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Todd Clark

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. Todd E. Clark, 1995. "Do producer prices lead consumer prices?," Economic Review, Federal Reserve Bank of Kansas City, vol. 80(Q III), pages 25-39.

    Mentioned in:

    1. From PPI to CPI
      by ? in FRED blog on 2021-04-12 13:00:00
  2. Author Profile
    1. Top Forecasting Institutions and Researchers According to IDEAS!
      by Clive Jones in Business Forecasting on 2013-06-28 01:43:46

RePEc Biblio mentions

As found on the RePEc Biblio, the curated bibliography of Economics:
  1. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2015. "Realtime nowcasting with a Bayesian mixed frequency model with stochastic volatility," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(4), pages 837-862, October.

    Mentioned in:

    1. > Econometrics > Forecasting > Nowcasting
    2. > Econometrics > Time Series Models > VAR Models > Time Varying Parameters and Stochastic Volatility
  2. Todd E. Clark & Fabian Krueger & Francesco Ravazzolo, 2015. "Using Entropic Tilting to Combine BVAR Forecasts with External Nowcasts," Working Papers (Old Series) 1439, Federal Reserve Bank of Cleveland.

    Mentioned in:

    1. > Econometrics > Time Series Models > VAR Models > Bayesian Vector autoregressions (BVARs)
  3. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2015. "Bayesian VARs: Specification Choices and Forecast Accuracy," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(1), pages 46-73, January.

    Mentioned in:

    1. > Econometrics > Time Series Models > VAR Models > Bayesian Vector autoregressions (BVARs)
  4. Clark, Todd E., 2011. "Real-Time Density Forecasts From Bayesian Vector Autoregressions With Stochastic Volatility," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(3), pages 327-341.

    Mentioned in:

    1. > Econometrics > Time Series Models > VAR Models > Time Varying Parameters and Stochastic Volatility
  5. Todd E. Clark & Michael W. McCracken, 2011. "Reality Checks and Comparisons of Nested Predictive Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 53-66, February.

    Mentioned in:

    1. > Econometrics > Forecasting

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Todd E. Clark & Michael W. McCracken, 2010. "Averaging forecasts from VARs with uncertain instabilities," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 5-29.

    Mentioned in:

    1. Averaging forecasts from VARs with uncertain instabilities (Journal of Applied Econometrics 2010) in ReplicationWiki ()

Working papers

  1. Marcellino, Massimiliano & Clark, Todd & Huber, Florian & Koop, Gary & Pfarrhofer, Michael, 2022. "Tail Forecasting with Multivariate Bayesian Additive Regression Trees," CEPR Discussion Papers 17461, C.E.P.R. Discussion Papers.

    Cited by:

    1. Florian Huber & Josef Schreiner, 2023. "Are Phillips curves in CESEE still alive and well behaved?," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue Q3/23, pages 7-27.
    2. Tony Chernis & Niko Hauzenberger & Florian Huber & Gary Koop & James Mitchell, 2023. "Predictive Density Combination Using a Tree-Based Synthesis Function," Working Papers 23-30, Federal Reserve Bank of Cleveland.
    3. Michael Pfarrhofer, 2024. "Forecasts with Bayesian vector autoregressions under real time conditions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(3), pages 771-801, April.
    4. Oyebayo Ridwan Olaniran & Ali Rashash R. Alzahrani, 2023. "On the Oracle Properties of Bayesian Random Forest for Sparse High-Dimensional Gaussian Regression," Mathematics, MDPI, vol. 11(24), pages 1-29, December.
    5. Zhemkov, Michael, 2021. "Nowcasting Russian GDP using forecast combination approach," International Economics, Elsevier, vol. 168(C), pages 10-24.
    6. Joshua Chan, 2023. "BVARs and Stochastic Volatility," Papers 2310.14438, arXiv.org.
    7. Lenza, Michele & Moutachaker, Inès & Paredes, Joan, 2023. "Forecasting euro area inflation with machine-learning models," Research Bulletin, European Central Bank, vol. 112.
    8. Jan Prüser & Florian Huber, 2024. "Nonlinearities in macroeconomic tail risk through the lens of big data quantile regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(2), pages 269-291, March.
    9. Jan Pruser & Florian Huber, 2023. "Nonlinearities in Macroeconomic Tail Risk through the Lens of Big Data Quantile Regressions," Papers 2301.13604, arXiv.org, revised Sep 2023.
    10. Philippe Goulet Coulombe & Mikael Frenette & Karin Klieber, 2023. "From Reactive to Proactive Volatility Modeling with Hemisphere Neural Networks," Working Papers 23-04, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Nov 2023.
    11. Philippe Goulet Coulombe & Mikael Frenette & Karin Klieber, 2023. "From Reactive to Proactive Volatility Modeling with Hemisphere Neural Networks," Papers 2311.16333, arXiv.org, revised Apr 2024.

  2. Todd E. Clark & Florian Huber & Gary Koop & Massimiliano Marcellino, 2022. "Forecasting US Inflation Using Bayesian Nonparametric Models," Papers 2202.13793, arXiv.org.

    Cited by:

    1. Petar Soric & Enric Monte & Salvador Torra & Oscar Claveria, 2022. ""Density forecasts of inflation using Gaussian process regression models"," IREA Working Papers 202210, University of Barcelona, Research Institute of Applied Economics, revised Jul 2022.
    2. Martin Gachter & Elias Hasler & Florian Huber, 2023. "A tale of two tails: 130 years of growth-at-risk," Papers 2302.08920, arXiv.org.
    3. Gael M. Martin & David T. Frazier & Worapree Maneesoonthorn & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2022. "Bayesian Forecasting in Economics and Finance: A Modern Review," Papers 2212.03471, arXiv.org, revised Jul 2023.
    4. Gael M. Martin & David T. Frazier & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2023. "Bayesian Forecasting in the 21st Century: A Modern Review," Monash Econometrics and Business Statistics Working Papers 1/23, Monash University, Department of Econometrics and Business Statistics.
    5. Lenza, Michele & Moutachaker, Inès & Paredes, Joan, 2023. "Density forecasts of inflation: a quantile regression forest approach," Working Paper Series 2830, European Central Bank.
    6. Jan Pruser & Florian Huber, 2023. "Nonlinearities in Macroeconomic Tail Risk through the Lens of Big Data Quantile Regressions," Papers 2301.13604, arXiv.org, revised Sep 2023.

  3. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2022. "Capturing Macroeconomic Tail Risks with Bayesian Vector Autoregressions," CEPR Discussion Papers 17512, C.E.P.R. Discussion Papers.

    Cited by:

    1. Szendrei, Tibor & Varga, Katalin, 2023. "Revisiting vulnerable growth in the Euro Area: Identifying the role of financial conditions in the distribution," Economics Letters, Elsevier, vol. 223(C).
    2. 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.
    3. Paul Labonne & Leif Anders Thorsrud, 2023. "Risky news and credit market sentiment," Working Papers No 14/2023, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    4. Gefang, Deborah & Koop, Gary & Poon, Aubrey, 2023. "Forecasting using variational Bayesian inference in large vector autoregressions with hierarchical shrinkage," International Journal of Forecasting, Elsevier, vol. 39(1), pages 346-363.
    5. Falconio, Andrea & Manganelli, Simone, 2020. "Financial conditions, business cycle fluctuations and growth at risk," Working Paper Series 2470, European Central Bank.
    6. Kiss, Tamás & Mazur, Stepan & Nguyen, Hoang & Österholm, Pär, 2021. "Modelling the Relation between the US Real Economy and the Corporate Bond-Yield Spread in Bayesian VARs with non-Gaussian Disturbances," Working Papers 2021:9, Örebro University, School of Business.
    7. Martin Iseringhausen, 2021. "A time-varying skewness model for Growth-at-Risk," Working Papers 49, European Stability Mechanism.
    8. Marcellino, Massimiliano & Clark, Todd & Carriero, Andrea, 2021. "Nowcasting Tail Risk to Economic Activity at a Weekly Frequency," CEPR Discussion Papers 16496, C.E.P.R. Discussion Papers.
    9. Martin Gachter & Elias Hasler & Florian Huber, 2023. "A tale of two tails: 130 years of growth-at-risk," Papers 2302.08920, arXiv.org.
    10. Pfarrhofer, Michael, 2022. "Modeling tail risks of inflation using unobserved component quantile regressions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    11. Patrick A. Adams & Tobias Adrian & Nina Boyarchenko & Domenico Giannone, 2020. "Forecasting Macroeconomic Risks," Staff Reports 914, Federal Reserve Bank of New York.
    12. Anthony Garratt & Timo Henckel & Shaun P. Vahey, 2019. "Empirically-transformed linear opinion pools," CAMA Working Papers 2019-47, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    13. Kevin Moran & Dalibor Stevanovic & Stéphane Surprenant, 2024. "Risk Scenarios and Macroeconomic Forecasts," CIRANO Working Papers 2024s-03, CIRANO.
    14. Kiss, Tamás & Nguyen, Hoang & Österholm, Pär, 2022. "The Relation between the High-Yield Bond Spread and the Unemployment Rate in the Euro Area," Finance Research Letters, Elsevier, vol. 46(PA).
    15. Deng, Chuang & Wu, Jian, 2023. "Macroeconomic downside risk and the effect of monetary policy," Finance Research Letters, Elsevier, vol. 54(C).
    16. Karlsson, Sune & Mazur, Stepan & Nguyen, Hoang, 2023. "Vector autoregression models with skewness and heavy tails," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).
    17. Mihail Yanchev, 2022. "Deep Growth-at-Risk Model: Nowcasting the 2020 Pandemic Lockdown Recession in Small Open Economies," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 7, pages 20-41.
    18. Leopoldo Catania & Alessandra Luati & Pierluigi Vallarino, 2021. "Economic vulnerability is state dependent," CREATES Research Papers 2021-09, Department of Economics and Business Economics, Aarhus University.

  4. Marcellino, Massimiliano & Bai, Yu & Carriero, Andrea & Clark, Todd, 2022. "Macroeconomic Forecasting in a Multi-country Context," CEPR Discussion Papers 16994, C.E.P.R. Discussion Papers.

    Cited by:

    1. Niko Hauzenberger & Florian Huber & Karin Klieber & Massimiliano Marcellino, 2022. "Bayesian Neural Networks for Macroeconomic Analysis," Papers 2211.04752, arXiv.org, revised Apr 2024.

  5. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2022. "Specification Choices in Quantile Regression for Empirical Macroeconomics," Working Papers 22-25, Federal Reserve Bank of Cleveland.

    Cited by:

    1. Jan Prüser & Florian Huber, 2024. "Nonlinearities in macroeconomic tail risk through the lens of big data quantile regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(2), pages 269-291, March.
    2. Jan Pruser & Florian Huber, 2023. "Nonlinearities in Macroeconomic Tail Risk through the Lens of Big Data Quantile Regressions," Papers 2301.13604, arXiv.org, revised Sep 2023.

  6. Marcellino, Massimiliano & Clark, Todd & Carriero, Andrea, 2021. "Nowcasting Tail Risk to Economic Activity at a Weekly Frequency," CEPR Discussion Papers 16496, C.E.P.R. Discussion Papers.

    Cited by:

    1. Eraslan, Sercan & Reif, Magnus, 2023. "A latent weekly GDP indicator for Germany," Technical Papers 08/2023, Deutsche Bundesbank.
    2. Antolín-Díaz, Juan & Drechsel, Thomas & Petrella, Ivan, 2024. "Advances in nowcasting economic activity: The role of heterogeneous dynamics and fat tails," Journal of Econometrics, Elsevier, vol. 238(2).
    3. Matteo Iacopini & Aubrey Poon & Luca Rossini & Dan Zhu, 2022. "Bayesian Mixed-Frequency Quantile Vector Autoregression: Eliciting tail risks of Monthly US GDP," Papers 2209.01910, arXiv.org.
    4. Paul Labonne, 2022. "Asymmetric Uncertainty: Nowcasting Using Skewness in Real-time Data," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2022-23, Economic Statistics Centre of Excellence (ESCoE).
    5. Matteo Iacopini & Francesco Ravazzolo & Luca Rossini, 2022. "Bayesian Multivariate Quantile Regression with alternative Time-varying Volatility Specifications," Papers 2211.16121, arXiv.org.
    6. Matteo Iacopini & Aubrey Poon & Luca Rossini & Dan Zhu, 2024. "A Quantile Nelson-Siegel model," Papers 2401.09874, arXiv.org.
    7. Narasingha Das & Partha Gangopadhyay, 2023. "Did weekly economic index and volatility index impact US food sales during the first year of the pandemic?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-23, December.

  7. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2021. "Forecasting with Shadow-Rate VARs," Working Papers 21-09, Federal Reserve Bank of Cleveland.

    Cited by:

    1. Schorfheide, Frank & Aruoba, Boragan & Mlikota, Marko & Villalvazo, Sergio, 2021. "SVARs With Occasionally-Binding Constraints," CEPR Discussion Papers 15923, C.E.P.R. Discussion Papers.

  8. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2021. "Using Time-Varying Volatility for Identification in Vector Autoregressions: An Application to Endogenous Uncertainty," CEPR Discussion Papers 16346, C.E.P.R. Discussion Papers.

    Cited by:

    1. Chang, Hao-Wen & Chang, Tsangyao & Lee, Chien-Chiang, 2023. "Return and volatility connectedness among the BRICS stock and oil markets," Resources Policy, Elsevier, vol. 86(PA).
    2. Olli Palm'en, 2022. "Macroeconomic Effect of Uncertainty and Financial Shocks: a non-Gaussian VAR approach," Papers 2202.10834, arXiv.org.
    3. Gnangnon, Sèna Kimm, 2023. "Effect of Economic Uncertainty on Remittances Flows from Developed Countries," EconStor Preprints 279480, ZBW - Leibniz Information Centre for Economics.
    4. Che, Ming & Zhu, Zixiang & Li, Yujia, 2023. "Geopolitical risk and economic policy uncertainty: Different roles in China's financial cycle," International Review of Financial Analysis, Elsevier, vol. 90(C).
    5. Andrea Carriero & Alessio Volpicella, 2022. "Generalizing the Max Share Identification to multiple shocks identification: an Application to Uncertainty," School of Economics Discussion Papers 0322, School of Economics, University of Surrey.
    6. Andrea Carriero & Massimiliano Marcellino & Tommaso Tornese, 2022. "Macro Uncertainty in the Long Run," BAFFI CAREFIN Working Papers 22188, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    7. Karlsson, Sune & Mazur, Stepan & Nguyen, Hoang, 2023. "Vector autoregression models with skewness and heavy tails," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).
    8. Ambrocio, Gene, 2020. "Inflationary household uncertainty shocks," Bank of Finland Research Discussion Papers 5/2020, Bank of Finland.
    9. Beckmann, Joscha & Czudaj, Robert L., 2024. "Uncertainty Shocks and Inflation: The Role of Credibility and Expectation Anchoring," MPRA Paper 119971, University Library of Munich, Germany.
    10. Yujia, Li & Zixiang, Zhu & Ming, Che, 2024. "Exploring the relationship between China's economic policy uncertainty and business cycles: Exogenous impulse or endogenous responses?," Emerging Markets Review, Elsevier, vol. 58(C).
    11. Dibiasi, Andreas & Sarferaz, Samad, 2023. "Measuring macroeconomic uncertainty: A cross-country analysis," European Economic Review, Elsevier, vol. 153(C).

  9. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd & Mertens, Elmar, 2021. "Measuring Uncertainty and Its Effects in the COVID-19 Era," CEPR Discussion Papers 15965, C.E.P.R. Discussion Papers.

    Cited by:

    1. Cross, Jamie L. & Hou, Chenghan & Koop, Gary & Poon, Aubrey, 2023. "Large stochastic volatility in mean VARs," Journal of Econometrics, Elsevier, vol. 236(1).
    2. Luis J. Álvarez & Florens Odendahl, 2022. "Data outliers and Bayesian VARs in the Euro Area," Working Papers 2239, Banco de España.

  10. Todd E. Clark & Florian Huber & Gary Koop & Massimiliano Marcellino & Michael Pfarrhofer, 2021. "Investigating Growth at Risk Using a Multi-country Non-parametric Quantile Factor Model," Papers 2110.03411, arXiv.org.

    Cited by:

    1. Dimitris Korobilis & Maximilian Schröder, 2023. "Monitoring multicountry macroeconomic risk," Working Papers No 06/2023, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    2. Simon Lloyd & Ed Manuel & Konstantin Panchev, 2024. "Foreign Vulnerabilities, Domestic Risks: The Global Drivers of GDP-at-Risk," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 72(1), pages 335-392, March.
    3. Pfarrhofer, Michael, 2022. "Modeling tail risks of inflation using unobserved component quantile regressions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    4. Dimitris Korobilis & Maximilian Schröder, 2023. "Probabilistic Quantile Factor Analysis," Working Papers No 05/2023, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.

  11. Marcellino, Massimiliano & Clark, Todd & Carriero, Andrea & Mertens, Elmar, 2021. "Addressing COVID-19 Outliers in BVARs with Stochastic Volatility," CEPR Discussion Papers 15964, C.E.P.R. Discussion Papers.

    Cited by:

    1. Barend Abeln & Jan P.A.M. Jacobs, 2021. "COVID-19 and seasonal adjustment," CAMA Working Papers 2021-23, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    2. Cross, Jamie L. & Hou, Chenghan & Koop, Gary & Poon, Aubrey, 2023. "Large stochastic volatility in mean VARs," Journal of Econometrics, Elsevier, vol. 236(1).
    3. Knüppel, Malte & Krüger, Fabian & Pohle, Marc-Oliver, 2022. "Score-based calibration testing for multivariate forecast distributions," Discussion Papers 50/2022, Deutsche Bundesbank.
    4. Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Working Papers 22-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
    5. Serena Ng, 2021. "Modeling Macroeconomic Variations After COVID-19," Papers 2103.02732, arXiv.org, revised Jul 2021.
    6. Nalban, Valeriu & Smădu, Andra, 2021. "Asymmetric effects of uncertainty shocks: Normal times and financial disruptions are different," Journal of Macroeconomics, Elsevier, vol. 69(C).
    7. Antolín-Díaz, Juan & Drechsel, Thomas & Petrella, Ivan, 2024. "Advances in nowcasting economic activity: The role of heterogeneous dynamics and fat tails," Journal of Econometrics, Elsevier, vol. 238(2).
    8. Florian Huber, 2023. "Bayesian Nonlinear Regression using Sums of Simple Functions," Papers 2312.01881, arXiv.org.
    9. Daniele Valenti & Andrea Bastianin & Matteo Manera, 2022. "A weekly structural VAR model of the US crude oil market," Working Papers 2022.11, Fondazione Eni Enrico Mattei.
    10. David Kohns & Arnab Bhattacharjee, 2020. "Nowcasting Growth using Google Trends Data: A Bayesian Structural Time Series Model," Papers 2011.00938, arXiv.org, revised May 2022.
    11. Davidson, Sharada Nia & Moccero, Diego Nicolas, 2024. "The nonlinear effects of banks’ vulnerability to capital depletion in euro area countries," Working Paper Series 2912, European Central Bank.
    12. Vito Polito & Yunyi Zhang, 2021. "Tackling Large Outliers in Macroeconomic Data with Vector Artificial Neural Network Autoregression," CESifo Working Paper Series 9395, CESifo.
    13. Evgenidis, Anastasios & Fasianos, Apostolos, 2023. "Modelling monetary policy’s impact on labour markets under Covid-19," Economics Letters, Elsevier, vol. 230(C).
    14. Joshua C. C. Chan, 2022. "Comparing Stochastic Volatility Specifications for Large Bayesian VARs," Papers 2208.13255, arXiv.org.
    15. Hwee Kwan Chow & Keen Meng Choy, 2023. "Economic forecasting in a pandemic: some evidence from Singapore," Empirical Economics, Springer, vol. 64(5), pages 2105-2124, May.
    16. Frank Schorfheide & Dongho Song, 2020. "Real-Time Forecasting with a (Standard) Mixed-Frequency VAR During a Pandemic," PIER Working Paper Archive 20-039, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    17. Prüser, Jan, 2021. "The horseshoe prior for time-varying parameter VARs and Monetary Policy," Journal of Economic Dynamics and Control, Elsevier, vol. 129(C).
    18. Chan, Joshua C.C. & Poon, Aubrey & Zhu, Dan, 2023. "High-dimensional conditionally Gaussian state space models with missing data," Journal of Econometrics, Elsevier, vol. 236(1).
    19. Bobeica, Elena & Hartwig, Benny, 2023. "The COVID-19 shock and challenges for inflation modelling," International Journal of Forecasting, Elsevier, vol. 39(1), pages 519-539.
    20. Karlsson, Sune & Mazur, Stepan & Nguyen, Hoang, 2023. "Vector autoregression models with skewness and heavy tails," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).
    21. Barauskaitė, Kristina & Nguyen, Anh D.M. & Rousová, Linda & Cappiello, Lorenzo, 2022. "The impact of credit supply shocks in the euro area: market-based financing versus loans," Working Paper Series 2673, European Central Bank.
    22. Kohns, David & Bhattacharjee, Arnab, 2023. "Nowcasting growth using Google Trends data: A Bayesian Structural Time Series model," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1384-1412.
    23. Todd E. Clark & Florian Huber & Gary Koop & Massimiliano Marcellino & Michael Pfarrhofer, 2023. "Tail Forecasting With Multivariate Bayesian Additive Regression Trees," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 64(3), pages 979-1022, August.
    24. Budnik, Katarzyna & Groß, Johannes & Vagliano, Gianluca & Dimitrov, Ivan & Lampe, Max & Panos, Jiri & Velasco, Sofia & Boucherie, Louis & Jančoková, Martina, 2023. "BEAST: A model for the assessment of system-wide risks and macroprudential policies," Working Paper Series 2855, European Central Bank.
    25. Sun, Weihong & Liu, Ding, 2023. "Great moderation with Chinese characteristics: Uncovering the role of monetary policy," Economic Modelling, Elsevier, vol. 121(C).
    26. 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.
    27. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2021. "Forecasting with Shadow-Rate VARs," Working Papers 21-09, Federal Reserve Bank of Cleveland.
    28. Luis J. Álvarez & Florens Odendahl, 2022. "Data outliers and Bayesian VARs in the Euro Area," Working Papers 2239, Banco de España.
    29. Colunga L. Fernando & Torre Cepeda Leonardo, 2023. "Effects of Supply, Demand, and Labor Market Shocks in the Mexican Manufacturing Sector," Working Papers 2023-10, Banco de México.
    30. Kiss, Tamas & Nguyen, Hoang & Österholm, Pär, 2022. "Modelling Okun’s Law – Does non-Gaussianity Matter?," Working Papers 2022:1, Örebro University, School of Business.
    31. Morley, James & Rodríguez-Palenzuela, Diego & Sun, Yiqiao & Wong, Benjamin, 2023. "Estimating the euro area output gap using multivariate information and addressing the COVID-19 pandemic," European Economic Review, Elsevier, vol. 153(C).
    32. Mertens, Elmar, 2023. "Precision-based sampling for state space models that have no measurement error," Journal of Economic Dynamics and Control, Elsevier, vol. 154(C).
    33. Bańbura, Marta & Belousova, Irina & Bodnár, Katalin & Tóth, Máté Barnabás, 2023. "Nowcasting employment in the euro area," Working Paper Series 2815, European Central Bank.
    34. Bańbura, Marta & Bobeica, Elena & Martínez Hernández, Catalina, 2023. "What drives core inflation? The role of supply shocks," Working Paper Series 2875, European Central Bank.
    35. Andrejs Zlobins, 2021. "On the Time-varying Effects of the ECB's Asset Purchases," Working Papers 2021/02, Latvijas Banka.
    36. Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Papers 2202.04146, arXiv.org.
    37. Danilo Cascaldi-Garcia, 2022. "Pandemic Priors," International Finance Discussion Papers 1352, Board of Governors of the Federal Reserve System (U.S.).
    38. Alanya-Beltran, Willy, 2022. "Unit roots in lower-bounded series with outliers," Economic Modelling, Elsevier, vol. 115(C).
    39. Saeed Zaman, 2021. "A Unified Framework to Estimate Macroeconomic Stars," Working Papers 21-23R, Federal Reserve Bank of Cleveland, revised 15 Aug 2022.

  12. 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.

    Cited by:

    1. Aaron J. Amburgey & Michael W. McCracken, 2023. "On the real‐time predictive content of financial condition indices for growth," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(2), pages 137-163, March.
    2. Hager Ben Romdhane, 2021. "Nowcasting in Tunisia using large datasets and mixed frequency models," IHEID Working Papers 11-2021, Economics Section, The Graduate Institute of International Studies.
    3. Galvao, Ana Beatriz & Owyang, Michael, 2020. "Forecasting Low Frequency Macroeconomic Events with High Frequency Data," EMF Research Papers 38, Economic Modelling and Forecasting Group.
    4. Stolbov, Mikhail & Shchepeleva, Maria, 2022. "Modeling global real economic activity: Evidence from variable selection across quantiles," The Journal of Economic Asymmetries, Elsevier, vol. 25(C).
    5. Marcellino, Massimiliano & Foroni, Claudia & Stevanovic, Dalibor, 2020. "Forecasting the Covid-19 recession and recovery: Lessons from the financial crisis," CEPR Discussion Papers 15114, C.E.P.R. Discussion Papers.
    6. David Kohns & Tibor Szendrei, 2021. "Decoupling Shrinkage and Selection for the Bayesian Quantile Regression," Papers 2107.08498, arXiv.org.
    7. 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.
    8. Berger, Tino & Morley, James & Wong, Benjamin, 2023. "Nowcasting the output gap," Journal of Econometrics, Elsevier, vol. 232(1), pages 18-34.
      • Tino Berger & James Morley & Benjamin Wong, 2020. "Nowcasting the output gap," CAMA Working Papers 2020-78, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    9. Martin Iseringhausen, 2021. "A time-varying skewness model for Growth-at-Risk," Working Papers 49, European Stability Mechanism.
    10. Jean-Guillaume Sahuc & Matteo Mogliani & Laurent Ferrara, 2022. "High-frequency monitoring of growth at risk," Post-Print hal-03361425, HAL.
    11. Pfarrhofer, Michael, 2022. "Modeling tail risks of inflation using unobserved component quantile regressions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    12. Frank Schorfheide & Dongho Song, 2020. "Real-Time Forecasting with a (Standard) Mixed-Frequency VAR During a Pandemic," PIER Working Paper Archive 20-039, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    13. Lenza, Michele & Cimadomo, Jacopo & Giannone, Domenico & Monti, Francesca & Sokol, Andrej, 2021. "Nowcasting with Large Bayesian Vector Autoregressions," CEPR Discussion Papers 15854, C.E.P.R. Discussion Papers.
    14. Gloria Gonzalez-Rivera & Vladimir Rodriguez-Caballero & Esther Ruiz, 2021. "Expecting the unexpected: economic growth under stress," Working Papers 202106, University of California at Riverside, Department of Economics.
    15. Salisu, Afees A. & Ogbonna, Ahamuefula E. & Vo, Xuan Vinh, 2023. "Oil tail risks and the realized variance of consumer prices in advanced economies," Resources Policy, Elsevier, vol. 83(C).
    16. Teng, Bin & Wang, Sicong & Shi, Yufeng & Sun, Yunchuan & Wang, Wei & Hu, Wentao & Shi, Chaojun, 2022. "Economic recovery forecasts under impacts of COVID-19," Economic Modelling, Elsevier, vol. 110(C).
    17. Korobilis, Dimitris & Landau, Bettina & Musso, Alberto & Phella, Anthoulla, 2021. "The time-varying evolution of inflation risks," Working Paper Series 2600, European Central Bank.
    18. Alina Stundziene & Vaida Pilinkiene & Jurgita Bruneckiene & Andrius Grybauskas & Mantas Lukauskas, 2023. "Nowcasting Economic Activity Using Electricity Market Data: The Case of Lithuania," Economies, MDPI, vol. 11(5), pages 1-21, May.
    19. Jennifer Betz & Maximilian Nagl & Daniel Rösch, 2022. "Credit line exposure at default modelling using Bayesian mixed effect quantile regression," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 2035-2072, October.
    20. Jack Fosten & Daniel Gutknecht & Marc-Oliver Pohle, 2023. "Testing Quantile Forecast Optimality," Papers 2302.02747, arXiv.org, revised Oct 2023.
    21. Wegmüller, Philipp & Glocker, Christian & Guggia, Valentino, 2023. "Weekly economic activity: Measurement and informational content," International Journal of Forecasting, Elsevier, vol. 39(1), pages 228-243.
    22. Hans Genberg & Özer Karagedikli, 2021. "Machine Learning and Central Banks: Ready for Prime Time?," Working Papers wp43, South East Asian Central Banks (SEACEN) Research and Training Centre.
    23. Yfanti, Stavroula & Karanasos, Menelaos & Zopounidis, Constantin & Christopoulos, Apostolos, 2023. "Corporate credit risk counter-cyclical interdependence: A systematic analysis of cross-border and cross-sector correlation dynamics," European Journal of Operational Research, Elsevier, vol. 304(2), pages 813-831.

  13. Marcellino, Massimiliano & Clark, Todd & Carriero, Andrea, 2019. "Assessing International Commonality in Macroeconomic Uncertainty and Its Effects," CEPR Discussion Papers 13970, C.E.P.R. Discussion Papers.

    Cited by:

    1. Jose E. Gomez-Gonzalez & Jorge Hirs-Garzon & Jorge M. Uribe, 2020. "Global effects of US uncertainty: real and financial shocks on real and financial markets," IREA Working Papers 202015, University of Barcelona, Research Institute of Applied Economics, revised Oct 2020.
    2. Cross, Jamie L. & Hou, Chenghan & Koop, Gary & Poon, Aubrey, 2023. "Large stochastic volatility in mean VARs," Journal of Econometrics, Elsevier, vol. 236(1).
    3. Efrem Castelnuovo, 2022. "Uncertainty Before and During COVID-19: A Survey," "Marco Fanno" Working Papers 0279, Dipartimento di Scienze Economiche "Marco Fanno".
    4. Iader Giraldo & Carlos Giraldo & José E. Gomez-Gonzalez & Jorge Mario Uribe, 2023. "US uncertainty shocks, credit, production, and prices: The case of fourteen Latin American countries," Documentos de trabajo 20667, FLAR.
    5. Miescu, Mirela S., 2023. "Uncertainty shocks in emerging economies: A global to local approach for identification," European Economic Review, Elsevier, vol. 154(C).
    6. Nina Biljanovska & Mr. Francesco Grigoli & Martina Hengge, 2017. "Fear Thy Neighbor: Spillovers from Economic Policy Uncertainty," IMF Working Papers 2017/240, International Monetary Fund.
    7. Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano, 2021. "Using time-varying volatility for identification in Vector Autoregressions: An application to endogenous uncertainty," Journal of Econometrics, Elsevier, vol. 225(1), pages 47-73.
    8. Gianluca Cubadda & Stefano Grassi & Barbara Guardabascio, 2024. "The Time-Varying Multivariate Autoregressive Index Model," CEIS Research Paper 571, Tor Vergata University, CEIS, revised 10 Jan 2024.
    9. Bobasu, Alina & Geis, André & Quaglietti, Lucia & Ricci, Martino, 2021. "Tracking global economic uncertainty: implications for the euro area," Working Paper Series 2541, European Central Bank.
    10. Beckmann, Joscha & Davidson, Sharada Nia & Koop, Gary & Schüssler, Rainer, 2023. "Cross-country uncertainty spillovers: Evidence from international survey data," Journal of International Money and Finance, Elsevier, vol. 130(C).
    11. Andrea Carriero & Alessio Volpicella, 2022. "Generalizing the Max Share Identification to multiple shocks identification: an Application to Uncertainty," School of Economics Discussion Papers 0322, School of Economics, University of Surrey.
    12. Paul Labonne, 2022. "Asymmetric Uncertainty: Nowcasting Using Skewness in Real-time Data," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2022-23, Economic Statistics Centre of Excellence (ESCoE).
    13. Lodge, David & Pérez, Javier J. & Albrizio, Silvia & Everett, Mary & De Bandt, Olivier & Georgiadis, Georgios & Ca' Zorzi, Michele & Lastauskas, Povilas & Carluccio, Juan & Parrága, Susana & Carvalho,, 2021. "The implications of globalisation for the ECB monetary policy strategy," Occasional Paper Series 263, European Central Bank.
    14. Arigoni, Filippo & Lenarcic, Crt, 2023. "Foreign economic policy uncertainty shocks and real activity in the Euro area," Research Technical Papers 7/RT/23, Central Bank of Ireland.
    15. Helena Chuliá & Ignacio Garrón & Jorge M. Uribe, 2021. ""Vulnerable Funding in the Global Economy"," IREA Working Papers 202106, University of Barcelona, Research Institute of Applied Economics, revised Mar 2021.
    16. Ogbuabor, Jonathan E. & Ukwueze, Ezebuilo R. & Mba, Ifeoma C. & Ojonta, Obed I. & Orji, Anthony, 2023. "The asymmetric impact of economic policy uncertainty on global retail energy markets: Are the markets responding to the fear of the unknown?," Applied Energy, Elsevier, vol. 334(C).
    17. Andreas Dibiasi & Samad Sarferaz, 2020. "Measuring Macroeconomic Uncertainty: The Labor Channel of Uncertainty from a Cross-Country Perspective," Papers 2006.09007, arXiv.org, revised Dec 2020.
    18. Giovanni Caggiano & Efrem Castelnuovo, 2023. "Global financial uncertainty," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(3), pages 432-449, April.
    19. Graziano Moramarco, 2022. "Measuring Global Macroeconomic Uncertainty and Cross-Country Uncertainty Spillovers," Econometrics, MDPI, vol. 11(1), pages 1-29, December.
    20. Jamie L. Cross & Chenghan Hou & Aubrey Poon, 2018. "International Transmission of Macroeconomic Uncertainty in Small Open Economies: An Empirical Approach," Working Papers No 12/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    21. Ductor, Lorenzo & Leiva-León, Danilo, 2022. "Fluctuations in global output volatility," Journal of International Money and Finance, Elsevier, vol. 120(C).
    22. Bonciani, Dario & Ricci, Martino, 2020. "The international effects of global financial uncertainty shocks," Journal of International Money and Finance, Elsevier, vol. 109(C).
    23. Dibiasi, Andreas & Sarferaz, Samad, 2023. "Measuring macroeconomic uncertainty: A cross-country analysis," European Economic Review, Elsevier, vol. 153(C).
    24. Crespo Cuaresma, Jesús & Huber, Florian & Onorante, Luca, 2020. "Fragility and the effect of international uncertainty shocks," Journal of International Money and Finance, Elsevier, vol. 108(C).
    25. Paul Labonne, 2020. "Asymmetric uncertainty : Nowcasting using skewness in real-time data," Papers 2012.02601, arXiv.org, revised May 2024.

  14. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2018. "Endogenous Uncertainty," Working Papers (Old Series) 1805, Federal Reserve Bank of Cleveland.

    Cited by:

    1. Qazi Haque & Leandro M. Magnusson & Kazuki Tomioka, 2019. "Empirical evidence on the dynamics of investment under uncertainty in the U.S," Economics Discussion / Working Papers 19-18, The University of Western Australia, Department of Economics.
    2. Hauzenberger, Niko & Pfarrhofer, Michael & Stelzer, Anna, 2021. "On the effectiveness of the European Central Bank’s conventional and unconventional policies under uncertainty," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 822-845.
    3. Maria Elena Bontempi & Michele Frigeri & Roberto Golinelli & Matteo Squadrani, 2021. "EURQ: A New Web Search‐based Uncertainty Index," Economica, London School of Economics and Political Science, vol. 88(352), pages 969-1015, October.
    4. Gian Paulo Soave, 2020. "International Drivers of Policy Uncertainty in Emerging Economies," Economics Bulletin, AccessEcon, vol. 40(1), pages 716-726.

  15. Todd E Clark & Michael W McCracken & Elmar Mertens, 2017. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," BIS Working Papers 667, Bank for International Settlements.

    Cited by:

    1. Kajal Lahiri & Huaming Peng & Xuguang Simon Sheng, 2021. "Measuring Uncertainty of a Combined Forecast and Some Tests for Forecaster Heterogeneity," Working Papers 2021-005, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    2. Li, Zheng & Zeng, Jingjing & Hensher, David A., 2023. "An efficient approach to structural breaks and the case of automobile gasoline consumption in Australia," Transportation Research Part A: Policy and Practice, Elsevier, vol. 169(C).
    3. Li, Zheng & Zhou, Bo & Hensher, David A., 2022. "Forecasting automobile gasoline demand in Australia using machine learning-based regression," Energy, Elsevier, vol. 239(PD).
    4. Oliver Grothe & Fabian Kachele & Fabian Kruger, 2022. "From point forecasts to multivariate probabilistic forecasts: The Schaake shuffle for day-ahead electricity price forecasting," Papers 2204.10154, arXiv.org.
    5. Efrem Castelnuovo, 2022. "Uncertainty Before and During COVID-19: A Survey," "Marco Fanno" Working Papers 0279, Dipartimento di Scienze Economiche "Marco Fanno".
    6. Kiss, Tamás & Mazur, Stepan & Nguyen, Hoang & Österholm, Pär, 2021. "Modelling the Relation between the US Real Economy and the Corporate Bond-Yield Spread in Bayesian VARs with non-Gaussian Disturbances," Working Papers 2021:9, Örebro University, School of Business.
    7. Mirela Miescu, 2019. "Uncertainty shocks in emerging economies," Working Papers 277077821, Lancaster University Management School, Economics Department.
    8. Marcellino, Massimiliano & Clark, Todd & Carriero, Andrea & Mertens, Elmar, 2021. "Addressing COVID-19 Outliers in BVARs with Stochastic Volatility," CEPR Discussion Papers 15964, C.E.P.R. Discussion Papers.
    9. Knüppel, Malte & Schultefrankenfeld, Guido, 2018. "Assessing the uncertainty in central banks' inflation outlooks," Discussion Papers 56/2018, Deutsche Bundesbank.
    10. 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.
    11. Bas Scheer, 2022. "Addressing Unemployment Rate Forecast Errors in Relation to the Business Cycle," CPB Discussion Paper 434, CPB Netherlands Bureau for Economic Policy Analysis.
    12. Ana Beatriz Galvão & James Mitchell, 2023. "Real‐Time Perceptions of Historical GDP Data Uncertainty," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 457-481, June.
    13. Patrick A. Adams & Tobias Adrian & Nina Boyarchenko & Domenico Giannone, 2020. "Forecasting Macroeconomic Risks," Staff Reports 914, Federal Reserve Bank of New York.
    14. Galvao, Ana Beatriz & Garratt, Anthony & Mitchell, James, 2020. "Does Judgment Improve Macroeconomic Density Forecasts?," EMF Research Papers 33, Economic Modelling and Forecasting Group.
    15. Weiqi Zhang & Huong Ha & Hui Ting Evelyn Gay, 2020. "Analysts’ forecasts between last consensus and earning announcement date," Journal of Financial Reporting and Accounting, Emerald Group Publishing Limited, vol. 18(4), pages 779-793, November.
    16. Todd E. Clark & Gergely Ganics & Elmar Mertens, 2022. "What is the Predictive Value of SPF Point and Density Forecasts?," Working Papers 22-37, Federal Reserve Bank of Cleveland.
    17. Knüppel, Malte, 2018. "Forecast-error-based estimation of forecast uncertainty when the horizon is increased," International Journal of Forecasting, Elsevier, vol. 34(1), pages 105-116.
    18. Corradi, Valentina & Fosten, Jack & Gutknecht, Daniel, 2023. "Out-of-sample tests for conditional quantile coverage an application to Growth-at-Risk," Journal of Econometrics, Elsevier, vol. 236(2).
    19. Barbara Rossi, 2018. "Identifying and estimating the effects of unconventional monetary policy in the data: How to do It and what have we learned?," Economics Working Papers 1641, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2020.
    20. Sharpe, Steven A. & Sinha, Nitish R. & Hollrah, Christopher A., 2023. "The power of narrative sentiment in economic forecasts," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1097-1121.
    21. Reifschneider, David & Tulip, Peter, 2019. "Gauging the uncertainty of the economic outlook using historical forecasting errors: The Federal Reserve’s approach," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1564-1582.
    22. Grothe, Oliver & Kächele, Fabian & Krüger, Fabian, 2023. "From point forecasts to multivariate probabilistic forecasts: The Schaake shuffle for day-ahead electricity price forecasting," Energy Economics, Elsevier, vol. 120(C).
    23. Simón Sosvilla-Rivero & María del Carmen Ramos-Herrera, 2018. "Inflation, real economic growth and unemployment expectations: an empirical analysis based on the ECB survey of professional forecasters," Applied Economics, Taylor & Francis Journals, vol. 50(42), pages 4540-4555, September.
    24. Dibiasi, Andreas & Sarferaz, Samad, 2023. "Measuring macroeconomic uncertainty: A cross-country analysis," European Economic Review, Elsevier, vol. 153(C).
    25. Fabian Kruger & Hendrik Plett, 2022. "Prediction intervals for economic fixed-event forecasts," Papers 2210.13562, arXiv.org, revised Mar 2024.

  16. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2016. "Measuring Uncertainty and Its Impact on the Economy," BAFFI CAREFIN Working Papers 1639, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.

    Cited by:

    1. Gian Paulo Soave, 2023. "A panel threshold VAR with stochastic volatility-in-mean model: an application to the effects of financial and uncertainty shocks in emerging economies," Applied Economics, Taylor & Francis Journals, vol. 55(4), pages 397-431, January.
    2. Laurent Ferrara & Stéphane Lhuissier & Fabien Tripier, 2017. "Uncertainty Fluctuations: Measures, Effects and Macroeconomic Policy Challenges," CEPII Policy Brief 2017-20, CEPII research center.
    3. Giovanni Caggiano & Efrem Castelnuovo & Juan Manuel Figueres, 2018. "Economic Policy Uncertainty Spillovers in Booms and Busts," "Marco Fanno" Working Papers 0220, Dipartimento di Scienze Economiche "Marco Fanno".
    4. Ma, Xiaohan & Samaniego, Roberto, 2020. "The macroeconomic impact of oil earnings uncertainty: New evidence from analyst forecasts," Energy Economics, Elsevier, vol. 90(C).
    5. 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.
    6. Danilo Leiva-Leon & Luis Uzeda, 2020. "Endogenous Time Variation in Vector Autoregressions," Staff Working Papers 20-16, Bank of Canada.
    7. Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2019. "How is Machine Learning Useful for Macroeconomic Forecasting?," CIRANO Working Papers 2019s-22, CIRANO.
    8. Fischer, Manfred M. & Huber, Florian & Pfarrhofer, Michael, 2018. "The transmission of uncertainty shocks on income inequality: State-level evidence from the United States," Working Papers in Regional Science 2018/06, WU Vienna University of Economics and Business.
    9. Balcilar, Mehmet & Ozdemir, Zeynel Abidin & Ozdemir, Huseyin & Aygun, Gurcan & Wohar, Mark E., 2022. "The macroeconomic impact of economic uncertainty and financial shocks under low and high financial stress," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    10. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2020. "Capturing Macroeconomic Tail Risks with Bayesian Vector Autoregressions," Working Papers 20-02R, Federal Reserve Bank of Cleveland, revised 22 Sep 2020.
    11. Yoosoon Chang & Ana María Herrera & Elena Pesavento, 2023. "Oil Prices Uncertainty, Endogenous Regime Switching, and Inflation Anchoring," CAMA Working Papers 2023-14, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    12. Xianbo Zhou & Zhuoran Chen, 2023. "The Impact of Uncertainty Shocks to Consumption under Different Confidence Regimes Based on a Stochastic Uncertainty-in-Mean TVAR Model," Sustainability, MDPI, vol. 15(4), pages 1-20, February.
    13. Gefang, Deborah & Koop, Gary & Poon, Aubrey, 2023. "Forecasting using variational Bayesian inference in large vector autoregressions with hierarchical shrinkage," International Journal of Forecasting, Elsevier, vol. 39(1), pages 346-363.
    14. Karamysheva, Madina, 2022. "How do fiscal adjustments work? An empirical investigation," Journal of Economic Dynamics and Control, Elsevier, vol. 137(C).
    15. Fabio Bertolotti & Massimiliano Marcellino, 2019. "Tax shocks with high and low uncertainty," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(6), pages 972-993, September.
    16. Piergiorgio Alessandri & Andrea Gazzani & Alejandro Vicondoa, 2021. "The Real Effects of Financial Uncertainty Shocks: A Daily Identification Approach," Documentos de Trabajo 559, Instituto de Economia. Pontificia Universidad Católica de Chile..
    17. Magnus, Jan R. & Pijls, Henk G.J. & Sentana, Enrique, 2021. "The Jacobian of the exponential function," Journal of Economic Dynamics and Control, Elsevier, vol. 127(C).
    18. Hernández Vega Marco A., 2021. "The Nonlinear Effect of Uncertainty in Portfolio Flows to Mexico," Working Papers 2021-11, Banco de México.
    19. Deborah Gefang & Gary Koop & Aubrey Poon, 2019. "Variational Bayesian inference in large Vector Autoregressions with hierarchical shrinkage," CAMA Working Papers 2019-08, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    20. Popiel Michal Ksawery, 2020. "Fiscal policy uncertainty and US output," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(2), pages 1-26, April.
    21. Cross, Jamie L. & Hou, Chenghan & Koop, Gary & Poon, Aubrey, 2023. "Large stochastic volatility in mean VARs," Journal of Econometrics, Elsevier, vol. 236(1).
    22. Bertrand Candelon & Laurent Ferrara & Marc Joëts, 2016. "Global Financial Interconnectedness: A nonlinear Assessment of the Uncertainty Channel," Post-Print hal-01667074, HAL.
    23. Joonseok Oh, 2020. "The Propagation Of Uncertainty Shocks: Rotemberg Versus Calvo," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 61(3), pages 1097-1113, August.
    24. Efrem Castelnuovo, 2022. "Uncertainty Before and During COVID-19: A Survey," "Marco Fanno" Working Papers 0279, Dipartimento di Scienze Economiche "Marco Fanno".
    25. Luca Rossi, 2020. "Indicators of uncertainty: a brief user’s guide," Questioni di Economia e Finanza (Occasional Papers) 564, Bank of Italy, Economic Research and International Relations Area.
    26. Oscar Claveria, 2021. "Uncertainty indicators based on expectations of business and consumer surveys," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 48(2), pages 483-505, May.
    27. Stefano Giglio & Ian Dew-Becker & David Berger, 2017. "Uncertainty Shocks as Second-Moment News Shocks," 2017 Meeting Papers 403, Society for Economic Dynamics.
    28. Miescu, Mirela S., 2023. "Uncertainty shocks in emerging economies: A global to local approach for identification," European Economic Review, Elsevier, vol. 154(C).
    29. Tosapol Apaitan & Pongsak Luangaram & Pym Manopimoke, 2020. "Uncertainty and Economic Activity: Does it Matter for Thailand?," PIER Discussion Papers 130, Puey Ungphakorn Institute for Economic Research.
    30. González-Sánchez, Mariano & Nave, Juan & Rubio, Gonzalo, 2020. "Effects of uncertainty and risk aversion on the exposure of investment-style factor returns to real activity," Research in International Business and Finance, Elsevier, vol. 53(C).
    31. Sentana, Enrique & Fiorentini, Gabriele, 2018. "Specification tests for non-Gaussian maximum likelihood estimators," CEPR Discussion Papers 12934, C.E.P.R. Discussion Papers.
    32. Oscar Claveria, 2021. "On the Aggregation of Survey-Based Economic Uncertainty Indicators Between Different Agents and Across Variables," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(1), pages 1-26, April.
    33. Ganwen Zheng & Songping Zhu, 2021. "Research on the Effectiveness of China’s Macro Control Policy on Output and Technological Progress under Economic Policy Uncertainty," Sustainability, MDPI, vol. 13(12), pages 1-18, June.
    34. Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano, 2021. "Using time-varying volatility for identification in Vector Autoregressions: An application to endogenous uncertainty," Journal of Econometrics, Elsevier, vol. 225(1), pages 47-73.
    35. Emmanuel Joel Aikins Abakah & Guglielmo Maria Caporale & Luis A. Gil-Alana, 2020. "Economic Policy Uncertainty: Persistence and Cross-Country Linkages," CESifo Working Paper Series 8289, CESifo.
    36. Beckmann, Joscha & Davidson, Sharada Nia & Koop, Gary & Schüssler, Rainer, 2023. "Cross-country uncertainty spillovers: Evidence from international survey data," Journal of International Money and Finance, Elsevier, vol. 130(C).
    37. Hauzenberger, Niko & Böck, Maximilian & Pfarrhofer, Michael & Stelzer, Anna & Zens, Gregor, 2018. "Implications of macroeconomic volatility in the Euro area," ESRB Working Paper Series 80, European Systemic Risk Board.
    38. Evren Erdogan Cosar & Sayg�n Sahinoz, 2018. "Quantifying Uncertainty and Identifying its Impacts on the Turkish Economy," Working Papers 1806, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    39. Aviral Kumar Tiwari & Micheal Kofi Boachie & Rangan Gupta, 2019. "Network Analysis of Economic and Financial Uncertainties in Advanced Economies: Evidence from Graph-Theory," Working Papers 201982, University of Pretoria, Department of Economics.
    40. Kang, Wensheng & Ratti, Ronald. A. & Vespignani, Joaquin, 2018. "Financial and non-financial global stock market volatility shocks," Working Papers 2018-07, University of Tasmania, Tasmanian School of Business and Economics.
    41. Karaki, Mohamad B. & Rangaraju, Sandeep Kumar, 2023. "The confidence channel of U.S. financial uncertainty: Evidence from industry-level data," Economic Modelling, Elsevier, vol. 129(C).
    42. Cesa-Bianchi, Ambrogio & Pesaran, M Hashem & Rebucci, Alessandro, 2018. "Uncertainty and economic activity: a multi-country perspective," Bank of England working papers 730, Bank of England.
    43. Fischer, Manfred M. & Huber, Florian & Pfarrhofer, Michael, 2021. "The regional transmission of uncertainty shocks on income inequality in the United States," Journal of Economic Behavior & Organization, Elsevier, vol. 183(C), pages 887-900.
    44. Joshua Chan, 2023. "BVARs and Stochastic Volatility," Papers 2310.14438, arXiv.org.
    45. 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.
    46. Kevin Moran & Dalibor Stevanovic & Adam Abdel Kader Touré, 2020. "Macroeconomic Uncertainty and the COVID-19 Pandemic: Measure and Impacts on the Canadian Economy," CIRANO Working Papers 2020s-47, CIRANO.
    47. Andrea Carriero & Alessio Volpicella, 2022. "Generalizing the Max Share Identification to multiple shocks identification: an Application to Uncertainty," School of Economics Discussion Papers 0322, School of Economics, University of Surrey.
    48. Joshua C.C. Chan & Rodney W. Strachan, 2023. "Bayesian State Space Models In Macroeconometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 58-75, February.
    49. Paul Labonne, 2022. "Asymmetric Uncertainty: Nowcasting Using Skewness in Real-time Data," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2022-23, Economic Statistics Centre of Excellence (ESCoE).
    50. Brianti, Marco, 2021. "Financial Shocks, Uncertainty Shocks, and Monetary Policy Trade-Offs," Working Papers 2021-5, University of Alberta, Department of Economics.
    51. Johnson Worlanyo Ahiadorme, 2022. "On the aggregate effects of global uncertainty: Evidence from an emerging economy," South African Journal of Economics, Economic Society of South Africa, vol. 90(3), pages 390-407, September.
    52. Shin, Minchul & Zhang, Boyuan & Zhong, Molin & Lee, Dong Jin, 2018. "Measuring international uncertainty: The case of Korea," Economics Letters, Elsevier, vol. 162(C), pages 22-26.
    53. Danilo Cascaldi-Garcia & Ana Beatriz Galvao, 2018. "News and Uncertainty Shocks," International Finance Discussion Papers 1240, Board of Governors of the Federal Reserve System (U.S.).
    54. Michael Ryan, 2020. "A Narrative Approach to Creating Instruments with Unstructured and Voluminous Text: An Application to Policy Uncertainty," Working Papers in Economics 20/10, University of Waikato.
    55. Amy Rice & Tugrul Vehbi & Benjamin Wong, 2018. "Measuring uncertainty and its impact on the New Zealand economy," Reserve Bank of New Zealand Analytical Notes series AN2018/01, Reserve Bank of New Zealand.
    56. Selçuk Gul & Rangan Gupta, 2020. "A Note on the Time-Varying Impact of Global, Region- and Country-Specific Uncertainties on the Volatility of International Trade," Working Papers 202025, University of Pretoria, Department of Economics.
    57. Miguel Cabello & Rafael Nivin, 2022. "Measuring Uncertainty and its effects in a Small Open Economy," IHEID Working Papers 25-2022, Economics Section, The Graduate Institute of International Studies.
    58. Refk Selmi & Jamal Bouoiyour & Shawkat Hammoudeh, 2020. "Common and country-specific uncertainty fluctuations in oil-producing countries : Measures, macroeconomic effects and policy challenges," Post-Print hal-02929898, HAL.
    59. Danilo Cascaldi-Garcia & Cisil Sarisoy & Juan M. Londono & Bo Sun & Deepa D. Datta & Thiago Ferreira & Olesya Grishchenko & Mohammad R. Jahan-Parvar & Francesca Loria & Sai Ma & Marius Rodriguez & Ilk, 2023. "What Is Certain about Uncertainty?," Journal of Economic Literature, American Economic Association, vol. 61(2), pages 624-654, June.
    60. Heinrich, Markus, 2020. "Does the Current State of the Business Cycle matter for Real-Time Forecasting? A Mixed-Frequency Threshold VAR approach," EconStor Preprints 219312, ZBW - Leibniz Information Centre for Economics.
    61. Zhuo Huang & Fang Liang & Chen Tong, 2021. "The predictive power of macroeconomic uncertainty for commodity futures volatility," International Review of Finance, International Review of Finance Ltd., vol. 21(3), pages 989-1012, September.
    62. Sujoy Mukerji & Han N. Ozsoylev & Jean‐Marc Tallon, 2023. "Trading Ambiguity: A Tale Of Two Heterogeneities," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 64(3), pages 1127-1164, August.
    63. Hammoudeh, Shawkat & Uddin, Gazi Salah & Sousa, Ricardo M. & Wadström, Christoffer & Sharmi, Rubaiya Zaman, 2022. "Do pandemic, trade policy and world uncertainties affect oil price returns?," Resources Policy, Elsevier, vol. 77(C).
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    92. Sangyup Choi & Jeeyeon Phi, 2023. "Impact of Uncertainty Shocks on Income and Wealth Inequality," CAMA Working Papers 2023-33, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    93. Travis J. Berge, 2023. "Time-Varying Uncertainty of the Federal Reserve's Output Gap Estimate," The Review of Economics and Statistics, MIT Press, vol. 105(5), pages 1191-1206, September.
    94. Karin Klieber, 2023. "Non-linear dimension reduction in factor-augmented vector autoregressions," Papers 2309.04821, arXiv.org.
    95. Guglielmo Maria Caporale & Menelaos Karanasos & Stavroula Yfanti, 2024. "Macro‐financial linkages in the high‐frequency domain: Economic fundamentals and the Covid‐induced uncertainty channel in US and UK financial markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(2), pages 1581-1608, April.
    96. Berger, Tino & Kempa, Bernd & Zou, Feina, 2023. "The role of macroeconomic uncertainty in the determination of the natural rate of interest," Economics Letters, Elsevier, vol. 229(C).
    97. Josué Diwambuena & Jean-Paul K. Tsasa, 2021. "The Real Effects of Uncertainty Shocks: New Evidence from Linear and Nonlinear SVAR Models," BEMPS - Bozen Economics & Management Paper Series BEMPS87, Faculty of Economics and Management at the Free University of Bozen.
    98. Luo, Jiawen & Marfatia, Hardik A. & Ji, Qiang & Klein, Tony, 2023. "Co-volatility and asymmetric transmission of risks between the global oil and China's futures markets," Energy Economics, Elsevier, vol. 117(C).
    99. Ma, Xiaohan & Samaniego, Roberto, 2019. "Deconstructing uncertainty," European Economic Review, Elsevier, vol. 119(C), pages 22-41.
    100. Cristiana Fiorelli & Alfredo Cartone & Matteo Foglia, 2021. "Shadow rates and spillovers across the Eurozone: a spatial dynamic panel model," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 48(1), pages 223-245, February.
    101. Piergiorgio Alessandri & Andrea Gazzani & Alejandro Vicondoa, 2023. "Are the Effects of Uncertainty Shocks Big or Small?," Working Papers 244, Red Nacional de Investigadores en Economía (RedNIE).
    102. Gupta, Rangan & Ma, Jun & Risse, Marian & Wohar, Mark E., 2018. "Common business cycles and volatilities in US states and MSAs: The role of economic uncertainty," Journal of Macroeconomics, Elsevier, vol. 57(C), pages 317-337.
    103. Fuest, Angela & Schmidt, Torsten, 2020. "Inflation expectation uncertainty in a New Keynesian framework," Ruhr Economic Papers 867, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    104. Philippe Goulet Coulombe & Mikael Frenette & Karin Klieber, 2023. "From Reactive to Proactive Volatility Modeling with Hemisphere Neural Networks," Papers 2311.16333, arXiv.org, revised Apr 2024.
    105. Schüler, Yves S., 2020. "The impact of uncertainty and certainty shocks," Discussion Papers 14/2020, Deutsche Bundesbank.
    106. Myriam Gómez-Méndez & Erwin Hansen, 2021. "Economic policy uncertainty and presidential approval: Evidence from Latin America," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-17, March.
    107. Timo Wollmershäuser & Florian Eckert & Marcell Göttert & Christian Grimme & Carla Krolage & Stefan Lautenbacher & Robert Lehmann & Sebastian Link & Heiner Mikosch & Stefan Neuwirth & Wolfgang Nierhaus, 2019. "ifo Konjunkturprognose Winter 2019: Deutsche Konjunktur stabilisiert sich," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 72(24), pages 27-89, December.
    108. Tong, Chen & Huang, Zhuo & Wang, Tianyi & Zhang, Cong, 2023. "The effects of economic uncertainty on financial volatility: A comprehensive investigation," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 369-389.
    109. Alessio Anzuini & Luca Rossi, 2021. "Fiscal policy in the US: a new measure of uncertainty and its effects on the American economy," Empirical Economics, Springer, vol. 61(5), pages 2613-2634, November.
    110. Kang, Wensheng & Ratti, Ronald A. & Vespignani, Joaquin L., 2020. "Revising the Impact of Financial and Non-Financial Global Stock Market Volatility Shocks," MPRA Paper 103019, University Library of Munich, Germany.
    111. Juan M. Londono & Sai Ma & Beth Anne Wilson, 2021. "The Global Transmission of Real Economic Uncertainty," International Finance Discussion Papers 1317, Board of Governors of the Federal Reserve System (U.S.).
    112. Lin Liu, 2021. "U.S. Economic Uncertainty Shocks and China’s Economic Activities: A Time-Varying Perspective," SAGE Open, , vol. 11(3), pages 21582440211, July.
    113. Bae, Siye & Jo, Soojin & Shim, Myungkyu, 2023. "United States of Mind under Uncertainty," Journal of Economic Behavior & Organization, Elsevier, vol. 213(C), pages 102-127.
    114. Jamie L. Cross & Chenghan Hou & Aubrey Poon, 2018. "International Transmission of Macroeconomic Uncertainty in Small Open Economies: An Empirical Approach," Working Papers No 12/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    115. Jamal Bouoiyour & Refk Selmi, 2019. "The Qatar-Gulf Crisis and Risk Management in Oil and Gas Markets," Working Papers hal-02101633, HAL.
    116. Oscar Claveria, 2021. "Disagreement on expectations: firms versus consumers," SN Business & Economics, Springer, vol. 1(12), pages 1-23, December.
    117. Gorodnichenko, Yuriy & Ng, Serena, 2017. "Level and volatility factors in macroeconomic data," Journal of Monetary Economics, Elsevier, vol. 91(C), pages 52-68.
    118. Ductor, Lorenzo & Leiva-León, Danilo, 2022. "Fluctuations in global output volatility," Journal of International Money and Finance, Elsevier, vol. 120(C).
    119. M. Karanasos & S. Yfanti & J. Hunter, 2022. "Emerging stock market volatility and economic fundamentals: the importance of US uncertainty spillovers, financial and health crises," Annals of Operations Research, Springer, vol. 313(2), pages 1077-1116, June.
    120. Dibiasi, Andreas & Sarferaz, Samad, 2023. "Measuring macroeconomic uncertainty: A cross-country analysis," European Economic Review, Elsevier, vol. 153(C).
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    124. Awijen, Haithem & Ben Zaied, Younes & Nguyen, Duc Khuong & Sensoy, Ahmet, 2020. "Endogenous Financial Uncertainty and Macroeconomic Volatility: Evidence from the United States," MPRA Paper 101276, University Library of Munich, Germany, revised Jun 2020.
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  17. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2016. "Large Vector Autoregressions with Stochastic Volatility and Flexible Priors," Working Papers (Old Series) 1617, Federal Reserve Bank of Cleveland.

    Cited by:

    1. 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.
    2. Koop, Gary & Korobilis, Dimitris & Pettenuzzo, Davide, 2019. "Bayesian compressed vector autoregressions," Journal of Econometrics, Elsevier, vol. 210(1), pages 135-154.
    3. Brave, Scott A. & Butters, R. Andrew & Justiniano, Alejandro, 2019. "Forecasting economic activity with mixed frequency BVARs," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1692-1707.
    4. Petrova, Katerina, 2019. "A quasi-Bayesian local likelihood approach to time varying parameter VAR models," Journal of Econometrics, Elsevier, vol. 212(1), pages 286-306.
    5. Turunen Harry & Zhutova Anastasia & Lemoine Matthieu, 2023. "Stochastic Simulation of the FR-BDF Model and an Assessment of Uncertainty around Conditional Forecasts," Working papers 920, Banque de France.
    6. Joshua C.C. Chan & Eric Eisenstat & Rodney W. Strachan, 2018. "Reducing dimensions in a large TVP-VAR," CAMA Working Papers 2018-49, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    7. Angelini, Elena & Lalik, Magdalena & Lenza, Michele & Paredes, Joan, 2019. "Mind the gap: A multi-country BVAR benchmark for the Eurosystem projections," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1658-1668.
    8. Bognanni, Mark, 2022. "Comment on “Large Bayesian vector autoregressions with stochastic volatility and non-conjugate priors”," Journal of Econometrics, Elsevier, vol. 227(2), pages 498-505.
    9. Petrova, Katerina, 2022. "Asymptotically valid Bayesian inference in the presence of distributional misspecification in VAR models," Journal of Econometrics, Elsevier, vol. 230(1), pages 154-182.
    10. Kohns, David & Potjagailo, Galina, 2023. "Flexible Bayesian MIDAS: time‑variation, group‑shrinkage and sparsity," Bank of England working papers 1025, Bank of England.
    11. Lu, Yunzhi & Li, Jie & Yang, Haisheng, 2023. "Time-varying impacts of monetary policy uncertainty on China's housing market," Economic Modelling, Elsevier, vol. 118(C).
    12. Dellaportas, Petros & Titsias, Michalis K. & Petrova, Katerina & Plataniotis, Anastasios, 2023. "Scalable inference for a full multivariate stochastic volatility model," Journal of Econometrics, Elsevier, vol. 232(2), pages 501-520.

  18. Fabian Kr�ger & Todd E. Clark & Francesco Ravazzolo, 2015. "Using Entropic Tilting to Combine BVAR Forecasts with External Nowcasts," Working Papers No 8/2015, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.

