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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. 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)
  3. 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)
  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. Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano, 2024. "Specification Choices in Quantile Regression for Empirical Macroeconomics," CEPR Discussion Papers 18901, C.E.P.R. Discussion Papers.

    Cited by:

    1. 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.

  2. Clark, Todd & Huber, Florian & Koop, Gary & Marcellino, Massimiliano & 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. Joshua C. C. Chan, 2024. "BVARs and stochastic volatility," Chapters, in: Michael P. Clements & Ana Beatriz Galvão (ed.), Handbook of Research Methods and Applications in Macroeconomic Forecasting, chapter 3, pages 43-67, Edward Elgar Publishing.
    3. 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.
    4. 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.
    5. 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.
    6. Joseph, Andreas & Potjagailo, Galina & Chakraborty, Chiranjit & Kapetanios, George, 2024. "Forecasting UK inflation bottom up," International Journal of Forecasting, Elsevier, vol. 40(4), pages 1521-1538.
    7. Tibor Szendrei & Arnab Bhattacharjee, 2024. "Momentum Informed Inflation-at-Risk," Papers 2408.12286, arXiv.org.
    8. Sui, Jianli & Lv, Wenqiang & Gao, Xiang & Koedijk, Kees G., 2024. "China’s GDP-at-Risk: Real-Time Monitoring, Risk Tracing, and Macroeconomic Policy Effects," Journal of International Money and Finance, Elsevier, vol. 147(C).
    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. Massimiliano MARCELLINO & Michael PFARRHOFER, 2024. "Bayesian nonparametric methods for macroeconomic forecasting," BAFFI CAREFIN Working Papers 24224, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    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.
    12. Huang, Yu-Fan & Liao, Wenting & Wang, Taining, 2024. "Does US financial uncertainty spill over through the (asymmetric) international credit channel? The role of market expectations," Journal of International Money and Finance, Elsevier, vol. 148(C).
    13. Martin Feldkircher & Luis Gruber & Florian Huber & Gregor Kastner, 2024. "Sophisticated and small versus simple and sizeable: When does it pay off to introduce drifting coefficients in Bayesian vector autoregressions?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 2126-2145, September.
    14. Martin, Gael M. & Frazier, David T. & Maneesoonthorn, Worapree & Loaiza-Maya, Rubén & Huber, Florian & Koop, Gary & Maheu, John & Nibbering, Didier & Panagiotelis, Anastasios, 2024. "Bayesian forecasting in economics and finance: A modern review," International Journal of Forecasting, Elsevier, vol. 40(2), pages 811-839.
    15. Zhemkov, Michael, 2021. "Nowcasting Russian GDP using forecast combination approach," International Economics, Elsevier, vol. 168(C), pages 10-24.
    16. Lenza, Michele & Moutachaker, Inès & Paredes, Joan, 2023. "Forecasting euro area inflation with machine-learning models," Research Bulletin, European Central Bank, vol. 112.
    17. Florian Huber & Karin Klieber & Massimiliano Marcellino & Luca Onorante & Michael Pfarrhofer, 2024. "Asymmetries in Financial Spillovers," Papers 2410.16214, arXiv.org.
    18. 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.

  3. 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. Lenza, Michele & Moutachaker, Inès & Paredes, Joan, 2023. "Density forecasts of inflation: a quantile regression forest approach," Working Paper Series 2830, European Central Bank.
    4. Joseph, Andreas & Potjagailo, Galina & Chakraborty, Chiranjit & Kapetanios, George, 2024. "Forecasting UK inflation bottom up," International Journal of Forecasting, Elsevier, vol. 40(4), pages 1521-1538.
    5. 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. Jacobi Liana & Kwok Chun Fung & Ramírez-Hassan Andrés & Nghiem Nhung, 2024. "Posterior Manifolds over Prior Parameter Regions: Beyond Pointwise Sensitivity Assessments for Posterior Statistics from MCMC Inference," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 28(2), pages 403-434, April.
    7. Martin, Gael M. & Frazier, David T. & Maneesoonthorn, Worapree & Loaiza-Maya, Rubén & Huber, Florian & Koop, Gary & Maheu, John & Nibbering, Didier & Panagiotelis, Anastasios, 2024. "Bayesian forecasting in economics and finance: A modern review," International Journal of Forecasting, Elsevier, vol. 40(2), pages 811-839.
    8. 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.

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

    Cited by:

    1. 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.
    2. Hilde C. Bjørnland & Roberto Casarin & Marco Lorusso & Francesco Ravazzolo, 2023. "Fiscal Policy Regimes in Resource-Rich Economies," Working Papers No 13/2023, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    3. 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.
    4. 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.
    5. Martin Gachter & Elias Hasler & Florian Huber, 2023. "A tale of two tails: 130 years of growth-at-risk," Papers 2302.08920, arXiv.org.
    6. Pfarrhofer, Michael, 2022. "Modeling tail risks of inflation using unobserved component quantile regressions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    7. Patrick A. Adams & Tobias Adrian & Nina Boyarchenko & Domenico Giannone, 2020. "Forecasting Macroeconomic Risks," Staff Reports 914, Federal Reserve Bank of New York.
    8. Schick, Manuel, 2024. "Real-time Nowcasting Growth-at-Risk using the Survey of Professional Forecasters," Working Papers 0750, University of Heidelberg, Department of Economics.
    9. 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).
    10. 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.
    11. Sune Karlsson & Stepan Mazur & Hoang Nguyen, 2021. "Vector autoregression models with skewness and heavy tails," Papers 2105.11182, arXiv.org.
    12. Sui, Jianli & Lv, Wenqiang & Gao, Xiang & Koedijk, Kees G., 2024. "China’s GDP-at-Risk: Real-Time Monitoring, Risk Tracing, and Macroeconomic Policy Effects," Journal of International Money and Finance, Elsevier, vol. 147(C).
    13. Iseringhausen, Martin, 2024. "A time-varying skewness model for Growth-at-Risk," International Journal of Forecasting, Elsevier, vol. 40(1), pages 229-246.
    14. Huang, Yu-Fan & Liao, Wenting & Luo, Sui & Ma, Jun, 2024. "Financial conditions, macroeconomic uncertainty, and macroeconomic tail risks," Journal of Economic Dynamics and Control, Elsevier, vol. 163(C).
    15. Kevin Moran & Dalibor Stevanovic & Stephane Surprenant, 2024. "Risk Scenarios and Macroeconomic Forecasts," Working Papers 24-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Apr 2024.
    16. Tamás Kiss & Stepan Mazur & Hoang Nguyen & Pär Österholm, 2023. "Modeling the relation between the US real economy and the corporate bond‐yield spread in Bayesian VARs with non‐Gaussian innovations," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 347-368, March.
    17. 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).
    18. Falconio, Andrea & Manganelli, Simone, 2020. "Financial conditions, business cycle fluctuations and growth at risk," Working Paper Series 2470, European Central Bank.
    19. Botelho, Vasco & Foroni, Claudia & Renzetti, Andrea, 2024. "Labour at risk," European Economic Review, Elsevier, vol. 170(C).
    20. 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.
    21. Kevin Moran & Dalibor Stevanovic & Stéphane Surprenant, 2024. "Risk Scenarios and Macroeconomic Impacts: Insights for Canadian Policy," CIRANO Working Papers 2024s-03, CIRANO.
    22. Deng, Chuang & Wu, Jian, 2023. "Macroeconomic downside risk and the effect of monetary policy," Finance Research Letters, Elsevier, vol. 54(C).
    23. 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.

  5. Bai, Yu & Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano, 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.
    2. Florian Huber & Gary Koop & Massimiliano Marcellino & Tobias Scheckel, 2024. "Bayesian modelling of VAR precision matrices using stochastic block networks," Papers 2407.16349, arXiv.org.
    3. Florian Huber & Karin Klieber & Massimiliano Marcellino & Luca Onorante & Michael Pfarrhofer, 2024. "Asymmetries in Financial Spillovers," Papers 2410.16214, arXiv.org.

  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. Gloria Gonzalez-Rivera & Vladimir Rodriguez-Caballero & Esther Ruiz, 2023. "Expecting the unexpected: Stressed scenarios for economic growth," Working Papers 202314, University of California at Riverside, Department of Economics.
    2. Chuliá, Helena & Garrón, Ignacio & Uribe, Jorge M., 2024. "Daily growth at risk: Financial or real drivers? The answer is not always the same," International Journal of Forecasting, Elsevier, vol. 40(2), pages 762-776.
    3. James Mitchell & Aubrey Poon & Dan Zhu, 2022. "Constructing Density Forecasts from Quantile Regressions: Multimodality in Macro-Financial Dynamics," Working Papers 22-12R, Federal Reserve Bank of Cleveland, revised 11 Apr 2023.
    4. Matteo Iacopini & Francesco Ravazzolo & Luca Rossini, 2022. "Bayesian Multivariate Quantile Regression with alternative Time-varying Volatility Specifications," Papers 2211.16121, arXiv.org, revised Aug 2024.
    5. Schick, Manuel, 2024. "Real-time Nowcasting Growth-at-Risk using the Survey of Professional Forecasters," Working Papers 0750, University of Heidelberg, Department of Economics.
    6. Antolin-Diaz, Juan & Drechsel, Thomas & Petrella, Ivan, 2023. "Advances in Nowcasting Economic Activity: The Role of Heterogeneous Dynamics and Fat Tails," CEPR Discussion Papers 17800, C.E.P.R. Discussion Papers.
    7. Iacopini, Matteo & Poon, Aubrey & Rossini, Luca & Zhu, Dan, 2023. "Bayesian mixed-frequency quantile vector autoregression: Eliciting tail risks of monthly US GDP," Journal of Economic Dynamics and Control, Elsevier, vol. 157(C).
    8. 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.
    9. Eraslan, Sercan & Reif, Magnus, 2023. "A latent weekly GDP indicator for Germany," Technical Papers 08/2023, Deutsche Bundesbank.
    10. Knut Are Aastveit & Tuva Marie Fastbø & Eleonora Granziera & Kenneth Sæterhagen Paulsen & Kjersti Næss Torstensen, 2024. "Nowcasting Norwegian household consumption with debit card transaction data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(7), pages 1220-1244, November.
    11. Ignacio Garr'on & Andrey Ramos, 2025. "High-frequency Density Nowcasts of U.S. State-Level Carbon Dioxide Emissions," Papers 2501.03380, arXiv.org.
    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. Matteo Iacopini & Aubrey Poon & Luca Rossini & Dan Zhu, 2024. "A Quantile Nelson-Siegel model," Papers 2401.09874, arXiv.org.

  7. 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. Olli Palm'en, 2022. "Macroeconomic Effect of Uncertainty and Financial Shocks: a non-Gaussian VAR approach," Papers 2202.10834, arXiv.org.
    2. Gnangnon, Sèna Kimm, 2023. "Effect of Economic Uncertainty on Remittances Flows from Developed Countries," EconStor Preprints 279480, ZBW - Leibniz Information Centre for Economics.
    3. 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).
    4. 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.
    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. Sune Karlsson & Stepan Mazur & Hoang Nguyen, 2021. "Vector autoregression models with skewness and heavy tails," Papers 2105.11182, arXiv.org.
    8. 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.
    9. 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).
    10. Koivisto, Tero, 2024. "Asset price shocks and inflation in the Finnish economy," BoF Economics Review 6/2024, Bank of Finland.
    11. Moreno-Pérez, Carlos & Minozzo, Marco, 2024. "‘Making text talk’: The minutes of the Central Bank of Brazil and the real economy," Journal of International Money and Finance, Elsevier, vol. 147(C).
    12. Dibiasi, Andreas & Sarferaz, Samad, 2023. "Measuring macroeconomic uncertainty: A cross-country analysis," European Economic Review, Elsevier, vol. 153(C).
    13. Sèna Kimm Gnangnon, 2024. "The effect of economic uncertainty on remittance flows from developed countries," Economic Affairs, Wiley Blackwell, vol. 44(2), pages 267-280, June.
    14. 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).
    15. Emanuele Bacchiocchi & Catalin Dragomirescu-Gaina, 2022. "Uncertainty spill-overs: when policy and financial realms overlap," Working Papers wp1174, Dipartimento Scienze Economiche, Universita' di Bologna.
    16. Ambrocio, Gene, 2020. "Inflationary household uncertainty shocks," Bank of Finland Research Discussion Papers 5/2020, Bank of Finland.
    17. Gabriele Fiorentini & Alessio Moneta & Francesca Papagni, 2024. "Identification of one independent shock in structural VARs," LEM Papers Series 2024/28, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.

  8. 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.

  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.
    3. Klieber, Karin, 2024. "Non-linear dimension reduction in factor-augmented vector autoregressions," Journal of Economic Dynamics and Control, Elsevier, vol. 159(C).

  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. Lloyd, S. & Manuel, E. & Panchev, K., 2021. "Foreign Vulnerabilities, Domestic Risks: The Global Drivers of GDP-at-Risk," Cambridge Working Papers in Economics 2156, Faculty of Economics, University of Cambridge.
    2. 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.
    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. Ignace De Vos & Gerdie Everaert, 2024. "GLS Estimation of Local Projections: Trading Robustness for Efficiency," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 24/1095, Ghent University, Faculty of Economics and Business Administration.
    5. Lv, Mengdi & Jiao, Shoukun & Ye, Shiqi & Song, Hongmei & Xu, Jiexin & Ye, Wuyi, 2024. "Assessing time-varying risk in China’s GDP growth," Economics Letters, Elsevier, vol. 242(C).
    6. 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.
    7. Niko Hauzenberger & Florian Huber & Karin Klieber & Massimiliano Marcellino, 2024. "Machine Learning the Macroeconomic Effects of Financial Shocks," Papers 2412.07649, arXiv.org.
    8. Vegard Høghaug Larsen & Nicolò Maffei-Faccioli & Laura Pagenhardt, 2023. "Where do they care? The ECB in the media and inflation expectations," Working Papers No 04/2023, 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. Cross, Jamie L. & Hou, Chenghan & Koop, Gary & Poon, Aubrey, 2023. "Large stochastic volatility in mean VARs," Journal of Econometrics, Elsevier, vol. 236(1).
    2. Knüppel, Malte & Krüger, Fabian & Pohle, Marc-Oliver, 2022. "Score-based calibration testing for multivariate forecast distributions," Discussion Papers 50/2022, Deutsche Bundesbank.
    3. 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.
    4. 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.
    5. 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.
    6. Morão, Hugo, 2024. "An economic policy uncertainty index for Portugal," International Economics, Elsevier, vol. 178(C).
    7. Evgenidis, Anastasios & Fasianos, Apostolos, 2023. "Modelling monetary policy’s impact on labour markets under Covid-19," Economics Letters, Elsevier, vol. 230(C).
    8. Frank Schorfheide & Dongho Song, 2024. "Real-Time Forecasting with a (Standard) Mixed-Frequency VAR During a Pandemic," International Journal of Central Banking, International Journal of Central Banking, vol. 20(4), pages 275-320, October.
    9. Joshua C. C. Chan, 2022. "Comparing Stochastic Volatility Specifications for Large Bayesian VARs," Papers 2208.13255, arXiv.org.
    10. 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.
    11. Prüser, Jan, 2021. "The horseshoe prior for time-varying parameter VARs and Monetary Policy," Journal of Economic Dynamics and Control, Elsevier, vol. 129(C).
    12. Colunga-Ramos, Luis Fernando & Cepeda, Leonardo E. Torre, 2024. "Regional supply, demand and labor shocks on the manufacturing sector during COVID-19 in Mexico," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 5(2).
    13. 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.
    14. Sune Karlsson & Stepan Mazur & Hoang Nguyen, 2021. "Vector autoregression models with skewness and heavy tails," Papers 2105.11182, arXiv.org.
    15. José R. Maria & Paulo Júlio, 2023. "Trends and cycles during the COVID-19 pandemic period," Working Papers w202311, Banco de Portugal, Economics and Research Department.
    16. Antolin-Diaz, Juan & Drechsel, Thomas & Petrella, Ivan, 2023. "Advances in Nowcasting Economic Activity: The Role of Heterogeneous Dynamics and Fat Tails," CEPR Discussion Papers 17800, C.E.P.R. Discussion Papers.
    17. 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.
    18. Luis J. Álvarez & Florens Odendahl, 2022. "Data outliers and Bayesian VARs in the Euro Area," Working Papers 2239, Banco de España.
    19. Budnik, Katarzyna & Ponte Marques, Aurea & Giglio, Carla & Grassi, Alberto & Durrani, Agha & Figueres, Juan Manuel & Konietschke, Paul & Le Grand, Catherine & Metzler, Julian & Población García, Franc, 2024. "Advancements in stress-testing methodologies for financial stability applications," Occasional Paper Series 348, European Central Bank.
    20. Kiss, Tamas & Nguyen, Hoang & Österholm, Pär, 2022. "Modelling Okun’s Law – Does non-Gaussianity Matter?," Working Papers 2022:1, Örebro University, School of Business.
    21. Serena Ng, 2021. "Modeling Macroeconomic Variations after Covid-19," NBER Working Papers 29060, National Bureau of Economic Research, Inc.
    22. Clark, Todd & Huber, Florian & Koop, Gary & Marcellino, Massimiliano & Pfarrhofer, Michael, 2022. "Tail Forecasting with Multivariate Bayesian Additive Regression Trees," CEPR Discussion Papers 17461, C.E.P.R. Discussion Papers.
    23. Bańbura, Marta & Belousova, Irina & Bodnár, Katalin & Tóth, Máté Barnabás, 2023. "Nowcasting employment in the euro area," Working Paper Series 2815, European Central Bank.
    24. Danilo Cascaldi-Garcia, 2022. "Pandemic Priors," International Finance Discussion Papers 1352, Board of Governors of the Federal Reserve System (U.S.).
    25. Granados, Camilo & Parra-Amado, Daniel, 2024. "Estimating the output gap after COVID: How to address unprecedented macroeconomic variations," Economic Modelling, Elsevier, vol. 135(C).
    26. Morley, James & Palenzuela, Diego Rodriguez & Sun, Yiqiao & Wong, Benjamin, 2022. "Estimating the Euro Area output gap using multivariate information and addressing the COVID-19 pandemic," Working Paper Series 2716, European Central Bank.
    27. Barend Abeln & Jan P.A.M. Jacobs, 2021. "COVID19 and Seasonal Adjustment," CIRANO Working Papers 2021s-05, CIRANO.
    28. Alanya-Beltran, Willy, 2022. "Unit roots in lower-bounded series with outliers," Economic Modelling, Elsevier, vol. 115(C).
    29. Saeed Zaman, 2021. "A Unified Framework to Estimate Macroeconomic Stars," Working Papers 21-23R2, Federal Reserve Bank of Cleveland, revised 31 May 2024.
    30. 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.
    31. Nalban, Valeriu & Smădu, Andra, 2021. "Asymmetric effects of uncertainty shocks: Normal times and financial disruptions are different," Journal of Macroeconomics, Elsevier, vol. 69(C).
    32. Florian Huber, 2023. "Bayesian Nonlinear Regression using Sums of Simple Functions," Papers 2312.01881, arXiv.org.
    33. Vito Polito & Yunyi Zhang, 2021. "Tackling Large Outliers in Macroeconomic Data with Vector Artificial Neural Network Autoregression," CESifo Working Paper Series 9395, CESifo.
    34. Arabinda Basistha, "undated". "Estimates of Quarterly and Monthly Episodes of Global Recessions: Evidence from Markov-switching Dynamic Factor Models," Working Papers 24-07, Department of Economics, West Virginia University.
    35. Liu, Ying & Wen, Long & Liu, Han & Song, Haiyan, 2024. "Predicting tourism recovery from COVID-19: A time-varying perspective," Economic Modelling, Elsevier, vol. 135(C).
    36. 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).
    37. 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.
    38. Sun, Weihong & Liu, Ding, 2023. "Great moderation with Chinese characteristics: Uncovering the role of monetary policy," Economic Modelling, Elsevier, vol. 121(C).
    39. 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.
    40. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2021. "Forecasting with Shadow-Rate VARs," Working Papers 21-09, Federal Reserve Bank of Cleveland.
    41. 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.
    42. 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).
    43. Martin Iseringhausen & Konstantinos Theodoridis, 2025. "A survey-based measure of asymmetric macroeconomic risk in the euro area," Working Papers 68, European Stability Mechanism, revised 11 Feb 2025.
    44. Bańbura, Marta & Bobeica, Elena & Martínez Hernández, Catalina, 2023. "What drives core inflation? The role of supply shocks," Working Paper Series 2875, European Central Bank.
    45. Andrejs Zlobins, 2021. "On the Time-varying Effects of the ECB's Asset Purchases," Working Papers 2021/02, Latvijas Banka.
    46. Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Papers 2202.04146, arXiv.org, revised Oct 2024.
    47. Allayioti, Anastasia & Gόrnicka, Lucyna & Holton, Sarah & Martínez Hernández, Catalina, 2024. "Monetary policy pass-through to consumer prices: evidence from granular price data," Working Paper Series 3003, European Central Bank.
    48. Klieber, Karin, 2024. "Non-linear dimension reduction in factor-augmented vector autoregressions," Journal of Economic Dynamics and Control, Elsevier, vol. 159(C).

  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. David Kohns & Tibor Szendrei, 2021. "Decoupling Shrinkage and Selection for the Bayesian Quantile Regression," Papers 2107.08498, arXiv.org.
    4. 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.
    5. Pfarrhofer, Michael, 2022. "Modeling tail risks of inflation using unobserved component quantile regressions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    6. Laurent Ferrara & Matteo Mogliani & Jean-Guillaume Sahuc, 2020. "High-frequency monitoring of growth-at-risk," CAMA Working Papers 2020-97, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    7. Ana Beatriz Galvão & Michael Owyang, 2022. "Forecasting low‐frequency macroeconomic events with high‐frequency data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(7), pages 1314-1333, November.
    8. Frank Schorfheide & Dongho Song, 2024. "Real-Time Forecasting with a (Standard) Mixed-Frequency VAR During a Pandemic," International Journal of Central Banking, International Journal of Central Banking, vol. 20(4), pages 275-320, October.
    9. 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.
    10. 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.
    11. 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).
    12. Iseringhausen, Martin, 2024. "A time-varying skewness model for Growth-at-Risk," International Journal of Forecasting, Elsevier, vol. 40(1), pages 229-246.
    13. Korobilis, Dimitris & Landau, Bettina & Musso, Alberto & Phella, Anthoulla, 2021. "The time-varying evolution of inflation risks," Working Paper Series 2600, European Central Bank.
    14. 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.
    15. 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.
    16. Tibor Szendrei & Arnab Bhattacharjee & Mark E. Schaffer, 2024. "MIDAS-QR with 2-Dimensional Structure," Papers 2406.15157, arXiv.org.
    17. 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.
    18. 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.
    19. Botelho, Vasco & Foroni, Claudia & Renzetti, Andrea, 2024. "Labour at risk," European Economic Review, Elsevier, vol. 170(C).
    20. 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).
    21. 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.
    22. 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).
    23. Jack Fosten & Daniel Gutknecht & Marc-Oliver Pohle, 2023. "Testing Quantile Forecast Optimality," Papers 2302.02747, arXiv.org, revised Oct 2023.
    24. 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.
    25. Forni, Mario & Gambetti, Luca & Maffei-Faccioli, Nicolò & Sala, Luca, 2024. "The effects of monetary policy on macroeconomic risk," European Economic Review, Elsevier, vol. 167(C).
    26. 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.

