & Fulvio Fontini & Monica Giulietti & Luigi Grossi, 2021. "The zonal and seasonal CO2 marginal emissions factors for the Italian power market," Working Papers 01/2021, University of Verona, Department of Economics.
    2745. Asuman Oktayer & Nagihan Oktayer, 2013. "Testing Wagner's Law for Turkey: Evidence from a Trivariate Causality Analysis," Prague Economic Papers, Prague University of Economics and Business, vol. 2013(2), pages 284-301.
    2746. Helmut Herwartz & Florian Siedenburg, 2010. "A New Approach to Unit Root Testing," Computational Economics, Springer;Society for Computational Economics, vol. 36(4), pages 365-384, December.
    2747. Dufour, Jean-Marie & Taamouti, Abderrahim, 2010. "Exact optimal inference in regression models under heteroskedasticity and non-normality of unknown form," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2532-2553, November.
    2748. Raihan, Asif & Pavel, Monirul Islam & Muhtasim, Dewan Ahmed & Farhana, Sadia & Faruk, Omar & Paul, Arindrajit, 2023. "The role of renewable energy use, technological innovation, and forest cover toward green development: Evidence from Indonesia," Innovation and Green Development, Elsevier, vol. 2(1).
    2749. 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.
    2750. Song, Wonho & Ryu, Doojin & Webb, Robert I., 2016. "Overseas market shocks and VKOSPI dynamics: A Markov-switching approach," Finance Research Letters, Elsevier, vol. 16(C), pages 275-282.
    2751. Sun, Yixiao & Yang, Jingjing, 2020. "Testing-optimal kernel choice in HAR inference," Journal of Econometrics, Elsevier, vol. 219(1), pages 123-136.
    2752. Sekioua, Sofiane H., 2008. "Real interest parity (RIP) over the 20th century: New evidence based on confidence intervals for the largest root and the half-life," Journal of International Money and Finance, Elsevier, vol. 27(1), pages 76-101, February.
    2753. Wang, Xuetong & Fang, Fang & Ma, Shiqun & Xiang, Lijin & Xiao, Zumian, 2024. "Dynamic volatility spillover among cryptocurrencies and energy markets: An empirical analysis based on a multilevel complex network," The North American Journal of Economics and Finance, Elsevier, vol. 69(PA).
    2754. Jamel JOUINI, 2018. "Measuring the Macroeconomic Impacts of Fiscal Policy Shocks in the Saudi Economy : A Markov Switching Approach," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 55-70, December.
    2755. Ibrahim Worku, 2011. "Road Sector Development and Economic Growth in Ethiopia," Working Papers 004, Policy Studies Institute.
    2756. Kaya, Huseyin, 2013. "Forecasting the yield curve and the role of macroeconomic information in Turkey," Economic Modelling, Elsevier, vol. 33(C), pages 1-7.
    2757. António Miguel Martins & Susana Cró, 2021. "The Impact of Tourism on Solid Waste Generation and Management Cost in Madeira Island for the Period 1996–2018," Sustainability, MDPI, vol. 13(9), pages 1-16, May.
    2758. Paraskevi Salamaliki & Ioannis Venetis & Nicholas Giannakopoulos, 2013. "The causal relationship between female labor supply and fertility in the USA: updated evidence via a time series multi-horizon approach," Journal of Population Economics, Springer;European Society for Population Economics, vol. 26(1), pages 109-145, January.
    2759. Juan Carlos Cuestas & Barry Harrison, 2009. "Further evidence on the Real Interest Rate Parity hypothesis in Central and Eastern European Countries: unit roots and nonlinearities," NBS Discussion Papers in Economics 2009/1, Economics, Nottingham Business School, Nottingham Trent University.
    2760. Nicholas Apergis & Arusha Cooray, 2016. "Old Wine In A New Bottle: Trade Openness And Fdi Flows—Are The Emerging Economies Converging?," Contemporary Economic Policy, Western Economic Association International, vol. 34(2), pages 336-351, April.
    2761. David Mautin Oke & Koye Gerry Bokana & Olatunji Abdul Shobande, 2017. "Some Correlates Of Rural-Urban Led Urbanization In Lagos, Nigeria," Review of Urban & Regional Development Studies, Wiley Blackwell, vol. 29(3), pages 185-195, November.
    2762. Giovanni Razzu & Carl Singleton, 2013. "Are Business Cycles Gender Neutral?," Economics Discussion Papers em-dp2013-07, Department of Economics, University of Reading.
    2763. Natalya Ketenci, 2010. "Major Determinants of Current Account in Russia," Transition Studies Review, Springer;Central Eastern European University Network (CEEUN), vol. 17(4), pages 790-806, December.
    2764. Tierney, Heather L.R. & Kim, Jiyoon (June) & Nazarov, Zafar, 2018. "The Effects of Temporal Aggregation on Search Engine Data," MPRA Paper 84474, University Library of Munich, Germany.
    2765. Raquel Ayestarán & Juan Infante & Juan José Tenorio & Luis Alberiko Gil-Alana, 2023. "Evidence of Inflation Using Harmonized Consumer Price Indices in Some Euro Countries: France, Germany, Italy, and Spain, along with the Euro Zone," Mathematics, MDPI, vol. 11(10), pages 1-12, May.
    2766. Asafo-Adjei, Emmanuel & Tiwari, Aviral Kumar & Abakah, Emmanuel Joel Aikins & Lee, Chi-Chuan, 2024. "Risk synchronization in Australia stock market: A sector analysis," International Review of Economics & Finance, Elsevier, vol. 93(PA), pages 582-610.
    2767. Lilian Muchimba, 2022. "Connectedness of money market instruments: A time-varying vector autoregression approach," Working Papers in Economics & Finance 2022-07, University of Portsmouth, Portsmouth Business School, Economics and Finance Subject Group.
    2768. Culver, Sarah E. & Papell, David H., 1999. "Long-run purchasing power parity with short-run data: evidence with a null hypothesis of stationarity," Journal of International Money and Finance, Elsevier, vol. 18(5), pages 751-768, October.
    2769. Gyasi, Genevieve, 2020. "The Impact of Fiscal Deficit on Economic Growth: Using the Bounds Test Approach in The Case of Morocco," MPRA Paper 98925, University Library of Munich, Germany.
    2770. Ding Chen & Umar Muhammad Gummi & Junping Wang, 2024. "Does Renminbi internationalization matter for petroleum security in China? Evidence from a disaggregate analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(1), pages 961-974, January.
    2771. Hlongwane, Nyiko Worship & Daw, Olebogeng David & Sithole, Mixo Sweetness, 2023. "Renewable electricity generation and government expenditure on economic growth of South Africa and Botswana," MPRA Paper 116497, University Library of Munich, Germany, revised 24 Feb 2023.
    2772. Jinzhao Chen, 2009. "Beyond Cheap Talks: Assessing the Undervaluation of the Chinese Currency between 1994 and 2007," Post-Print hal-03722246, HAL.
    2773. Casalin, Fabrizio, 2016. "Size and power of tests based on Permanent-Transitory Component Models," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 142-153.
    2774. Wilfredo L. Maldonado & Octávio A. F. Tourinho & Jorge A. B. M. de Abreu, 2014. "Cointegrated Periodically Collapsing Bubbles in the Exchange Rate of 'BRICS' Countries," CAMA Working Papers 2014-34, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    2775. Raihan, Asif & Voumik, Liton Chandra & Akter, Salma & Ridzuan, Abdul Rahim & Fahlevi, Mochammad & Aljuaid, Mohammed & Saniuk, Sebastian, 2024. "Taking flight: Exploring the relationship between air transport and Malaysian economic growth," Journal of Air Transport Management, Elsevier, vol. 115(C).
    2776. Takashi Fukuda, 2016. "South Korea’s finance--growth nexus: evidence from VARX analysis with financial crisis and openness," Macroeconomics and Finance in Emerging Market Economies, Taylor & Francis Journals, vol. 9(1), pages 18-33, March.
    2777. Holmes, Mark J. & Maghrebi, Nabil, 2016. "Financial market impact on the real economy: An assessment of asymmetries and volatility linkages between the stock market and unemployment rate," The Journal of Economic Asymmetries, Elsevier, vol. 13(C), pages 1-7.
    2778. Granville, Brigitte & Mallick, Sushanta, 2006. "Does inflation or currency depreciation drive monetary policy in Russia?," Research in International Business and Finance, Elsevier, vol. 20(2), pages 163-179, June.
    2779. Amano, Robert A., 1998. "On the Optimal Seigniorage Hypothesis," Journal of Macroeconomics, Elsevier, vol. 20(2), pages 295-308, April.
    2780. Chambers, MJ & Kyriacou, M, 2010. "Jackknife Bias Reduction in the Presence of a Unit Root," Economics Discussion Papers 2785, University of Essex, Department of Economics.
    2781. Neil Kellard & Denise Osborn & Jerry Coakley & Marcus J. Chambers, 2015. "Testing for a Unit Root in a Near-Integrated Model with Skip-Sampled Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(5), pages 630-649, September.
    2782. Wan-Jiun Chen, 2012. "The relationships of carbon dioxide emissions and income in a newly industrialized economy," Applied Economics, Taylor & Francis Journals, vol. 44(13), pages 1621-1630, May.
    2783. Ghassan, Hassan B., 2007. "La condition de Marshall-Lerner-Robinson est-elle stable ? Approche par le test GLS cointégration à niveau et puissance améliorés [Does the Marshall-Lerner-Robinson condition verify the stability? ," MPRA Paper 56354, University Library of Munich, Germany, revised 15 Jan 2008.
    2784. Aaron D. Smallwood, 2016. "A Monte Carlo Investigation of Unit Root Tests and Long Memory in Detecting Mean Reversion in I(0) Regime Switching, Structural Break, and Nonlinear Data," Econometric Reviews, Taylor & Francis Journals, vol. 35(6), pages 986-1012, June.
    2785. Yu Guo And Wei Ma, 2016. "Time-Varying Coefficient Taylor Rule and Chinese Monetary Policy: Evidence from the Time-Varying Cointegration," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 41(4), pages 27-44, December.
    2786. Cosimo Magazzino & Gordon L. Brady, 2018. "The relationship among renewable energy, economic growth, labor and capital formation in Italy," RIVISTA DI STUDI SULLA SOSTENIBILITA', FrancoAngeli Editore, vol. 2018(1), pages 35-48.
    2787. Peri, Massimo & Baldi, Lucia, 2013. "The effect of biofuel policies on feedstock market: Empirical evidence for rapeseed oil prices in EU," Resource and Energy Economics, Elsevier, vol. 35(1), pages 18-37.
    2788. Polat, Onur & Ertuğrul, Hasan Murat & Sakarya, Burçhan & Akgül, Ali, 2024. "TVP-VAR based time and frequency domain food & energy commodities connectedness an analysis for financial/geopolitical turmoil episodes," Applied Energy, Elsevier, vol. 357(C).
    2789. Abdul Rehman & Hengyun Ma & Rafael Alvarado & Fayyaz Ahmad, 2023. "The nexus of military, final consumption expenditures, total reserves, and economic development of Pakistan," Economic Change and Restructuring, Springer, vol. 56(3), pages 1753-1776, June.
    2790. Terra, Cristina & Vahia, Ana Lucia, 2008. "A note Purchasing Power Parity and The Choice of Price Index," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 62(1), September.
    2791. Taha, Roshaiza & Colombage, Sisira R.N. & Maslyuk, Svetlana & Nanthakumar, Loganathan, 2013. "Does financial system activity affect tax revenue in Malaysia? Bounds testing and causality approach," Journal of Asian Economics, Elsevier, vol. 24(C), pages 147-157.
    2792. Erik Hjalmarsson, 2005. "Estimation of average local-to-unity roots in heterogenous panels," International Finance Discussion Papers 852, Board of Governors of the Federal Reserve System (U.S.).
    2793. Onater-Isberk, Esra, 2016. "Environmental Kuznets curve under noncarbohydrate energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 338-347.
    2794. Zhitao Lin & Jinzhao Chen & Xingwang Qian, 2021. "Capital controls and the volatility of the renminbi covered interest deviation," Post-Print halshs-03436233, HAL.
    2795. Lean Hooi Hooi & Russell Smyth, 2007. "Are Asian real exchange rates mean reverting? Evidence from univariate and panel LM unit root tests with one and two structural breaks," Applied Economics, Taylor & Francis Journals, vol. 39(16), pages 2109-2120.
    2796. Jomana Amara & David Papell, 2006. "Testing for Purchasing Power Parity using stationary covariates," Applied Financial Economics, Taylor & Francis Journals, vol. 16(1-2), pages 29-39.
    2797. Chen, Shiu-Sheng, 2009. "Oil price pass-through into inflation," Energy Economics, Elsevier, vol. 31(1), pages 126-133, January.
    2798. Imed Drine & Christophe Rault, 2003. "Do panel data permit the rescue of the Balassa-Samuelson hypothesis for Latin American countries?," Applied Economics, Taylor & Francis Journals, vol. 35(3), pages 351-359.
    2799. Alimi, R. Santos, 2014. "DOLS Cointegration Vector Estimation of the Effect of Inflation and Financial Deepening on Output Growth in Nigeria," MPRA Paper 57182, University Library of Munich, Germany.
    2800. Kleimeier, Stefanie & Sander, Harald, 2022. "Twenty years with the Euro: Eurozone banking market integration revisited," Economic Modelling, Elsevier, vol. 114(C).
    2801. Massimo Peri & Lucia Baldi & Daniela Vandone, 2013. "Price discovery in commodity markets," Applied Economics Letters, Taylor & Francis Journals, vol. 20(4), pages 397-403, March.
    2802. Tarassow, Artur, 2010. "The empirical relevance of Goodwin’s business cycle model for the US economy," MPRA Paper 21012, University Library of Munich, Germany.
    2803. Harold Glenn A. Valera & Mark J. Holmes & Valerien O. Pede & Jean Balié, 2023. "How convergent are rice export prices in the international market?," Agricultural Economics, International Association of Agricultural Economists, vol. 54(1), pages 127-141, January.
    2804. Sachsida, Adolfo & Divino, Jose Angelo & Cajueiro, Daniel Oliveira, 2011. "Inflation, unemployment, and the time consistency of the US monetary policy," Structural Change and Economic Dynamics, Elsevier, vol. 22(2), pages 173-179, June.
    2805. Christopher Martin & Costas Milas, 2010. "Financial Market Liquidity and the Financial Crisis: An Assessment Using UK Data," International Finance, Wiley Blackwell, vol. 13(3), pages 443-459, December.
    2806. Evan LAU & Nelson FU, 2011. "Financial And Current Account Interrelationship: An Empirical Test," Journal of Applied Economic Sciences, Spiru Haret University, Faculty of Financial Management and Accounting Craiova, vol. 6(1(15)/ Sp), pages 34-42.
    2807. 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.
    2808. Vicente Esteve & Juan Sanchis-Llopis, 2005. "Estimating the substitutability between private and public consumption: the case of Spain, 1960-2003," Applied Economics, Taylor & Francis Journals, vol. 37(20), pages 2327-2334.
    2809. George Kapetanios & Zacharias Psaradakis, 2016. "Semiparametric Sieve-Type Generalized Least Squares Inference," Econometric Reviews, Taylor & Francis Journals, vol. 35(6), pages 951-985, June.
    2810. Antonio Bojanic, 2014. "The effect of coca and FDI on the level of corruption in Bolivia," Latin American Economic Review, Springer;Centro de Investigaciòn y Docencia Económica (CIDE), vol. 23(1), pages 1-23, December.
    2811. Nafeesa Yunus, 2023. "Co‐movement among oil, stock, bond, and housing markets: An analysis of U.S., Asian, and European economies," International Review of Finance, International Review of Finance Ltd., vol. 23(2), pages 393-436, June.
    2812. Ngo Thai Phuong & Bahaudin G. Mujtaba & Greg Fisher, 2014. "The Influence of Communism on Ethical Decision Making," Journal of Knowledge Management, Economics and Information Technology, ScientificPapers.org, vol. 4(1), pages 1-8, February.
    2813. Sorge, Marco M., 2021. "Stabilizing Taylor rules and determinacy under unit root supply shocks: A re-examination," Journal of Macroeconomics, Elsevier, vol. 68(C).
    2814. BOUAKEZ, Hafedh & KANO, Takashi, 2024. "Deciphering the Neo-Fisherian Effect," Discussion paper series HIAS-E-140, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    2815. Nikolaos Antonakakis & David Gabauer & Rangan Gupta, 2018. "Greek Economic Policy Uncertainty: Does it Matter for the European Union?," Working Papers 201840, University of Pretoria, Department of Economics.
    2816. Kellogg, Ryan, 2018. "Gasoline price uncertainty and the design of fuel economy standards," Journal of Public Economics, Elsevier, vol. 160(C), pages 14-32.
    2817. Xiaoyang Wang & Philip Garcia & Scott H. Irwin, 2014. "The Behavior of Bid-Ask Spreads in the Electronically-Traded Corn Futures Market," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 96(2), pages 557-577.
    2818. Gabauer, David & Stenfors, Alexis, 2024. "Quantile-on-quantile connectedness measures: Evidence from the US treasury yield curve," Finance Research Letters, Elsevier, vol. 60(C).
    2819. Dettoni, Robinson & Gil-Alana, Luis A. & Yaya, OlaOluwa S., 2024. "Stock market prices and Dividends in the US: Bubbles or Long-run equilibria relationships?," International Review of Financial Analysis, Elsevier, vol. 94(C).
    2820. Sowmya Subramaniam & David Gabauer & Rangan Gupta, 2018. "On the Transmission Mechanism of Asia-Pacific Yield Curve Characteristics," Working Papers 201864, University of Pretoria, Department of Economics.
    2821. Pagan, Adrian, 1996. "The econometrics of financial markets," Journal of Empirical Finance, Elsevier, vol. 3(1), pages 15-102, May.
    2822. Mehmet Balcilar & Abebe Beyene & Rangan Gupta & Monaheng Seleteng, 2013. "‘Ripple’ Effects in South African House Prices," Urban Studies, Urban Studies Journal Limited, vol. 50(5), pages 876-894, April.
    2823. Zhang, Rongmao & Chan, Ngai Hang, 2018. "Portmanteau-type tests for unit-root and cointegration," Journal of Econometrics, Elsevier, vol. 207(2), pages 307-324.
    2824. Nicholas Apergis & Ioannis Chatziantoniou, 2022. "US partisan conflict shocks and international stock market returns," Empirical Economics, Springer, vol. 63(6), pages 2817-2854, December.
    2825. Palazzi, Rafael Baptista & Meira, Erick & Klotzle, Marcelo Cabus, 2022. "The sugar-ethanol-oil nexus in Brazil: Exploring the pass-through of international commodity prices to national fuel prices," Journal of Commodity Markets, Elsevier, vol. 28(C).
    2826. Serletis, Apostolos & Istiak, Khandokar, 2017. "Financial intermediary leverage spillovers," Research in International Business and Finance, Elsevier, vol. 39(PB), pages 1000-1007.
    2827. Sephton, Peter S., 2022. "Revisiting the inflation-hedging properties of precious metals in Africa," Resources Policy, Elsevier, vol. 77(C).
    2828. Kao, Yu-Sheng & Day, Min-Yuh & Chou, Ke-Hsin, 2024. "A comparison of bitcoin futures return and return volatility based on news sentiment contemporaneously or lead-lag," The North American Journal of Economics and Finance, Elsevier, vol. 72(C).
    2829. Kirikkaleli, Dervis, 2020. "The effect of domestic and foreign risks on an emerging stock market: A time series analysis," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    2830. Lawrence Kryzanowski & Jie Zhang & Rui Zhong, 2021. "Currency hedging and quantitative easing: Evidence from global bond markets," International Review of Finance, International Review of Finance Ltd., vol. 21(2), pages 555-597, June.
    2831. Monika Blaszkiewicz-Schwartzman, 2007. "Explaining Exchange Rate Movements in New Member States of the European Union: Nominal and Real Convergence," Money Macro and Finance (MMF) Research Group Conference 2006 144, Money Macro and Finance Research Group.
    2832. Ahmet Ugur & Yusuf Ekrem Akbas & Mehmet Senturk, 2014. "Long Term Validity of Monetary Exchange Rate Model: Evidence from Turkey," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 17(51), pages 111-136, March.
    2833. Gaetano Perone, 2020. "An ARIMA model to forecast the spread and the final size of COVID-2019 epidemic in Italy," Health, Econometrics and Data Group (HEDG) Working Papers 20/07, HEDG, c/o Department of Economics, University of York.
    2834. Paresh Kumar Narayan & Xiujian Peng, 2006. "An Econometric Analysis of the Determinants of Fertility for China, 1952-2000," Journal of Chinese Economic and Business Studies, Taylor & Francis Journals, vol. 4(2), pages 165-183.
    2835. Vicente Esteve & Francisco Requena, 2006. "A Cointegration Analysis of Car Advertising and Sales Data in the Presence of Structural Change," International Journal of the Economics of Business, Taylor & Francis Journals, vol. 13(1), pages 111-128.
    2836. Gaolu Zou & K. W. Chau, 2019. "Long- and Short-Run Effects of Fuel Prices on Freight Transportation Volumes in Shanghai," Sustainability, MDPI, vol. 11(18), pages 1-12, September.
    2837. Cifter, Atilla, 2011. "Value-at-risk estimation with wavelet-based extreme value theory: Evidence from emerging markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(12), pages 2356-2367.
    2838. Yang, Lixiong & Lee, Chingnun & Shie, Fu Shuen, 2014. "How close a relationship does a capital market have with other markets? A reexamination based on the equal variance test," Pacific-Basin Finance Journal, Elsevier, vol. 26(C), pages 198-226.
    2839. Valadkhani, Abbas & Nguyen, Jeremy & Smyth, Russell, 2018. "Consumer electricity and gas prices across Australian capital cities: Structural breaks, effects of policy reforms and interstate differences," Energy Economics, Elsevier, vol. 72(C), pages 365-375.
    2840. Yingyi Wang & Md. Qamruzzaman & Ayesha Serfraz & Manickavasagam Theivanayaki, 2023. "Does Financial Deepening Foster Clean Energy Sustainability over Conventional Ones? Examining the Nexus between Financial Deepening, Urbanization, Institutional Quality, and Energy Consumption in Chin," Sustainability, MDPI, vol. 15(10), pages 1-28, May.
    2841. Li, Jiaqi & Li, Yushan & Zheng, Ziqi & Si, Xiaoyu, 2023. "Environment and natural resources degradation under COVID-19 crises: Recovery post pandemic," Resources Policy, Elsevier, vol. 83(C).
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    2882. Polat, Onur & Ozcan, Burcu & Ertuğrul, Hasan Murat & Atılgan, Emre & Özün, Alper, 2024. "Fintech: A Conduit for sustainability and renewable energy? Evidence from R2 connectedness analysis," Resources Policy, Elsevier, vol. 94(C).
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    3225. Lahura, Erick & Vega, Marco, 2014. "Stock market development and real economic activity in Peru," Working Papers 2014-022, Banco Central de Reserva del Perú.
    3226. Nur Setyowati, 2019. "Macroeconomic Determinants of Islamic Banking Products in Indonesia," Economies, MDPI, vol. 7(2), pages 1-15, June.
    3227. Gormus, Alper & Nazlioglu, Saban & Soytas, Ugur, 2018. "High-yield bond and energy markets," Energy Economics, Elsevier, vol. 69(C), pages 101-110.
    3228. Amin Sokhanvar & Chien-Chiang Lee, 2023. "How do energy price hikes affect exchange rates during the war in Ukraine?," Empirical Economics, Springer, vol. 64(5), pages 2151-2164, May.
    3229. Borja Balparda & Guglielmo Maria Caporale & Luis Alberiko Gil-Alana, 2017. "The fisher relationship in Nigeria," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 41(2), pages 343-353, April.
    3230. Rohan Fox & Marcel Schröder, 2018. "After Papua New Guinea's Resource Boom: Is the Kina Overvalued?," Asia and the Pacific Policy Studies, Wiley Blackwell, vol. 5(1), pages 65-76, January.
    3231. Peter S. Sephton, 2022. "Finite Sample Lag Adjusted Critical Values of the ADF-GLS Test," Computational Economics, Springer;Society for Computational Economics, vol. 59(1), pages 177-183, January.
    3232. Timilsina, Govinda & Steinbuks, Jevgenijs, 2021. "Economic costs of electricity load shedding in Nepal," Renewable and Sustainable Energy Reviews, Elsevier, vol. 146(C).
    3233. Koch, Cathérine Tahmee, 2014. "Risky adjustments or adjustments to risks: Decomposing bank leverage," Journal of Banking & Finance, Elsevier, vol. 45(C), pages 242-254.
    3234. Tahir Mukhtar & Aliya H. Khan, 2016. "The Current Account Deficit Sustainability: An Empirical Investigation for Pakistan," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 55(4), pages 397-419.
    3235. Pradeep Agrawal, 2014. "The Role of Exports in India's Economic Growth," IEG Working Papers 345 JEL Classification: O, Institute of Economic Growth.
    3236. 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.
    3237. Andrew C. Worthington & Helen Higgs, 2011. "Macro drivers of Australian housing affordability, 1985â 2010: An autoregressive distributed lag approach," Discussion Papers in Finance finance:201116, Griffith University, Department of Accounting, Finance and Economics.
    3238. Chambers, MJ, 2016. "The Effects of Sampling Frequency on Detrending Methods for Unit Root Tests," Economics Discussion Papers 16062, University of Essex, Department of Economics.
    3239. Antonio Rodriguez-Gil, 2018. "Hysteresis and labour market institutions. Evidence from the UK and the Netherlands," Empirical Economics, Springer, vol. 55(4), pages 1985-2025, December.
    3240. Maurer, Rainer, 2022. "Price levels in the European Monetary Union: Even tradables follow independent random walks," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    3241. Arize, Augustine C. & Malindretos, John, 2012. "Nonstationarity and nonlinearity in inflation rate: Some further evidence," International Review of Economics & Finance, Elsevier, vol. 24(C), pages 224-234.
    3242. Ana Bartolome & Michael McAleer & Vicente Ramos & Javier Rey-Maquieira, 2009. "Risk Management for International Tourist Arrivals: An Application to the Balearic Islands, Spain," CIRJE F-Series CIRJE-F-665, CIRJE, Faculty of Economics, University of Tokyo.
    3243. Haoming Liu & Jinli Zeng, 2007. "Airline passenger fatality and the demand for air travel," Applied Economics, Taylor & Francis Journals, vol. 39(14), pages 1773-1781.
    3244. Roberto Esposti, 2022. "Who Moves First? Commodity Price Interdependence Through Time-Varying Granger Causality," Working Papers 471, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    3245. Al-Shboul, Mohammad & Assaf, Ata & Mokni, Khaled, 2022. "When bitcoin lost its position: Cryptocurrency uncertainty and the dynamic spillover among cryptocurrencies before and during the COVID-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 83(C).
    3246. Lee, Chien-Chiang & Huang, Wei-Ling & Yin, Chun-Hao, 2013. "The dynamic interactions among the stock, bond and insurance markets," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 28-52.
    3247. Ogali, Oscar I.O. & Okoro, Emeka E. & Olafuyi, Saburi G., 2023. "Assessing consensus on nexus between natural gas consumption and economic growth," Renewable and Sustainable Energy Reviews, Elsevier, vol. 187(C).
    3248. Tsani, Stela Z., 2010. "Energy consumption and economic growth: A causality analysis for Greece," Energy Economics, Elsevier, vol. 32(3), pages 582-590, May.
    3249. Firouz Fallahi & Mohammad Karimi & Marcel-Cristian Voia, 2014. "Are Shocks to Energy Consumption Persistent? Evidence from Subsampling Confidence Intervals," Carleton Economic Papers 14-02, Carleton University, Department of Economics.
    3250. Ugur Korkut Pata & Sukran Kahveci, 2018. "A multivariate causality analysis between electricity consumption and economic growth in Turkey," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 20(6), pages 2857-2870, December.
    3251. Cheung, Yin-Wong & Lai, Kon S., 1998. "Parity reversion in real exchange rates during the post-Bretton Woods period," Journal of International Money and Finance, Elsevier, vol. 17(4), pages 597-614, August.
    3252. Chang, C-L. & Huang, B-W. & Chen, M-G., 2010. "Modelling the Asymmetric Volatility in Hog Prices in Taiwan," Econometric Institute Research Papers EI 2010-46, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3253. Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "International Financial Markets," Post-Print halshs-02183053, HAL.
    3254. Abbas Ali Chandio & Yuansheng Jiang & Jam Ghulam Murtaza Sahito & Fayyaz Ahmad, 2019. "Empirical Insights into the Long-Run Linkage between Households Energy Consumption and Economic Growth: Macro-Level Empirical Evidence from Pakistan," Sustainability, MDPI, vol. 11(22), pages 1-17, November.
    3255. Mark J. Holmes, 2010. "An Alternative Perspective on Tobin's Q and Aggregate Investment Expenditure," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 9(1), pages 23-28, April.
    3256. Cheng-Feng Lee & Ching-Chuan Tsong, 2012. "A revisit on real interest rate parity hypothesis -- simulation evidence from efficient unit root tests," Applied Economics, Taylor & Francis Journals, vol. 44(24), pages 3089-3099, August.
    3257. Robaina, M. & Madaleno, M. & Silva, S. & Eusébio, C. & Carneiro, M.J. & Gama, C. & Oliveira, K. & Russo, M.A. & Monteiro, A., 2020. "The relationship between tourism and air quality in five European countries," Economic Analysis and Policy, Elsevier, vol. 67(C), pages 261-272.
    3258. Magali Jaoul-Grammare, 2014. "Social prestige of occupations and substitutability of university courses in France during the 20th century [Prestige social des professions et substituabilité des filières universitaires en France," Post-Print hal-01744651, HAL.
    3259. Dogan, Eyup & Seker, Fahri, 2016. "Determinants of CO2 emissions in the European Union: The role of renewable and non-renewable energy," Renewable Energy, Elsevier, vol. 94(C), pages 429-439.
    3260. Cunado, J. & Gil-Alana, L.A. & Gracia, Fernando Perez de, 2010. "Mean reversion in stock market prices: New evidence based on bull and bear markets," Research in International Business and Finance, Elsevier, vol. 24(2), pages 113-122, June.
    3261. Chu-Ping C. Vijverberg & Wim P. M. Vijverberg, 2007. "Diagnosing the Productivity Effect of Public Capital in the Private Sector," Eastern Economic Journal, Eastern Economic Association, vol. 33(2), pages 207-230, Spring.
    3262. Helmut Herwartz & Malte Rengel, 2018. "Size-corrected inference in fiscal policy reaction functions: a three country assessment," Empirical Economics, Springer, vol. 55(2), pages 391-416, September.
    3263. Liew, Ping-Xin & Lim, Kian-Ping & Goh, Kim-Leng, 2022. "The dynamics and determinants of liquidity connectedness across financial asset markets," International Review of Economics & Finance, Elsevier, vol. 77(C), pages 341-358.
    3264. Anna Bykhovskaya & Vadim Gorin, 2020. "Cointegration in large VARs," Papers 2006.14179, arXiv.org, revised Dec 2021.
    3265. Muhammad Shahbaz & Faridul Islam & Muhammad Sabihuddin Butt, 2016. "Finance–Growth–Energy Nexus and the Role of Agriculture and Modern Sectors: Evidence from ARDL Bounds Test Approach to Cointegration in Pakistan," Global Business Review, International Management Institute, vol. 17(5), pages 1037-1059, October.
    3266. Wang, Ling, 2023. "Central bank asset purchases, banks’ risky security holdings and profitability: Macro and micro evidence from Japan and the U.S," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 347-364.
    3267. Massimiliano Marcellino, 2004. "Forecast Pooling for European Macroeconomic Variables," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(1), pages 91-112, February.
    3268. Yoon, Gawon, 2016. "Stochastic unit root processes: Maximum likelihood estimation, and new Lagrange multiplier and likelihood ratio tests," Economic Modelling, Elsevier, vol. 52(PB), pages 725-732.
    3269. Gómez-Puig, Marta & Sosvilla-Rivero, Simón, 2015. "The causal relationship between debt and growth in EMU countries," Journal of Policy Modeling, Elsevier, vol. 37(6), pages 974-989.
    3270. Tawadros, George B., 2008. "A structural time series test of the monetary model of exchange rates under four big inflations," Economic Modelling, Elsevier, vol. 25(6), pages 1216-1224, November.
    3271. Bilge Bakin & Gozde Gurgun, 2014. "Portfolio Investments and Asset Prices Relationship in Turkey," Proceedings of International Academic Conferences 0201138, International Institute of Social and Economic Sciences.