    Cited by:

    1. Bańbura, Marta & Leiva-Leon, Danilo & Menz, Jan-Oliver, 2021. "Do inflation expectations improve model-based inflation forecasts?," Working Paper Series 2604, European Central Bank.
    2. 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.
    3. Gary Koop & Stuart McIntyre & James Mitchell, 2018. "UK Regional Nowcasting using a Mixed Frequency Vector Autoregressive Model," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2018-07, Economic Statistics Centre of Excellence (ESCoE).
    4. Christopher McDonald & Craig Thamotheram & Shaun P. Vahey & Elizabeth C. Wakerly, 2016. "Assessing the economic value of probabilistic forecasts in the presence of an inflation target," CAMA Working Papers 2016-40, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    5. 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.
    6. Hauber, Philipp, 2021. "How useful is external information from professional forecasters? Conditional forecasts in large factor models," EconStor Preprints 251469, ZBW - Leibniz Information Centre for Economics.
    7. Edward S. Knotek & Saeed Zaman, 2017. "Financial Nowcasts and Their Usefulness in Macroeconomic Forecasting," Working Papers (Old Series) 1702, Federal Reserve Bank of Cleveland.
    8. Dimitris Kenourgios & Stephanos Papadamou & Dimitrios Dimitriou & Constantin Zopounidis, 2020. "Modelling the dynamics of unconventional monetary policies’ impact on professionals’ forecasts," Post-Print hal-02880071, HAL.
    9. 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.
    10. Ganics, Gergely & Odendahl, Florens, 2021. "Bayesian VAR forecasts, survey information, and structural change in the euro area," International Journal of Forecasting, Elsevier, vol. 37(2), pages 971-999.
    11. Richard K. Crump & Stefano Eusepi & Domenico Giannone & Eric Qian & Argia M. Sbordone, 2021. "A Large Bayesian VAR of the United States Economy," Staff Reports 976, Federal Reserve Bank of New York.
    12. Taeyoung Doh, 2017. "Trend and Uncertainty in the Long-Term Real Interest Rate: Bayesian Exponential Tilting with Survey Data," Research Working Paper RWP 17-8, Federal Reserve Bank of Kansas City.
    13. Knüppel, Malte & Krüger, Fabian, 2019. "Forecast uncertainty, disagreement, and the linear pool," Discussion Papers 28/2019, Deutsche Bundesbank.
    14. Galvao, Ana Beatriz & Garratt, Anthony & Mitchell, James, 2020. "Does Judgment Improve Macroeconomic Density Forecasts?," EMF Research Papers 33, Economic Modelling and Forecasting Group.
    15. Edward S. Knotek & Saeed Zaman, 2020. "Real-Time Density Nowcasts of US Inflation: A Model-Combination Approach," Working Papers 20-31, Federal Reserve Bank of Cleveland.
    16. Todd E. Clark & Gergely Ganics & Elmar Mertens, 2022. "What is the Predictive Value of SPF Point and Density Forecasts?," Working Papers 22-37, Federal Reserve Bank of Cleveland.
    17. Maryam Movahedifar & Hossein Hassani & Masoud Yarmohammadi & Mahdi Kalantari & Rangan Gupta, 2021. "A robust approach for outlier imputation: Singular Spectrum Decomposition," Working Papers 202164, University of Pretoria, Department of Economics.
    18. Fabian Krüger, 2017. "Survey-based forecast distributions for Euro Area growth and inflation: ensembles versus histograms," Empirical Economics, Springer, vol. 53(1), pages 235-246, August.
    19. Pablo Guerróon‐Quintana & Molin Zhong, 2023. "Macroeconomic forecasting in times of crises," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(3), pages 295-320, April.
    20. Cem Cakmakli & Hamza Demircan, 2020. "Using Survey Information for Improving the Density Nowcasting of US GDP with a Focus on Predictive Performance during Covid-19 Pandemic," Koç University-TUSIAD Economic Research Forum Working Papers 2016, Koc University-TUSIAD Economic Research Forum.
    21. Nadiia Shapovalenko, 2021. "A BVAR Model for Forecasting Ukrainian Inflation," IHEID Working Papers 05-2021, Economics Section, The Graduate Institute of International Studies.
    22. Montes-Galdón, Carlos & Paredes, Joan & Wolf, Elias, 2022. "Conditional density forecasting: a tempered importance sampling approach," Working Paper Series 2754, European Central Bank.
    23. Yuliya Rychalovska & Sergey Slobodyan & Rafael Wouters, 2023. "Professional Survey Forecasts and Expectations in DSGE Models," CERGE-EI Working Papers wp766, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    24. Bjarni G. Einarsson, 2024. "Online Monitoring of Policy Optimality," Economics wp95, Department of Economics, Central bank of Iceland.
    25. Christiane Baumeister, 2021. "Measuring Market Expectations," Working Papers 202163, University of Pretoria, Department of Economics.
    26. Richard Schnorrenberger & Aishameriane Schmidt & Guilherme Valle Moura, 2024. "Harnessing Machine Learning for Real-Time Inflation Nowcasting," Working Papers 806, DNB.
    27. Gary Koop & Stuart McIntyre & James Mitchell, 2020. "UK regional nowcasting using a mixed frequency vector auto‐regressive model with entropic tilting," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(1), pages 91-119, January.
    28. Marta Baltar Moreira Areosa & Wagner Piazza Gaglianone, 2023. "Anchoring Long-term VAR Forecasts Based On Survey Data and State-space Models," Working Papers Series 574, Central Bank of Brazil, Research Department.
    29. Bańbura, Marta & Brenna, Federica & Paredes, Joan & Ravazzolo, Francesco, 2021. "Combining Bayesian VARs with survey density forecasts: does it pay off?," Working Paper Series 2543, European Central Bank.
    30. Fabian Krüger & Sebastian Lerch & Thordis Thorarinsdottir & Tilmann Gneiting, 2021. "Predictive Inference Based on Markov Chain Monte Carlo Output," International Statistical Review, International Statistical Institute, vol. 89(2), pages 274-301, August.
    31. Markus Heinrich & Magnus Reif, 2020. "Real-Time Forecasting Using Mixed-Frequency VARS with Time-Varying Parameters," CESifo Working Paper Series 8054, CESifo.

  19. Joshua C. C. Chan & Todd E. Clark & Gary Koop, 2015. "A New Model of Inflation, Trend Inflation, and Long-Run Inflation Expectations," Working Papers (Old Series) 1520, Federal Reserve Bank of Cleveland.

    Cited by:

    1. Bańbura, Marta & Leiva-Leon, Danilo & Menz, Jan-Oliver, 2021. "Do inflation expectations improve model-based inflation forecasts?," Working Paper Series 2604, European Central Bank.
    2. Elizaveta Lukmanova & Katrin Rabitsch, 2018. "New VAR evidence on monetary transmission channels: temporary interest rate versus inflation target shocks," Department of Economics Working Papers wuwp274, Vienna University of Economics and Business, Department of Economics.
    3. Geraldine Dany-Knedlik & Juan Angel Garcia, 2018. "Monetary Policy and Inflation Dynamics in ASEAN Economies," IMF Working Papers 2018/147, International Monetary Fund.
    4. Mengheng Li & Siem Jan Koopman, 2021. "Unobserved components with stochastic volatility: Simulation‐based estimation and signal extraction," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 614-627, August.
    5. Juan Angel Garcia & Sebastian Werner, 2018. "Inflation News and Euro Area Inflation Expectations," IMF Working Papers 2018/167, International Monetary Fund.
    6. Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Working Papers 22-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
    7. Manuel M. F. Martins & Fabio Verona, 2020. "Forecasting Inflation with the New Keynesian Phillips Curve: Frequency Matters," CEF.UP Working Papers 2001, Universidade do Porto, Faculdade de Economia do Porto.
    8. Richard K. Crump & Stefano Eusepi & Emanuel Moench & Bruce Preston, 2021. "The Term Structure of Expectations," Staff Reports 992, Federal Reserve Bank of New York.
    9. Takushi Kurozumi & Willem Van Zandweghe, 2021. "Macroeconomic Changes with Declining Trend Inflation: Complementarity with the Superstar Firm Hypothesis," Bank of Japan Working Paper Series 21-E-13, Bank of Japan.
    10. Hauber, Philipp & Schumacher, Christian, 2021. "Precision-based sampling with missing observations: A factor model application," Discussion Papers 11/2021, Deutsche Bundesbank.
    11. Andriantomanga, Zo, 2023. "The role of survey-based expectations in real-time forecasting of US inflation," MPRA Paper 119904, University Library of Munich, Germany.
    12. Lenza, Michele & Jarociński, Marek, 2016. "An inflation-predicting measure of the output gap in the euro area," Working Paper Series 1966, European Central Bank.
    13. Pfarrhofer, Michael, 2022. "Modeling tail risks of inflation using unobserved component quantile regressions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    14. Marente Vlekke & Martin Mellens & Siem Jan Koopmans, 2020. "An assessment of the Phillips curve over time: evidence for the United States and the euro area," CPB Discussion Paper 416, CPB Netherlands Bureau for Economic Policy Analysis.
    15. Huber, Florian & Kaufmann, Daniel, 2016. "Trend Fundamentals and Exchange Rate Dynamics," Department of Economics Working Paper Series 214, WU Vienna University of Economics and Business.
    16. Martins, Manuel Mota Freitas & Verona, Fabio, 2021. "Inflation dynamics and forecast: Frequency matters," Bank of Finland Research Discussion Papers 8/2021, Bank of Finland.
    17. Juan Angel Garcia & Aubrey Poon, 2022. "Inflation trends in Asia: implications for central banks [Are Phillips curves useful for forecasting inflation?]," Oxford Economic Papers, Oxford University Press, vol. 74(3), pages 671-700.
    18. Diegel, Max, 2022. "Time-varying credibility, anchoring and the Fed's inflation target," Discussion Papers 2022/9, Free University Berlin, School of Business & Economics.
    19. Francesca Rondina, 2018. "Estimating unobservable inflation expectations in the New Keynesian Phillips Curve," Working Papers 1804E, University of Ottawa, Department of Economics.
    20. Christina Anderl & Guglielmo Maria Caporale, 2022. "Forecasting Inflation with a Zero Lower Bound or Negative Interest Rates: Evidence from Point and Density Forecasts," CESifo Working Paper Series 9687, CESifo.
    21. Murasawa, Yasutomo, 2019. "Bayesian multivariate Beveridge--Nelson decomposition of I(1) and I(2) series with cointegration," MPRA Paper 91979, University Library of Munich, Germany.
    22. Bańbura, Marta & Bobeica, Elena, 2020. "PCCI – a data-rich measure of underlying inflation in the euro area," Statistics Paper Series 38, European Central Bank.
    23. Ellis W. Tallman & Saeed Zaman, 2015. "Forecasting Inflation: Phillips Curve Effects on Services Price Measures," Working Papers (Old Series) 1519, Federal Reserve Bank of Cleveland.
    24. Bańbura, Marta & Bobeica, Elena, 2023. "Does the Phillips curve help to forecast euro area inflation?," International Journal of Forecasting, Elsevier, vol. 39(1), pages 364-390.
    25. Dany-Knedlik, Geraldine & Holtemöller, Oliver, 2018. "Inflation dynamics during the Financial Crisis in Europe: cross-sectional identification of long-run inflation expectations," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181520, Verein für Socialpolitik / German Economic Association.
    26. Juan Angel Garcia & Aubrey Poon, 2018. "Trend Inflation and Inflation Compensation," IMF Working Papers 2018/154, International Monetary Fund.
    27. Bowen Fu, Ivan Mendieta-Muñoz, 2023. "Structural shocks and trend inflation," Working Paper Series, Department of Economics, University of Utah 2023_04, University of Utah, Department of Economics.
    28. Arnoud Stevens & Joris Wauters, 2021. "Is euro area lowflation here to stay? Insights from a time‐varying parameter model with survey data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 566-586, August.
    29. Arbex, Marcelo & Caetano, Sidney & Correa, Wilson, 2019. "Macroeconomic effects of inflation target uncertainty shocks," Economics Letters, Elsevier, vol. 181(C), pages 111-115.
    30. Beechey, Meredith & Österholm, Pär & Poon, Aubrey, 2023. "Estimating the US trend short-term interest rate," Finance Research Letters, Elsevier, vol. 55(PA).
    31. Martin Feldkircher & Pierre L. Siklos, 2018. "Global inflation dynamics and inflation expectations," CAMA Working Papers 2018-60, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    32. Jaromir Baxa & Miroslav Plasil & Borek Vasicek, 2013. "Inflation and the Steeplechase Between Economic Activity Variables," Working Papers 2013/15, Czech National Bank.
    33. Diegel, Max & Nautz, Dieter, 2020. "The role of long-term inflation expectations for the transmission of monetary policy shocks," Discussion Papers 2020/19, Free University Berlin, School of Business & Economics.
    34. Chew Lian Chua & Tim Robinson, 2018. "Why Has Australian Wages Growth Been So Low? A Phillips Curve Perspective," The Economic Record, The Economic Society of Australia, vol. 94(S1), pages 11-32, June.
    35. Pär Österholm & Aubrey Poon, 2023. "Trend Inflation in Sweden," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 4707-4716, October.
    36. McNeil, James, 2023. "Monetary policy and the term structure of inflation expectations with information frictions," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).
    37. Chen, Ji & Yang, Xinglin & Liu, Xiliang, 2022. "Learning, disagreement and inflation forecasting," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    38. Güneş Kamber & Benjamin Wong, 2018. "Global factors and trend inflation," BIS Working Papers 688, Bank for International Settlements.
    39. Nikita D. Fokin & Ekaterina V. Malikova & Andrey V. Polbin, 2024. "Time-varying parameters error correction model for real ruble exchange rate and oil prices: What has changed due to capital control and sanctions?," Russian Journal of Economics, ARPHA Platform, vol. 10(1), pages 20-33, March.
    40. Niko Hauzenberger & Florian Huber & Karin Klieber, 2020. "Real-time Inflation Forecasting Using Non-linear Dimension Reduction Techniques," Papers 2012.08155, arXiv.org, revised Dec 2021.
    41. Cecchetti, Stephen & Feroli, Michael & Hooper, Peter & Kashyap, Anil & Schoenholtz, Kermit L., 2017. "Deflating Inflation Expectations: The Implications of Inflation’s Simple Dynamics," CEPR Discussion Papers 11925, C.E.P.R. Discussion Papers.
    42. Fu, Bowen, 2020. "Is the slope of the Phillips curve time-varying? Evidence from unobserved components models," Economic Modelling, Elsevier, vol. 88(C), pages 320-340.
    43. Kristin Forbes, 2019. "Has globalization changed the inflation process?," BIS Working Papers 791, Bank for International Settlements.
    44. Marta Banbura & Andries van Vlodrop, 2018. "Forecasting with Bayesian Vector Autoregressions with Time Variation in the Mean," Tinbergen Institute Discussion Papers 18-025/IV, Tinbergen Institute.
    45. Andrew B. Martinez, 2020. "Extracting Information from Different Expectations," Working Papers 2020-008, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    46. Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Papers 2202.04146, arXiv.org.
    47. Marco Gross & Willi Semmler, 2019. "Mind the Output Gap: The Disconnect of Growth and Inflation during Recessions and Convex Phillips Curves in the Euro Area," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 81(4), pages 817-848, August.
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    51. Aubrey Poon, 2018. "Assessing the Synchronicity and Nature of Australian State Business Cycles," The Economic Record, The Economic Society of Australia, vol. 94(307), pages 372-390, December.
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  20. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2015. "Large Vector Autoregressions with Asymmetric Priors," Working Papers 759, Queen Mary University of London, School of Economics and Finance.

    Cited by:

    1. Feldkircher, Martin & Gruber, Thomas & Huber, Florian, 2017. "Spreading the word or reducing the term spread? Assessing spillovers from euro area monetary policy," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168111, Verein für Socialpolitik / German Economic Association.
    2. Koop, Gary & Korobilis, Dimitris & Pettenuzzo, Davide, 2019. "Bayesian compressed vector autoregressions," Journal of Econometrics, Elsevier, vol. 210(1), pages 135-154.
    3. Joshua Chan & Arnaud Doucet & Roberto León-González & Rodney W. Strachan, 2018. "Multivariate Stochastic Volatility with Co-Heteroscedasticity," Working Paper series 18-38, Rimini Centre for Economic Analysis.
    4. Martin Feldkircher & Florian Huber, 2016. "Unconventional US Monetary Policy: New Tools, Same Channels?," Department of Economics Working Papers wuwp222, Vienna University of Economics and Business, Department of Economics.
    5. Martin Feldkircher & Elizaveta Lukmanova & Gabriele Tondl, 2019. "Global Factors Driving Inflation and Monetary Policy: A Global VAR Assessment," Department of Economics Working Papers wuwp289, Vienna University of Economics and Business, Department of Economics.
    6. Christian Hotz-Behofsits & Florian Huber & Thomas O. Zorner, 2018. "Predicting crypto-currencies using sparse non-Gaussian state space models," Papers 1801.06373, arXiv.org, revised Feb 2018.
    7. Florian Huber & Thomas Zörner, 2017. "Threshold cointegration and adaptive shrinkage," Department of Economics Working Papers wuwp250, Vienna University of Economics and Business, Department of Economics.
    8. Feldkircher, Martin & Gruber, Thomas & Huber, Florian, 2020. "International effects of a compression of euro area yield curves," Journal of Banking & Finance, Elsevier, vol. 113(C).
    9. Pappa, Evi & Molteni, Francesco, 2017. "The Combination of Monetary and Fiscal Policy Shocks: A TVP-FAVAR Approach," CEPR Discussion Papers 12541, C.E.P.R. Discussion Papers.
    10. Gregor Kastner & Florian Huber, 2017. "Sparse Bayesian vector autoregressions in huge dimensions," Papers 1704.03239, arXiv.org, revised Dec 2019.
    11. Emmanuel C. Mamatzakis & Steven Ongena & Mike G. Tsionas, 2023. "The response of household debt to COVID-19 using a neural networks VAR in OECD," Empirical Economics, Springer, vol. 65(1), pages 65-91, July.
    12. Huber, Florian & Zörner, Thomas O., 2019. "Threshold cointegration in international exchange rates:A Bayesian approach," International Journal of Forecasting, Elsevier, vol. 35(2), pages 458-473.
    13. Assaf, A. George & Tsionas, Mike G., 2019. "Forecasting occupancy rate with Bayesian compression methods," Annals of Tourism Research, Elsevier, vol. 75(C), pages 439-449.

  21. Kristle Romero Cortes & Philip E. Strahan, 2014. "Tracing Out Capital Flows: How Financially Integrated Banks Respond to Natural Disasters," Working Papers (Old Series) 1412, Federal Reserve Bank of Cleveland.

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    1. Noth, Felix & Rehbein, Oliver, 2019. "Badly hurt? Natural disasters and direct firm effects," Finance Research Letters, Elsevier, vol. 28(C), pages 254-258.
    2. Wang, Teng, 2021. "Local banks and the effects of oil price shocks," Journal of Banking & Finance, Elsevier, vol. 125(C).
    3. Huber, Kilian, 2021. "Are Bigger Banks Better? Firm-Level Evidence from Germany," CEPR Discussion Papers 15769, C.E.P.R. Discussion Papers.
    4. Giovanni Dell'Ariccia & Dalida Kadyrzhanova & Camelia Minoiu & Lev Ratnovski, 2020. "Bank Lending in the Knowledge Economy," Finance and Economics Discussion Series 2020-040, Board of Governors of the Federal Reserve System (U.S.).
    5. João Granja & Christian Leuz & Raghuram Rajan, 2018. "Going the Extra Mile: Distant Lending and Credit Cycles," NBER Working Papers 25196, National Bureau of Economic Research, Inc.
    6. Stefano Federico & Fadi Hassan & Veronica Rappoport, 2020. "Trade shocks and credit reallocation," Temi di discussione (Economic working papers) 1289, Bank of Italy, Economic Research and International Relations Area.
    7. Duqi, Andi & McGowan, Danny & Onali, Enrico & Torluccio, Giuseppe, 2021. "Natural disasters and economic growth: The role of banking market structure," Journal of Corporate Finance, Elsevier, vol. 71(C).
    8. Aguilar-Gomez, Sandra & Gutierrez, Emilio & Heres, David & Jaume, David & Tobal, Martin, 2024. "Thermal stress and financial distress: Extreme temperatures and firms’ loan defaults in Mexico," Journal of Development Economics, Elsevier, vol. 168(C).
    9. Petkov, Ivan, 2023. "Small business lending and the bank-branch network," Journal of Financial Stability, Elsevier, vol. 64(C).
    10. Avril Pauline & Levieuge Grégory & Turcu Camelia, 2022. "Natural Disasters and Financial Stress: Can Macroprudential Regulation Tame Green Swans?," Working papers 874, Banque de France.
    11. Kakuho Furukawa & Hibiki Ichiue & Noriyuki Shiraki, 2020. "How Does Climate Change Interact with the Financial System? A Survey," Bank of Japan Working Paper Series 20-E-8, Bank of Japan.
    12. Hua Song & Yudong Yang & Zheng Tao, 2020. "How different types of financial service providers support small- and medium- enterprises under the impact of COVID-19 pandemic: from the perspective of expectancy theory," Frontiers of Business Research in China, Springer, vol. 14(1), pages 1-27, December.
    13. Chakraborty, Indraneel & Goldstein, Itay & MacKinlay, Andrew, 2020. "Monetary stimulus and bank lending," Journal of Financial Economics, Elsevier, vol. 136(1), pages 189-218.
    14. Czura, Kristina & Klonner, Stefan, 2023. "Financial market responses to a natural disaster: Evidence from credit networks and the Indian Ocean tsunami," Journal of Development Economics, Elsevier, vol. 160(C).
    15. Roman Horvath, 2020. "Natural Catastrophes and Financial Development: An Empirical Analysis," Working Papers IES 2020/14, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised May 2020.
    16. Franziska Bremus & Malte Rieth, 2023. "Integrating Out Natural Disaster Shocks," Discussion Papers of DIW Berlin 2063, DIW Berlin, German Institute for Economic Research.
    17. Ivan Petkov, 2022. "Weather Shocks, Population, and Housing Prices: the Role of Expectation Revisions," Economics of Disasters and Climate Change, Springer, vol. 6(3), pages 495-540, November.
    18. Schüwer, Ulrich & Lambert, Claudia & Noth, Felix, 2017. "How do banks react to catastrophic events? Evidence from Hurricane Katrina," SAFE Working Paper Series 94, Leibniz Institute for Financial Research SAFE, revised 2017.
    19. Koetter, Michael & Noth, Felix & Rehbein, Oliver, 2019. "Borrowers under water! Rare disasters, regional banks, and recovery lending," IWH Discussion Papers 31/2016, Halle Institute for Economic Research (IWH), revised 2019.
    20. Tho Pham & Oleksandr Talavera & Andriy Tsapin, 2018. "Shock Contagion, Asset Quality and Lending Behavior," Working Papers 01/2018, National Bank of Ukraine.
    21. Feng, Zhi-Yuan & Wang, Chou-Wen & Lu, Yu-Hong, 2022. "The impact of climatic disaster on corporate investment policy," Journal of Multinational Financial Management, Elsevier, vol. 66(C).
    22. Allen N. Berger & Filippo Curti & Nika Lazaryan & Atanas Mihov & Raluca A. Roman, 2023. "Climate Risks in the U.S. Banking Sector: Evidence from Operational Losses and Extreme Storms," Working Papers 21-31, Federal Reserve Bank of Philadelphia.
    23. Ivan Faiella & Filippo Natoli, 2018. "Natural catastrophes and bank lending: the case of flood risk in Italy," Questioni di Economia e Finanza (Occasional Papers) 457, Bank of Italy, Economic Research and International Relations Area.
    24. Shi, Yining, 2022. "Financial liberalization and house prices: Evidence from China," Journal of Banking & Finance, Elsevier, vol. 145(C).
    25. Ross Levine & Chen Lin & Wensi Xie, 2021. "Geographic Diversification and Banks’ Funding Costs," Management Science, INFORMS, vol. 67(5), pages 2657-2678, May.
    26. Braun, Alexander & Braun, Julia & Weigert, Florian, 2023. "Extreme weather risk and the cost of equity," CFR Working Papers 23-08, University of Cologne, Centre for Financial Research (CFR).
    27. James R. Brown & Matthew T. Gustafson & Ivan T. Ivanov, 2021. "Weathering Cash Flow Shocks," Journal of Finance, American Finance Association, vol. 76(4), pages 1731-1772, August.
    28. Erel, Isil & Liebersohn, Jack, 2022. "Can FinTech reduce disparities in access to finance? Evidence from the Paycheck Protection Program," Journal of Financial Economics, Elsevier, vol. 146(1), pages 90-118.
    29. Mercy Berman DeMenno, 2023. "Environmental sustainability and financial stability: can macroprudential stress testing measure and mitigate climate-related systemic financial risk?," Journal of Banking Regulation, Palgrave Macmillan, vol. 24(4), pages 445-473, December.
    30. Holod, Dmytro & Torna, Gökhan, 2018. "Do community banks contribute to international trade? Evidence from U.S. Data," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 57(C), pages 185-204.
    31. Sebastian Doerr & Philipp Schaz, 2018. "Bank loan supply during crises: the importance of geographic diversification," ECON - Working Papers 288, Department of Economics - University of Zurich, revised Mar 2019.
    32. Noth, Felix & Schüwer, Ulrich, 2023. "Natural disasters and bank stability: Evidence from the U.S. financial system," Journal of Environmental Economics and Management, Elsevier, vol. 119(C).
    33. Wang, Jiaxin & Zhu, Zhaowei & Huang, Xiang, 2023. "Stock bubbles under sudden public crises: A perspective from the excessive financialization of firms," Finance Research Letters, Elsevier, vol. 57(C).
    34. Ruchi Avtar & Kristian S. Blickle & Rajashri Chakrabarti & Janavi Janakiraman & Maxim L. Pinkovskiy, 2023. "Understanding the Linkages between Climate Change and Inequality in the United States," Economic Policy Review, Federal Reserve Bank of New York, vol. 29(1), pages 1-39, June.
    35. Salih Fendo?lu & Eda Gül?en & José-Luis Peydró, 2019. "Global Liquidity and Impairment of Local Monetary Policy," Working Papers 1131, Barcelona School of Economics.
    36. Barth, James R. & Hu, Qinyou & Sickles, Robin & Sun, Yanfei & Yu, Xiaoyu, 2024. "Direct and indirect impacts of natural disasters on banks: A spatial framework," Journal of Financial Stability, Elsevier, vol. 70(C).
    37. Cuñat, Vicente & Cvijanovic, Dragana & Yuan, Kathy, 2018. "Within-bank spillovers of real estate shocks," LSE Research Online Documents on Economics 87374, London School of Economics and Political Science, LSE Library.
    38. Antonio Forte & Selay Sahan & Damiano B. Silipo, 2024. "Do Natural Disasters Reduce Loans to the More CO 2 -Emitting Sectors?," Sustainability, MDPI, vol. 16(10), pages 1-24, May.
    39. Wan-Li Zhang & Chun-Ping Chang & Yang Xuan, 2022. "The impacts of climate change on bank performance: What’s the mediating role of natural disasters?," Economic Change and Restructuring, Springer, vol. 55(3), pages 1913-1952, August.
    40. Rubio-Andrés, Mercedes & Ramos-González, Mª del Mar & Sastre-Castillo, Miguel Ángel & Gutiérrez-Broncano, Santiago, 2023. "Stakeholder pressure and innovation capacity of SMEs in the COVID-19 pandemic: Mediating and multigroup analysis," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
    41. Nuno Paixao, 2019. "Propagation of House Price Shocks through the Banking System," 2019 Meeting Papers 1237, Society for Economic Dynamics.
    42. Markus Herrmann & Martin Hibbeln, 2023. "Trading and liquidity in the catastrophe bond market," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 90(2), pages 283-328, June.
    43. Allen, Kyle D. & Whitledge, Matthew D. & Winters, Drew B., 2022. "Community bank liquidity: Natural disasters as a natural experiment," Journal of Financial Stability, Elsevier, vol. 60(C).
    44. Schüwer, Ulrich & Gropp, Reint E. & Noth, Felix, 2016. "What drives banks' geographic expansion? The role of locally non-diversifiable risk," VfS Annual Conference 2016 (Augsburg): Demographic Change 145885, Verein für Socialpolitik / German Economic Association.
    45. Smolyansky, Michael, 2019. "Policy externalities and banking integration," Journal of Financial Economics, Elsevier, vol. 132(3), pages 118-139.
    46. Agus Sugiarto & Ni Nyoman Puspani & Mustika Septiyas Trisilia, 2023. "The Shocks of Climate Change on Bank Loans," International Journal of Energy Economics and Policy, Econjournals, vol. 13(5), pages 493-514, September.
    47. Garbarino, Nicola & Guin, Benjamin, 2021. "High water, no marks? Biased lending after extreme weather," Journal of Financial Stability, Elsevier, vol. 54(C).
    48. Li, Jie & An, Yahui & Wang, Lidan & Zhang, Yongjie, 2022. "Combating the COVID-19 pandemic: The role of disaster experience," Research in International Business and Finance, Elsevier, vol. 60(C).
    49. Doerr, Sebastian & Schaz, Philipp, 2021. "Geographic diversification and bank lending during crises," Journal of Financial Economics, Elsevier, vol. 140(3), pages 768-788.
    50. Henry He Huang & Joseph Kerstein & Chong Wang & Feng (Harry) Wu, 2022. "Firm climate risk, risk management, and bank loan financing," Strategic Management Journal, Wiley Blackwell, vol. 43(13), pages 2849-2880, December.
    51. Martin R. Goetz & Juan Carlos Gozzi, 2020. "Financial Integration and the Co-Movement of Economic Activity: Evidence from U.S. States," International Finance Discussion Papers 1305, Board of Governors of the Federal Reserve System (U.S.).
    52. Benincasa, Emanuela & Betz, Frank & Gattini, Luca, 2024. "How do firms cope with losses from extreme weather events?," Journal of Corporate Finance, Elsevier, vol. 84(C).
    53. Bayangos, Veronica B. & Cachuela, Rafael Augusto D. & Prado, Fatima Lourdes E. Del, 2021. "Impact of extreme weather episodes on the Philippine banking sector – Evidence using branch-level supervisory data," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 2(1).
    54. Janet Gao & Shan Ge & Lawrence D. W. Schmidt & Cristina Tello-Trillo, 2023. "How Do Health Insurance Costs Affect Firm Labor Composition and Technology Investment?," Working Papers 23-47, Center for Economic Studies, U.S. Census Bureau.
    55. Pauline Avril & Gregory Levieuge & Camelia Turcu, 2023. "Do bankers want their umbrellas back when it rains? Evidence from typhoons in China," Working Papers 2023.08, International Network for Economic Research - INFER.
    56. Dmytro Holod & Joe Peek & Gökhan Torna, 2024. "Relationship Lending: That Ship Has Not Sailed for Community Banks," Working Papers 24-5, Federal Reserve Bank of Boston.
    57. Kristian S. Blickle & Evan Perry & João A. C. Santos, 2024. "Do Mortgage Lenders Respond to Flood Risk?," Staff Reports 1101, Federal Reserve Bank of New York.
    58. Celil, Hursit S. & Oh, Seungjoon & Selvam, Srinivasan, 2022. "Natural disasters and the role of regional lenders in economic recovery," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 116-132.
    59. Ge, Shan & Weisbach, Michael S., 2021. "The role of financial conditions in portfolio choices: The case of insurers," Journal of Financial Economics, Elsevier, vol. 142(2), pages 803-830.
    60. Sebastian Doerr & Thomas Drechsel & Donggyu Lee, 2021. "Income inequality, financial intermediation, and small firms," BIS Working Papers 944, Bank for International Settlements.
    61. Xu, Minhong & Xu, Yilan, 2023. "Do non-damaging earthquakes shake mortgage lenders' risk perception?," Journal of Environmental Economics and Management, Elsevier, vol. 117(C).
    62. Drechsel, Thomas & Doerr, Sebastian & Lee, Donggyu, 2022. "Income Inequality and Job Creation," CEPR Discussion Papers 17342, C.E.P.R. Discussion Papers.
    63. James Feigenbaum & James Lee & Filippo Mezzanotti, 2022. "Capital Destruction and Economic Growth: The Effects of Sherman's March, 1850–1920," American Economic Journal: Applied Economics, American Economic Association, vol. 14(4), pages 301-342, October.
    64. Kristle Romero Cortes & Yuliya Demyanyk & Lei Li & Elena Loutskina & Philip E. Strahan, 2018. "Stress Tests and Small Business Lending," Working Papers (Old Series) 1802, Federal Reserve Bank of Cleveland.
    65. Bos, Jaap W.B. & Li, Runliang & Sanders, Mark W.J.L., 2022. "Hazardous lending: The impact of natural disasters on bank asset portfolio," Economic Modelling, Elsevier, vol. 108(C).
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    68. Francisco Zabala Aguayo & Beata Ślusarczyk, 2020. "Risks of Banking Services’ Digitalization: The Practice of Diversification and Sustainable Development Goals," Sustainability, MDPI, vol. 12(10), pages 1-10, May.
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    84. Lee, Chien-Chiang & Wang, Chih-Wei & Thinh, Bui Tien & Xu, Zhi-Ting, 2022. "Climate risk and bank liquidity creation: International evidence," International Review of Financial Analysis, Elsevier, vol. 82(C).
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    89. Giovanni Calice & Yong Kyu Gam, 2023. "US National Banks and Local Economic Fragility," Journal of Financial Services Research, Springer;Western Finance Association, vol. 63(3), pages 313-338, June.
    90. Ghosh, Saibal, 2023. "Does climate legislation matter for bank lending? Evidence from MENA countries," Ecological Economics, Elsevier, vol. 212(C).
    91. Kong, Dongmin & Lin, Zhiyang & Wang, Yanan & Xiang, Junyi, 2021. "Natural disasters and analysts' earnings forecasts," Journal of Corporate Finance, Elsevier, vol. 66(C).
    92. Noth, Felix & Schüwer, Ulrich, 2018. "Natural disasters and bank stability: Evidence from the U.S. financial system," SAFE Working Paper Series 167, Leibniz Institute for Financial Research SAFE, revised 2018.
    93. Radoslav Raykov & Consuelo Silva-Buston, 2018. "Multibank Holding Companies and Bank Stability," Staff Working Papers 18-51, Bank of Canada.
    94. Shala, Iliriana & Schumacher, Benno, 2022. "The impact of natural disasters on banks' impairment flow: Evidence from Germany," Discussion Papers 36/2022, Deutsche Bundesbank.
    95. Bos, Jaap & Li, Runliang & Sanders, Mark, 2018. "Hazardous Lending: The Impact of Natural Disasters on Banks'Asset Portfolio," Research Memorandum 021, Maastricht University, Graduate School of Business and Economics (GSBE).
    96. Galina Hale, 2024. "Climate Disasters and Exchange Rates: Are Beliefs Keeping up with Climate Change?," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 72(1), pages 253-291, March.
    97. Kristian S. Blickle & Sarah Ngo Hamerling & Donald P. Morgan, 2021. "How Bad Are Weather Disasters for Banks?," Staff Reports 990, Federal Reserve Bank of New York.
    98. Robert Clark & Hui Wang & Victor Aguirregabiria, 2017. "The Geographic Flow Of Bank Funding And Access To Credit: Branch Networks And Local-market Competition," Working Paper 1402, Economics Department, Queen's University.
    99. Breckenfelder, Johannes & Maćkowiak, Bartosz & Marqués-Ibáñez, David & Olovsson, Conny & Popov, Alexander & Porcellacchia, Davide & Schepens, Glenn, 2023. "The climate and the economy," Working Paper Series 2793, European Central Bank.
    100. Le, Anh-Tuan & Tran, Thao Phuong & Mishra, Anil V., 2023. "Climate risk and bank stability: International evidence," Journal of Multinational Financial Management, Elsevier, vol. 70.
    101. Petkov, Ivan, 2015. "Small Business Lending and the Bank-Branch Network," MPRA Paper 85762, University Library of Munich, Germany, revised 13 Oct 2017.
    102. Ricardo Correa & Ai He & Christoph Herpfer & Ugur Lel, 2022. "The rising tide lifts some interest rates: climate change, natural disasters, and loan pricing," International Finance Discussion Papers 1345, Board of Governors of the Federal Reserve System (U.S.).
    103. Hu, Yichuan & Xue, Chang & Zhou, Xiaoyu, 2023. "Risk without strike: Nuclear crisis and corporate investment," European Economic Review, Elsevier, vol. 159(C).
    104. Littke, Helge C. N., 2018. "Channeling the Iron Ore Super-Cycle: The role of regional bank branch networks in emerging markets," IWH Discussion Papers 11/2018, Halle Institute for Economic Research (IWH).
    105. Vinzenz Peters & Jingtian Wang & Mark Sanders, 2023. "Resilience to extreme weather events and local financial structure of prefecture-level cities in China," Climatic Change, Springer, vol. 176(9), pages 1-21, September.
    106. Rehbein, Oliver, 2018. "Flooded through the back door: Firm-level effects of banks' lending shifts," IWH Discussion Papers 4/2018, Halle Institute for Economic Research (IWH).
    107. Olga Gorbachev & María José Luengo-Prado, 2019. "The Credit Card Debt Puzzle: The Role of Preferences, Credit Access Risk, and Financial Literacy," The Review of Economics and Statistics, MIT Press, vol. 101(2), pages 294-309, May.
    108. Tetsuji Okazaki & Toshihiro Okubo & Eric Strobl, 2021. "The Bright and Dark Side of Financial Support from Local and Central Banks after a Natural Disaster: Evidence from the Great Kanto Earthquake, 1923 Japan," CIGS Working Paper Series 21-001E, The Canon Institute for Global Studies.
    109. Hua, Renhai & Liu, Qingfu & Tse, Yiuman & Yu, Qin, 2023. "The impact of natural disaster risk on the return of agricultural futures," Journal of Asian Economics, Elsevier, vol. 87(C).
    110. OGURA Yoshiaki & NGUYEN Duc Giang & NGUYEN Thu Ha, 2022. "Floods and Loan Reallocation: New evidence," Discussion papers 22088, Research Institute of Economy, Trade and Industry (RIETI).
    111. Izadi, Mohammad & Saadi, Vahid, 2023. "Banking Market Structure and Trade Shocks," Journal of Banking & Finance, Elsevier, vol. 153(C).
    112. Sergio Mayordomo & Omar Rachedi, 2019. "The China syndrome affects banks: the credit supply channel of foreign import competition (Updated February 2020)," Working Papers 1908, Banco de España, revised Feb 2020.
    113. Pagnottoni, Paolo & Spelta, Alessandro & Flori, Andrea & Pammolli, Fabio, 2022. "Climate change and financial stability: Natural disaster impacts on global stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 599(C).
    114. Bos, Jaap & Li, Runliang, 2017. "Understanding the Trembles of Nature: How Do Disaster Experiences Shape Bank Risk Taking?," Research Memorandum 033, Maastricht University, Graduate School of Business and Economics (GSBE).
    115. Noth, Felix & Rehbein, Oliver, 2017. "Badly hurt? Natural disasters and direct firm effects," IWH Discussion Papers 25/2017, Halle Institute for Economic Research (IWH).
    116. MD Gyasuddin Ansari & Rudra Sensarma, 2023. "Monetary Policy, Liquidity Shock and Bank lending: The Case of Currency Demonetization in India," Working papers 575, Indian Institute of Management Kozhikode.
    117. Ivan T. Ivanov & Marco Macchiavelli & João A. C. Santos, 2022. "Bank lending networks and the propagation of natural disasters," Financial Management, Financial Management Association International, vol. 51(3), pages 903-927, September.
    118. Neville Francis & Laura E. Jackson & Michael T. Owyang, 2014. "How Has Empirical Monetary Policy Analysis Changed After the Financial Crisis?," Working Papers 2014-19, Federal Reserve Bank of St. Louis.
    119. Tho Pham & Oleksandr Talavera & Andriy Tsapin, 2021. "Shock contagion, asset quality and lending behaviour: The case of war in Eastern Ukraine," Kyklos, Wiley Blackwell, vol. 74(2), pages 243-269, May.
    120. Chabot, Miia & Bertrand, Jean-Louis, 2023. "Climate risks and financial stability: Evidence from the European financial system," Journal of Financial Stability, Elsevier, vol. 69(C).
    121. Alogoskoufis, Spyros & Dunz, Nepomuk & Emambakhsh, Tina & Hennig, Tristan & Kaijser, Michiel & Kouratzoglou, Charalampos & Muñoz, Manuel A. & Parisi, Laura & Salleo, Carmelo, 2021. "ECB’s economy-wide climate stress test," Occasional Paper Series 281, European Central Bank.
    122. Jose J. Canals-Cerda & Raluca Roman, 2021. "Climate Change and Consumer Finance: A Very Brief Literature Review," Consumer Finance Institute discussion papers 21-04, Federal Reserve Bank of Philadelphia.

  22. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2014. "No Arbitrage Priors, Drifting Volatilities, and the Term Structure of Interest Rates," CEPR Discussion Papers 9848, C.E.P.R. Discussion Papers.

    Cited by:

    1. Minchul Shin & Molin Zhong, 2015. "Does Realized Volatility Help Bond Yield Density Prediction?," Finance and Economics Discussion Series 2015-115, Board of Governors of the Federal Reserve System (U.S.).
    2. Huber, Florian & Krisztin, Tamás & Piribauer, Philipp, 2014. "Forecasting Global Equity Indices Using Large Bayesian VARs," Department of Economics Working Paper Series 184, WU Vienna University of Economics and Business.
    3. Andrea Renzetti, 2023. "Theory coherent shrinkage of Time-Varying Parameters in VARs," Papers 2311.11858, arXiv.org.
    4. Gregor Bäurle & Daniel Kaufmann, 2018. "Measuring Exchange Rate, Price, and Output Dynamics at the Effective Lower Bound," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 80(6), pages 1243-1266, December.

  23. Todd E. Clark & Michael W. McCracken, 2014. "Evaluating Conditional Forecasts from Vector Autoregressions," Working Papers (Old Series) 1413, Federal Reserve Bank of Cleveland.

    Cited by:

    1. Craig S. Hakkio & Jun Nie, 2014. "Implications of recent U.S. energy trends for trade forecasts," Economic Review, Federal Reserve Bank of Kansas City, issue Q IV, pages 29-51.
    2. Bańbura, Marta & Giannone, Domenico & Lenza, Michele, 2015. "Conditional forecasts and scenario analysis with vector autoregressions for large cross-sections," International Journal of Forecasting, Elsevier, vol. 31(3), pages 739-756.
    3. Mehmet Pasaogullari, 2015. "Forecasts from Reduced-form Models under the Zero-Lower-Bound Constraint," Working Papers (Old Series) 1512, Federal Reserve Bank of Cleveland.
    4. Boneva, Lena & Fawcett, Nicholas & Masolo, Riccardo M. & Waldron, Matt, 2019. "Forecasting the UK economy: Alternative forecasting methodologies and the role of off-model information," International Journal of Forecasting, Elsevier, vol. 35(1), pages 100-120.
    5. Berg Tim Oliver, 2017. "Forecast accuracy of a BVAR under alternative specifications of the zero lower bound," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(2), pages 1-29, April.
    6. Travis J. Berge & Andrew C. Chang & Nitish R. Sinha, 2019. "Evaluating the Conditionality of Judgmental Forecasts," Finance and Economics Discussion Series 2019-002, Board of Governors of the Federal Reserve System (U.S.).
    7. Sokol, Andrej, 2021. "Fan charts 2.0: flexible forecast distributions with expert judgement," Working Paper Series 2624, European Central Bank.
    8. Petrella, Ivan & Antolin-Diaz, Juan & Rubio-Ramírez, Juan Francisco, 2018. "Structural Scenario Analysis with SVARs," CEPR Discussion Papers 12579, C.E.P.R. Discussion Papers.
    9. Marcellino, Massimiliano & Aastveit, Knut Are & Carriero, Andrea & Clark, Todd, 2016. "Have Standard VARs Remained Stable Since the Crisis?," CEPR Discussion Papers 11558, C.E.P.R. Discussion Papers.
    10. Angelini, Elena & Lalik, Magdalena & Lenza, Michele & Paredes, Joan, 2019. "Mind the gap: A multi-country BVAR benchmark for the Eurosystem projections," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1658-1668.

  24. Knut Are Aastveit & Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2014. "Have standard VARs remained stable since the crisis?," Working Paper 2014/13, Norges Bank.

    Cited by:

    1. 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.
    2. Anastasios Evgenidis & Stephanos Papadamou, 2021. "The impact of unconventional monetary policy in the euro area. Structural and scenario analysis from a Bayesian VAR," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5684-5703, October.
    3. 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.
    4. Niko Hauzenberger & Florian Huber & Massimiliano Marcellino & Nico Petz, 2021. "Gaussian Process Vector Autoregressions and Macroeconomic Uncertainty," Papers 2112.01995, arXiv.org, revised Nov 2022.
    5. Edward S. Knotek & Saeed Zaman, 2017. "Financial Nowcasts and Their Usefulness in Macroeconomic Forecasting," Working Papers (Old Series) 1702, Federal Reserve Bank of Cleveland.
    6. Hacioglu Hoke, Sinem, 2019. "Macroeconomic effects of political risk shocks," Bank of England working papers 841, Bank of England.
    7. Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2019. "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Working Paper 2019/2, Norges Bank.
    8. Orkideh Gharehgozli & Sunhyung Lee, 2022. "Money Supply and Inflation after COVID-19," Economies, MDPI, vol. 10(5), pages 1-14, April.
    9. 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.
    10. Ganics, Gergely & Odendahl, Florens, 2021. "Bayesian VAR forecasts, survey information, and structural change in the euro area," International Journal of Forecasting, Elsevier, vol. 37(2), pages 971-999.
    11. Pfarrhofer, Michael, 2022. "Modeling tail risks of inflation using unobserved component quantile regressions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    12. Rachidi Kotchoni & Dalibor Stevanovic, 2020. "GDP Forecast Accuracy During Recessions," Working Papers 20-06, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
    13. Niko Hauzenberger, 2020. "Flexible Mixture Priors for Large Time-varying Parameter Models," Papers 2006.10088, arXiv.org, revised Nov 2020.
    14. Rachidi Kotchoni & Dalibor Stevanovic, 2016. "Forecasting U.S. Recessions and Economic Activity," Working Papers hal-04141569, HAL.
    15. Karlsson, Sune & Österholm, Pär, 2018. "A Note on the Stability of the Swedish Philips Curve," Working Papers 2018:6, Örebro University, School of Business.
    16. George Kapetanios & Massimiliano Marcellino & Fabrizio Venditti, 2017. "Large time-varying parameter VARs: a non-parametric approach," Temi di discussione (Economic working papers) 1122, Bank of Italy, Economic Research and International Relations Area.
    17. Jarociński, Marek & Bobeica, Elena, 2017. "Missing disinflation and missing inflation: the puzzles that aren't," Working Paper Series 2000, European Central Bank.
    18. Kavanagh, Ella & Zhu, Sheng & O’Sullivan, Niall, 2022. "Monetary policy, trade-offs and the transmission of UK Monetary Policy," Journal of Policy Modeling, Elsevier, vol. 44(6), pages 1128-1147.
    19. Heinrich, Markus, 2020. "Does the Current State of the Business Cycle matter for Real-Time Forecasting? A Mixed-Frequency Threshold VAR approach," EconStor Preprints 219312, ZBW - Leibniz Information Centre for Economics.
    20. Petrella, Ivan & Antolin-Diaz, Juan & Rubio-Ramírez, Juan Francisco, 2018. "Structural Scenario Analysis with SVARs," CEPR Discussion Papers 12579, C.E.P.R. Discussion Papers.
    21. Todd E. Clark & Michael W. McCracken, 2014. "Evaluating Conditional Forecasts from Vector Autoregressions," Working Papers 2014-25, Federal Reserve Bank of St. Louis.
    22. Aymeric Ortmans, 2020. "Evolving Monetary Policy in the Aftermath of the Great Recession," Documents de recherche 20-01, Centre d'Études des Politiques Économiques (EPEE), Université d'Evry Val d'Essonne.
    23. Arnaud Dufays & Zhuo Li & Jeroen V.K. Rombouts & Yong Song, 2021. "Sparse change‐point VAR models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(6), pages 703-727, September.
    24. Shang, Fei, 2022. "The effect of uncertainty on the sensitivity of the yield curve to monetary policy surprises," Journal of Economic Dynamics and Control, Elsevier, vol. 137(C).
    25. Pierre Guérin & Danilo Leiva-Leon & Massimiliano Marcellino, 2017. "Markov-switching three-pass regression filter," Working Papers 1748, Banco de España.
    26. Conti, Antonio M. & Nobili, Andrea & Signoretti, Federico M., 2023. "Bank capital requirement shocks: A narrative perspective," European Economic Review, Elsevier, vol. 151(C).
    27. Bjarni G. Einarsson, 2024. "Online Monitoring of Policy Optimality," Economics wp95, Department of Economics, Central bank of Iceland.
    28. Martin Feldkircher & Nico Hauzenberger, 2019. "How useful are time-varying parameter models for forecasting economic growth in CESEE?," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue Q1/19, pages 29-48.
    29. Conti, Antonio M., 2021. "Resurrecting the Phillips Curve in Low-Inflation Times," Economic Modelling, Elsevier, vol. 96(C), pages 172-195.
    30. Legrand, Romain, 2018. "Time-Varying Vector Autoregressions: Efficient Estimation, Random Inertia and Random Mean," MPRA Paper 88925, University Library of Munich, Germany.
    31. Karlsson, Sune & Österholm, Pär, 2019. "Volatilities, drifts and the relation between treasury yields and the corporate bond yield spread in australia," Finance Research Letters, Elsevier, vol. 30(C), pages 378-384.
    32. Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
    33. Edvinsson, Rodney & Karlsson, Sune & Österholm, Pär, 2023. "Does Money Growth Predict Inflation? Evidence from Vector Autoregressions Using Four Centuries of Data," Working Papers 2023:3, Örebro University, School of Business.
    34. Markus Heinrich & Magnus Reif, 2020. "Real-Time Forecasting Using Mixed-Frequency VARS with Time-Varying Parameters," CESifo Working Paper Series 8054, CESifo.
    35. Benjamin Garcia & Arsenios Skaperdas, 2017. "Inferring the Shadow Rate from Real Activity," Finance and Economics Discussion Series 2017-106, Board of Governors of the Federal Reserve System (U.S.).
    36. Neville Francis & Laura E. Jackson & Michael T. Owyang, 2014. "How Has Empirical Monetary Policy Analysis Changed After the Financial Crisis?," Working Papers 2014-19, Federal Reserve Bank of St. Louis.

  25. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2013. "Real-Time Nowcasting with a Bayesian Mixed Frequency Model with Stochastic Volatility," CEPR Discussion Papers 9312, C.E.P.R. Discussion Papers.

    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. Foroni, Claudia & Guérin, Pierre & Marcellino, Massimiliano, 2018. "Using low frequency information for predicting high frequency variables," International Journal of Forecasting, Elsevier, vol. 34(4), pages 774-787.
    5. Kenichiro McAlinn, 2021. "Mixed‐frequency Bayesian predictive synthesis for economic nowcasting," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(5), pages 1143-1163, November.
    6. Berg, Tim O. & Henzel, Steffen R., 2015. "Point and density forecasts for the euro area using Bayesian VARs," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1067-1095.
    7. Matteo Mogliani & Anna Simoni, 2024. "Bayesian Bi-level Sparse Group Regressions for Macroeconomic Forecasting," Papers 2404.02671, arXiv.org.
    8. 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.
    9. Edward S. Knotek & Saeed Zaman, 2014. "Nowcasting U.S. Headline and Core Inflation," Working Papers (Old Series) 1403, Federal Reserve Bank of Cleveland.
    10. Pettenuzzo, Davide & Timmermann, Allan & Valkanov, Rossen, 2016. "A MIDAS approach to modeling first and second moment dynamics," Journal of Econometrics, Elsevier, vol. 193(2), pages 315-334.
    11. Galvao, Ana Beatriz & Owyang, Michael, 2020. "Forecasting Low Frequency Macroeconomic Events with High Frequency Data," EMF Research Papers 38, Economic Modelling and Forecasting Group.
    12. Hassani, Hossein & Rua, António & Silva, Emmanuel Sirimal & Thomakos, Dimitrios, 2019. "Monthly forecasting of GDP with mixed-frequency multivariate singular spectrum analysis," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1263-1272.
    13. Marcellino, Massimiliano & Foroni, Claudia & Stevanovic, Dalibor, 2020. "Forecasting the Covid-19 recession and recovery: Lessons from the financial crisis," CEPR Discussion Papers 15114, C.E.P.R. Discussion Papers.
    14. Martin Feldkircher & Florian Huber & Michael Pfarrhofer, 2021. "Measuring the effectiveness of US monetary policy during the COVID‐19 recession," Scottish Journal of Political Economy, Scottish Economic Society, vol. 68(3), pages 287-297, July.
    15. Bec, Frédérique & Mogliani, Matteo, 2015. "Nowcasting French GDP in real-time with surveys and “blocked” regressions: Combining forecasts or pooling information?," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1021-1042.
    16. Kiss, Tamás & Mazur, Stepan & Nguyen, Hoang & Österholm, Pär, 2021. "Modelling the Relation between the US Real Economy and the Corporate Bond-Yield Spread in Bayesian VARs with non-Gaussian Disturbances," Working Papers 2021:9, Örebro University, School of Business.
    17. Mogliani, Matteo & Darné, Olivier & Pluyaud, Bertrand, 2017. "The new MIBA model: Real-time nowcasting of French GDP using the Banque de France's monthly business survey," Economic Modelling, Elsevier, vol. 64(C), pages 26-39.
    18. Rusnák, Marek, 2016. "Nowcasting Czech GDP in real time," Economic Modelling, Elsevier, vol. 54(C), pages 26-39.
    19. 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.
    20. Marcellino, Massimiliano & Clark, Todd & Carriero, Andrea, 2021. "Nowcasting Tail Risk to Economic Activity at a Weekly Frequency," CEPR Discussion Papers 16496, C.E.P.R. Discussion Papers.
    21. Knut Are Aastveit & Tuva Marie Fastbø & Eleonora Granziera & Kenneth Sæterhagen Paulsen & Kjersti Næss Torstensen, 2020. "Nowcasting Norwegian household consumption with debit card transaction data," Working Paper 2020/17, Norges Bank.
    22. Luiz Renato Lima & Lucas Lúcio Godeiro & Mohammed Mohsin, 2021. "Time-Varying Dictionary and the Predictive Power of FED Minutes," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 149-181, January.
    23. Bańbura, Marta & Giannone, Domenico & Modugno, Michele & Reichlin, Lucrezia, 2013. "Now-Casting and the Real-Time Data Flow," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 195-237, Elsevier.
    24. A. Girardi & R. Golinelli & C. Pappalardo, 2014. "The Role of Indicator Selection in Nowcasting Euro Area GDP in Pseudo Real Time," Working Papers wp919, Dipartimento Scienze Economiche, Universita' di Bologna.
    25. Foroni, Claudia & Ravazzolo, Francesco & Rossini, Luca, 2023. "Are low frequency macroeconomic variables important for high frequency electricity prices?," Economic Modelling, Elsevier, vol. 120(C).
    26. Matteo Mogliani & Anna Simoni, 2020. "Bayesian MIDAS penalized regressions: Estimation, selection, and prediction," Post-Print hal-03089878, HAL.
    27. Michael W. McCracken & Michael T. Owyang & Tatevik Sekhposyan, 2021. "Real-Time Forecasting and Scenario Analysis Using a Large Mixed-Frequency Bayesian VAR," International Journal of Central Banking, International Journal of Central Banking, vol. 17(71), pages 1-41, December.
    28. Fabian Krüger & Todd E. Clark & Francesco Ravazzolo, 2017. "Using Entropic Tilting to Combine BVAR Forecasts With External Nowcasts," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(3), pages 470-485, July.
    29. Carriero, Andrea & Mumtaz, Haroon & Theophilopoulou, Angeliki, 2015. "Macroeconomic information, structural change, and the prediction of fiscal aggregates," International Journal of Forecasting, Elsevier, vol. 31(2), pages 325-348.
    30. David Kohns & Arnab Bhattacharjee, 2020. "Nowcasting Growth using Google Trends Data: A Bayesian Structural Time Series Model," Papers 2011.00938, arXiv.org, revised May 2022.
    31. David Kohns & Arnab Bhattacharjee, 2019. "Interpreting Big Data in the Macro Economy: A Bayesian Mixed Frequency Estimator," CEERP Working Paper Series 010, Centre for Energy Economics Research and Policy, Heriot-Watt University.
    32. Edward S. Knotek & Saeed Zaman, 2020. "Real-Time Density Nowcasts of US Inflation: A Model-Combination Approach," Working Papers 20-31, Federal Reserve Bank of Cleveland.
    33. Antonello D’Agostino & Jacopo Cimadomo, 2015. "Combining time-variation and mixed-frequencies: an analysis of government spending multipliers in Italy," Working Papers 7, European Stability Mechanism.
    34. Jos Jansen, W. & Jin, Xiaowen & Winter, Jasper M. de, 2016. "Forecasting and nowcasting real GDP: Comparing statistical models and subjective forecasts," Munich Reprints in Economics 43488, University of Munich, Department of Economics.
    35. Lenza, Michele & Cimadomo, Jacopo & Giannone, Domenico & Monti, Francesca & Sokol, Andrej, 2021. "Nowcasting with Large Bayesian Vector Autoregressions," CEPR Discussion Papers 15854, C.E.P.R. Discussion Papers.
    36. Heinrich, Markus, 2020. "Does the Current State of the Business Cycle matter for Real-Time Forecasting? A Mixed-Frequency Threshold VAR approach," EconStor Preprints 219312, ZBW - Leibniz Information Centre for Economics.
    37. Boriss Siliverstovs, 2021. "New York FED Staff Nowcasts and Reality: What Can We Learn about the Future, the Present, and the Past?," Econometrics, MDPI, vol. 9(1), pages 1-25, March.
    38. Foroni, Claudia & Ravazzolo, Francesco & Rossini, Luca, 2019. "Forecasting daily electricity prices with monthly macroeconomic variables," Working Paper Series 2250, European Central Bank.
    39. George Kapetanios & Fotis Papailias, 2018. "Big Data & Macroeconomic Nowcasting: Methodological Review," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2018-12, Economic Statistics Centre of Excellence (ESCoE).
    40. Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87.
    41. Deborah Gefang & Gary Koop & Aubrey Poon, 2020. "Computationally Efficient Inference in Large Bayesian Mixed Frequency VARs," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2020-07, Economic Statistics Centre of Excellence (ESCoE).
    42. Knut Are Aastveit & Claudia Foroni & Francesco Ravazzolo, 2017. "Density Forecasts With Midas Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(4), pages 783-801, June.
    43. Marcellino, Massimiliano & Foroni, Claudia, 2014. "Markov-Switching Mixed-Frequency VAR Models," CEPR Discussion Papers 9815, C.E.P.R. Discussion Papers.
    44. Robert M. Kunst & Martin Wagner, 2020. "Economic forecasting: editors’ introduction," Empirical Economics, Springer, vol. 58(1), pages 1-5, January.
    45. Knut Are Aastveit & Francesco Ravazzolo & Herman K. van Dijk, 2018. "Combined Density Nowcasting in an Uncertain Economic Environment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 131-145, January.
    46. Kohns, David & Bhattacharjee, Arnab, 2023. "Nowcasting growth using Google Trends data: A Bayesian Structural Time Series model," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1384-1412.
    47. Soybilgen, Barış & Yazgan, Ege, 2018. "Evaluating nowcasts of bridge equations with advanced combination schemes for the Turkish unemployment rate," Economic Modelling, Elsevier, vol. 72(C), pages 99-108.
    48. Cem Cakmakli & Hamza Demircan, 2020. "Using Survey Information for Improving the Density Nowcasting of US GDP with a Focus on Predictive Performance during Covid-19 Pandemic," Koç University-TUSIAD Economic Research Forum Working Papers 2016, Koc University-TUSIAD Economic Research Forum.
    49. Boriss Siliverstovs, 2020. "Assessing nowcast accuracy of US GDP growth in real time: the role of booms and busts," Empirical Economics, Springer, vol. 58(1), pages 7-27, January.
    50. Ankargren Sebastian & Unosson Måns & Yang Yukai, 2020. "A Flexible Mixed-Frequency Vector Autoregression with a Steady-State Prior," Journal of Time Series Econometrics, De Gruyter, vol. 12(2), pages 1-41, July.
    51. Todd E. Clark & Florian Huber & Gary Koop & Massimiliano Marcellino & Michael Pfarrhofer, 2023. "Tail Forecasting With Multivariate Bayesian Additive Regression Trees," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 64(3), pages 979-1022, August.
    52. Sebastian Ankargren & Paulina Jon'eus, 2019. "Estimating Large Mixed-Frequency Bayesian VAR Models," Papers 1912.02231, arXiv.org.
    53. Richard Schnorrenberger & Aishameriane Schmidt & Guilherme Valle Moura, 2024. "Harnessing Machine Learning for Real-Time Inflation Nowcasting," Working Papers 806, DNB.
    54. George Athanasopoulos & Puwasala Gamakumara & Anastasios Panagiotelis & Rob J Hyndman & Mohamed Affan, 2019. "Hierarchical Forecasting," Monash Econometrics and Business Statistics Working Papers 2/19, Monash University, Department of Econometrics and Business Statistics.
    55. Garciga, Christian & Knotek II, Edward S., 2019. "Forecasting GDP growth with NIPA aggregates: In search of core GDP," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1814-1828.
    56. Boriss Siliverstovs, 2021. "Gauging the Effect of Influential Observations on Measures of Relative Forecast Accuracy in a Post-COVID-19 Era: Application to Nowcasting Euro Area GDP Growth," Working Papers 2021/01, Latvijas Banka.
    57. Gary Koop & Stuart McIntyre & James Mitchell, 2020. "UK regional nowcasting using a mixed frequency vector auto‐regressive model with entropic tilting," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(1), pages 91-119, January.
    58. Shrub, Yuliya & Rieger, Jonas & Müller, Henrik & Jentsch, Carsten, 2022. "Text data rule - don't they? A study on the (additional) information of Handelsblatt data for nowcasting German GDP in comparison to established economic indicators," Ruhr Economic Papers 964, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    59. Kohns, David & Potjagailo, Galina, 2023. "Flexible Bayesian MIDAS: time‑variation, group‑shrinkage and sparsity," Bank of England working papers 1025, Bank of England.
    60. González-Astudillo, Manuel & Baquero, Daniel, 2019. "A nowcasting model for Ecuador: Implementing a time-varying mean output growth," Economic Modelling, Elsevier, vol. 82(C), pages 250-263.
    61. Markus Heinrich & Magnus Reif, 2020. "Real-Time Forecasting Using Mixed-Frequency VARS with Time-Varying Parameters," CESifo Working Paper Series 8054, CESifo.
    62. Dario Caldara & Chiara Scotti & Molin Zhong, 2021. "Macroeconomic and Financial Risks: A Tale of Mean and Volatility," International Finance Discussion Papers 1326, Board of Governors of the Federal Reserve System (U.S.).

  26. Todd E. Clark & Michael W. McCracken, 2013. "Evaluating the accuracy of forecasts from vector autoregressions," Working Papers 2013-010, Federal Reserve Bank of St. Louis.

    Cited by:

    1. Pincheira, Pablo M. & West, Kenneth D., 2016. "A comparison of some out-of-sample tests of predictability in iterated multi-step-ahead forecasts," Research in Economics, Elsevier, vol. 70(2), pages 304-319.
    2. Coble, David & Pincheira, Pablo, 2017. "Nowcasting Building Permits with Google Trends," MPRA Paper 76514, University Library of Munich, Germany.
    3. Nicholson, William B. & Matteson, David S. & Bien, Jacob, 2017. "VARX-L: Structured regularization for large vector autoregressions with exogenous variables," International Journal of Forecasting, Elsevier, vol. 33(3), pages 627-651.
    4. Pincheira-Brown, Pablo & Selaive, Jorge & Nolazco, Jose Luis, 2019. "Forecasting inflation in Latin America with core measures," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1060-1071.
    5. Francisco Lasso-Valderrama & Héctor M. Zárate-Solano, 2019. "Forecasting the Colombian Unemployment Rate Using Labour Force Flows," Borradores de Economia 1073, Banco de la Republica de Colombia.
    6. 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. Mihaela Simionescu, 2015. "The Improvement of Unemployment Rate Predictions Accuracy," Prague Economic Papers, Prague University of Economics and Business, vol. 2015(3), pages 274-286.