  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. 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.
    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. Lodge, David & Pérez, Javier J. & Albrizio, Silvia & Everett, Mary & De Bandt, Olivier & Georgiadis, Georgios & Ca' Zorzi, Michele & Lastauskas, Povilas & Carluccio, Juan & Parraga Rodriguez, Susana &, 2021. "The implications of globalisation for the ECB monetary policy strategy," Occasional Paper Series 263, European Central Bank.
    7. 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.
    8. 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.
    9. Cubadda, Gianluca & Grassi, Stefano & Guardabascio, Barbara, 2025. "The time-varying Multivariate Autoregressive Index model," International Journal of Forecasting, Elsevier, vol. 41(1), pages 175-190.
    10. 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.
    11. Bonciani, Dario & Ricci, Martino, 2020. "The international effects of global financial uncertainty shocks," Journal of International Money and Finance, Elsevier, vol. 109(C).
    12. Dibiasi, Andreas & Sarferaz, Samad, 2023. "Measuring macroeconomic uncertainty: A cross-country analysis," European Economic Review, Elsevier, vol. 153(C).
    13. 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).
    14. 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.
    15. Miescu, Mirela S., 2023. "Uncertainty shocks in emerging economies: A global to local approach for identification," European Economic Review, Elsevier, vol. 154(C).
    16. Nina Biljanovska & Mr. Francesco Grigoli & Martina Hengge, 2017. "Fear Thy Neighbor: Spillovers from Economic Policy Uncertainty," IMF Working Papers 2017/240, International Monetary Fund.
    17. 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.
    18. 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).
    19. 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).
    20. 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.
    21. 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).
    22. Giovanni Caggiano & Efrem Castelnuovo, 2023. "Global financial uncertainty," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(3), pages 432-449, April.
    23. Gomez-Gonzalez, Jose E. & Hirs-Garzon, Jorge & Uribe, Jorge M., 2024. "US uncertainty shocks on real and financial markets: A multi-country perspective," Economic Systems, Elsevier, vol. 48(3).
    24. Graziano Moramarco, 2022. "Measuring Global Macroeconomic Uncertainty and Cross-Country Uncertainty Spillovers," Econometrics, MDPI, vol. 11(1), pages 1-29, December.
    25. Jaromir Baxa & Tomas Sestorad, 2024. "Economic Policy Uncertainty in Europe: Spillovers and Common Shocks," Working Papers IES 2024/34, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Sep 2024.
    26. Ductor, Lorenzo & Leiva-León, Danilo, 2022. "Fluctuations in global output volatility," Journal of International Money and Finance, Elsevier, vol. 120(C).
    27. Paul Labonne, 2020. "Asymmetric uncertainty : Nowcasting using skewness in real-time data," Papers 2012.02601, arXiv.org, revised May 2024.
    28. Wu, Ping, 2024. "Should I open to forecast? Implications from a multi-country unobserved components model with sparse factor stochastic volatility," International Journal of Forecasting, Elsevier, vol. 40(3), pages 903-917.

  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. Knüppel, Malte & Schultefrankenfeld, Guido, 2018. "Assessing the uncertainty in central banks' inflation outlooks," Discussion Papers 56/2018, Deutsche Bundesbank.
    7. Patrick A. Adams & Tobias Adrian & Nina Boyarchenko & Domenico Giannone, 2020. "Forecasting Macroeconomic Risks," Staff Reports 914, Federal Reserve Bank of New York.
    8. Schick, Manuel, 2024. "Real-time Nowcasting Growth-at-Risk using the Survey of Professional Forecasters," Working Papers 0750, University of Heidelberg, Department of Economics.
    9. 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).
    10. Yoosoon Chang & Yong-gun Kim & Boreum Kwak & Joon Y. Park, 2024. "Using Density Forecast for Growth-at-Risk to Improve Mean Forecast of GDP Growth in Korea," CAEPR Working Papers 2024-005 Classification-C, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    11. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2024. "Addressing COVID-19 Outliers in BVARs with Stochastic Volatility," The Review of Economics and Statistics, MIT Press, vol. 106(5), pages 1403-1417, September.
    12. 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.
    13. 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).
    14. 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.
    15. Knüppel, Malte, 2014. "Forecast-error-based estimation of forecast uncertainty when the horizon is increased," Discussion Papers 40/2014, Deutsche Bundesbank.
    16. Dibiasi, Andreas & Sarferaz, Samad, 2023. "Measuring macroeconomic uncertainty: A cross-country analysis," European Economic Review, Elsevier, vol. 153(C).
    17. Barbara Rossi, 2019. "Identifying and Estimating the Effects of Unconventional Monetary Policy in the Data: How to Do It and What Have We Learned?," Working Papers 1081, Barcelona School of Economics.
    18. Tamás Kiss & Stepan Mazur & Hoang Nguyen & Pär Österholm, 2023. "Modeling the relation between the US real economy and the corporate bond‐yield spread in Bayesian VARs with non‐Gaussian innovations," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 347-368, March.
    19. Fabian Kruger & Hendrik Plett, 2022. "Prediction intervals for economic fixed-event forecasts," Papers 2210.13562, arXiv.org, revised Mar 2024.
    20. Mirela Miescu, 2019. "Uncertainty shocks in emerging economies," Working Papers 277077821, Lancaster University Management School, Economics Department.
    21. 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.
    22. 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.
    23. 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.
    24. 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.
    25. Heinisch, Katja, 2024. "Step by step - A quarterly evaluation of EU Commission's GDP forecasts," IWH Discussion Papers 22/2024, Halle Institute for Economic Research (IWH).
    26. 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.

  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. 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.
    2. 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.
    3. 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.
    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. Karamysheva, Madina, 2022. "How do fiscal adjustments work? An empirical investigation," Journal of Economic Dynamics and Control, Elsevier, vol. 137(C).
    6. Joshua C. C. Chan, 2024. "BVARs and stochastic volatility," Chapters, in: Michael P. Clements & Ana Beatriz Galvão (ed.), Handbook of Research Methods and Applications in Macroeconomic Forecasting, chapter 3, pages 43-67, Edward Elgar Publishing.
    7. Hernández Vega Marco A., 2021. "The Nonlinear Effect of Uncertainty in Portfolio Flows to Mexico," Working Papers 2021-11, Banco de México.
    8. 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.
    9. Yoosoon Chang & Ana María Herrera & Elena Pesavento, 2023. "Oil prices uncertainty, endogenous regime switching, and inflation anchoring," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(6), pages 820-839, September.
    10. Popiel Michal Ksawery, 2020. "Fiscal policy uncertainty and US output," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(2), pages 1-26, April.
    11. Cross, Jamie L. & Hou, Chenghan & Koop, Gary & Poon, Aubrey, 2023. "Large stochastic volatility in mean VARs," Journal of Econometrics, Elsevier, vol. 236(1).
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    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. 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.
    3. Gary Koop & Dimitris Korobilis & Davide Pettenuzzo, 2016. "Bayesian Compressed Vector Autoregressions," Working Papers 103, Brandeis University, Department of Economics and International Business School.
    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. Harry Turunen & Anastasia Zhutova & Matthieu Lemoine, 2023. "Stochastic Simulation of the FR-BDF Model and an Assessment of Uncertainty around Conditional Forecasts," Working papers 920, Banque de France.
    6. Eric Eisenstat & Joshua C.C. Chan & Rodney W. Strachan, 2018. "Reducing Dimensions in a Large TVP-VAR," Working Paper Series 43, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
    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. 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.
    9. 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).
    10. 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.
    11. 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.
    12. Kohns, David & Potjagailo, Galina, 2023. "Flexible Bayesian MIDAS: time‑variation, group‑shrinkage and sparsity," Bank of England working papers 1025, Bank of England.

  18. 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. Gary Koop & Dimitris Korobilis & Davide Pettenuzzo, 2016. "Bayesian Compressed Vector Autoregressions," Working Papers 103, Brandeis University, Department of Economics and International Business School.
    3. 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.
    4. Feldkircher, Martin & Lukmanova, Elizaveta & Tondl, Gabriele, 2019. "Global Factors Driving Inflation and Monetary Policy: A Global VAR Assessment," Department of Economics Working Paper Series 289, WU Vienna University of Economics and Business.
    5. Joshua Chan & Arnaud Doucet & Roberto Leon-Gonzalez & Rodney W. Strachan, 2018. "Multivariate Stochastic Volatility with Co-Heteroscedasticity," GRIPS Discussion Papers 18-12, National Graduate Institute for Policy Studies.
    6. 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.
    7. Gregor Kastner & Florian Huber, 2020. "Sparse Bayesian vector autoregressions in huge dimensions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1142-1165, November.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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).

  19. 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. 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. Chris McDonald & Craig Thamotheram & Shaun P. Vahey & Elizabeth C. Wakerly, 2016. "Assessing the economic value of probabilistic forecasts in the presence of an inflation target," Reserve Bank of New Zealand Discussion Paper Series DP2016/10, Reserve Bank of New Zealand.
    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. 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.
    7. Todd E. Clark & Gergely Ganics & Elmar Mertens, 2024. "Constructing fan charts from the ragged edge of SPF forecasts," Working Papers 2429, Banco de España.
    8. 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.
    9. Milan Szabo, 2024. "Disciplining growth‐at‐risk models with survey of professional forecasters and Bayesian quantile regression," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 1975-1981, September.
    10. Galvão, Ana Beatriz & Garratt, Anthony & Mitchell, James, 2021. "Does judgment improve macroeconomic density forecasts?," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1247-1260.
    11. Knotek, Edward S. & Zaman, Saeed, 2023. "Real-time density nowcasts of US inflation: A model combination approach," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1736-1760.
    12. Bjarni G. Einarsson, 2024. "Online Monitoring of Policy Optimality," Economics wp95, Department of Economics, Central bank of Iceland.
    13. Richard Schnorrenberger & Aishameriane Schmidt & Guilherme Valle Moura, 2024. "Harnessing Machine Learning for Real-Time Inflation Nowcasting," Working Papers 806, DNB.
    14. 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.
    15. Baumeister, Christiane, 2021. "Measuring Market Expectations," CEPR Discussion Papers 16520, C.E.P.R. Discussion Papers.
    16. Markus Heinrich & Magnus Reif, 2020. "Real-Time Forecasting Using Mixed-Frequency VARS with Time-Varying Parameters," CESifo Working Paper Series 8054, CESifo.
    17. 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).
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. Knüppel, Malte & Krüger, Fabian, 2019. "Forecast uncertainty, disagreement, and the linear pool," Discussion Papers 28/2019, Deutsche Bundesbank.
    23. Zhiyuan Pan & Jun Zhang & Yudong Wang & Juan Huang, 2024. "Modeling and forecasting stock return volatility using the HARGARCH model with VIX information," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(8), pages 1383-1403, August.
    24. 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.
    25. 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.
    26. 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.
    27. 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.
    28. 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.
    29. Nadiia Shapovalenko, 2021. "A BVAR Model for Forecasting Ukrainian Inflation," IHEID Working Papers 05-2021, Economics Section, The Graduate Institute of International Studies.
    30. Montes-Galdón, Carlos & Paredes, Joan & Wolf, Elias, 2022. "Conditional density forecasting: a tempered importance sampling approach," Working Paper Series 2754, European Central Bank.
    31. 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.
    32. 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.
    33. Philip Hans Franses, 2024. "Incorporating judgment in forecasting models in times of crisis," Futures & Foresight Science, John Wiley & Sons, vol. 6(4), December.
    34. 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.
    35. 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.

  20. 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. Geraldine Dany-Knedlik & Juan Angel Garcia, 2018. "Monetary Policy and Inflation Dynamics in ASEAN Economies," IMF Working Papers 2018/147, International Monetary Fund.
    3. 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.
    4. Juan Angel Garcia & Sebastian Werner, 2018. "Inflation News and Euro Area Inflation Expectations," IMF Working Papers 2018/167, International Monetary Fund.
    5. 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.
    6. 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.
    7. Pfarrhofer, Michael, 2022. "Modeling tail risks of inflation using unobserved component quantile regressions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    8. 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.
    9. Martins, Manuel Mota Freitas & Verona, Fabio, 2021. "Inflation dynamics and forecast: Frequency matters," Bank of Finland Research Discussion Papers 8/2021, Bank of Finland.
    10. Florian Huber & Daniel Kaufmann, 2015. "Trend Fundamentals and Exchange Rate Dynamics," KOF Working papers 15-393, KOF Swiss Economic Institute, ETH Zurich.
    11. Diegel, Max, 2022. "Time-varying credibility, anchoring and the Fed's inflation target," Discussion Papers 2022/9, Free University Berlin, School of Business & Economics.
    12. Francesca Rondina, 2018. "Estimating unobservable inflation expectations in the New Keynesian Phillips Curve," Working Papers 1804E, University of Ottawa, Department of Economics.
    13. 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.
    14. 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.
    15. 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.
    16. Elizaveta Lukmanova & Katrin Rabitsch, 2018. "New VAR evidence on monetary transmission channels: temporary interest rate versus inflation target shocks," Working Papers of Department of Economics, Leuven 630040, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
    17. Juan Angel Garcia & Aubrey Poon, 2018. "Trend Inflation and Inflation Compensation," IMF Working Papers 2018/154, International Monetary Fund.
    18. García, Juan Angel & Poon, Aubrey, 2019. "Inflation trends in Asia: implications for central banks," Working Paper Series 2338, European Central Bank.
    19. 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.
    20. 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.
    21. Chen, Ji & Yang, Xinglin & Liu, Xiliang, 2022. "Learning, disagreement and inflation forecasting," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    22. 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.
    23. Christina Anderl & Guglielmo Maria Caporale, 2023. "Forecasting inflation with a zero lower bound or negative interest rates: Evidence from point and density forecasts," Manchester School, University of Manchester, vol. 91(3), pages 171-232, June.
    24. Marcelo Arbex & Sidney Caetano & Wilson Correa, 2018. "Macroeconomic Effects of Inflation Target Uncertainty Shocks," Working Papers 1804, University of Windsor, Department of Economics.
    25. Jmaes McNeil, 2020. "Monetary policy and the term structure of Inflation expectations with information frictions," Working Papers daleconwp2020-07, Dalhousie University, Department of Economics.
    26. Kamber, Güneş & Wong, Benjamin, 2020. "Global factors and trend inflation," Journal of International Economics, Elsevier, vol. 122(C).
    27. 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.
    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. Hauzenberger, Niko & Huber, Florian & Klieber, Karin, 2023. "Real-time inflation forecasting using non-linear dimension reduction techniques," International Journal of Forecasting, Elsevier, vol. 39(2), pages 901-921.
    30. Semmler, Willi & Gross, Marco, 2017. "Mind the output gap: the disconnect of growth and inflation during recessions and convex Phillips curves in the euro area," Working Paper Series 2004, European Central Bank.
    31. 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.
    32. Saeed Zaman, 2021. "A Unified Framework to Estimate Macroeconomic Stars," Working Papers 21-23R2, Federal Reserve Bank of Cleveland, revised 31 May 2024.
    33. 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.
    34. Richard K. Crump & Stefano Eusepi & Emanuel Moench & Bruce Preston, 2021. "The Term Structure of Expectations," Staff Reports 992, Federal Reserve Bank of New York.
    35. Hauber, Philipp & Schumacher, Christian, 2021. "Precision-based sampling with missing observations: A factor model application," Discussion Papers 11/2021, Deutsche Bundesbank.
    36. Andriantomanga, Zo, 2023. "The role of survey-based expectations in real-time forecasting of US inflation," MPRA Paper 119904, University Library of Munich, Germany.
    37. Lenza, Michele & Jarociński, Marek, 2016. "An inflation-predicting measure of the output gap in the euro area," Working Paper Series 1966, European Central Bank.
    38. 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.
    39. Bańbura, Marta & Bobeica, Elena, 2020. "PCCI – a data-rich measure of underlying inflation in the euro area," Statistics Paper Series 38, European Central Bank.
    40. 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.
    41. Beechey, Meredith & Österholm, Pär & Poon, Aubrey, 2023. "Estimating the US trend short-term interest rate," Finance Research Letters, Elsevier, vol. 55(PA).
    42. 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.
    43. Jaromir Baxa & Miroslav Plasil & Borek Vasicek, 2013. "Inflation and the Steeplechase Between Economic Activity Variables," Working Papers 2013/15, Czech National Bank.
    44. 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.
    45. 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.
    46. 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.
    47. 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.
    48. Kristin Forbes, 2019. "Has globalization changed the inflation process?," BIS Working Papers 791, Bank for International Settlements.
    49. 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.
    50. Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Papers 2202.04146, arXiv.org, revised Oct 2024.
    51. Koester, Gerrit & Lis, Eliza & Nickel, Christiane & Osbat, Chiara & Smets, Frank, 2021. "Understanding low inflation in the euro area from 2013 to 2019: cyclical and structural drivers," Occasional Paper Series 280, European Central Bank.
    52. Helder Ferreira de Mendonça & Pedro Mendes Garcia & José Valentim Machado Vicente, 2021. "Rationality and anchoring of inflation expectations: An assessment from survey‐based and market‐based measures," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(6), pages 1027-1053, September.
    53. 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.
    54. James Mitchell & Saeed Zaman, 2023. "The Distributional Predictive Content of Measures of Inflation Expectations," Working Papers 23-31, Federal Reserve Bank of Cleveland.
    55. Lukmanova, Elizaveta & Rabitsch, Katrin, 2023. "Evidence on monetary transmission and the role of imperfect information: Interest rate versus inflation target shocks," European Economic Review, Elsevier, vol. 158(C).

  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.

    Cited by:

    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. Petkov, Ivan, 2023. "Small business lending and the bank-branch network," Journal of Financial Stability, Elsevier, vol. 64(C).
    6. Avril Pauline & Levieuge Gr gory & Turcu Camelia, 2022. "Natural Disasters and Financial Stress: Can Macroprudential Regulation Tame Green Swans?," Working papers 874, Banque de France.
    7. Barbaglia, Luca & Fatica, Serena & Rho, Caterina, 2023. "Flooded credit markets: physical climate risk and small business lending," JRC Working Papers in Economics and Finance 2023-14, Joint Research Centre, European Commission.
    8. Chakraborty, Indraneel & Goldstein, Itay & MacKinlay, Andrew, 2020. "Monetary stimulus and bank lending," Journal of Financial Economics, Elsevier, vol. 136(1), pages 189-218.
    9. 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.
    10. Franziska Bremus & Malte Rieth, 2023. "Integrating Out Natural Disaster Shocks," Discussion Papers of DIW Berlin 2063, DIW Berlin, German Institute for Economic Research.
    11. 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.
    12. 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.
    13. Tho Pham & Oleksandr Talavera & Andriy Tsapin, 2018. "Shock Contagion, Asset Quality and Lending Behavior," Working Papers 01/2018, National Bank of Ukraine.
    14. Sandra Aguilar-Gomez & Emilio Gutierrez & David Heres & David Jaume & Martin Tobal, 2022. "Thermal Stress and Financial Distress: Extreme Temperatures and Firms’ Loan Defaults in Mexico," Working Papers 148, Red Nacional de Investigadores en Economía (RedNIE).
    15. 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.
    16. Shi, Yining, 2022. "Financial liberalization and house prices: Evidence from China," Journal of Banking & Finance, Elsevier, vol. 145(C).
    17. Ross Levine & Chen Lin & Wensi Xie, 2021. "Geographic Diversification and Banks’ Funding Costs," Management Science, INFORMS, vol. 67(5), pages 2657-2678, May.
    18. 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.
    19. 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.
    20. 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).
    21. 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).
    22. Wu, Baohui & Wen, Fenghua & Zhang, Yun & Huang, Zhijian (James), 2024. "Climate risk and the systemic risk of banks: A global perspective," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 95(C).
    23. 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.
    24. Victor Aguirregabiria & Robert Clark & Hui Wang, 2024. "The geographic flow of bank funding and access to credit: Branch networks, local synergies and competition," Papers 2407.03517, arXiv.org.
    25. Salih Fendoğlu & Eda Gülşen & José-Luis Peydró, 2019. "Global Liquidity and Impairment of Local Monetary Policy," Working Papers 1131, Barcelona School of Economics.
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  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, revised Nov 2024.
    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. 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.
    2. Mehmet Pasaogullari, 2015. "Forecasts from Reduced-form Models under the Zero-Lower-Bound Constraint," Working Papers (Old Series) 1512, Federal Reserve Bank of Cleveland.
    3. 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.
    4. 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.
    5. 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.).
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. Sokol, Andrej, 2021. "Fan charts 2.0: flexible forecast distributions with expert judgement," Working Paper Series 2624, European Central Bank.

  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. Pfarrhofer, Michael, 2022. "Modeling tail risks of inflation using unobserved component quantile regressions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    7. 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.
    8. Niko Hauzenberger, 2020. "Flexible Mixture Priors for Large Time-varying Parameter Models," Papers 2006.10088, arXiv.org, revised Nov 2020.
    9. Rachidi Kotchoni & Dalibor Stevanovic, 2016. "Forecasting U.S. Recessions and Economic Activity," Working Papers hal-04141569, HAL.
    10. Jarociński, Marek & Bobeica, Elena, 2017. "Missing disinflation and missing inflation: the puzzles that aren't," Working Paper Series 2000, European Central Bank.
    11. Sune Karlsson & Pär Österholm, 2020. "A note on the stability of the Swedish Phillips curve," Empirical Economics, Springer, vol. 59(6), pages 2573-2612, December.
    12. 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.
    13. Todd E. Clark & Michael W. McCracken, 2014. "Evaluating Conditional Forecasts from Vector Autoregressions," Working Papers 2014-25, Federal Reserve Bank of St. Louis.
    14. George Kapetanios & Massimiliano Marcellino & Fabrizio Venditti, 2019. "Large time‐varying parameter VARs: A nonparametric approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(7), pages 1027-1049, November.
    15. 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).
    16. Conti, Antonio M. & Nobili, Andrea & Signoretti, Federico M., 2023. "Bank capital requirement shocks: A narrative perspective," European Economic Review, Elsevier, vol. 151(C).
    17. Bjarni G. Einarsson, 2024. "Online Monitoring of Policy Optimality," Economics wp95, Department of Economics, Central bank of Iceland.
    18. 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.
    19. Conti, Antonio M., 2021. "Resurrecting the Phillips Curve in Low-Inflation Times," Economic Modelling, Elsevier, vol. 96(C), pages 172-195.
    20. Legrand, Romain, 2018. "Time-Varying Vector Autoregressions: Efficient Estimation, Random Inertia and Random Mean," MPRA Paper 88925, University Library of Munich, Germany.
    21. 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.
    22. Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
    23. Pierre Guérin & Danilo Leiva-Leon & Massimiliano Marcellino, 2017. "Markov-Switching Three-Pass Regression Filter," Staff Working Papers 17-13, Bank of Canada.
    24. 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.
    25. Markus Heinrich & Magnus Reif, 2020. "Real-Time Forecasting Using Mixed-Frequency VARS with Time-Varying Parameters," CESifo Working Paper Series 8054, CESifo.
    26. 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.
    27. Hacioglu Hoke, Sinem, 2019. "Macroeconomic effects of political risk shocks," Bank of England working papers 841, Bank of England.
    28. Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2019. "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Working Paper 2019/2, Norges Bank.
    29. Orkideh Gharehgozli & Sunhyung Lee, 2022. "Money Supply and Inflation after COVID-19," Economies, MDPI, vol. 10(5), pages 1-14, April.
    30. 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.
    31. 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.
    32. 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.
    33. 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.
    34. Antonio Maria Conti & Stefano Neri & Alessandro Notarpietro, 2024. "Credit strikes back: the macroeconomic impact of the 2022-23 ECB monetary tightening and the role of lending rates," Questioni di Economia e Finanza (Occasional Papers) 884, Bank of Italy, Economic Research and International Relations Area.
    35. 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.
    36. 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.
    37. 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.).