  21. Bewley, R. & Elliot, G., 1989. "The Rejection Of Homogeneity In Demand And Supply Analysis: An Explanation And Solution," Papers 89-2, New South Wales - School of Economics.

    Cited by:

    1. Gundlach, Erich, 1993. "Die Dienstleistungsnachfrage als Determinante des wirtschaftlichen Strukturwandels," Open Access Publications from Kiel Institute for the World Economy 763, Kiel Institute for the World Economy (IfW Kiel).
    2. Gundlach, Erich, 1990. "Ausgaben- und Preiselastizitäten der Dienstleistungsnachfrage: Zeitreihen- und Querschnittsergebnisse für die Bundesrepublik Deutschland," Kiel Working Papers 430, Kiel Institute for the World Economy (IfW Kiel).

  22. Graham Elliott & Colm Kearney, 1988. "The Intertemporal Government Budget Constraint and Tests for Bubbles," RBA Research Discussion Papers rdp8809, Reserve Bank of Australia.

    Cited by:

    1. Christophe Ehrhart & Matthieu Llorca, 2008. "The sustainability of fiscal policy: evidence from a panel of six South-Mediterranean countries," Applied Economics Letters, Taylor & Francis Journals, vol. 15(10), pages 797-803.
    2. Emilia Câmpeanu & Andreea Stoian, 2010. "Fiscal Policy Reaction in the Short Term for Assessing Fiscal Sustainability in the Long Runin Central and Eastern European Countries," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 60(6), pages 501-518, December.
    3. Stoian, Andreea, 2012. "Fiscal Sustainability of the European Welfare State: Evidence from Cumulative Excess of the Primary Balance," Working Papers 27/2012, Universidade Portucalense, Centro de Investigação em Gestão e Economia (CIGE).
    4. Burret Heiko T. & Feld Lars P. & Köhler Ekkehard A., 2013. "Sustainability of Public Debt in Germany – Historical Considerations and Time Series Evidence," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 233(3), pages 291-335, June.
    5. Ahmet Salih İkiz, 2020. "Testing the Ricardian Equivalence Theorem: Time Series Evidence from Turkey," Economies, MDPI, vol. 8(3), pages 1-20, August.
    6. Gozde Es POLAT & Onur POLAT, 2021. "Fiscal sustainability analysis in EU countries: a dynamic macro-panel approach," Eastern Journal of European Studies, Centre for European Studies, Alexandru Ioan Cuza University, vol. 12, pages 219-241, June.
    7. Bogdan Dima & Oana Lobonţ & Cristina Nicolescu, 2009. "The Fiscal Revenues And Public Expenditures: Is Their Evolution Sustenable? The Romanian Case," Annales Universitatis Apulensis Series Oeconomica, Faculty of Sciences, "1 Decembrie 1918" University, Alba Iulia, vol. 1(11), pages 1-42.
    8. António Afonso, 2005. "Fiscal Sustainability: The Unpleasant European Case," FinanzArchiv: Public Finance Analysis, Mohr Siebeck, Tübingen, vol. 61(1), pages 19-44, March.
    9. António Afonso, 2000. "Fiscal policy sustainability: some unpleasant European evidence," Working Papers Department of Economics 2000/12, ISEG - Lisbon School of Economics and Management, Department of Economics, Universidade de Lisboa.
    10. Juan Carlos Cuestas & Luis A. Gil-Alana & Laura Sauci, 2020. "Public finances in the EU-27: Are they sustainable?," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 47(1), pages 181-204, February.