  27. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2012. "Common Drifting Volatility in Large Bayesian VARs," CEPR Discussion Papers 8894, 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. Mike Tsionas & Marwan Izzeldin & Lorenzo Trapani, 2019. "Bayesian estimation of large dimensional time varying VARs using copulas," Papers 1912.12527, arXiv.org.
    3. Jonas Dovern & Martin Feldkircher & Florian Huber, 2015. "Does Joint Modelling of the World Economy Pay Off? Evaluating Global Forecasts from a Bayesian GVAR," Working Papers 200, Oesterreichische Nationalbank (Austrian Central Bank).
    4. Mumtaz, Haroon & Theodoridis, Konstantinos, 2017. "Common and country specific economic uncertainty," Journal of International Economics, Elsevier, vol. 105(C), pages 205-216.
    5. Valentina Aprigliano & Alessandro Borin & Francesco Paolo Conteduca & Simone Emiliozzi & Marco Flaccadoro & Sabina Marchetti & Stefania Villa, 2021. "Forecasting Italian GDP growth with epidemiological data," Questioni di Economia e Finanza (Occasional Papers) 664, Bank of Italy, Economic Research and International Relations Area.
    6. Huber, Florian, 2016. "Density forecasting using Bayesian global vector autoregressions with stochastic volatility," International Journal of Forecasting, Elsevier, vol. 32(3), pages 818-837.
    7. 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.
    8. Ching-Wai Chiu & Haroon Mumtaz & Gabor Pinter, 2016. "VAR Models with Non-Gaussian Shocks," Discussion Papers 1609, Centre for Macroeconomics (CFM).
    9. MeiChi Huang, 2022. "Time‐varying impacts of expectations on housing markets across hot and cold phases," International Finance, Wiley Blackwell, vol. 25(2), pages 249-265, August.
    10. Berg, Tim O. & Henzel, Steffen R., 2015. "Point and density forecasts for the euro area using Bayesian VARs," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1067-1095.
    11. Joshua C. C. Chan & Gary Koop & Xuewen Yu, 2024. "Large Order-Invariant Bayesian VARs with Stochastic Volatility," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(2), pages 825-837, April.
    12. Gary Koop & Stuart McIntyre & James Mitchell, 2018. "UK Regional Nowcasting using a Mixed Frequency Vector Autoregressive Model," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2018-07, Economic Statistics Centre of Excellence (ESCoE).
    13. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2020. "Capturing Macroeconomic Tail Risks with Bayesian Vector Autoregressions," Working Papers 20-02R, Federal Reserve Bank of Cleveland, revised 22 Sep 2020.
    14. Joshua C. C. Chan & Xuewen Yu, 2022. "Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility," Papers 2206.08438, arXiv.org.
    15. Hardik A. Marfatia & Qiang Ji & Jiawen Luo, 2022. "Forecasting the volatility of agricultural commodity futures: The role of co‐volatility and oil volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 383-404, March.
    16. Gefang, Deborah & Koop, Gary & Poon, Aubrey, 2023. "Forecasting using variational Bayesian inference in large vector autoregressions with hierarchical shrinkage," International Journal of Forecasting, Elsevier, vol. 39(1), pages 346-363.
    17. Uribe Jorge M. & Chuliá Helena, 2023. "Expected, unexpected, good and bad aggregate uncertainty," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(2), pages 265-284, April.
    18. Jan Philipp Fritsche & Mathias Klein & Malte Rieth, 2020. "Government Spending Multipliers in (Un)certain Times," Discussion Papers of DIW Berlin 1901, DIW Berlin, German Institute for Economic Research.
    19. Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2023. "Large Time‐Varying Volatility Models for Hourly Electricity Prices," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 545-573, June.
    20. 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.
    21. Koop, Gary & Korobilis, Dimitris & Pettenuzzo, Davide, 2019. "Bayesian compressed vector autoregressions," Journal of Econometrics, Elsevier, vol. 210(1), pages 135-154.
    22. Scott Brave & R. Andrew Butters & Alejandro Justiniano, 2016. "Forecasting Economic Activity with Mixed Frequency Bayesian VARs," Working Paper Series WP-2016-5, Federal Reserve Bank of Chicago.
    23. Deborah Gefang & Gary Koop & Aubrey Poon, 2019. "Variational Bayesian inference in large Vector Autoregressions with hierarchical shrinkage," CAMA Working Papers 2019-08, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    24. Bańbura, Marta & Giannone, Domenico & Lenza, Michele, 2015. "Conditional forecasts and scenario analysis with vector autoregressions for large cross-sections," International Journal of Forecasting, Elsevier, vol. 31(3), pages 739-756.
    25. Pettenuzzo, Davide & Timmermann, Allan & Valkanov, Rossen, 2016. "A MIDAS approach to modeling first and second moment dynamics," Journal of Econometrics, Elsevier, vol. 193(2), pages 315-334.
    26. Kyle Jurado & Sydney C. Ludvigson & Serena Ng, 2015. "Measuring Uncertainty," American Economic Review, American Economic Association, vol. 105(3), pages 1177-1216, March.
    27. Cross, Jamie L. & Hou, Chenghan & Koop, Gary & Poon, Aubrey, 2023. "Large stochastic volatility in mean VARs," Journal of Econometrics, Elsevier, vol. 236(1).
    28. Martin Feldkircher & Florian Huber & Michael Pfarrhofer, 2021. "Measuring the effectiveness of US monetary policy during the COVID‐19 recession," Scottish Journal of Political Economy, Scottish Economic Society, vol. 68(3), pages 287-297, July.
    29. Michael Pfarrhofer, 2024. "Forecasts with Bayesian vector autoregressions under real time conditions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(3), pages 771-801, April.
    30. Piergiorgio Alessandri & Haroon Mumtaz, 2014. "Financial regimes and uncertainty shocks," BCAM Working Papers 1404, Birkbeck Centre for Applied Macroeconomics.
    31. Tsionas, Mike G. & Izzeldin, Marwan & Trapani, Lorenzo, 2022. "Estimation of large dimensional time varying VARs using copulas," European Economic Review, Elsevier, vol. 141(C).
    32. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2012. "Real-time nowcasting with a Bayesian mixed frequency model with stochastic volatility," Working Papers (Old Series) 1227, Federal Reserve Bank of Cleveland.
    33. Koop, Gary & Korobilis, Dimitris, 2012. "Large time-varying parameter VARs," MPRA Paper 38591, University Library of Munich, Germany.
    34. Simon Beyeler, 2019. "Streamlining Time-varying VAR with a Factor Structure in the Parameters," Working Papers 19.03, Swiss National Bank, Study Center Gerzensee.
    35. Valeriu Nalban & Andra Smadu, 2020. "Financial disruptions and heightened uncertainty: a case for timely policy action," Working Papers 687, DNB.
    36. Michele Lenza & Giorgio E. Primiceri, 2020. "How to Estimate a VAR after March 2020," NBER Working Papers 27771, National Bureau of Economic Research, Inc.
    37. Brave, Scott A. & Butters, R. Andrew & Justiniano, Alejandro, 2019. "Forecasting economic activity with mixed frequency BVARs," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1692-1707.
    38. Nalban, Valeriu & Smădu, Andra, 2021. "Asymmetric effects of uncertainty shocks: Normal times and financial disruptions are different," Journal of Macroeconomics, Elsevier, vol. 69(C).
    39. 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.
    40. Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano, 2021. "Using time-varying volatility for identification in Vector Autoregressions: An application to endogenous uncertainty," Journal of Econometrics, Elsevier, vol. 225(1), pages 47-73.
    41. Chan, Joshua C.C. & Eisenstat, Eric & Strachan, Rodney W., 2020. "Reducing the state space dimension in a large TVP-VAR," Journal of Econometrics, Elsevier, vol. 218(1), pages 105-118.
    42. Knüppel, Malte & Krüger, Fabian, 2017. "Forecast Uncertainty, Disagreement, and Linear Pools of Density Forecasts," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168294, Verein für Socialpolitik / German Economic Association.
    43. Follett, Lendie & Yu, Cindy, 2019. "Achieving parsimony in Bayesian vector autoregressions with the horseshoe prior," Econometrics and Statistics, Elsevier, vol. 11(C), pages 130-144.
    44. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2016. "Large Vector Autoregressions with Stochastic Volatility and Flexible Priors," Working Papers (Old Series) 1617, Federal Reserve Bank of Cleveland.
    45. Gael M. Martin & David T. Frazier & Worapree Maneesoonthorn & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2022. "Bayesian Forecasting in Economics and Finance: A Modern Review," Papers 2212.03471, arXiv.org, revised Jul 2023.
    46. Carriero, Andrea & Mumtaz, Haroon & Theophilopoulou, Angeliki, 2015. "Macroeconomic information, structural change, and the prediction of fiscal aggregates," International Journal of Forecasting, Elsevier, vol. 31(2), pages 325-348.
    47. Gael M. Martin & David T. Frazier & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2023. "Bayesian Forecasting in the 21st Century: A Modern Review," Monash Econometrics and Business Statistics Working Papers 1/23, Monash University, Department of Econometrics and Business Statistics.
    48. 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.
    49. Lenza, Michele & Moutachaker, Inès & Paredes, Joan, 2023. "Density forecasts of inflation: a quantile regression forest approach," Working Paper Series 2830, European Central Bank.
    50. Huber, Florian & Krisztin, Tamás & Piribauer, Philipp, 2014. "Forecasting Global Equity Indices Using Large Bayesian VARs," Department of Economics Working Paper Series 184, WU Vienna University of Economics and Business.
    51. Jamie L. Cross & Aubrey Poon, 2020. "On the contribution of international shocks in Australian business cycle fluctuations," Empirical Economics, Springer, vol. 59(6), pages 2613-2637, December.
    52. Francisco Serranito & Nicolas Himounet & Julien Vauday, 2023. "Uncertainty is bad for Business. Really?," Working Papers hal-04219283, HAL.
    53. Joshua C.C. Chan & Rodney W. Strachan, 2023. "Bayesian State Space Models In Macroeconometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 58-75, February.
    54. Joshua C. C. Chan, 2022. "Asymmetric conjugate priors for large Bayesian VARs," Quantitative Economics, Econometric Society, vol. 13(3), pages 1145-1169, July.
    55. Paul Labonne, 2022. "Asymmetric Uncertainty: Nowcasting Using Skewness in Real-time Data," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2022-23, Economic Statistics Centre of Excellence (ESCoE).
    56. Matteo Iacopini & Francesco Ravazzolo & Luca Rossini, 2022. "Bayesian Multivariate Quantile Regression with alternative Time-varying Volatility Specifications," Papers 2211.16121, arXiv.org.
    57. Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2020. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," The Review of Economics and Statistics, MIT Press, vol. 102(1), pages 17-33, March.
    58. Joshua C. C. Chan, 2022. "Comparing Stochastic Volatility Specifications for Large Bayesian VARs," Papers 2208.13255, arXiv.org.
    59. Dovern, Jonas & Feldkircher, Martin & Huber, Florian, 2015. "Does Joint Modelling of the World Economy Pay Off? Evaluating Multivariate Forecasts from a Bayesian GVAR," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112999, Verein für Socialpolitik / German Economic Association.
    60. Gregor Kastner, 2016. "Sparse Bayesian time-varying covariance estimation in many dimensions," Papers 1608.08468, arXiv.org, revised Nov 2017.
    61. Sebastian Ankargren & Paulina Jon'eus, 2019. "Simulation smoothing for nowcasting with large mixed-frequency VARs," Papers 1907.01075, arXiv.org.
    62. Chuliá, Helena & Guillén, Montserrat & Uribe, Jorge M., 2017. "Measuring uncertainty in the stock market," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 18-33.
    63. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2014. "No Arbitrage Priors, Drifting Volatilities, and the Term Structure of Interest Rates," CEPR Discussion Papers 9848, C.E.P.R. Discussion Papers.
    64. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2015. "Large Vector Autoregressions with Asymmetric Priors," Working Papers 759, Queen Mary University of London, School of Economics and Finance.
    65. Florian Huber, 2014. "Density Forecasting using Bayesian Global Vector Autoregressions with Common Stochastic Volatility," Department of Economics Working Papers wuwp179, Vienna University of Economics and Business, Department of Economics.
    66. Zhang, Bo & Nguyen, Bao H., 2020. "Real-time forecasting of the Australian macroeconomy using Bayesian VARs," Working Papers 2020-12, University of Tasmania, Tasmanian School of Business and Economics.
    67. Lenza, Michele & Cimadomo, Jacopo & Giannone, Domenico & Monti, Francesca & Sokol, Andrej, 2021. "Nowcasting with Large Bayesian Vector Autoregressions," CEPR Discussion Papers 15854, C.E.P.R. Discussion Papers.
    68. Heinrich, Markus, 2020. "Does the Current State of the Business Cycle matter for Real-Time Forecasting? A Mixed-Frequency Threshold VAR approach," EconStor Preprints 219312, ZBW - Leibniz Information Centre for Economics.
    69. Chenghan Hou & Bao Nguyen & Bo Zhang, 2023. "Real‐time forecasting of the Australian macroeconomy using flexible Bayesian VARs," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 418-451, March.
    70. Haroon Mumtaz & Laura Sunder-Plassmann & Angeliki Theophilopoulou, 2016. "The State Level Impact of Uncertainty Shocks," Working Papers 793, Queen Mary University of London, School of Economics and Finance.
    71. Bognanni, Mark & Zito, John, 2020. "Sequential Bayesian inference for vector autoregressions with stochastic volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    72. Irina Zviadadze, 2014. "Term-structure of consumption risk premia in the cross-section of currency returns," 2014 Meeting Papers 1075, Society for Economic Dynamics.
    73. Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2020. "Large Time-Varying Volatility Models for Electricity Prices," Working Papers No 05/2020, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    74. Florian Huber & Gary Koop, 2023. "Fast and Order-invariant Inference in Bayesian VARs with Non-Parametric Shocks," Papers 2305.16827, arXiv.org.
    75. Chauvet, Marcelle & Potter, Simon, 2013. "Forecasting Output," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 141-194, Elsevier.
    76. Chan, Joshua C.C. & Poon, Aubrey & Zhu, Dan, 2023. "High-dimensional conditionally Gaussian state space models with missing data," Journal of Econometrics, Elsevier, vol. 236(1).
    77. Jonas E. Arias & Juan F. Rubio-Ramirez & Minchul Shin, 2021. "Macroeconomic Forecasting and Variable Ordering in Multivariate Stochastic Volatility Models," Working Papers 21-21, Federal Reserve Bank of Philadelphia.
    78. Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87.
    79. Dimitrios P. Louzis, 2019. "Steady‐state modeling and macroeconomic forecasting quality," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(2), pages 285-314, March.
    80. Joshua C.C. Chan & Eric Eisenstat & Rodney W. Strachan, 2018. "Reducing dimensions in a large TVP-VAR," CAMA Working Papers 2018-49, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    81. Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano, 2019. "Large Bayesian vector autoregressions with stochastic volatility and non-conjugate priors," Journal of Econometrics, Elsevier, vol. 212(1), pages 137-154.
    82. Nicolas Himounet, 2021. "Searching for the Nature of Uncertainty: Macroeconomic VS Financial," Working Papers 2021.05, International Network for Economic Research - INFER.
    83. Jan Prüser & Florian Huber, 2024. "Nonlinearities in macroeconomic tail risk through the lens of big data quantile regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(2), pages 269-291, March.
    84. Andrea Carriero & Francesco Corsello & Massimiliano Marcellino, 2020. "The economic drivers of volatility and uncertainty," Temi di discussione (Economic working papers) 1285, Bank of Italy, Economic Research and International Relations Area.
    85. Ankargren Sebastian & Unosson Måns & Yang Yukai, 2020. "A Flexible Mixed-Frequency Vector Autoregression with a Steady-State Prior," Journal of Time Series Econometrics, De Gruyter, vol. 12(2), pages 1-41, July.
    86. Todd E. Clark & Florian Huber & Gary Koop & Massimiliano Marcellino & Michael Pfarrhofer, 2023. "Tail Forecasting With Multivariate Bayesian Additive Regression Trees," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 64(3), pages 979-1022, August.
    87. Gregor Kastner & Florian Huber, 2017. "Sparse Bayesian vector autoregressions in huge dimensions," Papers 1704.03239, arXiv.org, revised Dec 2019.
    88. Prüser, Jan & Blagov, Boris, 2022. "Improving inference and forecasting in VAR models using cross-sectional information," Ruhr Economic Papers 960, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    89. Oguzhan Cepni & I. Ethem Guney & Norman R. Swanson, 2020. "Forecasting and nowcasting emerging market GDP growth rates: The role of latent global economic policy uncertainty and macroeconomic data surprise factors," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(1), pages 18-36, January.
    90. Jiawen Luo & Langnan Chen, 2019. "Multivariate realized volatility forecasts of agricultural commodity futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(12), pages 1565-1586, December.
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    93. Ellington, Michael, 2022. "Fat tails, serial dependence, and implied volatility index connections," European Journal of Operational Research, Elsevier, vol. 299(2), pages 768-779.
    94. Thore Schlaak & Malte Rieth & Maximilian Podstawski, 2018. "Monetary Policy, External Instruments and Heteroskedasticity," Discussion Papers of DIW Berlin 1749, DIW Berlin, German Institute for Economic Research.
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    99. Sebastian Ankargren & Paulina Jon'eus, 2019. "Estimating Large Mixed-Frequency Bayesian VAR Models," Papers 1912.02231, arXiv.org.
    100. Joshua C. C. Chan, 2019. "Large Bayesian vector autoregressions," CAMA Working Papers 2019-19, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
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    111. Hadjiantoni, Stella & Kontoghiorghes, Erricos John, 2022. "An alternative numerical method for estimating large-scale time-varying parameter seemingly unrelated regressions models," Econometrics and Statistics, Elsevier, vol. 21(C), pages 1-18.
    112. Gary Koop & Stuart McIntyre & James Mitchell, 2020. "UK regional nowcasting using a mixed frequency vector auto‐regressive model with entropic tilting," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(1), pages 91-119, January.
    113. Jamie L. Cross & Chenghan Hou & Aubrey Poon, 2018. "International Transmission of Macroeconomic Uncertainty in Small Open Economies: An Empirical Approach," Working Papers No 12/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    114. Mark Bognanni & John Zito, 2019. "Sequential Bayesian Inference for Vector Autoregressions with Stochastic Volatility," Working Papers 19-29, Federal Reserve Bank of Cleveland.
    115. Danilo Cascaldi-Garcia, 2022. "Pandemic Priors," International Finance Discussion Papers 1352, Board of Governors of the Federal Reserve System (U.S.).
    116. David L. Reifschneider & Peter Tulip, 2017. "Gauging the Uncertainty of the Economic Outlook Using Historical Forecasting Errors : The Federal Reserve's Approach," Finance and Economics Discussion Series 2017-020, Board of Governors of the Federal Reserve System (U.S.).
    117. Nam, Kyungsik, 2021. "Investigating the effect of climate uncertainty on global commodity markets," Energy Economics, Elsevier, vol. 96(C).
    118. Nguyen, BH & Zhang, Bo, 2022. "Forecasting oil Prices: can large BVARs help?," Working Papers 2022-04, University of Tasmania, Tasmanian School of Business and Economics.
    119. Helena Chuliá & Jorge M. Uribe, 2019. "“Expected, Unexpected, Good and Bad Uncertainty"," IREA Working Papers 201919, University of Barcelona, Research Institute of Applied Economics, revised Nov 2019.
    120. Prüser, Jan, 2023. "Data-based priors for vector error correction models," International Journal of Forecasting, Elsevier, vol. 39(1), pages 209-227.
    121. Malte Knüppel & Fabian Krüger, 2022. "Forecast uncertainty, disagreement, and the linear pool," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 23-41, January.
    122. Todd E. Clark & Francesco Ravazzolo, 2012. "The macroeconomic forecasting performance of autoregressive models with alternative specifications of time-varying volatility," Working Paper 2012/09, Norges Bank.
    123. Crespo Cuaresma, Jesús & Huber, Florian & Onorante, Luca, 2020. "Fragility and the effect of international uncertainty shocks," Journal of International Money and Finance, Elsevier, vol. 108(C).
    124. Jamie L. Cross & Chenghan Hou & Gary Koop, 2021. "Macroeconomic Forecasting with Large Stochastic Volatility in Mean VARs," Working Papers No 04/2021, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    125. Fu, Bowen, 2023. "Measuring the trend real interest rate in a data-rich environment," Journal of Economic Dynamics and Control, Elsevier, vol. 147(C).
    126. Aubrey Poon, 2018. "Assessing the Synchronicity and Nature of Australian State Business Cycles," The Economic Record, The Economic Society of Australia, vol. 94(307), pages 372-390, December.
    127. Paul Labonne, 2020. "Asymmetric uncertainty : Nowcasting using skewness in real-time data," Papers 2012.02601, arXiv.org, revised May 2024.
    128. Stefan Griller & Florian Huber & Michael Pfarrhofer, 2022. "Measuring Shocks to Central Bank Independence using Legal Rulings," Papers 2202.12695, arXiv.org.
    129. Hartwig, Benny, 2022. "Bayesian VARs and prior calibration in times of COVID-19," Discussion Papers 52/2022, Deutsche Bundesbank.
    130. Thomas B Götz & Klemens Hauzenberger, 2021. "Large mixed-frequency VARs with a parsimonious time-varying parameter structure," The Econometrics Journal, Royal Economic Society, vol. 24(3), pages 442-461.
    131. James P. LeSage & Daniel Hendrikz, 2019. "Large Bayesian vector autoregressive forecasting for regions: A comparison of methods based on alternative disturbance structures," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 62(3), pages 563-599, June.

  28. Todd E. Clark & Francesco Ravazzolo, 2012. "The macroeconomic forecasting performance of autoregressive models with alternative specifications of time-varying volatility," Working Paper 2012/09, Norges Bank.

    Cited by:

    1. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2012. "Time-varying Combinations of Predictive Densities using Nonlinear Filtering," Tinbergen Institute Discussion Papers 12-118/III, Tinbergen Institute.
    2. 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.
    3. Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman K. van Dijk, 2013. "Parallel Sequential Monte Carlo for Efficient Density Combination: The Deco Matlab Toolbox," CREATES Research Papers 2013-09, Department of Economics and Business Economics, Aarhus University.
    4. Roberto Casarin & Marco Tronzano & Domenico Sartore, 2013. "Bayesian Markov Switching Stochastic Correlation Models," Working Papers 2013:11, Department of Economics, University of Venice "Ca' Foscari".
    5. Fabian Krüger & Todd E. Clark & Francesco Ravazzolo, 2017. "Using Entropic Tilting to Combine BVAR Forecasts With External Nowcasts," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(3), pages 470-485, July.
    6. Davide Delle Monache & Ivan Petrella, 2014. "Adaptive Models and Heavy Tails," Working Papers 720, Queen Mary University of London, School of Economics and Finance.
    7. Mihaela Bratu, 2012. "A Strategy to Improve the Survey of Professional Forecasters (SPF) Predictions Using Bias-Corrected-Accelerated (BCA) Bootstrap Forecast Intervals," International Journal of Synergy and Research, ToKnowPress, vol. 1(2), pages 45-59.
    8. Knut Are Aastveit & Claudia Foroni & Francesco Ravazzolo, 2017. "Density Forecasts With Midas Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(4), pages 783-801, June.
    9. Benjamin K. Johannsen & Elmar Mertens, 2016. "A Time Series Model of Interest Rates With the Effective Lower Bound," Finance and Economics Discussion Series 2016-033, Board of Governors of the Federal Reserve System (U.S.).
    10. Pami Dua, 2023. "Macroeconomic Modelling and Bayesian Methods," Springer Books, in: Pami Dua (ed.), Macroeconometric Methods, chapter 0, pages 19-37, Springer.
    11. Samuel F. Onipede & Nafiu A. Bashir & Jamaladeen Abubakar, 2023. "Small open economies and external shocks: an application of Bayesian global vector autoregression model," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(2), pages 1673-1699, April.
    12. José Antonio Gibanel Salazar, 2014. "Economic models: comparative analysis of their adjustment and prediction capacities," Contribuciones a la Economía, Servicios Académicos Intercontinentales SL, issue 2014-05, November.
    13. Awijen, Haithem & Ben Zaied, Younes & Nguyen, Duc Khuong & Sensoy, Ahmet, 2020. "Endogenous Financial Uncertainty and Macroeconomic Volatility: Evidence from the United States," MPRA Paper 101276, University Library of Munich, Germany, revised Jun 2020.

  29. Todd E. Clark & Michael W. McCracken, 2011. "Tests of equal forecast accuracy for overlapping models," Working Papers (Old Series) 1121, Federal Reserve Bank of Cleveland.

    Cited by:

    1. Mayer, Walter J. & Liu, Feng & Dang, Xin, 2017. "Improving the power of the Diebold–Mariano–West test for least squares predictions," International Journal of Forecasting, Elsevier, vol. 33(3), pages 618-626.
    2. Firmin Doko Tchatoka & Qazi Haque, 2020. "On bootstrapping tests of equal forecast accuracy for nested models," Economics Discussion / Working Papers 20-06, The University of Western Australia, Department of Economics.
    3. Atsushi Inoue & Barbara Rossi, 2011. "Out-of-sample forecast tests robust to the choice of window size," Working Papers 11-31, Federal Reserve Bank of Philadelphia.
    4. Brent Meyer & Saeed Zaman, 2013. "It’s not just for inflation: The usefulness of the median CPI in BVAR forecasting," Working Papers (Old Series) 1303, Federal Reserve Bank of Cleveland.
    5. Corradi, Valentina & Fosten, Jack & Gutknecht, Daniel, 2023. "Out-of-sample tests for conditional quantile coverage an application to Growth-at-Risk," Journal of Econometrics, Elsevier, vol. 236(2).
    6. T. S. McElroy, 2016. "Nonnested model comparisons for time series," Biometrika, Biometrika Trust, vol. 103(4), pages 905-914.
    7. Isao Ishida & Virmantas Kvedaras, 2015. "Modeling Autoregressive Processes with Moving-Quantiles-Implied Nonlinearity," Econometrics, MDPI, vol. 3(1), pages 1-53, January.

  30. Todd E. Clark & Michael W. McCracken, 2011. "Advances in forecast evaluation," Working Papers (Old Series) 1120, Federal Reserve Bank of Cleveland.

    Cited by:

    1. Yin, Anwen, 2015. "Forecasting and model averaging with structural breaks," ISU General Staff Papers 201501010800005727, Iowa State University, Department of Economics.
    2. Galvão, Ana Beatriz, 2013. "Changes in predictive ability with mixed frequency data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 395-410.
    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. Shahzad Ahmad & Farooq Pasha, 2015. "A Pragmatic Model for Monetary Policy Analysis I: The Case of Pakistan," SBP Research Bulletin, State Bank of Pakistan, Research Department, vol. 11, pages 1-42.
    5. 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.
    6. Ayse Kabukcuoglu & Enrique Martínez-García, 2016. "What Helps Forecast U.S. Inflation?—Mind the Gap!," Koç University-TUSIAD Economic Research Forum Working Papers 1615, Koc University-TUSIAD Economic Research Forum.
    7. Ahmed, Shamim & Tsvetanov, Daniel, 2016. "The predictive performance of commodity futures risk factors," Journal of Banking & Finance, Elsevier, vol. 71(C), pages 20-36.
    8. Filip Stanek, 2021. "Optimal Out-of-Sample Forecast Evaluation under Stationarity," CERGE-EI Working Papers wp712, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    9. Pincheira, Pablo M. & West, Kenneth D., 2016. "A comparison of some out-of-sample tests of predictability in iterated multi-step-ahead forecasts," Research in Economics, Elsevier, vol. 70(2), pages 304-319.
    10. Kilian, Lutz & Baumeister, Christiane & Lee, Thomas K, 2014. "Are there Gains from Pooling Real-Time Oil Price Forecasts?," CEPR Discussion Papers 10075, C.E.P.R. Discussion Papers.
    11. Rodrigo Sekkel, 2014. "Balance Sheets of Financial Intermediaries: Do They Forecast Economic Activity?," Staff Working Papers 14-40, Bank of Canada.
    12. Nicolas S. Magner & Nicolás Hardy & Tiago Ferreira & Jaime F. Lavin, 2023. "“Agree to Disagree”: Forecasting Stock Market Implied Volatility Using Financial Report Tone Disagreement Analysis," Mathematics, MDPI, vol. 11(7), pages 1-16, March.
    13. Francesco Ravazzolo & Philip Rothman, 2011. "Oil and US GDP: A Real-Time out-of Sample Examination," Working Papers No 2/2011, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    14. Altug, Sumru & Çakmaklı, Cem, 2015. "Forecasting Inflation using Survey Expectations and Target Inflation: Evidence for Brazil and Turkey," CEPR Discussion Papers 10419, C.E.P.R. Discussion Papers.
    15. Tamás Kiss & Hoang Nguyen & Pär Österholm, 2021. "Modelling Returns in US Housing Prices—You’re the One for Me, Fat Tails," JRFM, MDPI, vol. 14(11), pages 1-17, October.
    16. Mayer, Walter J. & Liu, Feng & Dang, Xin, 2017. "Improving the power of the Diebold–Mariano–West test for least squares predictions," International Journal of Forecasting, Elsevier, vol. 33(3), pages 618-626.
    17. Magdalena Grothe & Aidan Meyler, 2018. "Inflation Forecasts: Are Market-Based and Survey-Based Measures Informative?," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 9(1), pages 171-188, January.
    18. Boneva, Lena & Fawcett, Nicholas & Masolo, Riccardo M. & Waldron, Matt, 2019. "Forecasting the UK economy: Alternative forecasting methodologies and the role of off-model information," International Journal of Forecasting, Elsevier, vol. 35(1), pages 100-120.
    19. Korobilis, Dimitris & Pettenuzzo, Davide, 2019. "Adaptive hierarchical priors for high-dimensional vector autoregressions," Journal of Econometrics, Elsevier, vol. 212(1), pages 241-271.
    20. Michael D. Bauer & Glenn D. Rudebusch, 2017. "Interest Rates Under Falling Stars," CESifo Working Paper Series 6571, CESifo.
    21. McGurk, Zachary, 2020. "US real estate inflation prediction: Exchange rates and net foreign assets," The Quarterly Review of Economics and Finance, Elsevier, vol. 75(C), pages 53-66.
    22. Muhammad Nadim Hanif & Muhammad Jahanzeb Malik, 2015. "Evaluating the Performance of Inflation Forecasting Models of Pakistan," SBP Research Bulletin, State Bank of Pakistan, Research Department, vol. 11, pages 43-78.
    23. Antolín-Díaz, Juan & Drechsel, Thomas & Petrella, Ivan, 2024. "Advances in nowcasting economic activity: The role of heterogeneous dynamics and fat tails," Journal of Econometrics, Elsevier, vol. 238(2).
    24. Christiane Baumeister & Lutz Kilian & Thomas K. Lee, 2016. "Inside the Crystal Ball: New Approaches to Predicting the Gasoline Price at the Pump," CESifo Working Paper Series 5759, CESifo.
    25. Fabian Krüger & Todd E. Clark & Francesco Ravazzolo, 2017. "Using Entropic Tilting to Combine BVAR Forecasts With External Nowcasts," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(3), pages 470-485, July.
    26. Brent Meyer & Saeed Zaman, 2019. "The usefulness of the median CPI in Bayesian VARs used for macroeconomic forecasting and policy," Empirical Economics, Springer, vol. 57(2), pages 603-630, August.
    27. Carriero, Andrea & Mumtaz, Haroon & Theophilopoulou, Angeliki, 2015. "Macroeconomic information, structural change, and the prediction of fiscal aggregates," International Journal of Forecasting, Elsevier, vol. 31(2), pages 325-348.
    28. 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.
    29. Pablo Pincheira & Nicolás Hardy & Felipe Muñoz, 2021. "“Go Wild for a While!”: A New Test for Forecast Evaluation in Nested Models," Mathematics, MDPI, vol. 9(18), pages 1-28, September.
    30. Laura Coroneo & Fabrizio Iacone, 2020. "Comparing predictive accuracy in small samples using fixed‐smoothing asymptotics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(4), pages 391-409, June.
    31. Sainan Jin & Valentina Corradi & Norman Swanson, 2015. "Robust Forecast Comparison," Departmental Working Papers 201502, Rutgers University, Department of Economics.
    32. Arai, Natsuki, 2014. "Using forecast evaluation to improve the accuracy of the Greenbook forecast," International Journal of Forecasting, Elsevier, vol. 30(1), pages 12-19.
    33. Michael Dotsey & Shigeru Fujita & Tom Stark, 2011. "Do Phillips curves conditionally help to forecast inflation?," Working Papers 11-40, Federal Reserve Bank of Philadelphia.
    34. Gregory R. Duffee, 2012. "Forecasting interest rates," Economics Working Paper Archive 599, The Johns Hopkins University,Department of Economics.
    35. Todd E. Clark & Taeyoung Doh, 2011. "A Bayesian evaluation of alternative models of trend inflation," Working Papers (Old Series) 1134, Federal Reserve Bank of Cleveland.
    36. Brent Meyer & Guhan Venkatu, 2014. "Trimmed-Mean Inflation Statistics: Just Hit the One in the Middle," FRB Atlanta Working Paper 2014-3, Federal Reserve Bank of Atlanta.
    37. 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.
    38. Catherine Doz & Laurent Ferrara & Pierre-Alain Pionnier, 2020. "Business cycle dynamics after the Great Recession: An Extended Markov-Switching Dynamic Factor Model," Working Papers halshs-02443364, HAL.
    39. Atsushi Inoue & Barbara Rossi, 2011. "Out-of-sample forecast tests robust to the choice of window size," Working Papers 11-31, Federal Reserve Bank of Philadelphia.
    40. Franc{c}ois Lafond & Aimee Gotway Bailey & Jan David Bakker & Dylan Rebois & Rubina Zadourian & Patrick McSharry & J. Doyne Farmer, 2017. "How well do experience curves predict technological progress? A method for making distributional forecasts," Papers 1703.05979, arXiv.org, revised Sep 2017.
    41. Yin, Anwen, 2020. "Equity premium prediction and optimal portfolio decision with Bagging," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    42. 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.
    43. Fawcett, Nicholas & Koerber, Lena & Masolo, Riccardo & Waldron, Matthew, 2015. "Evaluating UK point and density forecasts from an estimated DSGE model: the role of off-model information over the financial crisis," Bank of England working papers 538, Bank of England.
    44. Jonathan H. Wright, 2015. "Comment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(1), pages 12-13, January.
    45. Andrea Carriero & Galvao, Ana Beatriz & Kapetanios, George, 2016. "A comprehensive evaluation of macroeconomic forecasting methods," EMF Research Papers 10, Economic Modelling and Forecasting Group.
    46. Nima Nonejad, 2022. "New Findings Regarding the Out-of-Sample Predictive Impact of the Price of Crude Oil on the United States Industrial Production," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 18(1), pages 1-35, March.
    47. Gagnon, Marie-Hélène & Power, Gabriel J. & Toupin, Dominique, 2023. "The sum of all fears: Forecasting international returns using option-implied risk measures," Journal of Banking & Finance, Elsevier, vol. 146(C).
    48. Tunaru, Diana, 2017. "Gaussian estimation and forecasting of the U.K. yield curve with multi-factor continuous-time models," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 119-129.
    49. Håvard Hungnes, 2020. "Predicting the exchange rate path. The importance of using up-to-date observations in the forecasts," Discussion Papers 934, Statistics Norway, Research Department.
    50. Costantini, Mauro & Kunst, Robert M., 2021. "On using predictive-ability tests in the selection of time-series prediction models: A Monte Carlo evaluation," International Journal of Forecasting, Elsevier, vol. 37(2), pages 445-460.
    51. Kurmaş Akdoğan, 2019. "Size and sign asymmetries in house price adjustments," Applied Economics, Taylor & Francis Journals, vol. 51(48), pages 5268-5281, October.
    52. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2021. "Time-Varying Comovement of Foreign Exchange Markets: A GLS-Based Time-Varying Model Approach," Mathematics, MDPI, vol. 9(8), pages 1-13, April.
    53. Ziegel, Johanna F. & Krueger, Fabian & Jordan, Alexander & Fasciati, Fernando, 2017. "Murphy Diagrams: Forecast Evaluation of Expected Shortfall," Working Papers 0632, University of Heidelberg, Department of Economics.
    54. Dur, Ayşe & Martínez García, Enrique, 2020. "Mind the gap!—A monetarist view of the open-economy Phillips curve," Journal of Economic Dynamics and Control, Elsevier, vol. 117(C).
    55. Peter Reinhard Hansen & Allan Timmermann, 2012. "Choice of Sample Split in Out-of-Sample Forecast Evaluation," CREATES Research Papers 2012-43, Department of Economics and Business Economics, Aarhus University.
    56. Zhu, Yinchu & Timmermann, Allan, 2022. "Conditional rotation between forecasting models," Journal of Econometrics, Elsevier, vol. 231(2), pages 329-347.
    57. Francis X. Diebold, 2012. "Comparing Predictive Accuracy, Twenty Years Later: A Personal Perspective on the Use and Abuse of Diebold-Mariano Tests," PIER Working Paper Archive 12-035, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    58. Timmermann, Allan & Zhu, Yinchu, 2021. "Conditional Rotation Between Forecasting Models," CEPR Discussion Papers 15917, C.E.P.R. Discussion Papers.
    59. Michael W. McCracken, 2019. "Diverging Tests of Equal Predictive Ability," Working Papers 2019-018, Federal Reserve Bank of St. Louis, revised 09 Mar 2020.
    60. Hinterlang, Natascha, 2019. "Predicting Monetary Policy Using Artificial Neural Networks," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203503, Verein für Socialpolitik / German Economic Association.
    61. Krüger, Fabian & Nolte, Ingmar, 2016. "Disagreement versus uncertainty: Evidence from distribution forecasts," Journal of Banking & Finance, Elsevier, vol. 72(S), pages 172-186.
    62. Zeyyad Mandalinci, 2015. "Forecasting Inflation in Emerging Markets: An Evaluation of Alternative Models," CReMFi Discussion Papers 3, CReMFi, School of Economics and Finance, QMUL.
    63. Christian Hutter, 2020. "A new indicator for nowcasting employment subject to social security contributions in Germany," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 54(1), pages 1-10, December.
    64. Carlos Medel, 2015. "Inflation Dynamics and the Hybrid Neo Keynesian Phillips Curve: The Case of Chile," Working Papers Central Bank of Chile 769, Central Bank of Chile.
    65. Ahmed, Shamim & Liu, Xiaoquan & Valente, Giorgio, 2016. "Can currency-based risk factors help forecast exchange rates?," International Journal of Forecasting, Elsevier, vol. 32(1), pages 75-97.
    66. Hinterlang, Natascha, 2020. "Predicting monetary policy using artificial neural networks," Discussion Papers 44/2020, Deutsche Bundesbank.
    67. Hardy, Nicolás & Ferreira, Tiago & Quinteros, Maria J. & Magner, Nicolás S., 2023. "“Watch your tone!”: Forecasting mining industry commodity prices with financial report tone," Resources Policy, Elsevier, vol. 86(PA).
    68. Michael P Clements & Ana Beatriz Galvao, 2017. "Data Revisions and Real-time Probabilistic Forecasting of Macroeconomic Variables," ICMA Centre Discussion Papers in Finance icma-dp2017-01, Henley Business School, University of Reading.
    69. Wada, Tatsuma, 2022. "Out-of-sample forecasting of foreign exchange rates: The band spectral regression and LASSO," Journal of International Money and Finance, Elsevier, vol. 128(C).
    70. Dimitrios P. Louzis, 2017. "Macroeconomic and credit forecasts during the Greek crisis using Bayesian VARs," Empirical Economics, Springer, vol. 53(2), pages 569-598, September.
    71. Guizzardi, Andrea & Stacchini, Annalisa, 2015. "Real-time forecasting regional tourism with business sentiment surveys," Tourism Management, Elsevier, vol. 47(C), pages 213-223.
    72. David I. Harvey & Stephen J. Leybourne & Emily J. Whitehouse, 2017. "Forecast evaluation tests and negative long-run variance estimates in small samples," Discussion Papers 17/03, University of Nottingham, Granger Centre for Time Series Econometrics.
    73. Chalmovianský, Jakub & Porqueddu, Mario & Sokol, Andrej, 2020. "Weigh(t)ing the basket: aggregate and component-based inflation forecasts for the euro area," Working Paper Series 2501, European Central Bank.
    74. Federico D'Amario & Milos Ciganovic, 2022. "Forecasting Cryptocurrencies Log-Returns: a LASSO-VAR and Sentiment Approach," Papers 2210.00883, arXiv.org.
    75. Petrella, Ivan & Antolin-Diaz, Juan & Drechsel, Thomas, 2021. "Advances in Nowcasting Economic Activity: Secular Trends, Large Shocks and New Data," CEPR Discussion Papers 15926, C.E.P.R. Discussion Papers.
    76. Valentina Corradi & Sainan Jin & Norman R. Swanson, 2023. "Robust forecast superiority testing with an application to assessing pools of expert forecasters," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 596-622, June.
    77. Yin, Anwen, 2019. "Out-of-sample equity premium prediction in the presence of structural breaks," International Review of Financial Analysis, Elsevier, vol. 65(C).
    78. Håvard Hungnes, 2020. "Equal predictability test for multi-step-ahead system forecasts invariant to linear transformations," Discussion Papers 931, Statistics Norway, Research Department.
    79. Laura Coroneo & Fabrizio Iacone, 2015. "Comparing predictive accuracy in small samples," Discussion Papers 15/15, Department of Economics, University of York.
    80. Jiahan Li & Ilias Tsiakas & Wei Wang, 2015. "Predicting Exchange Rates Out of Sample: Can Economic Fundamentals Beat the Random Walk?," Journal of Financial Econometrics, Oxford University Press, vol. 13(2), pages 293-341.
    81. Mathijs Cosemans & Rik Frehen & Peter C. Schotman & Rob Bauer, 2016. "Estimating Security Betas Using Prior Information Based on Firm Fundamentals," The Review of Financial Studies, Society for Financial Studies, vol. 29(4), pages 1072-1112.
    82. Michael W. McCracken, 2020. "Tests of Conditional Predictive Ability: Existence, Size, and Power," Working Papers 2020-050, Federal Reserve Bank of St. Louis.
    83. Gonzalo, Jesús & Pitarakis, Jean-Yves, 2020. "Out of sample predictability in predictive regressions with many predictor candidates," UC3M Working papers. Economics 31554, Universidad Carlos III de Madrid. Departamento de Economía.
    84. Fabio Busetti & Juri Marcucci & Giovanni Veronese, 2009. "Comparing forecast accuracy: A Monte Carlo investigation," Temi di discussione (Economic working papers) 723, Bank of Italy, Economic Research and International Relations Area.
    85. Brent Meyer & Murat Tasci, 2015. "Lessons for forecasting unemployment in the United States: use flow rates, mind the trend," FRB Atlanta Working Paper 2015-1, Federal Reserve Bank of Atlanta.
    86. Engelke, Carola & Heinisch, Katja & Schult, Christoph, 2019. "How forecast accuracy depends on conditioning assumptions," IWH Discussion Papers 18/2019, Halle Institute for Economic Research (IWH).
    87. Boot, Tom & Pick, Andreas, 2020. "Does modeling a structural break improve forecast accuracy?," Journal of Econometrics, Elsevier, vol. 215(1), pages 35-59.
    88. Papantonis, Ioannis & Rompolis, Leonidas & Tzavalis, Elias, 2023. "Improving variance forecasts: The role of Realized Variance features," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1221-1237.
    89. 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.
    90. Stephen McKnight & Alexander Mihailov & Fabio Rumler, 2018. "NKPC-Based Inflation Forecasts with a Time-Varying Trend," Serie documentos de trabajo del Centro de Estudios Económicos 2018-05, El Colegio de México, Centro de Estudios Económicos.
    91. Nima Nonejad, 2020. "A detailed look at crude oil price volatility prediction using macroeconomic variables," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1119-1141, November.
    92. 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.
    93. Clark, Todd E. & Doh, Taeyoung, 2014. "Evaluating alternative models of trend inflation," International Journal of Forecasting, Elsevier, vol. 30(3), pages 426-448.
    94. Fabian Krüger & Sebastian Lerch & Thordis Thorarinsdottir & Tilmann Gneiting, 2021. "Predictive Inference Based on Markov Chain Monte Carlo Output," International Statistical Review, International Statistical Institute, vol. 89(2), pages 274-301, August.
    95. Petri Kuosmanen & Juuso Vataja, 2017. "The return of financial variables in forecasting GDP growth in the G-7," Economic Change and Restructuring, Springer, vol. 50(3), pages 259-277, August.
    96. Guizzardi, Andrea & Pons, Flavio Maria Emanuele & Angelini, Giovanni & Ranieri, Ercolino, 2021. "Big data from dynamic pricing: A smart approach to tourism demand forecasting," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1049-1060.
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    131. Jesús Crespo Cuaresma & Martin Feldkircher & Florian Huber, 2014. "Forecasting with Bayesian Global Vector Autoregressive Models: A Comparison of Priors," Working Papers 189, Oesterreichische Nationalbank (Austrian Central Bank).
    132. Garegnani, Lorena & Gómez Aguirre, Maximiliano, 2018. "Forecasting Inflation in Argentina," IDB Publications (Working Papers) 8940, Inter-American Development Bank.
    133. Todd E. Clark & Michael W. McCracken, 2013. "Evaluating the accuracy of forecasts from vector autoregressions," Working Papers 2013-010, Federal Reserve Bank of St. Louis.

  32. Todd E. Clark & Taeyoung Doh, 2011. "A Bayesian evaluation of alternative models of trend inflation," Working Papers (Old Series) 1134, Federal Reserve Bank of Cleveland.

    Cited by:

    1. Clark, Todd & McCracken, Michael, 2013. "Advances in Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1107-1201, Elsevier.
    2. Lasha Kavtaradze & Manouchehr Mokhtari, 2018. "Factor Models And Time†Varying Parameter Framework For Forecasting Exchange Rates And Inflation: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 302-334, April.
    3. Deborah Gefang & Gary Koop & Simon M. Potter, 2009. "The Dynamics of UK and US Inflation Expectations," Working Paper series 14_09, Rimini Centre for Economic Analysis.
    4. Davide Delle Monache & Ivan Petrella, 2014. "Adaptive Models and Heavy Tails," Working Papers 720, Queen Mary University of London, School of Economics and Finance.
    5. Chan, Joshua C.C., 2013. "Moving average stochastic volatility models with application to inflation forecast," Journal of Econometrics, Elsevier, vol. 176(2), pages 162-172.
    6. Faust, Jon & Wright, Jonathan H., 2013. "Forecasting Inflation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 2-56, Elsevier.
    7. Chan, Joshua & Koop, Gary & Potter, Simon, 2012. "A new model of trend inflation," MPRA Paper 39496, University Library of Munich, Germany.
    8. Emmanuel O. Akande & Elijah O. Akanni & Oyedamola F. Taiwo & Jeremiah D. Joshua & Abel Anthony, 2023. "Predicting inflation component drivers in Nigeria: a stacked ensemble approach," SN Business & Economics, Springer, vol. 3(1), pages 1-32, January.
    9. Sohei Kaihatsu & Jouchi Nakajima, 2015. "Has Trend Inflation Shifted?: An Empirical Analysis with a Regime-Switching Model," Bank of Japan Working Paper Series 15-E-3, Bank of Japan.
    10. Taeyoung Doh, 2011. "Is unemployment helpful in understanding inflation?," Economic Review, Federal Reserve Bank of Kansas City, vol. 96(Q IV), pages 5-26.
    11. Christine Garnier & Elmar Mertens & Edward Nelson, 2015. "Trend Inflation in Advanced Economies," International Journal of Central Banking, International Journal of Central Banking, vol. 11(4), pages 65-136, September.
    12. Henzel, Steffen R., 2013. "Fitting survey expectations and uncertainty about trend inflation," Journal of Macroeconomics, Elsevier, vol. 35(C), pages 172-185.

  33. Todd E. Clark & Michael W. McCracken, 2010. "Reality checks and nested forecast model comparisons," Working Papers 2010-032, Federal Reserve Bank of St. Louis.

    Cited by:

    1. Kirstin Hubrich & Kenneth D. West, 2010. "Forecast evaluation of small nested model sets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 574-594.
    2. Atsushi Inoue & Barbara Rossi, 2011. "Out-of-sample forecast tests robust to the choice of window size," Working Papers 11-31, Federal Reserve Bank of Philadelphia.

  34. Todd E. Clark & Michael W. McCracken, 2010. "Testing for unconditional predictive ability," Working Papers 2010-031, Federal Reserve Bank of St. Louis.

    Cited by:

    1. Clark, Todd & McCracken, Michael, 2013. "Advances in Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1107-1201, Elsevier.
    2. Francesco Ravazzolo & Philip Rothman, 2011. "Oil and US GDP: A Real-Time out-of Sample Examination," Working Papers No 2/2011, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    3. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2012. "Common drifting volatility in large Bayesian VARs," Working Papers (Old Series) 1206, Federal Reserve Bank of Cleveland.
    4. Todd E. Clark & Taeyoung Doh, 2011. "A Bayesian evaluation of alternative models of trend inflation," Working Papers (Old Series) 1134, Federal Reserve Bank of Cleveland.
    5. Santiago Cajiao Raigosa & Luis Fernando Melo Velandia & Daniel Parra Amado, 2014. "Pronósticos para una economía menos volátil: El caso colombiano," Borradores de Economia 821, Banco de la Republica de Colombia.
    6. Jamali, Ibrahim & Yamani, Ehab, 2019. "Out-of-sample exchange rate predictability in emerging markets: Fundamentals versus technical analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 61(C), pages 241-263.
    7. Santiago Cajiao Raigosa & Luis Fernando Melo Velandia & Daniel Parra Amado, 2014. "Pronósticos para una economía menos volátil: El caso colombiano," Borradores de Economia 11252, Banco de la Republica.

  35. Todd E. Clark & Michael W. McCracken, 2009. "Nested forecast model comparisons: a new approach to testing equal accuracy," Research Working Paper RWP 09-11, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman K. van Dijk, 2016. "Dynamic Predictive Density Combinations for Large Data Sets in Economics and Finance," Tinbergen Institute Discussion Papers 15-084/III, Tinbergen Institute, revised 03 Jul 2017.
    2. Christian Hutter & Enzo Weber, 2015. "Constructing a new leading indicator for unemployment from a survey among German employment agencies," Applied Economics, Taylor & Francis Journals, vol. 47(33), pages 3540-3558, July.
    3. Kang, Wensheng & Ratti, Ronald. A. & Vespignani, Joaquin, 2016. "The implications of liquidity expansion in China for the US dollar," Working Papers 2016-02, University of Tasmania, Tasmanian School of Business and Economics.
    4. 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.
    5. Clark, Todd & McCracken, Michael, 2013. "Advances in Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1107-1201, Elsevier.
    6. Calhoun, Gray, 2014. "Out-Of-Sample Comparisons of Overfit Models," Staff General Research Papers Archive 32462, Iowa State University, Department of Economics.
    7. Christiane Baumeister & Dimitris Korobilis & Thomas K. Lee, 2022. "Energy Markets and Global Economic Conditions," The Review of Economics and Statistics, MIT Press, vol. 104(4), pages 828-844, October.
    8. Nicolas S. Magner & Nicolás Hardy & Tiago Ferreira & Jaime F. Lavin, 2023. "“Agree to Disagree”: Forecasting Stock Market Implied Volatility Using Financial Report Tone Disagreement Analysis," Mathematics, MDPI, vol. 11(7), pages 1-16, March.
    9. Francesco Ravazzolo & Philip Rothman, 2011. "Oil and US GDP: A Real-Time out-of Sample Examination," Working Papers No 2/2011, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    10. Robert Gausden & Mohammad Hasan, 2022. "A reappraisal of Katona’s adaptive theory of consumer behaviour using U.K. data," Manchester School, University of Manchester, vol. 90(2), pages 122-143, March.
    11. Kiss, Tamás & Mazur, Stepan & Nguyen, Hoang & Österholm, Pär, 2021. "Modelling the Relation between the US Real Economy and the Corporate Bond-Yield Spread in Bayesian VARs with non-Gaussian Disturbances," Working Papers 2021:9, Örebro University, School of Business.
    12. Mayer, Walter J. & Liu, Feng & Dang, Xin, 2017. "Improving the power of the Diebold–Mariano–West test for least squares predictions," International Journal of Forecasting, Elsevier, vol. 33(3), pages 618-626.
    13. Todd E. Clark & Michael W. McCracken, 2009. "In-sample tests of predictive ability: a new approach," Research Working Paper RWP 09-10, Federal Reserve Bank of Kansas City.
    14. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2012. "Common drifting volatility in large Bayesian VARs," Working Papers (Old Series) 1206, Federal Reserve Bank of Cleveland.
    15. 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.
    16. Firmin Doko Tchatoka & Qazi Haque, 2020. "On bootstrapping tests of equal forecast accuracy for nested models," Economics Discussion / Working Papers 20-06, The University of Western Australia, Department of Economics.
    17. Knut Are Aastveit & Tuva Marie Fastbø & Eleonora Granziera & Kenneth Sæterhagen Paulsen & Kjersti Næss Torstensen, 2020. "Nowcasting Norwegian household consumption with debit card transaction data," Working Paper 2020/17, Norges Bank.
    18. Knut Are Aastveit & André K. Anundsen & Eyo I. Herstad, 2017. "Residential investment and recession predictability," Working Paper 2017/24, Norges Bank.
    19. Hossein Hassani & Emmanuel Sirimal Silva, 2015. "A Kolmogorov-Smirnov Based Test for Comparing the Predictive Accuracy of Two Sets of Forecasts," Econometrics, MDPI, vol. 3(3), pages 1-20, August.
    20. Kichian, Maral & Rumler, Fabio, 2014. "Forecasting Canadian inflation: A semi-structural NKPC approach," Economic Modelling, Elsevier, vol. 43(C), pages 183-191.
    21. Johanna Posch & Fabio Rumler, 2015. "Semi‐Structural Forecasting of UK Inflation Based on the Hybrid New Keynesian Phillips Curve," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(2), pages 145-162, March.
    22. Arai, Natsuki, 2014. "Using forecast evaluation to improve the accuracy of the Greenbook forecast," International Journal of Forecasting, Elsevier, vol. 30(1), pages 12-19.
    23. Todd E. Clark & Taeyoung Doh, 2011. "A Bayesian evaluation of alternative models of trend inflation," Working Papers (Old Series) 1134, Federal Reserve Bank of Cleveland.
    24. Todd E. Clark & Michael W. McCracken, 2010. "Testing for unconditional predictive ability," Working Papers 2010-031, Federal Reserve Bank of St. Louis.
    25. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2014. "No Arbitrage Priors, Drifting Volatilities, and the Term Structure of Interest Rates," CEPR Discussion Papers 9848, C.E.P.R. Discussion Papers.
    26. Kilian, Lutz & Vigfusson, Robert J., 2012. "Do Oil Prices Help Forecast U.S. Real GDP? The Role of Nonlinearities and Asymmetries," CEPR Discussion Papers 8980, C.E.P.R. Discussion Papers.
    27. 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.
    28. Todd E. Clark & Michael W. McCracken, 2010. "Reality checks and nested forecast model comparisons," Working Papers 2010-032, Federal Reserve Bank of St. Louis.
    29. Faust, Jon & Wright, Jonathan H., 2013. "Forecasting Inflation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 2-56, Elsevier.
    30. Håvard Hungnes, 2020. "Predicting the exchange rate path. The importance of using up-to-date observations in the forecasts," Discussion Papers 934, Statistics Norway, Research Department.
    31. Ron Alquist & Lutz Kilian & Robert Vigfusson, 2011. "Forecasting the Price of Oil," Staff Working Papers 11-15, Bank of Canada.
    32. Guérin, Pierre & Maurin, Laurent & Mohr, Matthias, 2015. "Trend-Cycle Decomposition Of Output And Euro Area Inflation Forecasts: A Real-Time Approach Based On Model Combination," Macroeconomic Dynamics, Cambridge University Press, vol. 19(2), pages 363-393, March.
    33. Hutter, Christian & Weber, Enzo, 2014. "Forecasting with a mismatch-enhanced labor market matching function," IAB-Discussion Paper 201416, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    34. Andreou, Elena & Ghysels, Eric, 2021. "Predicting the VIX and the volatility risk premium: The role of short-run funding spreads Volatility Factors," Journal of Econometrics, Elsevier, vol. 220(2), pages 366-398.
    35. Christian Hutter & Enzo Weber, 2017. "Mismatch and the Forecasting Performance of Matching Functions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(1), pages 101-123, February.
    36. In Choi & Hanbat Jeong, 2020. "Differencing versus nondifferencing in factor‐based forecasting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(6), pages 728-750, September.
    37. Dimitrios P. Louzis, 2019. "Steady‐state modeling and macroeconomic forecasting quality," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(2), pages 285-314, March.
    38. Knut Are Aastveit & Claudia Foroni & Francesco Ravazzolo, 2017. "Density Forecasts With Midas Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(4), pages 783-801, June.
    39. Boriss Siliverstovs, 2017. "Short-term forecasting with mixed-frequency data: a MIDASSO approach," Applied Economics, Taylor & Francis Journals, vol. 49(13), pages 1326-1343, March.
    40. Andrea Carriero & Francesco Corsello & Massimiliano Marcellino, 2018. "The global component of inflation volatility," Temi di discussione (Economic working papers) 1170, Bank of Italy, Economic Research and International Relations Area.
    41. Benjamin K. Johannsen & Elmar Mertens, 2016. "A Time Series Model of Interest Rates With the Effective Lower Bound," Finance and Economics Discussion Series 2016-033, Board of Governors of the Federal Reserve System (U.S.).
    42. Filip Staněk, 2023. "Optimal out‐of‐sample forecast evaluation under stationarity," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 2249-2279, December.
    43. Christian Hutter, 2020. "A new indicator for nowcasting employment subject to social security contributions in Germany," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 54(1), pages 1-10, December.
    44. Nikolsko-Rzhevskyy, Alex & Prodan, Ruxandra, 2012. "Markov switching and exchange rate predictability," International Journal of Forecasting, Elsevier, vol. 28(2), pages 353-365.
    45. Kang, Wensheng & Ratti, Ronald A. & Vespignani, Joaquin L., 2016. "The implications of monetary expansion in China for the US dollar," Journal of Asian Economics, Elsevier, vol. 46(C), pages 71-84.
    46. Szafranek, Karol, 2019. "Bagged neural networks for forecasting Polish (low) inflation," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1042-1059.
    47. Garratt, Anthony & Mise, Emi, 2014. "Forecasting exchange rates using panel model and model averaging," Economic Modelling, Elsevier, vol. 37(C), pages 32-40.
    48. Michael W. McCracken, 2019. "Tests of Conditional Predictive Ability: Some Simulation Evidence," Working Papers 2019-11, Federal Reserve Bank of St. Louis.
    49. Håvard Hungnes, 2020. "Equal predictability test for multi-step-ahead system forecasts invariant to linear transformations," Discussion Papers 931, Statistics Norway, Research Department.
    50. Oguzhan Akgun & Alain Pirotte & Giovanni Urga & Zhenlin Yang, 2020. "Equal Predictive Ability Tests Based on Panel Data with Applications to OECD and IMF Forecasts," Papers 2003.02803, arXiv.org, revised Feb 2023.
    51. Xiaojie Xu, 2020. "Corn Cash Price Forecasting," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(4), pages 1297-1320, August.
    52. Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman K. van Dijk, 2021. "A Bayesian Dynamic Compositional Model for Large Density Combinations in Finance," Tinbergen Institute Discussion Papers 21-016/III, Tinbergen Institute.
    53. Blasques, F. & Koopman, S.J. & Mallee, M. & Zhang, Z., 2016. "Weighted maximum likelihood for dynamic factor analysis and forecasting with mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 405-417.

  36. Todd E. Clark, 2009. "Real-time density forecasts from VARs with stochastic volatility," Research Working Paper RWP 09-08, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Xiaojie Xu, 2017. "Short-run price forecast performance of individual and composite models for 496 corn cash markets," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(14), pages 2593-2620, October.
    2. Francesco Ravazzolo & Shaun P. Vahey, 2010. "Forecast densities for economic aggregates from disaggregate ensembles," Working Paper 2010/02, Norges Bank.
    3. Wolden Bache, Ida & Sofie Jore, Anne & Mitchell, James & Vahey, Shaun P., 2011. "Combining VAR and DSGE forecast densities," Journal of Economic Dynamics and Control, Elsevier, vol. 35(10), pages 1659-1670, October.
    4. O'Brien, Martin & Velasco, Sofia, 2020. "Unobserved components models with stochastic volatility for extracting trends and cycles in credit," Research Technical Papers 09/RT/20, Central Bank of Ireland.
    5. Todd E. Clark, 2009. "Is the Great Moderation over? an empirical analysis," Economic Review, Federal Reserve Bank of Kansas City, vol. 94(Q IV), pages 5-42.

  37. Todd E. Clark & Michael W. McCracken, 2009. "In-sample tests of predictive ability: a new approach," Research Working Paper RWP 09-10, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Burcu Erik & Marco Jacopo Lombardi & Dubravko Mihaljek & Hyun Song Shin, 2020. "The dollar, bank leverage and real economic activity: an evolving relationship," BIS Working Papers 847, Bank for International Settlements.
    2. Manuel Lukas & Eric Hillebrand, 2014. "Bagging Weak Predictors," CREATES Research Papers 2014-01, Department of Economics and Business Economics, Aarhus University.
    3. Calhoun, Gray, 2014. "Out-Of-Sample Comparisons of Overfit Models," Staff General Research Papers Archive 32462, Iowa State University, Department of Economics.
    4. Marcelle Chauvet & Zeynep Senyuz & Emre Yoldas, 2013. "What does financial volatility tell us about macroeconomic fluctuations?," Finance and Economics Discussion Series 2013-61, Board of Governors of the Federal Reserve System (U.S.).
    5. 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.
    6. Hsiu-Hsin Ko, 2016. "Exchange Rate Predictability in Finite Samples," The Japanese Economic Review, Springer, vol. 67(3), pages 361-378, September.
    7. Hossein Hassani & Emmanuel Sirimal Silva, 2015. "A Kolmogorov-Smirnov Based Test for Comparing the Predictive Accuracy of Two Sets of Forecasts," Econometrics, MDPI, vol. 3(3), pages 1-20, August.
    8. Antolin-Diaz, Juan & Drechsel, Thomas & Petrella, Ivan, 2017. "Tracking the slowdown in long-run GDP growth," LSE Research Online Documents on Economics 81869, London School of Economics and Political Science, LSE Library.
    9. Kilian, Lutz & Vigfusson, Robert J., 2012. "Do Oil Prices Help Forecast U.S. Real GDP? The Role of Nonlinearities and Asymmetries," CEPR Discussion Papers 8980, C.E.P.R. Discussion Papers.
    10. Petrella, Ivan & Drechsel, Thomas & Antolin-Diaz, Juan, 2014. "Following the Trend: Tracking GDP when Long-Run Growth is Uncertain," CEPR Discussion Papers 10272, C.E.P.R. Discussion Papers.
    11. Hsiu-Hsin Ko, 2016. "Exchange Rate Predictability in Finite Samples," The Japanese Economic Review, Japanese Economic Association, vol. 67(3), pages 361-378, September.
    12. Pincheira-Brown, Pablo & Selaive, Jorge & Nolazco, Jose Luis, 2019. "Forecasting inflation in Latin America with core measures," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1060-1071.
    13. Su, Hao & Ying, Chengwei & Zhu, Xiaoneng, 2022. "Disaster risk matters in the bond market," Finance Research Letters, Elsevier, vol. 47(PA).
    14. Boot, Tom & Pick, Andreas, 2020. "Does modeling a structural break improve forecast accuracy?," Journal of Econometrics, Elsevier, vol. 215(1), pages 35-59.
    15. Mohan Subbiah & Frank J Fabozzi, 2016. "Equity style allocation: A nonparametric approach," Journal of Asset Management, Palgrave Macmillan, vol. 17(3), pages 141-164, May.
    16. Burcu Erik & Marco Jacopo Lombardi & Dubravko Mihaljek & Hyun Song Shin, 2019. "Financial conditions and purchasing managers' indices: exploring the links," BIS Quarterly Review, Bank for International Settlements, September.