  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. 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.
    6. 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.
    7. 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.
    8. 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.
    9. Reichlin, Lucrezia & Giannone, Domenico & Modugno, Michele & Banbura, Marta, 2012. "Now-casting and the real-time data flow," CEPR Discussion Papers 9112, C.E.P.R. Discussion Papers.
    10. 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.
    11. Matteo Mogliani & Anna Simoni, 2020. "Bayesian MIDAS penalized regressions: Estimation, selection, and prediction," Post-Print hal-03089878, HAL.
    12. 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.
    13. 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.
    14. 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.
    15. Ana Beatriz Galvão & Michael Owyang, 2022. "Forecasting low‐frequency macroeconomic events with high‐frequency data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(7), pages 1314-1333, November.
    16. 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.
    17. Martin Feldkircher & Florian Huber & Michael Pfarrhofer, 2020. "Measuring the Effectiveness of US Monetary Policy during the COVID-19 Recession," Papers 2007.15419, arXiv.org.
    18. 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.
    19. 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.
    20. 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.
    21. Foroni, Claudia & Ravazzolo, Francesco & Rossini, Luca, 2019. "Forecasting daily electricity prices with monthly macroeconomic variables," Working Paper Series 2250, European Central Bank.
    22. 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).
    23. 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, March.
    24. 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).
    25. Robert M. Kunst & Martin Wagner, 2020. "Economic forecasting: editors’ introduction," Empirical Economics, Springer, vol. 58(1), pages 1-5, January.
    26. 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.
    27. 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.
    28. Knotek, Edward S. & Zaman, Saeed, 2023. "Real-time density nowcasts of US inflation: A model combination approach," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1736-1760.
    29. Knut Are Aastveit & Francesco Ravazzolo & Herman K. van Dijk, 2014. "Combined Density Nowcasting in an uncertain economic environment," Working Paper 2014/17, Norges Bank.
    30. Claudia Foroni & Francesco Ravazzolo & Luca Rossini, 2020. "Are low frequency macroeconomic variables important for high frequency electricity prices?," Papers 2007.13566, arXiv.org, revised Dec 2022.
    31. Clark, Todd & Huber, Florian & Koop, Gary & Marcellino, Massimiliano & Pfarrhofer, Michael, 2022. "Tail Forecasting with Multivariate Bayesian Additive Regression Trees," CEPR Discussion Papers 17461, C.E.P.R. Discussion Papers.
    32. Richard Schnorrenberger & Aishameriane Schmidt & Guilherme Valle Moura, 2024. "Harnessing Machine Learning for Real-Time Inflation Nowcasting," Working Papers 806, DNB.
    33. 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.
    34. Boriss Siliverstovs, 2019. "Assessing Nowcast Accuracy of US GDP Growth in Real Time: The Role of Booms and Busts," Working Papers 2019/01, Latvijas Banka.
    35. Berg, Tim Oliver & Henzel, Steffen, 2013. "Point and Density Forecasts for the Euro Area Using Many Predictors: Are Large BVARs Really Superior?," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79783, Verein für Socialpolitik / German Economic Association.
    36. 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.
    37. Knut Are Aastveit & Claudia Foroni & Francesco Ravazzolo, 2014. "Density forecasts with MIDAS models," Working Paper 2014/10, Norges Bank.
    38. Marek Rusnak, 2013. "Nowcasting Czech GDP in Real Time," Working Papers 2013/06, Czech National Bank.
    39. Markus Heinrich & Magnus Reif, 2020. "Real-Time Forecasting Using Mixed-Frequency VARS with Time-Varying Parameters," CESifo Working Paper Series 8054, CESifo.
    40. Frédérique Bec & Matteo Mogliani, 2013. "Nowcasting French GDP in Real-Time from Survey Opinions : Information or Forecast Combinations ?," Working Papers 2013-21, Center for Research in Economics and Statistics.
    41. Tamás Kiss & Stepan Mazur & Hoang Nguyen & Pär Österholm, 2023. "Modeling the relation between the US real economy and the corporate bond‐yield spread in Bayesian VARs with non‐Gaussian innovations," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 347-368, March.
    42. Edward S. Knotek & Saeed Zaman, 2017. "Nowcasting U.S. Headline and Core Inflation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(5), pages 931-968, August.
    43. 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.
    44. Matteo Mogliani & Anna Simoni, 2024. "Bayesian Bi-level Sparse Group Regressions for Macroeconomic Density Forecasting," Papers 2404.02671, arXiv.org, revised Nov 2024.
    45. 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.
    46. 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.
    47. 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.
    48. Knut Are Aastveit & Tuva Marie Fastbø & Eleonora Granziera & Kenneth Sæterhagen Paulsen & Kjersti Næss Torstensen, 2024. "Nowcasting Norwegian household consumption with debit card transaction data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(7), pages 1220-1244, November.
    49. 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.
    50. 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.
    51. 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.
    52. 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.
    53. 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.
    54. Liu, Yang & Swanson, Norman R., 2024. "An assessment of the marginal predictive content of economic uncertainty indexes and business conditions predictors," International Journal of Forecasting, Elsevier, vol. 40(4), pages 1391-1409.
    55. Marcellino, Massimiliano & Foroni, Claudia, 2014. "Markov-Switching Mixed-Frequency VAR Models," CEPR Discussion Papers 9815, C.E.P.R. Discussion Papers.
    56. 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.
    57. Sebastian Ankargren & Paulina Jon'eus, 2019. "Estimating Large Mixed-Frequency Bayesian VAR Models," Papers 1912.02231, arXiv.org.
    58. Lucas P. Harlaar & Jacques J.F. Commandeur & Jan A. van den Brakel & Siem Jan Koopman & Niels Bos & Frits D. Bijleveld, 2024. "Statistical Early Warning Models with Applications," Tinbergen Institute Discussion Papers 24-037/III, Tinbergen Institute.
    59. 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.
    60. 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.
    61. 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.
    62. Tim Oliver Berg & Steffen Henzel, 2014. "Point and Density Forecasts for the Euro Area Using Bayesian VARs," CESifo Working Paper Series 4711, CESifo.
    63. Kohns, David & Potjagailo, Galina, 2023. "Flexible Bayesian MIDAS: time‑variation, group‑shrinkage and sparsity," Bank of England working papers 1025, Bank of England.
    64. 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.
    65. 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. 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.
    3. Pincheira, Pablo & Selaive, Jorge & Nolazco, Jose Luis, 2017. "Forecasting Inflation in Latin America with Core Measures," MPRA Paper 80496, University Library of Munich, Germany.
    4. Coble, David & Pincheira, Pablo, 2017. "Nowcasting Building Permits with Google Trends," MPRA Paper 76514, University Library of Munich, Germany.
    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. Mumtaz, Haroon & Theodoridis, Konstantinos, 2017. "Common and country specific economic uncertainty," Journal of International Economics, Elsevier, vol. 105(C), pages 205-216.
    2. Huber, Florian, 2016. "Density forecasting using Bayesian global vector autoregressions with stochastic volatility," International Journal of Forecasting, Elsevier, vol. 32(3), pages 818-837.
    3. 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.
    4. 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.
    5. Joshua C. C. Chan & Xuewen Yu, 2022. "Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility," Papers 2206.08438, arXiv.org.
    6. 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.
    7. 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.
    8. 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.
    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. 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.
    11. 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.
    12. 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.
    13. 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.
    14. Kyle Jurado & Sydney C. Ludvigson & Serena Ng, 2015. "Measuring Uncertainty," American Economic Review, American Economic Association, vol. 105(3), pages 1177-1216, March.
    15. Cross, Jamie L. & Hou, Chenghan & Koop, Gary & Poon, Aubrey, 2023. "Large stochastic volatility in mean VARs," Journal of Econometrics, Elsevier, vol. 236(1).
    16. 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.
    17. Piergiorgio Alessandri & Haroon Mumtaz, 2014. "Financial regimes and uncertainty shocks," BCAM Working Papers 1404, Birkbeck Centre for Applied Macroeconomics.
    18. Tsionas, Mike G. & Izzeldin, Marwan & Trapani, Lorenzo, 2022. "Estimation of large dimensional time varying VARs using copulas," European Economic Review, Elsevier, vol. 141(C).
    19. 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.
    20. Chiu, Ching-Wai (Jeremy) & Mumtaz, Haroon & Pinter, Gabor, 2016. "VAR models with non-Gaussian shocks," LSE Research Online Documents on Economics 86238, London School of Economics and Political Science, LSE Library.
    21. Simon Beyeler, 2019. "Streamlining Time-varying VAR with a Factor Structure in the Parameters," Working Papers 19.03, Swiss National Bank, Study Center Gerzensee.
    22. 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.
    23. Gary Koop & Dimitris Korobilis & Davide Pettenuzzo, 2016. "Bayesian Compressed Vector Autoregressions," Working Papers 103, Brandeis University, Department of Economics and International Business School.
    24. Gary Koop & Dimitris Korobilis, 2012. "Large Time-Varying Parameter VARs," Working Paper series 11_12, Rimini Centre for Economic Analysis.
    25. 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.
    26. 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.
    27. 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.
    28. Kelly Trinh & Bo Zhang & Chenghan Hou, 2025. "Macroeconomic real‐time forecasts of univariate models with flexible error structures," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(1), pages 59-78, January.
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  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. 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.
    2. 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".
    3. Davide Delle Monache & Ivan Petrella, 2014. "Adaptive Models and Heavy Tails," Working Papers 720, Queen Mary University of London, School of Economics and Finance.
    4. 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.
    5. 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.
    6. 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.
    7. Hilde C. Bjørnland & Francesco Ravazzolo & Leif Anders Thorsrud, 2015. "Forecasting GDP with global components. This time is different," Working Papers No 1/2015, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    8. Knut Are Aastveit & Claudia Foroni & Francesco Ravazzolo, 2014. "Density forecasts with MIDAS models," Working Paper 2014/10, Norges Bank.
    9. 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.
    10. 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.
    11. 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.).
    12. Pami Dua, 2023. "Macroeconomic Modelling and Bayesian Methods," Springer Books, in: Pami Dua (ed.), Macroeconometric Methods, chapter 0, pages 19-37, Springer.
    13. 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.

  29. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2011. "Bayesian VARs: Specification Choices and Forecast Accuracy," CEPR Discussion Papers 8273, C.E.P.R. Discussion Papers.

    Cited by:

    1. Koop, Gary & Korobilis, Dimitris, 2016. "Model uncertainty in Panel Vector Autoregressive models," European Economic Review, Elsevier, vol. 81(C), pages 115-131.
    2. Hashmat Khan & Santosh Upadhayaya, 2017. "Does Business Confidence Matter for Investment?," Carleton Economic Papers 17-13, Carleton University, Department of Economics, revised 20 Mar 2019.
    3. 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.
    4. Oriol Gonzalez-Casasus & Frank Schorfheide, 2025. "Misspecification-Robust Shrinkage and Selection for VAR Forecasts and IRFs," PIER Working Paper Archive 25-003, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    5. Joshua C. C. Chan & Xuewen Yu, 2022. "Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility," Papers 2206.08438, arXiv.org.
    6. 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.
    7. Salzmann, Leonard, 2020. "The Impact of Uncertainty and Financial Shocks in Recessions and Booms," VfS Annual Conference 2020 (Virtual Conference): Gender Economics 224588, Verein für Socialpolitik / German Economic Association.
    8. Anna Staszewska-Bystrova & Peter Winker, 2014. "Measuring Forecast Uncertainty of Corporate Bond Spreads by Bonferroni-Type Prediction Bands," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 6(2), pages 89-104, June.
    9. Joshua C. C. Chan, 2024. "BVARs and stochastic volatility," Chapters, in: Michael P. Clements & Ana Beatriz Galvão (ed.), Handbook of Research Methods and Applications in Macroeconomic Forecasting, chapter 3, pages 43-67, Edward Elgar Publishing.
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    11. Karlsson, Sune, 2012. "Forecasting with Bayesian Vector Autoregressions," Working Papers 2012:12, Örebro University, School of Business.
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    1. 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.
    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.
    3. 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.
    4. 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).
    5. T. S. McElroy, 2016. "Nonnested model comparisons for time series," Biometrika, Biometrika Trust, vol. 103(4), pages 905-914.
    6. Isao Ishida & Virmantas Kvedaras, 2015. "Modeling Autoregressive Processes with Moving-Quantiles-Implied Nonlinearity," Econometrics, MDPI, vol. 3(1), pages 1-53, January.
    7. Corradi, Valentina & Fosten, Jack & Gutknecht, Daniel, 2024. "Predictive ability tests with possibly overlapping models," Journal of Econometrics, Elsevier, vol. 241(1).
    8. 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.
    9. Arbués, Ignacio & Matilla-García, Mariano, 2024. "Multibenchmark reality checks," Economic Modelling, Elsevier, vol. 140(C).

  31. 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. Jesus Crespo Cuaresma & Ines Fortin & Jaroslava Hlouskova & Michael Obersteiner, 2024. "Regime‐dependent commodity price dynamics: A predictive analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(7), pages 2822-2847, November.
    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. Pablo Pincheira Brown & Nicolás Hardy, 2024. "Correlation‐based tests of predictability," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 1835-1858, September.
    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. 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.
    12. 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.
    13. 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.
    14. 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.
    15. Michael D. Bauer & Glenn D. Rudebusch, 2017. "Interest Rates Under Falling Stars," CESifo Working Paper Series 6571, CESifo.
    16. 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.
    17. Chuliá, Helena & Garrón, Ignacio & Uribe, Jorge M., 2024. "Daily growth at risk: Financial or real drivers? The answer is not always the same," International Journal of Forecasting, Elsevier, vol. 40(2), pages 762-776.
    18. 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.
    19. 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.
    20. 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.
    21. Francesco Ravazzolo & Philip Rothman, 2013. "Oil and U.S. GDP: A Real-Time Out-of-Sample Examination," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 45(2-3), pages 449-463, 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. Michael Dotsey & Shigeru Fujita & Tom Stark, 2011. "Do Phillips curves conditionally help to forecast inflation?," Working Papers 11-40, Federal Reserve Bank of Philadelphia.
    24. 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.
    25. 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.
    26. 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.
    27. Yin, Anwen, 2020. "Equity premium prediction and optimal portfolio decision with Bagging," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    28. 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.
    29. 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).
    30. 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.
    31. Dimitris Korobilis & Davide Pettenuzzo, 2017. "Adaptive Hierarchical Priors for High-Dimensional Vector Autoregessions," Working Papers 115, Brandeis University, Department of Economics and International Business School.
    32. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • 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.
    33. Zhu, Yinchu & Timmermann, Allan, 2022. "Conditional rotation between forecasting models," Journal of Econometrics, Elsevier, vol. 231(2), pages 329-347.
    34. 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.
    35. Jan J.J. Groen & George Kapetanios, 2008. "Revisiting Useful Approaches to Data-Rich Macroeconomic Forecasting," Working Papers 624, Queen Mary University of London, School of Economics and Finance.
    36. Michael W. McCracken, 2019. "Diverging Tests of Equal Predictive Ability," Working Papers 2019-018, Federal Reserve Bank of St. Louis, revised 09 Mar 2020.
    37. Antolin-Diaz, Juan & Drechsel, Thomas & Petrella, Ivan, 2023. "Advances in Nowcasting Economic Activity: The Role of Heterogeneous Dynamics and Fat Tails," CEPR Discussion Papers 17800, C.E.P.R. Discussion Papers.
    38. Brent Meyer & Guhan Venkatu, 2012. "Trimmed-mean inflation statistics: just hit the one in the middle," Working Papers (Old Series) 1217, Federal Reserve Bank of Cleveland.
    39. Peter Reinhard HANSEN & Allan TIMMERMANN, 2012. "Choice of Sample Split in Out-of-Sample Forecast Evaluation," Economics Working Papers ECO2012/10, European University Institute.
    40. Zeyyad Mandalinci, 2015. "Forecasting Inflation in Emerging Markets: An Evaluation of Alternative Models," CReMFi Discussion Papers 3, CReMFi, School of Economics and Finance, QMUL.
    41. 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.
    42. 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.
    43. 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.
    44. Hinterlang, Natascha, 2020. "Predicting monetary policy using artificial neural networks," Discussion Papers 44/2020, Deutsche Bundesbank.
    45. 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).
    46. 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.
    47. 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.
    48. Brent Meyer & Saeed Zaman, 2016. "The Usefulness of the Median CPI in Bayesian VARs Used for Macroeconomic Forecasting and Policy," FRB Atlanta Working Paper 2016-13, Federal Reserve Bank of Atlanta.
    49. Federico D'Amario & Milos Ciganovic, 2022. "Forecasting Cryptocurrencies Log-Returns: a LASSO-VAR and Sentiment Approach," Papers 2210.00883, arXiv.org.
    50. Jin, Sainan & Corradi, Valentina & Swanson, Norman R., 2017. "Robust Forecast Comparison," Econometric Theory, Cambridge University Press, vol. 33(6), pages 1306-1351, December.
    51. Christopher G. Gibbs & Andrey L. Vasnev, 2017. "Conditionally Optimal Weights and Forward-Looking Approaches to Combining Forecasts," Discussion Papers 2017-10, School of Economics, The University of New South Wales.
    52. Håvard Hungnes, 2020. "Equal predictability test for multi-step-ahead system forecasts invariant to linear transformations," Discussion Papers 931, Statistics Norway, Research Department.
    53. Laura Coroneo & Fabrizio Iacone, 2015. "Comparing predictive accuracy in small samples," Discussion Papers 15/15, Department of Economics, University of York.
    54. Hanif, Muhammad Nadim & Malik, Muhammad Jahanzeb, 2015. "Evaluating Performance of Inflation Forecasting Models of Pakistan," MPRA Paper 66843, University Library of Munich, Germany.
    55. 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.
    56. Kiss, Tamás & Nguyen, Hoang & Österholm, Pär, 2020. "Modelling Returns in US Housing Prices – You’re the One for Me, Fat Tails," Working Papers 2020:13, Örebro University, School of Business.
    57. 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.
    58. 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.
    59. 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.
    60. Sekkel, Rodrigo M., 2015. "Balance sheets of financial intermediaries: Do they forecast economic activity?," International Journal of Forecasting, Elsevier, vol. 31(2), pages 263-275.
    61. Daniel Borup & Jonas N. Eriksen & Mads M. Kjær & Martin Thyrsgaard, 2024. "Predicting Bond Return Predictability," Management Science, INFORMS, vol. 70(2), pages 931-951, February.
    62. McKnight, Stephen & Mihailov, Alexander & Rumler, Fabio, 2020. "Inflation forecasting using the New Keynesian Phillips Curve with a time-varying trend," Economic Modelling, Elsevier, vol. 87(C), pages 383-393.
    63. Busetti, Fabio & Marcucci, Juri, 2013. "Comparing forecast accuracy: A Monte Carlo investigation," International Journal of Forecasting, Elsevier, vol. 29(1), pages 13-27.
    64. Johanna F. Ziegel & Fabian Kruger & Alexander Jordan & Fernando Fasciati, 2017. "Murphy Diagrams: Forecast Evaluation of Expected Shortfall," Papers 1705.04537, arXiv.org.
    65. Jean-Yves Pitarakis, 2020. "A Novel Approach to Predictive Accuracy Testing in Nested Environments," Papers 2008.08387, arXiv.org, revised Oct 2023.
    66. 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.
    67. 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.
    68. Ahmed, Shamim & Tsvetanov, Daniel, 2016. "The predictive performance of commodity futures risk factors," Journal of Banking & Finance, Elsevier, vol. 71(C), pages 20-36.
    69. 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.
    70. 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.
    71. 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.
    72. Gregory R. Duffee, 2012. "Forecasting interest rates," Economics Working Paper Archive 599, The Johns Hopkins University,Department of Economics.
    73. 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.
    74. 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.
    75. Jonathan H. Wright, 2015. "Comment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(1), pages 12-13, January.
    76. 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.
    77. 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.
    78. 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.
    79. Kurmaş Akdoğan, 2019. "Size and sign asymmetries in house price adjustments," Applied Economics, Taylor & Francis Journals, vol. 51(48), pages 5268-5281, October.
    80. 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.
    81. 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.
    82. 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).
    83. Timmermann, Allan & Zhu, Yinchu, 2021. "Conditional Rotation Between Forecasting Models," CEPR Discussion Papers 15917, C.E.P.R. Discussion Papers.
    84. 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.
    85. Krüger, Fabian & Nolte, Ingmar, 2016. "Disagreement versus uncertainty: Evidence from distribution forecasts," Journal of Banking & Finance, Elsevier, vol. 72(S), pages 172-186.
    86. 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.
    87. 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).
    88. 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.
    89. Guizzardi, Andrea & Stacchini, Annalisa, 2015. "Real-time forecasting regional tourism with business sentiment surveys," Tourism Management, Elsevier, vol. 47(C), pages 213-223.
    90. 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.
    91. 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.
    92. Yin, Anwen, 2019. "Out-of-sample equity premium prediction in the presence of structural breaks," International Review of Financial Analysis, Elsevier, vol. 65(C).
    93. 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.
    94. 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.
    95. Michael W. McCracken, 2020. "Tests of Conditional Predictive Ability: Existence, Size, and Power," Working Papers 2020-050, Federal Reserve Bank of St. Louis.
    96. 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.
    97. 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).
    98. Boot, Tom & Pick, Andreas, 2020. "Does modeling a structural break improve forecast accuracy?," Journal of Econometrics, Elsevier, vol. 215(1), pages 35-59.
    99. 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.
    100. Clark, Todd E. & Doh, Taeyoung, 2014. "Evaluating alternative models of trend inflation," International Journal of Forecasting, Elsevier, vol. 30(3), pages 426-448.
    101. 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.
    102. 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.
    103. 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.
    104. Anwen Yin, 2021. "Forecasting the Market Equity Premium: Does Nonlinearity Matter?," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 13(5), pages 1-9, May.
    105. Mauersberger, Felix, 2019. "Thompson Sampling: Endogenously Random Behavior in Games and Markets," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203600, Verein für Socialpolitik / German Economic Association.

  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. 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. Davide Delle Monache & Ivan Petrella, 2014. "Adaptive Models and Heavy Tails," Working Papers 720, Queen Mary University of London, School of Economics and Finance.
    3. 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.
    4. 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.
    5. Chan, Joshua & Koop, Gary & Potter, Simon, 2012. "A new model of trend inflation," MPRA Paper 39496, University Library of Munich, Germany.
    6. Todd E. Clark & Michael W. McCracken, 2011. "Advances in forecast evaluation," Working Papers (Old Series) 1120, Federal Reserve Bank of Cleveland.
    7. 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.
    8. Deborah Gefang & Gary Koop & Simon Potter, 2011. "The Dynamics of UK and US Inflation Expectations," Working Papers 1120, University of Strathclyde Business School, Department of Economics.
    9. 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.
    10. 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.
    11. Taeyoung Doh, 2011. "Is unemployment helpful in understanding inflation?," Economic Review, Federal Reserve Bank of Kansas City, vol. 96(Q IV), pages 5-26.
    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. Francesco Ravazzolo & Philip Rothman, 2013. "Oil and U.S. GDP: A Real-Time Out-of-Sample Examination," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 45(2-3), pages 449-463, March.
    2. Todd E. Clark & Michael W. McCracken, 2011. "Advances in forecast evaluation," Working Papers (Old Series) 1120, Federal Reserve Bank of Cleveland.
    3. Santiago Cajiao Raigosa & Luis Fernando Melo Velandia & Daniel Parra Amado, 2014. "Pronósticos para una economía menos volátil: el caso colombiano," Coyuntura Económica, Fedesarrollo, December.
    4. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2012. "Common Drifting Volatility in Large Bayesian VARs," CEPR Discussion Papers 8894, C.E.P.R. Discussion Papers.
    5. 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.
    6. 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.