  23. Graham Elliott & Michael Jansson, "undated". "Testing for Unit Roots with Stationary Covariates," Economics Working Papers 2000-6, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Lupi, Claudio, 2009. "Covariate Augmented Dickey-Fuller Tests with R," Economics & Statistics Discussion Papers esdp09051, University of Molise, Department of Economics.
    2. Galvao Jr., Antonio F., 2009. "Unit root quantile autoregression testing using covariates," Journal of Econometrics, Elsevier, vol. 152(2), pages 165-178, October.
    3. Jomana Amara, 2011. "Testing for stationarity using covariates: an application to purchasing power parity," Applied Economics Letters, Taylor & Francis Journals, vol. 18(13), pages 1295-1301.
    4. Maican, Florin G. & Sweeney, Richard J., 2006. "Real Exchange Rate Adjustment In European Transition Countries," Working Papers in Economics 202, University of Gothenburg, Department of Economics.
    5. Fossati, Sebastian, 2011. "Covariate Unit Root Tests with Good Size and Power," Working Papers 2011-4, University of Alberta, Department of Economics.
    6. Mauro Costantini & Claudio Lupi, 2013. "A Simple Panel-CADF Test for Unit Roots," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(2), pages 276-296, April.
    7. Fossati, Sebastian, 2011. "Unit Root Testing with Stationary Covariates and a Structural Break in the Trend Function," Working Papers 2011-10, University of Alberta, Department of Economics.
    8. Pesavento, Elena & Rossi, Barbara, 2005. "Do Technology Shocks Drive Hours Up Or Down? A Little Evidence From An Agnostic Procedure," Macroeconomic Dynamics, Cambridge University Press, vol. 9(4), pages 478-488, September.
    9. Lyócsa, Štefan & Výrost, Tomáš & Baumöhl, Eduard, 2011. "Unit-root and stationarity testing with empirical application on industrial production of CEE-4 countries," MPRA Paper 29648, University Library of Munich, Germany.
    10. Cláudia Duarte, 2015. "Covariate-augmented unit root tests with mixed-frequency data," Working Papers w201507, Banco de Portugal, Economics and Research Department.
    11. Rossi, Barbara & Pesavento, Elena, 2003. "Small Sample Confidence Intervals for Multivariate Impulse Response Functions at Long Horizons," Working Papers 03-19, Duke University, Department of Economics.
    12. 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.
    13. Effrosyni Diamantoudi, 2003. "Equilibrium binding agreements under diverse behavioral assumptions," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 22(2), pages 431-446, September.
    14. Lawrence J. Christiano & Martin S. Eichenbaum & Robert J. Vigfusson, 2003. "What happens after a technology shock?," International Finance Discussion Papers 768, Board of Governors of the Federal Reserve System (U.S.).
    15. Barbara Rossi & Elena Pesavento, 2004. "Do Technology Shocks Drive Hours Up or Down?," Econometric Society 2004 North American Summer Meetings 96, Econometric Society.
    16. Brissimis, Sophocles & Migiakis, Petros, 2010. "Inflation persistence and the rationality of inflation expectations," MPRA Paper 29052, University Library of Munich, Germany.
    17. Maurizio Bovi, 2004. "The Dark, And Independent, Side Of Italy," ISAE Working Papers 46, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
    18. 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.
    19. Joakim Westerlund, 2013. "A computationally convenient unit root test with covariates, conditional heteroskedasticity and efficient detrending," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(4), pages 477-495, July.
    20. Elena Pesavento, 2006. "Near-Optimal Unit Root Tests with Stationary Covariates with Better Finite Sample Size," Economics Working Papers ECO2006/18, European University Institute.
    21. Lee, Cheng-Feng & Hu, Te-Chung & Li, Ping-Cheng & Tsong, Ching-Chuan, 2013. "Asymmetric behavior of unemployment rates: Evidence from the quantile covariate unit root test," Japan and the World Economy, Elsevier, vol. 28(C), pages 72-84.
    22. Tsong, Ching-Chuan & Wu, Chien-Wei & Chiu, Hsien-Hung & Lee, Cheng-Feng, 2013. "Covariate unit root tests under structural change and asymmetric STAR dynamics," Economic Modelling, Elsevier, vol. 33(C), pages 101-112.
    23. Matsuki, Takashi, 2019. "Per capita output convergence across Asian countries: Evidence from covariate unit root test with an endogenous structural break," Economic Modelling, Elsevier, vol. 82(C), pages 99-118.
    24. Marc Hallin & Ramon van den Akker & Bas J.M. Werker, 2011. "A class of simple distribution-free rank-based unit root tests," Post-Print hal-00834424, HAL.
    25. Chukiat Chaiboonsri & Prasert Chaitip & N. Rangaswamy, 2009. "Modelling International Tourism Demand in Thailand," Annals of the University of Petrosani, Economics, University of Petrosani, Romania, vol. 9(3), pages 125-146.
    26. Kaddour Hadri & Eiji Kurozumi & Daisuke Yamazaki, 2015. "Synergy between an Improved Covariate Unit Root Test and Cross-sectionally Dependent Panel Data Unit Root Tests," Manchester School, University of Manchester, vol. 83(6), pages 676-700, December.
    27. Emilian DOBRESCU, 2016. "Controversies over the Size of the Public Budget," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 5-34, December.
    28. Elliott, Graham & Jansson, Michael & Pesavento, Elena, 2004. "Optimal Power for Testing Potential Cointegrating Vectors with Known," University of California at San Diego, Economics Working Paper Series qt2bv7n071, Department of Economics, UC San Diego.
    29. Ayşegül Çorakcı & Furkan Emirmahmutoglu & Tolga Omay, 2017. "Re-examining the real interest rate parity hypothesis (RIPH) using panel unit root tests with asymmetry and cross-section dependence," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 44(1), pages 91-120, February.
    30. Yang, Yang & Zhao, Zhao, 2020. "Quantile nonlinear unit root test with covariates and an application to the PPP hypothesis," Economic Modelling, Elsevier, vol. 93(C), pages 728-736.
    31. Boriss Siliverstovs, 2005. "The Bi-parameter Smooth Transition Autoregressive model," Economics Bulletin, AccessEcon, vol. 3(23), pages 1-11.
    32. Kazuki Hiraga, 2011. "New Methods for Testing the Sustainability of Government Debt," Keio/Kyoto Joint Global COE Discussion Paper Series 2011-020, Keio/Kyoto Joint Global COE Program.
    33. Rehim Kılıç, 2009. "Nonlinearity and Persistence in PPP: Does Controlling for Nonlinearity Solve the PPP Puzzle?," Review of International Economics, Wiley Blackwell, vol. 17(3), pages 570-587, August.
    34. Tsong Ching-Chuan, 2012. "Unit Root Testing with Stationary Covariates in the Framework of Asymmetric STAR Nonlinearity," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(5), pages 1-27, December.
    35. Bo Sandemann Rasmussen, "undated". "Government Debt and Capital Accumulation in the Blanchard-Cass-Yaari OLG Model," Economics Working Papers 2000-14, Department of Economics and Business Economics, Aarhus University.
    36. Eiji Kurozumi & Daisuke Yamazaki & Kaddour Hadri, 2013. "Covariate Unit Root Test for Cross-Sectionally Dependent Panel Data," Economics Working Papers 13-01, Queen's Management School, Queen's University Belfast.
    37. Nikolaj Malchow-Moeller & Bo Jellesmark Thorsen, "undated". "A Dynamic Agricultural Household Model with Uncertain Income and Irreversible and Indivisible Investments under Credit Constraints," Economics Working Papers 2000-7, Department of Economics and Business Economics, Aarhus University.
    38. Ching-Chuan Tsong, 2010. "Are Real Exchange Rates Mean Reverting in Developing Economies in Asia? A Covariate Stationarity Approach," International Economic Journal, Taylor & Francis Journals, vol. 24(3), pages 397-412.
    39. Tsong Ching-Chuan & Lee Cheng-Feng & Tsai Li Ju, 2019. "A parametric stationarity test with smooth breaks," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 23(2), pages 1-14, April.
    40. Philip Kostov & John Lingard, 2004. "Regime-switching Vector Error Correction Model (VECM) analysis of UK meat consumption," Econometrics 0409007, University Library of Munich, Germany.
    41. Lee, Cheng-Feng & Tsong, Ching-Chuan, 2009. "Bootstrapping covariate stationarity tests for inflation rates," Economic Modelling, Elsevier, vol. 26(6), pages 1443-1448, November.
    42. Gaolu Zou, 2018. "Differences Between Prices of Goods and Services in China," The Journal of Social Sciences Research, Academic Research Publishing Group, vol. 4(2), pages 24-27, 02-2018.
    43. Hallin, M. & van den Akker, R. & Werker, B.J.M., 2011. "A Class of Simple Distribution-free Rank-based Unit Root Tests (Revision of DP 2010-72)," Discussion Paper 2011-002, Tilburg University, Center for Economic Research.
    44. Jansson, Michael, 2004. "Stationarity Testing With Covariates," Econometric Theory, Cambridge University Press, vol. 20(1), pages 56-94, February.
    45. Elliott, Graham & Pesavento, Elena, 2006. "On the Failure of Purchasing Power Parity for Bilateral Exchange Rates after 1973," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(6), pages 1405-1430, September.
    46. Ilir Miteza, 2012. "The Law of One Price in Six Central and Eastern European Economies," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 54(3), pages 581-596, September.
    47. Maria Elena Bontempi & Roberto Golinelli, 2012. "The effect of neglecting the slope parameters’ heterogeneity on dynamic models of corporate capital structure," Quantitative Finance, Taylor & Francis Journals, vol. 12(11), pages 1733-1751, November.
    48. Ching-Chuan Tsong & Cheng-Feng Lee, 2013. "Further Evidence On Real Interest Rate Equalization: Panel Information, Non-Linearities And Structural Changes," Bulletin of Economic Research, Wiley Blackwell, vol. 65, pages 85-105, May.
    49. Cheng-Feng Lee & Ching-Chuan Tsong, 2011. "Covariate selection for testing purchasing power parity," Applied Economics, Taylor & Francis Journals, vol. 43(15), pages 1923-1933.
    50. Tsong, Ching-Chuan & Lee, Cheng-Feng, 2011. "Asymmetric inflation dynamics: Evidence from quantile regression analysis," Journal of Macroeconomics, Elsevier, vol. 33(4), pages 668-680.
    51. Nikolaj Malchow-Moeller & Bo Jellesmark Thorsen, "undated". "Investment under Uncertainty - the Case of Repeated Investment Options," Economics Working Papers 2000-15, Department of Economics and Business Economics, Aarhus University.
    52. Tsong Ching-Chuan, 2012. "Unit Root Testing with Stationary Covariates in the Framework of Asymmetric STAR Nonlinearity," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(5), pages 1-27, December.
    53. Lance J. Bachmeier & Norman R. Swanson, 2003. "Predicting Inflation: Does The Quantity Theory Help?," Departmental Working Papers 200317, Rutgers University, Department of Economics.
    54. Tsong, Ching-Chuan, 2011. "Testing for a unit root with covariates against nonlinear alternatives," Economic Modelling, Elsevier, vol. 28(3), pages 1226-1234, May.
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Articles

  1. Graham Elliott & Nikolay Kudrin & Kaspar Wüthrich, 2022. "Detecting p‐Hacking," Econometrica, Econometric Society, vol. 90(2), pages 887-906, March.
    See citations under working paper version above.
  2. D. M. Davies & M. G. Verde & O. Mnyshenko & Y. R. Chen & R. Rajeev & Y. S. Meng & G. Elliott, 2019. "Combined economic and technological evaluation of battery energy storage for grid applications," Nature Energy, Nature, vol. 4(1), pages 42-50, January.

    Cited by:

    1. Wang, Qiao & Ye, Min & Cai, Xue & Sauer, Dirk Uwe & Li, Weihan, 2023. "Transferable data-driven capacity estimation for lithium-ion batteries with deep learning: A case study from laboratory to field applications," Applied Energy, Elsevier, vol. 350(C).
    2. Li, Mo & Yang, Yi & Smith, Timothy M. & Wilson, Elizabeth J., 2020. "Wind can reduce storage-induced emissions at grid scales," Applied Energy, Elsevier, vol. 276(C).
    3. Mathews, Ian & Xu, Bolun & He, Wei & Barreto, Vanessa & Buonassisi, Tonio & Peters, Ian Marius, 2020. "Technoeconomic model of second-life batteries for utility-scale solar considering calendar and cycle aging," Applied Energy, Elsevier, vol. 269(C).
    4. Alexandra von Meier & Elizabeth L. Ratnam & Kyle Brady & Keith Moffat & Jaimie Swartz, 2020. "Phasor-Based Control for Scalable Integration of Variable Energy Resources," Energies, MDPI, vol. 13(1), pages 1-14, January.
    5. Jafari, Mehdi & Botterud, Audun & Sakti, Apurba, 2020. "Estimating revenues from offshore wind-storage systems: The importance of advanced battery models," Applied Energy, Elsevier, vol. 276(C).
    6. Li, Canbing & Chen, Dawei & Li, Yingjie & Li, Furong & Li, Ran & Wu, Qiuwei & Liu, Xubin & Wei, Juan & He, Shengtao & Zhou, Bin & Allen, Stephen, 2022. "Exploring the interaction between renewables and energy storage for zero-carbon electricity systems," Energy, Elsevier, vol. 261(PA).
    7. Englberger, Stefan & Abo Gamra, Kareem & Tepe, Benedikt & Schreiber, Michael & Jossen, Andreas & Hesse, Holger, 2021. "Electric vehicle multi-use: Optimizing multiple value streams using mobile storage systems in a vehicle-to-grid context," Applied Energy, Elsevier, vol. 304(C).
    8. Chen, Dongwen & Li, Yong & Abbas, Zulkarnain & Li, Dehong & Wang, Ruzhu, 2022. "Network flow calculation based on the directional nodal potential method for meshed heating networks," Energy, Elsevier, vol. 243(C).
    9. Shi, Xingping & He, Qing & Lu, Chang & Wang, Tingting & Cui, Shuangshuang & Du, Dongmei, 2023. "Variable load modes and operation characteristics of closed Brayton cycle pumped thermal electricity storage system with liquid-phase storage," Renewable Energy, Elsevier, vol. 203(C), pages 715-730.
    10. Yuqiang Zeng & Fengyu Shen & Buyi Zhang & Jaeheon Lee & Divya Chalise & Qiye Zheng & Yanbao Fu & Sumanjeet Kaur & Sean D. Lubner & Vincent S. Battaglia & Bryan D. McCloskey & Michael C. Tucker & Ravi , 2023. "Nonintrusive thermal-wave sensor for operando quantification of degradation in commercial batteries," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    11. Yuhua Xia & Mengzheng Ouyang & Vladimir Yufit & Rui Tan & Anna Regoutz & Anqi Wang & Wenjie Mao & Barun Chakrabarti & Ashkan Kavei & Qilei Song & Anthony R. Kucernak & Nigel P. Brandon, 2022. "A cost-effective alkaline polysulfide-air redox flow battery enabled by a dual-membrane cell architecture," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    12. Zhou, Yuekuan, 2022. "Transition towards carbon-neutral districts based on storage techniques and spatiotemporal energy sharing with electrification and hydrogenation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    13. Schauf, Magnus & Schwenen, Sebastian, 2023. "System price dynamics for battery storage," Energy Policy, Elsevier, vol. 183(C).
    14. Zhang, Hongyan & Gao, Shuaizhi & Zhou, Peng, 2023. "Role of digitalization in energy storage technological innovation: Evidence from China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 171(C).
    15. Ruixue Liu & Guannan He & Xizhe Wang & Dharik Mallapragada & Hongbo Zhao & Yang Shao-Horn & Benben Jiang, 2024. "A cross-scale framework for evaluating flexibility values of battery and fuel cell electric vehicles," Nature Communications, Nature, vol. 15(1), pages 1-14, December.

  3. Graham Elliott, 2017. "Forecast combination when outcomes are difficult to predict," Empirical Economics, Springer, vol. 53(1), pages 7-20, August.

    Cited by:

    1. Cobb, Marcus P A, 2018. "Improving Underlying Scenarios for Aggregate Forecasts: A Multi-level Combination Approach," MPRA Paper 88593, University Library of Munich, Germany.
    2. Gael M. Martin & Rub'en Loaiza-Maya & David T. Frazier & Worapree Maneesoonthorn & Andr'es Ram'irez Hassan, 2020. "Optimal probabilistic forecasts: When do they work?," Papers 2009.09592, arXiv.org.
    3. Yongchen Zhao, 2021. "The robustness of forecast combination in unstable environments: a Monte Carlo study of advanced algorithms," Empirical Economics, Springer, vol. 61(1), pages 173-199, July.
    4. Marcus P. A. Cobb, 2020. "Aggregate density forecasting from disaggregate components using Bayesian VARs," Empirical Economics, Springer, vol. 58(1), pages 287-312, January.
    5. Knut Are Aastveit & James Mitchell & Francesco Ravazzolo & Herman van Dijk, 2018. "The Evolution of Forecast Density Combinations in Economics," Tinbergen Institute Discussion Papers 18-069/III, Tinbergen Institute.

  4. Graham Elliott & Allan Timmermann, 2016. "Forecasting in Economics and Finance," Annual Review of Economics, Annual Reviews, vol. 8(1), pages 81-110, October.
    See citations under working paper version above.
  5. Graham Elliott & Dalia Ghanem & Fabian Krüger, 2016. "Forecasting Conditional Probabilities of Binary Outcomes under Misspecification," The Review of Economics and Statistics, MIT Press, vol. 98(4), pages 742-755, October.

    Cited by:

    1. Werner Ehm & Tilmann Gneiting & Alexander Jordan & Fabian Krüger, 2016. "Of quantiles and expectiles: consistent scoring functions, Choquet representations and forecast rankings," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(3), pages 505-562, June.

  6. Graham Elliott & Ulrich K. Müller & Mark W. Watson, 2015. "Nearly Optimal Tests When a Nuisance Parameter Is Present Under the Null Hypothesis," Econometrica, Econometric Society, vol. 83, pages 771-811, March.
    See citations under working paper version above.
  7. Elliott, Graham & Gargano, Antonio & Timmermann, Allan, 2015. "Complete subset regressions with large-dimensional sets of predictors," Journal of Economic Dynamics and Control, Elsevier, vol. 54(C), pages 86-110.

    Cited by:

    1. Byron Botha & Rulof Burger & Kevin Kotze & Neil Rankin & Daan Steenkamp, 2022. "Big data forecasting of South African inflation," School of Economics Macroeconomic Discussion Paper Series 2022-03, School of Economics, University of Cape Town.
    2. Koop, Gary & Korobilis, Dimitris & Pettenuzzo, Davide, 2019. "Bayesian compressed vector autoregressions," Journal of Econometrics, Elsevier, vol. 210(1), pages 135-154.
    3. Timmermann, Allan, 2018. "Forecasting Methods in Finance," CEPR Discussion Papers 12692, C.E.P.R. Discussion Papers.
    4. 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.
    5. Cheng, Tingting & Jiang, Shan & Zhao, Albert Bo & Jia, Zhimin, 2023. "Complete subset averaging methods in corporate bond return prediction," Finance Research Letters, Elsevier, vol. 54(C).
    6. Araujo, Gustavo Silva & Gaglianone, Wagner Piazza, 2023. "Machine learning methods for inflation forecasting in Brazil: New contenders versus classical models," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 4(2).
    7. Antoine Mandel & Amir Sani, 2016. "Learning Time-Varying Forecast Combinations," Documents de travail du Centre d'Economie de la Sorbonne 16036, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    8. Antoine Mandel & Amir Sani, 2017. "A Machine Learning Approach to the Forecast Combination Puzzle," Working Papers halshs-01317974, HAL.
    9. 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.
    10. Garcia, Márcio G.P. & Medeiros, Marcelo C. & Vasconcelos, Gabriel F.R., 2017. "Real-time inflation forecasting with high-dimensional models: The case of Brazil," International Journal of Forecasting, Elsevier, vol. 33(3), pages 679-693.
    11. 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.
    12. Mukherjee, Krishnendu, 2024. "Machine Learning Methods for Surge Rate Prediction: A Case Study of Yassir," MPRA Paper 122151, University Library of Munich, Germany.
    13. Chen, Bin & Maung, Kenwin, 2023. "Time-varying forecast combination for high-dimensional data," Journal of Econometrics, Elsevier, vol. 237(2).
    14. Seojeong Lee & Youngki Shin, 2021. "Complete subset averaging with many instruments," The Econometrics Journal, Royal Economic Society, vol. 24(2), pages 290-314.
    15. Boot, Tom & Nibbering, Didier, 2019. "Forecasting using random subspace methods," Journal of Econometrics, Elsevier, vol. 209(2), pages 391-406.
    16. Lee, Ji Hyung & Shin, Youngki, 2023. "Complete Subset Averaging For Quantile Regressions," Econometric Theory, Cambridge University Press, vol. 39(1), pages 146-188, February.
    17. Rachidi Kotchoni & Maxime Leroux & Dalibor Stevanovic, 2019. "Macroeconomic Forecast Accuracy in data-rich environment," Post-Print hal-02435757, HAL.
    18. Seojeong Lee & Youngki Shin, 2018. "Optimal Estimation with Complete Subsets of Instruments," Department of Economics Working Papers 2018-15, McMaster University.
    19. Byung Yeon Kim & Heejoon Han, 2022. "Multi-Step-Ahead Forecasting of the CBOE Volatility Index in a Data-Rich Environment: Application of Random Forest with Boruta Algorithm," Korean Economic Review, Korean Economic Association, vol. 38, pages 541-569.
    20. Risse, Marian & Ohl, Ludwig, 2017. "Using dynamic model averaging in state space representation with dynamic Occam’s window and applications to the stock and gold market," Journal of Empirical Finance, Elsevier, vol. 44(C), pages 158-176.
    21. Costa, Alexandre Bonnet R. & Ferreira, Pedro Cavalcanti G. & Gaglianone, Wagner P. & Guillén, Osmani Teixeira C. & Issler, João Victor & Lin, Yihao, 2021. "Machine learning and oil price point and density forecasting," Energy Economics, Elsevier, vol. 102(C).
    22. Elliott, Graham & Timmermann, Allan G, 2016. "Forecasting in Economics and Finance," University of California at San Diego, Economics Working Paper Series qt6z55v472, Department of Economics, UC San Diego.
    23. Hollyman, Ross & Petropoulos, Fotios & Tipping, Michael E., 2021. "Understanding forecast reconciliation," European Journal of Operational Research, Elsevier, vol. 294(1), pages 149-160.
    24. Allan Timmermann, 2018. "Forecasting Methods in Finance," Annual Review of Financial Economics, Annual Reviews, vol. 10(1), pages 449-479, November.
    25. Risse, Marian, 2019. "Combining wavelet decomposition with machine learning to forecast gold returns," International Journal of Forecasting, Elsevier, vol. 35(2), pages 601-615.

  8. Elliott, Graham & Müller, Ulrich K., 2014. "Pre and post break parameter inference," Journal of Econometrics, Elsevier, vol. 180(2), pages 141-157.
    See citations under working paper version above.
  9. Elliott, Graham & Lieli, Robert P., 2013. "Predicting binary outcomes," Journal of Econometrics, Elsevier, vol. 174(1), pages 15-26.