  38. Todd E. Clark & Stephen J. Terry, 2009. "Time variation in the inflation passthrough of energy prices," Research Working Paper RWP 09-06, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Cristina Conflitti and Matteo Luciani, 2019. "Oil Price Pass-through into Core Inflation," The Energy Journal, International Association for Energy Economics, vol. 0(Number 6).
    2. Hilde C. Bjørnland & Julia Zhulanova, 2019. "The shale oil boom and the U.S. economy: Spillovers and time-varying effects," Working Paper 2019/14, Norges Bank.
    3. 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.
    4. Sheng, Xin & Marfatia, Hardik A. & Gupta, Rangan & Ji, Qiang, 2023. "The non-linear response of US state-level tradable and non-tradable inflation to oil shocks: The role of oil-dependence," Research in International Business and Finance, Elsevier, vol. 64(C).
    5. Ahmed Jamal Pirzada, 2017. "Energy Price Uncertainty and Decreasing Pass-through to Core Inflation," Bristol Economics Discussion Papers 17/681, School of Economics, University of Bristol, UK, revised 30 May 2017.
    6. Bijsterbosch, Martin & Falagiarda, Matteo, 2014. "Credit supply dynamics and economic activity in euro area countries: a time-varying parameter VAR analysis," Working Paper Series 1714, European Central Bank.
    7. Castillo, Paul & Montoro, Carlos & Tuesta, Vicente, 2020. "Inflation, oil price volatility and monetary policy," Journal of Macroeconomics, Elsevier, vol. 66(C).
    8. Shi, Xunpeng & Sun, Sizhong, 2017. "Energy price, regulatory price distortion and economic growth: A case study of China," Energy Economics, Elsevier, vol. 63(C), pages 261-271.
    9. Lutz Kilian & Xiaoqing Zhou, 2023. "Oil Price Shocks and Inflation," Working Papers 2312, Federal Reserve Bank of Dallas.
    10. Domenico Giannone & Michèle Lenza & Daphné Momferatu & Luca Onorante, 2010. "Short-term inflation projections: a Bayesian vector autoregressive approach," Working Papers ECARES ECARES 2010-011, ULB -- Universite Libre de Bruxelles.
    11. Martin Fukac, 2011. "Have rising oil prices become a greater threat to price stability?," Economic Review, Federal Reserve Bank of Kansas City, vol. 96(Q IV), pages 27-53.
    12. Lutz Kilian & Xiaoqing Zhou, 2020. "Oil Prices, Gasoline Prices and Inflation Expectations: A New Model and New Facts," CESifo Working Paper Series 8516, CESifo.
    13. Janet L. Yellen, 2015. "Inflation Dynamics and Monetary Policy : A speech at the Philip Gamble Memorial Lecture, University of Massachusetts, Amherst, Amherst, Massachusetts, September 24, 2015," Speech 863, Board of Governors of the Federal Reserve System (U.S.).
    14. Baharumshah, Ahmad Zubaidi & Sirag, Abdalla & Soon, Siew-Voon, 2017. "Asymmetric exchange rate pass-through in an emerging market economy: The case of Mexico," Research in International Business and Finance, Elsevier, vol. 41(C), pages 247-259.
    15. Michelle, Gilmartin, 2016. "A note on the identification and transmission of energy demand and supply shocks," MPRA Paper 76186, University Library of Munich, Germany.
    16. Zakaria, Muhammad & Khiam, Shahzeb & Mahmood, Hamid, 2021. "Influence of oil prices on inflation in South Asia: Some new evidence," Resources Policy, Elsevier, vol. 71(C).
    17. Antonio J., Garzón & Luis A., Hierro, 2022. "Inflation, oil prices and exchange rates. The Euro’s dampening effect," Journal of Policy Modeling, Elsevier, vol. 44(1), pages 130-146.
    18. Mirza, Nawazish & Naqvi, Bushra & Rizvi, Syed Kumail Abbas & Umar, Muhammad, 2023. "Fiscal or monetary? Efficacy of regulatory regimes and energy trilemma of the inflation reduction act (IRA)," International Review of Financial Analysis, Elsevier, vol. 90(C).
    19. Sohrab Rafiq, 2014. "What Do Energy Prices Tell Us About UK Inflation?," Economica, London School of Economics and Political Science, vol. 81(322), pages 293-310, April.
    20. Tomoyuki Yagi & Yoshiyuki Kurachi & Masato Takahashi & Kotone Yamada & Hiroshi Kawata, 2022. "Pass-Through of Cost-Push Pressures to Consumer Prices," Bank of Japan Working Paper Series 22-E-17, Bank of Japan.
    21. Francesco Corsello & Alex Tagliabracci, 2023. "Assessing the pass-through of energy prices to inflation in the euro area," Questioni di Economia e Finanza (Occasional Papers) 745, Bank of Italy, Economic Research and International Relations Area.
    22. James H. Stock & Mark W. Watson, 2015. "Core Inflation and Trend Inflation," NBER Working Papers 21282, National Bureau of Economic Research, Inc.
    23. Ioannidis, Christos & Ka, Kook, 2018. "The impact of oil price shocks on the term structure of interest rates," Energy Economics, Elsevier, vol. 72(C), pages 601-620.
    24. Fasanya, Ismail O. & Awodimila, Crystal P., 2020. "Are commodity prices good predictors of inflation? The African perspective," Resources Policy, Elsevier, vol. 69(C).
    25. Atsushi Sekine & Takayuki Tsuruga, 2014. "Effects of Commodity Price Shocks on Inflation: A Cross Country Analysis," Discussion papers e-13-006, Graduate School of Economics Project Center, Kyoto University.
    26. Tian, Shuairu & Hamori, Shigeyuki, 2016. "Time-varying price shock transmission and volatility spillover in foreign exchange, bond, equity, and commodity markets: Evidence from the United States," The North American Journal of Economics and Finance, Elsevier, vol. 38(C), pages 163-171.
    27. Rondina, Francesca, 2012. "The role of model uncertainty and learning in the US postwar policy response to oil prices," Journal of Economic Dynamics and Control, Elsevier, vol. 36(7), pages 1009-1041.
    28. de Mendonça, Helder Ferreira & Garcia, Pedro Mendes, 2023. "Effects of oil shocks and central bank credibility on price diffusion," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 304-317.
    29. Deborah Gefang & Gary Koop & Simon M. Potter, 2009. "The Dynamics of UK and US Inflation Expectations," Working Paper series 14_09, Rimini Centre for Economic Analysis.
    30. Kilian, Lutz & Zhou, Xiaoqing, 2021. "The impact of rising oil prices on U.S. inflation and inflation expectations in 2020-23," CFS Working Paper Series 670, Center for Financial Studies (CFS).
    31. Kilian, Lutz & Zhou, Xiaoqing, 2023. "A broader perspective on the inflationary effects of energy price shocks," CFS Working Paper Series 686, Center for Financial Studies (CFS).
    32. Muhammad Khan & Nikolay Nenovsky, 2017. "Monetary Regimes and External Shocks Reaction: Empirical Investigations on Eastern European Economies," Post-Print hal-03831265, HAL.
    33. Abdurrahman Nazif Çatik & Mehmet Karaçuka & A. Özlem Önder, 2022. "The Time-Varying Impact of External Shocks on the Consumer Price Components: Evidence from an Emerging Market," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 20(4), pages 781-807, December.
    34. Francesca Rondina, 2017. "The Impact of Oil Price Changes in a New Keynesian Model of the U.S. Economy," Working Papers 1709E, University of Ottawa, Department of Economics.
    35. Grzegorz Przekota & Anna Szczepańska-Przekota, 2022. "Pro-Inflationary Impact of the Oil Market—A Study for Poland," Energies, MDPI, vol. 15(9), pages 1-19, April.
    36. Edward S. Knotek & Saeed Zaman, 2020. "Asymmetric Responses of Consumer Spending to Energy Prices: A Threshold VAR Approach," Working Papers 20-17, Federal Reserve Bank of Cleveland.
    37. Tiwari, Aviral Kumar & Cunado, Juncal & Hatemi-J, Abdulnasser & Gupta, Rangan, 2019. "Oil price-inflation pass-through in the United States over 1871 to 2018: A wavelet coherency analysis," Structural Change and Economic Dynamics, Elsevier, vol. 50(C), pages 51-55.
    38. Anderson, Richard G. & Binner, Jane M. & Schmidt, Vincent A., 2012. "Connectionist-based rules describing the pass-through of individual goods prices into trend inflation in the United States," Economics Letters, Elsevier, vol. 117(1), pages 174-177.
    39. Uju Violet Alola & Ojonugwa Usman & Andrew Adewale Alola, 2023. "Is pass-through of the exchange rate to restaurant and hotel prices asymmetric in the US? Role of monetary policy uncertainty," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-19, December.
    40. Martin Feldkircher & Pierre L. Siklos, 2018. "Global inflation dynamics and inflation expectations," CAMA Working Papers 2018-60, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    41. Fazal, Rizwan & Rehman, Syed Aziz Ur & Bhatti, M. Ishaq, 2022. "Graph theoretic approach to expose the energy-induced crisis in Pakistan," Energy Policy, Elsevier, vol. 169(C).
    42. Gorgi, Paolo & Koopman, Siem Jan & Li, Mengheng, 2019. "Forecasting economic time series using score-driven dynamic models with mixed-data sampling," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1735-1747.
    43. Lutz Kilian & Xiaoqing Zhou, 2022. "Oil prices, gasoline prices, and inflation expectations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 867-881, August.
    44. Mustafa Kocoglu, 2023. "Drivers of inflation in Turkey: a new Keynesian Phillips curve perspective," Economic Change and Restructuring, Springer, vol. 56(4), pages 2825-2853, August.
    45. Zhang, Weiping & Zhuang, Xintian & Lu, Yang, 2020. "Spatial spillover effects and risk contagion around G20 stock markets based on volatility network," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    46. Todd E. Clark, 2009. "Is the Great Moderation over? an empirical analysis," Economic Review, Federal Reserve Bank of Kansas City, vol. 94(Q IV), pages 5-42.
    47. Fulli-Lemaire, Nicolas, 2012. "Allocating Commodities in Inflation Hedging Portfolios: A Core Driven Global Macro Strategy," MPRA Paper 42852, University Library of Munich, Germany, revised 15 Oct 2012.
    48. Ruiz, Miguel Haro & Schult, Christoph & Wunder, Christoph, 2024. "The effects of the Iberian exception mechanism on wholesale electricity prices and consumer inflation: A synthetic-controls approach," IWH Discussion Papers 5/2024, Halle Institute for Economic Research (IWH).
    49. Jeremy B. Rudd, 2022. "The Anatomy of Single-Digit Inflation in the 1960s," Finance and Economics Discussion Series 2022-029, Board of Governors of the Federal Reserve System (U.S.).
    50. Liu, Xueyong & An, Haizhong & Li, Huajiao & Chen, Zhihua & Feng, Sida & Wen, Shaobo, 2017. "Features of spillover networks in international financial markets: Evidence from the G20 countries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 265-278.
    51. Hilde C. Bjørnland, 2022. "The effect of rising energy prices amid geopolitical developments and supply disruptions," Working Papers No 07/2022, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    52. Mr. Yasser Abdih & Mr. Ravi Balakrishnan & Baoping Shang, 2016. "What is Keeping U.S. Core Inflation Low: Insights from a Bottom-Up Approach," IMF Working Papers 2016/124, International Monetary Fund.
    53. Binder, Carola Conces, 2018. "Inflation expectations and the price at the pump," Journal of Macroeconomics, Elsevier, vol. 58(C), pages 1-18.
    54. Ekaterina V. Peneva & Jeremy B. Rudd, 2015. "The Passthrough of Labor Costs to Price Inflation," Finance and Economics Discussion Series 2015-42, Board of Governors of the Federal Reserve System (U.S.).
    55. Fulli-Lemaire, Nicolas, 2013. "Alternative inflation hedging strategies for ALM," MPRA Paper 43755, University Library of Munich, Germany.
    56. Bijsterbosch, Martin & Falagiarda, Matteo, 2015. "The macroeconomic impact of financial fragmentation in the euro area: Which role for credit supply?," Journal of International Money and Finance, Elsevier, vol. 54(C), pages 93-115.
    57. Elsayed, Ahmed H. & Hammoudeh, Shawkat & Sousa, Ricardo M., 2021. "Inflation synchronization among the G7and China: The important role of oil inflation," Energy Economics, Elsevier, vol. 100(C).
    58. Matthew Klepacz, 2018. "Price Setting and Volatility: Evidence from Oil Price Volatility Shocks," 2018 Meeting Papers 145, Society for Economic Dynamics.
    59. Pooyan Amir-Ahmadi & Christian Matthes & Mu-Chun Wang, 2016. "Choosing Prior Hyperparameters," Working Paper 16-9, Federal Reserve Bank of Richmond.
    60. Kang, Sang Hoon & Islam, Faridul & Kumar Tiwari, Aviral, 2019. "The dynamic relationships among CO2 emissions, renewable and non-renewable energy sources, and economic growth in India: Evidence from time-varying Bayesian VAR model," Structural Change and Economic Dynamics, Elsevier, vol. 50(C), pages 90-101.
    61. Zhang, Weiping & Zhuang, Xintian & Lu, Yang & Wang, Jian, 2020. "Spatial linkage of volatility spillovers and its explanation across G20 stock markets: A network framework," International Review of Financial Analysis, Elsevier, vol. 71(C).
    62. Orlowski, Lucjan T., 2017. "Volatility of commodity futures prices and market-implied inflation expectations," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 51(C), pages 133-141.
    63. Andreani, Michele & Giri, Federico, 2023. "Not a short-run noise! The low-frequency volatility of energy inflation," Finance Research Letters, Elsevier, vol. 51(C).
    64. He, Yongda & Lin, Boqiang, 2019. "Regime differences and industry heterogeneity of the volatility transmission from the energy price to the PPI," Energy, Elsevier, vol. 176(C), pages 900-916.
    65. Matthew Klepacz, 2021. "Price Setting and Volatility: Evidence from Oil Price Volatility Shocks," International Finance Discussion Papers 1316, Board of Governors of the Federal Reserve System (U.S.).

  39. Todd E. Clark & Troy Davig, 2009. "Decomposing the declining volatility of long-term inflation expectations," Research Working Paper RWP 09-05, Federal Reserve Bank of Kansas City.

    Cited by:

    1. 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.
    2. Keating, John W. & Valcarcel, Victor J., 2015. "The Time-Varying Effects Of Permanent And Transitory Shocks To Real Output," Macroeconomic Dynamics, Cambridge University Press, vol. 19(3), pages 477-507, April.
    3. caterina mendicino & Antonello DÁgostino, 2016. "Expectation-driven cycles: Time-Varying Effects," EcoMod2016 9350, EcoMod.
    4. James M. Nason & Gregor W. Smith, 2013. "Measuring The Slowly Evolving Trend In Us Inflation With Professional Forecasts," Working Paper 1316, Economics Department, Queen's University.
    5. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2012. "Common drifting volatility in large Bayesian VARs," Working Papers (Old Series) 1206, Federal Reserve Bank of Cleveland.
    6. Ascari, Guido & Fasani, Stefano & Grazzini, Jakob & Rossi, Lorenza, 2023. "Endogenous uncertainty and the macroeconomic impact of shocks to inflation expectations," Journal of Monetary Economics, Elsevier, vol. 140(S), pages 48-63.
    7. Volha Audzei, 2022. "Confidence Cycles and Liquidity Hoarding," International Journal of Central Banking, International Journal of Central Banking, vol. 18(3), pages 281-320, September.
    8. Todd E. Clark & Taeyoung Doh, 2011. "A Bayesian evaluation of alternative models of trend inflation," Working Papers (Old Series) 1134, Federal Reserve Bank of Cleveland.
    9. Travis J. Berge, 2017. "Understanding Survey Based Inflation Expectations," Finance and Economics Discussion Series 2017-046, Board of Governors of the Federal Reserve System (U.S.).
    10. James M. Nason & Gregor W. Smith, 2013. "Reverse Kalman filtering U.S. inflation with sticky professional forecasts," Working Papers 13-34, Federal Reserve Bank of Philadelphia.
    11. Benjamin Wong, 2014. "Inflation Expectations and How it Explains the Inflationary Impact of Oil Price Shocks: Evidence from the Michigan Survey," CAMA Working Papers 2014-45, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    12. J. Scott Davis, 2012. "The effect of commodity price shocks on underlying inflation: the role of central bank credibility," Globalization Institute Working Papers 134, Federal Reserve Bank of Dallas.
    13. Elmar Mertens, 2011. "Measuring the level and uncertainty of trend inflation," Finance and Economics Discussion Series 2011-42, Board of Governors of the Federal Reserve System (U.S.).
    14. Keating, John W. & Valcarcel, Victor J., 2017. "What's so great about the Great Moderation?," Journal of Macroeconomics, Elsevier, vol. 51(C), pages 115-142.
    15. Diegel, Max & Nautz, Dieter, 2020. "The role of long-term inflation expectations for the transmission of monetary policy shocks," Discussion Papers 2020/19, Free University Berlin, School of Business & Economics.
    16. McNeil, James, 2023. "Monetary policy and the term structure of inflation expectations with information frictions," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).
    17. Benjamin Wong, 2017. "Historical decompositions for nonlinear vector autoregression models," CAMA Working Papers 2017-62, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    18. Christina Anderl & Guglielmo Maria Caporale, 2023. "Functional Shocks to Inflation Expectations and Real Interest Rates and Their Macroeconomic Effects," CESifo Working Paper Series 10656, CESifo.
    19. Virginia Queijo von Heideken & Ferre De Graeve, 2012. "Fiscal policy in contemporary DSGE models," 2012 Meeting Papers 74, Society for Economic Dynamics.
    20. J. Scott Davis & Adrienne Mack, 2013. "Cross-country variation in the anchoring of inflation expectations," Staff Papers, Federal Reserve Bank of Dallas, issue Oct.
    21. Valcarcel, Victor J., 2012. "The dynamic adjustments of stock prices to inflation disturbances," Journal of Economics and Business, Elsevier, vol. 64(2), pages 117-144.
    22. Kim, Jerim & Kim, Bara & Moon, Kyoung-Sook & Wee, In-Suk, 2012. "Valuation of power options under Heston's stochastic volatility model," Journal of Economic Dynamics and Control, Elsevier, vol. 36(11), pages 1796-1813.
    23. Del Negro, Marco & Eusepi, Stefano, 2011. "Fitting observed inflation expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 35(12), pages 2105-2131.
    24. Aleksei Netšunajev & Lars Winkelmann, 2016. "International dynamics of inflation expectations," SFB 649 Discussion Papers SFB649DP2016-019, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    25. Granville, Brigitte & Zeng, Ning, 2019. "Time variation in inflation persistence: New evidence from modelling US inflation," Economic Modelling, Elsevier, vol. 81(C), pages 30-39.
    26. Ekaterina V. Peneva & Jeremy B. Rudd, 2015. "The Passthrough of Labor Costs to Price Inflation," Finance and Economics Discussion Series 2015-42, Board of Governors of the Federal Reserve System (U.S.).
    27. Henzel, Steffen R., 2013. "Fitting survey expectations and uncertainty about trend inflation," Journal of Macroeconomics, Elsevier, vol. 35(C), pages 172-185.
    28. Diegel, Max & Nautz, Dieter, 2021. "Long-term inflation expectations and the transmission of monetary policy shocks: Evidence from a SVAR analysis," Journal of Economic Dynamics and Control, Elsevier, vol. 130(C).
    29. J. Scott Davis, 2012. "Central bank credibility and the persistence of inflation and inflation expectations," Globalization Institute Working Papers 117, Federal Reserve Bank of Dallas.
    30. Todd E. Clark & Francesco Ravazzolo, 2012. "The macroeconomic forecasting performance of autoregressive models with alternative specifications of time-varying volatility," Working Paper 2012/09, Norges Bank.
    31. Monica Jain, 2018. "Sluggish Forecasts," Staff Working Papers 18-39, Bank of Canada.
    32. Mazumder, Sandeep, 2018. "Inflation in Europe after the Great Recession," Economic Modelling, Elsevier, vol. 71(C), pages 202-213.
    33. Doh, Taeyoung & Smith, A. Lee, 2022. "A new approach to integrating expectations into VAR models," Journal of Monetary Economics, Elsevier, vol. 132(C), pages 24-43.

  40. Todd E. Clark & Troy Davig, 2008. "An empirical assessment of the relationships among inflation and short- and long-term expectations," Research Working Paper RWP 08-05, Federal Reserve Bank of Kansas City.

    Cited by:

    1. K. Istrefi & A. Piloiu, 2014. "Economic Policy Uncertainty and Inflation Expectations," Working papers 511, Banque de France.
    2. Olivier Coibion & Yuriy Gorodnichenko & Saten Kumar & Mathieu Pedemonte, 2019. "Inflation Expectations as a Policy Tool?," NBER Chapters, in: NBER International Seminar on Macroeconomics 2019, National Bureau of Economic Research, Inc.
    3. Chan, Joshua & Koop, Gary & Potter, Simon, 2012. "A new model of trend inflation," MPRA Paper 39496, University Library of Munich, Germany.
    4. Klodiana Istrefi & Anamaria Piloiu, 2013. "Economic Policy Uncertainty, Trust and Inflation Expectations," CESifo Working Paper Series 4294, CESifo.
    5. Gary Koop & Luca Onorante, 2011. "Estimating Phillips Curves in Turbulent Times using the ECBs Survey of Professional Forecasters," Working Papers 1109, University of Strathclyde Business School, Department of Economics.
    6. Koop, Gary & Tole, Lise, 2013. "Modeling the relationship between European carbon permits and certified emission reductions," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 166-181.
    7. Rafiq, Sohrab, 2010. "Fiscal stance, the current account and the real exchange rate: Some empirical estimates from a time-varying framework," Structural Change and Economic Dynamics, Elsevier, vol. 21(4), pages 276-290, November.
    8. Gabriele Galati & Peter Heemeijer & Richhild Moessner, 2011. "How do inflation expectations form? New insights from a high-frequency survey," BIS Working Papers 349, Bank for International Settlements.
    9. Mazumder, Sandeep, 2018. "Inflation in Europe after the Great Recession," Economic Modelling, Elsevier, vol. 71(C), pages 202-213.

  41. Todd E. Clark & Michael W. McCracken, 2007. "Averaging forecasts from VARs with uncertain instabilities," Finance and Economics Discussion Series 2007-42, Board of Governors of the Federal Reserve System (U.S.).

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    1. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    2. Buncic, Daniel & Müller, Oliver, 2017. "Measuring the output gap in Switzerland with linear opinion pools," Economic Modelling, Elsevier, vol. 64(C), pages 153-171.
    3. Carlo Altavilla & Matteo Ciccarelli, 2011. "Monetary Policy Analysis in Real-Time. Vintage Combination from a Real-Time Dataset," CESifo Working Paper Series 3372, CESifo.
    4. Yin, Anwen, 2015. "Forecasting and model averaging with structural breaks," ISU General Staff Papers 201501010800005727, Iowa State University, Department of Economics.
    5. Panopoulou, Ekaterini & Vrontos, Spyridon, 2015. "Hedge fund return predictability; To combine forecasts or combine information?," Journal of Banking & Finance, Elsevier, vol. 56(C), pages 103-122.
    6. Niu, Linlin & Xu, Xiu & Chen, Ying, 2015. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," BOFIT Discussion Papers 12/2015, Bank of Finland Institute for Emerging Economies (BOFIT).
    7. Longo, Luigi & Riccaboni, Massimo & Rungi, Armando, 2022. "A neural network ensemble approach for GDP forecasting," Journal of Economic Dynamics and Control, Elsevier, vol. 134(C).
    8. Jan J. J. Groen & Richard Paap & Francesco Ravazzolo, 2009. "Real-time inflation forecasting in a changing world," Staff Reports 388, Federal Reserve Bank of New York.
    9. 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.
    10. Duncan, Roberto & Martínez-García, Enrique, 2019. "New perspectives on forecasting inflation in emerging market economies: An empirical assessment," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1008-1031.
    11. Charles Rahal, 2015. "Housing Market Forecasting with Factor Combinations," Discussion Papers 15-05, Department of Economics, University of Birmingham.
    12. Gian Luigi Mazzi & James Mitchell & Gaetana Montana, 2014. "Density Nowcasts and Model Combination: Nowcasting Euro-Area GDP Growth over the 2008–09 Recession," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(2), pages 233-256, April.
    13. Berg, Tim O. & Henzel, Steffen R., 2015. "Point and density forecasts for the euro area using Bayesian VARs," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1067-1095.
    14. 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.
    15. Francesco Ravazzolo & Shaun P. Vahey, 2010. "Forecast densities for economic aggregates from disaggregate ensembles," Working Paper 2010/02, Norges Bank.
    16. Vladimir Kuzin & Massimiliano Marcellino & Christian Schumacher, 2009. "Pooling versus Model Selection for Nowcasting with Many Predictors: An Application to German GDP," Economics Working Papers ECO2009/13, European University Institute.
    17. Karlsson, Sune, 2012. "Forecasting with Bayesian Vector Autoregressions," Working Papers 2012:12, Örebro University, School of Business.
    18. Katja Drechsel & Dr. Rolf Scheufele, 2012. "Bottom-up or Direct? Forecasting German GDP in a Data-rich Environment," Working Papers 2012-16, Swiss National Bank.
    19. Hilde C. Bjørnland & Karsten Gerdrup & Anne Sofie Jore & Christie Smith & Leif Anders Thorsrud, 2012. "Does Forecast Combination Improve Norges Bank Inflation Forecasts?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 74(2), pages 163-179, April.
    20. Colino, Evelyn V. & Irwin, Scott H. & Garcia, Philip, 2009. "Do Composite Procedures Really Improve the Accuracy of Outlook Forecasts?," 2009 Conference, April 20-21, 2009, St. Louis, Missouri 53052, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    21. Francesco Ravazzolo & Tommy Sveen & Sepideh K. Zahiri, 2016. "Commodity Futures and Forecasting Commodity Currencies," Working Papers No 7/2016, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    22. Cristina Conflitti & Christine De Mol & Domenico Giannone, 2012. "Optimal Combination of Survey Forecasts," Working Papers ECARES ECARES 2012-023, ULB -- Universite Libre de Bruxelles.
    23. Maheu, John M & Song, Yong, 2017. "An Efficient Bayesian Approach to Multiple Structural Change in Multivariate Time Series," MPRA Paper 79211, University Library of Munich, Germany.
    24. Rusnák, Marek, 2016. "Nowcasting Czech GDP in real time," Economic Modelling, Elsevier, vol. 54(C), pages 26-39.
    25. 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.
    26. Bjørnland, Hilde C. & Gerdrup, Karsten & Jore, Anne Sofie & Smith, Christie & Thorsrud, Leif Anders, 2011. "Weights and pools for a Norwegian density combination," The North American Journal of Economics and Finance, Elsevier, vol. 22(1), pages 61-76, January.
    27. Wolden Bache, Ida & Sofie Jore, Anne & Mitchell, James & Vahey, Shaun P., 2011. "Combining VAR and DSGE forecast densities," Journal of Economic Dynamics and Control, Elsevier, vol. 35(10), pages 1659-1670, October.
    28. Sermpinis, Georgios & Stasinakis, Charalampos & Hassanniakalager, Arman, 2017. "Reverse adaptive krill herd locally weighted support vector regression for forecasting and trading exchange traded funds," European Journal of Operational Research, Elsevier, vol. 263(2), pages 540-558.
    29. Chatzitzisi, Evanthia & Fountas, Stilianos & Panagiotidis, Theodore, 2021. "Another look at calendar anomalies," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 823-840.
    30. Knut Are Aastveit & Jamie Cross & Herman K. van Dijk, 2021. "Quantifying time-varying forecast uncertainty and risk for the real price of oil," Tinbergen Institute Discussion Papers 21-053/III, Tinbergen Institute.
    31. Anthony Garratt & Timo Henckel & Shaun P. Vahey, 2019. "Empirically-transformed linear opinion pools," CAMA Working Papers 2019-47, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    32. John M Maheu & Thomas H McCurdy, 2007. "How useful are historical data for forecasting the long-run equity return distribution?," Working Papers tecipa-293, University of Toronto, Department of Economics.
    33. McElroy, Tucker S. & Wildi, Marc, 2020. "The Multivariate Linear Prediction Problem: Model-Based and Direct Filtering Solutions," Econometrics and Statistics, Elsevier, vol. 14(C), pages 112-130.
    34. Pierre Gosselin & Aileen Lotz & Charles Wyplosz, 2008. "The Expected Interest Rate Path: Alignment of Expectations vs. Creative Opacity," International Journal of Central Banking, International Journal of Central Banking, vol. 4(3), pages 145-185, September.
    35. Todd E. Clark & Taeyoung Doh, 2011. "A Bayesian evaluation of alternative models of trend inflation," Working Papers (Old Series) 1134, Federal Reserve Bank of Cleveland.
    36. Maheu, John & Song, Yong, 2012. "A new structural break model with application to Canadian inflation forecasting," MPRA Paper 36870, University Library of Munich, Germany.
    37. Anne Sofie Jore & James Mitchell & Shaun Vahey, 2008. "Combining Forecast Densities from VARs with Uncertain Instabilities," Reserve Bank of New Zealand Discussion Paper Series DP2008/18, Reserve Bank of New Zealand.
    38. Andrew C. Chang & Phillip Li, 2018. "Measurement Error In Macroeconomic Data And Economics Research: Data Revisions, Gross Domestic Product, And Gross Domestic Income," Economic Inquiry, Western Economic Association International, vol. 56(3), pages 1846-1869, July.
    39. Edward S. Knotek & Saeed Zaman, 2020. "Real-Time Density Nowcasts of US Inflation: A Model-Combination Approach," Working Papers 20-31, Federal Reserve Bank of Cleveland.
    40. Knut Are Aastveit & Karsten R. Gerdrup & Anne Sofie Jore & Leif Anders Thorsrud, 2011. "Nowcasting GDP in real-time: A density combination approach," Working Paper 2011/11, Norges Bank.
    41. Garratt, Anthony & Mitchell, James & Vahey, Shaun P., 2014. "Measuring output gap nowcast uncertainty," International Journal of Forecasting, Elsevier, vol. 30(2), pages 268-279.
    42. Jos Jansen, W. & Jin, Xiaowen & Winter, Jasper M. de, 2016. "Forecasting and nowcasting real GDP: Comparing statistical models and subjective forecasts," Munich Reprints in Economics 43488, University of Munich, Department of Economics.
    43. Colino, Evelyn V. & Irwin, Scott H. & Garcia, Philip, 2008. "How Much Can Outlook Forecasts be Improved? An Application to the U.S. Hog Market," 2008 Conference, April 21-22, 2008, St. Louis, Missouri 37620, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    44. Bańbura, Marta & Bobeica, Elena, 2023. "Does the Phillips curve help to forecast euro area inflation?," International Journal of Forecasting, Elsevier, vol. 39(1), pages 364-390.
    45. Chauvet, Marcelle & Potter, Simon, 2013. "Forecasting Output," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 141-194, Elsevier.
    46. Andrew C. Chang & Phillip Li, 2015. "Is Economics Research Replicable? Sixty Published Papers from Thirteen Journals Say \"Usually Not\"," Finance and Economics Discussion Series 2015-83, Board of Governors of the Federal Reserve System (U.S.).
    47. Tony Chernis & Rodrigo Sekkel, 2018. "Nowcasting Canadian Economic Activity in an Uncertain Environment," Discussion Papers 18-9, Bank of Canada.
    48. M. Hashem Pesaran & Andreas Pick, 2008. "Forecasting Random Walks Under Drift Instability," CESifo Working Paper Series 2293, CESifo.
    49. Constantin Bürgi & Tara M. Sinclair, 2015. "A Nonparametric Approach to Identifying a Subset of Forecasters that Outperforms the Simple Average," Working Papers 2015-006, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    50. Aristidou, Chrystalleni & Lee, Kevin & Shields, Kalvinder, 2022. "Fundamentals, regimes and exchange rate forecasts: Insights from a meta exchange rate model," Journal of International Money and Finance, Elsevier, vol. 123(C).
    51. Carstensen Kai & Wohlrabe Klaus & Ziegler Christina, 2011. "Predictive Ability of Business Cycle Indicators under Test: A Case Study for the Euro Area Industrial Production," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 82-106, February.
    52. Schumacher, Christian, 2009. "Factor forecasting using international targeted predictors: the case of German GDP," Discussion Paper Series 1: Economic Studies 2009,10, Deutsche Bundesbank.
    53. Chanont Banternghansa & Michael W. McCracken, 2010. "Real-time forecast averaging with ALFRED," Working Papers 2010-033, Federal Reserve Bank of St. Louis.
    54. Knut Are Aastveit & Francesco Ravazzolo & Herman K. van Dijk, 2018. "Combined Density Nowcasting in an Uncertain Economic Environment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 131-145, January.
    55. KOROBILIS, Dimitris, 2011. "VAR forecasting using Bayesian variable selection," LIDAM Discussion Papers CORE 2011022, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    56. Filippo di Mauro & Filippo di Mauro, Fabio Fornari, 2014. "Going granular: The importance of firm-level equity information in anticipating economic activity," EcoMod2014 6809, EcoMod.
    57. Anthony Garratt & James Mitchell & Shaun P. Vahey & Elizabeth C. Wakerly, 2010. "Real-time Inflation Forecast Densities from Ensemble Phillips Curves," CAMA Working Papers 2010-34, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    58. Soybilgen, Barış & Yazgan, Ege, 2018. "Evaluating nowcasts of bridge equations with advanced combination schemes for the Turkish unemployment rate," Economic Modelling, Elsevier, vol. 72(C), pages 99-108.
    59. Arnaud Dufays & Zhuo Li & Jeroen V.K. Rombouts & Yong Song, 2021. "Sparse change‐point VAR models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(6), pages 703-727, September.
    60. Bruno P. C. Levy & Hedibert F. Lopes, 2021. "Dynamic Ordering Learning in Multivariate Forecasting," Papers 2101.04164, arXiv.org, revised Nov 2021.
    61. Prasad S Bhattacharya & Dimitrios D Thomakos, 2011. "Improving forecasting performance by window and model averaging," CAMA Working Papers 2011-05, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    62. David Hendry & Michael P. Clements, 2010. "Forecasting from Mis-specified Models in the Presence of Unanticipated Location Shifts," Economics Series Working Papers 484, University of Oxford, Department of Economics.
    63. Leo Krippner & Leif Anders Thorsrud, 2009. "Forecasting New Zealand's economic growth using yield curve information," Reserve Bank of New Zealand Discussion Paper Series DP2009/18, Reserve Bank of New Zealand.
    64. di Mauro, Filippo & Fornari, Fabio & Mannucci, Dario, 2011. "Stock market firm-level information and real economic activity," Working Paper Series 1366, European Central Bank.
    65. Tony Chernis & Taylor Webley, 2022. "Nowcasting Canadian GDP with Density Combinations," Discussion Papers 2022-12, Bank of Canada.
    66. Bjarni G. Einarsson, 2024. "Online Monitoring of Policy Optimality," Economics wp95, Department of Economics, Central bank of Iceland.
    67. Tae-Hwy Lee & Shahnaz Parsaeian & Aman Ullah, 2022. "Optimal Forecast under Structural Breaks," Working Papers 202208, University of California at Riverside, Department of Economics.
    68. Dr. James Mitchell, 2009. "Measuring Output Gap Uncertainty," National Institute of Economic and Social Research (NIESR) Discussion Papers 342, National Institute of Economic and Social Research.
    69. Graefe, Andreas & Küchenhoff, Helmut & Stierle, Veronika & Riedl, Bernhard, 2015. "Limitations of Ensemble Bayesian Model Averaging for forecasting social science problems," International Journal of Forecasting, Elsevier, vol. 31(3), pages 943-951.
    70. Niko Hauzenberger & Florian Huber & Karin Klieber, 2020. "Real-time Inflation Forecasting Using Non-linear Dimension Reduction Techniques," Papers 2012.08155, arXiv.org, revised Dec 2021.
    71. Liebermann, Joelle, 2012. "Real-time forecasting in a data-rich environment," Research Technical Papers 07/RT/12, Central Bank of Ireland.
    72. Sean P. Grover & Kevin L. Kliesen & Michael W. McCracken, 2016. "A Macroeconomic News Index for Constructing Nowcasts of U.S. Real Gross Domestic Product Growth," Review, Federal Reserve Bank of St. Louis, vol. 98(4), pages 277-296.
    73. Steffen Henzel & Johannes Mayr, 2009. "The Virtues of VAR Forecast Pooling – A DSGE Model Based Monte Carlo Study," ifo Working Paper Series 65, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    74. Kuang-Liang Chang & Nan-Kuang Chen & Charles Ka Yui Leung, 2016. "Losing Track of the Asset Markets: the Case of Housing and Stock," International Real Estate Review, Global Social Science Institute, vol. 19(4), pages 435-492.
    75. Shahnaz Parsaeian, 2023. "Structural Breaks in Seemingly Unrelated Regression Models," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202308, University of Kansas, Department of Economics.
    76. 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.
    77. Christian Kascha & Francesco Ravazzolo, 2008. "Combining inflation density forecasts," Working Paper 2008/22, Norges Bank.
    78. Xiaojie Xu, 2020. "Corn Cash Price Forecasting," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(4), pages 1297-1320, August.
    79. 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.
    80. Mamdouh Abdelmoula M. ABDELSALAM, 2017. "Improving Phillips Curve’s Inflation Forecasts under Misspecification," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 54-76, September.
    81. Shahid IQBAL & Maqbool H. SIAL, 2016. "Projections of Inflation Dynamics for Pakistan: GMDH Approach," Journal of Economics and Political Economy, KSP Journals, vol. 3(3), pages 536-559, September.
    82. Wang, Xiaoqian & Hyndman, Rob J. & Li, Feng & Kang, Yanfei, 2023. "Forecast combinations: An over 50-year review," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1518-1547.
    83. Clark, Todd E. & Doh, Taeyoung, 2014. "Evaluating alternative models of trend inflation," International Journal of Forecasting, Elsevier, vol. 30(3), pages 426-448.
    84. Schumacher, Christian, 2016. "A comparison of MIDAS and bridge equations," International Journal of Forecasting, Elsevier, vol. 32(2), pages 257-270.
    85. Francisco Blasques & Siem Jan Koopman & André Lucas, 2014. "Optimal Formulations for Nonlinear Autoregressive Processes," Tinbergen Institute Discussion Papers 14-103/III, Tinbergen Institute.
    86. Drachal, Krzysztof, 2021. "Forecasting crude oil real prices with averaging time-varying VAR models," Resources Policy, Elsevier, vol. 74(C).
    87. Ard Reijer & Andreas Johansson, 2019. "Nowcasting Swedish GDP with a large and unbalanced data set," Empirical Economics, Springer, vol. 57(4), pages 1351-1373, October.
    88. Todd E. Clark & Michael W. McCracken, 2013. "Evaluating the accuracy of forecasts from vector autoregressions," Working Papers 2013-010, Federal Reserve Bank of St. Louis.

  42. Todd E. Clark & Michael W. McCracken, 2007. "Forecasting with small macroeconomic VARs in the presence of instabilities," Finance and Economics Discussion Series 2007-41, Board of Governors of the Federal Reserve System (U.S.).

    Cited by:

    1. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    2. Carlo Altavilla & Matteo Ciccarelli, 2011. "Monetary Policy Analysis in Real-Time. Vintage Combination from a Real-Time Dataset," CESifo Working Paper Series 3372, CESifo.
    3. Giannone, Domenico & D’Agostino, Antonello & Gambetti, Luca, 2009. "Macroeconomic Forecasting and Structural Change," CEPR Discussion Papers 7542, C.E.P.R. Discussion Papers.
    4. Rubaszek, Michal & Skrzypczynski, Pawel, 2008. "On the forecasting performance of a small-scale DSGE model," International Journal of Forecasting, Elsevier, vol. 24(3), pages 498-512.
    5. Michal Rubaszek & Pawel Skrzypczynski, 2007. "Can a simple DSGE model outperform Professional Forecasters?," NBP Working Papers 43, Narodowy Bank Polski.
    6. Colino, Evelyn V. & Irwin, Scott H. & Garcia, Philip, 2008. "How Much Can Outlook Forecasts be Improved? An Application to the U.S. Hog Market," 2008 Conference, April 21-22, 2008, St. Louis, Missouri 37620, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    7. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2015. "Bayesian VARs: Specification Choices and Forecast Accuracy," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(1), pages 46-73, January.
    8. David F. Hendry & Kirstin Hubrich, 2011. "Combining Disaggregate Forecasts or Combining Disaggregate Information to Forecast an Aggregate," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(2), pages 216-227, April.
    9. Karsten R. Gerdrup & Anne Sofie Jore & Christie Smith & Leif Anders Thorsrud, 2009. "Evaluating ensemble density combination - forecasting GDP and inflation," Working Paper 2009/19, Norges Bank.
    10. Albuquerque, Bruno & Baumann, Ursel & Seitz, Franz, 2016. "What does money and credit tell us about real activity in the United States?," The North American Journal of Economics and Finance, Elsevier, vol. 37(C), pages 328-347.
    11. David Hendry & Michael P. Clements, 2010. "Forecasting from Mis-specified Models in the Presence of Unanticipated Location Shifts," Economics Series Working Papers 484, University of Oxford, Department of Economics.
    12. Huang, Tao & Fildes, Robert & Soopramanien, Didier, 2019. "Forecasting retailer product sales in the presence of structural change," European Journal of Operational Research, Elsevier, vol. 279(2), pages 459-470.
    13. Edward S. Knotek, 2007. "How useful is Okun's law?," Economic Review, Federal Reserve Bank of Kansas City, vol. 92(Q IV), pages 73-103.
    14. Rossi, Barbara & Sekhposyan, Tatevik, 2010. "Have economic models' forecasting performance for US output growth and inflation changed over time, and when?," International Journal of Forecasting, Elsevier, vol. 26(4), pages 808-835, October.

  43. Todd E. Clark & Michael W. McCracken, 2007. "Tests of equal predictive ability with real-time data," Research Working Paper RWP 07-06, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Christian Hutter & Enzo Weber, 2015. "Constructing a new leading indicator for unemployment from a survey among German employment agencies," Applied Economics, Taylor & Francis Journals, vol. 47(33), pages 3540-3558, July.
    2. Galvão, Ana Beatriz, 2013. "Changes in predictive ability with mixed frequency data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 395-410.
    3. Aaron J. Amburgey & Michael W. McCracken, 2023. "On the real‐time predictive content of financial condition indices for growth," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(2), pages 137-163, March.
    4. Dany Brouillette & Marie-Noëlle Robitaille & Laurence Savoie-Chabot & Pierre St-Amant & Bassirou Gueye & Elise Martin, 2019. "The Trend Unemployment Rate in Canada: Searching for the Unobservable," Staff Working Papers 19-13, Bank of Canada.
    5. Clark, Todd & McCracken, Michael, 2013. "Advances in Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1107-1201, Elsevier.
    6. Andres Fernandez & Norman R. Swanson, 2009. "Real-time datasets really do make a difference: definitional change, data release, and forecasting," Working Papers 09-28, Federal Reserve Bank of Philadelphia.
    7. Tanya, Molodtsova & Nikolsko-Rzhevskyy, Alex & Papell, David, 2008. "Taylor Rules and the Euro," MPRA Paper 11348, University Library of Munich, Germany.
    8. Baumeister, Christiane & Kilian, Lutz, 2013. "Are product spreads useful for forecasting? An empirical evaluation of the Verleger hypothesis," CFS Working Paper Series 2013/09, Center for Financial Studies (CFS).
    9. Augustus J. Panton, 2020. "Climate hysteresis and monetary policy," CAMA Working Papers 2020-76, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    10. Edward S. Knotek & Saeed Zaman, 2014. "Nowcasting U.S. Headline and Core Inflation," Working Papers (Old Series) 1403, Federal Reserve Bank of Cleveland.
    11. Marcelle Chauvet & Zeynep Senyuz & Emre Yoldas, 2013. "What does financial volatility tell us about macroeconomic fluctuations?," Finance and Economics Discussion Series 2013-61, Board of Governors of the Federal Reserve System (U.S.).
    12. Francesco Ravazzolo & Philip Rothman, 2011. "Oil and US GDP: A Real-Time out-of Sample Examination," Working Papers No 2/2011, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    13. Edward S. Knotek & Saeed Zaman, 2017. "Financial Nowcasts and Their Usefulness in Macroeconomic Forecasting," Working Papers (Old Series) 1702, Federal Reserve Bank of Cleveland.
    14. Philippe de Peretti & Oren Tapiero, 2014. "A GARCH analysis of dark-pool trades," Post-Print hal-00984834, HAL.
    15. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2012. "Real-time nowcasting with a Bayesian mixed frequency model with stochastic volatility," Working Papers (Old Series) 1227, Federal Reserve Bank of Cleveland.
    16. Lise Pichette & Marie-Noëlle Robitaille, 2017. "Assessing the Business Outlook Survey Indicator Using Real-Time Data," Discussion Papers 17-5, Bank of Canada.
    17. Heij, Christiaan & van Dijk, Dick & Groenen, Patrick J.F., 2011. "Real-time macroeconomic forecasting with leading indicators: An empirical comparison," International Journal of Forecasting, Elsevier, vol. 27(2), pages 466-481, April.
    18. John W. Galbraith & Greg Tkacz, 2013. "Nowcasting GDP: Electronic Payments, Data Vintages and the Timing of Data Releases," CIRANO Working Papers 2013s-25, CIRANO.
    19. Kim, Hyun Hak & Swanson, Norman R., 2018. "Mining big data using parsimonious factor, machine learning, variable selection and shrinkage methods," International Journal of Forecasting, Elsevier, vol. 34(2), pages 339-354.
    20. Baumeister, Christiane & Guérin, Pierre & Kilian, Lutz, 2015. "Do high-frequency financial data help forecast oil prices? The MIDAS touch at work," International Journal of Forecasting, Elsevier, vol. 31(2), pages 238-252.
    21. Katja Heinisch & Rolf Scheufele, 2019. "Should Forecasters Use Real‐Time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence," German Economic Review, Verein für Socialpolitik, vol. 20(4), pages 170-200, November.
    22. Knut Are Aastveit & Tuva Marie Fastbø & Eleonora Granziera & Kenneth Sæterhagen Paulsen & Kjersti Næss Torstensen, 2020. "Nowcasting Norwegian household consumption with debit card transaction data," Working Paper 2020/17, Norges Bank.
    23. Calista Cheung & Luke Frymire & Lise Pichette, 2020. "Can the Business Outlook Survey Help Improve Estimates of the Canadian Output Gap?," Discussion Papers 2020-14, Bank of Canada.
    24. Alfonso Mendoza Velázquez & Peter N. Smith, 2013. "Equity Returns and the Business Cycle: The Role of Supply and Demand Shocks," CAMA Working Papers 2013-22, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    25. Guido Bulligan & Roberto Golinelli & Giuseppe Parigi, 2010. "Forecasting industrial production: the role of information and methods," IFC Bulletins chapters, in: Bank for International Settlements (ed.), The IFC's contribution to the 57th ISI Session, Durban, August 2009, volume 33, pages 227-235, Bank for International Settlements.
    26. Todd E. Clark & Michael W. McCracken, 2010. "Averaging forecasts from VARs with uncertain instabilities," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 5-29.
    27. Kohei Maehashi & Mototsugu Shintani, 2020. "Macroeconomic Forecasting Using Factor Models and Machine Learning: An Application to Japan," CIRJE F-Series CIRJE-F-1146, CIRJE, Faculty of Economics, University of Tokyo.
    28. Garratt, Anthony & Koop, Gary & Mise, Emi & Vahey, Shaun P., 2009. "Real-Time Prediction With U.K. Monetary Aggregates in the Presence of Model Uncertainty," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 480-491.
    29. Timmermann, Allan & Elliott, Graham, 2007. "Economic Forecasting," CEPR Discussion Papers 6158, C.E.P.R. Discussion Papers.
    30. Q. Farooq Akram, 2010. "Policy analysis in real time using IMF's monetary model," Working Paper 2010/10, Norges Bank.
    31. Todd E. Clark & Michael W. McCracken, 2010. "Testing for unconditional predictive ability," Working Papers 2010-031, Federal Reserve Bank of St. Louis.
    32. Anne Sofie Jore & James Mitchell & Shaun Vahey, 2008. "Combining Forecast Densities from VARs with Uncertain Instabilities," Reserve Bank of New Zealand Discussion Paper Series DP2008/18, Reserve Bank of New Zealand.
    33. Pichette, Lise & Robitaille, Marie-Noëlle & Salameh, Mohanad & St-Amant, Pierre, 2019. "Dismiss the output gaps? To use with caution given their limitations," Economic Modelling, Elsevier, vol. 76(C), pages 199-215.
    34. 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.
    35. Michael P. Clements & Ana Beatriz Galvão, 2009. "Forecasting US output growth using leading indicators: an appraisal using MIDAS models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(7), pages 1187-1206, November.
    36. Christiane Baumeister & Lutz Kilian, 2014. "What Central Bankers Need To Know About Forecasting Oil Prices," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 55(3), pages 869-889, August.
    37. Groen, Jan J.J. & Kapetanios, George & Price, Simon, 2009. "A real time evaluation of Bank of England forecasts of inflation and growth," International Journal of Forecasting, Elsevier, vol. 25(1), pages 74-80.
    38. Dean Croushore, 2011. "Frontiers of Real-Time Data Analysis," Journal of Economic Literature, American Economic Association, vol. 49(1), pages 72-100, March.
    39. Norman R. Swanson & Valentina Corradi & Andres Fernandez, 2011. "Information in the Revision Process of Real-Time Datasets," Departmental Working Papers 201107, Rutgers University, Department of Economics.
    40. Nima Nonejad, 2022. "New Findings Regarding the Out-of-Sample Predictive Impact of the Price of Crude Oil on the United States Industrial Production," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 18(1), pages 1-35, March.
    41. Faust, Jon & Wright, Jonathan H., 2013. "Forecasting Inflation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 2-56, Elsevier.
    42. Guérin, Pierre & Maurin, Laurent & Mohr, Matthias, 2015. "Trend-Cycle Decomposition Of Output And Euro Area Inflation Forecasts: A Real-Time Approach Based On Model Combination," Macroeconomic Dynamics, Cambridge University Press, vol. 19(2), pages 363-393, March.
    43. Beckers, Benjamin, 2015. "The real-time predictive content of asset price bubbles for macro forecasts," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112852, Verein für Socialpolitik / German Economic Association.
    44. Knut Are Aastveit & Claudia Foroni & Francesco Ravazzolo, 2017. "Density Forecasts With Midas Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(4), pages 783-801, June.
    45. Marcellino, Massimiliano & Foroni, Claudia, 2014. "Markov-Switching Mixed-Frequency VAR Models," CEPR Discussion Papers 9815, C.E.P.R. Discussion Papers.
    46. Francis X. Diebold, 2012. "Comparing Predictive Accuracy, Twenty Years Later: A Personal Perspective on the Use and Abuse of Diebold-Mariano Tests," PIER Working Paper Archive 12-035, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    47. Xueting Yu & Yuhan Zhu & Guangming Lv, 2020. "Analysis of the Impact of China’s GDP Data Revision on Monetary Policy from the Perspective of Uncertainty," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 56(6), pages 1251-1274, May.
    48. Todd E. Clark & Michael W. McCracken, 2008. "Tests of equal predictive ability with real-time data," Working Papers 2008-029, Federal Reserve Bank of St. Louis.
    49. Michael P. Clements & Ana Beatriz Galvão, 2007. "Macroeconomic Forecasting with Mixed Frequency Data: Forecasting US Output Growth," Working Papers 616, Queen Mary University of London, School of Economics and Finance.
    50. Barnett, Alina & Mumtaz, Haroon & Theodoridis, Konstantinos, 2014. "Forecasting UK GDP growth and inflation under structural change. A comparison of models with time-varying parameters," International Journal of Forecasting, Elsevier, vol. 30(1), pages 129-143.
    51. Christian Hutter, 2020. "A new indicator for nowcasting employment subject to social security contributions in Germany," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 54(1), pages 1-10, December.
    52. Marcellino, Massimiliano, 2011. "Markov-switching MIDAS models," CEPR Discussion Papers 8234, C.E.P.R. Discussion Papers.
    53. Christiane Baumeister & Lutz Kilian, 2011. "Real-Time Forecasts of the Real Price of Oil," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(2), pages 326-336, September.
    54. Heinisch, Katja, 2016. "A real-time analysis on the importance of hard and soft data for nowcasting German GDP," VfS Annual Conference 2016 (Augsburg): Demographic Change 145864, Verein für Socialpolitik / German Economic Association.
    55. Golinelli, Roberto & Parigi, Giuseppe, 2008. "Real-time squared: A real-time data set for real-time GDP forecasting," International Journal of Forecasting, Elsevier, vol. 24(3), pages 368-385.
    56. Rapach, David E. & Strauss, Jack K., 2012. "Forecasting US state-level employment growth: An amalgamation approach," International Journal of Forecasting, Elsevier, vol. 28(2), pages 315-327.
    57. Wang, Yudong & Liu, Li & Wu, Chongfeng, 2017. "Forecasting the real prices of crude oil using forecast combinations over time-varying parameter models," Energy Economics, Elsevier, vol. 66(C), pages 337-348.
    58. Hyun Hak Kim & Norman Swanson, 2013. "Mining Big Data Using Parsimonious Factor and Shrinkage Methods," Departmental Working Papers 201316, Rutgers University, Department of Economics.
    59. Valentina Raponi & Cecilia Frale, 2014. "Revisions in official data and forecasting," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(3), pages 451-472, August.
    60. Marcellino, Massimiliano & Musso, Alberto, 2010. "The Forecasting Performance of Real Time Estimates of the Euro Area Output Gap," CEPR Discussion Papers 7763, C.E.P.R. Discussion Papers.
    61. Garciga, Christian & Knotek II, Edward S., 2019. "Forecasting GDP growth with NIPA aggregates: In search of core GDP," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1814-1828.
    62. Lise Pichette & Marie-Noëlle Robitaille & Mohanad Salameh & Pierre St-Amant, 2018. "Dismiss the Gap? A Real-Time Assessment of the Usefulness of Canadian Output Gaps in Forecasting Inflation," Staff Working Papers 18-10, Bank of Canada.
    63. Guido Bulligan & Roberto Golinelli & Giuseppe Parigi, 2010. "Forecasting monthly industrial production in real-time: from single equations to factor-based models," Empirical Economics, Springer, vol. 39(2), pages 303-336, October.
    64. Cecilia Frale & Valentina Raponi, 2011. "Revisions in ocial data and forecasting," Working Papers LuissLab 1194, Dipartimento di Economia e Finanza, LUISS Guido Carli.
    65. Philippe de Peretti & Oren Tapiero, 2014. "A GARCH analysis of dark-pool trades," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00984834, HAL.
    66. Matthieu Lemoine & Gian Luigi Mazzi & Paola Monperrus-Veroni & Frédéric Reynes, 2010. "A new production function estimate of the euro area output gap This paper is based on a report for Eurostat: 'Real time estimation of potential output, output gap, NAIRU and Phillips curve for Euro-zo," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 29-53.
    67. Marcellino, Massimiliano & Musso, Alberto, 2010. "Real time estimates of the euro area output gap: reliability and forecasting performance," Working Paper Series 1157, European Central Bank.
    68. Francesco Ravazzolo & Philip Rothman, 2015. "Oil-Price Density Forecasts of U.S. GDP," Working Papers No 10/2015, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    69. 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.
    70. Todd E. Clark & Michael W. McCracken, 2013. "Evaluating the accuracy of forecasts from vector autoregressions," Working Papers 2013-010, Federal Reserve Bank of St. Louis.

  44. Todd E. Clark & Michael W. McCracken, 2007. "Combining forecasts from nested models," Finance and Economics Discussion Series 2007-43, Board of Governors of the Federal Reserve System (U.S.).

    Cited by:

    1. Clark, Todd E. & McCracken, Michael W., 2015. "Nested forecast model comparisons: A new approach to testing equal accuracy," Journal of Econometrics, Elsevier, vol. 186(1), pages 160-177.
    2. Morales-Arias, Leonardo & Moura, Guilherme V., 2010. "A conditionally heteroskedastic global inflation model," Kiel Working Papers 1666, Kiel Institute for the World Economy (IfW Kiel).
    3. Todd E. Clark & Michael W. McCracken, 2010. "Averaging forecasts from VARs with uncertain instabilities," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 5-29.
    4. Han Hong & Bruce Preston, 2008. "Bayesian Averaging, Prediction and Nonnested Model Selection," NBER Working Papers 14284, National Bureau of Economic Research, Inc.
    5. 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.
    6. Antoine Mandel & Amir Sani, 2017. "A Machine Learning Approach to the Forecast Combination Puzzle," Working Papers halshs-01317974, HAL.
    7. Eric Hillebrand & Tae-Hwy Lee, 2012. "Stein-Rule Estimation and Generalized Shrinkage Methods for Forecasting Using Many Predictors," CREATES Research Papers 2012-18, Department of Economics and Business Economics, Aarhus University.
    8. Avci, Ezgi & Ketter, Wolfgang & van Heck, Eric, 2018. "Managing electricity price modeling risk via ensemble forecasting: The case of Turkey," Energy Policy, Elsevier, vol. 123(C), pages 390-403.
    9. 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.
    10. Todd E. Clark & Michael W. McCracken, 2006. "Forecasting of small macroeconomic VARs in the presence of instabilities," Research Working Paper RWP 06-09, Federal Reserve Bank of Kansas City.
    11. 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).
    12. Huiyu Huang & Tae-Hwy Lee, 2010. "To Combine Forecasts or to Combine Information?," Econometric Reviews, Taylor & Francis Journals, vol. 29(5-6), pages 534-570.
    13. James H. Stock & Mark W. Watson, 2008. "Phillips Curve Inflation Forecasts," NBER Working Papers 14322, National Bureau of Economic Research, Inc.
    14. Bordignon, Silvano & Bunn, Derek W. & Lisi, Francesco & Nan, Fany, 2013. "Combining day-ahead forecasts for British electricity prices," Energy Economics, Elsevier, vol. 35(C), pages 88-103.
    15. 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.
    16. Andrea Carriero & Raffaella Giacomini, 2011. "How useful are no-arbitrage restrictions for forecasting the term structure of interest rates?," Post-Print hal-00844809, HAL.

  45. Todd E. Clark & Michael W. McCracken, 2006. "Forecasting of small macroeconomic VARs in the presence of instabilities," Research Working Paper RWP 06-09, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Giannone, Domenico & D’Agostino, Antonello & Gambetti, Luca, 2009. "Macroeconomic Forecasting and Structural Change," CEPR Discussion Papers 7542, C.E.P.R. Discussion Papers.
    2. Todd E. Clark & Michael W. McCracken, 2010. "Averaging forecasts from VARs with uncertain instabilities," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 5-29.
    3. Çepni, Oğuzhan & Gül, Selçuk & Hacıhasanoğlu, Yavuz Selim & Yılmaz, Muhammed Hasan, 2020. "Global uncertainties and portfolio flow dynamics of the BRICS countries," Research in International Business and Finance, Elsevier, vol. 54(C).
    4. BRATU SIMIONESCU, Mihaela, 2012. "Two Quantitative Forecasting Methods For Macroeconomic Indicators In Czech Republic," Annals of Spiru Haret University, Economic Series, Universitatea Spiru Haret, vol. 3(1), pages 71-87.
    5. 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.

  46. Todd E. Clark & Kenneth D. West, 2005. "Using Out-of-Sample Mean Squared Prediction Errors to Test the Martingale Difference," NBER Technical Working Papers 0305, National Bureau of Economic Research, Inc.

    Cited by:

    1. Adriana Fernandez & Evan F. Koenig & Alex Nikolsko-Rzhevskyy, 2011. "A real-time historical database for the OECD," Globalization Institute Working Papers 96, Federal Reserve Bank of Dallas.
    2. West, Kenneth D., 2006. "Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 3, pages 99-134, Elsevier.
    3. Kenneth D. West & Todd Clark, 2006. "Approximately Normal Tests for Equal Predictive Accuracy in Nested Models," NBER Technical Working Papers 0326, National Bureau of Economic Research, Inc.
    4. Campbell, John & Thompson, Samuel P., 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," Scholarly Articles 2622619, Harvard University Department of Economics.
    5. Onur Ince & Tanya Molodtsova, 2013. "Real-Time Out-of-Sample Exchange Rate Predictability," Working Papers 13-03, Department of Economics, Appalachian State University.
    6. Carstensen Kai & Wohlrabe Klaus & Ziegler Christina, 2011. "Predictive Ability of Business Cycle Indicators under Test: A Case Study for the Euro Area Industrial Production," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 82-106, February.
    7. Lees, Kirdan & Matheson, Troy, 2007. "Mind your ps and qs! Improving ARMA forecasts with RBC priors," Economics Letters, Elsevier, vol. 96(2), pages 275-281, August.
    8. Ana María Abarca & Felipe Alarcón & Pablo Pincheira & Jorge Selaive, 2007. "Chilean Nominal Exchange Rate: Forecasting Based Upon Technical Analysis," Working Papers Central Bank of Chile 425, Central Bank of Chile.
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    250. Qiu, Mei & Pinfold, John F. & Rose, Lawrence C., 2011. "Predicting foreign exchange movements using historic deviations from PPP," International Review of Economics & Finance, Elsevier, vol. 20(4), pages 485-497, October.
    251. Nikolaos Karouzakis, 2021. "The role of time‐varying risk premia in international interbank markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5720-5745, October.
    252. Nonejad, Nima, 2022. "Understanding the conditional out-of-sample predictive impact of the price of crude oil on aggregate equity return volatility," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    253. Nicolas Hardy, 2022. "“A Bias Recognized Is a Bias Sterilized”: The Effects of a Bias in Forecast Evaluation," Mathematics, MDPI, vol. 10(2), pages 1-33, January.
    254. Dimitris A. Georgoutsos & Georgios P. Kouretas, 2017. "The Relevance of the Monetary Model for the Euro / USD Exchange Rate Determination: a Long Run Perspective," Open Economies Review, Springer, vol. 28(5), pages 989-1010, November.
    255. Harun Özkan & M. Yazgan, 2015. "Is forecasting inflation easier under inflation targeting?," Empirical Economics, Springer, vol. 48(2), pages 609-626, March.
    256. Ismailov, Adilzhan & Rossi, Barbara, 2018. "Uncertainty and deviations from uncovered interest rate parity," Journal of International Money and Finance, Elsevier, vol. 88(C), pages 242-259.
    257. , "undated". "," IPEK Working Papers 1509, Ipek University, Department of Economics.
    258. Jamali, Ibrahim & Yamani, Ehab, 2019. "Out-of-sample exchange rate predictability in emerging markets: Fundamentals versus technical analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 61(C), pages 241-263.
    259. Jonathan Hambur & Lynne Cockerell & Christopher Potter & Penelope Smith & Michelle Wright, 2015. "Modelling the Australian Dollar," RBA Research Discussion Papers rdp2015-12, Reserve Bank of Australia.
    260. Jacob Boudoukh & Matthew Richardson & Robert Whitelaw, 2005. "The Information in Long-Maturity Forward Rates: Implications for Exchange Rates and the Forward Premium Anomaly," NBER Working Papers 11840, National Bureau of Economic Research, Inc.
    261. Gozluklu, Arie & Morin, Annaïg, 2019. "Stock vs. Bond yields and demographic fluctuations," Journal of Banking & Finance, Elsevier, vol. 109(C).
    262. Barbara Rossi, 2012. "Comment on "Taylor Rule Exchange Rate Forecasting during the Financial Crisis"," NBER Chapters, in: NBER International Seminar on Macroeconomics 2012, pages 106-116, National Bureau of Economic Research, Inc.
    263. Todd E. Clark & Michael W. McCracken, 2013. "Evaluating the accuracy of forecasts from vector autoregressions," Working Papers 2013-010, Federal Reserve Bank of St. Louis.
    264. Ca' Zorzi, Michele & Kocięcki, Andrzej & Rubaszek, Michał, 2015. "Bayesian forecasting of real exchange rates with a Dornbusch prior," Economic Modelling, Elsevier, vol. 46(C), pages 53-60.