  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. 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. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    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. 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.
    9. Francesco Ravazzolo & Philip Rothman, 2013. "Oil and U.S. GDP: A Real-Time Out-of-Sample Examination," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 45(2-3), pages 449-463, March.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. Todd E. Clark & Michael W. McCracken, 2010. "Reality checks and nested forecast model comparisons," Working Papers 2010-032, Federal Reserve Bank of St. Louis.
    15. 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.
    16. Ron Alquist & Lutz Kilian & Robert Vigfusson, 2011. "Forecasting the Price of Oil," Staff Working Papers 11-15, Bank of Canada.
    17. 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.
    18. 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].
    19. 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.
    20. Aastveit, Knut Are & Anundsen, André K. & Herstad, Eyo I., 2019. "Residential investment and recession predictability," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1790-1799.
    21. Todd E. Clark & Michael W. McCracken, 2011. "Advances in forecast evaluation," Working Papers (Old Series) 1120, Federal Reserve Bank of Cleveland.
    22. 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.
    23. Hilde C. Bjørnland & Francesco Ravazzolo & Leif Anders Thorsrud, 2015. "Forecasting GDP with global components. This time is different," Working Papers No 1/2015, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    24. Marcellino, Massimiliano & Carriero, Andrea & Corsello, Francesco, 2019. "The Global Component of Inflation Volatility," CEPR Discussion Papers 13470, C.E.P.R. Discussion Papers.
    25. 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.
    26. Garratt, Anthony & Mise, Emi, 2014. "Forecasting exchange rates using panel model and model averaging," Economic Modelling, Elsevier, vol. 37(C), pages 32-40.
    27. Nima Nonejad, 2024. "Point forecasts of the price of crude oil: an attempt to “beat” the end-of-month random-walk benchmark," Empirical Economics, Springer, vol. 67(4), pages 1497-1539, October.
    28. Michael W. McCracken, 2019. "Tests of Conditional Predictive Ability: Some Simulation Evidence," Working Papers 2019-11, Federal Reserve Bank of St. Louis.
    29. Karol Szafranek, 2017. "Bagged artificial neural networks in forecasting inflation: An extensive comparison with current modelling frameworks," NBP Working Papers 262, Narodowy Bank Polski.
    30. Håvard Hungnes, 2020. "Equal predictability test for multi-step-ahead system forecasts invariant to linear transformations," Discussion Papers 931, Statistics Norway, Research Department.
    31. Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman K. van Dijk, 2015. "Dynamic predictive density combinations for large data sets in economics and finance," Working Paper 2015/12, Norges Bank.
    32. 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.
    33. Andrea Carriero & Davide Pettenuzzo & Shubhranshu Shekhar, 2024. "Macroeconomic Forecasting with Large Language Models," Papers 2407.00890, arXiv.org, revised Jan 2025.
    34. Knut Are Aastveit & Claudia Foroni & Francesco Ravazzolo, 2014. "Density forecasts with MIDAS models," Working Paper 2014/10, Norges Bank.
    35. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2012. "Common Drifting Volatility in Large Bayesian VARs," CEPR Discussion Papers 8894, C.E.P.R. Discussion Papers.
    36. Tamás Kiss & Stepan Mazur & Hoang Nguyen & Pär Österholm, 2023. "Modeling the relation between the US real economy and the corporate bond‐yield spread in Bayesian VARs with non‐Gaussian innovations," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 347-368, March.
    37. Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman K. van Dijk, 2020. "A Bayesian Dynamic Compositional Model for Large Density Combinations in Finance," Working Paper series 20-27, Rimini Centre for Economic Analysis.
    38. 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.
    39. 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.
    40. David I. Harvey & Stephen J. Leybourne & Yang Zu, 2024. "Tests for equal forecast accuracy under heteroskedasticity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(5), pages 850-869, August.
    41. Calhoun, Gray, 2014. "Out-Of-Sample Comparisons of Overfit Models," Staff General Research Papers Archive 32462, Iowa State University, Department of Economics.
    42. 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.
    43. 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.
    44. Knut Are Aastveit & Tuva Marie Fastbø & Eleonora Granziera & Kenneth Sæterhagen Paulsen & Kjersti Næss Torstensen, 2024. "Nowcasting Norwegian household consumption with debit card transaction data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(7), pages 1220-1244, November.
    45. 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.
    46. Kichian, Maral & Rumler, Fabio, 2014. "Forecasting Canadian inflation: A semi-structural NKPC approach," Economic Modelling, Elsevier, vol. 43(C), pages 183-191.
    47. 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.
    48. Todd E. Clark & Michael W. McCracken, 2010. "Testing for unconditional predictive ability," Working Papers 2010-031, Federal Reserve Bank of St. Louis.
    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. 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.
    51. 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.
    52. 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.
    53. 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.
    54. 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.).
    55. 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.
    56. Nikolsko-Rzhevskyy, Alex & Prodan, Ruxandra, 2012. "Markov switching and exchange rate predictability," International Journal of Forecasting, Elsevier, vol. 28(2), pages 353-365.
    57. Xiaojie Xu, 2020. "Corn Cash Price Forecasting," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(4), pages 1297-1320, August.

  36. 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. 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.
    2. Hakan Yilmazkuday, 2024. "Pass‐through of shocks into different U.S. prices," Review of International Economics, Wiley Blackwell, vol. 32(3), pages 1300-1315, August.
    3. 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.
    4. Cristina Conflitti & Matteo Luciani, 2019. "Oil Price Pass-Through into Core Inflation," FEDS Notes 2019-04-30, Board of Governors of the Federal Reserve System (U.S.).
    5. Lutz Kilian & Xiaoqing Zhou, 2023. "Oil Price Shocks and Inflation," Working Papers 2312, Federal Reserve Bank of Dallas.
    6. 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.
    7. 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.
    8. Lutz Kilian & Xiaoqing Zhou, 2020. "Oil Prices, Gasoline Prices and Inflation Expectations: A New Model and New Facts," CESifo Working Paper Series 8516, CESifo.
    9. 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.).
    10. 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.
    11. 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.
    12. Castillo, Paul & Montoro, Carlos & Tuesta, Vicente., 2010. "Inflation, Oil Price Volatility and Monetary Policy," Working Papers 2010-002, Banco Central de Reserva del Perú.
    13. 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.
    14. 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.
    15. James H. Stock & Mark W. Watson, 2015. "Core Inflation and Trend Inflation," NBER Working Papers 21282, National Bureau of Economic Research, Inc.
    16. 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.
    17. 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.
    18. 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).
    19. 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.
    20. 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.
    21. 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.
    22. 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.
    23. Muhammad Khan & Nikolay Nenovsky, 2017. "Monetary Regimes and External Shocks Reaction: Empirical Investigations on Eastern European Economies," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 20(66), pages 63-81, December.
    24. Francesca Rondina, 2015. "The role of model uncertainty and learning in the U.S. postwar policy response to oil prices," Working Papers 478, Barcelona School of Economics.
    25. Lutz Kilian & Xiaoqing Zhou, 2021. "The Impact of Rising Oil Prices on U.S. Inflation and Inflation Expectations in 2020-23," Working Papers 2116, Federal Reserve Bank of Dallas.
    26. 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.
    27. Rodriguez, Gabriel & Castillo B., Paul & Calero, Roberto & Salcedo Cisneros, Rodrigo & Ataurima Arellano, Miguel, 2024. "Evolution of the exchange rate pass-through into prices in Peru: An empirical application using TVP-VAR-SV models," Journal of International Money and Finance, Elsevier, vol. 142(C).
    28. Knotek, Edward S. & Zaman, Saeed, 2021. "Asymmetric responses of consumer spending to energy prices: A threshold VAR approach," Energy Economics, Elsevier, vol. 95(C).
    29. 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.
    30. 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).
    31. 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.).
    32. Sánchez García, Javier & Galdeano Gómez, Emilio & Cruz Rambaud, Salvador, 2024. "Drivers of inflationary shocks and spillovers between Europe and the United States," Socio-Economic Planning Sciences, Elsevier, vol. 95(C).
    33. Jon Ellingsen & Caroline Espegren, 2022. "Lost in transition? Earnings losses of displaced petroleum workers," Working Papers No 06/2022, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    34. 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.
    35. Binder, Carola Conces, 2018. "Inflation expectations and the price at the pump," Journal of Macroeconomics, Elsevier, vol. 58(C), pages 1-18.
    36. 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.).
    37. Fulli-Lemaire, Nicolas, 2013. "Alternative inflation hedging strategies for ALM," MPRA Paper 43755, University Library of Munich, Germany.
    38. 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.
    39. Matthew Klepacz, 2018. "Price Setting and Volatility: Evidence from Oil Price Volatility Shocks," 2018 Meeting Papers 145, Society for Economic Dynamics.
    40. Pooyan Amir-Ahmadi & Christian Matthes & Mu-Chun Wang, 2016. "Choosing Prior Hyperparameters," Working Paper 16-9, Federal Reserve Bank of Richmond.
    41. 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.
    42. Deborah Gefang & Gary Koop & Simon Potter, 2011. "The Dynamics of UK and US Inflation Expectations," Working Papers 1120, University of Strathclyde Business School, Department of Economics.
    43. Andreani, Michele & Giri, Federico, 2023. "Not a short-run noise! The low-frequency volatility of energy inflation," Finance Research Letters, Elsevier, vol. 51(C).
    44. 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.
    45. 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.).
    46. 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.
    47. 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).
    48. 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.
    49. 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.
    50. 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.
    51. Michelle, Gilmartin, 2016. "A note on the identification and transmission of energy demand and supply shocks," MPRA Paper 76186, University Library of Munich, Germany.
    52. Gründler, Daniel, 2024. "Does the inflation pass-through of gasoline price shocks depend on the level of inflation?," Economics Letters, Elsevier, vol. 243(C).
    53. 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).
    54. 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).
    55. Fasanya, Ismail O. & Awodimila, Crystal P., 2020. "Are commodity prices good predictors of inflation? The African perspective," Resources Policy, Elsevier, vol. 69(C).
    56. 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.
    57. 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.
    58. 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.
    59. 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.
    60. 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.
    61. 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).
    62. Glocker, Christian & Wegmüller, Philipp, 2024. "Energy price surges and inflation: Fiscal policy to the rescue?," Journal of International Money and Finance, Elsevier, vol. 149(C).
    63. 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.
    64. 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.
    65. 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).
    66. 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.
    67. 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.
    68. López, Lucia & Odendahl, Florens & Parraga Rodriguez, Susana & Silgado-Gómez, Edgar, 2024. "The pass-through to inflation of gas price shocks," Working Paper Series 2968, European Central Bank.
    69. 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).
    70. 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).
    71. 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.

  37. 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. Francesco Ravazzolo & Shaun P. Vahey, 2010. "Forecast densities for economic aggregates from disaggregate ensembles," Working Paper 2010/02, Norges Bank.
    2. 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.
    3. 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.
    4. 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.
    5. 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.

  38. 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. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. Pincheira, Pablo & Selaive, Jorge & Nolazco, Jose Luis, 2017. "Forecasting Inflation in Latin America with Core Measures," MPRA Paper 80496, University Library of Munich, Germany.
    9. Su, Hao & Ying, Chengwei & Zhu, Xiaoneng, 2022. "Disaster risk matters in the bond market," Finance Research Letters, Elsevier, vol. 47(PA).
    10. Chauvet, Marcelle & Senyuz, Zeynep & Yoldas, Emre, 2010. "What does financial volatility tell us about macroeconomic fluctuations?," MPRA Paper 34104, University Library of Munich, Germany, revised Jun 2011.
    11. 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.
    12. Calhoun, Gray, 2014. "Out-Of-Sample Comparisons of Overfit Models," Staff General Research Papers Archive 32462, Iowa State University, Department of Economics.
    13. Hsiu-Hsin Ko, 2016. "Exchange Rate Predictability in Finite Samples," The Japanese Economic Review, Springer, vol. 67(3), pages 361-378, September.
    14. Hsiu-Hsin Ko, 2016. "Exchange Rate Predictability in Finite Samples," The Japanese Economic Review, Japanese Economic Association, vol. 67(3), pages 361-378, September.
    15. Boot, Tom & Pick, Andreas, 2020. "Does modeling a structural break improve forecast accuracy?," Journal of Econometrics, Elsevier, vol. 215(1), pages 35-59.
    16. 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.

  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 & Netšunajev, Aleksei & Strohsal, Till, 2016. "The anchoring of inflation expectations in the short and in the long run," SFB 649 Discussion Papers 2016-015, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    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. 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.
    6. Netésunajev, Aleksei & Winkelmann, Lars, 2016. "International dynamics of inflation expectations," SFB 649 Discussion Papers 2016-019, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    7. 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.).
    8. Benjamin Wong, 2015. "Do inflation expectations propagate the inflationary impact of real oil price shocks?: Evidence from the Michigan survey," Reserve Bank of New Zealand Discussion Paper Series DP2015/01, Reserve Bank of New Zealand.
    9. 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.
    10. 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.
    11. Virginia Queijo von Heideken & Ferre De Graeve, 2012. "Fiscal policy in contemporary DSGE models," 2012 Meeting Papers 74, Society for Economic Dynamics.
    12. J. Scott Davis & Adrienne Mack, 2013. "Cross-country variation in the anchoring of inflation expectations," Staff Papers, Federal Reserve Bank of Dallas, issue Oct.
    13. Jmaes McNeil, 2020. "Monetary policy and the term structure of Inflation expectations with information frictions," Working Papers daleconwp2020-07, Dalhousie University, Department of Economics.
    14. Scott Davis, 2012. "The Effect of Commodity Price Shocks on Underlying Inflation: The Role of Central Bank Credibility," Working Papers 272012, Hong Kong Institute for Monetary Research.
    15. 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.
    16. Del Negro, Marco & Eusepi, Stefano, 2011. "Fitting observed inflation expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 35(12), pages 2105-2131.
    17. 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.
    18. Volha Audzei, 2016. "Confidence Cycles and Liquidity Hoarding," Working Papers 2016/07, Czech National Bank.
    19. 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.).
    20. 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).
    21. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2012. "Common Drifting Volatility in Large Bayesian VARs," CEPR Discussion Papers 8894, C.E.P.R. Discussion Papers.
    22. 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.
    23. Mazumder, Sandeep, 2018. "Inflation in Europe after the Great Recession," Economic Modelling, Elsevier, vol. 71(C), pages 202-213.
    24. 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.
    25. 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.
    26. 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.).
    27. 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.
    28. 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.
    29. 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.
    30. 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.
    31. Henzel, Steffen R., 2013. "Fitting survey expectations and uncertainty about trend inflation," Journal of Macroeconomics, Elsevier, vol. 35(C), pages 172-185.
    32. 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.
    33. Monica Jain, 2018. "Sluggish Forecasts," Staff Working Papers 18-39, Bank of Canada.

  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. Chan, Joshua & Koop, Gary & Potter, Simon, 2012. "A new model of trend inflation," MPRA Paper 39496, University Library of Munich, Germany.
    2. 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.
    3. 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.
    4. Olivier Coibion & Yuriy Gorodnichenko & Saten Kumar & Mathieu Pedemonte, 2018. "Inflation Expectations as a Policy Tool?," NBER Working Papers 24788, National Bureau of Economic Research, Inc.
    5. 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.
    6. Mazumder, Sandeep, 2018. "Inflation in Europe after the Great Recession," Economic Modelling, Elsevier, vol. 71(C), pages 202-213.
    7. K. Istrefi & A. Piloiu, 2014. "Economic Policy Uncertainty and Inflation Expectations," Working papers 511, Banque de France.
    8. Klodiana Istrefi & Anamaria Piloiu, 2013. "Economic Policy Uncertainty, Trust and Inflation Expectations," CESifo Working Paper Series 4294, CESifo.
    9. 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.

  41. 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. 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.
    6. 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.
    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. 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.
    9. Lise Pichette & Marie-Noëlle Robitaille, 2017. "Assessing the Business Outlook Survey Indicator Using Real-Time Data," Discussion Papers 17-5, Bank of Canada.
    10. 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.
    11. John W. Galbraith & Greg Tkacz, 2013. "Nowcasting GDP: Electronic Payments, Data Vintages and the Timing of Data Releases," CIRANO Working Papers 2013s-25, CIRANO.
    12. 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.
    13. 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.
    14. 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.
    15. Francesco Ravazzolo & Philip Rothman, 2013. "Oil and U.S. GDP: A Real-Time Out-of-Sample Examination," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 45(2-3), pages 449-463, March.
    16. Timmermann, Allan & Elliott, Graham, 2007. "Economic Forecasting," CEPR Discussion Papers 6158, C.E.P.R. Discussion Papers.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. 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.
    23. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • 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.
    24. Tanya Molodtsova & Alex Nikolsko‐Rzhevskyy & David H. Papell, 2011. "Taylor Rules and the Euro," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 43(2‐3), pages 535-552, March.
    25. 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.
    26. Christiane Baumeister & Lutz Kilian, 2013. "What Central Bankers Need to Know about Forecasting Oil Prices," Staff Working Papers 13-15, Bank of Canada.
    27. 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.
    28. Alfonso Mendoza Velázquez & Peter N. Smith, 2013. "Equity Returns and the Business Cycle: the Role of Supply and Demand Shocks," Manchester School, University of Manchester, vol. 81, pages 100-124, September.
    29. Akram, Q. Farooq, 2011. "Policy analysis in real time using IMF's monetary model," Economic Modelling, Elsevier, vol. 28(4), pages 1696-1709, July.
    30. 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.
    31. Todd E. Clark & Michael W. McCracken, 2011. "Advances in forecast evaluation," Working Papers (Old Series) 1120, Federal Reserve Bank of Cleveland.
    32. Dean Croushore, 2008. "Frontiers of real-time data analysis," Working Papers 08-4, Federal Reserve Bank of Philadelphia.
    33. 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.
    34. 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.
    35. Barnett, Alina & Mumtaz, Haroon & Theodoridis, Konstantinos, 2012. "Forecasting UK GDP growth, inflation and interest rates under structural change: a comparison of models with time-varying parameters," Bank of England working papers 450, Bank of England.
    36. 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.
    37. Hyun Hak Kim & Norman Swanson, 2013. "Mining Big Data Using Parsimonious Factor and Shrinkage Methods," Departmental Working Papers 201316, Rutgers University, Department of Economics.
    38. Heinisch Katja & Scheufele Rolf, 2019. "Should Forecasters Use Real-Time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence," German Economic Review, De Gruyter, vol. 20(4), pages 170-200, December.
    39. 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.
    40. Christiane Baumeister & Lutz Kilian, 2011. "Real-Time Forecasts of the Real Price of Oil," Staff Working Papers 11-16, Bank of Canada.
    41. Kilian, Lutz & Baumeister, Christiane & Zhou, Xiaoqing, 2013. "Are Product Spreads Useful for Forecasting? An Empirical Evaluation of the Verleger Hypothesis," CEPR Discussion Papers 9572, C.E.P.R. Discussion Papers.
    42. 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.
    43. 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.
    44. Knut Are Aastveit & Claudia Foroni & Francesco Ravazzolo, 2014. "Density forecasts with MIDAS models," Working Paper 2014/10, Norges Bank.
    45. Chauvet, Marcelle & Senyuz, Zeynep & Yoldas, Emre, 2010. "What does financial volatility tell us about macroeconomic fluctuations?," MPRA Paper 34104, University Library of Munich, Germany, revised Jun 2011.
    46. 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.
    47. 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.
    48. Edward S. Knotek & Saeed Zaman, 2017. "Nowcasting U.S. Headline and Core Inflation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(5), pages 931-968, August.
    49. 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.
    50. Philippe de Peretti & Oren Tapiero, 2014. "A GARCH analysis of dark-pool trades," Post-Print hal-00984834, HAL.
    51. Knut Are Aastveit & Tuva Marie Fastbø & Eleonora Granziera & Kenneth Sæterhagen Paulsen & Kjersti Næss Torstensen, 2024. "Nowcasting Norwegian household consumption with debit card transaction data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(7), pages 1220-1244, November.
    52. 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.
    53. 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.
    54. 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.
    55. 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.
    56. 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.
    57. Todd E. Clark & Michael W. McCracken, 2010. "Testing for unconditional predictive ability," Working Papers 2010-031, Federal Reserve Bank of St. Louis.
    58. 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.
    59. 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.
    60. Marcellino, Massimiliano & Foroni, Claudia, 2014. "Markov-Switching Mixed-Frequency VAR Models," CEPR Discussion Papers 9815, C.E.P.R. Discussion Papers.
    61. Marcellino, Massimiliano, 2011. "Markov-switching MIDAS models," CEPR Discussion Papers 8234, C.E.P.R. Discussion Papers.
    62. 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.
    63. 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.
    64. 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.
    65. 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.
    66. 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.
    67. Cecilia Frale & Valentina Raponi, 2011. "Revisions in ocial data and forecasting," Working Papers LuissLab 1194, Dipartimento di Economia e Finanza, LUISS Guido Carli.
    68. 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.
    69. 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.
    70. 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.
    71. 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.

  42. 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.).