    Cited by:

    1. Andrii Babii & Xi Chen & Eric Ghysels & Rohit Kumar, 2020. "Binary Choice with Asymmetric Loss in a Data-Rich Environment: Theory and an Application to Racial Justice," Papers 2010.08463, arXiv.org, revised Nov 2021.
    2. Mathias Drehmann, 2013. "Evaluating early warning indicators of banking crises: Satisfying policy requirements," BIS Working Papers 421, Bank for International Settlements.
    3. Toru Kitagawa & Aleksey Tetenov, 2018. "Who Should Be Treated? Empirical Welfare Maximization Methods for Treatment Choice," Econometrica, Econometric Society, vol. 86(2), pages 591-616, March.
    4. Kajal Lahiri & Cheng Yang, 2022. "ROC approach to forecasting recessions using daily yield spreads," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 57(4), pages 191-203, October.
    5. André K. Anundsen & Frank Hansen & Karsten Gerdrup & Kasper Kragh-Sørensen, 2014. "Bubbles and crises: The role of house prices and credit," Working Paper 2014/14, Norges Bank.
    6. Le-Yu Chen & Sokbae Lee, 2016. "Best Subset Binary Prediction," Papers 1610.02738, arXiv.org, revised May 2018.
    7. Nyberg, Henri & Pönkä, Harri, 2016. "International sign predictability of stock returns: The role of the United States," Economic Modelling, Elsevier, vol. 58(C), pages 323-338.
    8. Travis J. Berge, 2015. "Predicting Recessions with Leading Indicators: Model Averaging and Selection over the Business Cycle," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(6), pages 455-471, September.
    9. Knut Are Aastveit & André K. Anundsen & Eyo I. Herstad, 2017. "Residential investment and recession predictability," Working Paper 2017/24, Norges Bank.
    10. Davide Viviano & Jess Rudder, 2020. "Policy design in experiments with unknown interference," Papers 2011.08174, arXiv.org, revised May 2024.
    11. Robert Pal Lieli & Yu-Chin Hsu, 2018. "Using the Area Under an Estimated ROC Curve to Test the Adequacy of Binary Predictors," CEU Working Papers 2018_1, Department of Economics, Central European University.
    12. Timmermann, Allan & Elliott, Graham, 2007. "Economic Forecasting," CEPR Discussion Papers 6158, C.E.P.R. Discussion Papers.
    13. Davide Viviano, 2019. "Policy Targeting under Network Interference," Papers 1906.10258, arXiv.org, revised Apr 2024.
    14. Jiun-Hua Su, 2019. "Model Selection in Utility-Maximizing Binary Prediction," Papers 1903.00716, arXiv.org, revised Jul 2020.
    15. Kajal Lahiri & Cheng Yang, 2023. "ROC and PRC Approaches to Evaluate Recession Forecasts," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 19(2), pages 119-148, September.
    16. Daniel F. Pellatt, 2022. "PAC-Bayesian Treatment Allocation Under Budget Constraints," Papers 2212.09007, arXiv.org, revised Jun 2023.
    17. 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.
    18. Timothy Christensen & Hyungsik Roger Moon & Frank Schorfheide, 2020. "Robust Forecasting," PIER Working Paper Archive 20-038, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
      • Timothy Christensen & Hyungsik Roger Moon & Frank Schorfheide, 2020. "Robust Forecasting," Papers 2011.03153, arXiv.org, revised Dec 2020.
    19. Jianghao Chu & Tae-Hwy Lee & Aman Ullah, 2023. "Asymmetric AdaBoost for High-dimensional Maximum Score Regression," Working Papers 202306, University of California at Riverside, Department of Economics.
    20. Kai Feng & Han Hong & Ke Tang & Jingyuan Wang, 2019. "Decision Making with Machine Learning and ROC Curves," Papers 1905.02810, arXiv.org.
    21. Lieli, Robert P. & White, Halbert, 2010. "The construction of empirical credit scoring rules based on maximization principles," Journal of Econometrics, Elsevier, vol. 157(1), pages 110-119, July.
    22. Toru Kitagawa & Aleksey Tetenov, 2015. "Who should be treated? Empirical welfare maximization methods for treatment choice," CeMMAP working papers 10/15, Institute for Fiscal Studies.
    23. Su, Jiun-Hua, 2021. "Model selection in utility-maximizing binary prediction," Journal of Econometrics, Elsevier, vol. 223(1), pages 96-124.
    24. Blaskowitz, Oliver & Herwartz, Helmut, 2011. "On economic evaluation of directional forecasts," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1058-1065, October.
    25. Pönkä, Harri, 2015. "Real oil prices and the international sign predictability of stock returns," MPRA Paper 68330, University Library of Munich, Germany.
    26. Stanislav Anatolyev & Natalia Kryzhanovskaya, 2009. "Directional Prediction of Returns under Asymmetric Loss: Direct and Indirect Approaches," Working Papers w0136, Center for Economic and Financial Research (CEFIR).
    27. Martin Feldkircher & Thomas Gruber & Isabella Moder, 2014. "Using a Threshold Approach to Flag Vulnerabilities in CESEE Economies," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue 3, pages 8-30.
    28. Òscar Jordà & Alan M. Taylor, 2011. "Performance Evaluation of Zero Net-Investment Strategies," NBER Working Papers 17150, National Bureau of Economic Research, Inc.
    29. Madden, Gary & Mayer, Walter & Wu, Chen & Tran, Thien, 2015. "The forecasting accuracy of models of post-award network deployment: An application of maximum score tests," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1153-1158.
    30. Mathias Drehmann & Kostas Tsatsaronis, 2014. "The credit-to-GDP gap and countercyclical capital buffers: questions and answers," BIS Quarterly Review, Bank for International Settlements, March.
    31. Halbert White & Karim Chalak, 2008. "Identifying Structural Effects in Nonseparable Systems Using Covariates," Boston College Working Papers in Economics 734, Boston College Department of Economics.
    32. Travis J. Berge, 2011. "Forecasting disconnected exchange rates," Research Working Paper RWP 11-12, Federal Reserve Bank of Kansas City.
    33. Geršl, Adam & Jašová, Martina, 2018. "Credit-based early warning indicators of banking crises in emerging markets," Economic Systems, Elsevier, vol. 42(1), pages 18-31.
    34. Florios, Kostas & Skouras, Spyros, 2008. "Exact computation of max weighted score estimators," Journal of Econometrics, Elsevier, vol. 146(1), pages 86-91, September.
    35. Davide Viviano & Jelena Bradic, 2020. "Fair Policy Targeting," Papers 2005.12395, arXiv.org, revised Jun 2022.
    36. Nyberg, Henri, 2011. "Forecasting the direction of the US stock market with dynamic binary probit models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 561-578, April.
    37. Baidoo, Edwin & Natarajan, Ramachandran, 2021. "Profit-based credit models with lender’s attitude towards risk and loss," Journal of Behavioral and Experimental Finance, Elsevier, vol. 32(C).
    38. Lee, Seung Jung & Posenau, Kelly E. & Stebunovs, Viktors, 2020. "The anatomy of financial vulnerabilities and banking crises," Journal of Banking & Finance, Elsevier, vol. 112(C).

  10. Elliott, Graham & Gargano, Antonio & Timmermann, Allan, 2013. "Complete subset regressions," Journal of Econometrics, Elsevier, vol. 177(2), pages 357-373.
    See citations under working paper version above.
  11. Elliott, Graham, 2011. "A control function approach for testing the usefulness of trending variables in forecast models and linear regression," Journal of Econometrics, Elsevier, vol. 164(1), pages 79-91, September.

    Cited by:

    1. Christis Katsouris, 2023. "Structural Break Detection in Quantile Predictive Regression Models with Persistent Covariates," Papers 2302.05193, arXiv.org.
    2. 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.
    3. Yijie Fei, 2024. "A joint test of predictability and structural break in predictive regressions," Empirical Economics, Springer, vol. 67(3), pages 985-1013, September.
    4. Christis Katsouris, 2023. "Predictability Tests Robust against Parameter Instability," Papers 2307.15151, arXiv.org.
    5. Seema Narayan & Russell Smyth, 2015. "The Financial Econometrics of Price Discovery and Predictability," Monash Economics Working Papers 06-15, Monash University, Department of Economics.
    6. Phillips, Peter C.B. & Lee, Ji Hyung, 2013. "Predictive regression under various degrees of persistence and robust long-horizon regression," Journal of Econometrics, Elsevier, vol. 177(2), pages 250-264.
    7. 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.
    8. Cai, Zongwu & Chen, Haiqiang & Liao, Xiaosai, 2023. "A new robust inference for predictive quantile regression," Journal of Econometrics, Elsevier, vol. 234(1), pages 227-250.
    9. Christis Katsouris, 2022. "Partial Sum Processes of Residual-Based and Wald-type Break-Point Statistics in Time Series Regression Models," Papers 2202.00141, arXiv.org, revised Feb 2022.

  12. Elliott, Graham & Pesavento, Elena, 2009. "Testing The Null Of No Cointegration When Covariates Are Known To Have A Unit Root," Econometric Theory, Cambridge University Press, vol. 25(6), pages 1829-1850, December.

    Cited by:

    1. Game Aaron & Wu Jason, 2013. "A Covariate Residual-Based Cointegration Test Applied to the CDS-Bond Basis," Journal of Time Series Econometrics, De Gruyter, vol. 5(2), pages 163-192, April.
    2. 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.
    3. Maxwell L. King & Sivagowry Sriananthakumar, 2015. "Point Optimal Testing: A Survey of the Post 1987 Literature," Monash Econometrics and Business Statistics Working Papers 5/15, Monash University, Department of Econometrics and Business Statistics.

  13. Graham Elliott & Ivana Komunjer & Allan Timmermann, 2008. "Biases in Macroeconomic Forecasts: Irrationality or Asymmetric Loss?," Journal of the European Economic Association, MIT Press, vol. 6(1), pages 122-157, March.
    See citations under working paper version above.
  14. Graham Elliott & Allan Timmermann, 2008. "Economic Forecasting," Journal of Economic Literature, American Economic Association, vol. 46(1), pages 3-56, March.
    See citations under working paper version above.
  15. Elliott, Graham & Muller, Ulrich K., 2007. "Confidence sets for the date of a single break in linear time series regressions," Journal of Econometrics, Elsevier, vol. 141(2), pages 1196-1218, December.
    See citations under working paper version above.
  16. 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.

    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. Bo Zhou, 2023. "Semiparametrically Optimal Cointegration Test," Papers 2305.08880, arXiv.org.
    3. Tran Viet Ha, 2009. "A discussion on power of ADF F-test with unexpected initial value," Applied Economics Letters, Taylor & Francis Journals, vol. 16(17), pages 1699-1703.
    4. Anton Skrobotov, 2016. "On Trend Breaks and Initial Condition in Unit Root Testing," Working Papers 0097, Gaidar Institute for Economic Policy, revised 2016.
    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. 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.
    7. Westerlund, Joakim, 2014. "Pooled panel unit root tests and the effect of past initialization," Working Papers fe_2014_06, Deakin University, Department of Economics.
    8. Smeekes, S., 2009. "Detrending bootstrap unit root tests," Research Memorandum 056, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    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. Matei Demetrescu & Christoph Hanck, 2016. "Robust Inference for Near-Unit Root Processes with Time-Varying Error Variances," Econometric Reviews, Taylor & Francis Journals, vol. 35(5), pages 751-781, May.
    11. Fabio Busetti & Silvia Fabiani & Andrew Harvey, 2006. "Convergence of Prices and Rates of Inflation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(s1), pages 863-877, December.
    12. Chambers, MJ, 2013. "The Calculation of Some Limiting Distributions Arising in Near-Integrated Models with GLS Detrending," Economics Discussion Papers 8975, University of Essex, Department of Economics.
    13. Niels Haldrup & Robinson Kruse & Timo Teräsvirta & Rasmus T. Varneskov, 2012. "Unit roots, nonlinearities and structural breaks," CREATES Research Papers 2012-14, Department of Economics and Business Economics, Aarhus University.
    14. Peter C.B. Phillips & Tassos Magdalinos, 2008. "Unit Root and Cointegrating Limit Theory When Initialization Is in the Infinite Past," Cowles Foundation Discussion Papers 1655, Cowles Foundation for Research in Economics, Yale University.
    15. 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.
    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. Marc Hallin & Ramon van den Akker & Bas J.M. Werker, 2011. "A class of simple distribution-free rank-based unit root tests," Post-Print hal-00834424, HAL.
    18. Chen, Jia & Li, Degui & Zhang, Lixin, 2010. "Robust estimation in a nonlinear cointegration model," Journal of Multivariate Analysis, Elsevier, vol. 101(3), pages 706-717, March.
    19. 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.
    20. 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.
    21. 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.
    22. Shelef, Amit, 2016. "A Gini-based unit root test," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 763-772.
    23. Aman Ullah & Yong Bao & Yun Wang, 2014. "Exact Distribution of the Mean Reversion Estimator in the Ornstein-Uhlenbeck Process," Working Papers 201413, University of California at Riverside, Department of Economics.
    24. Hallin, M. & van den Akker, R. & Werker, B.J.M., 2011. "A Class of Simple Distribution-free Rank-based Unit Root Tests (Revision of DP 2010-72)," Discussion Paper 2011-002, Tilburg University, Center for Economic Research.
    25. 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.
    26. 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.
    27. Bent Nielsen, 2003. "Power of tests for unit roots in the presence of a linear trend," Economics Papers 2003-W22, Economics Group, Nuffield College, University of Oxford.
    28. Ahlgren, Niklas & Juselius, Mikael, 2009. "Tests for Cointegration Rank and the Initial Condition," Working Papers 539, Hanken School of Economics.
    29. 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.
    30. Kazuhiko Hayakawa, 2008. "On the Effect of Nonstationary Initial Conditions in Dynamic Panel Data Models," Hi-Stat Discussion Paper Series d07-245, Institute of Economic Research, Hitotsubashi University.
    31. Heon Lee, 2021. "Money Creation and Banking: Theory and Evidence," Papers 2109.15096, arXiv.org, revised Jun 2024.
    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.

  17. Elliott, Graham & Pesavento, Elena, 2006. "On the Failure of Purchasing Power Parity for Bilateral Exchange Rates after 1973," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(6), pages 1405-1430, September.

    Cited by:

    1. Galvao Jr., Antonio F., 2009. "Unit root quantile autoregression testing using covariates," Journal of Econometrics, Elsevier, vol. 152(2), pages 165-178, October.
    2. Fossati, Sebastian, 2011. "Covariate Unit Root Tests with Good Size and Power," Working Papers 2011-4, University of Alberta, Department of Economics.
    3. Matteo Pelagatti & Emilio Colombo, 2012. "Unpuzzling the Purchasing Power Parity Puzzle," Working Papers 221, University of Milano-Bicocca, Department of Economics, revised Mar 2012.
    4. Lopez, Claude & Murray, Chris & Papell, David, 2009. "Median-Unbiased Estimation in DF-GLS Regressions and the PPP Puzzle," MPRA Paper 26091, University Library of Munich, Germany.
    5. Mauro Costantini & Claudio Lupi, 2013. "A Simple Panel-CADF Test for Unit Roots," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(2), pages 276-296, April.
    6. Mohsen Bahmani-Oskooee & Tsangyao Chang & Tsung-Hsien Chen & Han-Wen Tzeng, 2017. "Revisiting purchasing power parity in Eastern European countries: quantile unit root tests," Empirical Economics, Springer, vol. 52(2), pages 463-483, March.
    7. J. M. Belbute & Júlio A. Delgado & Suzana C. Monteiro & Teresa E. Pascoa, 2016. "Measuring persistence in nominal exchange rate: Implications for Angola’s entrepreneurship and business development," International Journal of Finance, Insurance and Risk Management, International Journal of Finance, Insurance and Risk Management, vol. 6(3), pages 1180-1180.
    8. Yanping Chong & Òscar Jordà & Alan M. Taylor, 2012. "The Harrod–Balassa–Samuelson Hypothesis: Real Exchange Rates And Their Long‐Run Equilibrium," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 53(2), pages 609-634, May.
    9. Yi-Hua Wu & Eric Lin, 2011. "Does purchasing power parity hold following the launch of the euro? Evidence from the panel unit root test," Applied Economics Letters, Taylor & Francis Journals, vol. 18(2), pages 167-172.
    10. Christopoulos, Dimitris K. & León-Ledesma, Miguel A., 2010. "Smooth breaks and non-linear mean reversion: Post-Bretton Woods real exchange rates," Journal of International Money and Finance, Elsevier, vol. 29(6), pages 1076-1093, October.
    11. Kim, Soyoung & Lima, Luiz Renato, 2010. "Local persistence and the PPP hypothesis," Journal of International Money and Finance, Elsevier, vol. 29(3), pages 555-569, April.
    12. Kaddour Hadri & Eiji Kurozumi & Daisuke Yamazaki, 2015. "Synergy between an Improved Covariate Unit Root Test and Cross-sectionally Dependent Panel Data Unit Root Tests," Manchester School, University of Manchester, vol. 83(6), pages 676-700, December.
    13. Yang, Yang & Zhao, Zhao, 2020. "Quantile nonlinear unit root test with covariates and an application to the PPP hypothesis," Economic Modelling, Elsevier, vol. 93(C), pages 728-736.
    14. Eiji Kurozumi & Daisuke Yamazaki & Kaddour Hadri, 2013. "Covariate Unit Root Test for Cross-Sectionally Dependent Panel Data," Economics Working Papers 13-01, Queen's Management School, Queen's University Belfast.
    15. Ching-Chuan Tsong, 2010. "Are Real Exchange Rates Mean Reverting in Developing Economies in Asia? A Covariate Stationarity Approach," International Economic Journal, Taylor & Francis Journals, vol. 24(3), pages 397-412.
    16. Shiu-Sheng Chen, 2012. "Does extracting inflation from stock returns solve the purchasing power parity puzzle?," Empirical Economics, Springer, vol. 42(3), pages 1097-1105, June.
    17. Jae H. Kim & In Choi, 2017. "Unit Roots in Economic and Financial Time Series: A Re-Evaluation at the Decision-Based Significance Levels," Econometrics, MDPI, vol. 5(3), pages 1-23, September.
    18. Kim, Jae & Choi, In, 2015. "Unit Roots in Economic and Financial Time Series: A Re-Evaluation based on Enlightened Judgement," MPRA Paper 68411, University Library of Munich, Germany.
    19. Ilir Miteza, 2012. "The Law of One Price in Six Central and Eastern European Economies," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 54(3), pages 581-596, September.
    20. Cheng-Feng Lee & Ching-Chuan Tsong, 2011. "Covariate selection for testing purchasing power parity," Applied Economics, Taylor & Francis Journals, vol. 43(15), pages 1923-1933.
    21. Lupi, Claudio, 2009. "Unit Root CADF Testing with R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 32(i02).

  18. Graham Elliott & Ulrich K. Muller, 2006. "Efficient Tests for General Persistent Time Variation in Regression Coefficients," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 73(4), pages 907-940.

    Cited by:

    1. Qazi Haque & Leandro M. Magnusson, 2020. "Identification robust empirical evidence on the Euler equation in open economies," CAMA Working Papers 2020-07, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    2. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    3. Yin, Anwen, 2015. "Forecasting and model averaging with structural breaks," ISU General Staff Papers 201501010800005727, Iowa State University, Department of Economics.
    4. Elliott, Graham & Muller, Ulrich K., 2007. "Confidence sets for the date of a single break in linear time series regressions," Journal of Econometrics, Elsevier, vol. 141(2), pages 1196-1218, December.
    5. Dario Caldara & Cristina Fuentes-Albero & Simon Gilchrist & Egon Zakrajšek, 2016. "The Macroeconomic Impact of Financial and Uncertainty Shocks," International Finance Discussion Papers 1166, Board of Governors of the Federal Reserve System (U.S.).
    6. Geoffrey Ngene & Charles Lambert & Ali Darrat, 2015. "Testing Long Memory in the Presence of Structural Breaks: An Application to Regional and National Housing Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 50(4), pages 465-483, May.
    7. Fabian Baetje & Lukas Menkhoff, 2016. "Equity Premium Prediction: Are Economic and Technical Indicators Unstable?," Discussion Papers of DIW Berlin 1552, DIW Berlin, German Institute for Economic Research.
    8. Ted Juhl & Zhijie Xiao, 2009. "Tests for Changing Mean with Monotonic Power," Boston College Working Papers in Economics 709, Boston College Department of Economics.
    9. Christopher J. Neely & David E. Rapach, 2008. "Real interest rate persistence: evidence and implications," Review, Federal Reserve Bank of St. Louis, vol. 90(Nov), pages 609-642.
    10. Timmermann, Allan & Pettenuzzo, Davide, 2016. "Forecasting Macroeconomic Variables under Model Instability," CEPR Discussion Papers 11355, C.E.P.R. Discussion Papers.
    11. Hervé Ott, 2014. "Extent and possible causes of intrayear agricultural commodity price volatility," Agricultural Economics, International Association of Agricultural Economists, vol. 45(2), pages 225-252, March.
    12. Barbara Rossi & Atsushi Inoue & Yiru Wang, 2024. "Has the Phillips curve flattened?," French Stata Users' Group Meetings 2024 22, Stata Users Group.
    13. Carneiro, Pedro & Locatelli, Andrea & Ghebremeskel, Tewolde & Keating, Joseph, 2012. "Do Public Health Interventions Crowd Out Private Health Investments? Malaria Control Policies in Eritrea," IZA Discussion Papers 6560, Institute of Labor Economics (IZA).
    14. Ben Omrane, Walid & Savaser, Tanseli & Welch, Robert & Zhou, Xinyao, 2019. "Time-varying effects of macroeconomic news on euro-dollar returns," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    15. 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.
    16. Abhimanyu Gupta & Myung Hwan Seo, 2019. "Robust Inference on Infinite and Growing Dimensional Time Series Regression," Papers 1911.08637, arXiv.org, revised Apr 2023.
    17. Lin, Qi, 2018. "Technical analysis and stock return predictability: An aligned approach," Journal of Financial Markets, Elsevier, vol. 38(C), pages 103-123.
    18. Nagayasu, Jun, 2013. "The Forward Premium Puzzle And The Euro," MPRA Paper 45746, University Library of Munich, Germany.
    19. Tristan Jourde, 2022. "The Rising Interconnectedness of the Insurance Sector," Working papers 857, Banque de France.
    20. Pierre Perron & Yohei Yamamoto, 2022. "Structural change tests under heteroskedasticity: Joint estimation versus two‐steps methods," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(3), pages 389-411, May.
    21. Paulo M.M. Rodrigues & Matei Demetrescu, 2019. "Testing for Episodic Predictability in Stock Returns," Working Papers w201906, Banco de Portugal, Economics and Research Department.
    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. Dong Jin Lee, 2021. "Bootstrap tests for structural breaks when the regressors and the serially correlated error term are unstable," Bulletin of Economic Research, Wiley Blackwell, vol. 73(2), pages 212-229, April.
    24. Seong Yeon Chang & Pierre Perron, 2013. "A Comparison of Alternative Methods to Construct Confidence Intervals for the Estimate of a Break Date in Linear Regression Models," Boston University - Department of Economics - Working Papers Series wp2015-010, Boston University - Department of Economics, revised 11 Oct 2015.
    25. 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.
    26. YAMAZAKI, Daisuke & 山崎, 大輔 & KUROZUMI, Eiji & 黒住, 英司, 2014. "Improving the Finite Sample Performance of Tests for a Shift in Mean," Discussion Papers 2014-16, Graduate School of Economics, Hitotsubashi University.
    27. Alessandro Casini, 2018. "Tests for Forecast Instability and Forecast Failure under a Continuous Record Asymptotic Framework," Papers 1803.10883, arXiv.org, revised Dec 2018.
    28. Dong Jin Lee, 2009. "Testing Parameter Stability in Quantile Models: An Application to the U.S. Inflation Process," Working papers 2009-26, University of Connecticut, Department of Economics.
    29. Schrimpf, Andreas & Wang, Qingwei, 2010. "A reappraisal of the leading indicator properties of the yield curve under structural instability," International Journal of Forecasting, Elsevier, vol. 26(4), pages 836-857, October.
    30. Silva, Ivair Ramos & Ernesto, Dulcidia & Oliveira, Fernando & Marques, Reinaldo & Oliveira, Anderson, 2021. "Monte Carlo Test for Stochastic Trend in Space State Models for the Location-Scale Family," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 40(2), April.
    31. James D. Hamilton & Ethan S. Harris & Jan Hatzius & Kenneth D. West, 2016. "The Equilibrium Real Funds Rate: Past, Present, and Future," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 64(4), pages 660-707, November.
    32. Dong Jin Lee & Jong Chil Son, 2011. "Nonlinearity and Structural Breaks in Monetary Policy Rules with Stock Prices," Working papers 2011-19, University of Connecticut, Department of Economics.
    33. Raffaella Giacomini & Barbara Rossi, 2014. "Forecasting in Nonstationary Environments: What Works and What Doesn't in Reduced-Form and Structural Models," Working Papers 819, Barcelona School of Economics.
    34. Leland E. Farmer & Lawrence Schmidt & Allan Timmermann, 2023. "Pockets of Predictability," Journal of Finance, American Finance Association, vol. 78(3), pages 1279-1341, June.
    35. Dr. Christian Grisse & Dr. Thomas Nitschka, 2014. "Exchange rate returns and external adjustment: evidence from Switzerland," Working Papers 2014-12, Swiss National Bank.
    36. KUROZUMI, Eiji & 黒住, 英司 & YAMAMOTO, Yohei & 山本, 庸平, 2015. "Confidence Sets for the Break Date Based on Optimal Tests," Discussion Papers 2015-01, Graduate School of Economics, Hitotsubashi University.
    37. Linda S. Goldberg & Michael W. Klein, 2007. "Establishing Credibility: Evolving Perceptions of the European Central Bank," The Institute for International Integration Studies Discussion Paper Series iiisdp194, IIIS.
    38. Timmermann, Allan & Elliott, Graham, 2007. "Economic Forecasting," CEPR Discussion Papers 6158, C.E.P.R. Discussion Papers.
    39. Yu, Deshui & Huang, Difang & Chen, Li & Li, Luyang, 2023. "Forecasting dividend growth: The role of adjusted earnings yield," Economic Modelling, Elsevier, vol. 120(C).
    40. Ulrich Haskamp, 2014. "Was Spanish fiscal policy sustainable?," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 41(2), pages 273-286, May.
    41. Russell Davidson & Niels S. Grønborg, 2018. "Time-varying parameters: New test tailored to applications in finance and macroeconomics," CREATES Research Papers 2018-22, Department of Economics and Business Economics, Aarhus University.
    42. Ott, Herve, 2012. "Which factors drive which volatility in the grain sector?," 123rd Seminar, February 23-24, 2012, Dublin, Ireland 122486, European Association of Agricultural Economists.
    43. Yijie Fei, 2024. "A joint test of predictability and structural break in predictive regressions," Empirical Economics, Springer, vol. 67(3), pages 985-1013, September.
    44. Li, Hong, 2008. "Estimation and testing of Euler equation models with time-varying reduced-form coefficients," Journal of Econometrics, Elsevier, vol. 142(1), pages 425-448, January.
    45. Thomas Nitschka, 2022. "China’s anti-corruption campaign and stock returns of luxury goods firms," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 36(2), pages 159-177, June.
    46. Zongwu Cai & Seong Yeon Chang, 2018. "A New Test In A Predictive Regression with Structural Breaks," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201811, University of Kansas, Department of Economics, revised Dec 2018.
    47. Barbara Rossi & Raffaella Giacomini, 2010. "Model Comparisons in Unstable Environments," Working Papers 10-29, Duke University, Department of Economics.
    48. Elliott, Graham & Müller, Ulrich K, 2014. "Pre and post break parameter inference," University of California at San Diego, Economics Working Paper Series qt4j733246, Department of Economics, UC San Diego.
    49. 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.
    50. David W. Berger & Alain P. Chaboud & Erik Hjalmarsson & Edward Howorka, 2006. "What drives volatility persistence in the foreign exchange market?," International Finance Discussion Papers 862, Board of Governors of the Federal Reserve System (U.S.).
    51. Ulrich K. Müller & Mark W. Watson, 2020. "Low-Frequency Analysis of Economic Time Series," Working Papers 2020-13, Princeton University. Economics Department..
    52. Linda S. Goldberg & Dr. Christian Grisse, 2013. "Time variation in asset price responses to macro announcements," Working Papers 2013-11, Swiss National Bank.
    53. Fu, Zhonghao & Hong, Yongmiao, 2019. "A model-free consistent test for structural change in regression possibly with endogeneity," Journal of Econometrics, Elsevier, vol. 211(1), pages 206-242.
    54. Entrop, O. & von la Hausse, L. & Wilkens, M., 2017. "Looking beyond banks’ average interest rate risk: Determinants of high exposures," The Quarterly Review of Economics and Finance, Elsevier, vol. 63(C), pages 204-218.
    55. Alessandro Casini & Pierre Perron, 2018. "Continuous Record Asymptotics for Change-Points Models," Papers 1803.10881, arXiv.org, revised Nov 2021.
    56. Tatiana PÎŞCHINA & Romeo Fortuna, 2017. "Moldova’s Phenomenon: Can Foreign Investments Help Out of the Poverty Circle?," European Journal of Economics and Business Studies Articles, Revistia Research and Publishing, vol. 3, ejes_v3_i.
    57. Müller, Ulrich K. & Wang, Yulong, 2019. "Nearly weighted risk minimal unbiased estimation," Journal of Econometrics, Elsevier, vol. 209(1), pages 18-34.
    58. Dr. Thomas Nitschka, 2018. "Did China's anti-corruption campaign affect the risk premium on stocks of global luxury goods firms?," Working Papers 2018-09, Swiss National Bank.
    59. Tatsuru Kikuchi & Toranosuke Onishi & Kenichi Ueda, 2021. "Price Stability of Cryptocurrencies as a Medium of Exchange," Papers 2111.08390, arXiv.org.
    60. Raffaella Giacomini & Barbara Rossi, 2012. "Model comparisons in unstable environments," CeMMAP working papers 13/12, Institute for Fiscal Studies.
    61. Eddie Gerba & Klemens Hauzenberger, 2013. "Estimating US Fiscal and Monetary Interactions in a Time Varying VAR," Studies in Economics 1303, School of Economics, University of Kent.
    62. Victoria Atanasov & Stig V. Møller & Richard Priestley, 2020. "Consumption Fluctuations and Expected Returns," Journal of Finance, American Finance Association, vol. 75(3), pages 1677-1713, June.
    63. Pettenuzzo, Davide & Timmermann, Allan, 2011. "Predictability of stock returns and asset allocation under structural breaks," Journal of Econometrics, Elsevier, vol. 164(1), pages 60-78, September.
    64. Alexandra Janssen & Rahel Studer, 2014. "The Swiss franc's honeymoon," ECON - Working Papers 170, Department of Economics - University of Zurich, revised Jan 2017.
    65. Linda S. Goldberg & Michael W. Klein, 2011. "Evolving Perceptions of Central Bank Credibility: The European Central Bank Experience," NBER International Seminar on Macroeconomics, University of Chicago Press, vol. 7(1), pages 153-182.
    66. Dong Jin Lee, 2020. "Optimal tests for parameter breaking process in conditional quantile models," The Japanese Economic Review, Springer, vol. 71(3), pages 479-510, July.
    67. Cyril May & Greg Farrell & Jannie Rossouw, 2018. "Do Monetary Policy Announcements Affect Exchange Rate Returns and Volatility of Returns? Some Evidence from High‐Frequency Intra‐Day South African Data," South African Journal of Economics, Economic Society of South Africa, vol. 86(3), pages 308-338, September.
    68. 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.
    69. Lin, Qi & Lin, Xi, 2021. "Cash conversion cycle and aggregate stock returns," Journal of Financial Markets, Elsevier, vol. 52(C).
    70. Pierre Perron & Yohei Yamamoto, 2008. "On the Usefulness or Lack Thereof of Optimality Criteria for Structural Change Tests," Boston University - Department of Economics - Working Papers Series wp2008-006, Boston University - Department of Economics.
    71. Atanasov, Victoria, 2021. "Unemployment and aggregate stock returns," Journal of Banking & Finance, Elsevier, vol. 129(C).
    72. Grisse, Christian & Nitschka, Thomas, 2015. "On financial risk and the safe haven characteristics of Swiss franc exchange rates," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 153-164.
    73. Smith, Simon C. & Timmermann, Allan & Zhu, Yinchu, 2019. "Variable selection in panel models with breaks," Journal of Econometrics, Elsevier, vol. 212(1), pages 323-344.
    74. Fossati, Sebastian, 2014. "Output Growth and Commodity Prices in Latin America: What Has Changed?," Working Papers 2014-11, University of Alberta, Department of Economics.
    75. Balaguer, Jacint, 2011. "Cross-border integration in the European electricity market. Evidence from the pricing behavior of Norwegian and Swiss exporters," Energy Policy, Elsevier, vol. 39(9), pages 4703-4712, September.
    76. Yamamoto, Yohei & Tanaka, Shinya, 2015. "Testing for factor loading structural change under common breaks," Journal of Econometrics, Elsevier, vol. 189(1), pages 187-206.
    77. Fabio Busetti, 2012. "On detecting end-of-sample instabilities," Temi di discussione (Economic working papers) 881, Bank of Italy, Economic Research and International Relations Area.
    78. Sebastian Fossati, 2017. "Output Growth And Structural Reform In Latin America: Have Business Cycles Changed?," Contemporary Economic Policy, Western Economic Association International, vol. 35(1), pages 62-75, January.
    79. Michael Fung, 2014. "Ocean Carriers’ Collusion Under Antitrust Immunity: Evidence of Asymmetric Pass-Through," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 45(1), pages 59-77, August.
    80. Raushan Kumar, 2017. "Price Discovery in Some Primary Commodity Markets in India," Economics Bulletin, AccessEcon, vol. 37(3), pages 1817-1829.
    81. 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).
    82. Simon Gilchrist & Egon Zakrajšek, 2019. "Trade Exposure and the Evolution of Inflation Dynamics," Finance and Economics Discussion Series 2019-007, Board of Governors of the Federal Reserve System (U.S.).
    83. Rapach, David & Zhou, Guofu, 2013. "Forecasting Stock Returns," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 328-383, Elsevier.
    84. Ivan Mendieta-Muñoz, 2014. "Is there any relationship between the rates of interest and profit in the U.S. economy?," Studies in Economics 1416, School of Economics, University of Kent.
    85. Francesco Calvori & Drew Creal & Siem Jan Koopman & Andre Lucas, 2014. "Testing for Parameter Instability in Competing Modeling Frameworks," Tinbergen Institute Discussion Papers 14-010/IV/DSF71, Tinbergen Institute.
    86. Ludwig Hausse & Martin Rohleder & Marco Wilkens, 2016. "Systemic interest rate and market risk at US banks," Journal of Business Economics, Springer, vol. 86(8), pages 933-961, November.
    87. Yu, Deshui & Chen, Li & Li, Luyang, 2023. "Nonparametric modeling for the time-varying persistence of inflation," Economics Letters, Elsevier, vol. 225(C).
    88. Albulescu, C.T. & Bouri, E. & Tiwari, A.K. & Roubaud, D., 2020. "Quantile causality between banking stock and real estate securities returns in the US," The Quarterly Review of Economics and Finance, Elsevier, vol. 78(C), pages 251-260.
    89. Atanasov, Victoria, 2018. "World output gap and global stock returns," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 181-197.
    90. Elliott, Graham & Timmermann, Allan G, 2016. "Forecasting in Economics and Finance," University of California at San Diego, Economics Working Paper Series qt6z55v472, Department of Economics, UC San Diego.
    91. Amir Rubin & Daniel Smith, 2010. "Comparing Different Explanations of the Volatility Trend," NCER Working Paper Series 68, National Centre for Econometric Research.
    92. Qazi Haque & Leandro M. Magnusson, 2023. "Identification Robust Empirical Evidence on the Open Economy IS‐Curve," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(2), pages 345-372, April.
    93. Leandro M. Magnusson & Sophocles Mavroeidis, 2014. "Identification Using Stability Restrictions," Econometrica, Econometric Society, vol. 82, pages 1799-1851, September.
    94. Stock, J.H. & Watson, M.W., 2016. "Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 415-525, Elsevier.
    95. Dong Jin Lee, 2016. "Parametric and Semi-Parametric Efficient Tests for Parameter Instability," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(4), pages 451-475, July.
    96. Dong Jin Lee & Jai Hyung Yoon, 2012. "The New Keynesian Phillips Curves in Multiple Quantiles and the Asymmetry of Monetary Policy," Working papers 2012-03, University of Connecticut, Department of Economics.
    97. 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.

  19. Swanson, Norman R. & Elliott, Graham & Ghysels, Eric & Gonzalo, Jesus, 2006. "Predictive methodology and application in economics and finance: Volume in honor of the accomplishments of Clive W.J. Granger," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 1-9.

    Cited by:

    1. Wei, Yu & Wang, Yudong & Huang, Dengshi, 2010. "Forecasting crude oil market volatility: Further evidence using GARCH-class models," Energy Economics, Elsevier, vol. 32(6), pages 1477-1484, November.
    2. Yu, Xing & Li, Yanyan & Lu, Junli & Shen, Xilin, 2023. "Futures hedging in crude oil markets: A trade-off between risk and return," Resources Policy, Elsevier, vol. 80(C).
    3. Wei, Yu, 2012. "Forecasting volatility of fuel oil futures in China: GARCH-type, SV or realized volatility models?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(22), pages 5546-5556.
    4. Martina Assereto & Julie Byrne, 2020. "The Implications of Policy Uncertainty on Solar Photovoltaic Investment," Energies, MDPI, vol. 13(23), pages 1-20, November.

  20. Graham Elliott & Allan Timmermann & Ivana Komunjer, 2005. "Estimation and Testing of Forecast Rationality under Flexible Loss," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(4), pages 1107-1125.