  50. Todd E. Clark & Sharon Kozicki, 2004. "Estimating equilibrium real interest rates in real time," Research Working Paper RWP 04-08, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Döpke, Jörg & Hartmann, Daniel & Pierdzioch, Christian, 2006. "Forecasting stock market volatility with macroeconomic variables in real time," Discussion Paper Series 2: Banking and Financial Studies 2006,01, Deutsche Bundesbank.
    2. Klaassen, Franc & Jager, Henk, 2011. "Definition-consistent measurement of exchange market pressure," Journal of International Money and Finance, Elsevier, vol. 30(1), pages 74-95, February.
    3. Sinclair, Tara M. & Gamber, Edward N. & Stekler, Herman & Reid, Elizabeth, 2012. "Jointly evaluating the Federal Reserve’s forecasts of GDP growth and inflation," International Journal of Forecasting, Elsevier, vol. 28(2), pages 309-314.
    4. Fabián Gredig, 2007. "Asymmetric Monetary Policy Rules and the Achievement of the Inflation Target: The Case of Chile," Working Papers Central Bank of Chile 451, Central Bank of Chile.
    5. Kathryn Holston & Thomas Laubach & John C. Williams, 2016. "Measuring the Natural Rate of Interest: International Trends and Determinants," Working Paper Series 2016-11, Federal Reserve Bank of San Francisco.
    6. Athanasios Orphanides, 2011. "Monetary Policy Lessons from the Crisis," Chapters, in: Sylvester Eijffinger & Donato Masciandaro (ed.), Handbook of Central Banking, Financial Regulation and Supervision, chapter 2, Edward Elgar Publishing.
    7. Ansgar Belke & Jens Klose, 2018. "Equilibrium Real Interest Rates, Secular Stagnation, and the Financial Cycle: Empirical Evidence for Euro-Area Member Countries," ROME Working Papers 201801, ROME Network.
    8. Michael T. Kiley, 2015. "What Can the Data Tell Us About the Equilibrium Real Interest Rate?," Finance and Economics Discussion Series 2015-77, Board of Governors of the Federal Reserve System (U.S.).
    9. Athanasios Orphanides & John C. Williams, 2008. "Imperfect knowledge and the pitfalls of optimal control monetary policy," Working Paper Series 2008-09, Federal Reserve Bank of San Francisco.
    10. Solikin M Juhro, 2016. "Comments on "A spectral perspective on natural interest rates in Asia-Pacific: changes and possible drivers"," BIS Papers chapters, in: Bank for International Settlements (ed.), Expanding the boundaries of monetary policy in Asia and the Pacific, volume 88, pages 151-156, Bank for International Settlements.
    11. Hans Dewachter, 2008. "Imperfect information, macroeconomic dynamics and the yield curve : an encompassing macro-finance model," Working Paper Research 144, National Bank of Belgium.
    12. Loretta J. Mester, 2015. "Comments on “The Equilibrium Real Funds Rate: Past, Present, and Future.”," Speech 52, Federal Reserve Bank of Cleveland.
    13. Richard G. Anderson & Michael Bordo & John V. Duca, 2016. "Money and Velocity During Financial Crises: From the Great Depression to the Great Recession," Economics Working Papers 16111, Hoover Institution, Stanford University.
    14. Richard G. Anderson, 2006. "Replicability, real-time data, and the science of economic research: FRED, ALFRED, and VDC," Review, Federal Reserve Bank of St. Louis, vol. 88(Jan), pages 81-93.
    15. Beyer, Robert & Milivojevic, Lazar, 2021. "Dynamics and synchronization of global equilibrium interest rates," IMFS Working Paper Series 146, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
    16. Enrico S. Levrero, 2019. "Estimates of the Natural Rate of Interest and the Stance of Monetary Policies: A Critical Assessment," Working Papers Series 88, Institute for New Economic Thinking.
    17. Sharon Kozicki & Peter A. Tinsley, 2005. "Minding the gap : central bank estimates of the unemployment natural rate," Research Working Paper RWP 05-03, Federal Reserve Bank of Kansas City.
    18. Mark A. Wynne & Ren Zhang, 2017. "Estimating the Natural Rate of Interest in an Open Economy," Globalization Institute Working Papers 316, Federal Reserve Bank of Dallas.
    19. Michael D. Bauer & Glenn D. Rudebusch, 2017. "Interest Rates Under Falling Stars," CESifo Working Paper Series 6571, CESifo.
    20. Athanasios Orphanides & John C. Williams, 2007. "Robust monetary policy with imperfect knowledge," Working Paper Series 2007-08, Federal Reserve Bank of San Francisco.
    21. Nikolsko-Rzhevskyy, Alex & Papell, David H. & Prodan, Ruxandra, 2019. "The Taylor principles," Journal of Macroeconomics, Elsevier, vol. 62(C).
    22. Fethi Oğunc & Inci Batmaz, 2009. "Estimating the neutral real interest rate in an emerging market economy," Applied Economics, Taylor & Francis Journals, vol. 43(6), pages 683-693.
    23. Todd E. Clark & Sharon Kozicki, 2004. "Estimating equilibrium real interest rates in real time," Research Working Paper RWP 04-08, Federal Reserve Bank of Kansas City.
    24. Kei Imakubo & Haruki Kojima & Jouchi Nakajima, 2015. "The natural yield curve: its concept and measurement," Bank of Japan Working Paper Series 15-E-5, Bank of Japan.
    25. Klose, Jens, 2020. "Equilibrium real interest rates for the BRICS countries," The Journal of Economic Asymmetries, Elsevier, vol. 21(C).
    26. Ansgar Belke & Jens Klose, 2017. "Equilibrium Real Interest Rates and Secular Stagnation: An Empirical Analysis for Euro Area Member Countries," Journal of Common Market Studies, Wiley Blackwell, vol. 55(6), pages 1221-1238, November.
    27. 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.
    28. Ansgar Belke & Jens Klose, 2010. "(How) Do the ECB and the Fed React to Financial Market Uncertainty?: The Taylor Rule in Times of Crisis," Discussion Papers of DIW Berlin 972, DIW Berlin, German Institute for Economic Research.
    29. Randal J. Verbrugge & Saeed Zaman, 2023. "The Hard Road to a Soft Landing: Evidence from a (Modestly) Nonlinear Structural Model," Working Papers 23-03, Federal Reserve Bank of Cleveland.
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    31. Michelle T. Armesto & William T. Gavin, 2005. "Monetary policy and commodity futures," Review, Federal Reserve Bank of St. Louis, vol. 87(May), pages 395-405.
    32. Trehan, Bharat & Wu, Tao, 2007. "Time-varying equilibrium real rates and monetary policy analysis," Journal of Economic Dynamics and Control, Elsevier, vol. 31(5), pages 1584-1609, May.
    33. Athanasios Orphanides & John C. Williams, 2007. "Inflation targeting under imperfect knowledge," Economic Review, Federal Reserve Bank of San Francisco, pages 1-23.
    34. Enrique Martínez García, 2020. "Get the Lowdown: The International Side of the Fall in the U.S. Natural Rate of Interest," Globalization Institute Working Papers 403, Federal Reserve Bank of Dallas, revised 20 Feb 2021.
    35. Ansgar Belke & Thorsten Polleit & Wim Kösters & Martin Leschke, 2006. "Money matters for inflation in the euro area," Diskussionspapiere aus dem Institut für Volkswirtschaftslehre der Universität Hohenheim 279/2006, Department of Economics, University of Hohenheim, Germany.
    36. Dean Croushore, 2011. "Frontiers of Real-Time Data Analysis," Journal of Economic Literature, American Economic Association, vol. 49(1), pages 72-100, March.
    37. Kose, M. Ayhan & Ha, Jongrim & Ohnsorge, Franziska, 2022. "Global Stagflation," CEPR Discussion Papers 17381, C.E.P.R. Discussion Papers.
    38. Paul Castillo & Carlos Montoro & Vicente Tuesta, 2006. "Measuring the Natural Interest Rate for the Peruvian Economy," Working Papers 2006-003, Banco Central de Reserva del Perú.
    39. Kurt F. Lewis & Francisco Vazquez-Grande, 2017. "Measuring the Natural Rate of Interest : A Note on Transitory Shocks," Finance and Economics Discussion Series 2017-059, Board of Governors of the Federal Reserve System (U.S.).
    40. Jean-Stephane Mesonnier, 2011. "The forecasting power of real interest rate gaps: an assessment for the Euro area," Applied Economics, Taylor & Francis Journals, vol. 43(2), pages 153-172.
    41. Krustev, Georgi, 2019. "The natural rate of interest and the financial cycle," Journal of Economic Behavior & Organization, Elsevier, vol. 162(C), pages 193-210.
    42. Feng Zhu, 2016. "A spectral perspective on natural interest rates in Asia-Pacific: changes and possible drivers," BIS Papers chapters, in: Bank for International Settlements (ed.), Expanding the boundaries of monetary policy in Asia and the Pacific, volume 88, pages 63-149, Bank for International Settlements.
    43. Ladislav Wintr & Paolo Guarda & Abdelaziz Rouabah, 2005. "Estimating the natural interest rate for the euro area and Luxembourg," BCL working papers 15, Central Bank of Luxembourg.
    44. Craig S. Hakkio & Andrew Lee Smith, 2017. "Bond Premiums and the Natural Real Rate of Interest," Economic Review, Federal Reserve Bank of Kansas City, issue Q I, pages 5-39.
    45. Joscha Beckmann & Klaus-Jürgen Gern & Nils Jannsen, 2022. "Should they stay or should they go? Negative interest rate policies under review," International Economics and Economic Policy, Springer, vol. 19(4), pages 885-912, October.
    46. Horvath, Roman, 2006. "Real-Time Time-Varying Equilibrium Interest Rates: Evidence on the Czech Republic," MPRA Paper 845, University Library of Munich, Germany.
    47. Rafael Cavalcanti De Araújo & Cleomar Gomes Da Silva, 2014. "The Neutral Interest Rate And The Stance Of Monetary Policy In Brazil," Anais do XLI Encontro Nacional de Economia [Proceedings of the 41st Brazilian Economics Meeting] 051, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    48. Wieland, Volker & Beyer, Robert, 2017. "Instability, imprecision and inconsistent use of equilibrium real interest rate estimates," CEPR Discussion Papers 11927, C.E.P.R. Discussion Papers.
    49. Jens H. E. Christensen & Glenn D. Rudebusch, 2018. "A New Normal for Interest Rates? Evidence from Inflation-Indexed Debt," Working Paper Series 2017-07, Federal Reserve Bank of San Francisco.
    50. Randal J. Verbrugge & Saeed Zaman, 2023. "Post-COVID Inflation Dynamics: Higher for Longer," Working Papers 23-06R, Federal Reserve Bank of Cleveland, revised 20 Jun 2023.
    51. Beyer, Robert C. M. & Wieland, Volker, 2015. "Schätzung des mittelfristigen Gleichgewichtszinses in den Vereinigten Staaten, Deutschland und dem Euro-Raum mit der Laubach-Williams-Methode," Working Papers 03/2015, German Council of Economic Experts / Sachverständigenrat zur Begutachtung der gesamtwirtschaftlichen Entwicklung.
    52. Mark A. Wynne & Ren Zhang, 2017. "Measuring the World Natural Rate of Interest," Globalization Institute Working Papers 315, Federal Reserve Bank of Dallas.
    53. John V. Duca & Tao Wu, 2009. "Regulation and the Neo-Wicksellian Approach to Monetary Policy," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(4), pages 799-807, June.
    54. Yuli Radev, 2015. "New dynamic disequilibrium," Economic Thought journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 6, pages 65-90.
    55. Naohisa Hirakata & Kazutoshi Kan & Akihiro Kanafuji & Yosuke Kido & Yui Kishaba & Tomonori Murakoshi & Takeshi Shinohara, 2019. "The Quarterly Japanese Economic Model (Q-JEM): 2019 version," Bank of Japan Working Paper Series 19-E-7, Bank of Japan.
    56. Umino, Shingo, 2014. "Real-time estimation of the equilibrium real interest rate: Evidence from Japan," The North American Journal of Economics and Finance, Elsevier, vol. 28(C), pages 17-32.
    57. Jens Klose, 2012. "Political business cycles and monetary policy revisited–an application of a two-dimensional asymmetric Taylor reaction function," International Economics and Economic Policy, Springer, vol. 9(3), pages 265-295, September.
    58. Ronny Mazzocchi, 2013. "Scope and Flaws of the New Neoclassical Synthesis," DEM Discussion Papers 2013/13, Department of Economics and Management.
    59. Benjamin K. Johannsen & Elmar Mertens, 2016. "A Time Series Model of Interest Rates With the Effective Lower Bound," Finance and Economics Discussion Series 2016-033, Board of Governors of the Federal Reserve System (U.S.).
    60. Dieter Gerdesmeier & Francesco Paolo Mongelli & Barbara Roffia, 2007. "The Eurosystem, the U.S. Federal Reserve, and the Bank of Japan: Similarities and Differences," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(7), pages 1785-1819, October.
    61. Mr. Andrea Pescatori & Mr. Jarkko Turunen, 2015. "Lower for Longer: Neutral Rates in the United States," IMF Working Papers 2015/135, International Monetary Fund.
    62. Döpke, Jörg & Hartmann, Daniel & Pierdzioch, Christian, 2008. "Real-time macroeconomic data and ex ante stock return predictability," International Review of Financial Analysis, Elsevier, vol. 17(2), pages 274-290.
    63. Rodrigo Fuentes & Fabián Gredig, 2007. "Estimating the Chilean Natural Rate of Interest," Working Papers Central Bank of Chile 448, Central Bank of Chile.
    64. Franc Klaassen & Henk Jager, 2007. "Model-free Measurement of Exchange Market Pressure," Tinbergen Institute Discussion Papers 06-112/2, Tinbergen Institute.
    65. Olmos, Lorena & Sanso Frago, Marcos, 2014. "Natural Rate of Interest with Endogenous Growth, Financial Frictions and Trend Inflation," MPRA Paper 57212, University Library of Munich, Germany.
    66. Dewachter, Hans & Iania, Leonardo & Lyrio, Marco, 2011. "A New-Keynesian Model of the Yield Curve with Learning Dynamics: A Bayesian Evaluation," Insper Working Papers wpe_250, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    67. Hiroshi Kawata & Yoshiyuki Kurachi & Koji Nakamura & Yuki Teranishi, 2013. "Impact of Macroprudential Policy Measures on Economic Dynamics: Simulation Using a Financial Macro-econometric Model," Bank of Japan Working Paper Series 13-E-3, Bank of Japan.
    68. Thomas Laubach & John C. Williams, 2015. "Measuring the natural rate of interest redux," Working Paper Series 2015-16, Federal Reserve Bank of San Francisco.
    69. Mésonnier, J-S., 2006. "The Reliability of Macroeconomic Forecasts based on Real Interest Rate Gap Estimates in Real Time: an Assessment for the Euro Area," Working papers 157, Banque de France.
    70. Zhang, Ren & Martínez-García, Enrique & Wynne, Mark A. & Grossman, Valerie, 2021. "Ties that bind: Estimating the natural rate of interest for small open economies," Journal of International Money and Finance, Elsevier, vol. 113(C).
    71. Bruno Feunou & Jean-Sébastien Fontaine, 2021. "Debt-Secular Economic Changes and Bond Yields," Staff Working Papers 21-14, Bank of Canada.
    72. Horváth, Roman, 2009. "The time-varying policy neutral rate in real-time: A predictor for future inflation?," Economic Modelling, Elsevier, vol. 26(1), pages 71-81, January.
    73. Brand, Claus & Bielecki, Marcin & Penalver, Adrian, 2018. "The natural rate of interest: estimates, drivers, and challenges to monetary policy JEL Classification: E52, E43," Occasional Paper Series 217, European Central Bank.
    74. Nikolsko-Rzhevskyy, Alex & Papell, David H. & Prodan, Ruxandra, 2021. "Policy Rules and Economic Performance," Journal of Macroeconomics, Elsevier, vol. 68(C).
    75. Rodrigo Fuentes S & Fabián Gredig U., 2008. "The Neutral Interest Rate: Estimates for Chile," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 11(2), pages 47-58, August.
    76. Ronny Mazzocchi, 2013. "Intertemporal Coordination Failure and Monetary Policy," DEM Discussion Papers 2013/15, Department of Economics and Management.
    77. Ronny Mazzocchi, 2013. "Monetary Policy when the NAIRI is unknown: The Fed and the Great Deviation," DEM Discussion Papers 2013/16, Department of Economics and Management.
    78. Alejandro Justiniano & Giorgio E. Primiceri, 2010. "Measuring the equilibrium real interest rate," Economic Perspectives, Federal Reserve Bank of Chicago, vol. 34(Q I), pages 14-27.
    79. Roman Horváth, 2007. "Estimating Time-Varying Policy Neutral Rate in Real Time," Working Papers IES 2007/01, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Jan 2007.
    80. FARAYIBI, Adesoji, 2016. "Stress Testing in the Nigerian Banking Sector," MPRA Paper 73615, University Library of Munich, Germany.
    81. Matteo Cacciatore & Dmitry Matveev & Rodrigo Sekkel, 2022. "Uncertainty and Monetary Policy Experimentation: Empirical Challenges and Insights from Academic Literature," Discussion Papers 2022-9, Bank of Canada.
    82. Jean-Philippe Cayen & Marc-André Gosselin & Sharon Kozicki, 2009. "Estimating DSGE-Model-Consistent Trends for Use in Forecasting," Staff Working Papers 09-35, Bank of Canada.
    83. Fu, Bowen, 2023. "Measuring the trend real interest rate in a data-rich environment," Journal of Economic Dynamics and Control, Elsevier, vol. 147(C).
    84. Belke, Ansgar & Klose, Jens, 2020. "Equilibrium real interest rates and the financial cycle: Empirical evidence for Euro area member countries," Economic Modelling, Elsevier, vol. 84(C), pages 357-366.
    85. Andrea Pescatori & Jarkko Turunen, 2016. "Lower for Longer: Neutral Rate in the U.S," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 64(4), pages 708-731, November.
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  51. Todd E. Clark & Michael W. McCracken, 2003. "The predictive content of the output gap for inflation : resolving in-sample and out-of-sample evidence," Research Working Paper RWP 03-06, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Ercio Muñoz S. & Alfredo Pistelli M., 2010. "¿Tienen los Terremotos un Impacto Inflacionario en el Corto Plazo? Evidencia para una Muestra de Países," Notas de Investigación Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 13(2), pages 113-127, April.
    2. Güneş Kamber & James Morley & Benjamin Wong, 2017. "Intuitive and Reliable Estimates of the Output Gap from a Beveridge-Nelson Filter," Reserve Bank of New Zealand Discussion Paper Series DP2017/01, Reserve Bank of New Zealand.
    3. Wu, Jyh-Lin & Wang, Yi-Chiuan, 2013. "Fundamentals, forecast combinations and nominal exchange-rate predictability," International Review of Economics & Finance, Elsevier, vol. 25(C), pages 129-145.
    4. Ayse Kabukcuoglu & Enrique Martínez-García, 2016. "What Helps Forecast U.S. Inflation?—Mind the Gap!," Koç University-TUSIAD Economic Research Forum Working Papers 1615, Koc University-TUSIAD Economic Research Forum.
    5. Clark, Todd E. & McCracken, Michael W., 2015. "Nested forecast model comparisons: A new approach to testing equal accuracy," Journal of Econometrics, Elsevier, vol. 186(1), pages 160-177.
    6. Raffella Giacomini & Barbara Rossi, 2005. "Detecting and Predicting Forecast Breakdowns," UCLA Economics Working Papers 845, UCLA Department of Economics.
    7. Camila Figueroa & Jorge Fornero & Pablo García, 2019. "Hindsight vs. Real time measurement of the output gap: Implications for the Phillips curve in the Chilean Case," Working Papers Central Bank of Chile 854, Central Bank of Chile.
    8. Edmond Berisha & David Gabauer & Rangan Gupta & Chi Keung Marco Lau, 2020. "Time-Varying Influence of Household Debt on Inequality in United Kingdom," Working Papers 202017, University of Pretoria, Department of Economics.
    9. Bec, Frédérique & Mogliani, Matteo, 2015. "Nowcasting French GDP in real-time with surveys and “blocked” regressions: Combining forecasts or pooling information?," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1021-1042.
    10. Qin, Ting & Enders, Walter, 2008. "In-sample and out-of-sample properties of linear and nonlinear Taylor rules," Journal of Macroeconomics, Elsevier, vol. 30(1), pages 428-443, March.
    11. Orphanides, Athanasios & van Norden, Simon, 2005. "The Reliability of Inflation Forecasts Based on Output Gap Estimates in Real Time," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 583-601, June.
    12. Mayer, Walter J. & Liu, Feng & Dang, Xin, 2017. "Improving the power of the Diebold–Mariano–West test for least squares predictions," International Journal of Forecasting, Elsevier, vol. 33(3), pages 618-626.
    13. Zhang, Qian & Li, Zeguang, 2021. "Time-varying risk attitude and the foreign exchange market behavior," Research in International Business and Finance, Elsevier, vol. 57(C).
    14. Don H. Kim, 2008. "Challenges in macro-finance modeling," Finance and Economics Discussion Series 2008-06, Board of Governors of the Federal Reserve System (U.S.).
    15. Andreas Billmeier, 2006. "Measuring a Roller Coaster: Evidence on the Finnish Output Gap," Finnish Economic Papers, Finnish Economic Association, vol. 19(2), pages 69-83, Autumn.
    16. Yonglian Wang & Lijun Wang & Han Liu & Yongjing Wang, 2021. "The Robust Causal Relationships Among Domestic Tourism Demand, Carbon Emissions, and Economic Growth in China," SAGE Open, , vol. 11(4), pages 21582440211, October.
    17. Karlsson, Sune & Österholm, Pär, 2018. "Is the US Phillips Curve Stable? Evidence from Bayesian VARs," Working Papers 2018:5, Örebro University, School of Business.
    18. Mr. Serhan Cevik & Tianle Zhu, 2019. "Trinity Strikes Back: Monetary Independence and Inflation in the Caribbean," IMF Working Papers 2019/197, International Monetary Fund.
    19. Rossi, Barbara & Wang, Yiru, 2019. "Vector autoregressive-based Granger causality test in the presence of instabilities," MPRA Paper 101492, University Library of Munich, Germany.
    20. Mehmet Balcilar & Gizem Uzuner & Festus Victor Bekun & Mark E. Wohar, 2023. "Housing price uncertainty and housing prices in the UK in a time-varying environment," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 50(2), pages 523-549, May.
    21. Quast, Josefine & Wolters, Maik H., 2019. "Reliable Real-time Output Gap Estimates Based on a Modified Hamilton Filter," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203535, Verein für Socialpolitik / German Economic Association.
    22. Driver, Ciaran & Trapani, Lorenzo & Urga, Giovanni, 2013. "On the use of cross-sectional measures of forecast uncertainty," International Journal of Forecasting, Elsevier, vol. 29(3), pages 367-377.
    23. Barbara Rossi & Yiru Wang, 2019. "VAR-Based Granger-Causality Test in the Presence of Instabilities," Working Papers 1083, Barcelona School of Economics.
    24. 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.
    25. Don H Kim & Athanasios Orphanides, 2007. "The bond market term premium: what is it, and how can we measure it?," BIS Quarterly Review, Bank for International Settlements, June.
    26. Peter Tillmann, 2009. "The Fed’s perceived Phillips curve: Evidence from individual FOMC forecasts," MAGKS Papers on Economics 200946, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    27. Michael W. McCracken & Todd E. Clark, 2003. "The Predictive Content of the Output Gap for Inflation: Resolving In-Sample and Out-of-Sample Evidence," Computing in Economics and Finance 2003 183, Society for Computational Economics.
    28. Todd E. Clark & Michael W. McCracken, 2010. "Averaging forecasts from VARs with uncertain instabilities," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 5-29.
    29. Aastveit, Knut Are & Trovik, Tørres, 2014. "Estimating the output gap in real time: A factor model approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(2), pages 180-193.
    30. Martha López P., 2003. "Efficient Policy Rule for Inflation Targeting in Colombia," Borradores de Economia 240, Banco de la Republica de Colombia.
    31. Massimo Guidolin & Manuela Pedio, 2022. "Switching Coefficients or Automatic Variable Selection: An Application in Forecasting Commodity Returns," Forecasting, MDPI, vol. 4(1), pages 1-32, February.
    32. James H. Stock & Mark W. Watson, 2007. "Why Has U.S. Inflation Become Harder to Forecast?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 3-33, February.
    33. Garratt, Anthony & Koop, Gary & Mise, Emi & Vahey, Shaun P., 2009. "Real-Time Prediction With U.K. Monetary Aggregates in the Presence of Model Uncertainty," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 480-491.
    34. Michael Dotsey & Shigeru Fujita & Tom Stark, 2011. "Do Phillips curves conditionally help to forecast inflation?," Working Papers 11-40, Federal Reserve Bank of Philadelphia.
    35. Todd E. Clark & Michael W. McCracken, 2010. "Testing for unconditional predictive ability," Working Papers 2010-031, Federal Reserve Bank of St. Louis.
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    37. Jeremy M. Piger & Robert H. Rasche, 2006. "Inflation: do expectations trump the gap?," Working Papers 2006-013, Federal Reserve Bank of St. Louis.
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    50. Frédérick Demers, 2003. "The Canadian Phillips Curve and Regime Shifting," Staff Working Papers 03-32, Bank of Canada.
    51. George Kapetanios & Vincent Labhard & Simon Price, 2007. "Forecast combination and the Bank of England’s suite of statistical forecasting models," Bank of England working papers 323, Bank of England.
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    54. Todd E. Clark & Michael W. McCracken, 2006. "Forecasting of small macroeconomic VARs in the presence of instabilities," Research Working Paper RWP 06-09, Federal Reserve Bank of Kansas City.
    55. Troy Matheson, 2006. "Phillips curve forecasting in a small open economy," Reserve Bank of New Zealand Discussion Paper Series DP2006/01, Reserve Bank of New Zealand.
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    57. Hilde C. Bjørnland & Leif Brubakk & Anne Sofie Jore, 2006. "Forecasting inflation with an uncertain output gap," Working Paper 2006/02, Norges Bank.
    58. Todd E. Clark & Michael W. McCracken, 2008. "Tests of equal predictive ability with real-time data," Working Papers 2008-029, Federal Reserve Bank of St. Louis.
    59. Barbara Rossi & Tatevik Sekhposyan, 2010. "Understanding Models' Forecasting Performance," Working Papers 10-56, Duke University, Department of Economics.
    60. Semei Coronado & Rangan Gupta & Saban Nazlioglu & Omar Rojas, 2020. "Time-Varying Causality between Bond and Oil Markets of the United States: Evidence from Over One and Half Centuries of Data," Working Papers 202006, University of Pretoria, Department of Economics.
    61. Scott Brave & Jonas D. M. Fisher, 2004. "In search of a robust inflation forecast," Economic Perspectives, Federal Reserve Bank of Chicago, vol. 28(Q IV), pages 12-31.
    62. Alexander Doser & Ricardo Nunes & Nikhil Rao & Viacheslav Sheremirov, 2023. "Inflation expectations and nonlinearities in the Phillips curve," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 453-471, June.
    63. Andrew Keinsley & Sandeep Kumar Rangaraju, 2021. "The Nonlinear Unemployment-Inflation Relationship and the Factors That Define It," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 47(3), pages 354-377, June.
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    65. Pablo Pincheira & Andrés Gatty, 2014. "Forecasting Chilean Inflation with International Factors," Working Papers Central Bank of Chile 723, Central Bank of Chile.
    66. Ahmad, Saad & Civelli, Andrea, 2016. "Globalization and inflation: A threshold investigation," Journal of Macroeconomics, Elsevier, vol. 48(C), pages 283-304.
    67. McCracken, Michael W., 2007. "Asymptotics for out of sample tests of Granger causality," Journal of Econometrics, Elsevier, vol. 140(2), pages 719-752, October.
    68. Don H. Kim, 2009. "Challenges in macro-finance modeling," Review, Federal Reserve Bank of St. Louis, vol. 91(Sep), pages 519-544.
    69. Manzan, Sebastiano & Zerom, Dawit, 2009. "Are Macroeconomic Variables Useful for Forecasting the Distribution of U.S. Inflation?," MPRA Paper 14387, University Library of Munich, Germany.
    70. Conti, Antonio M., 2021. "Resurrecting the Phillips Curve in Low-Inflation Times," Economic Modelling, Elsevier, vol. 96(C), pages 172-195.
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    72. Lee, Dong Jin & Yoon, Jai Hyung, 2016. "The New Keynesian Phillips Curve in multiple quantiles and the asymmetry of monetary policy," Economic Modelling, Elsevier, vol. 55(C), pages 102-114.
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    74. Serhan Cevik, João Tovar Jalles, 2023. "Eye of the Storm: The Impact of Climate Shocks on Inflation and Growth," Working Papers REM 2023/0276, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    75. Mésonnier, J-S., 2006. "The Reliability of Macroeconomic Forecasts based on Real Interest Rate Gap Estimates in Real Time: an Assessment for the Euro Area," Working papers 157, Banque de France.
    76. Daniel Borup & Bent Jesper Christensen & Yunus Emre Ergemen, 2019. "Assessing predictive accuracy in panel data models with long-range dependence," CREATES Research Papers 2019-04, Department of Economics and Business Economics, Aarhus University.
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    89. Todd E. Clark & Taisuke Nakata, 2008. "Has the behavior of inflation and long-term inflation expectations changed?," Economic Review, Federal Reserve Bank of Kansas City, vol. 93(Q I), pages 17-50.
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    91. Mr. Serhan Cevik & João Tovar Jalles, 2023. "Eye of the Storm: The Impact of Climate Shocks on Inflation and Growth," IMF Working Papers 2023/087, International Monetary Fund.

  52. Todd E. Clark, 2003. "Disaggregate evidence on the persistence of consumer price inflation," Research Working Paper RWP 03-11, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Frédérick Demers & Annie De Champlain, 2005. "Forecasting Core Inflation in Canada: Should We Forecast the Aggregate or the Components?," Staff Working Papers 05-44, Bank of Canada.
    2. Francis Leni Anguyo & Rangan Gupta & Kevin Kotzé, 2017. "Inflation Dynamics in Uganda: A Quantile Regression Approach," Working Papers 201772, University of Pretoria, Department of Economics.
    3. Cristina Conflitti and Matteo Luciani, 2019. "Oil Price Pass-through into Core Inflation," The Energy Journal, International Association for Energy Economics, vol. 0(Number 6).
    4. Byrne, Joseph P. & Kontonikas, Alexandros & Montagnoliz, Alberto, 2010. "International Evidence on the New Keynesian Phillips Curve Using Aggregate and Disaggregate Data," SIRE Discussion Papers 2010-57, Scottish Institute for Research in Economics (SIRE).
    5. Crucini, Mario J. & Shintani, Mototsugu & Tsuruga, Takayuki, 2010. "Accounting for persistence and volatility of good-level real exchange rates: The role of sticky information," Journal of International Economics, Elsevier, vol. 81(1), pages 48-60, May.
    6. Marios Zachariadis, 2012. "Global Versus Local Shocks in Micro Price Dynamics," 2012 Meeting Papers 66, Society for Economic Dynamics.
    7. Ryo Kato & Tatsushi Okuda, 2017. "Market Concentration and Sectoral Inflation under Imperfect Common Knowledge," IMES Discussion Paper Series 17-E-11, Institute for Monetary and Economic Studies, Bank of Japan.
    8. Francesco Ravazzolo & Shaun P. Vahey, 2010. "Forecast densities for economic aggregates from disaggregate ensembles," Working Paper 2010/02, Norges Bank.
    9. Ian Babetskii & Fabrizio Coricelli & Roman Horvath, 2009. "Assessing Inflation Persistence: Micro Evidence on an Inflation Targeting Economy," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00643340, HAL.
    10. Laura Mayoral, 2013. "Heterogeneous Dynamics, Aggregation, And The Persistence Of Economic Shocks," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 54(4), pages 1295-1307, November.
    11. Patrick Lünnemann & Thomas Y. Mathä, 2010. "Rigidities and inflation persistence of services and regulated prices," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 31(2-3), pages 193-208.
    12. Erdenebat Bataa & Denise R. Osborn & Marianne Sensier & Dick van Dijk, 2008. "Identifying Changes in Mean, Seasonality, Persistence and Volatility for G7 and Euro Area Inflation," Centre for Growth and Business Cycle Research Discussion Paper Series 109, Economics, The University of Manchester.
    13. Chong, Terence Tai Leung & Zhu, Tingting & Rafiq, M.S., 2013. "Are Prices Sticky in Large Developing Economies? An Empirical Comparison of China and India," MPRA Paper 60985, University Library of Munich, Germany.
    14. Espasa, Antoni & Carlomagno, Guillermo, 2014. "The pairwise approach to model a large set of disaggregates with common trends," DES - Working Papers. Statistics and Econometrics. WS ws141309, Universidad Carlos III de Madrid. Departamento de Estadística.
    15. Espasa, Antoni & Pino, Gabriel & Tena Horrillo, Juan de Dios, 2013. "Forecasting disaggregates by sectors and regions : the case of inflation in the euro area and Spain," DES - Working Papers. Statistics and Econometrics. WS ws130807, Universidad Carlos III de Madrid. Departamento de Estadística.
    16. Tatsushi Oka & Pierre Perron, 2016. "Testing for Common Breaks in a Multiple Equations System," Papers 1606.00092, arXiv.org, revised Jan 2018.
    17. Logan Rangasamy, 2011. "Food Inflation In South Africa: Some Implications For Economic Policy," South African Journal of Economics, Economic Society of South Africa, vol. 79(2), pages 184-201, June.
    18. Blazej Mazur, 2015. "Density forecasts based on disaggregate data: nowcasting Polish inflation," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 15, pages 71-87.
    19. Richiardi, Matteo & Valenzuela, Luis, 2019. "Firm Heterogeneity and the Aggregate Labour Share," INET Oxford Working Papers 2019-08, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.
    20. Hubrich, Kirstin & Marcellino, Massimiliano & Beck, Günter W., 2011. "On the importance of sectoral and regional shocks for price-setting," Working Paper Series 1334, European Central Bank.
    21. Chong, Terence Tai Leung & Wu, Zhang, 2018. "Price Rigidity in China: Empirical Results at Home and Abroad," MPRA Paper 92013, University Library of Munich, Germany.
    22. Filippo Altissimo & Benoit Mojon & Paolo Zaffaroni, 2007. "Fast micro and slow macro: can aggregation explain the persistence of inflation?," Working Paper Series WP-07-02, Federal Reserve Bank of Chicago.
    23. Todd E. Clark, 2003. "Disaggregate evidence on the persistence of consumer price inflation," Research Working Paper RWP 03-11, Federal Reserve Bank of Kansas City.
    24. Fröhling, Annette & Lommatzsch, Kirsten, 2011. "Output sensitivity of inflation in the euro area: Indirect evidence from disaggregated consumer prices," Discussion Paper Series 1: Economic Studies 2011,25, Deutsche Bundesbank.
    25. Tillmann, Peter & Wolters, Maik Hendrik, 2012. "The changing dynamics of US inflation persistence: A quantile regression approach," IMFS Working Paper Series 60, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
    26. Gantungalag Altansukh & Ralf Becker & George Bratsiotis & Denise R. Osborn, 2018. "Structural Breaks in International Inflation Linkages for OECD Countries," Centre for Growth and Business Cycle Research Discussion Paper Series 240, Economics, The University of Manchester.
    27. Steven Cook, 2009. "A re-examination of the stationarity of inflation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(6), pages 1047-1053.
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    29. James Yetman, 2009. "Hong Kong Consumer Prices are Flexible," Working Papers 052009, Hong Kong Institute for Monetary Research.
    30. Huw Dixon & Engin Kara, 2010. "Can We Explain Inflation Persistence in a Way that Is Consistent with the Microevidence on Nominal Rigidity?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(1), pages 151-170, February.
    31. Boivin, Jean & Giannoni, Marc P. & Mihov, Ilian, 2006. "Sticky prices and monetary policy: Evidence from disaggregated US data," CFS Working Paper Series 2007/14, Center for Financial Studies (CFS).
    32. Hännikäinen, Jari, 2016. "When does the yield curve contain predictive power? Evidence from a data-rich environment," MPRA Paper 70489, University Library of Munich, Germany.
    33. Simone Elmer & Thomas Maag, 2009. "The Persistence of Inflation in Switzerland," KOF Working papers 09-235, KOF Swiss Economic Institute, ETH Zurich.
    34. Altissimo, Filippo & Mojon, Benoit & Zaffaroni, Paolo, 2009. "Can aggregation explain the persistence of inflation?," Journal of Monetary Economics, Elsevier, vol. 56(2), pages 231-241, March.
    35. Laura Mayoral, 2009. "Heterogeneous dynamics, aggregation and the persistence of economic shocks," UFAE and IAE Working Papers 786.09, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
    36. Peter Tillmann, 2013. "Inflation Targeting and Regional Inflation Persistence: Evidence from Korea," Pacific Economic Review, Wiley Blackwell, vol. 18(2), pages 147-161, May.
    37. Bouakez, Hafedh & Cardia, Emanuela & Ruge-Murcia, Francisco, 2014. "Sectoral price rigidity and aggregate dynamics," European Economic Review, Elsevier, vol. 65(C), pages 1-22.
    38. Guglielmo Maria Caporale & Alexandros Kontonikas, 2006. "The Euro And Inflation Uncertainty In The European Monetary Union," Economics and Finance Discussion Papers 06-01, Economics and Finance Section, School of Social Sciences, Brunel University.
    39. Pongpitch Amatyakul & Deniz Igan & Marco Jacopo Lombardi, 2024. "Sectoral price dynamics in the last mile of post-Covid-19 disinflation," BIS Quarterly Review, Bank for International Settlements, March.
    40. Joseph P. Byrne & Alexandros Kontonikas & Alberto Montagnoli, 2010. "The Time‐Series Properties Of Uk Inflation: Evidence From Aggregate And Disaggregate Data," Scottish Journal of Political Economy, Scottish Economic Society, vol. 57(1), pages 33-47, February.
    41. Guillermo Carlomagno & Nicolas Eterovic & L. G. Hernández-Román, 2023. "Disentangling Demand and Supply Inflation Shocks from Chilean Electronic Payment Data," Working Papers Central Bank of Chile 986, Central Bank of Chile.
    42. Troy Davig & Taeyoung Doh, 2014. "Monetary Policy Regime Shifts and Inflation Persistence," The Review of Economics and Statistics, MIT Press, vol. 96(5), pages 862-875, December.
    43. Chiara Perricone, 2013. "Clustering Macroeconomic Variables," CEIS Research Paper 283, Tor Vergata University, CEIS, revised 11 Jun 2013.
    44. Pankaj Kumar, 2015. "Can Univariate Time Series Models of Inflation Help Discriminate Between Alternative Sources of Inflation PersistenceAuthor-Name: Naveen Srinivasan," Working Papers 2015-104, Madras School of Economics,Chennai,India.
    45. César Castro & Rebeca Jiménez-Rodríguez & Pilar Poncela & Eva Senra, 2017. "A new look at oil price pass-through into inflation: evidence from disaggregated European data," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 34(1), pages 55-82, April.
    46. Binder, Carola Conces, 2016. "Estimation of historical inflation expectations," Explorations in Economic History, Elsevier, vol. 61(C), pages 1-31.
    47. Dixon, Huw & Kara, Engin, 2006. "Understanding inflation persistence: a comparison of different models," Working Paper Series 672, European Central Bank.
    48. Rangan Gupta & Charl Jooste & Omid Ranjbar, 2015. "The Changing Dynamics of South Africa's Inflation Persistence: Evidence from a Quantile Regression Framework," Working Papers 201563, University of Pretoria, Department of Economics.
    49. Ryo Kato & Tatsushi Okuda & Takayuki Tsuruga, 2021. "Sectoral inflation persistence, market concentration, and imperfect common knowledge," Working Papers e165, Tokyo Center for Economic Research.
    50. Rafal Raciborski, 2008. "Searching for additional sources of inflation persistence : the micro-price panel data approach," Working Paper Research 132, National Bank of Belgium.
    51. Baumeister, Christiane & Liu, Philip & Mumtaz, Haroon, 2013. "Changes in the effects of monetary policy on disaggregate price dynamics," Journal of Economic Dynamics and Control, Elsevier, vol. 37(3), pages 543-560.
    52. Byrne, Joseph P. & Fazio, Giorgio & Fiess, Norbert, 2011. "Primary commodity prices : co-movements, common factors and fundamentals," Policy Research Working Paper Series 5578, The World Bank.
    53. Ian Babetskii & Fabrizio Coricelli & Roman Horvath, 2007. "Measuring and Explaining Inflation Persistence: Disaggregate Evidence on the Czech Republic," Working Papers 2007/1, Czech National Bank.
    54. Viacheslav Kramkov, 2023. "Does CPI disaggregation improve inflation forecast accuracy?," Bank of Russia Working Paper Series wps112, Bank of Russia.
    55. Bilke, L., 2005. "Break in the Mean and Persistence of Inflation: a Sectoral Analysis of French CPI," Working papers 122, Banque de France.
    56. Christian Bauer & Sebastian Weber, 2016. "The Efficiency of Monetary Policy when Guiding Inflation Expectations," Research Papers in Economics 2016-14, University of Trier, Department of Economics.
    57. Roy Cerqueti & Mauro Costantini & Luciano Gutierrez, 2009. "New panel tests to assess inflation persistence," Working Papers 54-2009, Macerata University, Department of Finance and Economic Sciences, revised Oct 2009.
    58. Gregory E. Givens & Robert R. Reed, 2018. "Monetary Policy and Investment Dynamics: Evidence from Disaggregate Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(8), pages 1851-1878, December.
    59. Khundrakpam, Jeevan K., 2008. "How Persistent is Indian Inflationary Process, Has it Changed?," MPRA Paper 50927, University Library of Munich, Germany.
    60. Carlomagno, Guillermo & Espasa, Antoni, 2016. "Discovering common trends in a large set of disaggregates: statistical procedures and their properties," DES - Working Papers. Statistics and Econometrics. WS ws1519, Universidad Carlos III de Madrid. Departamento de Estadística.
    61. Karl Whelan, 2005. "Testing parameter stability : a wild bootstrap approach," Open Access publications 10197/225, School of Economics, University College Dublin.
    62. Agnieszka Leszczynska & Katarzyna Hertel, 2013. "Inflation persistence – a disaggregated approach," EcoMod2013 5692, EcoMod.
    63. Rangan Gupta & Charl Jooste & Omid Ranjbar, 2017. "South Africa’s inflation persistence: a quantile regression framework," Economic Change and Restructuring, Springer, vol. 50(4), pages 367-386, November.
    64. Caglayan, Mustafa & Filiztekin, Alpay, 2015. "Price dynamics and market segmentation," Economics Letters, Elsevier, vol. 134(C), pages 94-97.
    65. Richard S. J. Tol & Francisco Estrada & Carlos Gay-García, 2012. "The persistence of shocks in GDP and the estimation of the potential economic costs of climate change," Working Paper Series 4312, Department of Economics, University of Sussex Business School.
    66. Senra, Eva & Espasa, Antoni, 2017. "22 Years of inflation assessment and forecasting experience at the bulletin of EU & US inflation and macroeconomic analysis," DES - Working Papers. Statistics and Econometrics. WS 24678, Universidad Carlos III de Madrid. Departamento de Estadística.
    67. Carlomagno, Guillermo & Espasa, Antoni, 2015. "Forecasting a large set of disaggregates with common trends and outliers," DES - Working Papers. Statistics and Econometrics. WS ws1518, Universidad Carlos III de Madrid. Departamento de Estadística.
    68. Tianfeng Li & June Wei, 2015. "Multiple Structural Breaks and Inflation Persistence: Evidence from China," Asian Economic Journal, East Asian Economic Association, vol. 29(1), pages 1-20, March.
    69. Logan Rangasamy, 2009. "Inflation Persistence And Core Inflation: The Case Of South Africa," South African Journal of Economics, Economic Society of South Africa, vol. 77(3), pages 430-444, September.
    70. Adam Check & Jeremy Piger, 2021. "Structural Breaks in U.S. Macroeconomic Time Series: A Bayesian Model Averaging Approach," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 53(8), pages 1999-2036, December.
    71. Choi, Chi-Young & O'Sullivan, Róisín, 2013. "Heterogeneous response of disaggregate inflation to monetary policy regime change: The role of price stickiness," Journal of Economic Dynamics and Control, Elsevier, vol. 37(9), pages 1814-1832.
    72. Kumar, Ankit & Dash, Pradyumna, 2020. "Changing transmission of monetary policy on disaggregate inflation in India," Economic Modelling, Elsevier, vol. 92(C), pages 109-125.
    73. Katsurako Sonoda, 2006. "An Empirical Analysis of Price Stickiness and Price Revision Behavior in Japan Using Micro CPI Data," Bank of Japan Working Paper Series 06-E-8, Bank of Japan.
    74. Byrne, Joseph P & Fazio, Giorgio & Fiess, Norbert, 2010. "Optimism and commitment: An elementary theory of bargaining and war," SIRE Discussion Papers 2010-102, Scottish Institute for Research in Economics (SIRE).
    75. Mr. James P Walsh, 2011. "Reconsidering the Role of Food Prices in Inflation," IMF Working Papers 2011/071, International Monetary Fund.
    76. Choi, Chi-Young & Matsubara, Kiyoshi, 2007. "Heterogeneity in the persistence of relative prices: What do the Japanese cities tell us?," Journal of the Japanese and International Economies, Elsevier, vol. 21(2), pages 260-286, June.
    77. Chi-Young Choi & Joo Yong Lee & Róisín O'Sullivan, 2015. "Monetary Policy Regime Change and Regional Inflation Dynamics: Looking through the Lens of Sector-Level Data for Korea," Working Papers 2015-20, Economic Research Institute, Bank of Korea.
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  53. Todd E. Clark & Michael W. McCracken, 2002. "Forecast-based model selection in the presence of structural breaks," Research Working Paper RWP 02-05, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Ayse Kabukcuoglu & Enrique Martínez-García, 2016. "What Helps Forecast U.S. Inflation?—Mind the Gap!," Koç University-TUSIAD Economic Research Forum Working Papers 1615, Koc University-TUSIAD Economic Research Forum.
    2. Kilian, Lutz & Inoue, Atsushi, 2002. "In-Sample or Out-of-Sample Tests of Predictability: Which One Should We Use?," CEPR Discussion Papers 3671, C.E.P.R. Discussion Papers.
    3. Corradi, Valentina & Swanson, Norman R., 2006. "Predictive density and conditional confidence interval accuracy tests," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 187-228.
    4. Michael W. McCracken & Todd E. Clark, 2003. "The Predictive Content of the Output Gap for Inflation: Resolving In-Sample and Out-of-Sample Evidence," Computing in Economics and Finance 2003 183, Society for Computational Economics.
    5. Jorge Selaive & Vicente Tuesta, 2004. "Can Fluctuations in the Consumption-Wealth Ratio Help to Predict Exchange Rates?," International Finance 0404014, University Library of Munich, Germany.
    6. Rapach, David E. & Wohar, Mark E. & Rangvid, Jesper, 2005. "Macro variables and international stock return predictability," International Journal of Forecasting, Elsevier, vol. 21(1), pages 137-166.
    7. Burns, Kelly & Moosa, Imad A., 2015. "Enhancing the forecasting power of exchange rate models by introducing nonlinearity: Does it work?," Economic Modelling, Elsevier, vol. 50(C), pages 27-39.

  54. Todd E. Clark & Michael W. McCracken, 2001. "Evaluating long-horizon forecasts," Research Working Paper RWP 01-14, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Martin D. D. Evans & Richard K. Lyons, 2017. "Meese-Rogoff Redux: Micro-Based Exchange-Rate Forecasting," World Scientific Book Chapters, in: Studies in Foreign Exchange Economics, chapter 11, pages 457-475, World Scientific Publishing Co. Pte. Ltd..
    2. Nelson C. Mark & Donggyu Sul, 2004. "The Use of Predictive Regressions at Alternative Horizons in Finance and Economics," Finance 0409032, University Library of Munich, Germany.
    3. Mehmet Balcilar & Rangan Gupta & Stephen M. Miller, 2012. "The Out-of-Sample Forecasting Performance of Non-Linear Models of Regional Housing Prices in the US," Working papers 2012-12, University of Connecticut, Department of Economics.
    4. Orphanides, Athanasios & van Norden, Simon, 2005. "The Reliability of Inflation Forecasts Based on Output Gap Estimates in Real Time," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 583-601, June.
    5. Barbara Rossi, 2007. "Expectations hypotheses tests at Long Horizons," Econometrics Journal, Royal Economic Society, vol. 10(3), pages 554-579, November.
    6. Clark, Todd E. & West, Kenneth D., 2006. "Using out-of-sample mean squared prediction errors to test the martingale difference hypothesis," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 155-186.
    7. Todd E. Clark & Kenneth D. West, 2005. "Using Out-of-Sample Mean Squared Prediction Errors to Test the Martingale Difference," NBER Technical Working Papers 0305, National Bureau of Economic Research, Inc.
    8. Bessec Marie & Bouabdallah Othman, 2005. "What Causes The Forecasting Failure of Markov-Switching Models? A Monte Carlo Study," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(2), pages 1-24, June.
    9. Michael W. McCracken & Todd E. Clark, 2003. "The Predictive Content of the Output Gap for Inflation: Resolving In-Sample and Out-of-Sample Evidence," Computing in Economics and Finance 2003 183, Society for Computational Economics.
    10. 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.
    11. Todd E. Clark & Michael W. McCracken, 2002. "Forecast-based model selection in the presence of structural breaks," Research Working Paper RWP 02-05, Federal Reserve Bank of Kansas City.
    12. Boucher, Christophe, 2006. "Stock prices-inflation puzzle and the predictability of stock market returns," Economics Letters, Elsevier, vol. 90(2), pages 205-212, February.
    13. McCracken, Michael W., 2007. "Asymptotics for out of sample tests of Granger causality," Journal of Econometrics, Elsevier, vol. 140(2), pages 719-752, October.
    14. Rapach, David E. & Wohar, Mark E., 2006. "The out-of-sample forecasting performance of nonlinear models of real exchange rate behavior," International Journal of Forecasting, Elsevier, vol. 22(2), pages 341-361.
    15. Mestre, Ricardo, 2007. "Are survey-based inflation expections in the euro area informative?," Working Paper Series 721, European Central Bank.
    16. Clark, Todd E. & McCracken, Michael W., 2005. "The power of tests of predictive ability in the presence of structural breaks," Journal of Econometrics, Elsevier, vol. 124(1), pages 1-31, January.
    17. Nombulelo Gumata & Alain Kabundi & Eliphas Ndou, 2013. "Important channels of transmission of monetary policy shock in South Africa," Working Papers 6021, South African Reserve Bank.
    18. Rapach, David E. & Wohar, Mark E. & Rangvid, Jesper, 2005. "Macro variables and international stock return predictability," International Journal of Forecasting, Elsevier, vol. 21(1), pages 137-166.
    19. Moser, Gabriel & Rumler, Fabio & Scharler, Johann, 2007. "Forecasting Austrian inflation," Economic Modelling, Elsevier, vol. 24(3), pages 470-480, May.
    20. Bruneau, C. & De Bandt, O. & Flageollet, A. & Michaux, E., 2003. "Forecasting Inflation using Economic Indicators: the Case of France," Working papers 101, Banque de France.
    21. Michael Steiner, 2009. "Predicting premiums for the market, size, value, and momentum factors," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 23(2), pages 137-155, June.
    22. Rapach, David E. & Wohar, Mark E., 2006. "In-sample vs. out-of-sample tests of stock return predictability in the context of data mining," Journal of Empirical Finance, Elsevier, vol. 13(2), pages 231-247, March.

  55. Todd E. Clark, 2000. "Can out-of-sample forecast comparisons help prevent overfitting?," Research Working Paper RWP 00-05, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Medel, Carlos A., 2012. "¿Akaike o Schwarz? ¿Cuál elegir para predecir el PIB chileno? [Akaike or Schwarz? Which One is a Better Predictor of Chilean GDP?]," MPRA Paper 35950, University Library of Munich, Germany.
    2. Clark, Todd & McCracken, Michael, 2013. "Advances in Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1107-1201, Elsevier.
    3. Calhoun, Gray, 2014. "Out-Of-Sample Comparisons of Overfit Models," Staff General Research Papers Archive 32462, Iowa State University, Department of Economics.
    4. Rangel, José Gonzalo, 2011. "Macroeconomic news, announcements, and stock market jump intensity dynamics," Journal of Banking & Finance, Elsevier, vol. 35(5), pages 1263-1276, May.
    5. Pereda, Javier, 2010. "Estimación de la Tasa Natural de Interés para el Perú: Un Enfoque Financiero," Working Papers 2010-018, Banco Central de Reserva del Perú.
    6. Österholm, Pär, 2009. "Improving Unemployment Rate Forecasts Using Survey Data," Working Papers 112, National Institute of Economic Research.
    7. Mogliani, Matteo & Darné, Olivier & Pluyaud, Bertrand, 2017. "The new MIBA model: Real-time nowcasting of French GDP using the Banque de France's monthly business survey," Economic Modelling, Elsevier, vol. 64(C), pages 26-39.
    8. Ippei Fujiwara & Maiko Koga, 2002. "A Statistical Forecasting Method for Inflation Forecasting," Bank of Japan Working Paper Series Research and Statistics D, Bank of Japan.
    9. McGurk, Zachary, 2020. "US real estate inflation prediction: Exchange rates and net foreign assets," The Quarterly Review of Economics and Finance, Elsevier, vol. 75(C), pages 53-66.
    10. Gelper, Sarah & Croux, Christophe, 2007. "Multivariate out-of-sample tests for Granger causality," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3319-3329, April.
    11. Pablo Pincheira & Jorge Selaive, 2011. "External imbalance, valuation adjustments and real Exchange rate: evidence of predictability in an emerging economy," Revista de Analisis Economico – Economic Analysis Review, Universidad Alberto Hurtado/School of Economics and Business, vol. 26(1), pages 107-125, Junio.
    12. Glocker, Christian & Kaniovski, Serguei, 2020. "Structural modeling and forecasting using a cluster of dynamic factor models," MPRA Paper 101874, University Library of Munich, Germany.
    13. Ismaël Rafaï & Thierry Blayac & Dimitri Dubois & Sebastien Duchene & Phu Nguyen-Van & Bruno Ventelou & Marc Willinger, 2023. "Stated preferences outperform elicited preferences for predicting reported compliance with Covid-19 prophylactic measures," Working Papers hal-04219784, HAL.
    14. Sinéad Keogh & Stephen O’Neill & Kieran Walsh, 2021. "Composite Measures for Assessing Multidimensional Social Exclusion in Later Life: Conceptual and Methodological Challenges," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 155(2), pages 389-410, June.
    15. Ana María Abarca G. & Felipe Alarcón G. & Pablo Pincheira B. & Jorge Selaive C., 2007. "Nominal Exchange Rate in Chile: Predictions based on technical analysis," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 10(2), pages 57-80, August.
    16. Karlsson, Sune & Österholm, Pär, 2018. "A Note on the Stability of the Swedish Philips Curve," Working Papers 2018:6, Örebro University, School of Business.
    17. Pao, H.T., 2009. "Forecasting energy consumption in Taiwan using hybrid nonlinear models," Energy, Elsevier, vol. 34(10), pages 1438-1446.
    18. Christian Glocker & Serguei Kaniovski, 2020. "Macroeconometric Forecasting Using a Cluster of Dynamic Factor Models," WIFO Working Papers 614, WIFO.
    19. Medel, Carlos A., 2014. "Probabilidad Clásica de Sobreajuste con Criterios de Información: Estimaciones con Series Macroeconómicas Chilenas [Classical Probability of Overfitting with Information Criteria: Estimations with ," MPRA Paper 57401, University Library of Munich, Germany.
    20. Gupta, Rangan & Modise, Mampho P., 2013. "Macroeconomic Variables and South African Stock Return Predictability," Economic Modelling, Elsevier, vol. 30(C), pages 612-622.
    21. Medel, Carlos A., 2012. "How informative are in-sample information criteria to forecasting? the case of Chilean GDP," MPRA Paper 35949, University Library of Munich, Germany.
    22. Ryan Compton & Syeed Khan, 2010. "An examination of the stability of short-run Canadian stock predictability," Economics Bulletin, AccessEcon, vol. 30(2), pages 1293-1306.
    23. Michael Graff, 2005. "Ein multisektoraler Sammelindikator fuer die Schweizer Konjunktur," KOF Working papers 05-107, KOF Swiss Economic Institute, ETH Zurich.
    24. Ramon E. Lopez & Kevin Sepulveda, 2022. "¿Cual es el efecto de shocks de demanda interna sobre la inflacion en una economia pequena y abierta? Chile 2000-2021," Working Papers wp529, University of Chile, Department of Economics.
    25. Carlos A. Medel & Sergio C. Salgado, 2012. "Does BIC Estimate and Forecast Better Than AIC?," Working Papers Central Bank of Chile 679, Central Bank of Chile.
    26. Wu, Shue-Jen & Lee, Wei-Ming, 2015. "Predicting severe simultaneous bear stock markets using macroeconomic variables as leading indicators," Finance Research Letters, Elsevier, vol. 13(C), pages 196-204.
    27. Giuseppe Parigi & Roberto Golinelli, 2007. "The use of monthly indicators to forecast quarterly GDP in the short run: an application to the G7 countries," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(2), pages 77-94.
    28. Makin, Anthony J. & Ratnasiri, Shyama, 2015. "Competitiveness and government expenditure: The Australian example," Economic Modelling, Elsevier, vol. 49(C), pages 154-161.
    29. Todd E. Clark & Michael W. McCracken, 2001. "Evaluating long-horizon forecasts," Research Working Paper RWP 01-14, Federal Reserve Bank of Kansas City.
    30. Parigi, Giuseppe & Golinelli, Roberto, 2005. "Short-Run Italian GDP Forecasting and Real-Time Data," CEPR Discussion Papers 5302, C.E.P.R. Discussion Papers.
    31. Zachary McGurk & Adam Nowak & Joshua C. Hall, 2019. "Stock Returns and Investor Sentiment: Textual Analysis and Social Media," Working Papers 19-03, Department of Economics, West Virginia University.
    32. Naresh Bansal & Jack Strauss & Alireza Nasseh, 2015. "Can we consistently forecast a firm’s earnings? Using combination forecast methods to predict the EPS of Dow firms," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 39(1), pages 1-22, January.
    33. Golinelli, Roberto & Parigi, Giuseppe, 2008. "Real-time squared: A real-time data set for real-time GDP forecasting," International Journal of Forecasting, Elsevier, vol. 24(3), pages 368-385.
    34. McCracken, Michael W., 2007. "Asymptotics for out of sample tests of Granger causality," Journal of Econometrics, Elsevier, vol. 140(2), pages 719-752, October.
    35. Fujiwara, Ippei & Koga, Maiko, 2004. "A Statistical Forecasting Method for Inflation Forecasting: Hitting Every Vector Autoregression and Forecasting under Model Uncertainty," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 22(1), pages 123-142, March.
    36. Frank Schiller & Gerold Seidler & Maximilian Wimmer, 2012. "Temperature models for pricing weather derivatives," Quantitative Finance, Taylor & Francis Journals, vol. 12(3), pages 489-500, March.
    37. Yang, Zihui & Zhao, Yongliang, 2014. "Energy consumption, carbon emissions, and economic growth in India: Evidence from directed acyclic graphs," Economic Modelling, Elsevier, vol. 38(C), pages 533-540.
    38. Ana María Abarca & Felipe Alarcón & Pablo Pincheira & Jorge Selaive, 2007. "Chilean Nominal Exchange Rate: Forecasting Based Upon Technical Analysis," Working Papers Central Bank of Chile 425, Central Bank of Chile.
    39. Rapach, David E. & Wohar, Mark E. & Rangvid, Jesper, 2005. "Macro variables and international stock return predictability," International Journal of Forecasting, Elsevier, vol. 21(1), pages 137-166.
    40. Carlos A. Medel Vera, 2011. "¿Akaike o Schwarz? ¿Cuál utilizar para predecir el PIB chileno?," Monetaria, CEMLA, vol. 0(4), pages 591-615, octubre-d.
    41. Pincheira-Brown, Pablo & Selaive, Jorge & Nolazco, Jose Luis, 2019. "Forecasting inflation in Latin America with core measures," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1060-1071.
    42. Jacques Peeperkorn & Yudhvir Seetharam, 2016. "A learning-augmented approach to pricing risk in South Africa," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 6(1), pages 117-139, April.
    43. Gerhard Hambusch & Sherrill Shaffer, 2016. "Forecasting bank leverage: an alternative to regulatory early warning models," Journal of Regulatory Economics, Springer, vol. 50(1), pages 38-69, August.
    44. López, Ramón & Sepúlveda, Kevin A., 2022. "The effects of domestic demand shocks on inflation in a small open economy: Chile in the period 2000–2021," Revista CEPAL, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), December.
    45. Daniel Fernández, 2011. "Suficiencia del capital y previsiones de la banca uruguaya por su exposición al sector industrial," Monetaria, CEMLA, vol. 0(4), pages 517-589, octubre-d.
    46. Edvinsson, Rodney & Karlsson, Sune & Österholm, Pär, 2023. "Does Money Growth Predict Inflation? Evidence from Vector Autoregressions Using Four Centuries of Data," Working Papers 2023:3, Örebro University, School of Business.
    47. Ghandar, Adam & Michalewicz, Zbigniew & Zurbruegg, Ralf, 2016. "The relationship between model complexity and forecasting performance for computer intelligence optimization in finance," International Journal of Forecasting, Elsevier, vol. 32(3), pages 598-613.
    48. Michael Scholz & Jens Perch Nielsen & Stefan Sperlich, 2012. "Nonparametric prediction of stock returns guided by prior knowledge," Graz Economics Papers 2012-02, University of Graz, Department of Economics.
    49. Gary Cornwall & Jeffrey A. Mills & Beau A. Sauley & Huibin Weng, 2018. "Predictive Testing for Granger Causality via Posterior Simulation and Cross Validation," BEA Working Papers 0156, Bureau of Economic Analysis.
    50. Tamara Burdisso & Eduardo Ariel Corso, 2011. "Incertidumbre y dolarización de cartera: el caso argentino en el último medio siglo," Monetaria, CEMLA, vol. 0(4), pages 461-515, octubre-d.
    51. Paldam, Martin, 2018. "A model of the representative economist, as researcher and policy advisor," European Journal of Political Economy, Elsevier, vol. 54(C), pages 5-15.
    52. 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.

  56. Todd E. Clark & Michael W. McCracken, 2000. "Tests of Equal Forecast Accuracy and Encompassing for Nested Models," Econometric Society World Congress 2000 Contributed Papers 0319, Econometric Society.