    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. 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.
    3. 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).
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. Francesco Ravazzolo & Shaun P. Vahey, 2010. "Forecast densities for economic aggregates from disaggregate ensembles," Working Paper 2010/02, Norges Bank.
    9. Karlsson, Sune, 2012. "Forecasting with Bayesian Vector Autoregressions," Working Papers 2012:12, Örebro University, School of Business.
    10. 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.
    11. 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.
    12. 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.
    13. Jan J. J. Groen & Richard Paap & Francesco Ravazzolo, 2013. "Real-Time Inflation Forecasting in a Changing World," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(1), pages 29-44, January.
    14. 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.
    15. 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.
    16. 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.
    17. Niu, Linlin & Xu, Xiu & Chen, Ying, 2017. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," Economic Modelling, Elsevier, vol. 66(C), pages 201-213.
    18. 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.
    19. 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.
    20. 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.
    21. Hilde Bjørnland & Karsten Gerdrup & Christie Smith & Anne Sofie Jore & Leif Anders Thorsrud, 2010. "Weights and pools for a Norwegian density combination," Working Paper 2010/06, Norges Bank.
    22. 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.
    23. 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.
    24. 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.
    25. 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.).
    26. M. Hashem Pesaran & Andreas Pick, 2008. "Forecasting Random Walks Under Drift Instability," CESifo Working Paper Series 2293, CESifo.
    27. 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.
    28. Schumacher, Christian, 2009. "Factor forecasting using international targeted predictors: the case of German GDP," Discussion Paper Series 1: Economic Studies 2009,10, Deutsche Bundesbank.
    29. 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).
    30. 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.
    31. Katja Heinisch & Rolf Scheufele, 2018. "Bottom-up or direct? Forecasting German GDP in a data-rich environment," Empirical Economics, Springer, vol. 54(2), pages 705-745, March.
    32. 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.
    33. 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.
    34. Kuzin, Vladimir N. & Marcellino, Massimiliano & Schumacher, Christian, 2009. "Pooling versus model selection for nowcasting with many predictors: an application to German GDP," Discussion Paper Series 1: Economic Studies 2009,03, Deutsche Bundesbank.
    35. Knotek, Edward S. & Zaman, Saeed, 2023. "Real-time density nowcasts of US inflation: A model combination approach," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1736-1760.
    36. Tony Chernis & Taylor Webley, 2022. "Nowcasting Canadian GDP with Density Combinations," Discussion Papers 2022-12, Bank of Canada.
    37. John M. Maheu & Yong Song, 2012. "A New Structural Break Model with Application to Canadian Inflation Forecasting," Working Paper series 27_12, Rimini Centre for Economic Analysis.
    38. Bjarni G. Einarsson, 2024. "Online Monitoring of Policy Optimality," Economics wp95, Department of Economics, Central bank of Iceland.
    39. Knut Are Aastveit & Francesco Ravazzolo & Herman K. van Dijk, 2014. "Combined Density Nowcasting in an uncertain economic environment," Working Paper 2014/17, Norges Bank.
    40. Tae-Hwy Lee & Shahnaz Parsaeian & Aman Ullah, 2022. "Optimal Forecast under Structural Breaks," Working Papers 202208, University of California at Riverside, Department of Economics.
    41. Carstensen, Kai & Wohlrabe, Klaus & Ziegler, Christina, 2011. "Predictive ability of business cycle indicators under test: A case study for the Euro area industrial production," Munich Reprints in Economics 19953, University of Munich, Department of Economics.
    42. 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.
    43. 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.
    44. 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.
    45. 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.
    46. 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.
    47. 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.
    48. Berg, Tim Oliver & Henzel, Steffen, 2013. "Point and Density Forecasts for the Euro Area Using Many Predictors: Are Large BVARs Really Superior?," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79783, Verein für Socialpolitik / German Economic Association.
    49. Duc Do, Nguyen, 2024. "Money/asset ratio as a predictor of inflation," The Quarterly Review of Economics and Finance, Elsevier, vol. 97(C).
    50. Knut Are Aastveit & Jamie L. Cross & Herman K. van Dijk, 2021. "Quantifying time-varying forecast uncertainty and risk for the real price of oil," Working Paper 2021/3, Norges Bank.
    51. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
    52. John M. Maheu & Thomas H. McCurdy, 2007. "How useful are historical data for forecasting the long-run equity return distribution?," Working Paper series 19_07, Rimini Centre for Economic Analysis.
    53. Hauzenberger, Niko & Huber, Florian & Klieber, Karin, 2023. "Real-time inflation forecasting using non-linear dimension reduction techniques," International Journal of Forecasting, Elsevier, vol. 39(2), pages 901-921.
    54. Giannone, Domenico & De Mol, Christine & Conflitti, Cristina, 2012. "Optimal Combination of Survey Forecasts," CEPR Discussion Papers 9096, C.E.P.R. Discussion Papers.
    55. Marek Rusnak, 2013. "Nowcasting Czech GDP in Real Time," Working Papers 2013/06, Czech National Bank.
    56. Graham Elliott & Allan Timmermann, 2016. "Forecasting in Economics and Finance," Annual Review of Economics, Annual Reviews, vol. 8(1), pages 81-110, October.
    57. 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.
    58. Schumacher, Christian, 2016. "A comparison of MIDAS and bridge equations," International Journal of Forecasting, Elsevier, vol. 32(2), pages 257-270.
    59. Drachal, Krzysztof, 2021. "Forecasting crude oil real prices with averaging time-varying VAR models," Resources Policy, Elsevier, vol. 74(C).
    60. 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.
    61. Buncic, Daniel & Müller, Oliver, 2017. "Measuring the output gap in Switzerland with linear opinion pools," Economic Modelling, Elsevier, vol. 64(C), pages 153-171.
    62. Carlo Altavilla & Matteo Ciccarelli, 2011. "Monetary Policy Analysis in Real-Time. Vintage Combination from a Real-Time Dataset," CESifo Working Paper Series 3372, CESifo.
    63. Charles Rahal, 2015. "Housing Market Forecasting with Factor Combinations," Discussion Papers 15-05, Department of Economics, University of Birmingham.
    64. 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.
    65. 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.
    66. 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.
    67. 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.
    68. 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.
    69. 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.
    70. Garratt, Anthony & Mitchell, James & Vahey, Shaun P., 2014. "Measuring output gap nowcast uncertainty," International Journal of Forecasting, Elsevier, vol. 30(2), pages 268-279.
    71. 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.
    72. Tony Chernis & Rodrigo Sekkel, 2018. "Nowcasting Canadian Economic Activity in an Uncertain Environment," Discussion Papers 18-9, Bank of Canada.
    73. 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).
    74. Chanont Banternghansa & Michael W. McCracken, 2010. "Real-time forecast averaging with ALFRED," Working Papers 2010-033, Federal Reserve Bank of St. Louis.
    75. 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.
    76. 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.
    77. Bruno P. C. Levy & Hedibert F. Lopes, 2021. "Dynamic Ordering Learning in Multivariate Forecasting," Papers 2101.04164, arXiv.org, revised Nov 2021.
    78. 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.
    79. 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.
    80. di Mauro, Filippo & Fornari, Fabio & Mannucci, Dario, 2011. "Stock market firm-level information and real economic activity," Working Paper Series 1366, European Central Bank.
    81. Liebermann, Joelle, 2012. "Real-time forecasting in a data-rich environment," Research Technical Papers 07/RT/12, Central Bank of Ireland.
    82. 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.
    83. Christian Kascha & Francesco Ravazzolo, 2008. "Combining inflation density forecasts," Working Paper 2008/22, Norges Bank.
    84. Xiaojie Xu, 2020. "Corn Cash Price Forecasting," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(4), pages 1297-1320, August.
    85. Tim Oliver Berg & Steffen Henzel, 2014. "Point and Density Forecasts for the Euro Area Using Bayesian VARs," CESifo Working Paper Series 4711, CESifo.
    86. 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.
    87. 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.
    88. Clark, Todd E. & Doh, Taeyoung, 2014. "Evaluating alternative models of trend inflation," International Journal of Forecasting, Elsevier, vol. 30(3), pages 426-448.
    89. Francisco Blasques & Siem Jan Koopman & André Lucas, 2014. "Optimal Formulations for Nonlinear Autoregressive Processes," Tinbergen Institute Discussion Papers 14-103/III, Tinbergen Institute.
    90. 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.

  43. 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. Giannone, Domenico & D’Agostino, Antonello & Gambetti, Luca, 2009. "Macroeconomic Forecasting and Structural Change," CEPR Discussion Papers 7542, C.E.P.R. Discussion Papers.
    2. 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.
    3. Michal Rubaszek & Pawel Skrzypczynski, 2007. "Can a simple DSGE model outperform Professional Forecasters?," NBP Working Papers 43, Narodowy Bank Polski.
    4. 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.
    5. 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.
    6. Hendry, David F. & Hubrich, Kirstin, 2010. "Combining disaggregate forecasts or combining disaggregate information to forecast an aggregate," Working Paper Series 1155, European Central Bank.
    7. 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.
    8. 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.
    9. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
    10. Carlo Altavilla & Matteo Ciccarelli, 2011. "Monetary Policy Analysis in Real-Time. Vintage Combination from a Real-Time Dataset," CESifo Working Paper Series 3372, CESifo.
    11. 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.
    12. 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.
    13. 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.
    14. 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.

  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. Antoine Mandel & Amir Sani, 2017. "A Machine Learning Approach to the Forecast Combination Puzzle," Working Papers halshs-01317974, HAL.
    5. 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.
    6. 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.
    7. 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).
    8. Hong, Han & Preston, Bruce, 2012. "Bayesian averaging, prediction and nonnested model selection," Journal of Econometrics, Elsevier, vol. 167(2), pages 358-369.
    9. 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.
    10. James H. Stock & Mark W. Watson, 2008. "Phillips Curve Inflation Forecasts," NBER Working Papers 14322, National Bureau of Economic Research, Inc.
    11. 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.
    12. Eric Hillebrand & Tae-Hwy Lee, 2012. "Stein-Rule Estimation and Generalized Shrinkage Methods for Forecasting Using Many Predictors," Advances in Econometrics, in: 30th Anniversary Edition, pages 171-196, Emerald Group Publishing Limited.
    13. Antoine Mandel & Amir Sani, 2016. "Learning Time-Varying Forecast Combinations," Documents de travail du Centre d'Economie de la Sorbonne 16036r, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Sep 2016.
    14. Carriero, Andrea & Giacomini, Raffaella, 2011. "How useful are no-arbitrage restrictions for forecasting the term structure of interest rates?," Journal of Econometrics, Elsevier, vol. 164(1), pages 21-34, September.
    15. 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.
    16. Emrah Gulay & Serkan Aras, 2024. "Does a meta-combining method lead to more accurate forecasts in the decision-making process?," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 34(3), pages 101-124.
    17. 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.

  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. 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.
    2. 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.
    3. Kirdan Lees & Troy Matheson, 2005. "Mind your Ps and Qs! Improving ARMA forecasts with RBC priors," Reserve Bank of New Zealand Discussion Paper Series DP2005/02, Reserve Bank of New Zealand.
    4. Carstensen, Kai & Wohlrabe, Klaus & Ziegler, Christina, 2011. "Predictive ability of business cycle indicators under test: A case study for the Euro area industrial production," Munich Reprints in Economics 19953, University of Munich, Department of Economics.
    5. 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.
    6. 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.
    7. 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.
    8. Onur Ince & Tanya Molodtsova, 2013. "Real-Time Out-of-Sample Exchange Rate Predictability," Working Papers 13-03, Department of Economics, Appalachian State University.
    9. 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.

  47. Todd E. Clark & Kenneth D. West, 2005. "Approximately normal tests for equal predictive accuracy in nested models," Research Working Paper RWP 05-05, Federal Reserve Bank of Kansas City.

    Cited by:

    1. Wang, Yudong & Hao, Xianfeng, 2023. "Forecasting the real prices of crude oil: What is the role of parameter instability?," Energy Economics, Elsevier, vol. 117(C).
    2. Michael J. Dueker & Zacharias Psaradakis & Martin Sola & Fabio Spagnolo, 2013. "State-Dependent Threshold Smooth Transition Autoregressive Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(6), pages 835-854, December.
    3. 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.
    4. Viktor Todorov & Yang Zhang, 2022. "Information gains from using short‐dated options for measuring and forecasting volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(2), pages 368-391, March.
    5. Afees A. Salisu & Ahamuefula E. Ogbonna & Elie Bouri & Rangan Gupta, 2024. "Climate Risks and Prediction of Sectoral REITs Volatility: International Evidence," Working Papers 202434, University of Pretoria, Department of Economics.
    6. Etienne, Xiaoli, 2015. "Financialization of Agricultural Commodity Markets: Do Financial Data Help to Forecast Agricultural Prices," 2015 Conference, August 9-14, 2015, Milan, Italy 211626, International Association of Agricultural Economists.
    7. Chen, Shiu-Sheng, 2013. "Forecasting Crude Oil Price Movements with Oil-Sensitive Stocks," MPRA Paper 49240, University Library of Munich, Germany.
    8. Zhang, Xiaoyun & Guo, Qiang, 2024. "How useful are energy-related uncertainty for oil price volatility forecasting?," Finance Research Letters, Elsevier, vol. 60(C).
    9. Carstensen, Kai & Heinrich, Markus & Reif, Magnus & Wolters, Maik H., 2020. "Predicting ordinary and severe recessions with a three-state Markov-switching dynamic factor model," International Journal of Forecasting, Elsevier, vol. 36(3), pages 829-850.
    10. Rossi, José Luiz Júnior, 2013. "Liquidity and Exchange Rates," Insper Working Papers wpe_325, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    11. Yin, Anwen, 2015. "Forecasting and model averaging with structural breaks," ISU General Staff Papers 201501010800005727, Iowa State University, Department of Economics.
    12. Robert Lehmann & Antje Weyh, 2016. "Forecasting Employment in Europe: Are Survey Results Helpful?," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(1), pages 81-117, September.
    13. Hashmat Khan & Santosh Upadhayaya, 2017. "Does Business Confidence Matter for Investment?," Carleton Economic Papers 17-13, Carleton University, Department of Economics, revised 20 Mar 2019.
    14. Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2023. "Forecasting the Realized Volatility of Agricultural Commodity Prices: Does Sentiment Matter?," Working Papers 202316, University of Pretoria, Department of Economics.
    15. Eric Ghysels & Leonardo Iania & Jonas Striaukas, 2018. "Quantile-based Inflation Risk Models," Working Paper Research 349, National Bank of Belgium.
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    1245. 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.
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  48. Todd E. Clark & Michael W. McCracken, 2004. "Improving forecast accuracy by combining recursive and rolling forecasts," Research Working Paper RWP 04-10, Federal Reserve Bank of Kansas City.

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    1. Chen, Guojin & Liu, Yanzhen & Zhang, Yu, 2020. "Can systemic risk measures predict economic shocks? Evidence from China," China Economic Review, Elsevier, vol. 64(C).
    2. 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.
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    5. Cai, Zongwu & Juhl, Ted, 2023. "The distribution of rolling regression estimators," Journal of Econometrics, Elsevier, vol. 235(2), pages 1447-1463.
    6. 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.
    7. Scott A. Brave & Charles S. Gascon & William Kluender & Thomas Walstrum, 2019. "Predicting Benchmarked US State Employment Data in Real Time," Working Papers 2019-037, Federal Reserve Bank of St. Louis, revised 11 Mar 2021.
    8. Andersen, Torben G. & Varneskov, Rasmus T., 2022. "Testing for parameter instability and structural change in persistent predictive regressions," Journal of Econometrics, Elsevier, vol. 231(2), pages 361-386.
    9. Luis F. Melo Velandia & Rubén A. Loaiza Maya & Mauricio Villamizar-Villegas, 2014. "Bayesian Combination for Inflation Forecasts: The Effects of a Prior Based on Central Banks’ Estimates," Borradores de Economia 853, Banco de la Republica de Colombia.
    10. 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.
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    12. Ming-Chih Lee & Chien-Liang Chiu & Wan-Hsiu Cheng, 2007. "Enhancing Forecast Accuracy By Using Long Estimation Periods," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 1(2), pages 1-9.
    13. 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.
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    44. Rodolfo C. Moura & Márcio P. Laurini, 2021. "Spillovers and jumps in global markets: A comparative analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5997-6013, October.
    45. Renata Tavanielli & Márcio Laurini, 2023. "Yield Curve Models with Regime Changes: An Analysis for the Brazilian Interest Rate Market," Mathematics, MDPI, vol. 11(11), pages 1-28, June.
    46. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
    47. Andre Jungmittag, 2016. "Combination of Forecasts across Estimation Windows: An Application to Air Travel Demand," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(4), pages 373-380, July.
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    49. Charles Hoffreumon & Nicolas van Zeebroeck, 2018. "Forecasting short-term transaction fees on a smart contracts platform," Working Papers TIMES² 2018-028, ULB -- Universite Libre de Bruxelles.
    50. Vellachami, Sanggetha & Hasanov, Akram Shavkatovich & Brooks, Robert, 2023. "Risk transmission from the energy markets to the carbon market: Evidence from the recursive window approach," International Review of Financial Analysis, Elsevier, vol. 89(C).
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    52. Leung, Charles Ka Yui & Tang, Edward Chi Ho, 2014. "Availability, Affordability and Volatility: the case of Hong Kong Housing Market," MPRA Paper 58770, University Library of Munich, Germany.
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    55. Christopher J. Neely & David E. Rapach & Jun Tu & Guofu Zhou, 2014. "Forecasting the Equity Risk Premium: The Role of Technical Indicators," Management Science, INFORMS, vol. 60(7), pages 1772-1791, July.
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    61. Dimitrios D. Thomakos & Fotis Papailias, 2013. "Covariance Averaging for Improved Estimation and Portfolio Allocation," Working Paper series 66_13, Rimini Centre for Economic Analysis.
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    69. Damiano B. Silipo & Giovanni Verga & Sviatlana Hlebik, 2023. "Managerial Beliefs and Banking Behavior," Journal of Financial Services Research, Springer;Western Finance Association, vol. 64(3), pages 401-431, December.
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  49. 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. 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.
    2. 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.
    3. 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.
    4. 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.).
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    6. Bagsic, Cristeta & Paul, McNelis, 2007. "Output Gap Estimation for Inflation Forecasting: The Case of the Philippines," MPRA Paper 86789, University Library of Munich, Germany.
    7. Raheem, Ibrahim, 2020. "Global financial cycles and exchange rate forecast: A factor analysis," MPRA Paper 105358, University Library of Munich, Germany.
    8. Joseph P. Byrne & Dimitris Korobilis & Pinho J. Ribeiro, 2014. "Exchange Rate Predictability in a Changing World," Working Paper series 06_14, Rimini Centre for Economic Analysis.
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    39. Yu-chin Chen & Stephen J. Turnovsky & Eric Zivot, 2011. "Forecasting Inflation using Commodity Price Aggregates," Working Papers UWEC-2011-14, University of Washington, Department of Economics.
    40. Sager, Michael & Taylor, Mark P., 2014. "Generating currency trading rules from the term structure of forward foreign exchange premia," Journal of International Money and Finance, Elsevier, vol. 44(C), pages 230-250.
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    43. Souza, Thiago de Oliveira, 2020. "Dollar carry timing," Discussion Papers on Economics 10/2020, University of Southern Denmark, Department of Economics.
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    45. 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.
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    47. Luis Filipe Martins & Pierre Perron, 2014. "Improved Tests for Forecast Comparisons in the Presence of Instabilities," Boston University - Department of Economics - Working Papers Series 2014-003, Boston University - Department of Economics.
    48. Jian Wang & Jason J. Wu, 2012. "The Taylor Rule and Forecast Intervals for Exchange Rates," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(1), pages 103-144, February.
    49. Pincheira, Pablo, 2017. "A Power Booster Factor for Out-of-Sample Tests of Predictability," MPRA Paper 77027, University Library of Munich, Germany.
    50. Søren Kjærgaard & Yunus Emre Ergemen & Marie-Pier Bergeron Boucher & Jim Oeppen & Malene Kallestrup-Lamb, 2019. "Longevity forecasting by socio-economic groups using compositional data analysis," CREATES Research Papers 2019-08, Department of Economics and Business Economics, Aarhus University.
    51. Alice Albonico & Alessia Paccagnini & Patrizio Tirelli, 2018. "Limited Asset Market Participation and the Euro Area Crisis. An Empirical DSGE Model," Working Papers 391, University of Milano-Bicocca, Department of Economics, revised Nov 2018.
    52. Joseph P. Byrne & Shuo Cao. & Dimitris Korobilis., 2015. "Term Structure Dynamics, Macro-Finance Factors and Model Uncertainty," Working Papers 2015_08, Business School - Economics, University of Glasgow.
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    56. Rossi Junior, Jose Luiz & Felicio, Wilson Rafael de Oliveira, 2014. "Common Factors and the Exchange Rate: Results From the Brazilian Case," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 68(1), April.
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    66. 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.
    67. 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.
    68. Carlos Capistrán & Manuel Ramos‐Francia, 2009. "Inflation Dynamics In Latin America," Contemporary Economic Policy, Western Economic Association International, vol. 27(3), pages 349-362, July.
    69. James Yetman, 2009. "Hong Kong Consumer Prices are Flexible," Working Papers 052009, Hong Kong Institute for Monetary Research.
    70. 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.
    71. 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.
    72. Chiara Perricone, 2013. "Clustering Macroeconomic Variables," CEIS Research Paper 283, Tor Vergata University, CEIS, revised 11 Jun 2013.
    73. 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.
    74. 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.
    75. Viacheslav Kramkov, 2023. "Does CPI disaggregation improve inflation forecast accuracy?," Bank of Russia Working Paper Series wps112, Bank of Russia.
    76. Carlomagno, Guillermo, 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.
    77. Agnieszka Leszczynska & Katarzyna Hertel, 2013. "Inflation persistence – a disaggregated approach," EcoMod2013 5692, EcoMod.
    78. 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.
    79. Senra, Eva, 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.
    80. 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.
    81. 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.
    82. 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.
    83. Mr. James P Walsh, 2011. "Reconsidering the Role of Food Prices in Inflation," IMF Working Papers 2011/071, International Monetary Fund.
    84. Antoni Espasa & Eva Senra, 2017. "Twenty-Two Years of Inflation Assessment and Forecasting Experience at the Bulletin of EU & US Inflation and Macroeconomic Analysis," Econometrics, MDPI, vol. 5(4), pages 1-28, October.
    85. Shintani, Mototsugu & Guo, Zi-Yi, 2011. "Finite Sample Performance of Principal Components Estimators for Dynamic Factor Models: Asymptotic vs. Bootstrap Approximations," EconStor Preprints 167627, ZBW - Leibniz Information Centre for Economics.
    86. Kim, Dukpa, 2011. "Estimating a common deterministic time trend break in large panels with cross sectional dependence," Journal of Econometrics, Elsevier, vol. 164(2), pages 310-330, October.