    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. Ivana Komunjer & Michael T. Owyang, 2012. "Multivariate Forecast Evaluation and Rationality Testing," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1066-1080, November.
    3. Stan Hurn & Jing Tian & Lina Xu, 2021. "Assessing the Informational Content of Official Australian Bureau of Meteorology Forecasts of Wind Speed," The Economic Record, The Economic Society of Australia, vol. 97(319), pages 525-547, December.
    4. 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.
    5. Michael Frenkel & Jin-Kyu Jung & Jan-Christoph Rülke, 2017. "Rationalizing the Bias in Central Banks' Interest Rate Projections," WHU Working Paper Series - Economics Group 17-03, WHU - Otto Beisheim School of Management.
    6. Lee, Tae-Hwy & Ullah, Aman & Wang, He, 2018. "The second-order bias of quantile estimators," Economics Letters, Elsevier, vol. 173(C), pages 143-147.
    7. Kilian, Lutz & Alquist, Ron, 2007. "What Do We Learn from the Price of Crude Oil Futures?," CEPR Discussion Papers 6548, C.E.P.R. Discussion Papers.
    8. Wieland, Volker & Wolters, Maik, 2013. "Forecasting and Policy Making," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 239-325, Elsevier.
    9. Emmanuel C. Mamatzakis & Mike G. Tsionas, 2020. "Revealing forecaster's preferences: A Bayesian multivariate loss function approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 412-437, April.
    10. Carlos Capistrán-Carmona, 2005. "Bias in Federal Reserve Inflation Forecasts: Is the Federal Reserve Irrational or Just Cautious?," Computing in Economics and Finance 2005 127, Society for Computational Economics.
    11. Aretz, Kevin & Bartram, Söhnke M. & Pope, Peter F., 2011. "Asymmetric Loss Functions and the Rationality of Expected Stock Returns," MPRA Paper 47343, University Library of Munich, Germany.
    12. Emilio Zanetti Chini, 2018. "Forecaster’s utility and forecasts coherence," CREATES Research Papers 2018-01, Department of Economics and Business Economics, Aarhus University.
    13. Christian Pierdzioch & Jan-Christoph Rülke & Peter Tillmann, 2013. "Using forecasts to uncover the loss function of FOMC members," MAGKS Papers on Economics 201302, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    14. Pierdzioch, Christian & Rülke, Jan-Christoph & Stadtmann, Georg, 2015. "Central banks’ inflation forecasts under asymmetric loss: Evidence from four Latin-American countries," Economics Letters, Elsevier, vol. 129(C), pages 66-70.
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    152. Pierdzioch, Christian & Risse, Marian & Rohloff, Sebastian, 2016. "A boosting approach to forecasting the volatility of gold-price fluctuations under flexible loss," Resources Policy, Elsevier, vol. 47(C), pages 95-107.
    153. 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.
    154. Giovannelli, Alessandro & Pericoli, Filippo Maria, 2020. "Are GDP forecasts optimal? Evidence on European countries," International Journal of Forecasting, Elsevier, vol. 36(3), pages 963-973.
    155. Baghestani, Hamid & Khallaf, Ashraf, 2012. "Predictions of growth in U.S. corporate profits: Asymmetric vs. symmetric loss," International Review of Economics & Finance, Elsevier, vol. 22(1), pages 222-229.
    156. Ghysels, Eric & Wright, Jonathan H., 2009. "Forecasting Professional Forecasters," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 504-516.
    157. Hamid Baghestani, 2014. "On the loss structure of federal reserve forecasts of output growth," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 38(3), pages 518-527, July.
    158. Collin Philipps, 2022. "Interpreting Expectiles," Working Papers 2022-01, Department of Economics and Geosciences, US Air Force Academy.
    159. Tsuchiya, Yoichi, 2016. "Assessing macroeconomic forecasts for Japan under an asymmetric loss function," International Journal of Forecasting, Elsevier, vol. 32(2), pages 233-242.
    160. Schnatz, Bernd & D'Agostino, Antonello, 2012. "Survey-based nowcasting of US growth: a real-time forecast comparison over more than 40 years," Working Paper Series 1455, European Central Bank.
    161. Gneiting, Tilmann, 2011. "Quantiles as optimal point forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 197-207.
    162. Krüger, Jens J. & Hoss, Julian, 2012. "German business cycle forecasts, asymmetric loss and financial variables," Economics Letters, Elsevier, vol. 114(3), pages 284-287.
    163. Pierdzioch, Christian & Rülke, Jan-Christoph & Stadtmann, Georg, 2013. "A note on forecasting the prices of gold and silver: Asymmetric loss and forecast rationality," The Quarterly Review of Economics and Finance, Elsevier, vol. 53(3), pages 294-301.
    164. Tae-Hwy Lee & Yiyao Wang, 2015. "Finding SPF Percentiles Closest to Greenbook," Working Papers 201503, University of California at Riverside, Department of Economics.
    165. Elliott, Graham & Timmermann, Allan G, 2016. "Forecasting in Economics and Finance," University of California at San Diego, Economics Working Paper Series qt6z55v472, Department of Economics, UC San Diego.
    166. Tae-Hwy Lee & Aman Ullah & He Wang, 2023. "The Second-order Bias and Mean Squared Error of Quantile Regression Estimators," Working Papers 202313, University of California at Riverside, Department of Economics.
    167. Ulu, Yasemin, 2013. "Multivariate test for forecast rationality under asymmetric loss functions: Recent evidence from MMS survey of inflation–output forecasts," Economics Letters, Elsevier, vol. 119(2), pages 168-171.
    168. Kontogeorgos, Georgios & Lambrias, Kyriacos, 2019. "An analysis of the Eurosystem/ECB projections," Working Paper Series 2291, European Central Bank.
    169. Conrad, Christian & Lahiri, Kajal, 2024. "Heterogeneous Expectations among Professional Forecasters," Working Papers 0754, University of Heidelberg, Department of Economics.
    170. Riza Demirer & Rangan Gupta & Christian Pierdzioch, 2020. "Forecasting Realized Stock-Market Volatility: Do Industry Returns have Predictive Value?," Working Papers 2020107, University of Pretoria, Department of Economics.
    171. Tsuchiya, Yoichi, 2016. "Asymmetric loss and rationality of Chinese renminbi forecasts: An implication for the trade between China and the US," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 44(C), pages 116-127.
    172. Komunjer, Ivana, 2013. "Quantile Prediction," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 961-994, Elsevier.
    173. Ulrich Fritsche & Christian Pierdzioch & Jan-Christoph R�lke & Georg Stadtmann, 2014. "A Note on Forecasting the Euro: Do Forecasters Have an Asymmetric Loss Function?," International Economic Journal, Taylor & Francis Journals, vol. 28(2), pages 333-343, June.
    174. Frenkel, Michael & Rülke, Jan-Christoph & Zimmermann, Lilli, 2013. "Do private sector forecasters chase after IMF or OECD forecasts?," Journal of Macroeconomics, Elsevier, vol. 37(C), pages 217-229.
    175. Tsuchiya, Yoichi, 2012. "Evaluating Japanese corporate executives’ forecasts under an asymmetric loss function," Economics Letters, Elsevier, vol. 116(3), pages 601-603.
    176. Rülke, Jan-Christoph & Silgoner, Maria & Wörz, Julia, 2016. "Herding behavior of business cycle forecasters," International Journal of Forecasting, Elsevier, vol. 32(1), pages 23-33.
    177. Boero, Gianna & Smith, Jeremy & Wallis, Kenneth F., 2008. "Evaluating a three-dimensional panel of point forecasts: The Bank of England Survey of External Forecasters," International Journal of Forecasting, Elsevier, vol. 24(3), pages 354-367.
    178. Kexin Ding & Ani L. Katchova, 2024. "Testing the optimality of USDA's WASDE forecasts under unknown loss," Agribusiness, John Wiley & Sons, Ltd., vol. 40(4), pages 846-865, October.
    179. Hamid Baghestani, 2013. "Evaluating Federal Reserve predictions of growth in consumer spending," Applied Economics, Taylor & Francis Journals, vol. 45(13), pages 1637-1646, May.
    180. Yen, Yu-Min & Yen, Tso-Jung, 2021. "Testing forecast accuracy of expectiles and quantiles with the extremal consistent loss functions," International Journal of Forecasting, Elsevier, vol. 37(2), pages 733-758.
    181. Alexander, Marcus & Christakis, Nicholas A., 2008. "Bias and asymmetric loss in expert forecasts: A study of physician prognostic behavior with respect to patient survival," Journal of Health Economics, Elsevier, vol. 27(4), pages 1095-1108, July.
    182. de Mendonça, Helder Ferreira & de Deus, Joseph David Barroso Vasconcelos, 2019. "Central bank forecasts and private expectations: An empirical assessment from three emerging economies," Economic Modelling, Elsevier, vol. 83(C), pages 234-244.
    183. Marinovic, Iván & Ottaviani, Marco & Sorensen, Peter, 2013. "Forecasters’ Objectives and Strategies," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 690-720, Elsevier.
    184. Young Bin Ahn & Yoichi Tsuchiya, 2022. "Consumer’s perceived and expected inflation in Japan—irrationality or asymmetric loss?," Empirical Economics, Springer, vol. 63(3), pages 1247-1292, September.
    185. Arai, Natsuki, 2020. "Investigating the inefficiency of the CBO’s budgetary projections," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1290-1300.

  21. Graham Elliott & Michael Jansson & Elena Pesavento, 2005. "Optimal Power for Testing Potential Cointegrating Vectors With Known Parameters for Nonstationarity," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 34-48, January.

    Cited by:

    1. Elliott, Graham & Jansson, Michael, 2000. "Testing for Unit Roots with Stationary Covariances," Department of Economics, Working Paper Series qt47k7z69n, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    2. Fossati, Sebastian, 2011. "Covariate Unit Root Tests with Good Size and Power," Working Papers 2011-4, University of Alberta, Department of Economics.
    3. Chor Foon Tang & Nai-Peng Tey, 2017. "Low fertility in Malaysia: Can it be explained?," Journal of Population Research, Springer, vol. 34(2), pages 101-118, June.
    4. Pesavento, Elena & Rossi, Barbara, 2005. "Do Technology Shocks Drive Hours Up Or Down? A Little Evidence From An Agnostic Procedure," Macroeconomic Dynamics, Cambridge University Press, vol. 9(4), pages 478-488, September.
    5. Rossi, Barbara & Pesavento, Elena, 2003. "Small Sample Confidence Intervals for Multivariate Impulse Response Functions at Long Horizons," Working Papers 03-19, Duke University, Department of Economics.
    6. Barbara Rossi & Elena Pesavento, 2004. "Do Technology Shocks Drive Hours Up or Down?," Econometric Society 2004 North American Summer Meetings 96, Econometric Society.
    7. Sohail Amjed & Iqtidar Ali Shah & Adnan Riaz, 2022. "Investigating the Interactive Role of Demand Side Factors Potentially Responsible for Energy Crisis in Pakistan," International Journal of Energy Economics and Policy, Econjournals, vol. 12(3), pages 236-246, May.
    8. 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.
    9. Elena Pesavento, 2006. "Near-Optimal Unit Root Tests with Stationary Covariates with Better Finite Sample Size," Economics Working Papers ECO2006/18, European University Institute.
    10. Paolo Paruolo & Riccardo Girardi, 2010. "Wages and prices in Europe before and after the onset of the Monetary Union," Economics and Quantitative Methods qf1009, Department of Economics, University of Insubria.
    11. Adeel Saleem & Ghulam Sarwar & Jahanzaib Sultan & Zulfiqar Ali, 2022. "Determinants of Public Healthcare Investment: Cointegration and Causality Evidence from Pakistan," Journal of Economic Impact, Science Impact Publishers, vol. 4(2), pages 01-13.
    12. Christian Bayer & Christoph Hanck, 2013. "Combining non-cointegration tests," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(1), pages 83-95, January.
    13. Ahmed, Khalid, 2017. "Revisiting the role of financial development for energy-growth-trade nexus in BRICS economies," Energy, Elsevier, vol. 128(C), pages 487-495.
    14. Gabriel Rodriguez & Pierre Perron, 2013. "Single-equation tests for Cointegration with GLS Detrended Data," Boston University - Department of Economics - Working Papers Series 2013-016, Boston University - Department of Economics.
    15. Chandran Govindaraju, V.G.R. & Tang, Chor Foon, 2013. "The dynamic links between CO2 emissions, economic growth and coal consumption in China and India," Applied Energy, Elsevier, vol. 104(C), pages 310-318.
    16. Ionuț Nica & Irina Georgescu & Jani Kinnunen, 2024. "Evaluating Renewable Energy’s Role in Mitigating CO 2 Emissions: A Case Study of Solar Power in Finland Using the ARDL Approach," Energies, MDPI, vol. 17(16), pages 1-29, August.
    17. Shahbaz, Muhammad & Farhani, Sahbi & Ozturk, Ilhan, 2013. "Coal Consumption, Industrial Production and CO2 Emissions in China and India," MPRA Paper 50618, University Library of Munich, Germany, revised 12 Oct 2013.
    18. Tursoy, Turgut & Faisal, Faisal & Berk, Niyazi & Shahbaz, Muhammad, 2018. "How do Stock Prices and Metal Prices Contribute to Economic Activity in Turkey? The Importance of Linear and Non-linear ARDL," MPRA Paper 88899, University Library of Munich, Germany.
    19. Muhammad Ahad & Zaheer Anwer, 2021. "Asymmetric impact of oil price on trade balance in BRICS countries: Multiplier dynamic analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2177-2197, April.
    20. Elliott, Graham & Pesavento, Elena, 2006. "On the Failure of Purchasing Power Parity for Bilateral Exchange Rates after 1973," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(6), pages 1405-1430, September.
    21. Ladislava Grochova & Ludek Kouba, 2011. "Is Elite Political Stability a Necessary Condition for Economic Growth? An Empirical Evidence from the Baltic States," MENDELU Working Papers in Business and Economics 2011-15, Mendel University in Brno, Faculty of Business and Economics.
    22. Lynda Atil & Hocine Fellag & Ana E. Sipols & M. T. Santos-Martín & Clara Simón Blas, 2024. "Non-linear Cointegration Test, Based on Record Counting Statistic," Computational Economics, Springer;Society for Computational Economics, vol. 64(4), pages 2205-2230, October.
    23. Tang, Chor Foon & Tan, Eu Chye, 2013. "How stable is the tourism-led growth hypothesis in Malaysia? Evidence from disaggregated tourism markets," Tourism Management, Elsevier, vol. 37(C), pages 52-57.
    24. Maxwell L. King & Sivagowry Sriananthakumar, 2015. "Point Optimal Testing: A Survey of the Post 1987 Literature," Monash Econometrics and Business Statistics Working Papers 5/15, Monash University, Department of Econometrics and Business Statistics.
    25. Farhani, Sahbi & Solarin, Sakiru Adebola, 2017. "Financial development and energy demand in the United States: New evidence from combined cointegration and asymmetric causality tests," Energy, Elsevier, vol. 134(C), pages 1029-1037.

  22. Graham Elliott & Allan Timmermann, 2005. "Optimal Forecast Combination Under Regime Switching ," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 46(4), pages 1081-1102, November.
    See citations under working paper version above.
  23. Elliott, Graham & Timmermann, Allan, 2004. "Optimal forecast combinations under general loss functions and forecast error distributions," Journal of Econometrics, Elsevier, vol. 122(1), pages 47-79, September.
    See citations under working paper version above.
  24. Elliott, Graham & Granger, Clive W.J., 2004. "Evaluating significance: comments on "size matters"," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 33(5), pages 547-550, November.

    Cited by:

    1. Stephen T. Ziliak & Deirdre N. McCloskey, 2013. "We Agree That Statistical Significance Proves Essentially Nothing: A Rejoinder to Thomas Mayer," Econ Journal Watch, Econ Journal Watch, vol. 10(1), pages 97-107, January.
    2. Figueiredo, Antonio & Parhizgari, A.M., 2017. "Currency volatility and bid-ask spreads of ADRs and local shares," Global Finance Journal, Elsevier, vol. 34(C), pages 54-71.
    3. Kevin D. Hoover & Mark V. Siegler, 2005. "Sound and Fury: McCloskey and Significance Testing in Economics," Econometrics 0511018, University Library of Munich, Germany.
    4. Fabrizio Bernardi & Marco Cozzani, 2021. "Soccer Scores, Short-Term Mood and Fertility," European Journal of Population, Springer;European Association for Population Studies, vol. 37(3), pages 625-641, July.
    5. John D. Levendis, 2018. "Time Series Econometrics," Springer Texts in Business and Economics, Springer, number 978-3-319-98282-3, June.

  25. Elliott, Graham & Jansson, Michael, 2003. "Testing for unit roots with stationary covariates," Journal of Econometrics, Elsevier, vol. 115(1), pages 75-89, July.
    See citations under working paper version above.
  26. Ulrich K. M¸ller & Graham Elliott, 2003. "Tests for Unit Roots and the Initial Condition," Econometrica, Econometric Society, vol. 71(4), pages 1269-1286, July.

    Cited by:

    1. Werker, Bas J.M. & Zhou, Bo, 2022. "Semiparametric testing with highly persistent predictors," Journal of Econometrics, Elsevier, vol. 227(2), pages 347-370.
    2. Jansson Michael & Nielsen Morten Ørregaard, 2011. "Nearly Efficient Likelihood Ratio Tests for Seasonal Unit Roots," Journal of Time Series Econometrics, De Gruyter, vol. 3(1), pages 1-21, February.
    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. Bo Zhou, 2023. "Semiparametrically Optimal Cointegration Test," Papers 2305.08880, arXiv.org.
    5. Martin Browning & Mette Ejrnaes & Javier Alvarez, 2006. "Modelling income processes with lots of heterogeneity," Economics Series Working Papers 285, University of Oxford, Department of Economics.
    6. Andrews, Donald W.K. & Guggenberger, Patrik, 2012. "Asymptotics for LS, GLS, and feasible GLS statistics in an AR(1) model with conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 169(2), pages 196-210.
    7. Del Barrio Castro, T & Rodrigues, PMM & Taylor, AMR, 2015. "Semi-Parametric Seasonal Unit Root Tests," Essex Finance Centre Working Papers 16807, University of Essex, Essex Business School.
    8. Tran Viet Ha, 2009. "A discussion on power of ADF F-test with unexpected initial value," Applied Economics Letters, Taylor & Francis Journals, vol. 16(17), pages 1699-1703.
    9. Anton Skrobotov, 2016. "On Trend Breaks and Initial Condition in Unit Root Testing," Working Papers 0097, Gaidar Institute for Economic Policy, revised 2016.
    10. 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.
    11. 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.
    12. Busetti, Fabio & Forni, Lorenzo & Harvey, Andrew & Venditti, Fabrizio, 2006. "Inflation convergence and divergence within the European Monetary Union," Working Paper Series 574, European Central Bank.
    13. Steven Cook, 2004. "Detecting changes in persistence in linear time series," Economics Bulletin, AccessEcon, vol. 3(24), pages 1-11.
    14. Marsh, Patrick, 2007. "The Available Information For Invariant Tests Of A Unit Root," Econometric Theory, Cambridge University Press, vol. 23(4), pages 686-710, August.
    15. 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.
    16. Lopez, Claude & Murray, Chris & Papell, David, 2009. "Median-Unbiased Estimation in DF-GLS Regressions and the PPP Puzzle," MPRA Paper 26091, University Library of Munich, Germany.
    17. Morten Ørregaard Nielsen, 2008. "A Powerful Test of the Autoregressive Unit Root Hypothesis Based on a Tuning Parameter Free Statistic," CREATES Research Papers 2008-36, Department of Economics and Business Economics, Aarhus University.
    18. Cavaliere, Giuseppe & Xu, Fang, 2014. "Testing for unit roots in bounded time series," Journal of Econometrics, Elsevier, vol. 178(P2), pages 259-272.
    19. Donald W. K. Andrews & Patrik Guggenberger, 2008. "Asymptotics for stationary very nearly unit root processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(1), pages 203-212, January.
    20. Miranda-Agrippino, Silvia & Ricco, Giovanni, 2018. "Bayesian vector autoregressions," LSE Research Online Documents on Economics 87393, London School of Economics and Political Science, LSE Library.
    21. 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.
    22. Avdis, Efstathios & Wachter, Jessica A., 2017. "Maximum likelihood estimation of the equity premium," Journal of Financial Economics, Elsevier, vol. 125(3), pages 589-609.
    23. Westerlund, Joakim, 2014. "Pooled panel unit root tests and the effect of past initialization," Working Papers fe_2014_06, Deakin University, Department of Economics.
    24. Smeekes, S., 2009. "Detrending bootstrap unit root tests," Research Memorandum 056, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    25. Cláudia Duarte, 2015. "Covariate-augmented unit root tests with mixed-frequency data," Working Papers w201507, Banco de Portugal, Economics and Research Department.
    26. 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.
    27. Michael Jansson, 2008. "Semiparametric Power Envelopes for Tests of the Unit Root Hypothesis," Econometrica, Econometric Society, vol. 76(5), pages 1103-1142, September.
    28. Castro, Tomás del Barrio & Rodrigues, Paulo M.M. & Taylor, A.M. Robert, 2013. "The Impact Of Persistent Cycles On Zero Frequency Unit Root Tests," Econometric Theory, Cambridge University Press, vol. 29(6), pages 1289-1313, December.
    29. Qiankun Zhou & Jun Yu, 2012. "Asymptotic Distributions of the Least Squares Estimator for Diffusion Processes," Working Papers 11-2012, Singapore Management University, School of Economics.
    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. 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.
    32. Busetti, Fabio, 2009. "Initial conditions and stationarity tests," Economics Letters, Elsevier, vol. 105(3), pages 296-299, December.
    33. Hyungsik Roger Moon & Benoit Perron & Peter C.B. Phillips, 2005. "Incidental Trends and the Power of Panel Unit Root Tests," IEPR Working Papers 05.38, Institute of Economic Policy Research (IEPR).
    34. Matei Demetrescu & Christoph Hanck, 2016. "Robust Inference for Near-Unit Root Processes with Time-Varying Error Variances," Econometric Reviews, Taylor & Francis Journals, vol. 35(5), pages 751-781, May.
    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. Fabio Busetti & Silvia Fabiani & Andrew Harvey, 2006. "Convergence of Prices and Rates of Inflation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(s1), pages 863-877, December.
    37. Mueller, Ulrich, 2008. "An Alternative Sense of Asymptotic Efficiency," MPRA Paper 7741, University Library of Munich, Germany.
    38. Sven Otto, 2020. "Unit Root Testing with Slowly Varying Trends," Papers 2003.04066, arXiv.org, revised Aug 2020.
    39. Bas Werker & Bo Zhou, 2020. "Semiparametric Testing with Highly Persistent Predictors," Papers 2009.08291, arXiv.org.
    40. Boswijk, H. Peter & Jansson, Michael & Nielsen, Morten Ørregaard, 2015. "Improved likelihood ratio tests for cointegration rank in the VAR model," Journal of Econometrics, Elsevier, vol. 184(1), pages 97-110.
    41. Donald W. K. Andrews & Patrik Guggenberger, 2014. "A Conditional-Heteroskedasticity-Robust Confidence Interval for the Autoregressive Parameter," The Review of Economics and Statistics, MIT Press, vol. 96(2), pages 376-381, May.
    42. Niels Haldrup & Robinson Kruse & Timo Teräsvirta & Rasmus T. Varneskov, 2012. "Unit roots, nonlinearities and structural breaks," CREATES Research Papers 2012-14, Department of Economics and Business Economics, Aarhus University.
    43. Peter C.B. Phillips & Tassos Magdalinos, 2008. "Unit Root and Cointegrating Limit Theory When Initialization Is in the Infinite Past," Cowles Foundation Discussion Papers 1655, Cowles Foundation for Research in Economics, Yale University.
    44. 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.
    45. Zhou, Bo, 2017. "Semiparametric inference for non-LAN models," Other publications TiSEM 0ea4fd8a-937d-4c19-8f77-f, Tilburg University, School of Economics and Management.
    46. Donald W.K. Andrews & Patrik Guggenberger, 2007. "Hybrid and Size-Corrected Subsample Methods," Cowles Foundation Discussion Papers 1606, Cowles Foundation for Research in Economics, Yale University.
    47. 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.
    48. Werker, Bas J.M. & Zhou, B., 2022. "Semiparametric testing with highly persistent predictors," Other publications TiSEM 2974ce9c-97c1-44cd-9331-0, Tilburg University, School of Economics and Management.
    49. 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.
    50. 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.
    51. Marcet, Albert & Jarociński, Marek, 2010. "Autoregressions in small samples, priors about observables and initial conditions," Working Paper Series 1263, European Central Bank.
    52. 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.
    53. Patrik Guggenberger, "undated". "Asymptotics for Stationary Very Nearly Unit Root Processes (joint with D.W.K. Andrews), this version November 2006," UCLA Economics Online Papers 402, UCLA Department of Economics.
    54. Steve Leybourne & David Harvey, 2003. "On Unit Root Tests and the Initial Observation," Econometrics 0311006, University Library of Munich, Germany.
    55. 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.
    56. Clayton Webb & Suzanna Linn & Matthew J. Lebo, 2020. "Beyond the Unit Root Question: Uncertainty and Inference," American Journal of Political Science, John Wiley & Sons, vol. 64(2), pages 275-292, April.
    57. Donald W.K. Andrews & Xu Cheng & Patrik Guggenberger, 2011. "Generic Results for Establishing the Asymptotic Size of Confidence Sets and Tests," Cowles Foundation Discussion Papers 1813, Cowles Foundation for Research in Economics, Yale University.
    58. Michael Jansson & Marcelo J. Moreira, 2006. "Optimal Inference in Regression Models with Nearly Integrated Regressors," Econometrica, Econometric Society, vol. 74(3), pages 681-714, May.
    59. Steven Cook, 2005. "Estimating the autoregressive parameter: recursive mean adjustment and the initial condition," Applied Economics Letters, Taylor & Francis Journals, vol. 12(4), pages 203-206.
    60. Primiceri, Giorgio & Giannone, Domenico & Lenza, Michele, 2016. "Priors for the Long Run," CEPR Discussion Papers 11261, C.E.P.R. Discussion Papers.
    61. Marc Hallin & Ramon van den Akker & Bas J.M. Werker, 2011. "A class of simple distribution-free rank-based unit root tests," Post-Print hal-00834424, HAL.
    62. Steven Cook, 2004. "On the finite-sample power of modified Dickey-Fuller tests: The role of the initial condition," Economics Bulletin, AccessEcon, vol. 3(11), pages 1-9.
    63. Cook, Steven, 2008. "Joint maximum likelihood estimation of unit root testing equations and GARCH processes: Some finite-sample issues," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 77(1), pages 109-116.
    64. Chen, Jia & Li, Degui & Zhang, Lixin, 2010. "Robust estimation in a nonlinear cointegration model," Journal of Multivariate Analysis, Elsevier, vol. 101(3), pages 706-717, March.
    65. 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.
    66. 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.
    67. 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.
    68. Peter E. Kennedy & John Elder, 2004. "More on F versus t tests for unit roots when there is no trend," Economics Bulletin, AccessEcon, vol. 3(37), pages 1-6.
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    81. Nielsen, Morten, 2008. "A Powerful Tuning Parameter Free Test of the Autoregressive Unit Root Hypothesis," Working Papers 08-05, Cornell University, Center for Analytic Economics.
    82. Muller, Ulrich K., 2005. "Size and power of tests of stationarity in highly autocorrelated time series," Journal of Econometrics, Elsevier, vol. 128(2), pages 195-213, October.
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    84. Loukia Meligkotsidou & Elias Tzavalis & Ioannis D. Vrontos, 2012. "A Bayesian panel data framework for examining the economic growth convergence hypothesis: do the G7 countries converge?," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(9), pages 1975-1990, May.
    85. Aman Ullah & Yong Bao & Yun Wang, 2014. "Exact Distribution of the Mean Reversion Estimator in the Ornstein-Uhlenbeck Process," Working Papers 201413, University of California at Riverside, Department of Economics.
    86. Hallin, M. & van den Akker, R. & Werker, B.J.M., 2011. "A Class of Simple Distribution-free Rank-based Unit Root Tests (Revision of DP 2010-72)," Discussion Paper 2011-002, Tilburg University, Center for Economic Research.
    87. Jardet, C. & Monfort, A. & Pegoraro, F., 2009. "No-arbitrage Near-Cointegrated VAR(p) Term Structure Models, Term Premia and GDP Growth," Working papers 234, Banque de France.
    88. 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.
    89. Hiroshi Ono, 2014. "The government expenditure-economic growth relation in Japan: an analysis by using the ADL test for threshold cointegration," Applied Economics, Taylor & Francis Journals, vol. 46(28), pages 3523-3531, October.
    90. Joakim Westerlund, 2015. "Rethinking the Univariate Approach to Panel Unit Root Testing: Using Covariates to Resolve the Incidental Trend Problem," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(3), pages 430-443, July.
    91. 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.
    92. Khumbuzile C. Mosoma & Renee van Eyden & Heinrich R. Bohlmann, 2023. "Measuring Total Factor Productivity in the South African Agricultural Sector Using a Growth Accounting Framework," Working Papers 202306, University of Pretoria, Department of Economics.
    93. 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.
    94. Ahlgren, Niklas & Juselius, Mikael, 2009. "Tests for Cointegration Rank and the Initial Condition," Working Papers 539, Hanken School of Economics.
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    96. 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.
    97. Maxwell L. King & Sivagowry Sriananthakumar, 2015. "Point Optimal Testing: A Survey of the Post 1987 Literature," Monash Econometrics and Business Statistics Working Papers 5/15, Monash University, Department of Econometrics and Business Statistics.
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  27. Elliott, Graham, 2002. "Comments on 'Forecasting with a real-time data set for macroeconomists'," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 533-539, December.