    Cited by:

    1. Christian Hutter & Enzo Weber, 2015. "Constructing a new leading indicator for unemployment from a survey among German employment agencies," Applied Economics, Taylor & Francis Journals, vol. 47(33), pages 3540-3558, July.
    2. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    3. Mario Porqueddu & Fabrizio Venditti, 2012. "Do food commodity prices have asymmetric effects on Euro-Area inflation?," Temi di discussione (Economic working papers) 878, Bank of Italy, Economic Research and International Relations Area.
    4. Ataman Ozyildirim & Brian Schaitkin & Victor Zarnowitz, 2008. "Business Cycles in the Euro Area Defined with Coincident Economic Indicators and Predicted with Leading Economic Indicators," Economics Program Working Papers 08-04, The Conference Board, Economics Program.
    5. Norman R. Swanson & Nii Ayi Armah, 2011. "Predictive Inference Under Model Misspecification with an Application to Assessing the Marginal Predictive Content of Money for Output," Departmental Working Papers 201103, Rutgers University, Department of Economics.
    6. Adam J. Check & Anna K Nolan & Tyler C. Schipper, 2019. "Forecasting GDP Growth using Disaggregated GDP Revisions," Economics Bulletin, AccessEcon, vol. 39(4), pages 2580-2588.
    7. Nicolas Chanut & Mario Marcel & Carlos Medel, 2018. "Can Economic Perception Surveys Improve Macroeconomic Forecasting in Chile?," Working Papers Central Bank of Chile 824, Central Bank of Chile.
    8. Freire, Gustavo, 2021. "Tail risk and investors’ concerns: Evidence from Brazil," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    9. Lee, Kevin & Olekalns, Nils & Shields, Kalvinder, 2009. "Nowcasting, Business Cycle Dating and the Interpretation of New Information when Real-Time Data are Available," CEPR Discussion Papers 7426, C.E.P.R. Discussion Papers.
    10. 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.
    11. Yin, Anwen, 2015. "Forecasting and model averaging with structural breaks," ISU General Staff Papers 201501010800005727, Iowa State University, Department of Economics.
    12. Mauro Bernardi & Leopoldo Catania, 2014. "The Model Confidence Set package for R," Papers 1410.8504, arXiv.org.
    13. Amélie Charles & Olivier Darné & Jae H. Kim, 2022. "Stock return predictability: Evaluation based on interval forecasts," Bulletin of Economic Research, Wiley Blackwell, vol. 74(2), pages 363-385, April.
    14. Jondeau, Eric & Zhang, Qunzi & Zhu, Xiaoneng, 2019. "Average skewness matters," Journal of Financial Economics, Elsevier, vol. 134(1), pages 29-47.
    15. Massimiliano Marcellino & James Stock & Mark Watson, 2005. "A Comparison of Direct and Iterated Multistep AR Methods for Forecasting Macroeconomic Time Series," Working Papers 285, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    16. Granziera, Eleonora & Sekhposyan, Tatevik, 2019. "Predicting relative forecasting performance: An empirical investigation," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1636-1657.
    17. Tae-Hwy Lee & Ekaterina Seregina & Yaojue Xu, 2023. "Elicitability and Encompassing for Volatility Forecasts by Bregman Functions," Working Papers 202311, University of California at Riverside, Department of Economics.
    18. Christophe Boucher & Bertrand Maillet, 2012. "Prévoir sans persistance," Post-Print hal-01386006, HAL.
    19. Hui Guo, 2003. "On the out-of-sample predictability of stock market returns," Working Papers 2002-008, Federal Reserve Bank of St. Louis.
    20. Aaron J. Amburgey & Michael W. McCracken, 2023. "On the real‐time predictive content of financial condition indices for growth," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(2), pages 137-163, March.
    21. Todd E. Clark, 2004. "Can out-of-sample forecast comparisons help prevent overfitting?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(2), pages 115-139.
    22. Rossi, Barbara, 2013. "Exchange Rate Predictability," CEPR Discussion Papers 9575, C.E.P.R. Discussion Papers.
    23. Odile Chagny & Matthieu Lemoine, 2004. "An estimation of the Euro Area potential output with a semi-structural multivariate Hodrick-Prescott filter," SciencePo Working papers Main hal-00972840, HAL.
    24. Guglielmo Maria Caporale & Juncal Cunado & Luis A. Gil-Alana, 2008. "Modelling Long-Run Trends and Cycles in Financial Time Series Data," CESifo Working Paper Series 2330, CESifo.
    25. Skjeltorp, Johannes & Ødegaard, Bernt Arne, 2009. "The information content of market liquidity: An empirical analysis of liquidity at the Oslo Stock Exchange," UiS Working Papers in Economics and Finance 2009/35, University of Stavanger.
    26. Rossi, Barbara & Odendahl, Florens & Sekhposyan, Tatevik, 2020. "Comparing Forecast Performance with State Dependence," CEPR Discussion Papers 15217, C.E.P.R. Discussion Papers.
    27. Vivian, Andrew & Wohar, Mark E., 2013. "The output gap and stock returns: Do cyclical fluctuations predict portfolio returns?," International Review of Financial Analysis, Elsevier, vol. 26(C), pages 40-50.
    28. Caroline Jardet & Baptiste Meunier, 2022. "Nowcasting world GDP growth with high‐frequency data," Post-Print hal-03647097, HAL.
    29. Hansson, Jesper & Jansson, Per & Löf, Mårten, 2003. "Business Survey Data: Do They Help in Forecasting the Macro Economy?," Working Paper Series 151, Sveriges Riksbank (Central Bank of Sweden).
    30. Gonçalves, Sílvia & McCracken, Michael W. & Perron, Benoit, 2017. "Tests of equal accuracy for nested models with estimated factors," Journal of Econometrics, Elsevier, vol. 198(2), pages 231-252.
    31. Abhyankar, Abhay & Sarno, Lucio & Valente, Giorgio, 2004. "Exchange Rates and Fundamentals: Evidence on the Economic Value of Predictability," CEPR Discussion Papers 4365, C.E.P.R. Discussion Papers.
    32. Martin Lettau & Sydney C. Ludvigson, 1999. "Consumption, aggregate wealth and expected stock returns," Staff Reports 77, Federal Reserve Bank of New York.
    33. Miguel A. Ferreira & Pedro Santa-Clara, 2008. "Forecasting Stock Market Returns: The Sum of the Parts is More than the Whole," NBER Working Papers 14571, National Bureau of Economic Research, Inc.
    34. Pincheira, Pablo & Hernández, Ana María, 2019. "Forecasting Unemployment Rates with International Factors," MPRA Paper 97855, University Library of Munich, Germany.
    35. Ubilava, David, 2014. "On the Relationship between Financial Instability and Economic Performance: Stressing the Business of Nonlinear Modelling," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170222, Agricultural and Applied Economics Association.
    36. Nicolás Magner & Nicolás Hardy, 2022. "Cryptocurrency Forecasting: More Evidence of the Meese-Rogoff Puzzle," Mathematics, MDPI, vol. 10(13), pages 1-27, July.
    37. Maria Caporale, Guglielmo & A. Gil-Alana, Luis, 2011. "Multi-Factor Gegenbauer Processes and European Inflation Rates," Journal of Economic Integration, Center for Economic Integration, Sejong University, vol. 26, pages 386-409.
    38. Berger, Helge & Österholm, Pär, 2008. "Does money matter for U.S. inflation? Evidence from Bayesian VARs," Discussion Papers 2008/9, Free University Berlin, School of Business & Economics.
    39. Liu, Yang & Han, Liyan & Xu, Yang, 2021. "The impact of geopolitical uncertainty on energy volatility," International Review of Financial Analysis, Elsevier, vol. 75(C).
    40. Clark, Todd E. & McCracken, Michael W., 2015. "Nested forecast model comparisons: A new approach to testing equal accuracy," Journal of Econometrics, Elsevier, vol. 186(1), pages 160-177.
    41. Chen, Shiu-Sheng & Chou, Yu-Hsi, 2023. "Liquidity yield and exchange rate predictability," Journal of International Money and Finance, Elsevier, vol. 137(C).
    42. Clark, Todd & McCracken, Michael, 2013. "Advances in Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1107-1201, Elsevier.
    43. Eric Jondeau & Xuewu Wang & Zhipeng Yan & Qunzi Zhang, 2020. "Skewness and index futures return," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(11), pages 1648-1664, November.
    44. Arabinda Basistha, 2023. "Estimation of short‐run predictive factor for US growth using state employment data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(1), pages 34-50, January.
    45. Andres Fernandez & Norman R. Swanson, 2009. "Real-time datasets really do make a difference: definitional change, data release, and forecasting," Working Papers 09-28, Federal Reserve Bank of Philadelphia.
    46. Breitung, Jörg & Knüppel, Malte, 2018. "How far can we forecast? Statistical tests of the predictive content," Discussion Papers 07/2018, Deutsche Bundesbank.
    47. Michael Funke & Aaron Mehrotra & Hao Yu, 2015. "Tracking Chinese CPI inflation in real time," Empirical Economics, Springer, vol. 48(4), pages 1619-1641, June.
    48. Guo, Hui & Savickas, Robert & Wang, Zijun & Yang, Jian, 2009. "Is the Value Premium a Proxy for Time-Varying Investment Opportunities? Some Time-Series Evidence," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 44(1), pages 133-154, February.
    49. Faust, Jon & Wright, Jonathan H., 2009. "Comparing Greenbook and Reduced Form Forecasts Using a Large Realtime Dataset," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 468-479.
    50. Giacomini, Raffaella, 2014. "Economic theory and forecasting: lessons from the literature," CEPR Discussion Papers 10201, C.E.P.R. Discussion Papers.
    51. Yip Yin & Quah Hoe, 2008. "A New Variant of ARFIMA Process and Its Predictive Ability," Modern Applied Science, Canadian Center of Science and Education, vol. 2(2), pages 142-142, March.
    52. Ahmed, Shamim & Tsvetanov, Daniel, 2016. "The predictive performance of commodity futures risk factors," Journal of Banking & Finance, Elsevier, vol. 71(C), pages 20-36.
    53. Arabinda Basistha & Richard Startz, 2023. "Measuring Persistent Global Economic Factors with Output, Commodity Price, and Commodity Currency Data," Working Papers 23-05, Department of Economics, West Virginia University.
    54. Rangan Gupta & Alain Kabundi & Emmanuel Ziramba, 2009. "The Effect Of Defense Spending On Us Output: A Factor Augmented Vector Autoregression (Favar) Approach," Working Papers 200911, University of Pretoria, Department of Economics.
    55. Costas Milas & Ruthira Naraidoo, 2009. "Financial Market Conditions, Real Time, Nonlinearity and European Central Bank Monetary Policy: In-Sample and Out-of-Sample Assessment," Working Paper series 42_09, Rimini Centre for Economic Analysis.
    56. Steven J. Jordan & Andrew Vivian & Mark E. Wohar, 2015. "Location, location, location: currency effects and return predictability?," Applied Economics, Taylor & Francis Journals, vol. 47(18), pages 1883-1898, April.
    57. Filip Stanek, 2021. "Optimal Out-of-Sample Forecast Evaluation under Stationarity," CERGE-EI Working Papers wp712, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
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    Cited by:

    1. Brian M. Doyle & Jon Faust, 2003. "Breaks in the variability and co-movement of G-7 economic growth," International Finance Discussion Papers 786, Board of Governors of the Federal Reserve System (U.S.).
    2. Michael Graff, 2005. "Internationale Konjunkturverbunde," KOF Working papers 05-108, KOF Swiss Economic Institute, ETH Zurich.
    3. Georgiadis, Georgios, 2015. "Determinants of global spillovers from US monetary policy," Working Paper Series 1854, European Central Bank.
    4. Jarko Fidrmuc, 2004. "The Endogenity of the Optimum Currency Area Criteria, Trade, and Labour Market Rigidities: Implications for EMU Enlargement," EUI-RSCAS Working Papers 16, European University Institute (EUI), Robert Schuman Centre of Advanced Studies (RSCAS).
    5. Jean Barthélemy & Sandra Poncet, 2008. "Ampleur et déterminants des cycles d’activité en Chine," Économie et Prévision, Programme National Persée, vol. 185(4), pages 1-12.
    6. Jorge Miranda-Pinto & Gang Zhang, 2022. "Trade Credit and Sectoral Comovement during Recessions," Working Papers Central Bank of Chile 961, Central Bank of Chile.
    7. Sebnem Kalemli-Ozcan & Elias Papaioannou & José Luis Peydró, 2010. "Financial Regulation, Integration and Synchronization of Economic Activity," Koç University-TUSIAD Economic Research Forum Working Papers 1005, Koc University-TUSIAD Economic Research Forum, revised Apr 2010.
    8. Benoit Julien & John Kennes & Ian King, "undated". "Quality Job Programs, Unemployment and the Job Quality Mix," MRG Discussion Paper Series 4721, School of Economics, University of Queensland, Australia.
    9. Kim, Soyoung & Lee, Jong-Wha & Park, Cyn-Young, 2009. "Emerging Asia: Decoupling or Recoupling," Working Papers on Regional Economic Integration 31, Asian Development Bank.
    10. Jean Imbs, 2004. "Trade, Finance, Specialization, and Synchronization," The Review of Economics and Statistics, MIT Press, vol. 86(3), pages 723-734, August.
    11. Jan Schiefer & Stefan Hirsch & Monika Hartmann & Adelina Gschwandtner, 2013. "Industry, firm, year and country effects on profitability in EU food processing," Studies in Economics 1309, School of Economics, University of Kent.
    12. Tamotsu Onozaki, 2018. "Nonlinearity, Bounded Rationality, and Heterogeneity," Springer Books, Springer, number 978-4-431-54971-0, September.
    13. Frankel, Jeffrey, 2004. "Real Convergence and Euro Adoption in Central and Eastern Europe: Trade and Business Cycle Correlations as Endogenous Criteria for Joining EMU," Working Paper Series rwp04-039, Harvard University, John F. Kennedy School of Government.
    14. Luca De Benedictis & Lucia Tajoli, 2003. "Economic integration, similarity and convergence in the EU and CEECs trade structures," KITeS Working Papers 148, KITeS, Centre for Knowledge, Internationalization and Technology Studies, Universita' Bocconi, Milano, Italy, revised Jul 2003.
    15. Antonio Cosma & antonio.cosma@uni.lu & Michel Beine & Robert Vermeulen, 2009. "The Dark Side of Global Integration: Increasing Tail Dependence," LSF Research Working Paper Series 09-05, Luxembourg School of Finance, University of Luxembourg.
    16. Dinu, Marin & Marinas, Marius-Corneliu & Socol, Cristian & Socol, Aura-Gabriela, 2014. "Testing the Endogeneity of Trade and Financial Integration and Sectoral Specialization in an Enlarged Euro Area," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 86-104, March.
    17. Alejandro Jara & Néstor Romero, 2016. "Sincronía internacional de los precios de la vivienda," Notas de Investigación Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 19(1), pages 76-91, April.
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    3. Kajal Lahiri & Gultekin Isiklar, 2010. "Estimating International Transmission of Shocks Using GDP Forecasts: India and Its Trading Partners," Discussion Papers 10-06, University at Albany, SUNY, Department of Economics.
    4. Martin Gächter & Aleksandra Riedl & Doris Ritzberger-Grünwald, 2012. "Business Cycle Synchronization in the Euro Area and the Impact of the Financial Crisis," Monetary Policy & the Economy, Oesterreichische Nationalbank (Austrian Central Bank), issue 2, pages 33-60.
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    6. Svatopluk Kapounek & Jitka Poměnková, 2012. "Spurious synchronization of business cycles - Dynamic correlation analysis of V4 countries," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 60(4), pages 181-188.
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    19. Christian Volpe Martincus & Andrea Molinari, 2007. "Regional Business Cycles and National Economic Borders: What Are the Effects of Trade in Developing Countries?," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 143(1), pages 140-178, April.
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    26. Christian Matthes & Felipe Schwartzman, 2019. "What Do Sectoral Dynamics Tell Us About the Origins of Business Cycles?," Working Paper 19-9, Federal Reserve Bank of Richmond.
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    30. Furceri, Davide & Loungani, Prakash & Pizzuto, Pietro, 2022. "Moving closer? Comparing regional adjustments to shocks in EMU and the United States," Journal of International Money and Finance, Elsevier, vol. 120(C).
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    32. Yuriy Gorodnichenko, 2005. "Reduced-Rank Identification of Structural Shocks in VARs," Macroeconomics 0512011, University Library of Munich, Germany.
    33. Ansgar Belke & Jens Heine, 2007. "On the endogeneity of an exogenous OCA-criterion: specialisation and the correlation of regional business cycles in Europe," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 34(1), pages 15-44, March.
    34. Thomas Walker & David Norman, 2004. "Co-movement of Australian State Business Cycles," Econometric Society 2004 Australasian Meetings 334, Econometric Society.
    35. Svaleryd, Helena & Vlachos, Jonas, 2000. "Does Financial Development Lead to Trade Liberalization?," Research Papers in Economics 2000:11, Stockholm University, Department of Economics.
    36. Ossama Mikhail, 2004. "No More Rocking Horses: Trading Business-Cycle Depth for Duration Using an Economy-Specific Characteristic," Macroeconomics 0402026, University Library of Munich, Germany.
    37. Rafiq, M.S., 2011. "The optimality of a gulf currency union: Commonalities and idiosyncrasies," Economic Modelling, Elsevier, vol. 28(1-2), pages 728-740, January.
    38. Gerald A. Carlino, 2003. "A confluence of events? explaining fluctuations in local employment," Business Review, Federal Reserve Bank of Philadelphia, issue Q1, pages 6-12.
    39. Jürgen Bierbaumer-Polly & Werner Hölzl, 2016. "Business Cycle Dynamics and Firm Heterogeneity. Evidence for Austria Using Survey Data," WIFO Working Papers 504, WIFO.
    40. Kalemli-Ozcan, Sebnem & Sorensen, Bent E. & Yosha, Oved, 2001. "Economic integration, industrial specialization, and the asymmetry of macroeconomic fluctuations," Journal of International Economics, Elsevier, vol. 55(1), pages 107-137, October.
    41. Davide Furceri, 2002. "Risk-sharing e architettura istituzionale delle politiche di stabilizzazione nell'UME: aspetti metodologici e verifica empirica," Rivista di Politica Economica, SIPI Spa, vol. 92(6), pages 175-210, November-.
    42. Ṣebnem Kalemli-Özcan & Bent E. Sorensen & Oved Yosha, 1999. "Industrial specialization and the asymmetry of shocks across regions," Research Working Paper 99-06, Federal Reserve Bank of Kansas City.
    43. Michael Fratantoni & Scott Schuh, 2000. "Monetary policy, housing investment, and heterogeneous regional markets," Working Papers 00-1, Federal Reserve Bank of Boston.

  59. Todd E. Clark, 1997. "Do producer prices help predict consumer prices?," Research Working Paper 97-09, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Chihying, Hsiao & Chen, Pu, 2007. "Learning Causal Relations in Multivariate Time Series Data," Economics Discussion Papers 2007-15, Kiel Institute for the World Economy (IfW Kiel).
    2. Jonsson, Magnus & Palmqvist, Stefan, 2004. "Do Higher Wages Cause Inflation?," Working Paper Series 159, Sveriges Riksbank (Central Bank of Sweden).
    3. Carbajal-De-Nova, Carolina, 2021. "Wages and inflation in Mexican manufacturing. A two-period comparison: 1994-2003 and 2007-2016," MPRA Paper 109555, University Library of Munich, Germany.
    4. Gregory D. Hess & Mark E. Schweitzer, 2000. "Does wage inflation cause price inflation?," Policy Discussion Papers, Federal Reserve Bank of Cleveland, issue Apr.

  60. Todd E. Clark, 1996. "Finite-sample properties of tests for forecast equivalence," Research Working Paper RWP 96-03, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Frédérick Demers & Annie De Champlain, 2005. "Forecasting Core Inflation in Canada: Should We Forecast the Aggregate or the Components?," Staff Working Papers 05-44, Bank of Canada.
    2. Martin Lettau & Sydney C. Ludvigson, 1999. "Consumption, aggregate wealth and expected stock returns," Staff Reports 77, Federal Reserve Bank of New York.
    3. Berger, Helge & Österholm, Pär, 2007. "Does Money Growth Granger-Cause Inflation in the Euro Area? Evidence from Out-of-Sample Forecasts Using Bayesian VARs," Working Paper Series 2007:30, Uppsala University, Department of Economics.
    4. Todd E. Clark & Michael W. McCracken, 1999. "Tests of equal forecast accuracy and encompassing for nested models," Research Working Paper 99-11, Federal Reserve Bank of Kansas City.
    5. Hendry, David F. & Hubrich, Kirstin, 2006. "Forecasting economic aggregates by disaggregates," Working Paper Series 589, European Central Bank.
    6. Kenneth D. West & Michael W. McCracken, 1998. "Regression-Based Tests of Predictive Ability," NBER Technical Working Papers 0226, National Bureau of Economic Research, Inc.

  61. Todd E. Clark, 1996. "The responses of prices at different stages of production to monetary policy shocks," Research Working Paper 96-12, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Kevin X. D. Huang & Zheng Liu, 2004. "Multiple stages of processing and the quantity anomaly in international business cycle models," Research Working Paper RWP 04-05, Federal Reserve Bank of Kansas City.
    2. Kevin Huang, 2006. "Specific factors meet intermediate inputs: implications for the persistence problem," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 9(3), pages 483-507, July.
    3. Huang, Kevin X. D. & Liu, Zheng, 2001. "Production chains and general equilibrium aggregate dynamics," Journal of Monetary Economics, Elsevier, vol. 48(2), pages 437-462, October.
    4. Kevin X. D. Huang & Jonathan L. Willis, 2018. "Sectoral Interactions and Monetary Policy under Costly Price Adjustments," Annals of Economics and Finance, Society for AEF, vol. 19(2), pages 337-374, November.
    5. Ng, Serena, 2003. "Can sticky prices account for the variations and persistence in real exchange rates?," Journal of International Money and Finance, Elsevier, vol. 22(1), pages 65-85, February.
    6. Felipe Morandé & Matías Tapia, 2002. "Exchange Rate Policy in Chile: From the Band to Floating and Beyond," Working Papers wp192, University of Chile, Department of Economics.
    7. Gong Liutang & Wang Chan & Zou Heng-Fu, 2020. "Optimal monetary policy in a model of vertical production and trade with reference currency," The B.E. Journal of Macroeconomics, De Gruyter, vol. 20(1), pages 1-21, January.
    8. Kevin X. D. Huang, 2005. "Specific factors meet intermediate inputs: implications for strategic complementarities and persistence," Working Papers 04-7, Federal Reserve Bank of Philadelphia.
    9. Huang, Kevin X.D. & Liu, Zheng, 2005. "Inflation targeting: What inflation rate to target?," Journal of Monetary Economics, Elsevier, vol. 52(8), pages 1435-1462, November.
    10. Dutta, Shantanu & Bergen, Mark & Levy, Daniel, 2002. "Price flexibility in channels of distribution: Evidence from scanner data," Journal of Economic Dynamics and Control, Elsevier, vol. 26(11), pages 1845-1900, September.
    11. Brad E. Strum, 2010. "Inflation persistence, backward-looking firms, and monetary policy in an input-output economy," Finance and Economics Discussion Series 2010-55, Board of Governors of the Federal Reserve System (U.S.).
    12. Noussair, Charles & Plott, Charles & Riezman, Raymond, 2007. "Production, trade, prices, exchange rates and equilibration in large experimental economies," European Economic Review, Elsevier, vol. 51(1), pages 49-76, January.
    13. Noussair, C.N. & Plott, C. & Riezman, R., 2007. "Production, trade and exchange rates in large experimental economies," Other publications TiSEM 3bf683fe-0650-4e8a-8682-c, Tilburg University, School of Economics and Management.
    14. Rao, Nasir Hamid & Bukhari, Syed Kalim Hyder, 2010. "Asymmetric Shocks and Co-movement of Price Indices," MPRA Paper 28723, University Library of Munich, Germany.
    15. Julio J. Rotemberg & Michael Woodford, 1999. "The Cyclical Behavior of Prices and Costs," NBER Working Papers 6909, National Bureau of Economic Research, Inc.
    16. An, Lian, 2006. "Exchange Rate Pass-Through:Evidence Based on Vector Autoregression with Sign Restrictions," MPRA Paper 527, University Library of Munich, Germany.
    17. Todd E. Clark, 2003. "Disaggregate evidence on the persistence of consumer price inflation," Research Working Paper RWP 03-11, Federal Reserve Bank of Kansas City.
    18. Latorre, Concepción & Gómez-Plana, Antonio G., 2010. "Multinationals in the Motor vehicles industry: A general equilibrium analysis for a Transition Economy," Conference papers 332025, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    19. Marzinotto, Benedicta, 2009. "Beyond monetary credibility: The impact of globalisation on the output-inflation trade-off in euro-area countries," The North American Journal of Economics and Finance, Elsevier, vol. 20(2), pages 162-176, August.
    20. Chan Wang & Heng-fu Zou, 2015. "Optimal Monetary Policy Under a Global Dollar Standard: The Effect of Vertical Trade and Production," Open Economies Review, Springer, vol. 26(1), pages 121-137, February.
    21. Takatoshi Ito & Kiyotaka Sato, 2006. "Exchange Rate Changes and Inflation in Post-Crisis Asian Economies: VAR Analysis of the Exchange Rate Pass-Through," Discussion papers 06018, Research Institute of Economy, Trade and Industry (RIETI).
    22. Kevin X. D. Huang & Zheng Liu, 1999. "Chain of production as a monetary propagation mechanism," Discussion Paper / Institute for Empirical Macroeconomics 130, Federal Reserve Bank of Minneapolis.
    23. Simon Bilo, 2021. "Hayek’s Theory of Business Cycles: A Theory That Will Remain Obscure?," Journal of Private Enterprise, The Association of Private Enterprise Education, vol. 36(Fall 2021), pages 27-47.
    24. J. McCarthy, 1999. "Pass-through of exchange rates and import prices to domestic inflation in some industrialised economies," BIS Working Papers 79, Bank for International Settlements.
    25. Akdi, Yilmaz & Berument, Hakan & Mümin Cilasun, Seyit, 2006. "The relationship between different price indices: Evidence from Turkey," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 360(2), pages 483-492.
    26. James C. MacGee & Pedro S. Amaral, 2010. "A Multi-sectoral Approach to the U.S. Great Depression," 2010 Meeting Papers 1242, Society for Economic Dynamics.
    27. Mohamed Ilyes Gritli, 2021. "Price inflation and exchange rate pass‐through in Tunisia," African Development Review, African Development Bank, vol. 33(4), pages 715-728, December.
    28. Georgios Bampinas & Theodore Panagiotidis, 2016. "Hedging Inflation with Individual US stocks: A long-run portfolio analysis," Working Paper series 16-11, Rimini Centre for Economic Analysis.
    29. Winkelried, Diego, 2012. "Traspaso del tipo de cambio y metas de inflación en el Perú," Revista Estudios Económicos, Banco Central de Reserva del Perú, issue 23, pages 9-24.
    30. Juan manuel Julio & Héctor manuel Zárate, 2008. "The Price Setting Behavior in Colombia: evidence from PPI micro data," Revista ESPE - Ensayos Sobre Política Económica, Banco de la República, vol. 26(56), pages 12-44, June.
    31. Takatoshi Ito & Kiyotaka Sato, 2006. "Exchange Rate Changes and Inflation in Post-Crisis Asian Economies: VAR Analysis of the Exchange Rate Pass-Through (Subsequently published in "Journal of Money, Credit and Banking", Volume 4," CARF F-Series CARF-F-063, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    32. Balke, Nathan S. & Wynne, Mark A., 2007. "The relative price effects of monetary shocks," Journal of Macroeconomics, Elsevier, vol. 29(1), pages 19-36, March.
    33. Felipe Morandé L. & Matías Tapia G., 2002. "Exchange Rate Policy in Chile: the Abandonment of the Band and the Floating Experience," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 5(3), pages 67-94, December.
    34. Jian Wang, 2007. "Home bias, exchange rate disconnect, and optimal exchange rate policy," Working Papers 0701, Federal Reserve Bank of Dallas.
    35. Louis Phaneuf & Nooman Rebei, 2008. "Production Stages and the Transmission of Technological Progress," Cahiers de recherche 0802, CIRPEE.
    36. Devereux, Michael B. & Engel, Charles, 2007. "Expenditure switching versus real exchange rate stabilization: Competing objectives for exchange rate policy," Journal of Monetary Economics, Elsevier, vol. 54(8), pages 2346-2374, November.
    37. Takatoshi Ito & Yuri N. Sasaki & Kiyotaka Sato, 2005. "Pass-Through of Exchange Rate Changes and Macroeconomic Shocks to Domestic Inflation in East Asian Countries," Discussion papers 05020, Research Institute of Economy, Trade and Industry (RIETI).
    38. Eleanor Doyle, 2004. "Exchange rate pass-through in a small open economy: the Anglo-Irish case," Applied Economics, Taylor & Francis Journals, vol. 36(5), pages 443-455.
    39. Besnik Fetai, 2013. "Exchange Rate Pass-Through in Transition Economies: The Case of Republic of Macedonia," Transition Studies Review, Springer;Central Eastern European University Network (CEEUN), vol. 20(3), pages 309-324, November.
    40. Zeng, Shihong & Nan, Xin & Liu, Chao & Chen, Jiuying, 2017. "The response of the Beijing carbon emissions allowance price (BJC) to macroeconomic and energy price indices," Energy Policy, Elsevier, vol. 106(C), pages 111-121.
    41. Schenkelberg, Heike, 2011. "Why are Prices Sticky? Evidence from Business Survey Data," Discussion Papers in Economics 12158, University of Munich, Department of Economics.
    42. Niclas Andrén & Lars Oxelheim, 2011. "Exchange rate regime shift and price patterns," International Journal of Managerial Finance, Emerald Group Publishing Limited, vol. 7(2), pages 153-178, April.
    43. Diego Winkelried, 2014. "Exchange rate pass-through and inflation targeting in Peru," Empirical Economics, Springer, vol. 46(4), pages 1181-1196, June.
    44. Onmus-Baykal Elif, 2011. "How Costly is CPI Inflation Targeting: A Two Sector Model with No Labor Mobility," The B.E. Journal of Macroeconomics, De Gruyter, vol. 11(1), pages 1-32, January.
    45. Liutang Gong & Chan Wang & Heng-fu Zou, 2016. "Optimal monetary policy with international trade in intermediate inputs," CEMA Working Papers 604, China Economics and Management Academy, Central University of Finance and Economics.
    46. Tiwari, Aviral Kumar & Mutascu, Mihai & Andries, Alin Marius, 2013. "Decomposing time-frequency relationship between producer price and consumer price indices in Romania through wavelet analysis," Economic Modelling, Elsevier, vol. 31(C), pages 151-159.
    47. Erwan Gautier, 2008. "The behaviour of producer prices: evidence from French PPI micro data," Empirical Economics, Springer, vol. 35(2), pages 301-332, September.
    48. Gu, Gyun Cheol, 2012. "Denial, Rationalization, and the Administered Price Thesis," MPRA Paper 42594, University Library of Munich, Germany.
    49. Singh, Aarti & Di Crestvolant, Stefano Tornielli, 2020. "Transmission Of Monetary Policy Shocks: Do Input–Output Interactions Matter?," Macroeconomic Dynamics, Cambridge University Press, vol. 24(8), pages 1881-1903, December.
    50. Yoshibumi Makabe & Yosuke Matsumoto & Wataru Hirata, 2023. "Estimating Pipeline Pressures in New Keynesian Phillips Curves: A Bayesian VAR-GMM Approach," Bank of Japan Working Paper Series 23-E-13, Bank of Japan.
    51. Kevin X. D. Huang & Zheng Liu, 2003. "Inflation to target : what inflation to target?," Research Working Paper RWP 03-10, Federal Reserve Bank of Kansas City.
    52. K. Huang & Z. Liu & L. Phaneuf, "undated". "Staggered contracts, intermediate goods and the dynamic effects of monetary shocks on output, inflation and real wages," Working Papers 2000-20, Utah State University, Department of Economics.
    53. Kevin X.D. Huang & Zheng Liu & Louis Phaneuf, 2004. "Why Does the Cyclical Behavior of Real Wages Change Over Time?," American Economic Review, American Economic Association, vol. 94(4), pages 836-856, September.
    54. Liutang Gong & Chan Wang & Heng-fu Zou, 2017. "Optimal Exchange-Rate Policy in a Model of Local-Currency Pricing with Vertical Production and Trade," CEMA Working Papers 603, China Economics and Management Academy, Central University of Finance and Economics.
    55. Rachel Male, 2010. "Business Cycle Persistence in Developing Countries: How Successful is a DSGE Model with a Vertical Production Chain and Sticky Prices?," Working Papers 672, Queen Mary University of London, School of Economics and Finance.
    56. Mr. Leo Bonato & Mr. Andreas Billmeier, 2002. "Exchange Rate Pass-Through and Monetary Policy in Croatia," IMF Working Papers 2002/109, International Monetary Fund.
    57. Toyoichiro Shirota, 2021. "Cost of Sticky Prices under Multiple Stages of Production," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 53(5), pages 1211-1222, August.
    58. Chan Wang & Heng-fu Zou, 2013. "Optimal monetary policy in open economies: the role of reference currency in vertical production and trade," CEMA Working Papers 586, China Economics and Management Academy, Central University of Finance and Economics.

  62. Todd E. Clark, 1995. "Small sample properties of estimators of non-linear models of covariance structure," Research Working Paper 95-01, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Andrew E. Clark, 2003. "Unemployment as a Social Norm: Psychological Evidence from Panel Data," Journal of Labor Economics, University of Chicago Press, vol. 21(2), pages 289-322, April.
    2. Aedín Doris & Donal O’Neill & Olive Sweetman, 2013. "Identification of the covariance structure of earnings using the GMM estimator," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 11(3), pages 343-372, September.
    3. Toda, Alexis Akira & Walsh, Kieran James, 2017. "Fat tails and spurious estimation of consumption-based asset pricing models," University of California at San Diego, Economics Working Paper Series qt8df3x7gw, Department of Economics, UC San Diego.
    4. Clark, Todd E, 1998. "Employment Fluctuations in U.S. Regions and Industries: The Roles of National, Region-Specific, and Industry-Specific Shocks," Journal of Labor Economics, University of Chicago Press, vol. 16(1), pages 202-229, January.
    5. Andrew Shephard & Xu Cheng & Alejándro Sanchez-Becerra, 2023. "How to weight in moments matchings: A new approach and applications to earnings dynamics," CeMMAP working papers 13/23, Institute for Fiscal Studies.
    6. Kezdi, Gabor & Hahn, Jinyong & Solon, Gary, 2002. "Jackknife minimum distance estimation," Economics Letters, Elsevier, vol. 76(1), pages 35-45, June.
    7. Myck, Michal & Ochmann, Richard & Qari, Salmai, 2008. "Dynamics of Earnings and Hourly Wages in Germany," IZA Discussion Papers 3751, Institute of Labor Economics (IZA).
    8. Ostrovsky Yuri, 2010. "Long-Run Earnings Inequality and Earnings Instability among Canadian Men Revisited, 1985-2005," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 10(1), pages 1-34, March.
    9. Jason Allen & Allan Gregory & Katsumi Shimotsu, 2008. "Empirical Likelihood Block Bootstrapping," Staff Working Papers 08-18, Bank of Canada.
    10. Giesecke, Matthias & Bönke, Timm & Lüthen, Holger, 2011. "The Dynamics of Earnings in Germany: Evidence from Social Security Records," VfS Annual Conference 2011 (Frankfurt, Main): The Order of the World Economy - Lessons from the Crisis 48692, Verein für Socialpolitik / German Economic Association.
    11. George Kapetanios & Tony Yates, 2010. "Estimating time variation in measurement error from data revisions: an application to backcasting and forecasting in dynamic models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(5), pages 869-893.
    12. Inkmann, Joachim, 2000. "Finite Sample Properties of One-step, Two-step and Bootstrap Empirical Likelihood Approaches to Efficient GMM Estimation," CoFE Discussion Papers 00/03, University of Konstanz, Center of Finance and Econometrics (CoFE).
    13. Sologon, Denisa Maria & O'Donoghue, Cathal, 2009. "Earnings Dynamics and Inequality among Men across 14 EU Countries, 1994-2001: Evidence from ECHP," IZA Discussion Papers 4012, Institute of Labor Economics (IZA).
    14. SOLOGON Denisa & VAN KERM Philippe, 2014. "Earnings dynamics, foreign workers and the stability of inequality trends in Luxembourg 1988-2009," LISER Working Paper Series 2014-03, Luxembourg Institute of Socio-Economic Research (LISER).
    15. Michael Baker & Gary Solon, 1998. "Earnings Dynamics and Inequality among Canadian Men, 1976-1992: Evidence from Longitudinal Income Tax Records," Working Papers baker-98-01, University of Toronto, Department of Economics.
    16. Gustafsson, Johan & Holmberg, Johan, 2019. "Earning dynamics in Sweden: The recent evolution of permanent inequality and earnings volatility," Umeå Economic Studies 963, Umeå University, Department of Economics.
    17. Bredemeier, Christian & Gravert, Jan & Juessen, Falko, 2016. "Estimating Labor-Supply Elasticities with Joint Borrowing Constraints of Couples," IZA Discussion Papers 10267, Institute of Labor Economics (IZA).
    18. Magnus Gustavsson, 2007. "The 1990s rise in Swedish earnings inequality -- persistent or transitory?," Applied Economics, Taylor & Francis Journals, vol. 39(1), pages 25-30.
    19. Damba Lkhagvasuren, 2009. "Large Locational Differences in Unemployment Despite High Labor Mobility: Impact of Moving Cost on Aggregate Unemployment and Welfare," Working Papers 09009, Concordia University, Department of Economics, revised Mar 2010.
    20. Vanesa Jorda & Jos Mar a Sarabia & Markus J ntti, 2020. "Estimation of Income Inequality from Grouped Data," LIS Working papers 804, LIS Cross-National Data Center in Luxembourg.
    21. Taisuke Nakata & Christopher Tonetti, 2015. "Small Sample Properties of Bayesian Estimators of Labor Income Processes," Journal of Applied Economics, Taylor & Francis Journals, vol. 18(1), pages 121-148, May.
    22. Yuriy Gorodnichenko, 2007. "Using Firm Optimization to Evaluate and Estimate Returns to Scale," NBER Working Papers 13666, National Bureau of Economic Research, Inc.
    23. Bhashkar Mazumder, 2002. "The Mis-Measurement of Permanent Earnings: New Evidence from Social Security Earnings Data," Working Papers 02-12, Center for Economic Studies, U.S. Census Bureau.
    24. Eric S. Lin & Ta-Sheng Chou, 2018. "Finite-sample refinement of GMM approach to nonlinear models under heteroskedasticity of unknown form," Econometric Reviews, Taylor & Francis Journals, vol. 37(1), pages 1-28, January.
    25. Yuriy Gorodnichenko, 2005. "Reduced-Rank Identification of Structural Shocks in VARs," Macroeconomics 0512011, University Library of Munich, Germany.
    26. Giraitis, Liudas & Kapetanios, George & Theodoridis, Konstantinos & Yates, Tony, 2014. "Estimating time-varying DSGE models using minimum distance methods," Bank of England working papers 507, Bank of England.
    27. Prokhorov, Artem, 2012. "Second order bias of quasi-MLE for covariance structure models," Economics Letters, Elsevier, vol. 114(2), pages 195-197.
    28. Gustavsson, Magnus, 2004. "Trends in the Transitory Variance of Earnings: Evidence from Sweden 1960-1990 and a Comparison with the United States," Working Paper Series 2004:11, Uppsala University, Department of Economics.
    29. Hanns de la Fuente-Mella & Rolando Rubilar & Karime Chahuán-Jiménez & Víctor Leiva, 2021. "Modeling COVID-19 Cases Statistically and Evaluating Their Effect on the Economy of Countries," Mathematics, MDPI, vol. 9(13), pages 1-13, July.
    30. Yasutomo Murasawa, 2009. "Do coincident indicators have one-factor structure?," Empirical Economics, Springer, vol. 36(2), pages 339-365, May.
    31. George Kapetanios & Tony Yates, 2004. "Estimating time-variation in measurement error from data revisions; an application to forecasting in dynamic models," Bank of England working papers 238, Bank of England.
    32. Gustavsson, Magnus, 2002. "Earnings Dynamics and Inequality during Macroeconomic Turbulence: Sweden 1991-1999," Working Paper Series 2002:20, Uppsala University, Department of Economics.
    33. Albert Maydeu-Olivares, 1999. "Thurstonian modeling of ranking data via mean and covariance structure analysis," Psychometrika, Springer;The Psychometric Society, vol. 64(3), pages 325-340, September.

  63. Todd E. Clark, 1993. "Cross-country evidence on long run growth and inflation," Research Working Paper 93-05, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Daniel L. Thornton, 1996. "The costs and benefits of price stability: an assessment of Howitt's rule," Review, Federal Reserve Bank of St. Louis, vol. 78(Mar), pages 23-38.
    2. Manoel Bittencourt, 2008. "Inflation and Financial Development: Evidence from Brazil," WIDER Working Paper Series RP2008-14, World Institute for Development Economic Research (UNU-WIDER).
    3. Neil R. Ericsson & John S. Irons & Ralph W. Tryon, 2001. "Output and inflation in the long run," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 241-253.
    4. Lindh, Thomas & Malmberg, Bo, 1998. "Age structure and inflation - a Wicksellian interpretation of the OECD data," Journal of Economic Behavior & Organization, Elsevier, vol. 36(1), pages 19-37, July.
    5. Noha Emara, 2012. "Inflation Volatility, Institutions, and Economic Growth," Global Journal of Emerging Market Economies, Emerging Markets Forum, vol. 4(1), pages 29-53, January.
    6. Girijasankar Mallik & Anis Chowdhury, 2011. "Effect of inflation uncertainty, output uncertainty and oil price on inflation and growth in Australia," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 38(4), pages 414-429, September.
    7. George Bitros & Epaminondas Panas, 2006. "The inflation-productivity trade-off revisited," Journal of Productivity Analysis, Springer, vol. 26(1), pages 51-65, August.
    8. Karen H. Johnson & David H. Small & Ralph W. Tryon, 1999. "Monetary policy and price stability," International Finance Discussion Papers 641, Board of Governors of the Federal Reserve System (U.S.).
    9. Michelle L. Barnes, 2000. "Threshold Relationships among Inflation, Financial Market Development and Growth," School of Economics and Public Policy Working Papers 2000-04, University of Adelaide, School of Economics and Public Policy.
    10. Doho, Libaud Rudy Aurelien & Somé, Sobom Matthieu & Banto, Jean Michel, 2023. "Inflation and west African sectoral stock price indices: An asymmetric kernel method analysis," Emerging Markets Review, Elsevier, vol. 54(C).
    11. Ruth A. Judson & Athanasios Orphanides, 1996. "Inflation, volatility and growth," Finance and Economics Discussion Series 96-19, Board of Governors of the Federal Reserve System (U.S.).
    12. R. I. Udegbunam, 2002. "Openness, Stock Market Development, and Industrial Growth in Nigeria," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 41(1), pages 69-92.
    13. John Loizides & George Vamvoukas, 2005. "Government expenditure and economic growth: Evidence from trivariate causality testing," Journal of Applied Economics, Universidad del CEMA, vol. 8, pages 125-152, May.
    14. Bitros, G.C. & Panas, E.J., 1999. "Another Look at the Inflation-Productivity Trade-Off," Athens University of Economics and Business 114, Athens University of Economics and Business, Department of International and European Economic Studies.
    15. Mustafa Caglayan & Ozge Kandemir & Kostas Mouratidis, 2012. "The Impact of Inflation Uncertainty on Economic Growth: A MRS-IV Approach," Working Papers 2012025, The University of Sheffield, Department of Economics.
    16. Bonga-Bonga, Lumengo & Ahiakpor, Ferdinand, 2015. "Determinants of Economic Growth in Sub-Saharan Africa: The case of Ghana," MPRA Paper 66923, University Library of Munich, Germany.
    17. Hendrickson, Joshua R. & Salter, Alexander William, 2016. "Money, liquidity, and the structure of production," Journal of Economic Dynamics and Control, Elsevier, vol. 73(C), pages 314-328.
    18. Abu N. M., Wahid & Muhammad, Shahbaz & Pervez, Azeem, 2011. "Inflation and financial sector correlation: the case of Bangladesh," MPRA Paper 32935, University Library of Munich, Germany, revised 20 Aug 2011.
    19. Orphanides, Athanasios & Wieland, Volker & Coenen, Günter, 2003. "Price stability and monetary policy effectiveness when nominal interest rates are bounded at zero," Working Paper Series 231, European Central Bank.
    20. Hongyi Li & Heng-fu Zou, 2002. "Inflation, Growth, and Income Distribution: A Cross-Country Study," Annals of Economics and Finance, Society for AEF, vol. 3(1), pages 85-101, May.
    21. Manoel Bittencourt & Reneé Eyden & Monaheng Seleteng, 2015. "Inflation and Economic Growth: Evidence from the Southern African Development Community," South African Journal of Economics, Economic Society of South Africa, vol. 83(3), pages 411-424, September.
    22. Orphanides, Athanasios & Wieland, Volker, 2000. "Inflation zone targeting," European Economic Review, Elsevier, vol. 44(7), pages 1351-1387, June.
    23. Muhammad Farooq Arby & Amjad Ali, 2017. "Threshold Inflation in Pakistan," SBP Research Bulletin, State Bank of Pakistan, Research Department, vol. 13, pages 1-19.
    24. Ramaprasad Bhar, 2010. "Stochastic Filtering with Applications in Finance," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 7736, June.
    25. Brian O'Reilly, 1998. "The Benefits of Low Inflation: Taking Shock "A nickel ain't worth a dime any more" [Yogi Berra]," Technical Reports 83, Bank of Canada.
    26. Apergis, Nicholas & Eleftheriou, Sophia, 2002. "Interest rates, inflation, and stock prices: the case of the Athens Stock Exchange," Journal of Policy Modeling, Elsevier, vol. 24(3), pages 231-236, June.
    27. Bittencourt, Manoel, 2012. "Inflation and economic growth in Latin America: Some panel time-series evidence," Economic Modelling, Elsevier, vol. 29(2), pages 333-340.
    28. Kushal Banik Chowdhury & Nityananda Sarkar, 2019. "Regime Dependent Effect Of Output Growth On Output Growth Uncertainty: Evidence From Oecd Countries," Bulletin of Economic Research, Wiley Blackwell, vol. 71(3), pages 257-282, July.
    29. Huybens, Elisabeth & Smith, Bruce D., 1999. "Inflation, financial markets and long-run real activity," Journal of Monetary Economics, Elsevier, vol. 43(2), pages 283-315, April.
    30. Kyriakos C. Neanidis & Christos S. Savva, 2010. "Macroeconomic Uncertainty, Inflation and Growth: Regime-Dependent Effects in the G7," Centre for Growth and Business Cycle Research Discussion Paper Series 145, Economics, The University of Manchester.
    31. Andres, Javier & Domenech, Rafael & Molinas, Cesar, 1996. "Macroeconomic performance and convergence in OECD countries," European Economic Review, Elsevier, vol. 40(9), pages 1683-1704, December.
    32. F. Heylen & L. Pozzi & J. Vandewege, 2004. "Inflation crises, human capital formation and growth," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 04/260, Ghent University, Faculty of Economics and Business Administration.
    33. Grier, Robin & Grier, Kevin B., 2006. "On the real effects of inflation and inflation uncertainty in Mexico," Journal of Development Economics, Elsevier, vol. 80(2), pages 478-500, August.
    34. Mustafa Caglayan & Ozge Kandemir Kocaaslan & Kostas Mouratidis, 2016. "Regime Dependent Effects of Inflation Uncertainty on Real Growth: A Markov Switching Approach," Scottish Journal of Political Economy, Scottish Economic Society, vol. 63(2), pages 135-155, May.
    35. Hachicha, Ahmed & Lean Hooi Hooi, 2013. "Inflation, inflation uncertainty and output in Tunisia," Economics Discussion Papers 2013-1, Kiel Institute for the World Economy (IfW Kiel).
    36. Binder, Carola C., 2017. "Measuring uncertainty based on rounding: New method and application to inflation expectations," Journal of Monetary Economics, Elsevier, vol. 90(C), pages 1-12.
    37. Daniel Bolton & W. Robert & J. Alexander, 2001. "The differing consequences of low and high rates of inflation," Applied Economics Letters, Taylor & Francis Journals, vol. 8(6), pages 411-414.
    38. Aribah Aslam, 2020. "The hotly debate of human capital and economic growth: why institutions may matter?," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(4), pages 1351-1362, August.
    39. Mustafa Caglayan & Ozge Kandemir & Kostas Mouratidis, 2011. "Real effects of inflation uncertainty in the US," Working Papers 2011002, The University of Sheffield, Department of Economics, revised Feb 2015.
    40. Javier Andrés & Ignacio Hernando & J. David López-Salido, 1999. "Assessing the benefits of price stability: The international experience," Estudios Económicos, Banco de España, number 69.
    41. Metiu, Norbert & Prieto, Esteban, 2023. "The macroeconomic effects of inflation uncertainty," Discussion Papers 32/2023, Deutsche Bundesbank.
    42. Hunter Humphries & Stephen Knowles, 1998. "Does agriculture contribute to economic growth? Some empirical evidence," Applied Economics, Taylor & Francis Journals, vol. 30(6), pages 775-781.
    43. F. Heylen & A. Schollaert & G. Everaert & L. Pozzi, 2003. "Inflation and human capital formation : theory and panel data evidence," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 03/174, Ghent University, Faculty of Economics and Business Administration.
    44. Mustafa Caglayan & Feng Jiang, 2006. "Reexamining the linkages between inflation and output growth: A bivariate ARFIMA-FIGARCH approach," Working Papers 2006_8, Business School - Economics, University of Glasgow.
    45. Emara, Noha, 2012. "Inflation volatility, financial institutions and sovereign debt rating," MPRA Paper 68688, University Library of Munich, Germany.
    46. Narayan, Seema & Narayan, Paresh Kumar, 2013. "The inflation–output nexus: Empirical evidence from India, South Africa, and Brazil," Research in International Business and Finance, Elsevier, vol. 28(C), pages 19-34.
    47. Wilson, Bradley Kemp, 2006. "The links between inflation, inflation uncertainty and output growth: New time series evidence from Japan," Journal of Macroeconomics, Elsevier, vol. 28(3), pages 609-620, September.

  64. Todd E. Clark, 1993. "Rents and prices of housing across areas of the U.S.: a cross-section examination of the present value model," Research Working Paper 93-04, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Brian Micallef & Nathaniel Debono, 2020. "The rental sector and the housing block in STREAM," CBM Working Papers WP/03/2020, Central Bank of Malta.
    2. Clark, Todd E., 1995. "Rents and prices of housing across areas of the United States. A cross-section examination of the present value model," Regional Science and Urban Economics, Elsevier, vol. 25(2), pages 237-247, April.

  65. Todd E. Clark, 1992. "Business cycle fluctuations in U.S. regions and industries: the roles of national, region-specific, and industry-specific shocks," Research Working Paper 92-05, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Cribari-Neto, Francisco, 1996. "On time series econometrics," The Quarterly Review of Economics and Finance, Elsevier, vol. 36(Supplemen), pages 37-60.
    2. David D. Selover & Roderick V. Jensen & John Kroll, 2005. "Mode‐Locking and Regional Business Cycle Synchronization," Journal of Regional Science, Wiley Blackwell, vol. 45(4), pages 703-745, November.
    3. Cribari-Neto, Francisco, 1993. "Unit roots, random walks and the sources of business cycles: a survey," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 47(3), July.
    4. Joshua L. Rosenbloom & William A. Sundstrom, 1997. "The Sources of Regional Variation in the Severity of the Great Depression: Evidence from U.S. Manufacturing, 1919-1937," NBER Working Papers 6288, National Bureau of Economic Research, Inc.
    5. Atish R. Ghosh & Holger C. Wolf, 1997. "Geographical and Sectoral Shocks in the U.S. Business Cycle," NBER Working Papers 6180, National Bureau of Economic Research, Inc.
    6. Jonathan McCarthy & Charles Steindel, 1996. "The relative importance of national and regional factors in the New York Metropolitan economy," Research Paper 9621, Federal Reserve Bank of New York.

Articles

  1. Todd E. Clark & Matthew V. Gordon, 2023. "The Impacts of Supply Chain Disruptions on Inflation," Economic Commentary, Federal Reserve Bank of Cleveland, vol. 2023(08), pages 1-8, May.

    Cited by:

    1. Paula Bejarano Carbo, 2024. "The Nature of the Inflationary Surprise in Europe and the USA," National Institute of Economic and Social Research (NIESR) Discussion Papers 554, National Institute of Economic and Social Research.
    2. Xiwen Bai & Jesús Fernández-Villaverde & Yiliang Li & Francesco Zanetti, 2024. "The Causal Effects of Global Supply Chain Disruptions on Macroeconomic Outcomes: Evidence and Theory," CESifo Working Paper Series 10930, CESifo.
    3. Christopher Healy & Chengcheng Jia, 2023. "Monetary Policy since the Onset of the COVID-19 Pandemic: A Path-Dependent Interpretation," Economic Commentary, Federal Reserve Bank of Cleveland, vol. 2023(12), pages 1-8, July.

  2. Todd E. Clark & Florian Huber & Gary Koop & Massimiliano Marcellino & Michael Pfarrhofer, 2023. "Tail Forecasting With Multivariate Bayesian Additive Regression Trees," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 64(3), pages 979-1022, August.
    See citations under working paper version above.
  3. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2022. "Nowcasting tail risk to economic activity at a weekly frequency," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 843-866, August.
    See citations under working paper version above.
  4. Yu Bai & Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2022. "Macroeconomic forecasting in a multi‐country context," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(6), pages 1230-1255, September.
    See citations under working paper version above.
  5. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2021. "No‐arbitrage priors, drifting volatilities, and the term structure of interest rates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 495-516, August.
    See citations under working paper version above.
  6. Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano, 2021. "Using time-varying volatility for identification in Vector Autoregressions: An application to endogenous uncertainty," Journal of Econometrics, Elsevier, vol. 225(1), pages 47-73.
    See citations under working paper version above.
  7. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2020. "Assessing international commonality in macroeconomic uncertainty and its effects," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(3), pages 273-293, April.
    See citations under working paper version above.
  8. Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2020. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," The Review of Economics and Statistics, MIT Press, vol. 102(1), pages 17-33, March.
    See citations under working paper version above.
  9. Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano, 2019. "Large Bayesian vector autoregressions with stochastic volatility and non-conjugate priors," Journal of Econometrics, Elsevier, vol. 212(1), pages 137-154.

    Cited by:

    1. Ha, Jongrim & Kose, M. Ayhan & Ohnsorge, Franziska, 2021. "Inflation During the Pandemic: What Happened? What is Next?," MPRA Paper 108677, University Library of Munich, Germany.
    2. Mike Tsionas & Marwan Izzeldin & Lorenzo Trapani, 2019. "Bayesian estimation of large dimensional time varying VARs using copulas," Papers 1912.12527, arXiv.org.
    3. Bańbura, Marta & Leiva-Leon, Danilo & Menz, Jan-Oliver, 2021. "Do inflation expectations improve model-based inflation forecasts?," Working Paper Series 2604, European Central Bank.
    4. Leonardo Nogueira Ferreira & Silvia Miranda-Agrippino & Giovanni Ricco, 2023. "Bayesian Local Projections," Working Papers Series 581, Central Bank of Brazil, Research Department.
    5. David Alaminos & M. Belén Salas & Manuel A. Fernández-Gámez, 2022. "Quantum Computing and Deep Learning Methods for GDP Growth Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 803-829, February.
    6. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2020. "Capturing Macroeconomic Tail Risks with Bayesian Vector Autoregressions," Working Papers 20-02R, Federal Reserve Bank of Cleveland, revised 22 Sep 2020.
    7. Joshua C. C. Chan & Xuewen Yu, 2022. "Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility," Papers 2206.08438, arXiv.org.
    8. Gefang, Deborah & Koop, Gary & Poon, Aubrey, 2023. "Forecasting using variational Bayesian inference in large vector autoregressions with hierarchical shrinkage," International Journal of Forecasting, Elsevier, vol. 39(1), pages 346-363.
    9. Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2023. "Large Time‐Varying Volatility Models for Hourly Electricity Prices," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 545-573, June.
    10. Annalisa Cadonna & Sylvia Fruhwirth-Schnatter & Peter Knaus, 2019. "Triple the gamma -- A unifying shrinkage prior for variance and variable selection in sparse state space and TVP models," Papers 1912.03100, arXiv.org.
    11. Juan Antolin-Diaz & Ivan Petrella & Juan F. Rubio-Ramirez, 2021. "Dividend Momentum and Stock Return Predictability: A Bayesian Approach," FRB Atlanta Working Paper 2021-25, Federal Reserve Bank of Atlanta.
    12. Christiane Baumeister & Dimitris Korobilis & Thomas K. Lee, 2022. "Energy Markets and Global Economic Conditions," The Review of Economics and Statistics, MIT Press, vol. 104(4), pages 828-844, October.
    13. Tsionas, Mike G. & Izzeldin, Marwan & Trapani, Lorenzo, 2022. "Estimation of large dimensional time varying VARs using copulas," European Economic Review, Elsevier, vol. 141(C).
    14. Marcellino, Massimiliano & Clark, Todd & Carriero, Andrea & Mertens, Elmar, 2021. "Addressing COVID-19 Outliers in BVARs with Stochastic Volatility," CEPR Discussion Papers 15964, C.E.P.R. Discussion Papers.
    15. Martin Feldkircher & Florian Huber & Gary Koop & Michael Pfarrhofer, 2022. "APPROXIMATE BAYESIAN INFERENCE AND FORECASTING IN HUGE‐DIMENSIONAL MULTICOUNTRY VARs," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 63(4), pages 1625-1658, November.
    16. Niko Hauzenberger & Florian Huber & Luca Onorante, 2021. "Combining shrinkage and sparsity in conjugate vector autoregressive models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(3), pages 304-327, April.
    17. Antonio Pacifico, 2021. "Structural Panel Bayesian VAR with Multivariate Time-Varying Volatility to Jointly Deal with Structural Changes, Policy Regime Shifts, and Endogeneity Issues," Econometrics, MDPI, vol. 9(2), pages 1-35, May.
    18. 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.
    19. Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano, 2021. "Using time-varying volatility for identification in Vector Autoregressions: An application to endogenous uncertainty," Journal of Econometrics, Elsevier, vol. 225(1), pages 47-73.
    20. Tsionas, Mike, 2022. "Efficiency estimation using probabilistic regression trees with an application to Chilean manufacturing industries," International Journal of Production Economics, Elsevier, vol. 249(C).
    21. Gao, Shen & Hou, Chenghan & Nguyen, Bao H., 2021. "Forecasting natural gas prices using highly flexible time-varying parameter models," Economic Modelling, Elsevier, vol. 105(C).
    22. Gael M. Martin & David T. Frazier & Worapree Maneesoonthorn & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2022. "Bayesian Forecasting in Economics and Finance: A Modern Review," Papers 2212.03471, arXiv.org, revised Jul 2023.
    23. Gael M. Martin & David T. Frazier & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2023. "Bayesian Forecasting in the 21st Century: A Modern Review," Monash Econometrics and Business Statistics Working Papers 1/23, Monash University, Department of Econometrics and Business Statistics.
    24. Huber, Florian & Koop, Gary & Onorante, Luca & Pfarrhofer, Michael & Schreiner, Josef, 2023. "Nowcasting in a pandemic using non-parametric mixed frequency VARs," Journal of Econometrics, Elsevier, vol. 232(1), pages 52-69.
    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. Joshua C.C. Chan & Rodney W. Strachan, 2023. "Bayesian State Space Models In Macroeconometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 58-75, February.
    27. Joshua C. C. Chan, 2022. "Asymmetric conjugate priors for large Bayesian VARs," Quantitative Economics, Econometric Society, vol. 13(3), pages 1145-1169, July.
    28. Dimitris Korobilis & Kenichi Shimizu, 2021. "Bayesian Approaches to Shrinkage and Sparse Estimation," Working Papers 2021_19, Business School - Economics, University of Glasgow.
    29. Korobilis, Dimitris, 2022. "A new algorithm for structural restrictions in Bayesian vector autoregressions," European Economic Review, Elsevier, vol. 148(C).
    30. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2022. "Reconciled Estimates of Monthly GDP in the US," Working Papers 22-01, Federal Reserve Bank of Cleveland.
    31. Joshua C. C. Chan, 2022. "Comparing Stochastic Volatility Specifications for Large Bayesian VARs," Papers 2208.13255, arXiv.org.
    32. Niko Hauzenberger, 2020. "Flexible Mixture Priors for Large Time-varying Parameter Models," Papers 2006.10088, arXiv.org, revised Nov 2020.
    33. Nima Nonejad, 2021. "An Overview Of Dynamic Model Averaging Techniques In Time‐Series Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 566-614, April.
    34. Javier Sánchez García & Salvador Cruz Rambaud, 2022. "Machine Learning Regularization Methods in High-Dimensional Monetary and Financial VARs," Mathematics, MDPI, vol. 10(6), pages 1-15, March.
    35. Edward S. Knotek & Saeed Zaman, 2020. "Real-Time Density Nowcasts of US Inflation: A Model-Combination Approach," Working Papers 20-31, Federal Reserve Bank of Cleveland.
    36. Chen, Zhengyang & Valcarcel, Victor J., 2021. "Monetary transmission in money markets: The not-so-elusive missing piece of the puzzle," Journal of Economic Dynamics and Control, Elsevier, vol. 131(C).
    37. Sebastian Ankargren & Paulina Jon'eus, 2019. "Simulation smoothing for nowcasting with large mixed-frequency VARs," Papers 1907.01075, arXiv.org.
    38. Sokol, Andrej, 2021. "Fan charts 2.0: flexible forecast distributions with expert judgement," Working Paper Series 2624, European Central Bank.
    39. Chenghan Hou & Bao Nguyen & Bo Zhang, 2023. "Real‐time forecasting of the Australian macroeconomy using flexible Bayesian VARs," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 418-451, March.
    40. Kose, M. Ayhan & Ha, Jongrim & Ohnsorge, Franziska, 2022. "Global Stagflation," CEPR Discussion Papers 17381, C.E.P.R. Discussion Papers.
    41. Ramis Khabibullin & Sergei Seleznev, 2022. "Fast Estimation of Bayesian State Space Models Using Amortized Simulation-Based Inference," Papers 2210.07154, arXiv.org.
    42. Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2020. "Large Time-Varying Volatility Models for Electricity Prices," Working Papers No 05/2020, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    43. Florian Huber & Gary Koop, 2023. "Fast and Order-invariant Inference in Bayesian VARs with Non-Parametric Shocks," Papers 2305.16827, arXiv.org.
    44. Marcellino, Massimiliano & Bai, Yu & Carriero, Andrea & Clark, Todd, 2022. "Macroeconomic Forecasting in a Multi-country Context," CEPR Discussion Papers 16994, C.E.P.R. Discussion Papers.
    45. Florian Huber & Massimiliano Marcellino, 2023. "Coarsened Bayesian VARs -- Correcting BVARs for Incorrect Specification," Papers 2304.07856, arXiv.org, revised May 2023.
    46. Rub'en Loaiza-Maya & Didier Nibbering, 2022. "Efficient variational approximations for state space models," Papers 2210.11010, arXiv.org, revised Jun 2023.
    47. Florian Huber & Luca Rossini, 2020. "Inference in Bayesian Additive Vector Autoregressive Tree Models," Papers 2006.16333, arXiv.org, revised Mar 2021.
    48. Florian Huber & Gary Koop, 2023. "Subspace shrinkage in conjugate Bayesian vector autoregressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 556-576, June.
    49. Michael P. Clements & Ana Beatriz Galvão, 2023. "Density forecasting with Bayesian Vector Autoregressive models under macroeconomic data uncertainty," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(2), pages 164-185, March.
    50. Loaiza-Maya, Rubén & Smith, Michael Stanley & Nott, David J. & Danaher, Peter J., 2022. "Fast and accurate variational inference for models with many latent variables," Journal of Econometrics, Elsevier, vol. 230(2), pages 339-362.
    51. Chan, Joshua C.C. & Poon, Aubrey & Zhu, Dan, 2023. "High-dimensional conditionally Gaussian state space models with missing data," Journal of Econometrics, Elsevier, vol. 236(1).
    52. Jonas E. Arias & Juan F. Rubio-Ramirez & Minchul Shin, 2021. "Macroeconomic Forecasting and Variable Ordering in Multivariate Stochastic Volatility Models," Working Papers 21-21, Federal Reserve Bank of Philadelphia.
    53. Annalisa Cadonna & Sylvia Frühwirth-Schnatter & Peter Knaus, 2020. "Triple the Gamma—A Unifying Shrinkage Prior for Variance and Variable Selection in Sparse State Space and TVP Models," Econometrics, MDPI, vol. 8(2), pages 1-36, May.
    54. Nadja Klein & Michael Stanley Smith & David J. Nott, 2020. "Deep Distributional Time Series Models and the Probabilistic Forecasting of Intraday Electricity Prices," Papers 2010.01844, arXiv.org, revised May 2021.
    55. Cross, Jamie L. & Hou, Chenghan & Nguyen, Bao H., 2021. "On the China factor in the world oil market: A regime switching approach11We thank Hilde Bjørnland, Tatsuyoshi Okimoto, Ippei Fujiwara, Knut Aastveit, Leif Anders Thorsrud, Francesco Ravazzolo, Renee ," Energy Economics, Elsevier, vol. 95(C).
    56. Hauzenberger, Niko & Pfarrhofer, Michael & Stelzer, Anna, 2021. "On the effectiveness of the European Central Bank’s conventional and unconventional policies under uncertainty," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 822-845.
    57. Ping Wu & Gary Koop, 2022. "Fast, Order-Invariant Bayesian Inference in VARs using the Eigendecomposition of the Error Covariance Matrix," Working Papers 2310, University of Strathclyde Business School, Department of Economics.
    58. Arnaud Dufays & Zhuo Li & Jeroen V.K. Rombouts & Yong Song, 2021. "Sparse change‐point VAR models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(6), pages 703-727, September.
    59. Andrea Carriero & Francesco Corsello & Massimiliano Marcellino, 2020. "The economic drivers of volatility and uncertainty," Temi di discussione (Economic working papers) 1285, Bank of Italy, Economic Research and International Relations Area.
    60. Luis Gruber & Gregor Kastner, 2022. "Forecasting macroeconomic data with Bayesian VARs: Sparse or dense? It depends!," Papers 2206.04902, arXiv.org, revised Jul 2023.
    61. Todd E. Clark & Florian Huber & Gary Koop & Massimiliano Marcellino & Michael Pfarrhofer, 2023. "Tail Forecasting With Multivariate Bayesian Additive Regression Trees," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 64(3), pages 979-1022, August.
    62. Gregor Kastner & Florian Huber, 2017. "Sparse Bayesian vector autoregressions in huge dimensions," Papers 1704.03239, arXiv.org, revised Dec 2019.
    63. Bognanni, Mark, 2022. "Comment on “Large Bayesian vector autoregressions with stochastic volatility and non-conjugate priors”," Journal of Econometrics, Elsevier, vol. 227(2), pages 498-505.
    64. Niko Hauzenberger & Florian Huber & Gary Koop, 2020. "Dynamic Shrinkage Priors for Large Time-varying Parameter Regressions using Scalable Markov Chain Monte Carlo Methods," Papers 2005.03906, arXiv.org, revised May 2023.
    65. Antonio Pacifico, 2022. "Structural Compressed Panel VAR with Stochastic Volatility: A Robust Bayesian Model Averaging Procedure," Econometrics, MDPI, vol. 10(3), pages 1-24, July.
    66. Zheng, Tingguo & Ye, Shiqi & Hong, Yongmiao, 2023. "Fast estimation of a large TVP-VAR model with score-driven volatilities," Journal of Economic Dynamics and Control, Elsevier, vol. 157(C).
    67. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2021. "Forecasting with Shadow-Rate VARs," Working Papers 21-09, Federal Reserve Bank of Cleveland.
    68. Michael Pfarrhofer & Anna Stelzer, 2019. "The international effects of central bank information shocks," Papers 1912.03158, arXiv.org.
    69. Boeck, Maximilian & Feldkircher, Martin, 2021. "The Impact of Monetary Policy on Yield Curve Expectations," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 887-901.
    70. Zhang, Wen, 2022. "China’s government spending and global inflation dynamics: The role of the oil price channel," Energy Economics, Elsevier, vol. 110(C).
    71. Sebastian Ankargren & Paulina Jon'eus, 2019. "Estimating Large Mixed-Frequency Bayesian VAR Models," Papers 1912.02231, arXiv.org.
    72. Chan, Joshua C.C., 2021. "Minnesota-type adaptive hierarchical priors for large Bayesian VARs," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1212-1226.
    73. Manfred M. Fischer & Niko Hauzenberger & Florian Huber & Michael Pfarrhofer, 2021. "General Bayesian time-varying parameter VARs for predicting government bond yields," Papers 2102.13393, arXiv.org.
    74. Philippe Goulet Coulombe & Mikael Frenette & Karin Klieber, 2023. "From Reactive to Proactive Volatility Modeling with Hemisphere Neural Networks," Papers 2311.16333, arXiv.org, revised Apr 2024.
    75. Yousuf, Kashif & Ng, Serena, 2021. "Boosting high dimensional predictive regressions with time varying parameters," Journal of Econometrics, Elsevier, vol. 224(1), pages 60-87.
    76. Dimitris Korobilis, 2020. "Sign restrictions in high-dimensional vector autoregressions," Working Paper series 20-09, Rimini Centre for Economic Analysis.
    77. Nadja Klein & Michael Stanley Smith & David J. Nott, 2023. "Deep distributional time series models and the probabilistic forecasting of intraday electricity prices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 493-511, June.
    78. Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano & Mertens, Elmar, 2023. "Shadow-rate VARs," Discussion Papers 14/2023, Deutsche Bundesbank.
    79. Botelho, Vasco & Foroni, Claudia & Renzetti, Andrea, 2023. "Labour at risk," Working Paper Series 2840, European Central Bank.
    80. Todd E. Clark & Matthew V. Gordon & Saeed Zaman, 2023. "Forecasting Core Inflation and Its Goods, Housing, and Supercore Components," Working Papers 23-34, Federal Reserve Bank of Cleveland.
    81. Niko Hauzenberger & Michael Pfarrhofer & Luca Rossini, 2020. "Sparse time-varying parameter VECMs with an application to modeling electricity prices," Papers 2011.04577, arXiv.org, revised Apr 2023.
    82. Cross, Jamie L. & Hou, Chenghan & Poon, Aubrey, 2020. "Macroeconomic forecasting with large Bayesian VARs: Global-local priors and the illusion of sparsity," International Journal of Forecasting, Elsevier, vol. 36(3), pages 899-915.
    83. Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
    84. Fischer, Manfred M. & Hauzenberger, Niko & Huber, Florian & Pfarrhofer, Michael, 2022. "General Bayesian time-varying parameter VARs for modeling government bond yields," Working Papers in Regional Science 2021/01, WU Vienna University of Economics and Business.
    85. Bańbura, Marta & Brenna, Federica & Paredes, Joan & Ravazzolo, Francesco, 2021. "Combining Bayesian VARs with survey density forecasts: does it pay off?," Working Paper Series 2543, European Central Bank.
    86. Nguyen, BH & Zhang, Bo, 2022. "Forecasting oil Prices: can large BVARs help?," Working Papers 2022-04, University of Tasmania, Tasmanian School of Business and Economics.
    87. Kunovac, Davor & Palenzuela, Diego Rodriguez & Sun, Yiqiao, 2022. "A new optimum currency area index for the euro area," Working Paper Series 2730, European Central Bank.
    88. Li, Chenxing & Maheu, John M & Yang, Qiao, 2022. "An Infinite Hidden Markov Model with Stochastic Volatility," MPRA Paper 115456, University Library of Munich, Germany.
    89. Clements, Michael P. & Galvao, Ana Beatriz, 2020. "Density Forecasting with BVAR Models under Macroeconomic Data Uncertainty," EMF Research Papers 36, Economic Modelling and Forecasting Group.
    90. Anna Pajor & Justyna Wróblewska & Łukasz Kwiatkowski & Jacek Osiewalski, 2024. "Hybrid SV‐GARCH, t‐GARCH and Markov‐switching covariance structures in VEC models—Which is better from a predictive perspective?," International Statistical Review, International Statistical Institute, vol. 92(1), pages 62-86, April.
    91. Zens, Gregor & Böck, Maximilian & Zörner, Thomas O., 2020. "The heterogeneous impact of monetary policy on the US labor market," Journal of Economic Dynamics and Control, Elsevier, vol. 119(C).
    92. Zhao, Jing, 2023. "Time-varying impact of geopolitical risk on natural resources prices: Evidence from the hybrid TVP-VAR model with large system," Resources Policy, Elsevier, vol. 82(C).
    93. Saeed Zaman, 2021. "A Unified Framework to Estimate Macroeconomic Stars," Working Papers 21-23R, Federal Reserve Bank of Cleveland, revised 15 Aug 2022.