  52. 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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.).
    7. 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.
    8. 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.
    9. Karlsson, Sune & Österholm, Pär, 2018. "Is the US Phillips Curve Stable? Evidence from Bayesian VARs," Working Papers 2018:5, Örebro University, School of Business.
    10. Mr. Serhan Cevik & Tianle Zhu, 2019. "Trinity Strikes Back: Monetary Independence and Inflation in the Caribbean," IMF Working Papers 2019/197, International Monetary Fund.
    11. Rossi, Barbara & Wang, Yiru, 2019. "Vector autoregressive-based Granger causality test in the presence of instabilities," MPRA Paper 101492, University Library of Munich, Germany.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. Martha López P., 2003. "Efficient Policy Rule for Inflation Targeting in Colombia," Borradores de Economia 240, Banco de la Republica de Colombia.
    18. Michael Dotsey & Shigeru Fujita & Tom Stark, 2011. "Do Phillips curves conditionally help to forecast inflation?," Working Papers 11-40, Federal Reserve Bank of Philadelphia.
    19. Kabukçuoğlu, Ayşe & Martínez-García, Enrique, 2018. "Inflation as a global phenomenon—Some implications for inflation modeling and forecasting," Journal of Economic Dynamics and Control, Elsevier, vol. 87(C), pages 46-73.
    20. 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.
    21. 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.
    22. Lillian Kamal, 2014. "Do GAP Models Still have a Role to Play in Forecasting Inflation?," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 8(3), pages 1-12.
    23. Oguzhan Cepni & David Gabauer & Rangan Gupta & Khuliso Ramabulana, 2020. "Time-Varying Spillover of US Trade War on the Growth of Emerging Economies," Working Papers 202002, University of Pretoria, Department of Economics.
    24. Sune Karlsson & Pär Österholm, 2020. "A note on the stability of the Swedish Phillips curve," Empirical Economics, Springer, vol. 59(6), pages 2573-2612, December.
    25. César Calderón & Klaus Schmidt-Hebbel, 2010. "What Drives Inflation in the World?," RBA Annual Conference Volume (Discontinued), in: Renée Fry & Callum Jones & Christopher Kent (ed.),Inflation in an Era of Relative Price Shocks, Reserve Bank of Australia.
    26. Pablo Pincheira & Hernán Rubio, 2010. "The Low Predictive Power of Simple Phillips Curves in Chile: A Real-Time Evaluation," Working Papers Central Bank of Chile 559, Central Bank of Chile.
    27. Dieppe, Alistair & Ortega, Eva & D'Agostino, Antonello & Karlsson, Tohmas & Benkovskis, Konstantins & Caivano, Michele & Hurtado, Samuel & Várnai, Tímea, 2011. "Assessing the sensitivity of inflation to economic activity," Working Paper Series 1357, European Central Bank.
    28. 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.
    29. Jean-Stéphane MESONNIER, 2007. "The predictive content of the real interest rate gap for macroeconomic variables in the euro area," Money Macro and Finance (MMF) Research Group Conference 2006 102, Money Macro and Finance Research Group.
    30. 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.
    31. Wayne Robinson, 2004. "Real Shocks, Credibility & Stabilization Policy in a Small Open Economy," Money Affairs, CEMLA, vol. 0(1), pages 39-55, January-J.
    32. 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.
    33. 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.
    34. 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.
    35. 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.
    36. Sune Karlsson & Pär Österholm, 2023. "Is the US Phillips curve stable? Evidence from Bayesian vector autoregressions," Scandinavian Journal of Economics, Wiley Blackwell, vol. 125(1), pages 287-314, January.
    37. Gonzalo Llosa & Shirley Miller, 2005. "Using additional information in estimating the output gap in Peru: a multivariate unobserved component approach," Working Papers 2005-004, Banco Central de Reserva del Perú.
    38. Tillmann, Peter, 2010. "The Fed's perceived Phillips curve: Evidence from individual FOMC forecasts," Journal of Macroeconomics, Elsevier, vol. 32(4), pages 1008-1013, December.
    39. Hamza Bennani, 2018. "Media Perception of Fed Chair's Overconfidence and Market Expectations," EconomiX Working Papers 2018-29, University of Paris Nanterre, EconomiX.
    40. Rossi, Barbara & Sekhposyan, Tatevik, 2011. "Understanding models' forecasting performance," Journal of Econometrics, Elsevier, vol. 164(1), pages 158-172, September.
    41. Conti, Antonio M., 2021. "Resurrecting the Phillips Curve in Low-Inflation Times," Economic Modelling, Elsevier, vol. 96(C), pages 172-195.
    42. Yiru Wang & Barbara Rossi, 2019. "VAR-based Granger-causality test in the presence of instabilities," Economics Working Papers 1642, Department of Economics and Business, Universitat Pompeu Fabra.
    43. Matheson, Troy D., 2008. "Phillips curve forecasting in a small open economy," Economics Letters, Elsevier, vol. 98(2), pages 161-166, February.
    44. 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.
    45. James H. Stock & Mark W. Watson, 2008. "Phillips Curve Inflation Forecasts," NBER Working Papers 14322, National Bureau of Economic Research, Inc.
    46. Pablo Pincheira & Andrés Gatty, 2016. "Forecasting Chilean inflation with international factors," Empirical Economics, Springer, vol. 51(3), pages 981-1010, November.
    47. Lance J. Bachmeier & Norman R. Swanson, 2003. "Predicting Inflation: Does The Quantity Theory Help?," Departmental Working Papers 200317, Rutgers University, Department of Economics.
    48. Pincheira, Pablo & Selaive, Jorge & Nolazco, Jose Luis, 2017. "Forecasting Inflation in Latin America with Core Measures," MPRA Paper 80496, University Library of Munich, Germany.
    49. Christina Anderl & Guglielmo Maria Caporale, 2023. "The Asymmetric Impact of Economic Policy and Oil Price Uncertainty on Inflation: Evidence from Developed and Emerging Economies," CESifo Working Paper Series 10276, CESifo.
    50. Luca Agnello & Vítor Castro & Ricardo M. Sousa, 2023. "Interest rate gaps in an uncertain global context: why “too” low (high) for “so” long?," Empirical Economics, Springer, vol. 64(2), pages 539-565, February.
    51. Yonglian Wang & Lijun Wang & Changchun Pan, 2022. "Tourism–Growth Nexus in the Presence of Instability," Sustainability, MDPI, vol. 14(4), pages 1-11, February.
    52. 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.
    53. Frédérique Bec & Matteo Mogliani, 2013. "Nowcasting French GDP in Real-Time from Survey Opinions : Information or Forecast Combinations ?," Working Papers 2013-21, Center for Research in Economics and Statistics.
    54. Orphanides, Athanasios & van Norden, Simon, 2005. "The Reliability of Inflation Forecasts Based on Output Gap Estimates in Real Time," CEPR Discussion Papers 4830, C.E.P.R. Discussion Papers.
    55. 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.
    56. 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.
    57. Raffella Giacomini & Barbara Rossi, 2005. "Detecting and Predicting Forecast Breakdowns," UCLA Economics Working Papers 845, UCLA Department of Economics.
    58. 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.
    59. 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.
    60. 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).
    61. 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.
    62. 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.
    63. 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.
    64. Tri Minh Phan, 2024. "Sentiment-semantic word vectors: A new method to estimate management sentiment," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 160(1), pages 1-22, December.
    65. 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.
    66. 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.
    67. 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.
    68. Todd E. Clark & Michael W. McCracken, 2010. "Testing for unconditional predictive ability," Working Papers 2010-031, Federal Reserve Bank of St. Louis.
    69. Jeremy M. Piger & Robert H. Rasche, 2006. "Inflation: do expectations trump the gap?," Working Papers 2006-013, Federal Reserve Bank of St. Louis.
    70. Gary J. Cornwall & Jeffrey A. Mills & Beau A. Sauley & Huibin Weng, 2019. "Predictive Testing for Granger Causality via Posterior Simulation and Cross-validation," Advances in Econometrics, in: Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling: Part A, volume 40, pages 275-292, Emerald Group Publishing Limited.
    71. Nicholas Apergis & Panagiotis G. Artikis, 2016. "Foreign Exchange Risk, Equity Risk Factors and Economic Growth," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 44(4), pages 425-445, December.
    72. Lance Bachmeier & Qi Li & Dandan Liu, 2008. "Should Oil Prices Receive So Much Attention? An Evaluation Of The Predictive Power Of Oil Prices For The U.S. Economy," Economic Inquiry, Western Economic Association International, vol. 46(4), pages 528-539, October.
    73. Frédérick Demers, 2003. "The Canadian Phillips Curve and Regime Shifting," Staff Working Papers 03-32, Bank of Canada.
    74. 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).
    75. Hilde C. Bjørnland & Leif Brubakk & Anne Sofie Jore, 2006. "Forecasting inflation with an uncertain output gap," Working Paper 2006/02, Norges Bank.
    76. 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.
    77. Ahmad, Saad & Civelli, Andrea, 2016. "Globalization and inflation: A threshold investigation," Journal of Macroeconomics, Elsevier, vol. 48(C), pages 283-304.
    78. McCracken, Michael W., 2007. "Asymptotics for out of sample tests of Granger causality," Journal of Econometrics, Elsevier, vol. 140(2), pages 719-752, October.
    79. Cevik Serhan & Jalles Joao, 2024. "Eye of the Storm: The Impact of Climate Shocks on Inflation and Growth," Review of Economics, De Gruyter, vol. 75(2), pages 109-138.
    80. Don H. Kim, 2009. "Challenges in macro-finance modeling," Review, Federal Reserve Bank of St. Louis, vol. 91(Sep), pages 519-544.
    81. 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.
    82. Michał Hulej & Grzegorz Grabek, 2015. "Output gap measure based on survey data," NBP Working Papers 200, Narodowy Bank Polski.
    83. 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.
    84. Adriana Arreaza & Enid Blanco & Miguel Dorta, 2004. "A Small Scale Macroeconomic Model for Venezuela," Money Affairs, CEMLA, vol. 0(1), pages 25-38, January-J.
    85. 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.
    86. M sonnier, 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.
    87. 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.
    88. Heaton, Chris, 2015. "Testing for multiple-period predictability between serially dependent time series," International Journal of Forecasting, Elsevier, vol. 31(3), pages 587-597.
    89. Ulrich Gunter, 2019. "Estimating and forecasting with a two-country DSGE model of the Euro area and the USA: the merits of diverging interest-rate rules," Empirical Economics, Springer, vol. 56(4), pages 1283-1323, April.
    90. 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.
    91. Dong Jin Lee & Jai Hyung Yoon, 2012. "The New Keynesian Phillips Curves in Multiple Quantiles and the Asymmetry of Monetary Policy," Working papers 2012-03, University of Connecticut, Department of Economics.
    92. 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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  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. 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.
    3. Valentina Corradi & Norman Swanson, 2004. "Predective Density and Conditional Confidence Interval Accuracy Tests," Departmental Working Papers 200423, Rutgers University, Department of Economics.
    4. Atsushi Inoue & Lutz Kilian, 2005. "In-Sample or Out-of-Sample Tests of Predictability: Which One Should We Use?," Econometric Reviews, Taylor & Francis Journals, vol. 23(4), pages 371-402.
    5. 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.
    6. Jorge Selaive & Vicente Tuesta, 2006. "Can fluctuations in the consumption-wealth ratio help to predict exchange rates?," Applied Financial Economics, Taylor & Francis Journals, vol. 16(17), pages 1251-1263.
    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. 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.
    2. Martin D. D. Evans(Georgetown University and NBER) and Richard K. Lyons(U.C. Berkeley and NBER, Haas School of Business), 2005. "Meese-Rogoff Redux: Micro-Based Exchange Rate Forecasting," Working Papers gueconwpa~05-05-01, Georgetown University, Department of Economics.
    3. 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.
    4. 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 1209, University of Nevada, Las Vegas , Department of Economics.
    5. 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.
    6. Marie Bessec & Othman Bouabdallah, 2005. "What causes the forecasting failure of Markov-Switching models? A Monte Carlo study," Econometrics 0503018, University Library of Munich, Germany.
    7. 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.
    8. Nelson C. Mark & Donggyu Sul, 2004. "The Use of Predictive Regressions at Alternative Horizons in Finance and Economics," NBER Technical Working Papers 0298, National Bureau of Economic Research, Inc.
    9. 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.
    10. 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.
    11. 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.
    12. Moser, Gabriel & Rumler, Fabio & Scharler, Johann, 2007. "Forecasting Austrian inflation," Economic Modelling, Elsevier, vol. 24(3), pages 470-480, May.
    13. O. De Bandt & E. Michaux & C. Bruneau & A. Flageollet, 2007. "Forecasting inflation using economic indicators: the case of France," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(1), pages 1-22.
    14. 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.
    15. 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.
    16. Orphanides, Athanasios & van Norden, Simon, 2005. "The Reliability of Inflation Forecasts Based on Output Gap Estimates in Real Time," CEPR Discussion Papers 4830, C.E.P.R. Discussion Papers.
    17. Barbara Rossi, 2007. "Expectations hypotheses tests at Long Horizons," Econometrics Journal, Royal Economic Society, vol. 10(3), pages 554-579, November.
    18. 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.
    19. Boucher, Christophe, 2006. "Stock prices-inflation puzzle and the predictability of stock market returns," Economics Letters, Elsevier, vol. 90(2), pages 205-212, February.
    20. McCracken, Michael W., 2007. "Asymptotics for out of sample tests of Granger causality," Journal of Econometrics, Elsevier, vol. 140(2), pages 719-752, October.
    21. 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.
    22. Mestre, Ricardo, 2007. "Are survey-based inflation expections in the euro area informative?," Working Paper Series 721, European Central Bank.

  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. 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.
    3. 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.
    4. 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.
    5. Pao, H.T., 2009. "Forecasting energy consumption in Taiwan using hybrid nonlinear models," Energy, Elsevier, vol. 34(10), pages 1438-1446.
    6. Rangel José Gonzalo, 2009. "Macroeconomic News, Announcements, and Stock Market Jump Intensity Dynamics," Working Papers 2009-15, Banco de México.
    7. Gupta, Rangan & Modise, Mampho P., 2013. "Macroeconomic Variables and South African Stock Return Predictability," Economic Modelling, Elsevier, vol. 30(C), pages 612-622.
    8. 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.
    9. Sune Karlsson & Pär Österholm, 2020. "A note on the stability of the Swedish Phillips curve," Empirical Economics, Springer, vol. 59(6), pages 2573-2612, December.
    10. Rafaï, Ismaël & Blayac, Thierry & Dubois, Dimitri & Duchêne, Sébastien & Nguyen-Van, Phu & Ventelou, Bruno & Willinger, Marc, 2023. "Stated preferences outperform elicited preferences for predicting reported compliance with COVID-19 prophylactic measures," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 107(C).
    11. Todd E. Clark & Michael W. McCracken, 2011. "Advances in forecast evaluation," Working Papers (Old Series) 1120, Federal Reserve Bank of Cleveland.
    12. Christian Glocker & Serguei Kaniovski, 2022. "Macroeconometric forecasting using a cluster of dynamic factor models," Empirical Economics, Springer, vol. 63(1), pages 43-91, July.
    13. 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.
    14. Todd E. Clark & Michael W. McCracken, 2001. "Evaluating long-horizon forecasts," Research Working Paper RWP 01-14, Federal Reserve Bank of Kansas City.
    15. Parigi, Giuseppe & Golinelli, Roberto, 2005. "Short-Run Italian GDP Forecasting and Real-Time Data," CEPR Discussion Papers 5302, C.E.P.R. Discussion Papers.
    16. 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.
    17. Carlos A. Medel, 2015. "Probabilidad Clásica de Sobreajuste con Criterios de Información: Estimaciones con Series Macroeconómicas Chilenas," Revista de Analisis Economico – Economic Analysis Review, Universidad Alberto Hurtado/School of Economics and Business, vol. 30(1), pages 57-72, Abril.
    18. 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.
    19. Pär Österholm, 2010. "Improving Unemployment Rate Forecasts Using Survey Data," Finnish Economic Papers, Finnish Economic Association, vol. 23(1), pages 16-26, Spring.
    20. 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.
    21. 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.
    22. 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.
    23. Javier Pereda, 2011. "Estimación de la tasa natural de interés para Perú: un enfoque financiero," Monetaria, CEMLA, vol. 0(4), pages 429-459, octubre-d.
    24. 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.
    25. Carlos A. Medel & Sergio C. Salgado, 2013. "Does the Bic Estimate and Forecast Better than the Aic?," Revista de Analisis Economico – Economic Analysis Review, Universidad Alberto Hurtado/School of Economics and Business, vol. 28(1), pages 47-64, April.
    26. Pincheira, Pablo & Selaive, Jorge & Nolazco, Jose Luis, 2017. "Forecasting Inflation in Latin America with Core Measures," MPRA Paper 80496, University Library of Munich, Germany.
    27. 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.
    28. Calhoun, Gray, 2014. "Out-Of-Sample Comparisons of Overfit Models," Staff General Research Papers Archive 32462, Iowa State University, Department of Economics.
    29. 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.
    30. 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.
    31. 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.
    32. Glocker, Christian & Kaniovski, Serguei, 2020. "Structural modeling and forecasting using a cluster of dynamic factor models," MPRA Paper 101874, University Library of Munich, Germany.
    33. 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.
    34. Gary J. Cornwall & Jeffrey A. Mills & Beau A. Sauley & Huibin Weng, 2019. "Predictive Testing for Granger Causality via Posterior Simulation and Cross-validation," Advances in Econometrics, in: Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling: Part A, volume 40, pages 275-292, Emerald Group Publishing Limited.
    35. 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.
    36. Michael Graff, 2005. "Ein multisektoraler Sammelindikator fuer die Schweizer Konjunktur," KOF Working papers 05-107, KOF Swiss Economic Institute, ETH Zurich.
    37. 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.
    38. 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.
    39. Makin, Anthony J. & Ratnasiri, Shyama, 2015. "Competitiveness and government expenditure: The Australian example," Economic Modelling, Elsevier, vol. 49(C), pages 154-161.
    40. 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.
    41. 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.
    42. McCracken, Michael W., 2007. "Asymptotics for out of sample tests of Granger causality," Journal of Econometrics, Elsevier, vol. 140(2), pages 719-752, October.
    43. 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.
    44. 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.
    45. 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.
    46. 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.
    47. 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.
    48. 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.
    49. 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.
    50. 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.
    51. 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. 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.
    3. 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.
    4. Freire, Gustavo, 2021. "Tail risk and investors’ concerns: Evidence from Brazil," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    5. Yin, Anwen, 2015. "Forecasting and model averaging with structural breaks," ISU General Staff Papers 201501010800005727, Iowa State University, Department of Economics.
    6. 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.
    7. Granziera, Eleonora & Sekhposyan, Tatevik, 2019. "Predicting relative forecasting performance: An empirical investigation," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1636-1657.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. Rossi, Barbara & Odendahl, Florens & Sekhposyan, Tatevik, 2020. "Comparing Forecast Performance with State Dependence," CEPR Discussion Papers 15217, C.E.P.R. Discussion Papers.
    13. Caroline Jardet & Baptiste Meunier, 2022. "Nowcasting world GDP growth with high‐frequency data," Post-Print hal-03647097, HAL.
    14. 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).
    15. 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.
    16. Stock, James & Watson, Mark & Marcellino, Massimiliano, 2005. "A Comparison of Direct and Iterated Multistep AR Methods for Forecasting Macroeconomic Time Series," CEPR Discussion Papers 4976, C.E.P.R. Discussion Papers.
    17. 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.
    18. 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.
    19. Chen, Shiu-Sheng & Chou, Yu-Hsi, 2023. "Liquidity yield and exchange rate predictability," Journal of International Money and Finance, Elsevier, vol. 137(C).
    20. 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.
    21. 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.
    22. Pablo Pincheira Brown & Nicolás Hardy, 2024. "Correlation‐based tests of predictability," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 1835-1858, September.
    23. 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.
    24. 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.
    25. 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.
    26. 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.
    27. Inoue, Atsushi & Kilian, Lutz, 2003. "On the selection of forecasting models," Working Paper Series 214, European Central Bank.
    28. Florens Odendahl & Tatevik Sekhposyan & Barbara Rossi, 2021. "Evaluating Forecast Performance with State Dependence," Working Papers 1295, Barcelona School of Economics.
    29. 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.
    30. Asmara Jamaleh, 2002. "Explaining and forecasting the euro/dollar exchange rate through a non-linear threshold model," The European Journal of Finance, Taylor & Francis Journals, vol. 8(4), pages 422-448.
    31. Jung, Alexander & Carcel Villanova, Hector, 2020. "The empirical properties of euro area M3, 1980-2017," The Quarterly Review of Economics and Finance, Elsevier, vol. 77(C), pages 37-49.
    32. Michael P. Clements & David I. Harvey, 2010. "Forecast encompassing tests and probability forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(6), pages 1028-1062.
    33. Yin, Libo & Nie, Jing, 2021. "Adjusted dividend-price ratios and stock return predictability: Evidence from China," International Review of Financial Analysis, Elsevier, vol. 73(C).
    34. Saša ŽIKOVIÆ & Randall K. FILER, 2013. "Ranking of VaR and ES Models: Performance in Developed and Emerging Markets," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(4), pages 327-359, August.
    35. 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.
    36. Chia-Lin Chang & Philip Hans Franses & Michael McAleer, 2010. "Are Forecast Updates Progressive?," Working Papers in Economics 10/12, University of Canterbury, Department of Economics and Finance.
    37. Hofmann, Boris, 2009. "Do monetary indicators lead euro area inflation?," Journal of International Money and Finance, Elsevier, vol. 28(7), pages 1165-1181, November.
    38. 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.
    39. 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.
    40. Kung, Ko-Lun & MacMinn, Richard D. & Kuo, Weiyu & Tsai, Chenghsien Jason, 2022. "Multi-population mortality modeling: When the data is too much and not enough," Insurance: Mathematics and Economics, Elsevier, vol. 103(C), pages 41-55.
    41. Eric Ghysels & Casidhe Horan & Emanuel Moench, 2018. "Forecasting through the Rearview Mirror: Data Revisions and Bond Return Predictability," The Review of Financial Studies, Society for Financial Studies, vol. 31(2), pages 678-714.
    42. Mototsugu Shintani, 2003. "Nonlinear Forecasting Analysis Using Diffusion Indexes: An Application to Japan," Vanderbilt University Department of Economics Working Papers 0322, Vanderbilt University Department of Economics, revised Apr 2004.
    43. 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.
    44. Ding, Yishan, 2018. "A novel decompose-ensemble methodology with AIC-ANN approach for crude oil forecasting," Energy, Elsevier, vol. 154(C), pages 328-336.
    45. Valentina Corradi & Norman Swanson, 2013. "A Survey of Recent Advances in Forecast Accuracy Comparison Testing, with an Extension to Stochastic Dominance," Departmental Working Papers 201309, Rutgers University, Department of Economics.
    46. Møller, Stig V. & Rangvid, Jesper, 2015. "End-of-the-year economic growth and time-varying expected returns," Journal of Financial Economics, Elsevier, vol. 115(1), pages 136-154.
    47. Kenneth Rogoff & Barbara Rossi & Yu-chin Chen, 2008. "Can Exchange Rates Forecast Commodity Prices?," 2008 Meeting Papers 540, Society for Economic Dynamics.
    48. Zhanglong Wang & Kent Wang & Zheyao Pan, 2015. "Conditional equity risk premia and realized variance jump risk," Australian Journal of Management, Australian School of Business, vol. 40(2), pages 295-317, May.
    49. Wang, Zijun, 2021. "The high volume return premium and economic fundamentals," Journal of Financial Economics, Elsevier, vol. 140(1), pages 325-345.
    50. 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.
    51. Libo Yin & Jing Nie, 2021. "Intermediary asset pricing in currency carry trade returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(8), pages 1241-1267, August.
    52. Barbara Rossi, 2013. "Exchange rate predictability," Economics Working Papers 1369, Department of Economics and Business, Universitat Pompeu Fabra.
    53. 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.
    54. Barbara Rossi, 2005. "Are Exchange Rates Really Random Walks? Some Evidence Robust to Parameter Instability," International Finance 0503006, University Library of Munich, Germany.
    55. Bryan Kelly & Hao Jiang, 2013. "Tail Risk and Asset Prices," NBER Working Papers 19375, National Bureau of Economic Research, Inc.
    56. 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.
    57. Phan, Dinh Hoang Bach & Sharma, Susan Sunila & Narayan, Paresh Kumar, 2016. "Intraday volatility interaction between the crude oil and equity markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 40(C), pages 1-13.
    58. 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.
    59. Pincheira, Pablo & Hardy, Nicolás, 2019. "Forecasting Aluminum Prices with Commodity Currencies," MPRA Paper 97005, University Library of Munich, Germany.
    60. Yu-chin Chen & Stephen J. Turnovsky & Eric Zivot, 2011. "Forecasting Inflation using Commodity Price Aggregates," Working Papers UWEC-2011-14, University of Washington, Department of Economics.
    61. Kholodilin Konstantin Arkadievich & Siliverstovs Boriss, 2006. "On the Forecasting Properties of the Alternative Leading Indicators for the German GDP: Recent Evidence," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 226(3), pages 234-259, June.
    62. Imene Mootamri & Mohamed Boutahar & Anne Peguin-Feissolle, 2008. "A fractionally integrated exponential STAR model applied to the US real effective exchange rate," Post-Print halshs-00390134, HAL.
    63. Bertrand Candelon & Elena Ivona Dumitrescu & Christophe Hurlin, 2012. "How to Evaluate an Early Warning System? Towards a Unified Statistical Framework for Assessing Financial Crises Forecasting Methods," Post-Print hal-01385900, HAL.
    64. Galbraith, John W. & KI[#x1e63]Inbay, Turgut, 2005. "Content horizons for conditional variance forecasts," International Journal of Forecasting, Elsevier, vol. 21(2), pages 249-260.
    65. Marie Bessec & Julien Fouquau, 2018. "Short-run electricity load forecasting with combinations of stationary wavelet transforms," Post-Print hal-01644930, HAL.
    66. Kevin L. Kliesen, 2007. "How well does employment predict output?," Review, Federal Reserve Bank of St. Louis, vol. 89(Sep), pages 433-446.
    67. Souza, Thiago de Oliveira, 2020. "Dollar carry timing," Discussion Papers on Economics 10/2020, University of Southern Denmark, Department of Economics.
    68. Franses, Ph.H.B.F., 2009. "Forecasting Sales," Econometric Institute Research Papers EI 2009-29, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    69. Pincheira, Pablo, 2017. "A Power Booster Factor for Out-of-Sample Tests of Predictability," MPRA Paper 77027, University Library of Munich, Germany.
    70. Guglielmo Caporale & Luis Gil-Alana, 2016. "Persistence and cyclical dependence in the monthly euribor rate," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 40(1), pages 157-171, January.
    71. Christophe Boucher & Bertrand Maillet, 2011. "Une analyse temps-fréquences des cycles financiers," Post-Print halshs-00565229, HAL.
    72. 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.
    73. Chava, Sudheer & Gallmeyer, Michael & Park, Heungju, 2015. "Credit conditions and stock return predictability," Journal of Monetary Economics, Elsevier, vol. 74(C), pages 117-132.
    74. Ming-Chih Lee & Chien-Liang Chiu & Wan-Hsiu Cheng, 2007. "Enhancing Forecast Accuracy By Using Long Estimation Periods," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 1(2), pages 1-9.
    75. Robledo, Carlos W. & Zapata, Hector O. & McCracken, Michael, 2001. "New Mse Tests For Evaluating Forecasting Performance: Empirics And Bootstrap," 2001 Annual meeting, August 5-8, Chicago, IL 20686, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    76. Philip Hans Franses & Michael McAleer & Rianne Legerstee, 2010. "Evaluating Macroeconomic Forecasts: A Review of Some Recent Developments," CIRJE F-Series CIRJE-F-729, CIRJE, Faculty of Economics, University of Tokyo.
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    4. Georgiadis, Georgios, 2016. "Determinants of global spillovers from US monetary policy," Journal of International Money and Finance, Elsevier, vol. 67(C), pages 41-61.
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    5. 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.
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    22. Yuriy Gorodnichenko, 2005. "Reduced-Rank Identification of Structural Shocks in VARs," Macroeconomics 0512011, University Library of Munich, Germany.
    23. 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.
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    25. Svaleryd, Helena & Vlachos, Jonas, 1999. "Markets for Risk and Openness to Trade: How are they Related?," SSE/EFI Working Paper Series in Economics and Finance 327, Stockholm School of Economics, revised 28 Aug 2001.
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    27. 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.
    28. 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-.
    29. 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.
    30. Economidou, Claire & Kool, Clemens, 2009. "European economic integration and (a)symmetry of macroeconomic fluctuations," Economic Modelling, Elsevier, vol. 26(4), pages 778-787, July.
    31. António Afonso & Davide Furceri, 2007. "Sectoral Business Cycle Synchronization in the European Union," Working Papers Department of Economics 2007/02, ISEG - Lisbon School of Economics and Management, Department of Economics, Universidade de Lisboa.
    32. D. Furceri & G. Karras, 2008. "Business-cycle synchronization in the EMU," Applied Economics, Taylor & Francis Journals, vol. 40(12), pages 1491-1501.
    33. Marianne Baxter & Michael A. Kouparitsas, 2004. "Determinants of Business Cycle Comovement: A Robust Analysis," NBER Working Papers 10725, National Bureau of Economic Research, Inc.
    34. Guerron-Quintana, Pablo A., 2013. "Common and idiosyncratic disturbances in developed small open economies," Journal of International Economics, Elsevier, vol. 90(1), pages 33-49.
    35. 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.
    36. Beate Schirwitz & Christian Seiler & Klaus Wohlrabe, 2009. "Regionale Konjunkturzyklen in Deutschland – Teil III: Konvergenz," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 62(15), pages 23-32, August.
    37. 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).
    38. 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.
    39. Thomas Walker & David Norman, 2004. "Co-movement of Australian State Business Cycles," Econometric Society 2004 Australasian Meetings 334, Econometric Society.
    40. Svaleryd, Helena & Vlachos, Jonas, 2000. "Does Financial Development Lead to Trade Liberalization?," Research Papers in Economics 2000:11, Stockholm University, Department of Economics.
    41. 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.
    42. 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.
    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. 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.
    3. 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.
    4. Kenneth D. West & Michael W. McCracken, 1998. "Regression-Based Tests of Predictive Ability," NBER Technical Working Papers 0226, National Bureau of Economic Research, Inc.
    5. Martin Lettau & Sydney Ludvigson, 2001. "Consumption, Aggregate Wealth, and Expected Stock Returns," Journal of Finance, American Finance Association, vol. 56(3), pages 815-849, June.
    6. Hendry, David F. & Hubrich, Kirstin, 2006. "Forecasting economic aggregates by disaggregates," Working Paper Series 589, European Central Bank.