    Cited by:

    1. Carlos Capistrán-Carmona, 2005. "Bias in Federal Reserve Inflation Forecasts: Is the Federal Reserve Irrational or Just Cautious?," Computing in Economics and Finance 2005 127, Society for Computational Economics.
    2. Tierney, Heather L.R., 2009. "Examining the Ability of Core Inflation to Capture the Overall Trend of Total Inflation," MPRA Paper 22409, University Library of Munich, Germany, revised Feb 2010.
    3. Gloria Lucía Bernal Nisperuza & Johanna Táutiva Pradere, 2008. "Relevancia de los datos en tiempo real en la estimación de la regla de Taylor para Colombia," Documentos de Economía 5421, Universidad Javeriana - Bogotá.
    4. Massimiliano Marcellino, 2008. "A linear benchmark for forecasting GDP growth and inflation?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(4), pages 305-340.
    5. 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.
    6. Tierney, Heather L.R., 2011. "Real-time data revisions and the PCE measure of inflation," Economic Modelling, Elsevier, vol. 28(4), pages 1763-1773, July.
    7. Tierney, Heather L.R., 2009. "A Local Examination for Persistence in Exclusions-from-Core Measures of Inflation Using Real-Time Data," MPRA Paper 13383, University Library of Munich, Germany, revised 03 Feb 2009.
    8. Tierney, Heather L.R., 2009. "Evaluating Exclusion-from-Core Measures of Inflation using Real-Time Data," MPRA Paper 17856, University Library of Munich, Germany.
    9. 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.
    10. Tara M. Sinclair & H.O. Stekler, 2011. "Differences in Early GDP Component Estimates Between Recession and Expansion," Working Papers 2011-05, The George Washington University, Institute for International Economic Policy.

  28. Elliott, Graham & Stock, James H., 2001. "Confidence intervals for autoregressive coefficients near one," Journal of Econometrics, Elsevier, vol. 103(1-2), pages 155-181, July.
    See citations under working paper version above.
  29. Elliott, Graham, 2000. "Estimating Restricted Cointegrating Vectors," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(1), pages 91-99, January.
    See citations under working paper version above.
  30. Elliott, Graham & Ito, Takatoshi, 1999. "Heterogeneous expectations and tests of efficiency in the yen/dollar forward exchange rate market," Journal of Monetary Economics, Elsevier, vol. 43(2), pages 435-456, April.
    See citations under working paper version above.
  31. Elliott, Graham, 1999. "Efficient Tests for a Unit Root When the Initial Observation Is Drawn from Its Unconditional Distribution," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 40(3), pages 767-783, August.

    Cited by:

    1. Jansson Michael & Nielsen Morten Ørregaard, 2011. "Nearly Efficient Likelihood Ratio Tests for Seasonal Unit Roots," Journal of Time Series Econometrics, De Gruyter, vol. 3(1), pages 1-21, February.
    2. Zheng, Shiyong & Irfan, Muhammad & Ai, Fengyi & Al-Faryan, Mamdouh Abdulaziz Saleh, 2023. "Do renewable energy, urbanisation, and natural resources enhance environmental quality in China? Evidence from novel bootstrap Fourier Granger causality in quantiles," Resources Policy, Elsevier, vol. 81(C).
    3. Andrews, Donald W.K. & Guggenberger, Patrik, 2012. "Asymptotics for LS, GLS, and feasible GLS statistics in an AR(1) model with conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 169(2), pages 196-210.
    4. Tran Viet Ha, 2009. "A discussion on power of ADF F-test with unexpected initial value," Applied Economics Letters, Taylor & Francis Journals, vol. 16(17), pages 1699-1703.
    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. Rodrigues, Paulo M. M. & Taylor, A. M. Robert, 2004. "Alternative estimators and unit root tests for seasonal autoregressive processes," Journal of Econometrics, Elsevier, vol. 120(1), pages 35-73, May.
    7. Elliott, Graham & Jansson, Michael, 2000. "Testing for Unit Roots with Stationary Covariances," Department of Economics, Working Paper Series qt47k7z69n, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    8. Serena Ng & Timothy Vogelsang, 1999. "Forecasting Dynamic Time Series in the Presence of Deterministic Components," Boston College Working Papers in Economics 445, Boston College Department of Economics.
    9. Weshah Razzak, 2009. "On the GCC Currency Union," EERI Research Paper Series EERI_RP_2009_29, Economics and Econometrics Research Institute (EERI), Brussels.
    10. Alicia Garcia-Herrero & Eric Girardin, 2013. "China's Monetary Policy Communication: Money Markets not only Listen, They also Understand," Working Papers 022013, Hong Kong Institute for Monetary Research.
    11. L. Vanessa Smith & Stephen Leybourne & Tae-Hwan Kim & Paul Newbold, 2004. "More powerful panel data unit root tests with an application to mean reversion in real exchange rates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(2), pages 147-170.
    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.
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    47. Giannellis, Nikolaos & Papadopoulos, Athanasios P., 2016. "Intra-national and international spillovers between the real economy and the stock market: The case of China," The Journal of Economic Asymmetries, Elsevier, vol. 14(PA), pages 78-92.
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    50. Anastassios A. Drakos & Georgios P. Kouretas & Leonidas P. Zarangas, 2010. "Forecasting financial volatility of the Athens stock exchange daily returns: an application of the asymmetric normal mixture GARCH model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 15(4), pages 331-350.
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    58. António Portugal Duarte & João Sousa Andrade, 2012. "How the Gold Standard functioned in Portugal: an analysis of some macroeconomic aspects," Applied Economics, Taylor & Francis Journals, vol. 44(5), pages 617-629, February.
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    132. Demetrescu, Matei & Rodrigues, Paulo M.M., 2022. "Residual-augmented IVX predictive regression," Journal of Econometrics, Elsevier, vol. 227(2), pages 429-460.
    133. Valkanov, Rossen, 1999. "The Term Structure with Highly Persistent Interest Rates," University of California at Los Angeles, Anderson Graduate School of Management qt8x91m4hg, Anderson Graduate School of Management, UCLA.
    134. Bingduo Yang & Xiaohui Liu & Liang Peng & Zongwu Cai, 2018. "Unified Tests for a Dynamic Predictive Regression," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201808, University of Kansas, Department of Economics, revised Sep 2018.
    135. Moore, Alvon, 2011. "Demand elasticity of oil in Barbados," Energy Policy, Elsevier, vol. 39(6), pages 3515-3519, June.
    136. Maynard, Alex & Ren, Dongmeng, 2019. "The finite sample power of long-horizon predictive tests in models with financial bubbles," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 418-430.
    137. Jiang, Xiaoquan & Lee, Bong-Soo, 2007. "Stock returns, dividend yield, and book-to-market ratio," Journal of Banking & Finance, Elsevier, vol. 31(2), pages 455-475, February.
    138. 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.
    139. Valkanov, Rossen, 2003. "Long-horizon regressions: theoretical results and applications," Journal of Financial Economics, Elsevier, vol. 68(2), pages 201-232, May.
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    141. Marcelo Moreira & Rafael Mourão & Humberto Moreira, 2016. "A critical value function approach, with an application to persistent time-series," CeMMAP working papers CWP24/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    142. Ansgar Belke & Thorsten Polleit, 2006. "Dividend Yields for Forecasting Stock Market Returns. An ARDL Cointegration Analysis for Germany," Ekonomia, Cyprus Economic Society and University of Cyprus, vol. 9(1), pages 86-116, Summer.
    143. Ghysels, Eric & Plazzi, Alberto & Valkanov, Rossen & Torous, Walter, 2013. "Forecasting Real Estate Prices," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 509-580, Elsevier.
    144. Phillips, Peter C.B. & Lee, Ji Hyung, 2013. "Predictive regression under various degrees of persistence and robust long-horizon regression," Journal of Econometrics, Elsevier, vol. 177(2), pages 250-264.
    145. 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.
    146. 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.
    147. Brown, Craig R. & Cyree, Ken B. & Griffiths, Mark D. & Winters, Drew B., 2008. "Further analysis of the expectations hypothesis using very short-term rates," Journal of Banking & Finance, Elsevier, vol. 32(4), pages 600-613, April.
    148. Hwang, Jen-Te & Wen, Min, 2024. "Electronic payments and money demand in China," Economic Analysis and Policy, Elsevier, vol. 82(C), pages 47-64.
    149. Horowitz, Joel L. & Savin, N. E., 2000. "Empirically relevant critical values for hypothesis tests: A bootstrap approach," Journal of Econometrics, Elsevier, vol. 95(2), pages 375-389, April.
    150. Hjalmarsson, Erik, 2008. "The Stambaugh bias in panel predictive regressions," Finance Research Letters, Elsevier, vol. 5(1), pages 47-58, March.
    151. Rapach, David & Zhou, Guofu, 2013. "Forecasting Stock Returns," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 328-383, Elsevier.
    152. Bakshi, Gurdip & Panayotov, George & Skoulakis, Georgios, 2011. "Improving the predictability of real economic activity and asset returns with forward variances inferred from option portfolios," Journal of Financial Economics, Elsevier, vol. 100(3), pages 475-495, June.
    153. Elsadig Musa Ahmed & Geeta Krishnasamy, 2012. "Telecommunications investment and economic growth in ASEAN5: An assessment from UECM," New Zealand Economic Papers, Taylor & Francis Journals, vol. 46(3), pages 315-332, December.
    154. Cai, Zongwu & Wang, Yunfei, 2014. "Testing predictive regression models with nonstationary regressors," Journal of Econometrics, Elsevier, vol. 178(P1), pages 4-14.
    155. Jungbin Hwang & Gonzalo Valdés, 2020. "Low Frequency Cointegrating Regression in the Presence of Local to Unity Regressors and Unknown Form of Serial Dependence," Working papers 2020-03, University of Connecticut, Department of Economics, revised Aug 2020.
    156. Aaron Smallwood; Alex Maynard; Mark Wohar, 2005. "The Long and the Short of It: Long Memory Regressors and Predictive Regressions," Computing in Economics and Finance 2005 384, Society for Computational Economics.
    157. Jonathan H. Wright, 1999. "A simple approach to robust inference in a cointegrating system," International Finance Discussion Papers 654, Board of Governors of the Federal Reserve System (U.S.).
    158. Zhou, Weilun & Gao, Jiti & Harris, David & Kew, Hsein, 2024. "Semi-parametric single-index predictive regression models with cointegrated regressors," Journal of Econometrics, Elsevier, vol. 238(1).
    159. Erik Hjalmarsson, 2005. "Estimation of average local-to-unity roots in heterogenous panels," International Finance Discussion Papers 852, Board of Governors of the Federal Reserve System (U.S.).
    160. Markku Lanne, 1999. "Near Unit Roots And The Predictive Power Of Yield Spreads For Changes In Long-Term Interest Rates," The Review of Economics and Statistics, MIT Press, vol. 81(3), pages 393-398, August.
    161. Kothari, Pratik & O’Doherty, Michael S., 2023. "Job postings and aggregate stock returns," Journal of Financial Markets, Elsevier, vol. 64(C).
    162. Toni Gravelle & James Morley, 2005. "A Kalman filter approach to characterizing the Canadian term structure of interest rates," Applied Financial Economics, Taylor & Francis Journals, vol. 15(10), pages 691-705.
    163. Sarmidi, Tamat, 2010. "Ringgit Malaysia Predictability: Do Currencies and Prediction Horizon Matters?," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 44, pages 51-60.
    164. Jennie Bai, 2010. "Equity premium predictions with adaptive macro indexes," Staff Reports 475, Federal Reserve Bank of New York.
    165. Christis Katsouris, 2023. "Bootstrapping Nonstationary Autoregressive Processes with Predictive Regression Models," Papers 2307.14463, arXiv.org.
    166. Liu, Xiaohui & Yang, Bingduo & Cai, Zongwu & Peng, Liang, 2019. "A unified test for predictability of asset returns regardless of properties of predicting variables," Journal of Econometrics, Elsevier, vol. 208(1), pages 141-159.
    167. Dunbar, Kwamie & Owusu-Amoako, Johnson, 2023. "Predicting inflation expectations: A habit-based explanation under hedging," International Review of Financial Analysis, Elsevier, vol. 89(C).
    168. Efstathios Avdis & Jessica A. Wachter, 2013. "Maximum likelihood estimation of the equity premium," NBER Working Papers 19684, National Bureau of Economic Research, Inc.
    169. Hasnul, Al Gifari & Masih, Mansur, 2016. "Role of instability in affecting capital flight magnitude: An ARDL bounds testing approach," MPRA Paper 72086, University Library of Munich, Germany.
    170. Theodoros Zachariadis & Nicoletta Pashourtidou, 2006. "An Empirical analysis of electricity consumption in Cyprus," University of Cyprus Working Papers in Economics 4-2006, University of Cyprus Department of Economics.
    171. Campbell, John, 2008. "Estimating the Equity Premium," Scholarly Articles 3196339, Harvard University Department of Economics.
    172. Alex Maynard & Katsumi Shimotsu & Nina Kuriyama, 2023. "Inference in Predictive Quantile Regressions," Papers 2306.00296, arXiv.org, revised May 2024.
    173. Paye, Bradley S. & Timmermann, Allan, 2006. "Instability of return prediction models," Journal of Empirical Finance, Elsevier, vol. 13(3), pages 274-315, June.
    174. Amélie Charles & Olivier Darné & Jae H Kim, 2017. "International Stock Return Predictability: Evidence from New Statistical Tests," Post-Print hal-01626101, HAL.
    175. 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.
    176. Jiang, Shi-jie & Nieh, Chien-Chung, 2012. "Dynamics of underwriting profits: Evidence from the U.S. insurance market," International Review of Economics & Finance, Elsevier, vol. 21(1), pages 1-15.
    177. Ljungwall, Christer & Xiong, Yi & Yutong, Zou, 2013. "Central bank financial strength and the cost of sterilization in China," China Economic Review, Elsevier, vol. 25(C), pages 105-116.
    178. Chen, Chaoyi & Gospodinov, Nikolay & Maynard, Alex & Pesavento, Elena, 2022. "Long-horizon stock valuation and return forecasts based on demographic projections," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 190-215.
    179. Christis Katsouris, 2022. "Partial Sum Processes of Residual-Based and Wald-type Break-Point Statistics in Time Series Regression Models," Papers 2202.00141, arXiv.org, revised Feb 2022.
    180. Christophe Boucher & Bertrand Maillet, 2012. "Prévoir sans persistance," Post-Print halshs-00662771, HAL.

  36. Elliott, Graham & Stock, James H., 1994. "Inference in Time Series Regression When the Order of Integration of a Regressor is Unknown," Econometric Theory, Cambridge University Press, vol. 10(3-4), pages 672-700, August.
    See citations under working paper version above.
  37. Edey, Malcolm & Elliott, Graham, 1992. "Some Evidence on Option Prices as Predictors of Volatility," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 54(4), pages 567-578, November.

    Cited by:

    1. Owain Ap Gwilym & Mike Buckle, 1999. "Volatility forecasting in the framework of the option expiry cycle," The European Journal of Finance, Taylor & Francis Journals, vol. 5(1), pages 73-94.
    2. Lim, Terence & Lo, Andrew W. & Merton, Robert C. & Scholes, Myron S., 2006. "The Derivatives Sourcebook," Foundations and Trends(R) in Finance, now publishers, vol. 1(5–6), pages 365-572, April.
    3. Vipul Kumar Singh, 2013. "Effectiveness of volatility models in option pricing: evidence from recent financial upheavals," Journal of Advances in Management Research, Emerald Group Publishing Limited, vol. 10(3), pages 352-375, October.