  10. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2018. "Measuring Uncertainty and Its Impact on the Economy," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 799-815, December.
    See citations under working paper version above.
  11. Joshua C.C. Chan & Todd E. Clark & Gary Koop, 2018. "A New Model of Inflation, Trend Inflation, and Long‐Run Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(1), pages 5-53, February.
    See citations under working paper version above.
  12. Todd E. Clark & Michael W. McCracken, 2017. "Tests of Predictive Ability for Vector Autoregressions Used for Conditional Forecasting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(3), pages 533-553, April.

    Cited by:

    1. 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.
    2. Michael W. McCracken & Joseph McGillicuddy, 2017. "An Empirical Investigation of Direct and Iterated Multistep Conditional Forecasts," Working Papers 2017-40, Federal Reserve Bank of St. Louis.
    3. Giusto Andrea & İşcan Talan B., 2018. "The Rescaled VAR Model with an Application to Mixed-Frequency Macroeconomic Forecasting," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(4), pages 1-16, September.
    4. Kontogeorgos, Georgios & Lambrias, Kyriacos, 2019. "An analysis of the Eurosystem/ECB projections," Working Paper Series 2291, European Central Bank.
    5. 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.
    6. Arai, Natsuki, 2020. "Investigating the inefficiency of the CBO’s budgetary projections," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1290-1300.

  13. Fabian Krüger & Todd E. Clark & Francesco Ravazzolo, 2017. "Using Entropic Tilting to Combine BVAR Forecasts With External Nowcasts," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(3), pages 470-485, July.
    See citations under working paper version above.
  14. Knut Are Aastveit & Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2017. "Have Standard VARS Remained Stable Since the Crisis?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(5), pages 931-951, August.
    See citations under working paper version above.
  15. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2016. "Common Drifting Volatility in Large Bayesian VARs," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(3), pages 375-390, July.
    See citations under working paper version above.
  16. Todd E. Clark & Francesco Ravazzolo, 2015. "Macroeconomic Forecasting Performance under Alternative Specifications of Time‐Varying Volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(4), pages 551-575, June.

    Cited by:

    1. Gergely Ganics & Barbara Rossi & Tatevik Sekhposyan, 2019. "From fixed-event to fixed-horizon density forecasts: Obtaining measures of multi-horizon uncertainty from survey density forecasts," Economics Working Papers 1689, Department of Economics and Business, Universitat Pompeu Fabra.
    2. Huang, Yingying & Duan, Kun & Urquhart, Andrew, 2023. "Time-varying dependence between Bitcoin and green financial assets: A comparison between pre- and post-COVID-19 periods," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    3. David Alaminos & M. Belén Salas & Manuel A. Fernández-Gámez, 2022. "Quantum Computing and Deep Learning Methods for GDP Growth Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 803-829, February.
    4. Valentina Aprigliano & Alessandro Borin & Francesco Paolo Conteduca & Simone Emiliozzi & Marco Flaccadoro & Sabina Marchetti & Stefania Villa, 2021. "Forecasting Italian GDP growth with epidemiological data," Questioni di Economia e Finanza (Occasional Papers) 664, Bank of Italy, Economic Research and International Relations Area.
    5. Huber, Florian, 2016. "Density forecasting using Bayesian global vector autoregressions with stochastic volatility," International Journal of Forecasting, Elsevier, vol. 32(3), pages 818-837.
    6. 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.
    7. Ching-Wai Chiu & Haroon Mumtaz & Gabor Pinter, 2016. "VAR Models with Non-Gaussian Shocks," Discussion Papers 1609, Centre for Macroeconomics (CFM).
    8. Davide Pettenuzzo & Rossen Valkanov & Allan Timmermann, 2014. "A Bayesian MIDAS Approach to Modeling First and Second Moment Dynamics," Working Papers 76, Brandeis University, Department of Economics and International Business School.
    9. Berg, Tim O. & Henzel, Steffen R., 2015. "Point and density forecasts for the euro area using Bayesian VARs," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1067-1095.
    10. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2020. "Capturing Macroeconomic Tail Risks with Bayesian Vector Autoregressions," Working Papers 20-02R, Federal Reserve Bank of Cleveland, revised 22 Sep 2020.
    11. 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.
    12. 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.
    13. ARATA Yoshiyuki, 2022. "Is empirical granularity high enough to cause aggregate fluctuations? The closeness to Gaussian," Discussion papers 22039, Research Institute of Economy, Trade and Industry (RIETI).
    14. Gary Koop & Dimitris Korobilis, 2018. "Forecasting with High-Dimensional Panel VARs," Working Paper series 18-20, Rimini Centre for Economic Analysis.
    15. Davide Pettenuzzo & Francesco Ravazzolo, 2014. "Optimal portfolio choice under decision-based model combinations," Working Paper 2014/15, Norges Bank.
    16. Christiane Baumeister & Dimitris Korobilis & Thomas K. Lee, 2022. "Energy Markets and Global Economic Conditions," The Review of Economics and Statistics, MIT Press, vol. 104(4), pages 828-844, October.
    17. Korobilis, Dimitris & Koop, Gary, 2020. "Bayesian dynamic variable selection in high dimensions," MPRA Paper 100164, University Library of Munich, Germany.
    18. Minchul Shin & Molin Zhong, 2015. "Does Realized Volatility Help Bond Yield Density Prediction?," Finance and Economics Discussion Series 2015-115, Board of Governors of the Federal Reserve System (U.S.).
    19. Cross, Jamie L. & Hou, Chenghan & Koop, Gary & Poon, Aubrey, 2023. "Large stochastic volatility in mean VARs," Journal of Econometrics, Elsevier, vol. 236(1).
    20. 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.
    21. Tamás Kiss & Hoang Nguyen & Pär Österholm, 2021. "Modelling Returns in US Housing Prices—You’re the One for Me, Fat Tails," JRFM, MDPI, vol. 14(11), pages 1-17, October.
    22. Tsionas, Mike G. & Izzeldin, Marwan & Trapani, Lorenzo, 2022. "Estimation of large dimensional time varying VARs using copulas," European Economic Review, Elsevier, vol. 141(C).
    23. Kiss, Tamás & Mazur, Stepan & Nguyen, Hoang & Österholm, Pär, 2021. "Modelling the Relation between the US Real Economy and the Corporate Bond-Yield Spread in Bayesian VARs with non-Gaussian Disturbances," Working Papers 2021:9, Örebro University, School of Business.
    24. Marcellino, Massimiliano & Clark, Todd & Carriero, Andrea & Mertens, Elmar, 2021. "Addressing COVID-19 Outliers in BVARs with Stochastic Volatility," CEPR Discussion Papers 15964, C.E.P.R. Discussion Papers.
    25. Koop, Gary & Korobilis, Dimitris, 2018. "Variational Bayes inference in high-dimensional time-varying parameter models," MPRA Paper 87972, University Library of Munich, Germany.
    26. Blazej Mazur, 2015. "Density forecasts based on disaggregate data: nowcasting Polish inflation," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 15, pages 71-87.
    27. Knüppel, Malte & Schultefrankenfeld, Guido, 2018. "Assessing the uncertainty in central banks' inflation outlooks," Discussion Papers 56/2018, Deutsche Bundesbank.
    28. Antonio Pacifico, 2021. "Structural Panel Bayesian VAR with Multivariate Time-Varying Volatility to Jointly Deal with Structural Changes, Policy Regime Shifts, and Endogeneity Issues," Econometrics, MDPI, vol. 9(2), pages 1-35, May.
    29. Andrea Bastianin & Elisabetta Mirto & Yan Qin & Luca Rossini, 2024. "What drives the European carbon market? Macroeconomic factors and forecasts," Working Papers 2024.02, Fondazione Eni Enrico Mattei.
    30. Marcellino, Massimiliano & Clark, Todd & Carriero, Andrea, 2021. "Nowcasting Tail Risk to Economic Activity at a Weekly Frequency," CEPR Discussion Papers 16496, C.E.P.R. Discussion Papers.
    31. Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano, 2021. "Using time-varying volatility for identification in Vector Autoregressions: An application to endogenous uncertainty," Journal of Econometrics, Elsevier, vol. 225(1), pages 47-73.
    32. Ganics, Gergely & Odendahl, Florens, 2021. "Bayesian VAR forecasts, survey information, and structural change in the euro area," International Journal of Forecasting, Elsevier, vol. 37(2), pages 971-999.
    33. Che, Ming & Zhu, Zixiang & Li, Yujia, 2023. "Geopolitical risk and economic policy uncertainty: Different roles in China's financial cycle," International Review of Financial Analysis, Elsevier, vol. 90(C).
    34. Joshua C. C. Chan, 2017. "The Stochastic Volatility in Mean Model With Time-Varying Parameters: An Application to Inflation Modeling," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(1), pages 17-28, January.
    35. Antolín-Díaz, Juan & Drechsel, Thomas & Petrella, Ivan, 2024. "Advances in nowcasting economic activity: The role of heterogeneous dynamics and fat tails," Journal of Econometrics, Elsevier, vol. 238(2).
    36. Rossi, Barbara & Ganics, Gergely & Sekhposyan, Tatevik, 2020. "From Fixed-event to Fixed-horizon Density Forecasts: Obtaining Measures of Multi-horizon Uncertainty from Survey Density Foreca," CEPR Discussion Papers 14267, C.E.P.R. Discussion Papers.
    37. Gao, Shen & Hou, Chenghan & Nguyen, Bao H., 2021. "Forecasting natural gas prices using highly flexible time-varying parameter models," Economic Modelling, Elsevier, vol. 105(C).
    38. Follett, Lendie & Yu, Cindy, 2019. "Achieving parsimony in Bayesian vector autoregressions with the horseshoe prior," Econometrics and Statistics, Elsevier, vol. 11(C), pages 130-144.
    39. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2016. "Large Vector Autoregressions with Stochastic Volatility and Flexible Priors," Working Papers (Old Series) 1617, Federal Reserve Bank of Cleveland.
    40. Gael M. Martin & David T. Frazier & Worapree Maneesoonthorn & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2022. "Bayesian Forecasting in Economics and Finance: A Modern Review," Papers 2212.03471, arXiv.org, revised Jul 2023.
    41. Christian Hotz-Behofsits & Florian Huber & Thomas O. Zorner, 2018. "Predicting crypto-currencies using sparse non-Gaussian state space models," Papers 1801.06373, arXiv.org, revised Feb 2018.
    42. Flavio Pérez Rojo & Gabriel Rodríguez, 2023. "Jane Haldimand Marcet: Impact of Monetary Policy Shocks in the Peruvian Economy Over Time," Documentos de Trabajo / Working Papers 2023-523, Departamento de Economía - Pontificia Universidad Católica del Perú.
    43. Gael M. Martin & David T. Frazier & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2023. "Bayesian Forecasting in the 21st Century: A Modern Review," Monash Econometrics and Business Statistics Working Papers 1/23, Monash University, Department of Econometrics and Business Statistics.
    44. Huber, Florian & Kaufmann, Daniel, 2016. "Trend Fundamentals and Exchange Rate Dynamics," Department of Economics Working Paper Series 214, WU Vienna University of Economics and Business.
    45. Joshua Chan, 2023. "BVARs and Stochastic Volatility," Papers 2310.14438, arXiv.org.
    46. 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.
    47. Chiu, Ching-Wai (Jeremy) & Mumtaz, Haroon & Pintér, Gábor, 2017. "Forecasting with VAR models: Fat tails and stochastic volatility," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1124-1143.
    48. Francesco Furlanetto & Kåre Hagelund & Frank Hansen & Ørjan Robstad, 2020. "Norges Bank Output Gap Estimates: Forecasting Properties, Reliability and Cyclical Sensitivity," Working Paper 2020/7, Norges Bank.
    49. Emilio Zanetti Chini, 2018. "Forecasting dynamically asymmetric fluctuations of the U.S. business cycle," CREATES Research Papers 2018-13, Department of Economics and Business Economics, Aarhus University.
    50. Joshua C.C. Chan & Rodney W. Strachan, 2023. "Bayesian State Space Models In Macroeconometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 58-75, February.
    51. Justyna Wróblewska & Anna Pajor, 2019. "One-period joint forecasts of Polish inflation, unemployment and interest rate using Bayesian VEC-MSF models," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 11(1), pages 23-45, March.
    52. Matteo Iacopini & Francesco Ravazzolo & Luca Rossini, 2022. "Bayesian Multivariate Quantile Regression with alternative Time-varying Volatility Specifications," Papers 2211.16121, arXiv.org.
    53. Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2020. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," The Review of Economics and Statistics, MIT Press, vol. 102(1), pages 17-33, March.
    54. Joshua C. C. Chan, 2022. "Comparing Stochastic Volatility Specifications for Large Bayesian VARs," Papers 2208.13255, arXiv.org.
    55. Virbickaite, Audrone & Nguyen, Hoang & Tran, Minh-Ngoc, 2023. "Bayesian Predictive Distributions of Oil Returns Using Mixed Data Sampling Volatility Models," Working Papers 2023:7, Örebro University, School of Business.
    56. Bo Zhang & Joshua C.C. Chan & Jamie L. Cross, 2018. "Stochastic volatility models with ARMA innovations: An application to G7 inflation forecasts," CAMA Working Papers 2018-32, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    57. Sebastian Ankargren & Paulina Jon'eus, 2019. "Simulation smoothing for nowcasting with large mixed-frequency VARs," Papers 1907.01075, arXiv.org.
    58. Hou, Chenghan, 2017. "Infinite hidden markov switching VARs with application to macroeconomic forecast," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1025-1043.
    59. Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2018. "Comparing the Forecasting Performances of Linear Models for Electricity Prices with High RES Penetration," Working Papers No 2/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    60. Dominik Bertsche & Robin Braun, 2022. "Identification of Structural Vector Autoregressions by Stochastic Volatility," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 328-341, January.
    61. Rick Bohte & Luca Rossini, 2019. "Comparing the Forecasting of Cryptocurrencies by Bayesian Time-Varying Volatility Models," JRFM, MDPI, vol. 12(3), pages 1-18, September.
    62. Zhang, Bo & Nguyen, Bao H., 2020. "Real-time forecasting of the Australian macroeconomy using Bayesian VARs," Working Papers 2020-12, University of Tasmania, Tasmanian School of Business and Economics.
    63. Gergely Akos Ganics, 2017. "Optimal density forecast combinations," Working Papers 1751, Banco de España.
    64. Pervin, Shahida, 2018. "Dynamics and Interactions of Monetary Policy and Macroeconomic Variables: Empirical Investigation in the UK Economy with Bayesian VAR," MPRA Paper 91816, University Library of Munich, Germany.
    65. Chenghan Hou & Bao Nguyen & Bo Zhang, 2023. "Real‐time forecasting of the Australian macroeconomy using flexible Bayesian VARs," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 418-451, March.
    66. Fresoli, Diego Eduardo & Ruiz Ortega, Esther, 2014. "The uncertainty of conditional returns, volatilities and correlations in DCC models," DES - Working Papers. Statistics and Econometrics. WS ws140202, Universidad Carlos III de Madrid. Departamento de Estadística.
    67. Bognanni, Mark & Zito, John, 2020. "Sequential Bayesian inference for vector autoregressions with stochastic volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    68. Liu, Xiaochun, 2019. "On tail fatness of macroeconomic dynamics," Journal of Macroeconomics, Elsevier, vol. 62(C).
    69. Ching-Wai (Jeremy) Chiu & Haroon Mumtaz & Gabor Pinter, 2016. "Bayesian Vector Autoregressions with Non-Gaussian Shocks," CReMFi Discussion Papers 5, CReMFi, School of Economics and Finance, QMUL.
    70. Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2020. "Large Time-Varying Volatility Models for Electricity Prices," Working Papers No 05/2020, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    71. Marcellino, Massimiliano & Bai, Yu & Carriero, Andrea & Clark, Todd, 2022. "Macroeconomic Forecasting in a Multi-country Context," CEPR Discussion Papers 16994, C.E.P.R. Discussion Papers.
    72. Florian Huber & Luca Rossini, 2020. "Inference in Bayesian Additive Vector Autoregressive Tree Models," Papers 2006.16333, arXiv.org, revised Mar 2021.
    73. Belomestny, Denis & Krymova, Ekaterina & Polbin, Andrey, 2021. "Bayesian TVP-VARX models with time invariant long-run multipliers," Economic Modelling, Elsevier, vol. 101(C).
    74. Lu, Fei & Ma, Feng & Hu, Shiyang, 2024. "Does energy consumption play a key role? Re-evaluating the energy consumption-economic growth nexus from GDP growth rates forecasting," Energy Economics, Elsevier, vol. 129(C).
    75. Todd E. Clark & Gergely Ganics & Elmar Mertens, 2022. "Constructing Fan Charts from the Ragged Edge of SPF Forecasts," Working Papers 22-36, Federal Reserve Bank of Cleveland.
    76. Loaiza-Maya, Rubén & Smith, Michael Stanley & Nott, David J. & Danaher, Peter J., 2022. "Fast and accurate variational inference for models with many latent variables," Journal of Econometrics, Elsevier, vol. 230(2), pages 339-362.
    77. Tore Dubbert, 2022. "Stochastic debt sustainability analysis using time-varying fiscal reaction functions. An agnostic approach to fiscal forecasting," CQE Working Papers 10422, Center for Quantitative Economics (CQE), University of Muenster.
    78. Smith, Michael Stanley & Maneesoonthorn, Worapree, 2018. "Inversion copulas from nonlinear state space models with an application to inflation forecasting," International Journal of Forecasting, Elsevier, vol. 34(3), pages 389-407.
    79. Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87.
    80. Bobeica, Elena & Hartwig, Benny, 2023. "The COVID-19 shock and challenges for inflation modelling," International Journal of Forecasting, Elsevier, vol. 39(1), pages 519-539.
    81. Dimitrios P. Louzis, 2019. "Steady‐state modeling and macroeconomic forecasting quality," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(2), pages 285-314, March.
    82. Andrea Carriero & Massimiliano Marcellino & Tommaso Tornese, 2023. "Blended Identification in Structural VARs," BAFFI CAREFIN Working Papers 23200, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    83. Karlsson, Sune & Mazur, Stepan & Nguyen, Hoang, 2023. "Vector autoregression models with skewness and heavy tails," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).
    84. Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano, 2019. "Large Bayesian vector autoregressions with stochastic volatility and non-conjugate priors," Journal of Econometrics, Elsevier, vol. 212(1), pages 137-154.
    85. Kiss, Tamás & Mazur, Stepan & Nguyen, Hoang, 2022. "Predicting returns and dividend growth — The role of non-Gaussian innovations," Finance Research Letters, Elsevier, vol. 46(PA).
    86. Lijuan Zhang & Neil Fargher, 2022. "Aggregate accounting earnings, special items and growth in gross domestic product: evidence from Australia," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 62(2), pages 2467-2496, June.
    87. Joshua C. C. Chan & Liana Jacobi & Dan Zhu, 2019. "An automated prior robustness analysis in Bayesian model comparison," CAMA Working Papers 2019-45, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    88. Anna Pajor & Justyna Wróblewska, 2022. "Forecasting performance of Bayesian VEC-MSF models for financial data in the presence of long-run relationships," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 12(3), pages 427-448, September.
    89. Marcellino, Massimiliano & Aastveit, Knut Are & Carriero, Andrea & Clark, Todd, 2016. "Have Standard VARs Remained Stable Since the Crisis?," CEPR Discussion Papers 11558, C.E.P.R. Discussion Papers.
    90. Andrea Carriero & Francesco Corsello & Massimiliano Marcellino, 2020. "The economic drivers of volatility and uncertainty," Temi di discussione (Economic working papers) 1285, Bank of Italy, Economic Research and International Relations Area.
    91. Luis Gruber & Gregor Kastner, 2022. "Forecasting macroeconomic data with Bayesian VARs: Sparse or dense? It depends!," Papers 2206.04902, arXiv.org, revised Jul 2023.
    92. Andrea Carriero & Francesco Corsello & Massimiliano Marcellino, 2018. "The global component of inflation volatility," Temi di discussione (Economic working papers) 1170, Bank of Italy, Economic Research and International Relations Area.
    93. Todd E. Clark & Florian Huber & Gary Koop & Massimiliano Marcellino & Michael Pfarrhofer, 2023. "Tail Forecasting With Multivariate Bayesian Additive Regression Trees," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 64(3), pages 979-1022, August.
    94. Gregor Kastner & Florian Huber, 2017. "Sparse Bayesian vector autoregressions in huge dimensions," Papers 1704.03239, arXiv.org, revised Dec 2019.
    95. Matei Demetrescu & Christoph Hanck & Robinson Kruse‐Becher, 2022. "Robust inference under time‐varying volatility: A real‐time evaluation of professional forecasters," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 1010-1030, August.
    96. Krüger, Fabian & Nolte, Ingmar, 2016. "Disagreement versus uncertainty: Evidence from distribution forecasts," Journal of Banking & Finance, Elsevier, vol. 72(S), pages 172-186.
    97. Benjamin K. Johannsen & Elmar Mertens, 2016. "A Time Series Model of Interest Rates With the Effective Lower Bound," Finance and Economics Discussion Series 2016-033, Board of Governors of the Federal Reserve System (U.S.).
    98. Dimitrakopoulos, Stefanos, 2017. "Semiparametric Bayesian inference for time-varying parameter regression models with stochastic volatility," Economics Letters, Elsevier, vol. 150(C), pages 10-14.
    99. Dimitrakopoulos, Stefanos, 2017. "The semiparametric asymmetric stochastic volatility model with time-varying parameters: The case of US inflation," Economics Letters, Elsevier, vol. 155(C), pages 14-18.
    100. Tino Werner, 2022. "Elicitability of Instance and Object Ranking," Decision Analysis, INFORMS, vol. 19(2), pages 123-140, June.
    101. Ellington, Michael, 2022. "Fat tails, serial dependence, and implied volatility index connections," European Journal of Operational Research, Elsevier, vol. 299(2), pages 768-779.
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    103. Zeyyad Mandalinci, 2015. "Forecasting Inflation in Emerging Markets: An Evaluation of Alternative Models," CReMFi Discussion Papers 3, CReMFi, School of Economics and Finance, QMUL.
    104. Rub'en Loaiza-Maya & Michael S. Smith & Worapree Maneesoonthorn, 2017. "Time Series Copulas for Heteroskedastic Data," Papers 1701.07152, arXiv.org.
    105. 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.
    106. Philippe Goulet Coulombe & Mikael Frenette & Karin Klieber, 2023. "From Reactive to Proactive Volatility Modeling with Hemisphere Neural Networks," Working Papers 23-04, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Nov 2023.
    107. Florian Huber & Michael Pfarrhofer & Philipp Piribauer, 2020. "A multi‐country dynamic factor model with stochastic volatility for euro area business cycle analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 911-926, September.
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    109. Joshua C. C. Chan, 2019. "Large Bayesian vector autoregressions," CAMA Working Papers 2019-19, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    110. Niko Hauzenberger & Florian Huber & Karin Klieber, 2020. "Real-time Inflation Forecasting Using Non-linear Dimension Reduction Techniques," Papers 2012.08155, arXiv.org, revised Dec 2021.
    111. Chan, Joshua C.C., 2021. "Minnesota-type adaptive hierarchical priors for large Bayesian VARs," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1212-1226.
    112. Alfan Mansur, 2023. "Simultaneous identification of fiscal and monetary policy shocks," Empirical Economics, Springer, vol. 65(2), pages 697-728, August.
    113. Gong, Xiao-Li & Liu, Xi-Hua & Xiong, Xiong & Zhuang, Xin-Tian, 2019. "Non-Gaussian VARMA model with stochastic volatility and applications in stock market bubbles," Chaos, Solitons & Fractals, Elsevier, vol. 121(C), pages 129-136.
    114. Wang, Yudong & Liu, Li & Wu, Chongfeng, 2017. "Forecasting the real prices of crude oil using forecast combinations over time-varying parameter models," Energy Economics, Elsevier, vol. 66(C), pages 337-348.
    115. Pettenuzzo, Davide & Sabbatucci, Riccardo & Timmermann, Allan, 2023. "Dividend suspensions and cash flows during the Covid-19 pandemic: A dynamic econometric model," Journal of Econometrics, Elsevier, vol. 235(2), pages 1522-1541.
    116. Eller, Markus & Huber, Florian & Schuberth, Helene, 2018. "How Important are Global Factors for Understanding the Dynamics of International Capital Flows?," Working Papers in Economics 2018-2, University of Salzburg.
    117. George Athanasopoulos & Puwasala Gamakumara & Anastasios Panagiotelis & Rob J Hyndman & Mohamed Affan, 2019. "Hierarchical Forecasting," Monash Econometrics and Business Statistics Working Papers 2/19, Monash University, Department of Econometrics and Business Statistics.
    118. Philippe Goulet Coulombe & Mikael Frenette & Karin Klieber, 2023. "From Reactive to Proactive Volatility Modeling with Hemisphere Neural Networks," Papers 2311.16333, arXiv.org, revised Apr 2024.
    119. Didier Nibbering & Richard Paap & Michel van der Wel, 2016. "A Bayesian Infinite Hidden Markov Vector Autoregressive Model," Tinbergen Institute Discussion Papers 16-107/III, Tinbergen Institute, revised 13 Oct 2017.
    120. Beatrice Franzolini & Alexandros Beskos & Maria De Iorio & Warrick Poklewski Koziell & Karolina Grzeszkiewicz, 2022. "Change point detection in dynamic Gaussian graphical models: the impact of COVID-19 pandemic on the US stock market," Papers 2208.00952, arXiv.org, revised May 2023.
    121. Pacifico, Antonio, 2020. "Structural Panel Bayesian VAR with Multivariate Time-varying Volatility to jointly deal with Structural Changes, Policy Regime Shifts, and Endogeneity Issues," MPRA Paper 104292, University Library of Munich, Germany.
    122. Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano & Mertens, Elmar, 2023. "Shadow-rate VARs," Discussion Papers 14/2023, Deutsche Bundesbank.
    123. Ulm, M. & Hambuckers, J., 2022. "Do interest rate differentials drive the volatility of exchange rates? Evidence from an extended stochastic volatility model," Journal of Empirical Finance, Elsevier, vol. 65(C), pages 125-148.
    124. Joshua C.C. Chan & Eric Eisenstat, 2018. "Comparing hybrid time-varying parameter VARs," CAMA Working Papers 2018-31, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    125. Denis Belomestny & Ekaterina Krymova & Andrey Polbin, 2020. "Estimating TVP-VAR models with time invariant long-run multipliers," Papers 2008.00718, arXiv.org.
    126. Cross, Jamie L. & Hou, Chenghan & Poon, Aubrey, 2020. "Macroeconomic forecasting with large Bayesian VARs: Global-local priors and the illusion of sparsity," International Journal of Forecasting, Elsevier, vol. 36(3), pages 899-915.
    127. Thomas A. Lubik & Christian Matthes, 2019. "How Likely Is the Zero Lower Bound?," Economic Quarterly, Federal Reserve Bank of Richmond, issue 1Q, pages 41-54.
    128. Rozina Shaheen, 2019. "Impact of Fiscal Policy on Consumption and Labor Supply under a Time-Varying Structural VAR Model," Economies, MDPI, vol. 7(2), pages 1-15, June.
    129. Michele Lenza & Giorgio E. Primiceri, 2022. "How to estimate a vector autoregression after March 2020," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(4), pages 688-699, June.
    130. Joshua C.C. Chan, 2015. "Specification tests for time-varying parameter models with stochastic volatility," CAMA Working Papers 2015-42, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    131. Mark Bognanni, 2018. "A Class of Time-Varying Parameter Structural VARs for Inference under Exact or Set Identification," Working Papers (Old Series) 1811, Federal Reserve Bank of Cleveland.
    132. Magnus Reif, 2018. "Macroeconomic Uncertainty and Forecasting Macroeconomic Aggregates," ifo Working Paper Series 265, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    133. Helmut Lutkepohl & Fei Shang & Luis Uzeda & Tomasz Wo'zniak, 2024. "Partial Identification of Heteroskedastic Structural VARs: Theory and Bayesian Inference," Papers 2404.11057, arXiv.org.
    134. Hou, Chenghan & Nguyen, Bao H., 2018. "Understanding the US natural gas market: A Markov switching VAR approach," Energy Economics, Elsevier, vol. 75(C), pages 42-53.
    135. Bojaj, Martin M. & Muhadinovic, Milica & Bracanovic, Andrej & Mihailovic, Andrej & Radulovic, Mladen & Jolicic, Ivan & Milosevic, Igor & Milacic, Veselin, 2022. "Forecasting macroeconomic effects of stablecoin adoption: A Bayesian approach," Economic Modelling, Elsevier, vol. 109(C).
    136. Svetlana Makarova, 2018. "European Central Bank Footprints On Inflation Forecast Uncertainty," Economic Inquiry, Western Economic Association International, vol. 56(1), pages 637-652, January.
    137. Mark Bognanni & John Zito, 2019. "Sequential Bayesian Inference for Vector Autoregressions with Stochastic Volatility," Working Papers 19-29, Federal Reserve Bank of Cleveland.
    138. Gao, Shen & Hou, Chenghan & Nguyen, Bao H., 2020. "Forecasting natural gas prices using highly flexible time-varying parameter models," Working Papers 2020-01, University of Tasmania, Tasmanian School of Business and Economics.
    139. Solikin M. Juhro & Bernard Njindan Iyke, 2019. "Forecasting Indonesian Inflation Within An Inflation-Targeting Framework: Do Large-Scale Models Pay Off?," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 22(4), pages 423-436, December.
    140. Cross, Jamie & Poon, Aubrey, 2016. "Forecasting structural change and fat-tailed events in Australian macroeconomic variables," Economic Modelling, Elsevier, vol. 58(C), pages 34-51.
    141. Nguyen, BH & Zhang, Bo, 2022. "Forecasting oil Prices: can large BVARs help?," Working Papers 2022-04, University of Tasmania, Tasmanian School of Business and Economics.
    142. Romain Aumond & Julien Royer, 2024. "Improving the robustness of Markov-switching dynamic factor models with time-varying volatility," Working Papers 2024-04, Center for Research in Economics and Statistics.
    143. Fabian Krüger & Sebastian Lerch & Thordis Thorarinsdottir & Tilmann Gneiting, 2021. "Predictive Inference Based on Markov Chain Monte Carlo Output," International Statistical Review, International Statistical Institute, vol. 89(2), pages 274-301, August.
    144. Charemza, Wojciech & Díaz, Carlos & Makarova, Svetlana, 2019. "Quasi ex-ante inflation forecast uncertainty," International Journal of Forecasting, Elsevier, vol. 35(3), pages 994-1007.
    145. Huber, Florian & Zörner, Thomas O., 2019. "Threshold cointegration in international exchange rates:A Bayesian approach," International Journal of Forecasting, Elsevier, vol. 35(2), pages 458-473.
    146. Jamie L. Cross & Chenghan Hou & Gary Koop, 2021. "Macroeconomic Forecasting with Large Stochastic Volatility in Mean VARs," Working Papers No 04/2021, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    147. Anna Pajor & Justyna Wróblewska & Łukasz Kwiatkowski & Jacek Osiewalski, 2024. "Hybrid SV‐GARCH, t‐GARCH and Markov‐switching covariance structures in VEC models—Which is better from a predictive perspective?," International Statistical Review, International Statistical Institute, vol. 92(1), pages 62-86, April.
    148. Markus Heinrich & Magnus Reif, 2020. "Real-Time Forecasting Using Mixed-Frequency VARS with Time-Varying Parameters," CESifo Working Paper Series 8054, CESifo.
    149. Constantin Anghelache & Madalina-Gabriela Anghel & Alina-Georgiana Solomon, 2017. "National Accounts System: Source of Information in Macroeconomic Forecast," International Journal of Academic Research in Accounting, Finance and Management Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Accounting, Finance and Management Sciences, vol. 7(2), pages 76-82, April.
    150. Fu, Bowen, 2023. "Measuring the trend real interest rate in a data-rich environment," Journal of Economic Dynamics and Control, Elsevier, vol. 147(C).
    151. Aubrey Poon, 2018. "Assessing the Synchronicity and Nature of Australian State Business Cycles," The Economic Record, The Economic Society of Australia, vol. 94(307), pages 372-390, December.
    152. Gordana Djurovic & Vasilije Djurovic & Martin M. Bojaj, 2020. "The macroeconomic effects of COVID-19 in Montenegro: a Bayesian VARX approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-16, December.
    153. Francesco Ravazzolo & Philip Rothman, 2015. "Oil-Price Density Forecasts of U.S. GDP," Working Papers No 10/2015, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    154. Vortelinos, Dimitrios I., 2015. "Out-of-sample evaluation of macro announcements, linearity, long memory, heterogeneity and jumps in mini-futures markets," Review of Financial Economics, Elsevier, vol. 27(C), pages 58-67.
    155. Bo Zhang, 2019. "Real‐time inflation forecast combination for time‐varying coefficient models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(3), pages 175-191, April.
    156. Hartwig, Benny, 2022. "Bayesian VARs and prior calibration in times of COVID-19," Discussion Papers 52/2022, Deutsche Bundesbank.
    157. S. Avouyi-Dovi & C. Labonne & R. Lecat & S. Ray, 2017. "Insight from a Time-Varying VAR Model with Stochastic Volatility of the French Housing and Credit Markets," Working papers 620, Banque de France.
    158. Florin Paul Costel LILEA & Andreea – Ioana MARINESCU, 2017. "Macroeconomic Forecast Models – Concepts And Theoretical Notions," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 65(6), pages 118-123, June.

  17. Todd E. Clark & Edward S. Knotek & Saeed Zaman, 2015. "Measuring Inflation Forecast Uncertainty," Economic Commentary, Federal Reserve Bank of Cleveland, vol. 2015(03), pages 1-6, March.

    Cited by:

    1. Lasha Kavtaradze & Manouchehr Mokhtari, 2018. "Factor Models And Time†Varying Parameter Framework For Forecasting Exchange Rates And Inflation: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 302-334, April.
    2. Randal J. Verbrugge & Saeed Zaman, 2022. "Improving Inflation Forecasts Using Robust Measures," Working Papers 22-23R, Federal Reserve Bank of Cleveland, revised 30 May 2023.
    3. Tumala, Mohammed M & Olubusoye, Olusanya E & Yaaba, Baba N & Yaya, OlaOluwa S & Akanbi, Olawale B, 2017. "Investigating Predictors of Inflation in Nigeria: BMA and WALS Techniques," MPRA Paper 88773, University Library of Munich, Germany, revised Feb 2018.

  18. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2015. "Realtime nowcasting with a Bayesian mixed frequency model with stochastic volatility," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(4), pages 837-862, October.
    See citations under working paper version above.
  19. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2015. "Bayesian VARs: Specification Choices and Forecast Accuracy," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(1), pages 46-73, January.
    See citations under working paper version above.
  20. Clark, Todd E. & McCracken, Michael W., 2015. "Nested forecast model comparisons: A new approach to testing equal accuracy," Journal of Econometrics, Elsevier, vol. 186(1), pages 160-177.
    See citations under working paper version above.
  21. Todd E. Clark, 2014. "The Importance of Trend Inflation in the Search for Missing Disinflation," Economic Commentary, Federal Reserve Bank of Cleveland, issue Aug.

    Cited by:

    1. Łukasz Rawdanowicz & Romain Bouis & Kei-Ichiro Inaba & Ane Kathrine Christensen, 2014. "Secular Stagnation: Evidence and Implications for Economic Policy," OECD Economics Department Working Papers 1169, OECD Publishing.
    2. Karlsson, Sune & Österholm, Pär, 2018. "Is the US Phillips Curve Stable? Evidence from Bayesian VARs," Working Papers 2018:5, Örebro University, School of Business.
    3. Karlsson, Sune & Österholm, Pär, 2018. "A Note on the Stability of the Swedish Philips Curve," Working Papers 2018:6, Örebro University, School of Business.
    4. Özer Karagedikli & Dr John McDermott, 2016. "Inflation expectations and low inflation in New Zealand," Reserve Bank of New Zealand Discussion Paper Series DP2016/09, Reserve Bank of New Zealand.
    5. Conti, Antonio M., 2021. "Resurrecting the Phillips Curve in Low-Inflation Times," Economic Modelling, Elsevier, vol. 96(C), pages 172-195.

  22. Todd E. Clark & Edward S. Knotek, 2014. "2013 Annual Report Why Inflation Is Very Low, and Why It Matters," Annual Report, Federal Reserve Bank of Cleveland, pages 1-42.

    Cited by:

    1. Edward S. Knotek & Saeed Zaman, 2014. "On the Relationships between Wages, Prices, and Economic Activity," Economic Commentary, Federal Reserve Bank of Cleveland, issue Aug.

  23. Todd E. Clark & Michael W. Mccracken, 2014. "Tests Of Equal Forecast Accuracy For Overlapping Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(3), pages 415-430, April.
    See citations under working paper version above.
  24. Clark, Todd E. & Doh, Taeyoung, 2014. "Evaluating alternative models of trend inflation," International Journal of Forecasting, Elsevier, vol. 30(3), pages 426-448.

    Cited by:

    1. Bańbura, Marta & Leiva-Leon, Danilo & Menz, Jan-Oliver, 2021. "Do inflation expectations improve model-based inflation forecasts?," Working Paper Series 2604, European Central Bank.
    2. 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.
    3. 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.
    4. Philippe Goulet Coulombe & Karin Klieber & Christophe Barrette & Maximilian Goebel, 2024. "Maximally Forward-Looking Core Inflation," Papers 2404.05209, arXiv.org.
    5. Marco Del Negro & Domenico Giannone & Marc P. Giannoni & Andrea Tambalotti, 2017. "Safety, Liquidity, and the Natural Rate of Interest," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 48(1 (Spring), pages 235-316.
    6. Michael D. Bauer & Glenn D. Rudebusch, 2017. "Interest Rates Under Falling Stars," CESifo Working Paper Series 6571, CESifo.
    7. Karlsson, Sune & Österholm, Pär, 2018. "Is the US Phillips Curve Stable? Evidence from Bayesian VARs," Working Papers 2018:5, Örebro University, School of Business.
    8. Michael W. McCracken & Michael T. Owyang & Tatevik Sekhposyan, 2021. "Real-Time Forecasting and Scenario Analysis Using a Large Mixed-Frequency Bayesian VAR," International Journal of Central Banking, International Journal of Central Banking, vol. 17(71), pages 1-41, December.
    9. Lenza, Michele & Jarociński, Marek, 2016. "An inflation-predicting measure of the output gap in the euro area," Working Paper Series 1966, European Central Bank.
    10. Kim, Insu & Kim, Young Se, 2019. "Inattentive agents and inflation forecast error dynamics: A Bayesian DSGE approach," Journal of Macroeconomics, Elsevier, vol. 62(C).
    11. Kim, Insu & Yie, Myung-Soo, 2016. "Trend inflation, firms' backward-looking behavior, and inflation gap persistence," Economic Modelling, Elsevier, vol. 58(C), pages 116-125.
    12. Jeremy J. Nalewaik, 2016. "Inflation Expectations and the Stabilization of Inflation : Alternative Hypotheses," Finance and Economics Discussion Series 2016-035, Board of Governors of the Federal Reserve System (U.S.).
    13. Juan Angel Garcia & Aubrey Poon, 2022. "Inflation trends in Asia: implications for central banks [Are Phillips curves useful for forecasting inflation?]," Oxford Economic Papers, Oxford University Press, vol. 74(3), pages 671-700.
    14. Bo Zhang & Joshua C.C. Chan & Jamie L. Cross, 2018. "Stochastic volatility models with ARMA innovations: An application to G7 inflation forecasts," CAMA Working Papers 2018-32, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    15. Karlsson, Sune & Österholm, Pär, 2018. "A Note on the Stability of the Swedish Philips Curve," Working Papers 2018:6, Örebro University, School of Business.
    16. Behera, Harendra Kumar & Patra, Michael Debabrata, 2022. "Measuring trend inflation in India," Journal of Asian Economics, Elsevier, vol. 80(C).
    17. Travis J. Berge, 2017. "Understanding Survey Based Inflation Expectations," Finance and Economics Discussion Series 2017-046, Board of Governors of the Federal Reserve System (U.S.).
    18. Giacomo Sbrana & Andrea Silvestrini & Fabrizio Venditti, 2015. "Short term inflation forecasting: the M.E.T.A. approach," Temi di discussione (Economic working papers) 1016, Bank of Italy, Economic Research and International Relations Area.
    19. Hasenzagl, Thomas & Pellegrino, Filippo & Reichlin, Lucrezia & Ricco, Giovanni, 2017. "A Model of the Fed’s View on Inflation," The Warwick Economics Research Paper Series (TWERPS) 1145, University of Warwick, Department of Economics.
    20. Bańbura, Marta & Bobeica, Elena, 2020. "PCCI – a data-rich measure of underlying inflation in the euro area," Statistics Paper Series 38, European Central Bank.
    21. Ellis W. Tallman & Saeed Zaman, 2015. "Forecasting Inflation: Phillips Curve Effects on Services Price Measures," Working Papers (Old Series) 1519, Federal Reserve Bank of Cleveland.
    22. Bańbura, Marta & Bobeica, Elena, 2023. "Does the Phillips curve help to forecast euro area inflation?," International Journal of Forecasting, Elsevier, vol. 39(1), pages 364-390.
    23. Belomestny, Denis & Krymova, Ekaterina & Polbin, Andrey, 2021. "Bayesian TVP-VARX models with time invariant long-run multipliers," Economic Modelling, Elsevier, vol. 101(C).
    24. Jeremy J. Nalewaik, 2016. "Non-Linear Phillips Curves with Inflation Regime-Switching," Finance and Economics Discussion Series 2016-078, Board of Governors of the Federal Reserve System (U.S.).
    25. Todd E. Clark & Michael W. McCracken, 2014. "Evaluating Conditional Forecasts from Vector Autoregressions," Working Papers 2014-25, Federal Reserve Bank of St. Louis.
    26. Andrle, Michal & Plašil, Miroslav, 2018. "Econometrics with system priors," Economics Letters, Elsevier, vol. 172(C), pages 134-137.
    27. Michal Andrle & Miroslav Plašil, 2016. "System Priors for Econometric Time Series," IMF Working Papers 2016/231, International Monetary Fund.
    28. Beechey, Meredith & Österholm, Pär & Poon, Aubrey, 2023. "Estimating the US trend short-term interest rate," Finance Research Letters, Elsevier, vol. 55(PA).
    29. Davide Delle Monache & Ivan Petrella & Fabrizio Venditti, 2016. "Common Faith or Parting Ways? A Time Varying Parameters Factor Analysis of Euro-Area Inflation," Advances in Econometrics, in: Dynamic Factor Models, volume 35, pages 539-565, Emerald Group Publishing Limited.
    30. Kaihatsu, Sohei & Nakajima, Jouchi, 2018. "Has trend inflation shifted?: An empirical analysis with an equally-spaced regime-switching model," Economic Analysis and Policy, Elsevier, vol. 59(C), pages 69-83.
    31. Todd E. Clark, 2014. "The Importance of Trend Inflation in the Search for Missing Disinflation," Economic Commentary, Federal Reserve Bank of Cleveland, issue Aug.
    32. Jaromir Baxa & Miroslav Plasil & Borek Vasicek, 2013. "Inflation and the Steeplechase Between Economic Activity Variables," Working Papers 2013/15, Czech National Bank.
    33. Mónica Correa-López & Matías Pacce & Kathi Schlepper, 2019. "Exploring trend inFLation dynamics in Euro Area countries," Working Papers 1909, Banco de España.
    34. Manuel Gonzalez-Astudillo, 2018. "An Output Gap Measure for the Euro Area : Exploiting Country-Level and Cross-Sectional Data Heterogeneity," Finance and Economics Discussion Series 2018-040, Board of Governors of the Federal Reserve System (U.S.).
    35. Randal J. Verbrugge & Saeed Zaman, 2022. "Improving Inflation Forecasts Using Robust Measures," Working Papers 22-23R, Federal Reserve Bank of Cleveland, revised 30 May 2023.
    36. Pär Österholm & Aubrey Poon, 2023. "Trend Inflation in Sweden," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 4707-4716, October.
    37. Nikita D. Fokin & Ekaterina V. Malikova & Andrey V. Polbin, 2024. "Time-varying parameters error correction model for real ruble exchange rate and oil prices: What has changed due to capital control and sanctions?," Russian Journal of Economics, ARPHA Platform, vol. 10(1), pages 20-33, March.
    38. Angelia L. Grant, 2017. "The Early Millennium Slowdown: Replicating the Peersman (2005) Results," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(1), pages 224-232, January.
    39. Luis Uzeda, 2022. "State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models," Advances in Econometrics, in: Essays in Honour of Fabio Canova, volume 44, pages 25-53, Emerald Group Publishing Limited.
    40. Christopher J. Erceg & James Hebden & Michael T. Kiley & J. David López-Salido & Robert J. Tetlow, 2018. "Some Implications of Uncertainty and Misperception for Monetary Policy," Finance and Economics Discussion Series 2018-059, Board of Governors of the Federal Reserve System (U.S.).
    41. Alessandro Barbarino & Travis J. Berge & Han Chen & Andrea Stella, 2020. "Which Output Gap Estimates Are Stable in Real Time and Why?," Finance and Economics Discussion Series 2020-102, Board of Governors of the Federal Reserve System (U.S.).
    42. Denis Belomestny & Ekaterina Krymova & Andrey Polbin, 2020. "Estimating TVP-VAR models with time invariant long-run multipliers," Papers 2008.00718, arXiv.org.
    43. Joshua C.C. Chan & Yong Song, 2018. "Measuring Inflation Expectations Uncertainty Using High‐Frequency Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(6), pages 1139-1166, September.
    44. Marta Banbura & Andries van Vlodrop, 2018. "Forecasting with Bayesian Vector Autoregressions with Time Variation in the Mean," Tinbergen Institute Discussion Papers 18-025/IV, Tinbergen Institute.
    45. Joshua C.C. Chan & Todd E. Clark & Gary Koop, 2018. "A New Model of Inflation, Trend Inflation, and Long‐Run Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(1), pages 5-53, February.
    46. Svetlana Makarova, 2018. "European Central Bank Footprints On Inflation Forecast Uncertainty," Economic Inquiry, Western Economic Association International, vol. 56(1), pages 637-652, January.
    47. 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.
    48. Stephen McKnight & Alexander Mihailov & Fabio Rumler, 2018. "NKPC-Based Inflation Forecasts with a Time-Varying Trend," Serie documentos de trabajo del Centro de Estudios Económicos 2018-05, El Colegio de México, Centro de Estudios Económicos.
    49. N. Kundan Kishor & Evan F. Koenig, 2016. "The roles of inflation expectations, core inflation, and slack in real-time inflation forecasting," Working Papers 1613, Federal Reserve Bank of Dallas.

  25. Todd E. Clark & Saeed Zaman, 2013. "Forecasting implications of the recent decline in inflation," Economic Commentary, Federal Reserve Bank of Cleveland, issue Nov.

    Cited by:

    1. Randal J. Verbrugge & Saeed Zaman, 2023. "Post-COVID Inflation Dynamics: Higher for Longer," Working Papers 23-06R, Federal Reserve Bank of Cleveland, revised 20 Jun 2023.
    2. Edward S. Knotek & Saeed Zaman, 2014. "The Slowdown in Residential Investment and Future Prospects," Economic Commentary, Federal Reserve Bank of Cleveland, issue May.

  26. Todd E. Clark, 2012. "Policy rules in macroeconomic forecasting models," Economic Commentary, Federal Reserve Bank of Cleveland, issue Oct.

    Cited by:

    1. Nadav Ben Zeev & Christopher Gunn & Hashmat Khan, 2020. "Monetary News Shocks," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 52(7), pages 1793-1820, October.

  27. Clark, Todd E. & McCracken, Michael W., 2012. "In-sample tests of predictive ability: A new approach," Journal of Econometrics, Elsevier, vol. 170(1), pages 1-14.
    See citations under working paper version above.
  28. Clark, Todd E., 2011. "Real-Time Density Forecasts From Bayesian Vector Autoregressions With Stochastic Volatility," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(3), pages 327-341.

    Cited by:

    1. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    2. Jonas Dovern & Hans Manner, 2018. "Order Invariant Tests for Proper Calibration of Multivariate Density Forecasts," CESifo Working Paper Series 7023, CESifo.
    3. Mike Tsionas & Marwan Izzeldin & Lorenzo Trapani, 2019. "Bayesian estimation of large dimensional time varying VARs using copulas," Papers 1912.12527, arXiv.org.
    4. Bańbura, Marta & Leiva-Leon, Danilo & Menz, Jan-Oliver, 2021. "Do inflation expectations improve model-based inflation forecasts?," Working Paper Series 2604, European Central Bank.
    5. Jonas Dovern & Martin Feldkircher & Florian Huber, 2015. "Does Joint Modelling of the World Economy Pay Off? Evaluating Global Forecasts from a Bayesian GVAR," Working Papers 200, Oesterreichische Nationalbank (Austrian Central Bank).
    6. David Alaminos & M. Belén Salas & Manuel A. Fernández-Gámez, 2022. "Quantum Computing and Deep Learning Methods for GDP Growth Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 803-829, February.
    7. Gaglianone, Wagner Piazza & Guillén, Osmani Teixeira de Carvalho & Figueiredo, Francisco Marcos Rodrigues, 2018. "Estimating inflation persistence by quantile autoregression with quantile-specific unit roots," Economic Modelling, Elsevier, vol. 73(C), pages 407-430.
    8. Huber, Florian, 2016. "Density forecasting using Bayesian global vector autoregressions with stochastic volatility," International Journal of Forecasting, Elsevier, vol. 32(3), pages 818-837.
    9. 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.
    10. Hanck, Christoph & Demetrescu, Matei & Kruse, Robinson, 2015. "Fixed-b Asymptotics for t-Statistics in the Presence of Time-Varying Volatility," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112916, Verein für Socialpolitik / German Economic Association.
    11. 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.
    12. Barbara Rossi & Tatevik Sekhposyan, 2015. "Alternative Tests for Correct Specification of Conditional Predictive Densities," Working Papers 758, Barcelona School of Economics.
    13. Chiara Scotti, 2023. "Financial Shocks in an Uncertain Economy," Working Papers 2308, Federal Reserve Bank of Dallas.
    14. Antonello D'Agostino & Domenico Giannone & Michele Lenza & Michele Modugno, 2015. "Nowcasting Business Cycles: a Bayesian Approach to Dynamic Heterogeneous Factor Models," Finance and Economics Discussion Series 2015-66, Board of Governors of the Federal Reserve System (U.S.).
    15. Dovern, Jonas & Manner, Hans, 2016. "Robust Evaluation of Multivariate Density Forecasts," VfS Annual Conference 2016 (Augsburg): Demographic Change 145547, Verein für Socialpolitik / German Economic Association.
    16. Davide Pettenuzzo & Rossen Valkanov & Allan Timmermann, 2014. "A Bayesian MIDAS Approach to Modeling First and Second Moment Dynamics," Working Papers 76, Brandeis University, Department of Economics and International Business School.
    17. Louzis Dimitrios P., 2016. "Steady-state priors and Bayesian variable selection in VAR forecasting," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(5), pages 495-527, December.
    18. Berg, Tim O. & Henzel, Steffen R., 2015. "Point and density forecasts for the euro area using Bayesian VARs," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1067-1095.
    19. Christopher McDonald & Craig Thamotheram & Shaun P. Vahey & Elizabeth C. Wakerly, 2016. "Assessing the economic value of probabilistic forecasts in the presence of an inflation target," CAMA Working Papers 2016-40, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    20. Joshua C. C. Chan & Gary Koop & Xuewen Yu, 2024. "Large Order-Invariant Bayesian VARs with Stochastic Volatility," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(2), pages 825-837, April.
    21. Gary Koop & Stuart McIntyre & James Mitchell, 2018. "UK Regional Nowcasting using a Mixed Frequency Vector Autoregressive Model," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2018-07, Economic Statistics Centre of Excellence (ESCoE).
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  29. Clark, Todd E. & Davig, Troy, 2011. "Decomposing the declining volatility of long-term inflation expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 35(7), pages 981-999, July.
    See citations under working paper version above.
  30. Todd E. Clark & Michael W. McCracken, 2011. "Reality Checks and Comparisons of Nested Predictive Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 53-66, February.

    Cited by:

    1. Cepni, Oguzhan & Clements, Michael P., 2024. "How local is the local inflation factor? Evidence from emerging European countries," International Journal of Forecasting, Elsevier, vol. 40(1), pages 160-183.
    2. Granziera, Eleonora & Sekhposyan, Tatevik, 2019. "Predicting relative forecasting performance: An empirical investigation," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1636-1657.
    3. Gonçalves, Sílvia & McCracken, Michael W. & Perron, Benoit, 2017. "Tests of equal accuracy for nested models with estimated factors," Journal of Econometrics, Elsevier, vol. 198(2), pages 231-252.
    4. Clark, Todd E. & McCracken, Michael W., 2015. "Nested forecast model comparisons: A new approach to testing equal accuracy," Journal of Econometrics, Elsevier, vol. 186(1), pages 160-177.
    5. Clark, Todd & McCracken, Michael, 2013. "Advances in Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1107-1201, Elsevier.
    6. Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2023. "Large Time‐Varying Volatility Models for Hourly Electricity Prices," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 545-573, June.
    7. Ahmed, Shamim & Tsvetanov, Daniel, 2016. "The predictive performance of commodity futures risk factors," Journal of Banking & Finance, Elsevier, vol. 71(C), pages 20-36.
    8. Nima Nonejad, 2021. "Crude oil price point forecasts of the Norwegian GDP growth rate," Empirical Economics, Springer, vol. 61(5), pages 2913-2930, November.
    9. Firmin Doko Tchatoka & Qazi Haque, 2020. "On bootstrapping tests of equal forecast accuracy for nested models," Economics Discussion / Working Papers 20-06, The University of Western Australia, Department of Economics.
    10. Karen Miranda & Pilar Poncela & Esther Ruiz, 2022. "Dynamic factor models: Does the specification matter?," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 13(1), pages 397-428, May.
    11. Grégory Levieuge, 2017. "Explaining and forecasting bank loans. Good times and crisis," Post-Print hal-03529226, HAL.
    12. Michael W. McCracken & Serena Ng, 2016. "FRED-MD: A Monthly Database for Macroeconomic Research," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 574-589, October.
    13. Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2018. "Comparing the Forecasting Performances of Linear Models for Electricity Prices with High RES Penetration," Working Papers No 2/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    14. Todd E. Clark & Michael W. McCracken, 2011. "Tests of equal forecast accuracy for overlapping models," Working Papers (Old Series) 1121, Federal Reserve Bank of Cleveland.
    15. Rudan Wang & Bruce Morley & Javier Ordóñez, 2015. "The Taylor Rule, Wealth Effects and the Exchange Rate," Working Papers 2015/08, Economics Department, Universitat Jaume I, Castellón (Spain).
    16. Jaqueson K. Galimberti, 2020. "Forecasting GDP Growth from Outer Space," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(4), pages 697-722, August.
    17. Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2020. "Large Time-Varying Volatility Models for Electricity Prices," Working Papers No 05/2020, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    18. Zeng-Hua Lu, 2019. "Extended MinP Tests of Multiple Hypotheses," Papers 1911.04696, arXiv.org.
    19. Christian Hutter & Enzo Weber, 2017. "Mismatch and the Forecasting Performance of Matching Functions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(1), pages 101-123, February.
    20. Sander, Magnus, 2018. "Market timing over the business cycle," Journal of Empirical Finance, Elsevier, vol. 46(C), pages 130-145.
    21. Nguyen, Duc Binh Benno & Prokopczuk, Marcel & Wese Simen, Chardin, 2017. "International Tail Risk and World Fear," Hannover Economic Papers (HEP) dp-620, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    22. Ahmed, Shamim & Liu, Xiaoquan & Valente, Giorgio, 2016. "Can currency-based risk factors help forecast exchange rates?," International Journal of Forecasting, Elsevier, vol. 32(1), pages 75-97.
    23. Khalaf, Lynda & Saunders, Charles J., 2017. "Monte Carlo forecast evaluation with persistent data," International Journal of Forecasting, Elsevier, vol. 33(1), pages 1-10.
    24. Wang, Rudan & Morley, Bruce & Stamatogiannis, Michalis P., 2019. "Forecasting the exchange rate using nonlinear Taylor rule based models," International Journal of Forecasting, Elsevier, vol. 35(2), pages 429-442.
    25. Kolev, Gueorgui I. & Karapandza, Rasa, 2017. "Out-of-sample equity premium predictability and sample split–invariant inference," Journal of Banking & Finance, Elsevier, vol. 84(C), pages 188-201.
    26. Wada, Tatsuma, 2022. "Out-of-sample forecasting of foreign exchange rates: The band spectral regression and LASSO," Journal of International Money and Finance, Elsevier, vol. 128(C).
    27. Hubrich, Kirstin & Granziera, Eleonora & Moon, Hyungsik Roger, 2013. "A predictability test for a small number of nested models," Working Paper Series 1580, European Central Bank.
    28. Enoch Cheng & Clemens C. Struck, 2019. "Time-Series Momentum: A Monte-Carlo Approach," Working Papers 201906, School of Economics, University College Dublin.
    29. 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.
    30. Xiaojie Xu, 2020. "Corn Cash Price Forecasting," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(4), pages 1297-1320, August.
    31. 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.
    32. Tarassow, Artur, 2019. "Forecasting U.S. money growth using economic uncertainty measures and regularisation techniques," International Journal of Forecasting, Elsevier, vol. 35(2), pages 443-457.
    33. Amélie Charles & Olivier Darné & Jae H Kim, 2017. "International Stock Return Predictability: Evidence from New Statistical Tests," Post-Print hal-01626101, HAL.
    34. Daniel Borup & Jonas N. Eriksen & Mads M. Kjær & Martin Thyrsgaard, 2020. "Predicting bond return predictability," CREATES Research Papers 2020-09, Department of Economics and Business Economics, Aarhus University.
    35. Tobback, Ellen & Naudts, Hans & Daelemans, Walter & Junqué de Fortuny, Enric & Martens, David, 2018. "Belgian economic policy uncertainty index: Improvement through text mining," International Journal of Forecasting, Elsevier, vol. 34(2), pages 355-365.

  31. Todd E. Clark & Michael W. McCracken, 2010. "Averaging forecasts from VARs with uncertain instabilities," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 5-29.
    See citations under working paper version above.
  32. Todd E. Clark & Stephen J. Terry, 2010. "Time Variation in the Inflation Passthrough of Energy Prices," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(7), pages 1419-1433, October.
    See citations under working paper version above.
  33. Clark, Todd E. & McCracken, Michael W., 2009. "Tests of Equal Predictive Ability With Real-Time Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 441-454.
    See citations under working paper version above.
  34. Todd E. Clark & Michael W. McCracken, 2009. "Improving Forecast Accuracy By Combining Recursive And Rolling Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 50(2), pages 363-395, May.
    See citations under working paper version above.
  35. Todd E. Clark, 2009. "Is the Great Moderation over? an empirical analysis," Economic Review, Federal Reserve Bank of Kansas City, vol. 94(Q IV), pages 5-42.

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    1. Hanck, Christoph & Demetrescu, Matei & Kruse, Robinson, 2015. "Fixed-b Asymptotics for t-Statistics in the Presence of Time-Varying Volatility," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112916, Verein für Socialpolitik / German Economic Association.
    2. 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.
    3. Giuseppe Cavaliere & Morten Ørregaard Nielsen & Robert Taylor, 2017. "Quasi-Maximum Likelihood Estimation and Bootstrap Inference in Fractional Time Series Models with Heteroskedasticity of Unknown Form," CREATES Research Papers 2017-02, Department of Economics and Business Economics, Aarhus University.
    4. Ahn, Dong-Hyun & Min, Byoung-Kyu & Yoon, Bohyun, 2019. "Why has the size effect disappeared?," Journal of Banking & Finance, Elsevier, vol. 102(C), pages 256-276.
    5. Demetrescu, Matei & Kruse, Robinson, 2015. "Testing heteroskedastic time series for normality," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113221, Verein für Socialpolitik / German Economic Association.
    6. Gerdie Everaert & Martin Iseringhausen, 2017. "Measuring The International Dimension Of Output Volatility," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 17/928, Ghent University, Faculty of Economics and Business Administration.
    7. Antonio Pacifico, 2021. "Structural Panel Bayesian VAR with Multivariate Time-Varying Volatility to Jointly Deal with Structural Changes, Policy Regime Shifts, and Endogeneity Issues," Econometrics, MDPI, vol. 9(2), pages 1-35, May.
    8. Maximo Camacho & Gabriel Perez-Quiros & Hugo Rodríguez Mendizábal, 2009. "High-growth Recoveries, Inventories and the Great Moderation," Working Papers 0917, Banco de España.
    9. Amélie Charles & Olivier Darné & Laurent Ferrara, 2014. "Does the Great Recession imply the end of the Great Moderation? International evidence," Working Papers hal-04141344, HAL.
    10. Valcarcel, Victor J., 2013. "Exchange rate volatility and the time-varying effects of aggregate shocks," Journal of International Money and Finance, Elsevier, vol. 32(C), pages 822-843.
    11. 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.
    12. Breitung, Jörg & Demetrescu, Matei, 2015. "Instrumental variable and variable addition based inference in predictive regressions," Journal of Econometrics, Elsevier, vol. 187(1), pages 358-375.
    13. James Morley & Aarti Singh, 2012. "Inventory Mistakes and the Great Moderation," Discussion Papers 2012-42, School of Economics, The University of New South Wales.
    14. Ha,Jongrim & Ivanova,Anna & Ohnsorge,Franziska Lieselotte & Unsal Portillo Ocando,Derya Filiz, 2019. "Inflation : Concepts, Evolution, and Correlates," Policy Research Working Paper Series 8738, The World Bank.
    15. 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.
    16. Spierdijk, Laura & Umar, Zaghum, 2015. "Stocks, bonds, T-bills and inflation hedging: From great moderation to great recession," Journal of Economics and Business, Elsevier, vol. 79(C), pages 1-37.
    17. Heinrich, Markus, 2020. "Does the Current State of the Business Cycle matter for Real-Time Forecasting? A Mixed-Frequency Threshold VAR approach," EconStor Preprints 219312, ZBW - Leibniz Information Centre for Economics.
    18. Matei Demetrescu & Christoph Hanck & Robinson Kruse, 2016. "Fixed-b Inference in the Presence of Time-Varying Volatility," CREATES Research Papers 2016-01, Department of Economics and Business Economics, Aarhus University.
    19. James Morley & Aarti Singh, 2016. "Inventory Shocks and the Great Moderation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 48(4), pages 699-728, June.
    20. Matei Demetrescu & Christoph Hanck & Adina I. Tarcolea, 2014. "Iv-Based Cointegration Testing In Dependent Panels With Time-Varying Variance," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(5), pages 393-406, August.
    21. Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87.
    22. Gamber, Edward N. & Smith, Julie K. & Weiss, Matthew A., 2011. "Forecast errors before and during the Great Moderation," Journal of Economics and Business, Elsevier, vol. 63(4), pages 278-289, July.
    23. Keating, John W. & Valcarcel, Victor J., 2017. "What's so great about the Great Moderation?," Journal of Macroeconomics, Elsevier, vol. 51(C), pages 115-142.
    24. Luzzetti, Matthew N. & Neumuller, Seth, 2016. "Learning and the dynamics of consumer unsecured debt and bankruptcies," Journal of Economic Dynamics and Control, Elsevier, vol. 67(C), pages 22-39.
    25. Matei Demetrescu & Christoph Hanck, 2013. "Nonlinear IV panel unit root testing under structural breaks in the error variance," Statistical Papers, Springer, vol. 54(4), pages 1043-1066, November.
    26. Ambrose, Brent W. & Coulson, N. Edward & Yoshida, Jiro, 2017. "Inflation Rates Are Very Different When Housing Rents Are Accurately Measured," HIT-REFINED Working Paper Series 71, Institute of Economic Research, Hitotsubashi University.
    27. Smales, Lee A. & Apergis, Nick, 2016. "The influence of FOMC member characteristics on the monetary policy decision-making process," Journal of Banking & Finance, Elsevier, vol. 64(C), pages 216-231.
    28. Valcarcel, Victor J., 2012. "The dynamic adjustments of stock prices to inflation disturbances," Journal of Economics and Business, Elsevier, vol. 64(2), pages 117-144.
    29. Xuan, Chunji & Kim, Chang-Jin & Kim, Dong Heon, 2019. "New dynamics of consumption and output," Journal of Macroeconomics, Elsevier, vol. 60(C), pages 50-59.
    30. Selgin, George & Lastrapes, William D. & White, Lawrence H., 2012. "Has the Fed been a failure?," Journal of Macroeconomics, Elsevier, vol. 34(3), pages 569-596.
    31. Orhan Erem Atesagaoglu, 2017. "Taxes, Financial Markets and the Great Moderation," Bogazici Journal, Review of Social, Economic and Administrative Studies, Bogazici University, Department of Economics, vol. 31(2), pages 83-115.
    32. Ludvigson, Sydney C., 2013. "Advances in Consumption-Based Asset Pricing: Empirical Tests," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 799-906, Elsevier.
    33. Valcarcel, Victor J. & Wohar, Mark E., 2013. "Changes in the oil price-inflation pass-through," Journal of Economics and Business, Elsevier, vol. 68(C), pages 24-42.
    34. Friedrich Lucke, 2022. "The Great Moderation and the Financial Cycle," Working Papers REM 2022/0238, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.