  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. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.).
    7. Julio J. Rotemberg & Michael Woodford, 1999. "The Cyclical Behavior of Prices and Costs," NBER Working Papers 6909, National Bureau of Economic Research, Inc.
    8. 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.
    9. 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.
    10. 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.
    11. 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).
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. Shantanu Dutta & Mark Bergen & Daniel Levy, 2004. "Price Flexibility in Channels of Distribution: Evidence from Scanner Data," Macroeconomics 0402018, University Library of Munich, Germany.
    19. 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.
    20. Jian Wang, 2007. "Home bias, exchange rate disconnect, and optimal exchange rate policy," Working Papers 0701, Federal Reserve Bank of Dallas.
    21. Louis Phaneuf & Nooman Rebei, 2008. "Production Stages and the Transmission of Technological Progress," Cahiers de recherche 0802, CIRPEE.
    22. 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.
    23. 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.
    24. Diego Winkelried, 2014. "Exchange rate pass-through and inflation targeting in Peru," Empirical Economics, Springer, vol. 46(4), pages 1181-1196, June.
    25. 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.
    26. Erwan Gautier, 2008. "The behaviour of producer prices: evidence from French PPI micro data," Empirical Economics, Springer, vol. 35(2), pages 301-332, September.
    27. Nasir Hamid Rao & Syed Kalim Hyder Bukhari, 2011. "Asymmetric Shocks and Co-movement of Price Indices," SBP Working Paper Series 38, State Bank of Pakistan, Research Department.
    28. 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.
    29. Lian An & Jian Wang, 2011. "Exchange rate pass-through: evidence based on vector autoregression with sign restrictions," Globalization Institute Working Papers 70, Federal Reserve Bank of Dallas.
    30. 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.
    31. 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.
    32. 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.
    33. Billmeier, Andreas & Bonato, Leo, 2004. "Exchange rate pass-through and monetary policy in Croatia," Journal of Comparative Economics, Elsevier, vol. 32(3), pages 426-444, September.
    34. Besnik Fetai, 2011. "Exchange Rate Pass-Through in Transition Economies: The Case of the Republic of Macedonia," William Davidson Institute Working Papers Series wp1014, William Davidson Institute at the University of Michigan.
    35. Gong, Liutang & Wang, Chan & Zou, Heng-fu, 2016. "Optimal monetary policy with international trade in intermediate inputs," Journal of International Money and Finance, Elsevier, vol. 65(C), pages 140-165.
    36. Singh, Aarti & Tornielli di Crestvolant, Stefano, 2018. "Transmission of monetary policy shocks: do input-output interactions matter?," Working Papers 2018-12, University of Sydney, School of Economics.
    37. 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.
    38. 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.
    39. 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.
    40. 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.
    41. 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.
    42. 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.
    43. 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.
    44. 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.
    45. 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.
    46. 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.
    47. 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.
    48. 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.
    49. 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).
    50. 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.
    51. 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.
    52. Schenkelberg, Heike, 2011. "Why are Prices Sticky? Evidence from Business Survey Data," Discussion Papers in Economics 12158, University of Munich, Department of Economics.
    53. 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.
    54. Gu, Gyun Cheol, 2012. "Denial, Rationalization, and the Administered Price Thesis," MPRA Paper 42594, University Library of Munich, Germany.
    55. Heng-fu Zou, 2023. "Recent Studies on Macro Dynamics and Finance," CEMA Working Papers 632, China Economics and Management Academy, Central University of Finance and Economics.
    56. 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.
    57. 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.
    58. 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.
    59. 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. 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.
    3. 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.
    4. Myck, Michal & Ochmann, Richard & Qari, Salmai, 2008. "Dynamics of Earnings and Hourly Wages in Germany," IZA Discussion Papers 3751, Institute of Labor Economics (IZA).
    5. Jason Allen & Allan Gregory & Katsumi Shimotsu, 2008. "Empirical Likelihood Block Bootstrapping," Staff Working Papers 08-18, Bank of Canada.
    6. 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.
    7. 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).
    8. 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).
    9. 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.
    10. 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.
    11. Vanesa Jorda & José María Sarabia & Markus Jäntti, 2020. "Estimation of Income Inequality from Grouped Data," LIS Working papers 804, LIS Cross-National Data Center in Luxembourg.
    12. 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.
    13. Yuriy Gorodnichenko, 2007. "Using Firm Optimization to Evaluate and Estimate Returns to Scale," NBER Working Papers 13666, National Bureau of Economic Research, Inc.
    14. Toda, Alexis Akira & Walsh, Kieran James, 2016. "Fat Tails and Spurious Estimation of Consumption-Based Asset Pricing Models," MPRA Paper 78980, University Library of Munich, Germany.
    15. Christian Bredemeier & Jan Gravert & Falko Juessen, 2019. "Estimating Labor Supply Elasticities with Joint Borrowing Constraints of Couples," Journal of Labor Economics, University of Chicago Press, vol. 37(4), pages 1215-1265.
    16. Yuriy Gorodnichenko, 2005. "Reduced-Rank Identification of Structural Shocks in VARs," Macroeconomics 0512011, University Library of Munich, Germany.
    17. Bhashkar Mazumder, 2001. "The mis-measurement of permanent earnings: new evidence from Social Security earnings data," Working Paper Series WP-01-24, Federal Reserve Bank of Chicago.
    18. 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.
    19. 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.
    20. Yasutomo Murasawa, 2009. "Do coincident indicators have one-factor structure?," Empirical Economics, Springer, vol. 36(2), pages 339-365, May.
    21. 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.
    22. Gustavsson, Magnus, 2002. "Earnings Dynamics and Inequality during Macroeconomic Turbulence: Sweden 1991-1999," Working Paper Series 2002:20, Uppsala University, Department of Economics.
    23. 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.
    24. Kezdi, Gabor & Hahn, Jinyong & Solon, Gary, 2002. "Jackknife minimum distance estimation," Economics Letters, Elsevier, vol. 76(1), pages 35-45, June.
    25. 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.
    26. 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.
    27. 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).
    28. 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.
    29. Magnus Gustavsson, 2007. "The 1990s rise in Swedish earnings inequality -- persistent or transitory?," Applied Economics, Taylor & Francis Journals, vol. 39(1), pages 25-30.
    30. 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.
    31. 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.
    32. Prokhorov, Artem, 2012. "Second order bias of quasi-MLE for covariance structure models," Economics Letters, Elsevier, vol. 114(2), pages 195-197.
    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. 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.
    3. 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.
    4. 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.
    5. 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.).
    6. 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.
    7. 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).
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. Orphanides, Athanasios & Wieland, Volker, 2000. "Inflation zone targeting," European Economic Review, Elsevier, vol. 44(7), pages 1351-1387, June.
    15. Muhammad Farooq Arby & Amjad Ali, 2017. "Threshold Inflation in Pakistan," SBP Research Bulletin, State Bank of Pakistan, Research Department, vol. 13, pages 1-19.
    16. 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.
    17. 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.
    18. Coenen Günter & Orphanides Athanasios & Wieland Volker, 2004. "Price Stability and Monetary Policy Effectiveness when Nominal Interest Rates are Bounded at Zero," The B.E. Journal of Macroeconomics, De Gruyter, vol. 4(1), pages 1-25, February.
    19. Georgios Bitros & Epaminondas Panas, 2005. "Another look at the inflation-productivity trade-off," Macroeconomics 0506001, University Library of Munich, Germany.
    20. Manoel Bittencourt, 2008. "Inflation and Financial Development: Evidence from Brazil," Working Papers 067, Economic Research Southern Africa.
    21. 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.
    22. 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.
    23. 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).
    24. 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.
    25. 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.
    26. 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.
    27. 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.
    28. 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.
    29. 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.
    30. 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.
    31. 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.
    32. 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.
    33. George Bitros & Epaminondas Panas, 2006. "The inflation-productivity trade-off revisited," Journal of Productivity Analysis, Springer, vol. 26(1), pages 51-65, August.
    34. 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.).
    35. 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.
    36. 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.
    37. Ramaprasad Bhar, 2010. "Stochastic Filtering with Applications in Finance," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 7736, September.
    38. 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.
    39. 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.
    40. Bittencourt, Manoel, 2012. "Inflation and economic growth in Latin America: Some panel time-series evidence," Economic Modelling, Elsevier, vol. 29(2), pages 333-340.
    41. 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.
    42. 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.
    43. 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.
    44. 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.
    45. 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.
    46. Metiu, Norbert & Prieto, Esteban, 2023. "The macroeconomic effects of inflation uncertainty," Discussion Papers 32/2023, Deutsche Bundesbank.
    47. Emara, Noha, 2012. "Inflation volatility, financial institutions and sovereign debt rating," MPRA Paper 68688, University Library of Munich, Germany.

  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. 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.
    2. 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.
    3. Cribari-Neto, Francisco, 1996. "On time series econometrics," The Quarterly Review of Economics and Finance, Elsevier, vol. 36(Supplemen), pages 37-60.
    4. 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.
    5. 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.
    6. 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.

Articles

  1. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2025. "Specification Choices in Quantile Regression for Empirical Macroeconomics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 40(1), pages 57-73, January.
    See citations under working paper version above.
  2. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2024. "Capturing Macro‐Economic Tail Risks with Bayesian Vector Autoregressions," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 56(5), pages 1099-1127, August.
    See citations under working paper version above.
  3. Todd E. Clark & Florian Huber & Gary Koop & Massimiliano Marcellino & Michael Pfarrhofer, 2024. "Investigating Growth-at-Risk Using a Multicountry Nonparametric Quantile Factor Model," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(4), pages 1302-1317, October.
    See citations under working paper version above.
  4. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2024. "Addressing COVID-19 Outliers in BVARs with Stochastic Volatility," The Review of Economics and Statistics, MIT Press, vol. 106(5), pages 1403-1417, September.
    See citations under working paper version above.
  5. 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. Mirjana Miletic, Danilo Cerovic and Aleksandar Tomin & Mirjana Miletic & Danilo Cerovic & Aleksandar Tomin, 2023. "Impact of global supply disruptions and energy prices on inflation in European countries," Working Papers Bulletin 19, National Bank of Serbia.
    4. Jan Schulz & Kerstin Hötte & Daniel M. Mayerhoffer, 2024. "Pluralist economics in an era of polycrisis," Review of Evolutionary Political Economy, Springer, vol. 5(2), pages 201-218, September.
    5. Diaz, Elena Maria & Cunado, Juncal & de Gracia, Fernando Perez, 2024. "Global drivers of inflation: The role of supply chain disruptions and commodity price shocks," Economic Modelling, Elsevier, vol. 140(C).
    6. 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.
    7. Mrabet, Zouhair & Alsamara, Mouyad & Mimouni, Karim & Awwad, Abdulkareem, 2025. "Do supply chain pressures affect consumer prices in major economies? New evidence from time-varying causality analysis," Economic Modelling, Elsevier, vol. 142(C).

  6. 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.
  7. 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.
  8. 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.
  9. 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.
  10. 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.
  11. 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.
  12. 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.
  13. 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. Bańbura, Marta & Leiva-Leon, Danilo & Menz, Jan-Oliver, 2021. "Do inflation expectations improve model-based inflation forecasts?," Working Paper Series 2604, European Central Bank.
    3. Leonardo Nogueira Ferreira & Silvia Miranda-Agrippino & Giovanni Ricco, 2023. "Bayesian Local Projections," Working Papers Series 581, Central Bank of Brazil, Research Department.
    4. Joshua C. C. Chan & Xuewen Yu, 2022. "Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility," Papers 2206.08438, arXiv.org.
    5. 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.
    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. 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.
    8. 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.
    9. Cross, Jamie L. & Hou, Chenghan & Koop, Gary & Poon, Aubrey, 2023. "Large stochastic volatility in mean VARs," Journal of Econometrics, Elsevier, vol. 236(1).
    10. Tsionas, Mike G. & Izzeldin, Marwan & Trapani, Lorenzo, 2022. "Estimation of large dimensional time varying VARs using copulas," European Economic Review, Elsevier, vol. 141(C).
    11. 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.
    12. 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.
    13. 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).
    14. 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.
    15. Frank C. Z. Wu, 2024. "Bayesian collapsed Gibbs sampling for a stochastic volatility model with a Dirichlet process mixture," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(4), pages 697-704, June.
    16. Dimitris Korobilis & Kenichi Shimizu, 2021. "Bayesian Approaches to Shrinkage and Sparse Estimation," Working Papers 2021_19, Business School - Economics, University of Glasgow.
    17. 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.
    18. Joshua C. C. Chan, 2022. "Comparing Stochastic Volatility Specifications for Large Bayesian VARs," Papers 2208.13255, arXiv.org.
    19. 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.
    20. Niko Hauzenberger, 2020. "Flexible Mixture Priors for Large Time-varying Parameter Models," Papers 2006.10088, arXiv.org, revised Nov 2020.
    21. 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.
    22. Florian, Huber & Koop, Gary & Onorante, Luca & Pfarrhofer, Michael & Schreiner, Josef, 2021. "Nowcasting in a Pandemic using Non-Parametric Mixed Frequency VARs," JRC Working Papers in Economics and Finance 2021-01, Joint Research Centre, European Commission.
    23. Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano, 2022. "Capturing Macroeconomic Tail Risks with Bayesian Vector Autoregressions," CEPR Discussion Papers 17512, C.E.P.R. Discussion Papers.
    24. 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.
    25. Ha, Jongrim & Kose, M. Ayhan & Ohnsorge, Franziska, 2022. "Global Stagflation," CEPR Discussion Papers 17381, C.E.P.R. Discussion Papers.
    26. Ramis Khabibullin & Sergei Seleznev, 2022. "Fast Estimation of Bayesian State Space Models Using Amortized Simulation-Based Inference," Papers 2210.07154, arXiv.org.
    27. 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.
    28. Florian Huber & Gary Koop, 2023. "Fast and Order-invariant Inference in Bayesian VARs with Non-Parametric Shocks," Papers 2305.16827, arXiv.org.
    29. Bai, Yu & Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano, 2022. "Macroeconomic Forecasting in a Multi-country Context," CEPR Discussion Papers 16994, C.E.P.R. Discussion Papers.
    30. 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.
    31. 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.
    32. Arias, Jonas E. & Rubio-Ramírez, Juan F. & Shin, Minchul, 2023. "Macroeconomic forecasting and variable ordering in multivariate stochastic volatility models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1054-1086.
    33. 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.
    34. 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.
    35. 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.
    36. Ikhlaas Gurrib & Firuz Kamalov & Osama Atayah & Dalia Hemdan & Olga Starkova, 2024. "Long-Run Trade Relationship between the U.S. and Canada: The Case of the Canadian Dollar with the U.S. Dollar," JRFM, MDPI, vol. 17(9), pages 1-21, September.
    37. Knotek, Edward S. & Zaman, Saeed, 2023. "Real-time density nowcasts of US inflation: A model combination approach," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1736-1760.
    38. 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).
    39. Chen, Zhengyang & Valcarcel, Victor J., 2021. "Monetary transmission in money markets: The not-so-elusive missing piece of the puzzle," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 131, pages 1-16.
    40. Zhang, Wen, 2022. "China’s government spending and global inflation dynamics: The role of the oil price channel," Energy Economics, Elsevier, vol. 110(C).
    41. Clark, Todd & Huber, Florian & Koop, Gary & Marcellino, Massimiliano & Pfarrhofer, Michael, 2022. "Tail Forecasting with Multivariate Bayesian Additive Regression Trees," CEPR Discussion Papers 17461, C.E.P.R. Discussion Papers.
    42. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2024. "Addressing COVID-19 Outliers in BVARs with Stochastic Volatility," The Review of Economics and Statistics, MIT Press, vol. 106(5), pages 1403-1417, September.
    43. 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.
    44. Gregor Kastner & Florian Huber, 2020. "Sparse Bayesian vector autoregressions in huge dimensions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1142-1165, November.
    45. Tomasz Wo'zniak, 2024. "Fast and Efficient Bayesian Analysis of Structural Vector Autoregressions Using the R Package bsvars," Papers 2410.15090, arXiv.org.
    46. Dimitris Korobilis, 2020. "Sign restrictions in high-dimensional vector autoregressions," Working Paper series 20-09, Rimini Centre for Economic Analysis.
    47. 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.
    48. Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano & Mertens, Elmar, 2023. "Shadow-rate VARs," Discussion Papers 14/2023, Deutsche Bundesbank.
    49. Wu, Ping & Koop, Gary, 2023. "Estimating the ordering of variables in a VAR using a Plackett–Luce prior," Economics Letters, Elsevier, vol. 230(C).
    50. Botelho, Vasco & Foroni, Claudia & Renzetti, Andrea, 2023. "Labour at risk," Working Paper Series 2840, European Central Bank.
    51. 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.
    52. Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
    53. Andrea Carriero & Davide Pettenuzzo & Shubhranshu Shekhar, 2024. "Macroeconomic Forecasting with Large Language Models," Papers 2407.00890, arXiv.org, revised Jan 2025.
    54. 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.
    55. Panovska, Irina & Zhang, Licheng, 2024. "Jobless recoveries and time variation in labor markets," Journal of Macroeconomics, Elsevier, vol. 81(C).
    56. Dimitris Korobilis, 2022. "A new algorithm for structural restrictions in Bayesian vector autoregressions," Papers 2206.06892, arXiv.org.
    57. 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.
    58. Joshua C. C. Chan, 2019. "Minnesota-type adaptive hierarchical priors for large Bayesian VARs," CAMA Working Papers 2019-61, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    59. Li, Chenxing & Maheu, John M & Yang, Qiao, 2022. "An Infinite Hidden Markov Model with Stochastic Volatility," MPRA Paper 115456, University Library of Munich, Germany.
    60. Ankargren, Sebastian & Jonéus, Paulina, 2021. "Simulation smoothing for nowcasting with large mixed-frequency VARs," Econometrics and Statistics, Elsevier, vol. 19(C), pages 97-113.
    61. Kumar, Utkarsh & Ahmad, Wasim, 2024. "Navigating the “twin titans” of global manufacturing: The impact of US and China on industrial production forecasting in G20 nations," Pacific-Basin Finance Journal, Elsevier, vol. 87(C).
    62. Lukas Berend & Jan Pruser, 2024. "The Transmission of Monetary Policy via Common Cycles in the Euro Area," Papers 2410.05741, arXiv.org, revised Nov 2024.
    63. Martin Feldkircher & Luis Gruber & Florian Huber & Gregor Kastner, 2024. "Sophisticated and small versus simple and sizeable: When does it pay off to introduce drifting coefficients in Bayesian vector autoregressions?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 2126-2145, September.
    64. 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).
    65. 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).
    66. Martin, Gael M. & Frazier, David T. & Maneesoonthorn, Worapree & Loaiza-Maya, Rubén & Huber, Florian & Koop, Gary & Maheu, John & Nibbering, Didier & Panagiotelis, Anastasios, 2024. "Bayesian forecasting in economics and finance: A modern review," International Journal of Forecasting, Elsevier, vol. 40(2), pages 811-839.
    67. Saeed Zaman, 2021. "A Unified Framework to Estimate Macroeconomic Stars," Working Papers 21-23R2, Federal Reserve Bank of Cleveland, revised 31 May 2024.
    68. Mike Tsionas & Marwan Izzeldin & Lorenzo Trapani, 2019. "Bayesian estimation of large dimensional time varying VARs using copulas," Papers 1912.12527, arXiv.org.
    69. 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.
    70. Matteo Mogliani & Anna Simoni, 2024. "Bayesian Bi-level Sparse Group Regressions for Macroeconomic Density Forecasting," Papers 2404.02671, arXiv.org, revised Nov 2024.
    71. Botelho, Vasco & Foroni, Claudia & Renzetti, Andrea, 2024. "Labour at risk," European Economic Review, Elsevier, vol. 170(C).
    72. 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.
    73. 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.
    74. 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.
    75. 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.
    76. 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).
    77. 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.
    78. 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.
    79. Joshua C. C. Chan, 2022. "Asymmetric conjugate priors for large Bayesian VARs," Quantitative Economics, Econometric Society, vol. 13(3), pages 1145-1169, July.
    80. 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).
    81. Sokol, Andrej, 2021. "Fan charts 2.0: flexible forecast distributions with expert judgement," Working Paper Series 2624, European Central Bank.
    82. Florian Huber & Gary Koop & Massimiliano Marcellino & Tobias Scheckel, 2024. "Bayesian modelling of VAR precision matrices using stochastic block networks," Papers 2407.16349, arXiv.org.
    83. Florian Huber & Massimiliano Marcellino, 2023. "Coarsened Bayesian VARs -- Correcting BVARs for Incorrect Specification," Papers 2304.07856, arXiv.org, revised May 2023.
    84. Rub'en Loaiza-Maya & Didier Nibbering, 2022. "Efficient variational approximations for state space models," Papers 2210.11010, arXiv.org, revised Jun 2023.
    85. Florian Huber & Luca Rossini, 2020. "Inference in Bayesian Additive Vector Autoregressive Tree Models," Papers 2006.16333, arXiv.org, revised Mar 2021.
    86. 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.
    87. Wen Zhang, 2024. "The evolving international effects of China's government spending," The World Economy, Wiley Blackwell, vol. 47(5), pages 1851-1869, May.
    88. 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.
    89. 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).
    90. 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.
    91. 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).
    92. 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.
    93. 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.
    94. Luis Gruber & Gregor Kastner, 2022. "Forecasting macroeconomic data with Bayesian VARs: Sparse or dense? It depends!," Papers 2206.04902, arXiv.org, revised Feb 2025.
    95. Zhang, Bo & Nguyen, Bao H. & Sun, Chuanwang, 2024. "Forecasting oil prices: Can large BVARs help?," Energy Economics, Elsevier, vol. 137(C).
    96. 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.
    97. 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.
    98. 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.
    99. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2021. "Forecasting with Shadow-Rate VARs," Working Papers 21-09, Federal Reserve Bank of Cleveland.
    100. Michael Pfarrhofer & Anna Stelzer, 2019. "High-frequency and heteroskedasticity identification in multicountry models: Revisiting spillovers of monetary shocks," Papers 1912.03158, arXiv.org, revised Dec 2024.
    101. 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.
    102. Sebastian Ankargren & Paulina Jon'eus, 2019. "Estimating Large Mixed-Frequency Bayesian VAR Models," Papers 1912.02231, arXiv.org.
    103. 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.
    104. Yousuf, Kashif & Ng, Serena, 2021. "Boosting high dimensional predictive regressions with time varying parameters," Journal of Econometrics, Elsevier, vol. 224(1), pages 60-87.
    105. 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.
    106. 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.
    107. 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.
    108. 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.
    109. 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.
    110. Klieber, Karin, 2024. "Non-linear dimension reduction in factor-augmented vector autoregressions," Journal of Economic Dynamics and Control, Elsevier, vol. 159(C).
    111. 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.
    112. Florian Eckert & Nina Mühlebach, 2023. "Global and local components of output gaps," Empirical Economics, Springer, vol. 65(5), pages 2301-2331, November.