Chapters

  1. Elliott, Graham, 2006. "Forecasting with Trending Data," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 11, pages 555-604, Elsevier.

    Cited by:

    1. Athanasopoulos, George & Guillen, Osmani Teixeira Carvalho & Issler, João Victor & Vahid, Farshid, 2011. "Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 713, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    2. Giacomini, Raffaella, 2014. "Economic theory and forecasting: lessons from the literature," CEPR Discussion Papers 10201, C.E.P.R. Discussion Papers.
    3. Goulet Coulombe, Philippe & Leroux, Maxime & Stevanovic, Dalibor & Surprenant, Stéphane, 2021. "Macroeconomic data transformations matter," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1338-1354.
    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, September.
    5. J. Isaac Miller, 2014. "Simple Robust Tests for the Specification of High-Frequency Predictors of a Low-Frequency Series," Working Papers 1412, Department of Economics, University of Missouri.
    6. Müller, Ulrich K. & Wang, Yulong, 2019. "Nearly weighted risk minimal unbiased estimation," Journal of Econometrics, Elsevier, vol. 209(1), pages 18-34.
    7. Chevillon, Guillaume, 2017. "Robustness of Multistep Forecasts and Predictive Regressions at Intermediate and Long Horizons," ESSEC Working Papers WP1710, ESSEC Research Center, ESSEC Business School.
    8. Josef Baumgartner, 2008. "Die Preistransmission entlang der Wertschöpfungskette in Österreich für ausgewählte Produktgruppen," WIFO Studies, WIFO, number 33139, March.
    9. Heather Anderson & Howard Chan & Robert Faff & Yew Kee Ho, 2012. "Reported earnings and analyst forecasts as competing sources of information: A new approach," Australian Journal of Management, Australian School of Business, vol. 37(3), pages 333-359, December.
    10. Heather M Anderson & Farshid Vahid, 2010. "VARs, Cointegration and Common Cycle Restrictions," Monash Econometrics and Business Statistics Working Papers 14/10, Monash University, Department of Econometrics and Business Statistics.

  2. Ronald Bewley & Graham Elliott, 1992. "Accounting for Non-stationarity in Demand Systems," Palgrave Macmillan Books, in: Ronald Bewley & Tran Hoa (ed.), Contributions to Consumer Demand and Econometrics, chapter 4, pages 58-73, Palgrave Macmillan.

    Cited by:

    1. Deschamps, P. J., 1997. "Full maximum likelihood estimation of dynamic demand models," LIDAM Reprints CORE 1291, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

Books

  1. Graham Elliott & Allan Timmermann, 2016. "Economic Forecasting," Economics Books, Princeton University Press, edition 1, number 10740.
    See citations under working paper version above.
  2. G. Elliott & C. Granger & A. Timmermann (ed.), 2013. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 2, number 2.

    Cited by:

    1. Jeffrey Schafer, 2022. "Inflation Expectations and Their Formation: Working Paper 2022-03," Working Papers 57398, Congressional Budget Office.
    2. Wright, Jonathan H., 2019. "Some observations on forecasting and policy," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1186-1192.
    3. Yunus Aksoy & Rubens Morita & Zacharias Psaradakis, 2019. "The Chair of the U.S. Federal Reserve and the Macroeconomic Causality Regimes," CESifo Working Paper Series 8035, CESifo.
    4. Kilian, Lutz & Lee, Thomas K, 2013. "Quantifying the Speculative Component in the Real Price of Oil: The Role of Global Oil Inventories," CEPR Discussion Papers 9297, C.E.P.R. Discussion Papers.
    5. Arai, Natsuki, 2023. "The FOMC’s new individual economic projections and macroeconomic theories," Journal of Banking & Finance, Elsevier, vol. 151(C).
    6. Tiwari, Aviral Kumar & Dar, Arif Billah & Bhanja, Niyati & Gupta, Rangan, 2016. "A historical analysis of the US stock price index using empirical mode decomposition over 1791-2015," Economics Discussion Papers 2016-9, Kiel Institute for the World Economy (IfW Kiel).
    7. Marine Carrasco & Barbara Rossi, 2016. "In-sample inference and forecasting in misspecified factor models," Economics Working Papers 1530, Department of Economics and Business, Universitat Pompeu Fabra.
    8. Luca Brugnolini, 2018. "Forecasting Deflation Probability in the EA: A Combinatoric Approach," CBM Working Papers WP/01/2018, Central Bank of Malta.
    9. Galvão, Ana Beatriz & Giraitis, Liudas & Kapetanios, George & Petrova, Katerina, 2016. "A time varying DSGE model with financial frictions," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 690-716.
    10. Rangan Gupta & Patrick Kanda & Mark E. Wohar, 2021. "Predicting Stock Market Movements in the United States: The Role of Presidential Approval Ratings," International Review of Finance, International Review of Finance Ltd., vol. 21(1), pages 324-335, March.
    11. Sung Je Byun & Soojin Jo, 2018. "Heterogeneity in the dynamic effects of uncertainty on investment," Canadian Journal of Economics, Canadian Economics Association, vol. 51(1), pages 127-155, February.
    12. Carstensen, Kai & Heinrich, Markus & Reif, Magnus & Wolters, Maik H., 2020. "Predicting ordinary and severe recessions with a three-state Markov-switching dynamic factor model," International Journal of Forecasting, Elsevier, vol. 36(3), pages 829-850.
    13. Andrii Babii & Eric Ghysels & Jonas Striaukas, 2022. "Machine Learning Time Series Regressions With an Application to Nowcasting," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 1094-1106, June.
    14. Snowberg, Erik & Wolfers, Justin & Zitzewitz, Eric, 2012. "Prediction Markets for Economic Forecasting," IZA Discussion Papers 6720, Institute of Labor Economics (IZA).
    15. Delle Monache, Davide & Petrella, Ivan, 2017. "Adaptive models and heavy tails with an application to inflation forecasting," International Journal of Forecasting, Elsevier, vol. 33(2), pages 482-501.
    16. Viet Hoang Dinh & Didier Nibbering & Benjamin Wong, 2024. "Random Subspace Local Projections," Papers 2406.01002, arXiv.org.
    17. Bańbura, Marta & Leiva-Leon, Danilo & Menz, Jan-Oliver, 2021. "Do inflation expectations improve model-based inflation forecasts?," Working Paper Series 2604, European Central Bank.
    18. Massimo Guidolin & Alexei G. Orlov, 2022. "Can Investors Benefit from Hedge Fund Strategies? Utility-Based, Out-of-Sample Evidence," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 12(03), pages 1-61, September.
    19. Dr. Angela Abbate & Sandra Eickmeier & Esteban Prieto, 2020. "Financial shocks and inflation dynamics," Working Papers 2020-13, Swiss National Bank.
    20. Wendy Nyakabawo & Rangan Gupta & Hardik A. Marfatia, 2018. "High-Frequency Impact of Monetary Policy and Macroeconomic Surprises on US MSAs and Aggregate US Housing Returns and Volatility: A GJR-GARCH Approach," Working Papers 201817, University of Pretoria, Department of Economics.
    21. Soojin Jo & Rodrigo Sekkel, 2019. "Macroeconomic Uncertainty Through the Lens of Professional Forecasters," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(3), pages 436-446, July.
    22. Byron Botha & Rulof Burger & Kevin Kotze & Neil Rankin & Daan Steenkamp, 2022. "Big data forecasting of South African inflation," School of Economics Macroeconomic Discussion Paper Series 2022-03, School of Economics, University of Cape Town.
    23. Cipullo, Davide & Reslow, André, 2019. "Biased Forecasts to Affect Voting Decisions? The Brexit Case," Working Paper Series 2019:4, Uppsala University, Department of Economics.
    24. Gao, Liping & Kim, Hyeongwoo & Saba, Richard, 2014. "How Do Oil Price Shocks Affect Consumer Prices?," MPRA Paper 57259, University Library of Munich, Germany.
    25. Fabian Baetje & Lukas Menkhoff, 2016. "Equity Premium Prediction: Are Economic and Technical Indicators Unstable?," Discussion Papers of DIW Berlin 1552, DIW Berlin, German Institute for Economic Research.
    26. Davide Pettenuzzo & Konstantinos Metaxoglou & Aaron Smith, 2016. "Option-Implied Equity Premium Predictions via Entropic TiltinG," Working Papers 99R, Brandeis University, Department of Economics and International Business School, revised Aug 2016.
    27. Joshua C. C. Chan & Liana Jacobi & Dan Zhu, 2020. "Efficient selection of hyperparameters in large Bayesian VARs using automatic differentiation," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 934-943, September.
    28. Rossi, Barbara, 2013. "Exchange Rate Predictability," CEPR Discussion Papers 9575, C.E.P.R. Discussion Papers.
    29. Andrea Carriero & Todd E. Clark & Marcellino Massimiliano, 2020. "Nowcasting Tail Risks to Economic Activity with Many Indicators," Working Papers 20-13R2, Federal Reserve Bank of Cleveland, revised 22 Sep 2020.
    30. Anders Warne & Günter Coenen & Kai Christoffel, 2017. "Marginalized Predictive Likelihood Comparisons of Linear Gaussian State‐Space Models with Applications to DSGE, DSGE‐VAR, and VAR Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(1), pages 103-119, January.
    31. Markku Lanne & Jani Luoto, 2017. "A New Time‐Varying Parameter Autoregressive Model for U.S. Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(5), pages 969-995, August.
    32. Ricardo Reis, 2018. "Is something really wrong with macroeconomics?," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 34(1-2), pages 132-155.
    33. Ekaterina V. Peneva & Jeremy B. Rudd, 2017. "The Passthrough of Labor Costs to Price Inflation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(8), pages 1777-1802, December.
    34. Kilian, Lutz & Inoue, Atsushi, 2020. "The Role of the Prior in Estimating VAR Models with Sign Restrictions," CEPR Discussion Papers 15545, C.E.P.R. Discussion Papers.
    35. Baumeister, Christiane & Kilian, Lutz, 2014. "A general approach to recovering market expectations from futures prices with an application to crude oil," CFS Working Paper Series 466, Center for Financial Studies (CFS).
    36. Manuel Lukas & Eric Hillebrand, 2014. "Bagging Weak Predictors," CREATES Research Papers 2014-01, Department of Economics and Business Economics, Aarhus University.
    37. Kyle C. Meng, 2016. "Using a Free Permit Rule to Forecast the Marginal Abatement Cost of Proposed Climate Policy," NBER Working Papers 22255, National Bureau of Economic Research, Inc.
    38. Christou, Christina & Gupta, Rangan & Nyakabawo, Wendy & Wohar, Mark E., 2018. "Do house prices hedge inflation in the US? A quantile cointegration approach," International Review of Economics & Finance, Elsevier, vol. 54(C), pages 15-26.
    39. Richard K. Crump & Nikolay Gospodinov, 2022. "On the Factor Structure of Bond Returns," Econometrica, Econometric Society, vol. 90(1), pages 295-314, January.
    40. Breen, John David & Hu, Liang, 2021. "The predictive content of oil price and volatility: New evidence on exchange rate forecasting," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
    41. Jannsen, Nils & Wolters, Maik H., 2016. "Zu Produktionspotenzial und Produktionslücke in den Vereinigten Staaten," Kiel Insight 2016.2, Kiel Institute for the World Economy (IfW Kiel).
    42. Vincent Brémond & Emmanuel Hache & Tovonony Razafindrabe, 2016. "The Oil Price and Exchange Rate Relationship Revisited: A time-varying VAR parameter approach," European Journal of Comparative Economics, Cattaneo University (LIUC), vol. 13(1), pages 97-131, June.
    43. Charles W. Calomiris & Nida Çakır Melek & Harry Mamaysky, 2021. "Predicting the Oil Market," NBER Working Papers 29379, National Bureau of Economic Research, Inc.
    44. William Chen & Marco Del Negro & Michele Lenza & Giorgio E. Primiceri & Andrea Tambalotti, 2020. "What’s Up with the Phillips Curve?," Liberty Street Economics 20200918a, Federal Reserve Bank of New York.
    45. Luci Alessi & Eric Ghysels & Luca Onorante & Richard Peach & Simon M. Potter, 2014. "Central bank macroeconomic forecasting during the global financial crisis: the European Central Bank and Federal Reserve Bank of New York experiences," Staff Reports 680, Federal Reserve Bank of New York.
    46. 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.
    47. Christiansen, Charlotte & Eriksen, Jonas N. & Møller, Stig V., 2019. "Negative house price co-movements and US recessions," Regional Science and Urban Economics, Elsevier, vol. 77(C), pages 382-394.
    48. Wolters, Maik Hendrik, 2012. "Evaluating point and density forecasts of DSGE models," MPRA Paper 36147, University Library of Munich, Germany.
    49. Georg Graetz, 2019. "Labor Demand in the Past, Present, and Future," European Economy - Discussion Papers 114, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    50. Giovannelli, Alessandro & Massacci, Daniele & Soccorsi, Stefano, 2021. "Forecasting stock returns with large dimensional factor models," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 252-269.
    51. Nonejad, Nima, 2021. "Predicting equity premium using news-based economic policy uncertainty: Not all uncertainty changes are equally important," International Review of Financial Analysis, Elsevier, vol. 77(C).
    52. Marco Del Negro & Marc P. Giannoni & Frank Schorfheide, 2015. "Inflation in the Great Recession and New Keynesian Models," American Economic Journal: Macroeconomics, American Economic Association, vol. 7(1), pages 168-196, January.
    53. Klick, Larissa & Schaffner, Sandra, 2019. "FDZ data description: Regional real estate price indices for Germany (RWI-GEO-REDX) - Version 2: 2008-02/2019," RWI Projektberichte, RWI - Leibniz-Institut für Wirtschaftsforschung, number 202066.
    54. Goodness C. Aye & Frederick W. Deale & Rangan Gupta, 2016. "Does Debt Ceiling and Government Shutdown Help in Forecasting the US Equity Risk Premium?," Panoeconomicus, Savez ekonomista Vojvodine, Novi Sad, Serbia, vol. 63(3), pages 273-291.
    55. Paresh K. Narayan & Rangan Gupta, 2014. "Has Oil Pirce Predicted Stock Returns for Over a Century?," Working Papers 201446, University of Pretoria, Department of Economics.
    56. Markus Heinrich & Magnus Reif, 2018. "Forecasting using mixed-frequency VARs with time-varying parameters," ifo Working Paper Series 273, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    57. Li, Kai, 2019. "Portfolio selection with inflation-linked bonds and indexation lags," Journal of Economic Dynamics and Control, Elsevier, vol. 107(C), pages 1-1.
    58. Tae-Hwy Lee & Shahnaz Parsaeian & Aman Ullah, 2022. "Forecasting under Structural Breaks Using Improved Weighted Estimation," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202212, University of Kansas, Department of Economics.
    59. Jeremy Bertomeu, 2020. "Machine learning improves accounting: discussion, implementation and research opportunities," Review of Accounting Studies, Springer, vol. 25(3), pages 1135-1155, September.
    60. Cristiana Belu Manescu & Ine Van Robays, 2016. "Forecasting the Brent Oil Price: Addressing Time-Variation in Forecast Performance," CESifo Working Paper Series 6242, CESifo.
    61. Mr. Ken Miyajima & James Yetman, 2018. "Inflation Expectations Anchoring Across Different Types of Agents: the Case of South Africa," IMF Working Papers 2018/177, International Monetary Fund.
    62. Carlo Altavilla & Domenico Giannone, 2014. "The effectiveness of non-standard monetary policy measures: evidence from survey data," Working Papers CASMEF 1406, Dipartimento di Economia e Finanza, LUISS Guido Carli.
    63. Plakandaras, Vasilios & Gupta, Rangan & Papadimitriou, Theophilos & Gogas, Periklis, 2014. "Forecasting the U.S. Real House Price Index," DUTH Research Papers in Economics 10-2014, Democritus University of Thrace, Department of Economics.
    64. Richard H. Clarida, 2019. "The Federal Reserve’s Review of Its Monetary Policy Strategy, Tools, and Communication Practices : A speech at \"Fed Policy: A Shadow Review\" Cato Institute’s 37th Annual Monetary Conferenc," Speech 1104, Board of Governors of the Federal Reserve System (U.S.).
    65. Eguren-Martin, Fernando & O'Neill, Cian & Sokol, Andrej & von dem Berge, Lukas, 2024. "Capital flows-at-risk: Push, pull and the role of policy," Journal of International Money and Finance, Elsevier, vol. 147(C).
    66. Pablo Pincheira Brown & Nicolás Hardy, 2024. "Correlation‐based tests of predictability," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 1835-1858, September.
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    20. Michael Clements, 2016. "Are Macroeconomic Density Forecasts Informative?," ICMA Centre Discussion Papers in Finance icma-dp2016-02, Henley Business School, University of Reading.
    21. 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.
    22. Menkhoff, Lukas & Sakha, Sahra, 2017. "Estimating risky behavior with multiple-item risk measures," Journal of Economic Psychology, Elsevier, vol. 59(C), pages 59-86.
    23. Barbara Annicchiarico & Fabio Di Dio & Francesca Diluiso, 2022. "Climate Actions, Market Beliefs and Monetary Policy," CEIS Research Paper 535, Tor Vergata University, CEIS, revised 25 Mar 2022.
    24. Pauwels, Laurent & Radchenko, Peter & Vasnev, Andrey, 2019. "Higher Moment Constraints for Predictive Density Combinations," Working Papers BAWP-2019-01, University of Sydney Business School, Discipline of Business Analytics.
    25. Wieland, Volker & Wolters, Maik, 2013. "Forecasting and Policy Making," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 239-325, Elsevier.
    26. Ghysels, Eric & Ozkan, Nazire, 2015. "Real-time forecasting of the US federal government budget: A simple mixed frequency data regression approach," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1009-1020.
    27. Krüger Fabian & Pohlmeier Winfried & Mokinski Frieder, 2011. "Combining Survey Forecasts and Time Series Models: The Case of the Euribor," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 63-81, February.
    28. Degiannakis, Stavros & Filis, George, 2017. "Forecasting oil price realized volatility using information channels from other asset classes," MPRA Paper 96276, University Library of Munich, Germany.
    29. Christiane Baumeister & Pierre Guérin, 2020. "A Comparison of Monthly Global Indicators for Forecasting Growth," CESifo Working Paper Series 8656, CESifo.
    30. Rossi, Barbara, 2013. "Exchange Rate Predictability," CEPR Discussion Papers 9575, C.E.P.R. Discussion Papers.
    31. Andrea Carriero & Todd E. Clark & Marcellino Massimiliano, 2020. "Nowcasting Tail Risks to Economic Activity with Many Indicators," Working Papers 20-13R2, Federal Reserve Bank of Cleveland, revised 22 Sep 2020.
    32. Matteo Manera & Massimiliano Serati & Michele Plotegher, 2008. "Modeling Electricity Prices: From the State of the Art to a Draft of a New Proposal," Working Papers 2008.9, Fondazione Eni Enrico Mattei.
    33. Eric Hillebrand & Huiyu Huang & Tae-Hwy Lee & Canlin Li, 2018. "Using the Entire Yield Curve in Forecasting Output and Inflation," Econometrics, MDPI, vol. 6(3), pages 1-27, August.
    34. Bjørnland, Hilde C. & Ravazzolo, Francesco & Thorsrud, Leif Anders, 2017. "Forecasting GDP with global components: This time is different," International Journal of Forecasting, Elsevier, vol. 33(1), pages 153-173.
    35. Wilson, Kevin J., 2017. "An investigation of dependence in expert judgement studies with multiple experts," International Journal of Forecasting, Elsevier, vol. 33(1), pages 325-336.
    36. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Post-Print halshs-01442618, HAL.
    37. Henzel, Steffen R. & Mayr, Johannes, 2013. "The mechanics of VAR forecast pooling—A DSGE model based Monte Carlo study," The North American Journal of Economics and Finance, Elsevier, vol. 24(C), pages 1-24.
    38. Winkelried, Diego, 2012. "Predicting quarterly aggregates with monthly indicators," Working Papers 2012-023, Banco Central de Reserva del Perú.
    39. Mehmet Pinar & Thanasis Stengos & M. Ege Yazgan, 2018. "Quantile forecast combination using stochastic dominance," Empirical Economics, Springer, vol. 55(4), pages 1717-1755, December.
    40. Jiahan Li & Ilias Tsiakas, 2016. "Equity Premium Prediction: The Role of Economic and Statistical Constraints," Working Paper series 16-25, Rimini Centre for Economic Analysis.
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