  36. 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.
    See citations under working paper version above.
  37. Todd E. Clark & Taisuke Nakata, 2008. "Has the behavior of inflation and long-term inflation expectations changed?," Economic Review, Federal Reserve Bank of Kansas City, vol. 93(Q I), pages 17-50.

    Cited by:

    1. Riccardo M Masolo & Francesca Monti, 2021. "Ambiguity, Monetary Policy and Trend Inflation," Journal of the European Economic Association, European Economic Association, vol. 19(2), pages 839-871.
    2. M. Ayhan Kose & Hideaki Matsuoka & Ugo Panizza & Dana Vorisek, 2019. "Inflation Expectations: Review and Evidence," Koç University-TUSIAD Economic Research Forum Working Papers 1904, Koc University-TUSIAD Economic Research Forum.
    3. Carrasco, Carlos A., 2013. "El Nuevo Consenso Macroeconómico y la mediocridad del crecimiento económico en México [New Consensus Macroeconomics and the mediocrity of economic growth in Mexico]," MPRA Paper 53391, University Library of Munich, Germany.
    4. Bharat Trehan, 2015. "Survey Measures of Expected Inflation and the Inflation Process," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 47(1), pages 207-222, February.
    5. Bosworth, Barry & Flaaen, Aaron, 2009. "America's Financial Crisis: The End of an Era," ADBI Working Papers 142, Asian Development Bank Institute.
    6. Reicher Christopher Phillip & Utlaut Johannes Friederich, 2013. "Monetary policy shocks and real commodity prices," The B.E. Journal of Macroeconomics, De Gruyter, vol. 13(1), pages 1-35, October.
    7. Bodo Herzog, 2015. "Anchoring of expectations: The role of credible targets in a game experiment," Journal of Economic and Financial Studies (JEFS), LAR Center Press, vol. 3(6), pages 1-15, December.
    8. Gerunov, Anton, 2013. "Връзка Между Икономическите Очаквания И Стопанската Динамика В Ес-27 [Linkages Between Expectations and Economic Dynamics in EU-27]," MPRA Paper 68795, University Library of Munich, Germany.
    9. Demertzis, Maria & Viegi, Nicola & Marcellino, Massimiliano, 2008. "A Measure for Credibility: Tracking US Monetary Developments," CEPR Discussion Papers 7036, C.E.P.R. Discussion Papers.
    10. Reicher, Christopher Phillip & Utlaut, Johannes Friederich, 2011. "The effect of inflation on real commodity prices," Kiel Working Papers 1704, Kiel Institute for the World Economy (IfW Kiel).
    11. Todd E. Clark & Troy Davig, 2008. "An empirical assessment of the relationships among inflation and short- and long-term expectations," Research Working Paper RWP 08-05, Federal Reserve Bank of Kansas City.
    12. Gabriele Galati & Peter Heemeijer & Richhild Moessner, 2011. "How do inflation expectations form? New insights from a high-frequency survey," BIS Working Papers 349, Bank for International Settlements.

  38. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    See citations under working paper version above.
  39. Clark, Todd E. & McCracken, Michael W., 2006. "The Predictive Content of the Output Gap for Inflation: Resolving In-Sample and Out-of-Sample Evidence," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(5), pages 1127-1148, August.
    See citations under working paper version above.
  40. Clark, Todd E. & West, Kenneth D., 2006. "Using out-of-sample mean squared prediction errors to test the martingale difference hypothesis," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 155-186.
    See citations under working paper version above.
  41. Todd E. Clark, 2006. "Disaggregate evidence on the persistence of consumer price inflation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(5), pages 563-587.
    See citations under working paper version above.
  42. 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.

    Cited by:

    1. Paraskevi Salamaliki, 2015. "Economic Policy Uncertainty and Economic Activity: A Focus on Infrequent Structural Shifts," Working Paper Series of the Department of Economics, University of Konstanz 2015-08, Department of Economics, University of Konstanz.
    2. Riccardo DiCecio & Kristie M. Engemann & Michael T. Owyang & Christopher H. Wheeler, 2008. "Changing trends in the labor force: a survey," Review, Federal Reserve Bank of St. Louis, vol. 90(Jan), pages 47-62.
    3. C. Alan Garner, 2008. "Is commercial real estate reliving the 1980s and early 1990s?," Economic Review, Federal Reserve Bank of Kansas City, vol. 93(Q III), pages 89-115.

  43. Clark, Todd E. & Kozicki, Sharon, 2005. "Estimating equilibrium real interest rates in real time," The North American Journal of Economics and Finance, Elsevier, vol. 16(3), pages 395-413, December.
    See citations under working paper version above.
  44. Clark, Todd E. & McCracken, Michael W., 2005. "The power of tests of predictive ability in the presence of structural breaks," Journal of Econometrics, Elsevier, vol. 124(1), pages 1-31, January.

    Cited by:

    1. Frédérick Demers & Annie De Champlain, 2005. "Forecasting Core Inflation in Canada: Should We Forecast the Aggregate or the Components?," Staff Working Papers 05-44, Bank of Canada.
    2. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    3. Mario Porqueddu & Fabrizio Venditti, 2012. "Do food commodity prices have asymmetric effects on Euro-Area inflation?," Temi di discussione (Economic working papers) 878, Bank of Italy, Economic Research and International Relations Area.
    4. Yin, Anwen, 2015. "Forecasting and model averaging with structural breaks," ISU General Staff Papers 201501010800005727, Iowa State University, Department of Economics.
    5. Galvão, Ana Beatriz, 2013. "Changes in predictive ability with mixed frequency data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 395-410.
    6. 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.
    7. Cremaschini, Alessandro & Maruotti, Antonello, 2023. "A finite mixture analysis of structural breaks in the G-7 gross domestic product series," Research in Economics, Elsevier, vol. 77(1), pages 76-90.
    8. Elena Andreou & Eric Ghysels & Andros Kourtellos, 2010. "Should macroeconomic forecasters use daily financial data and how?," University of Cyprus Working Papers in Economics 09-2010, University of Cyprus Department of Economics.
    9. Clark, Todd E. & McCracken, Michael W., 2015. "Nested forecast model comparisons: A new approach to testing equal accuracy," Journal of Econometrics, Elsevier, vol. 186(1), pages 160-177.
    10. Tian, Jing & Anderson, Heather M., 2014. "Forecast combinations under structural break uncertainty," International Journal of Forecasting, Elsevier, vol. 30(1), pages 161-175.
    11. Clark, Todd & McCracken, Michael, 2013. "Advances in Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1107-1201, Elsevier.
    12. Pincheira, Pablo M. & West, Kenneth D., 2016. "A comparison of some out-of-sample tests of predictability in iterated multi-step-ahead forecasts," Research in Economics, Elsevier, vol. 70(2), pages 304-319.
    13. Jing Tian & Heather M. Anderson, 2011. "Forecasting Under Strucural Break Uncertainty," Monash Econometrics and Business Statistics Working Papers 8/11, Monash University, Department of Econometrics and Business Statistics.
    14. Todd E. Clark & Michael W. McCracken, 2009. "In-sample tests of predictive ability: a new approach," Research Working Paper RWP 09-10, Federal Reserve Bank of Kansas City.
    15. Eichengreen, Barry & Mody, Ashoka & Nedeljkovic, Milan & Sarno, Lucio, 2012. "How the Subprime Crisis went global: Evidence from bank credit default swap spreads," Journal of International Money and Finance, Elsevier, vol. 31(5), pages 1299-1318.
    16. Barbara Rossi, 2005. "Are Exchange Rates Really Random Walks? Some Evidence Robust to Parameter Instability," International Finance 0503006, University Library of Munich, Germany.
    17. 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.
    18. Junsoo Lee & John A. List & Mark Strazicich, 2005. "Nonrenewable Resource Prices: Deterministic or Stochastic Trends?," NBER Working Papers 11487, National Bureau of Economic Research, Inc.
    19. McGurk, Zachary, 2020. "US real estate inflation prediction: Exchange rates and net foreign assets," The Quarterly Review of Economics and Finance, Elsevier, vol. 75(C), pages 53-66.
    20. Alessandro Casini, 2018. "Tests for Forecast Instability and Forecast Failure under a Continuous Record Asymptotic Framework," Papers 1803.10883, arXiv.org, revised Dec 2018.
    21. Raffaella Giacomini & Barbara Rossi, 2006. "How Stable is the Forecasting Performance of the Yield Curve for Output Growth?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(s1), pages 783-795, December.
    22. Pablo Pincheira & Nicolás Hardy & Felipe Muñoz, 2021. "“Go Wild for a While!”: A New Test for Forecast Evaluation in Nested Models," Mathematics, MDPI, vol. 9(18), pages 1-28, September.
    23. Brooks, Chris & Burke, Simon P. & Stanescu, Silvia, 2016. "Finite sample weighting of recursive forecast errors," International Journal of Forecasting, Elsevier, vol. 32(2), pages 458-474.
    24. Pincheira, Pablo & Hardy, Nicolás & Muñoz, Felipe, 2021. ""Go wild for a while!": A new asymptotically Normal test for forecast evaluation in nested models," MPRA Paper 105368, University Library of Munich, Germany.
    25. Todd E. Clark & Michael W. McCracken, 2010. "Testing for unconditional predictive ability," Working Papers 2010-031, Federal Reserve Bank of St. Louis.
    26. Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2013. "Biofuels and Food Prices: Searching for the Causal Link," Working Papers 239, University of Milano-Bicocca, Department of Economics, revised Mar 2013.
    27. West, Kenneth D., 2006. "Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 3, pages 99-134, Elsevier.
    28. Atsushi Inoue & Barbara Rossi, 2011. "Out-of-sample forecast tests robust to the choice of window size," Working Papers 11-31, Federal Reserve Bank of Philadelphia.
    29. 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.
    30. Zachary McGurk & Adam Nowak, 2014. "The Relationship Between Stock Returns and Investor Sentiment: Evidence from Social Media," Working Papers 14-38, Department of Economics, West Virginia University.
    31. Yi-Ting Chen, 2016. "Testing for Granger Causality in Moments," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(2), pages 265-288, April.
    32. Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2013. "Food versus Fuel: Causality and Predictability in Distribution," IEFE Working Papers 56, IEFE, Center for Research on Energy and Environmental Economics and Policy, Universita' Bocconi, Milano, Italy.
    33. Dudek, Sławomir, 2008. "Consumer Survey Data and short-term forecasting of households consumption expenditures in Poland," MPRA Paper 19818, University Library of Munich, Germany.
    34. Shiu-Sheng Chen, 2005. "A note on in-sample and out-of-sample tests for Granger causality," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(6), pages 453-464.
    35. Barbara Rossi & Tatevik Sekhposyan, 2010. "Understanding Models' Forecasting Performance," Working Papers 10-56, Duke University, Department of Economics.
    36. Akhter Faroque & William Veloce & Jean-Francois Lamarche, 2012. "Have structural changes eliminated the out-of-sample ability of financial variables to forecast real activity after the mid-1980s? Evidence from the Canadian economy," Applied Economics, Taylor & Francis Journals, vol. 44(30), pages 3965-3985, October.
    37. John Y. Campbell & Samuel B. Thompson, 2005. "Predicting the Equity Premium Out of Sample: Can Anything Beat the Historical Average?," NBER Working Papers 11468, National Bureau of Economic Research, Inc.
    38. Cai Zongwu & Chen Linna & Fang Ying, 2012. "A New Forecasting Model for USD/CNY Exchange Rate," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(3), pages 1-20, September.
    39. Marilena Furno, 2011. "Goodness of Fit and Misspecification in Quantile Regressions," Journal of Educational and Behavioral Statistics, , vol. 36(1), pages 105-131, February.
    40. Zachary McGurk & Adam Nowak & Joshua C. Hall, 2019. "Stock Returns and Investor Sentiment: Textual Analysis and Social Media," Working Papers 19-03, Department of Economics, West Virginia University.
    41. McCracken, Michael W., 2007. "Asymptotics for out of sample tests of Granger causality," Journal of Econometrics, Elsevier, vol. 140(2), pages 719-752, October.
    42. Hubrich, Kirstin & Granziera, Eleonora & Moon, Hyungsik Roger, 2013. "A predictability test for a small number of nested models," Working Paper Series 1580, European Central Bank.
    43. Marcellino, Massimiliano & Musso, Alberto, 2010. "The Forecasting Performance of Real Time Estimates of the Euro Area Output Gap," CEPR Discussion Papers 7763, C.E.P.R. Discussion Papers.
    44. Rossi, Barbara & Sekhposyan, Tatevik, 2010. "Have economic models' forecasting performance for US output growth and inflation changed over time, and when?," International Journal of Forecasting, Elsevier, vol. 26(4), pages 808-835, October.
    45. 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.
    46. Adrian Austin & Swarna Dutt, 2015. "Exchange Rates and Fundamentals: A New Look at the Evidence on Long-Horizon Predictability," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 43(1), pages 147-159, March.
    47. Gantungalag Altansukh & Denise R. Osborn, 2022. "Using structural break inference for forecasting time series," Empirical Economics, Springer, vol. 63(1), pages 1-41, July.
    48. Fabio Busetti & Juri Marcucci & Giovanni Veronese, 2009. "Comparing forecast accuracy: A Monte Carlo investigation," Temi di discussione (Economic working papers) 723, Bank of Italy, Economic Research and International Relations Area.
    49. Smith Aaron, 2012. "Markov Breaks in Regression Models," Journal of Time Series Econometrics, De Gruyter, vol. 4(1), pages 1-35, May.
    50. Gary Cornwall & Jeffrey A. Mills & Beau A. Sauley & Huibin Weng, 2018. "Predictive Testing for Granger Causality via Posterior Simulation and Cross Validation," BEA Working Papers 0156, Bureau of Economic Analysis.
    51. Marcellino, Massimiliano & Musso, Alberto, 2010. "Real time estimates of the euro area output gap: reliability and forecasting performance," Working Paper Series 1157, European Central Bank.
    52. Jing Tian & Qing Zhou, 2018. "Improving equity premium forecasts by incorporating structural break uncertainty," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(S1), pages 619-656, November.

  45. Todd Clark & Michael McCracken, 2005. "Evaluating Direct Multistep Forecasts," Econometric Reviews, Taylor & Francis Journals, vol. 24(4), pages 369-404.

    Cited by:

    1. Norman R. Swanson & Nii Ayi Armah, 2011. "Predictive Inference Under Model Misspecification with an Application to Assessing the Marginal Predictive Content of Money for Output," Departmental Working Papers 201103, Rutgers University, Department of Economics.
    2. Arratibel, Olga & Leiner-Killinger, Nadine & Kamps, Christophe, 2009. "Inflation forecasting in the new EU Member States," Working Paper Series 1015, European Central Bank.
    3. Pablo Pincheira, 2008. "Combining Tests of Predictive Ability Theory and Evidence for Chilean and Canadian Exchange Rates," Working Papers Central Bank of Chile 459, Central Bank of Chile.
    4. Galvão, Ana Beatriz, 2013. "Changes in predictive ability with mixed frequency data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 395-410.
    5. Vivian, Andrew & Wohar, Mark E., 2013. "The output gap and stock returns: Do cyclical fluctuations predict portfolio returns?," International Review of Financial Analysis, Elsevier, vol. 26(C), pages 40-50.
    6. Gonçalves, Sílvia & McCracken, Michael W. & Perron, Benoit, 2017. "Tests of equal accuracy for nested models with estimated factors," Journal of Econometrics, Elsevier, vol. 198(2), pages 231-252.
    7. Berger, Helge & Österholm, Pär, 2008. "Does money matter for U.S. inflation? Evidence from Bayesian VARs," Discussion Papers 2008/9, Free University Berlin, School of Business & Economics.
    8. Ayse Kabukcuoglu & Enrique Martínez-García, 2016. "What Helps Forecast U.S. Inflation?—Mind the Gap!," Koç University-TUSIAD Economic Research Forum Working Papers 1615, Koc University-TUSIAD Economic Research Forum.
    9. Clark, Todd E. & McCracken, Michael W., 2015. "Nested forecast model comparisons: A new approach to testing equal accuracy," Journal of Econometrics, Elsevier, vol. 186(1), pages 160-177.
    10. Clark, Todd & McCracken, Michael, 2013. "Advances in Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1107-1201, Elsevier.
    11. Forni, Mario & Gambetti, Luca, 2016. "Government spending shocks in open economy VARs," Journal of International Economics, Elsevier, vol. 99(C), pages 68-84.
    12. Andres Fernandez & Norman R. Swanson, 2009. "Real-time datasets really do make a difference: definitional change, data release, and forecasting," Working Papers 09-28, Federal Reserve Bank of Philadelphia.
    13. Steven J. Jordan & Andrew Vivian & Mark E. Wohar, 2015. "Location, location, location: currency effects and return predictability?," Applied Economics, Taylor & Francis Journals, vol. 47(18), pages 1883-1898, April.
    14. Bulkley, George & Harris, Richard D.F. & Nawosah, Vivekanand, 2015. "Can behavioral biases explain the rejections of the expectation hypothesis of the term structure of interest rates?," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 179-193.
    15. Calhoun, Gray, 2014. "Out-Of-Sample Comparisons of Overfit Models," Staff General Research Papers Archive 32462, Iowa State University, Department of Economics.
    16. LAURENT, Sébastien & VIOLANTE, Francesco, 2012. "Volatility forecasts evaluation and comparison," LIDAM Reprints CORE 2414, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    17. Pincheira, Pablo M. & West, Kenneth D., 2016. "A comparison of some out-of-sample tests of predictability in iterated multi-step-ahead forecasts," Research in Economics, Elsevier, vol. 70(2), pages 304-319.
    18. Norman Swanson & Richard Urbach, 2013. "Prediction and Simulation Using Simple Models Characterized by Nonstationarity and Seasonality," Departmental Working Papers 201323, Rutgers University, Department of Economics.
    19. David E. Rapach & Jack K. Strauss, 2008. "Structural breaks and GARCH models of exchange rate volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(1), pages 65-90.
    20. Hofmann, Boris, 2009. "Do monetary indicators lead euro area inflation?," Journal of International Money and Finance, Elsevier, vol. 28(7), pages 1165-1181, November.
    21. Altug, Sumru & Çakmaklı, Cem, 2015. "Forecasting Inflation using Survey Expectations and Target Inflation: Evidence for Brazil and Turkey," CEPR Discussion Papers 10419, C.E.P.R. Discussion Papers.
    22. Kevin L. Kliesen, 2008. "Oil and the U.S. macroeconomy: an update and a simple forecasting exercise," Review, Federal Reserve Bank of St. Louis, vol. 90(Sep), pages 505-516.
    23. Magnus Gustavsson & Pär Österholm, 2010. "The presence of unemployment hysteresis in the OECD: what can we learn from out-of-sample forecasts?," Empirical Economics, Springer, vol. 38(3), pages 779-792, June.
    24. Österholm, Pär, 2009. "Improving Unemployment Rate Forecasts Using Survey Data," Working Papers 112, National Institute of Economic Research.
    25. Mogliani, Matteo & Darné, Olivier & Pluyaud, Bertrand, 2017. "The new MIBA model: Real-time nowcasting of French GDP using the Banque de France's monthly business survey," Economic Modelling, Elsevier, vol. 64(C), pages 26-39.
    26. Antonello D'Agostino & Paolo Surico, 2009. "Does Global Liquidity Help to Forecast U.S. Inflation?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(2-3), pages 479-489, March.
    27. Firmin Doko Tchatoka & Qazi Haque, 2020. "On bootstrapping tests of equal forecast accuracy for nested models," Economics Discussion / Working Papers 20-06, The University of Western Australia, Department of Economics.
    28. Boriss Siliverstovs & Konstantin A. Kholodilin, 2006. "On Selection of Components for a Diffusion Index Model: It's not the Size, It's How You Use It," Discussion Papers of DIW Berlin 598, DIW Berlin, German Institute for Economic Research.
    29. Kevin L. Kliesen, 2007. "How well does employment predict output?," Review, Federal Reserve Bank of St. Louis, vol. 89(Sep), pages 433-446.
    30. Peter Reinhard Hansen & Allan Timmermann, 2012. "Equivalence Between Out-of-Sample Forecast Comparisons and Wald Statistics," CREATES Research Papers 2012-45, Department of Economics and Business Economics, Aarhus University.
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    72. Ron Alquist & Lutz Kilian & Robert Vigfusson, 2011. "Forecasting the Price of Oil," Staff Working Papers 11-15, Bank of Canada.
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    78. Onur Ince, 2013. "Forecasting Exchange Rates Out-of-Sample with Panel Methods and Real-Time Data," Working Papers 13-04, Department of Economics, Appalachian State University.
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    81. Chevillon, Guillaume, 2009. "Multi-step forecasting in emerging economies: An investigation of the South African GDP," International Journal of Forecasting, Elsevier, vol. 25(3), pages 602-628, July.
    82. Marcellino, Massimiliano, 2011. "Markov-switching MIDAS models," CEPR Discussion Papers 8234, C.E.P.R. Discussion Papers.
    83. Roi D. Taussig, 2017. "Stickiness of employee expenses and implications for stock returns," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 7(2), pages 297-309, August.
    84. Hardy, Nicolás & Ferreira, Tiago & Quinteros, Maria J. & Magner, Nicolás S., 2023. "“Watch your tone!”: Forecasting mining industry commodity prices with financial report tone," Resources Policy, Elsevier, vol. 86(PA).
    85. Nikolsko-Rzhevskyy, Alex & Prodan, Ruxandra, 2012. "Markov switching and exchange rate predictability," International Journal of Forecasting, Elsevier, vol. 28(2), pages 353-365.
    86. Pincheira, Pablo & Hardy, Nicolas, 2018. "Forecasting Base Metal Prices with Commodity Currencies," MPRA Paper 83564, University Library of Munich, Germany.
    87. Rapach, David E. & Strauss, Jack K., 2012. "Forecasting US state-level employment growth: An amalgamation approach," International Journal of Forecasting, Elsevier, vol. 28(2), pages 315-327.
    88. Wright, Jonathan H. & Zhou, Hao, 2009. "Bond risk premia and realized jump risk," Journal of Banking & Finance, Elsevier, vol. 33(12), pages 2333-2345, December.
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    90. Hubrich, Kirstin & Granziera, Eleonora & Moon, Hyungsik Roger, 2013. "A predictability test for a small number of nested models," Working Paper Series 1580, European Central Bank.
    91. Valseth, Siri, 2016. "Informed trading in Hybrid Bond Markets," UiS Working Papers in Economics and Finance 2016/13, University of Stavanger.
    92. Haskamp, Ulrich, 2017. "Forecasting exchange rates: The time-varying relationship between exchange rates and Taylor rule fundamentals," Ruhr Economic Papers 704, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    93. Mésonnier, J-S., 2006. "The Reliability of Macroeconomic Forecasts based on Real Interest Rate Gap Estimates in Real Time: an Assessment for the Euro Area," Working papers 157, Banque de France.
    94. Medel, Carlos A., 2015. "A Critical Review of Posch, J. and F. Rumler (2015), 'Semi-Structural Forecasting of UK Inflation Based on the Hybrid New Keynesian Phillips Curve,' Journal of Forecasting 34(2): 145-62," MPRA Paper 65665, University Library of Munich, Germany.
    95. Pincheira-Brown, Pablo & Selaive, Jorge & Nolazco, Jose Luis, 2019. "Forecasting inflation in Latin America with core measures," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1060-1071.
    96. Berger, Helge & Österholm, Pär, 2008. "Does money growth granger-cause inflation in the Euro Area? Evidence from output-of-sample forecasts using Bayesian VARs," Discussion Papers 2008/10, Free University Berlin, School of Business & Economics.
    97. Ricardo Mestre & Peter McAdam, 2011. "Is forecasting with large models informative? Assessing the role of judgement in macroeconomic forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(3), pages 303-324, April.
    98. Molodtsova, Tanya & Nikolsko-Rzhevskyy, Alex & Papell, David H., 2008. "Taylor rules with real-time data: A tale of two countries and one exchange rate," Journal of Monetary Economics, Elsevier, vol. 55(Supplemen), pages 63-79, October.
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  46. Todd E. Clark, 2004. "An evaluation of the decline in goods inflation," Economic Review, Federal Reserve Bank of Kansas City, vol. 89(Q II), pages 19-51.

    Cited by:

    1. Miljkovic, Dragan & Jin, Hyun Joung & Paul, Rodney, 2007. "The Role of Productivity Growth and Farmers' Income Protection Policies in the Decline of Relative Farm Prices in the United States," Agribusiness & Applied Economics Report 9368, North Dakota State University, Department of Agribusiness and Applied Economics.
    2. Cobb, Marcus P A, 2018. "Improving Underlying Scenarios for Aggregate Forecasts: A Multi-level Combination Approach," MPRA Paper 88593, University Library of Munich, Germany.
    3. Ellis W. Tallman & Saeed Zaman, 2015. "Forecasting Inflation: Phillips Curve Effects on Services Price Measures," Working Papers (Old Series) 1519, Federal Reserve Bank of Cleveland.
    4. Gernot Pehnelt, 2007. "Globalisation and Inflation in OECD Countries," Jena Economics Research Papers 2007-055, Friedrich-Schiller-University Jena.
    5. Mr. Benjamin L Hunt, 2007. "U.K. Inflation and Relative Prices over the Last Decade: How Important was Globalization?," IMF Working Papers 2007/208, International Monetary Fund.
    6. Robert W. Rich & Randal J. Verbrugge & Saeed Zaman, 2022. "Adjusting Median and Trimmed-Mean Inflation Rates for Bias Based on Skewness," Economic Commentary, Federal Reserve Bank of Cleveland, vol. 2022(05), pages 1-7, March.

  47. Todd E. Clark, 2004. "Can out-of-sample forecast comparisons help prevent overfitting?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(2), pages 115-139.
    See citations under working paper version above.
  48. Clark, Todd E. & van Wincoop, Eric, 2001. "Borders and business cycles," Journal of International Economics, Elsevier, vol. 55(1), pages 59-85, October.
    See citations under working paper version above.
  49. Clark, Todd E. & McCracken, Michael W., 2001. "Tests of equal forecast accuracy and encompassing for nested models," Journal of Econometrics, Elsevier, vol. 105(1), pages 85-110, November.
    See citations under working paper version above.
  50. Todd E. Clark, 2001. "Comparing measures of core inflation," Economic Review, Federal Reserve Bank of Kansas City, vol. 86(Q II), pages 5-31.

    Cited by:

    1. Boysen-Hogrefe, Jens & Dovern, Jonas & Gern, Klaus-Jürgen & Jannsen, Nils & Van Roye, Björn & Scheide, Joachim & Boss, Alfred & Groll, Dominik & Meier, Carsten-Patrick, 2010. "Weltkonjunktur und deutsche Konjunktur im Winter 2009," Kiel Discussion Papers 470/471, Kiel Institute for the World Economy (IfW Kiel).
    2. Priyanka Sahu, 2021. "A Study on the Dynamic Behaviour of Headline Versus Core Inflation: Evidence from India," Global Business Review, International Management Institute, vol. 22(6), pages 1574-1593, December.
    3. Kemp-Benedict, Eric, 2012. "Material needs and aggregate demand," MPRA Paper 39960, University Library of Munich, Germany.
    4. Bermingham, Colin, 2006. "How Useful is Core Inflation for Forecasting Headline Inflation?," Research Technical Papers 11/RT/06, Central Bank of Ireland.
    5. Philippe Goulet Coulombe & Karin Klieber & Christophe Barrette & Maximilian Goebel, 2024. "Maximally Forward-Looking Core Inflation," Papers 2404.05209, arXiv.org.
    6. Mazumder, Sandeep, 2017. "Output gains from accelerating core inflation," Journal of Macroeconomics, Elsevier, vol. 51(C), pages 63-74.
    7. Ashima Goyal & Arjun Singh, 2007. "Through a Glass Darkly," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 1(2), pages 139-166, April.
    8. Jushan Bai & Serena Ng, 2001. "A PANIC Attack on Unit Roots and Cointegration," Boston College Working Papers in Economics 519, Boston College Department of Economics.
    9. Ivan O. Kitov & Oleg I. Kitov, 2008. "Long-Term Linear Trends In Consumer Price Indices," Journal of Applied Economic Sciences, Spiru Haret University, Faculty of Financial Management and Accounting Craiova, vol. 3(2(4)_Summ).
    10. Robert W. Rich & Charles Steindel, 2007. "A comparison of measures of core inflation," Economic Policy Review, Federal Reserve Bank of New York, vol. 13(Dec), pages 19-38.
    11. 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.
    12. 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.
    13. Döhrn, Roland & Barabas, György & Gebhardt, Heinz & Middendorf, Torge & Schäfer, Günter & Zimmermann, Tobias, 2008. "Die wirtschaftliche Entwicklung im Inland: Konjunktur im Zwischentief," RWI Konjunkturberichte, RWI - Leibniz-Institut für Wirtschaftsforschung, vol. 59(1), pages 31-82.
    14. James H. Stock & Mark W. Watson, 2015. "Core Inflation and Trend Inflation," NBER Working Papers 21282, National Bureau of Economic Research, Inc.
    15. Oğuz Atuk & Mustafa Utku Özmen, 2009. "Design and evaluation of core inflation measures for Turkey," IFC Working Papers 3, Bank for International Settlements.
    16. Dowd, Kevin & Cotter, John & Loh, Lixia, 2011. "U.S. Core Inflation: A Wavelet Analysis," Macroeconomic Dynamics, Cambridge University Press, vol. 15(4), pages 513-536, September.
    17. Bańbura, Marta & Bobeica, Elena, 2020. "PCCI – a data-rich measure of underlying inflation in the euro area," Statistics Paper Series 38, European Central Bank.
    18. Altansukh, Gantungalag & Becker, Ralf & Bratsiotis, George J. & Osborn, Denise R., 2017. "What is the Globalisation of Inflation?," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 74, pages 1-27.
    19. Bermingham, Colin, 2010. "A critical assessment of existing estimates of US core inflation," Journal of Macroeconomics, Elsevier, vol. 32(4), pages 993-1007, December.
    20. Stefano Siviero & Giovanni Veronese, 2011. "A policy-sensible benchmark core inflation measure," Oxford Economic Papers, Oxford University Press, vol. 63(4), pages 648-672, December.
    21. Jamie Armour, 2006. "An Evaluation of Core Inflation Measures," Staff Working Papers 06-10, Bank of Canada.
    22. Chrigui Zouhair & Boujelbene Younes, 2009. "The Opportunities for Adopting Inflation Targeting in Tunisia: a Cointegration Study and Transmission Channels of Monetary Policy," Transition Studies Review, Springer;Central Eastern European University Network (CEEUN), vol. 16(3), pages 671-692, October.
    23. Eric Kemp-Benedict, 2019. "Convergence of actual, warranted, and natural growth rates in a Kaleckian-Harrodian-classical model," Working Papers PKWP1913, Post Keynesian Economics Society (PKES).
    24. Guillermo Carlomagno & Jorge Fornero & Andrés Sansone, 2021. "Toward a general framework for constructing and evaluating core inflation measures," Working Papers Central Bank of Chile 913, Central Bank of Chile.
    25. Le Bihan, Hervé & Leiva-Leon, Danilo & Pacce, Matías, 2023. "Underlying inflation and asymmetric risks," Working Paper Series 2848, European Central Bank.
    26. Abdul Aleem & Amine Lahiani, 2011. "Estimation and evaluation of core inflation measures," Applied Economics, Taylor & Francis Journals, vol. 43(25), pages 3619-3629.
    27. Mazumder, Sandeep, 2014. "The sacrifice ratio and core inflation," Journal of Macroeconomics, Elsevier, vol. 40(C), pages 400-421.
    28. Stefano Eusepi & Bart Hobijn & Andrea Tambalotti, 2011. "CONDI: A Cost-of-Nominal-Distortions Index," American Economic Journal: Macroeconomics, American Economic Association, vol. 3(3), pages 53-91, July.
    29. Wynne, Mark A., 1999. "Core inflation: a review of some conceptual issues," Working Paper Series 5, European Central Bank.
    30. Necati Tekatli, 2010. "A New Core Inflation Indicator for Turkey (Turkiye Ekonomisi Icin Yeni Bir Cekirdek Enflasyon Gostergesi)," Working Papers 1019, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    31. Virginie Traclet, 2004. "Monetary and Fiscal Policies in Canada: Some Interesting Principles for EMU?," Staff Working Papers 04-28, Bank of Canada.
    32. Colin Bermingham, 2007. "How Useful is Core Inflation for Forecasting Headline Inflation?," The Economic and Social Review, Economic and Social Studies, vol. 38(3), pages 355-377.
    33. Boss, Alfred & Dovern, Jonas & Groll, Dominik & Meier, Carsten-Patrick & van Roye, Björn & Scheide, Joachim, 2010. "Aufschwung lässt auf sich warten," Open Access Publications from Kiel Institute for the World Economy 32954, Kiel Institute for the World Economy (IfW Kiel).
    34. Pincheira-Brown, Pablo & Selaive, Jorge & Nolazco, Jose Luis, 2019. "Forecasting inflation in Latin America with core measures," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1060-1071.
    35. Gatt, William, 2014. "An evaluation of core inflation measures for Malta," MPRA Paper 61250, University Library of Munich, Germany.
    36. Choi, Chi-Young & O'Sullivan, Róisín, 2013. "Heterogeneous response of disaggregate inflation to monetary policy regime change: The role of price stickiness," Journal of Economic Dynamics and Control, Elsevier, vol. 37(9), pages 1814-1832.
    37. Joice John & Abhiman Das & Sanjay Singh, 2016. "An Application of Quah and Vahey’s SVAR Methodology for Estimating Core Inflation in India: A Note," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 14(1), pages 151-158, June.
    38. Stephen G Cecchetti & Richhild Moessner, 2008. "Commodity prices and inflation dynamics," BIS Quarterly Review, Bank for International Settlements, December.
    39. Robert W. Rich & Charles Steindel, 2005. "A review of core inflation and an evaluation of its measures," Staff Reports 236, Federal Reserve Bank of New York.
    40. Castañeda, Juan Carlos & Chang, Rodrigo, 2023. "Evaluating core inflation measures: A statistical inference approach," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 4(4).
    41. 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.
    42. James Ming Chen & Mobeen Ur Rehman, 2021. "A Pattern New in Every Moment: The Temporal Clustering of Markets for Crude Oil, Refined Fuels, and Other Commodities," Energies, MDPI, vol. 14(19), pages 1-58, September.
    43. Gamber, Edward N. & Smith, Julie K. & Eftimoiu, Raluca, 2015. "The dynamic relationship between core and headline inflation," Journal of Economics and Business, Elsevier, vol. 81(C), pages 38-53.
    44. Misati, Roseline Nyakerario & Munene, Olive, 2015. "Second Round Effects And Pass-Through Of Food Prices To Inflation In Kenya," International Journal of Food and Agricultural Economics (IJFAEC), Alanya Alaaddin Keykubat University, Department of Economics and Finance, vol. 3(3), pages 1-13, July.

  51. Todd E. Clark, 1999. "The Responses Of Prices At Different Stages Of Production To Monetary Policy Shocks," The Review of Economics and Statistics, MIT Press, vol. 81(3), pages 420-433, August.
    See citations under working paper version above.
  52. Todd E. Clark, 1999. "A comparison of the CPI and the PCE price index," Economic Review, Federal Reserve Bank of Kansas City, vol. 84(Q III), pages 15-29.

    Cited by:

    1. Craig S. Hakkio, 2008. "PCE and CPI inflation differentials: converting inflation forecasts," Economic Review, Federal Reserve Bank of Kansas City, vol. 93(Q I), pages 51-68.
    2. Hanson, Michael S., 2004. "The "price puzzle" reconsidered," Journal of Monetary Economics, Elsevier, vol. 51(7), pages 1385-1413, October.
    3. Andrew Bauer & Nicholas Haltom & William B. Peterman, 2004. "Examining contributions to core consumer inflation measures," FRB Atlanta Working Paper 2004-7, Federal Reserve Bank of Atlanta.
    4. William C. Whitesell, 2005. "An inflation goal with multiple reference measures," Finance and Economics Discussion Series 2005-62, Board of Governors of the Federal Reserve System (U.S.).
    5. Roberto M. Billi & George A. Kahn, 2008. "What is the optimal inflation rate?," Economic Review, Federal Reserve Bank of Kansas City, vol. 93(Q II), pages 5-28.
    6. Fan Ding & Alexander L. Wolman, 2005. "Inflation and changing expenditure shares," Economic Quarterly, Federal Reserve Bank of Richmond, vol. 91(Win), pages 1-20.
    7. Andrew Ang & Geert Bekaert & Min Wei, 2005. "Do Macro Variables, Asset Markets or Surveys Forecast Inflation Better?," NBER Working Papers 11538, National Bureau of Economic Research, Inc.
    8. David Fielding & Paul Mizen, 2008. "Evidence on the Functional Relationship between Relative Price Variability and Inflation with Implications for Monetary Policy," Economica, London School of Economics and Political Science, vol. 75(300), pages 683-699, November.
    9. Stefano Eusepi & Bart Hobijn & Andrea Tambalotti, 2011. "CONDI: A Cost-of-Nominal-Distortions Index," American Economic Journal: Macroeconomics, American Economic Association, vol. 3(3), pages 53-91, July.
    10. Ricardo Reis, 2005. "A Dynamic Measure of Inflation," NBER Working Papers 11746, National Bureau of Economic Research, Inc.
    11. Andrew Bauer & Nicholas Haltom & William B. Peterman, 2004. "Decomposing inflation," Economic Review, Federal Reserve Bank of Atlanta, vol. 89(Q 1), pages 39-51.
    12. Emmanuel Carré, 2013. "La cible d'inflation de la Fed : continuité ou rupture ?," Post-Print hal-01419130, HAL.
    13. Christopher Kent, 2004. "Discussion of 'Inflation Measurement for Central Bankers'," RBA Annual Conference Volume (Discontinued), in: Christopher Kent & Simon Guttmann (ed.),The Future of Inflation Targeting, Reserve Bank of Australia.
    14. Binner, J.M. & Tino, P. & Tepper, J. & Anderson, R. & Jones, B. & Kendall, G., 2010. "Does money matter in inflation forecasting?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4793-4808.
    15. Robert W. Rich & Donald Rissmiller, 2001. "Structural change in U.S. wage determination," Staff Reports 117, Federal Reserve Bank of New York.

  53. Clark, Todd E, 1998. "Employment Fluctuations in U.S. Regions and Industries: The Roles of National, Region-Specific, and Industry-Specific Shocks," Journal of Labor Economics, University of Chicago Press, vol. 16(1), pages 202-229, January.

    Cited by:

    1. Shu-hen Chiang, 2009. "The effects of regional diversity on national unemployment through inter-regional migration: new evidence from Taiwan," Applied Economics, Taylor & Francis Journals, vol. 41(19), pages 2505-2511.
    2. Pi-Fem Hsu, 2008. "Sources of employment fluctuations in Taiwan's industries and regions," Applied Economics, Taylor & Francis Journals, vol. 40(17), pages 2279-2293.
    3. Clark, Todd E. & van Wincoop, Eric, 2001. "Borders and business cycles," Journal of International Economics, Elsevier, vol. 55(1), pages 59-85, October.
    4. Gregory D. Hess & Kwanho Shin, 1997. "Risk sharing by households within and across regions and industries," Research Working Paper 97-07, Federal Reserve Bank of Kansas City.
    5. Arabinda Basistha, 2023. "Estimation of short‐run predictive factor for US growth using state employment data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(1), pages 34-50, January.
    6. Michael T. Owyang & Jeremy M. Piger & Howard J. Wall, 2004. "Business cycle phases in U.S. states," Working Papers 2003-011, Federal Reserve Bank of St. Louis.
    7. Carlino, Gerald A. & DeFina, Robert H. & Sill, Keith, 2001. "Sectoral Shocks and Metropolitan Employment Growth," Journal of Urban Economics, Elsevier, vol. 50(3), pages 396-417, November.
    8. Steven J. Davis & R. Jason Faberman & John Haltiwanger & Ron Jarmin & Javier Miranda, 2010. "Business Volatility, Job Destruction, and Unemployment," American Economic Journal: Macroeconomics, American Economic Association, vol. 2(2), pages 259-287, April.
    9. Hubrich, Kirstin & Marcellino, Massimiliano & Beck, Günter W., 2011. "On the importance of sectoral and regional shocks for price-setting," Working Paper Series 1334, European Central Bank.
    10. Fratantoni, Michael & Schuh, Scott, 2003. "Monetary Policy, Housing, and Heterogeneous Regional Markets," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 35(4), pages 557-589, August.
    11. Chortareas, Georgios & Kapetanios, George & Ventouri, Alexia, 2016. "Credit market freedom and cost efficiency in US state banking," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 173-185.
    12. Partridge, Mark D. & Rickman, Dan S., 2003. "The waxing and waning of regional economies: the chicken-egg question of jobs versus people," Journal of Urban Economics, Elsevier, vol. 53(1), pages 76-97, January.
    13. Dick van Dijk & Dennis Fok & Philip Hans Franses, 2005. "A multi-level panel STAR model for US manufacturing sectors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(6), pages 811-827.
    14. Vlachos, Jonas, 2005. "Does Labour Market Risk Increase the Size of the Public Sector? Evidence from Swedish Municipalities," CEPR Discussion Papers 5091, C.E.P.R. Discussion Papers.
    15. Cassou, Steven P. & Vázquez Pérez, Jesús, 2009. "Employment comovements at the sectoral level over the business cycle," DFAEII Working Papers 1988-088X, University of the Basque Country - Department of Foundations of Economic Analysis II.
    16. Michael Owyang & Jeremy Piger & Howard Wall, 2011. "Discordant City Employment Cycles," ERSA conference papers ersa11p1525, European Regional Science Association.
    17. Shu‐hen Chiang, 2012. "The sources of metropolitan unemployment fluctuations in the Greater Taipei metropolitan area," Papers in Regional Science, Wiley Blackwell, vol. 91(4), pages 775-793, November.
    18. Mejía-Reyes, Pablo & Rendón-Rojas, Liliana & Vergara-González, Reyna & Aroca, Patricio, 2018. "International synchronization of the Mexican states business cycles: Explaining factors," The North American Journal of Economics and Finance, Elsevier, vol. 44(C), pages 278-288.
    19. Di Caro, Paolo, 2014. "Regional recessions and recoveries in theory and practice: a resilience-based overview," MPRA Paper 60300, University Library of Munich, Germany.
    20. Nicolaas Groenewold & Guoping Lee & Anping Chen, 2005. "Inter-Regional Spillovers in China: The Importance of Common Shocks and the Definition of Regions," Economics Discussion / Working Papers 05-19, The University of Western Australia, Department of Economics.
    21. Kangasharju, Aki & Pekkala, Sari, 2002. "Adjustment to Regional Labour Market Shocks," Discussion Papers 274, VATT Institute for Economic Research.
    22. Marco Del Negro, 2000. "Asymmetric shocks among U.S. states," FRB Atlanta Working Paper 2000-27, Federal Reserve Bank of Atlanta.
    23. Nicolaas Groenewold & Guoping Lee & Anping Chen, 2006. "Inter-Regional Output Spillovers of Policy Shocks in China," Economics Discussion / Working Papers 06-26, The University of Western Australia, Department of Economics.
    24. Theodore M. Crone, 2004. "A redefinition of economic regions in the U.S," Working Papers 04-12, Federal Reserve Bank of Philadelphia.
    25. André van Stel & Martin Carree & Emilio Congregado & Antonio Golpe, 2013. "Self-employment and Job Generation in Metropolitan Areas, 1969-2009," Scales Research Reports H201306, EIM Business and Policy Research.
    26. Michael Anderson & Jason Bram, 2001. "Declining manufacturing employment in the New York-New Jersey region: 1969-99," Current Issues in Economics and Finance, Federal Reserve Bank of New York, vol. 7(Jan).
    27. Geoffrey Hewings, 2008. "On some conundra in regional science," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 42(2), pages 251-265, June.
    28. Shu-hen Chiang, 2009. "The effects of industrial diversification on regional unemployment in Taiwan: is the portfolio theory applicable?," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 43(4), pages 947-962, December.
    29. Tomomi Miyazaki & Haruo Kondoh, 2022. "Effects of Monetary and Fiscal Policy Interactions on Regional Employment: Evidence from Japan," Discussion Papers 2206, Graduate School of Economics, Kobe University.
    30. Coulson, N. Edward, 1999. "Sectoral sources of metropolitan growth," Regional Science and Urban Economics, Elsevier, vol. 29(6), pages 723-743, November.
    31. Nath, Hiranya K., 2016. "A note on the cyclical behavior of sectoral employment in the U.S," Economic Analysis and Policy, Elsevier, vol. 50(C), pages 52-61.
    32. Bradley Ewing & Jamie Kruse & Mark Thompson, 2009. "Twister! Employment responses to the 3 May 1999 Oklahoma City tornado," Applied Economics, Taylor & Francis Journals, vol. 41(6), pages 691-702.
    33. Alexander Chudik & Janet Koech & Mark Wynne, 2021. "The Heterogeneous Effects of Global and National Business Cycles on Employment in US States and Metropolitan Areas," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(2), pages 495-517, April.
    34. Theodore M. Crone, 2003. "An alternative definition of economic regions in the U.S. based on similarities in state business cycles," Working Papers 03-23, Federal Reserve Bank of Philadelphia.
    35. Breandán Ó'hUallacháin, 2008. "Regional growth transition clubs in the United States," Papers in Regional Science, Wiley Blackwell, vol. 87(1), pages 33-53, March.
    36. Partridge, Mark D. & Rickman, Dan S., 1999. "Which comes first, jobs or people? An analysis of the recent stylized facts," Economics Letters, Elsevier, vol. 64(1), pages 117-123, July.
    37. Owyang, Michael T. & Rapach, David E. & Wall, Howard J., 2009. "States and the business cycle," Journal of Urban Economics, Elsevier, vol. 65(2), pages 181-194, March.
    38. Wall, Howard J., 2013. "The employment cycles of neighboring cities," Regional Science and Urban Economics, Elsevier, vol. 43(1), pages 177-185.
    39. Mark D. Partridge & Dan S. Rickman, 2002. "Did The New Economy Vanquish The Regional Business Cycle?," Contemporary Economic Policy, Western Economic Association International, vol. 20(4), pages 456-469, October.
    40. Sari Pekkala & Aki Kangasharju, 2002. "Regional Labour Market Adjustment: Are Positive and Negative Shocks Different?," LABOUR, CEIS, vol. 16(2), pages 267-286, June.
    41. Christian L. Redfearn, 2000. "The Composition of Metropolitan Employment and the Correlation of Housing Prices Across Metropolitan Areas," Working Paper 8641, USC Lusk Center for Real Estate.
    42. Ewing, Bradley T. & Kruse, Jamie Brown & Thompson, Mark A., 2004. "Employment Dynamics and the Nashville Tornado," Journal of Regional Analysis and Policy, Mid-Continent Regional Science Association, vol. 34(4), pages 1-14.
    43. Nicolaas Groenewold & Guoping Lee & Anping Chen, 2006. "Inter-Regional Output Spillovers in China: Disentangling National from Regional Shocks," Economics Discussion / Working Papers 06-25, The University of Western Australia, Department of Economics.
    44. Rafiq, M.S., 2011. "The optimality of a gulf currency union: Commonalities and idiosyncrasies," Economic Modelling, Elsevier, vol. 28(1-2), pages 728-740, January.
    45. Gerald A. Carlino, 2003. "A confluence of events? explaining fluctuations in local employment," Business Review, Federal Reserve Bank of Philadelphia, issue Q1, pages 6-12.
    46. Campolieti, Michele & Gefang, Deborah & Koop, Gary, 2014. "A new look at variation in employment growth in Canada: The role of industry, provincial, national and external factors," Journal of Economic Dynamics and Control, Elsevier, vol. 41(C), pages 257-275.
    47. Shu-hen Chiang, 2016. "Rising residential rents in Chinese mega cities: The role of monetary policy," Urban Studies, Urban Studies Journal Limited, vol. 53(16), pages 3493-3509, December.
    48. Casto Montero Kuscevic, 2014. "Okun’s law and urban spillovers in US unemployment," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 53(3), pages 719-730, November.
    49. Ron Martin & Peter Sunley & Ben Gardiner & Peter Tyler, 2016. "How Regions React to Recessions: Resilience and the Role of Economic Structure," Regional Studies, Taylor & Francis Journals, vol. 50(4), pages 561-585, April.
    50. Glendon, Spencer P. & Vigdor, Jacob L., 2003. "Thy neighbor's jobs: geography and labor market dynamics," Regional Science and Urban Economics, Elsevier, vol. 33(6), pages 663-693, October.
    51. Carlino, Gerald A. & DeFina, Robert H., 2004. "How strong is co-movement in employment over the business cycle? Evidence from state/sector data," Journal of Urban Economics, Elsevier, vol. 55(2), pages 298-315, March.
    52. Vasile-Aurel Caus & Daniel Badulescu & Mircea Cristian Gherman, 2017. "Using Wavelets In Economics. An Application On The Analysis Of Wage-Price Relation," Oradea Journal of Business and Economics, University of Oradea, Faculty of Economics, vol. 2(1), pages 32-42, March.
    53. Michele Campolieti & Deborah Gefang & Gary Koop, 2013. "A new look at variation in employment growth in Canada," Working Papers 26145565, Lancaster University Management School, Economics Department.
    54. Nicolaas Groenewold & Lee Guoping & Chen Anping, 2007. "Regional output spillovers in China: Estimates from a VAR model," Papers in Regional Science, Wiley Blackwell, vol. 86(1), pages 101-122, March.
    55. Carlos Lamarche & Alberto Porto & Walter Sosa Escudero, 1998. "Aspectos Regionales del Desempleo en la Argentina," IIE, Working Papers 008, IIE, Universidad Nacional de La Plata.
    56. Howley, P.; & Knight, S.;, 2018. "Taking pleasure from neighbours’ misfortune: Comparison effects, social norms and the well-being of the unemployed," Health, Econometrics and Data Group (HEDG) Working Papers 18/02, HEDG, c/o Department of Economics, University of York.
    57. Vidhi Chhaochharia & George M. Korniotis & Alok Kumar, 2020. "Prozac for depressed states? Effect of mood on local economic recessions," Review of Financial Economics, John Wiley & Sons, vol. 38(2), pages 245-274, April.
    58. XIE, Xiao-ting & LIAO, Le-huan, 2015. "云南省县域经济差异的空间分析 [A spatial analysis of the county-level differences in economic growth rates in Yunnan province]," MPRA Paper 68820, University Library of Munich, Germany, revised 20 Aug 2015.
    59. Rafiq, M.S., 2011. "The optimality of a gulf currency union: Commonalities and idiosyncrasies," Economic Modelling, Elsevier, vol. 28(1), pages 728-740.

  54. Clark, Todd E, 1997. "Cross-country Evidence on Long-Run Growth and Inflation," Economic Inquiry, Western Economic Association International, vol. 35(1), pages 70-81, January.
    See citations under working paper version above.
  55. Clark, Todd E, 1996. "Small-Sample Properties of Estimators of Nonlinear Models of Covariance Structure," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 367-373, July.
    See citations under working paper version above.
  56. Todd E. Clark, 1995. "Do producer prices lead consumer prices?," Economic Review, Federal Reserve Bank of Kansas City, vol. 80(Q III), pages 25-39.

    Cited by:

    1. Sidaoui José Julián & Capistrán Carlos & Chiquiar Daniel & Ramos Francia Manuel, 2009. "A Note on the Predictive Content of PPI over CPI Inflation: The Case of Mexico," Working Papers 2009-14, Banco de México.
    2. Muhammad, Shahbaz & Kumar, A.T.K. & Mohammad, Iqbal Tahir, 2012. "Does CPI Granger-Cause WPI? New Extensions from Frequency Domain Approach in Pakistan," MPRA Paper 38816, University Library of Munich, Germany, revised 14 May 2012.
    3. Tiwari, Aviral & Shahbaz, Muhammad, 2010. "Modelling the Relationship between Whole Sale Price and Consumer Price Indices: Cointegration and Causality Analysis for India," MPRA Paper 27333, University Library of Munich, Germany.
    4. Mohd, Rafede & Masih, Mansur, 2018. "Testing the asymmetric and lead-lag relationship between CPI and PPI: an application of the ARDL and NARDL approaches," MPRA Paper 112500, University Library of Munich, Germany.
    5. Gibson, Heather D. & Lazaretou, Sophia, 2001. "Leading inflation indicators for Greece," Economic Modelling, Elsevier, vol. 18(3), pages 325-348, August.
    6. Ahlander, Edvin & Carlsson, Mikael & Klein, Mathias, 2023. "Price Pass-Through Along the Supply Chain:Evidence from PPI and CPI Microdata," Working Paper Series 426, Sveriges Riksbank (Central Bank of Sweden).
    7. Robert Lehmann & Timo Wollmershäuser, 2017. "Inflation is Returning! More and More Firms in Germany Plan to Increase Prices," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 70(05), pages 16-21, March.
    8. George, Edward I. & Sun, Dongchu & Ni, Shawn, 2008. "Bayesian stochastic search for VAR model restrictions," Journal of Econometrics, Elsevier, vol. 142(1), pages 553-580, January.
    9. Yusuf V. Topuz & Hassan Yazdifar & Sunil Sahadev, 2018. "The relation between the producer and consumer price indices: a two-country study," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 17(3), pages 122-130, June.
    10. Niclas Andrén & Lars Oxelheim, 2011. "Exchange rate regime shift and price patterns," International Journal of Managerial Finance, Emerald Group Publishing Limited, vol. 7(2), pages 153-178, April.
    11. Tiwari, Aviral Kumar, 2012. "An empirical investigation of causality between producers' price and consumers' price indices in Australia in frequency domain," Economic Modelling, Elsevier, vol. 29(5), pages 1571-1578.
    12. Tiwari, Aviral Kumar & Mutascu, Mihai & Andries, Alin Marius, 2013. "Decomposing time-frequency relationship between producer price and consumer price indices in Romania through wavelet analysis," Economic Modelling, Elsevier, vol. 31(C), pages 151-159.
    13. Gerba, Eddie, 2015. "Have the US macro-financial linkages changed? The balance sheet dimension," LSE Research Online Documents on Economics 59886, London School of Economics and Political Science, LSE Library.
    14. Ülke, Volkan & Ergun, Ugur, 2013. "The Relationship between Consumer Price and Producer Price Indices in Turkey," MPRA Paper 59437, University Library of Munich, Germany.
    15. Jing Sun & Jinhui Xu & Xin Cheng & Jichao Miao & Hairong Mu, 2023. "Dynamic causality between PPI and CPI in China: A rolling window bootstrap approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(2), pages 1279-1289, April.
    16. Carlos Huertas C. & Munir A. Jalil. B., 2000. "Relación Entre El Índice De Precios Del Productor (Ipp) Y El Índice De Precios Al Consumidor (Ipc)," Borradores de Economia 3449, Banco de la Republica.
    17. Xiangyun Gao & Haizhong An & Weiqiong Zhong, 2013. "Features of the Correlation Structure of Price Indices," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-9, April.
    18. Tiwari, Aviral Kumar & Suresh K.G., & Arouri, Mohamed & Teulon, Frédéric, 2014. "Causality between consumer price and producer price: Evidence from Mexico," Economic Modelling, Elsevier, vol. 36(C), pages 432-440.
    19. Ivo da Rocha Lima Filho, Roberto, 2019. "Does PPI lead CPI IN Brazil?," International Journal of Production Economics, Elsevier, vol. 214(C), pages 73-79.
    20. He, Yongda & Lin, Boqiang, 2019. "Regime differences and industry heterogeneity of the volatility transmission from the energy price to the PPI," Energy, Elsevier, vol. 176(C), pages 900-916.

  57. Clark, Todd E., 1995. "Rents and prices of housing across areas of the United States. A cross-section examination of the present value model," Regional Science and Urban Economics, Elsevier, vol. 25(2), pages 237-247, April.

    Cited by:

    1. Carmona, Juan & Lampe, Markus & Rosés, Joan R., 2011. "Spanish housing markets during the first phase of the rural-urban transition process," IFCS - Working Papers in Economic History.WH wp11-08, Universidad Carlos III de Madrid. Instituto Figuerola.
    2. Winters, John V., 2009. "Wages and prices: Are workers fully compensated for cost of living differences?," Regional Science and Urban Economics, Elsevier, vol. 39(5), pages 632-643, September.
    3. Sofie R. Waltl, 2016. "Estimating aggregate quantile-specific gross rental yields for residential housing in Sydney," Graz Economics Papers 2016-09, University of Graz, Department of Economics.
    4. Rickman, Dan S. & Guettabi, Mouhcine, 2013. "The Great Recession and Nonmetropolitan America," MPRA Paper 44829, University Library of Munich, Germany.
    5. Joshua Gallin, 2008. "The Long‐Run Relationship Between House Prices and Rents," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 36(4), pages 635-658, December.
    6. Vyacheslav Mikhed & Petr Zemčík, 2009. "Testing for Bubbles in Housing Markets: A Panel Data Approach," The Journal of Real Estate Finance and Economics, Springer, vol. 38(4), pages 366-386, May.
    7. Carmona, Juan & Lampe, Markus & Rosés, Joan R., 2012. "Housing markets during the rural-urban transition : evidence from early 20th century Spain," IFCS - Working Papers in Economic History.WH wp12-10, Universidad Carlos III de Madrid. Instituto Figuerola.
    8. Tsai, I-Chun & Chiang, Shu-Hen, 2019. "Exuberance and spillovers in housing markets: Evidence from first- and second-tier cities in China," Regional Science and Urban Economics, Elsevier, vol. 77(C), pages 75-86.
    9. Rosés, Joan R. & Carmona, Juan & Lampe, Markus, 2014. "Housing affordability during the urban transition in Spain," IFCS - Working Papers in Economic History.WH wp14-05, Universidad Carlos III de Madrid. Instituto Figuerola.
    10. Jing Li & Badi Baltagi, 2015. "Cointegration of Matched Home Purchases and Rental Price Indexes - Evidence from Singapore," ERSA conference papers ersa15p571, European Regional Science Association.
    11. Rose Neng Lai & Robert A. Van Order, 2020. "A Tale of Two Countries: Comparing the US and Chinese Housing Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 61(3), pages 505-547, October.
    12. Sharpe, Jamie, 2019. "Re-evaluating the impact of immigration on the U.S. rental housing market," Journal of Urban Economics, Elsevier, vol. 111(C), pages 14-34.
    13. Arthur Grimes & Andrew Aitken, 2007. "House Prices and Rents: Socio-Economic Impacts and Prospects," Working Papers 07_01, Motu Economic and Public Policy Research.
    14. Ge Bao & Guoliang Feng, 2018. "Testing the Dividend Discount Model in Housing Markets: the Role of Risk," The Journal of Real Estate Finance and Economics, Springer, vol. 57(4), pages 677-701, November.
    15. Winters, John V, 2010. "Differences in Quality of Life Estimates Using Rents and Home Values," MPRA Paper 22455, University Library of Munich, Germany.
    16. Galina An & Charles Becker & Enoch Cheng, 2021. "Bubbling Away: Forecasting Real Estate Prices, Rents, and Bubbles in a Transition Economy," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 63(2), pages 263-317, June.
    17. Joshua H. Gallin, 2004. "The long-run relationship between house prices and rents," Finance and Economics Discussion Series 2004-50, Board of Governors of the Federal Reserve System (U.S.).
    18. Petr Zemcik, 2009. "Housing Markets in Central and Eastern Europe: Is There a Bubble in the Czech Republic?," CERGE-EI Working Papers wp390, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    19. Alex S. MacNevin, 1997. "Marginal Effective Tax Rates On Canadian Rental Housing Investments: an Asset Pricing Model Approach," Public Finance Review, , vol. 25(3), pages 306-326, May.
    20. Gavin A. Wood & Rachel Ong, 2013. "When and Why Do Landlords Retain Property Investments?," Urban Studies, Urban Studies Journal Limited, vol. 50(16), pages 3243-3261, December.
    21. Vyacheslav Mikhed & Petr Zemcik, 2007. "Testing for Bubbles in Housing Markets: A Panel Data Approach," CERGE-EI Working Papers wp338, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    22. Petr Zemcik, 2011. "Is There a Real Estate Bubble in the Czech Republic?," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 61(1), pages 49-66, January.
    23. Jung, Hosung & Lee, Jieun, 2017. "The effects of macroprudential policies on house prices: Evidence from an event study using Korean real transaction data," Journal of Financial Stability, Elsevier, vol. 31(C), pages 167-185.

  58. Todd E. Clark, 1994. "Nominal GDP targeting rules: can they stabilize the economy?," Economic Review, Federal Reserve Bank of Kansas City, vol. 79(Q III), pages 11-25.

    Cited by:

    1. Fair, Ray C. & Howrey, E. Philip, 1996. "Evaluating alternative monetary policy rules," Journal of Monetary Economics, Elsevier, vol. 38(2), pages 173-193, October.
    2. Roberto M. Billi, 2020. "Output Gaps and Robust Monetary Policy Rules," International Journal of Central Banking, International Journal of Central Banking, vol. 16(2), pages 125-152, March.
    3. Bilal Bagis, 2017. "Central Banking in the New Era," Eurasian Journal of Economics and Finance, Eurasian Publications, vol. 5(4), pages 197-225.
    4. Thornton, Saranna R., 1998. "Suitable policy instruments for monetary rules," Journal of Economics and Business, Elsevier, vol. 50(4), pages 379-397, July.
    5. Veetil, Vipin P. & Wagner, Richard E., 2018. "Nominal GDP stabilization: Chasing a mirage," The Quarterly Review of Economics and Finance, Elsevier, vol. 67(C), pages 227-236.
    6. Ray C. Fair, 2001. "Actual Federal Reserve policy behavior and interest rate rules," Economic Policy Review, Federal Reserve Bank of New York, issue Mar, pages 61-72.
    7. Ray Fair, 2003. "Optimal Control and Stochastic Simulation of Large Nonlinear Models with Rational Expectations," Computational Economics, Springer;Society for Computational Economics, vol. 21(3), pages 245-256, June.
    8. Thornton, Saranna Robinson, 2000. "How do broader monetary aggregates and divisia measures of money perform in McCallum's adaptive monetary rule?," Journal of Economics and Business, Elsevier, vol. 52(1-2), pages 181-204.
    9. Ray C. Fair, 2000. "Estimated, Calibrated, and Optimal Interest Rate Rules," Cowles Foundation Discussion Papers 1258, Cowles Foundation for Research in Economics, Yale University.

Chapters

  1. Clark, Todd & McCracken, Michael, 2013. "Advances in Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1107-1201, Elsevier.
    See citations under working paper version above.Sorry, no citations of chapters recorded.
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