  14. 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.
  15. 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.
  16. 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. Kontogeorgos, Georgios & Lambrias, Kyriacos, 2019. "An analysis of the Eurosystem/ECB projections," Working Paper Series 2291, European Central Bank.
    4. 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.
    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.

  17. 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.
  18. 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.
  19. 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.
  20. 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. Huber, Florian, 2016. "Density forecasting using Bayesian global vector autoregressions with stochastic volatility," International Journal of Forecasting, Elsevier, vol. 32(3), pages 818-837.
    4. 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.
    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. 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.
    7. 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).
    8. Gary Koop & Dimitris Korobilis, 2018. "Forecasting with High-Dimensional Panel VARs," Working Paper series 18-20, Rimini Centre for Economic Analysis.
    9. Davide Pettenuzzo & Francesco Ravazzolo, 2014. "Optimal portfolio choice under decision-based model combinations," Working Paper 2014/15, Norges Bank.
    10. Joshua C. C. Chan, 2024. "BVARs and stochastic volatility," Chapters, in: Michael P. Clements & Ana Beatriz Galvão (ed.), Handbook of Research Methods and Applications in Macroeconomic Forecasting, chapter 3, pages 43-67, Edward Elgar Publishing.
    11. 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.
    12. Korobilis, Dimitris & Koop, Gary, 2020. "Bayesian dynamic variable selection in high dimensions," MPRA Paper 100164, University Library of Munich, Germany.
    13. 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.).
    14. Cross, Jamie L. & Hou, Chenghan & Koop, Gary & Poon, Aubrey, 2023. "Large stochastic volatility in mean VARs," Journal of Econometrics, Elsevier, vol. 236(1).
    15. Tsionas, Mike G. & Izzeldin, Marwan & Trapani, Lorenzo, 2022. "Estimation of large dimensional time varying VARs using copulas," European Economic Review, Elsevier, vol. 141(C).
    16. Koop, Gary & Korobilis, Dimitris, 2018. "Variational Bayes inference in high-dimensional time-varying parameter models," MPRA Paper 87972, University Library of Munich, Germany.
    17. Blazej Mazur, 2015. "Density forecasts based on disaggregate data: nowcasting Polish inflation," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 15, pages 71-87.
    18. Knüppel, Malte & Schultefrankenfeld, Guido, 2018. "Assessing the uncertainty in central banks' inflation outlooks," Discussion Papers 56/2018, Deutsche Bundesbank.
    19. Chiu, Ching-Wai (Jeremy) & Mumtaz, Haroon & Pinter, Gabor, 2016. "VAR models with non-Gaussian shocks," LSE Research Online Documents on Economics 86238, London School of Economics and Political Science, LSE Library.
    20. 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.
    21. 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.
    22. 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).
    23. Todd E. Clark & Gergely Ganics & Elmar Mertens, 2024. "Constructing fan charts from the ragged edge of SPF forecasts," Working Papers 2429, Banco de España.
    24. 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).
    25. Davide Pettenuzzo & Antonio Gargano & Allan Timmermann, 2014. "Bond Return Predictability: Economic Value and Links to the Macroeconomy," Working Papers 75, Brandeis University, Department of Economics and International Business School.
    26. 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.
    27. 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.
    28. 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.
    29. Frank C. Z. Wu, 2024. "Bayesian collapsed Gibbs sampling for a stochastic volatility model with a Dirichlet process mixture," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(4), pages 697-704, June.
    30. 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.
    31. Zanetti Chini, Emilio, 2018. "Forecasting dynamically asymmetric fluctuations of the U.S. business cycle," International Journal of Forecasting, Elsevier, vol. 34(4), pages 711-732.
    32. Florian Huber & Daniel Kaufmann, 2015. "Trend Fundamentals and Exchange Rate Dynamics," KOF Working papers 15-393, KOF Swiss Economic Institute, ETH Zurich.
    33. Matteo Iacopini & Francesco Ravazzolo & Luca Rossini, 2022. "Bayesian Multivariate Quantile Regression with alternative Time-varying Volatility Specifications," Papers 2211.16121, arXiv.org, revised Aug 2024.
    34. 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.
    35. Joshua C. C. Chan, 2022. "Comparing Stochastic Volatility Specifications for Large Bayesian VARs," Papers 2208.13255, arXiv.org.
    36. 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.
    37. Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano, 2022. "Capturing Macroeconomic Tail Risks with Bayesian Vector Autoregressions," CEPR Discussion Papers 17512, C.E.P.R. Discussion Papers.
    38. Hou, Chenghan, 2017. "Infinite hidden markov switching VARs with application to macroeconomic forecast," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1025-1043.
    39. 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.
    40. 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.
    41. Gergely Akos Ganics, 2017. "Optimal density forecast combinations," Working Papers 1751, Banco de España.
    42. 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.
    43. Bognanni, Mark & Zito, John, 2020. "Sequential Bayesian inference for vector autoregressions with stochastic volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    44. 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.
    45. 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.
    46. Bai, Yu & Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano, 2022. "Macroeconomic Forecasting in a Multi-country Context," CEPR Discussion Papers 16994, C.E.P.R. Discussion Papers.
    47. 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.
    48. 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, March.
    49. 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.
    50. Carriero, Andrea & Marcellino, Massimiliano & Tornese, Tommaso, 2022. "Blended Identification in Structural VARs," CEPR Discussion Papers 17640, C.E.P.R. Discussion Papers.
    51. 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).
    52. 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.
    53. 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.
    54. 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.
    55. Sune Karlsson & Stepan Mazur & Hoang Nguyen, 2021. "Vector autoregression models with skewness and heavy tails," Papers 2105.11182, arXiv.org.
    56. Antolin-Diaz, Juan & Drechsel, Thomas & Petrella, Ivan, 2023. "Advances in Nowcasting Economic Activity: The Role of Heterogeneous Dynamics and Fat Tails," CEPR Discussion Papers 17800, C.E.P.R. Discussion Papers.
    57. 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.
    58. Dominik Bertsche & Robin Braun, 2018. "Identification of Structural Vector Autoregressions by Stochastic Volatility," Working Paper Series of the Department of Economics, University of Konstanz 2018-03, Department of Economics, University of Konstanz.
    59. Dimitrakopoulos, Stefanos, 2017. "Semiparametric Bayesian inference for time-varying parameter regression models with stochastic volatility," Economics Letters, Elsevier, vol. 150(C), pages 10-14.
    60. Ellington, Michael, 2022. "Fat tails, serial dependence, and implied volatility index connections," European Journal of Operational Research, Elsevier, vol. 299(2), pages 768-779.
    61. Yunyun Wang & Tatsushi Oka & Dan Zhu, 2024. "Inflation Target at Risk: A Time-varying Parameter Distributional Regression," Papers 2403.12456, arXiv.org.
    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. Ruben Loaiza-Maya & Gael M. Martin & David T. Frazier & Worapree Maneesoonthorn & Andres Ramirez Hassan, 2020. "Optimal probabilistic forecasts: When do they work?," Monash Econometrics and Business Statistics Working Papers 33/20, Monash University, Department of Econometrics and Business Statistics.
    64. 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.
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    66. Alfan Mansur, 2023. "Simultaneous identification of fiscal and monetary policy shocks," Empirical Economics, Springer, vol. 65(2), pages 697-728, August.
    67. 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.
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    147. 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.
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  21. 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.
  22. 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.

  23. 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.
  24. 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.
  25. 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. Sune Karlsson & Pär Österholm, 2020. "A note on the stability of the Swedish Phillips curve," Empirical Economics, Springer, vol. 59(6), pages 2573-2612, December.
    2. 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.
    3. Sune Karlsson & Pär Österholm, 2023. "Is the US Phillips curve stable? Evidence from Bayesian vector autoregressions," Scandinavian Journal of Economics, Wiley Blackwell, vol. 125(1), pages 287-314, January.
    4. Conti, Antonio M., 2021. "Resurrecting the Phillips Curve in Low-Inflation Times," Economic Modelling, Elsevier, vol. 96(C), pages 172-195.
    5. 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.

  26. 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.

  27. 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.
  28. 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. Michael D. Bauer & Glenn D. Rudebusch, 2017. "Interest Rates Under Falling Stars," CESifo Working Paper Series 6571, CESifo.
    5. Karlsson, Sune & Österholm, Pär, 2018. "Is the US Phillips Curve Stable? Evidence from Bayesian VARs," Working Papers 2018:5, Örebro University, School of Business.
    6. 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.
    7. 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.
    8. Berger, Helge & Karlsson, Sune & Österholm, Pär, 2023. "A Note of Caution on the Relation between Money Growth and Inflation," Working Papers 2023:9, Örebro University, School of Business.
    9. 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.).
    10. Behera, Harendra Kumar & Patra, Michael Debabrata, 2022. "Measuring trend inflation in India," Journal of Asian Economics, Elsevier, vol. 80(C).
    11. 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.
    12. Sune Karlsson & Pär Österholm, 2020. "A note on the stability of the Swedish Phillips curve," Empirical Economics, Springer, vol. 59(6), pages 2573-2612, December.
    13. 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.
    14. Thomas Hasenzagl & Filippo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2020. "A Model of the Fed's View on Inflation," Papers 2006.14110, arXiv.org.
    15. García, Juan Angel & Poon, Aubrey, 2019. "Inflation trends in Asia: implications for central banks," Working Paper Series 2338, European Central Bank.
    16. 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.).
    17. Todd E. Clark & Michael W. McCracken, 2014. "Evaluating Conditional Forecasts from Vector Autoregressions," Working Papers 2014-25, Federal Reserve Bank of St. Louis.
    18. Michal Andrle & Miroslav Plašil, 2016. "System Priors for Econometric Time Series," IMF Working Papers 2016/231, International Monetary Fund.
    19. 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.
    20. 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.
    21. Mónica Correa-López & Matías Pacce & Kathi Schlepper, 2019. "Exploring trend inFLation dynamics in Euro Area countries," Working Papers 1909, Banco de España.
    22. Manuel M. F. Martins & Fabio Verona, 2024. "Forecasting Inflation with the New Keynesian Phillips Curve: Frequencies Matter," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 86(4), pages 811-832, August.
    23. Sune Karlsson & Pär Österholm, 2023. "Is the US Phillips curve stable? Evidence from Bayesian vector autoregressions," Scandinavian Journal of Economics, Wiley Blackwell, vol. 125(1), pages 287-314, January.
    24. 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.
    25. 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.
    26. González-Astudillo, Manuel, 2019. "An output gap measure for the euro area: Exploiting country-level and cross-sectional data heterogeneity," European Economic Review, Elsevier, vol. 120(C).
    27. Sbrana, Giacomo & Silvestrini, Andrea & Venditti, Fabrizio, 2017. "Short-term inflation forecasting: The M.E.T.A. approach," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1065-1081.
    28. Luis Uzeda, 2018. "State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models," Staff Working Papers 18-14, Bank of Canada.
    29. Joshua C C Chan & Yong Song, 2017. "Measuring inflation expectations uncertainty using high-frequency data," CAMA Working Papers 2017-61, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    30. Marc Giannoni & Domenico Giannone & Andrea Tambalotti & Marco Del Negro, 2017. "Safety, Liquidity, and the Natural Rate of Interest," 2017 Meeting Papers 803, Society for Economic Dynamics.
    31. McKnight, Stephen & Mihailov, Alexander & Rumler, Fabio, 2020. "Inflation forecasting using the New Keynesian Phillips Curve with a time-varying trend," Economic Modelling, Elsevier, vol. 87(C), pages 383-393.
    32. 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.
    33. Philippe Goulet Coulombe & Karin Klieber & Christophe Barrette & Maximilian Goebel, 2024. "Maximally Forward-Looking Core Inflation," Papers 2404.05209, arXiv.org.
    34. Lenza, Michele & Jarociński, Marek, 2016. "An inflation-predicting measure of the output gap in the euro area," Working Paper Series 1966, European Central Bank.
    35. Kim, Insu & Kim, Young Se, 2019. "Inattentive agents and inflation forecast error dynamics: A Bayesian DSGE approach," Journal of Macroeconomics, Elsevier, vol. 62(C).
    36. 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.
    37. 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.).
    38. Bańbura, Marta & Bobeica, Elena, 2020. "PCCI – a data-rich measure of underlying inflation in the euro area," Statistics Paper Series 38, European Central Bank.
    39. Belomestny, Denis & Krymova, Ekaterina & Polbin, Andrey, 2021. "Bayesian TVP-VARX models with time invariant long-run multipliers," Economic Modelling, Elsevier, vol. 101(C).
    40. Andrle, Michal & Plašil, Miroslav, 2018. "Econometrics with system priors," Economics Letters, Elsevier, vol. 172(C), pages 134-137.
    41. Beechey, Meredith & Österholm, Pär & Poon, Aubrey, 2023. "Estimating the US trend short-term interest rate," Finance Research Letters, Elsevier, vol. 55(PA).
    42. Todd E. Clark, 2014. "The Importance of Trend Inflation in the Search for Missing Disinflation," Economic Commentary, Federal Reserve Bank of Cleveland, issue Aug.
    43. Jaromir Baxa & Miroslav Plasil & Borek Vasicek, 2013. "Inflation and the Steeplechase Between Economic Activity Variables," Working Papers 2013/15, Czech National Bank.
    44. 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.
    45. 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.
    46. 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.).
    47. 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.).
    48. Denis Belomestny & Ekaterina Krymova & Andrey Polbin, 2020. "Estimating TVP-VAR models with time invariant long-run multipliers," Papers 2008.00718, arXiv.org.
    49. 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.
    50. 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.
    51. Svetlana Makarova, 2018. "European Central Bank Footprints On Inflation Forecast Uncertainty," Economic Inquiry, Western Economic Association International, vol. 56(1), pages 637-652, January.
    52. 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.

  29. 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.

  30. 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.

  31. 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.
  32. 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. 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. 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.
    3. Huber, Florian, 2016. "Density forecasting using Bayesian global vector autoregressions with stochastic volatility," International Journal of Forecasting, Elsevier, vol. 32(3), pages 818-837.
    4. 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.
    5. 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.
    6. 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.).
    7. 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.
    8. 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.
    9. Timmermann, Allan & Pettenuzzo, Davide, 2016. "Forecasting Macroeconomic Variables under Model Instability," CEPR Discussion Papers 11355, C.E.P.R. Discussion Papers.
    10. Joshua C. C. Chan & Xuewen Yu, 2022. "Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility," Papers 2206.08438, arXiv.org.
    11. Sebastian Ankargren & Mårten Bjellerup & Hovick Shahnazarian, 2017. "The importance of the financial system for the real economy," Empirical Economics, Springer, vol. 53(4), pages 1553-1586, December.
    12. 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.
    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. Marco Del Negro & Marc P. Giannoni & Frank Schorfheide, 2015. "Inflation in the Great Recession and New Keynesian Models," American Economic Journal: Macroeconomics, American Economic Association, vol. 7(1), pages 168-196, January.
    15. Joshua C. C. Chan, 2024. "BVARs and stochastic volatility," Chapters, in: Michael P. Clements & Ana Beatriz Galvão (ed.), Handbook of Research Methods and Applications in Macroeconomic Forecasting, chapter 3, pages 43-67, Edward Elgar Publishing.
    16. Davide Pettenuzzo & Francesco Ravazzolo, 2014. "Optimal portfolio choice under decision-based model combinations," Working Paper 2014/15, Norges Bank.
    17. 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.
    18. Karlsson, Sune, 2012. "Forecasting with Bayesian Vector Autoregressions," Working Papers 2012:12, Örebro University, School of Business.
    19. Mumtaz, Haroon & Theodoridis, Konstantinos, 2018. "Dynamic Effects of Monetary Policy Shocks on Macroeconomic Volatility," Cardiff Economics Working Papers E2018/21, Cardiff University, Cardiff Business School, Economics Section.
    20. 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.
    21. 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.).
    22. Cross, Jamie L. & Hou, Chenghan & Koop, Gary & Poon, Aubrey, 2023. "Large stochastic volatility in mean VARs," Journal of Econometrics, Elsevier, vol. 236(1).
    23. Chris McDonald & Craig Thamotheram & Shaun P. Vahey & Elizabeth C. Wakerly, 2016. "Assessing the economic value of probabilistic forecasts in the presence of an inflation target," Reserve Bank of New Zealand Discussion Paper Series DP2016/10, Reserve Bank of New Zealand.
    24. Knüppel, Malte & Krüger, Fabian & Pohle, Marc-Oliver, 2022. "Score-based calibration testing for multivariate forecast distributions," Discussion Papers 50/2022, Deutsche Bundesbank.
    25. Miranda-Agrippino, Silvia & Ricco, Giovanni, 2018. "Bayesian vector autoregressions," LSE Research Online Documents on Economics 87393, London School of Economics and Political Science, LSE Library.
    26. 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.
    27. Frank Schorfheide & Dongho Song, 2015. "Real-Time Forecasting With a Mixed-Frequency VAR," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(3), pages 366-380, July.
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    29. 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.
    30. Maximilian Böck & Martin Feldkircher & Florian Huber, 2020. "BGVAR: Bayesian Global Vector Autoregressions with Shrinkage Priors in R," Globalization Institute Working Papers 395, Federal Reserve Bank of Dallas.
    31. Franta, Michal, 2021. "The Likelihood Of Effective Lower Bound Events," Macroeconomic Dynamics, Cambridge University Press, vol. 25(8), pages 2058-2079, December.
    32. 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".
    33. 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.
    34. Allayioti, Anastasia & Venditti, Fabrizio, 2024. "The role of comovement and time-varying dynamics in forecasting commodity prices," Working Paper Series 2901, European Central Bank.
    35. Gary Koop & Dimitris Korobilis & Davide Pettenuzzo, 2016. "Bayesian Compressed Vector Autoregressions," Working Papers 103, Brandeis University, Department of Economics and International Business School.
    36. Michael S. Smith & Shaun P. Vahey, 2016. "Asymmetric Forecast Densities for U.S. Macroeconomic Variables from a Gaussian Copula Model of Cross-Sectional and Serial Dependence," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(3), pages 416-434, July.
    37. Martin Gachter & Elias Hasler & Florian Huber, 2023. "A tale of two tails: 130 years of growth-at-risk," Papers 2302.08920, arXiv.org.
    38. Mawuli Segnon & Rangan Gupta & Stelios Bekiros & Mark E. Wohar, 2018. "Forecasting US GNP growth: The role of uncertainty," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(5), pages 541-559, August.
    39. Todd E. Clark & Gergely Ganics & Elmar Mertens, 2024. "Constructing fan charts from the ragged edge of SPF forecasts," Working Papers 2429, Banco de España.
    40. Pfarrhofer, Michael, 2022. "Modeling tail risks of inflation using unobserved component quantile regressions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    41. Clark, Todd & Huber, Florian & Koop, Gary & Marcellino, Massimiliano, 2023. "Forecasting US Inflation Using Bayesian Nonparametric Models," CEPR Discussion Papers 18244, C.E.P.R. Discussion Papers.
    42. Ferrara, Laurent & Marcellino, Massimiliano & Mogliani, Matteo, 2015. "Macroeconomic forecasting during the Great Recession: The return of non-linearity?," International Journal of Forecasting, Elsevier, vol. 31(3), pages 664-679.
    43. 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.
    44. Luiz Renato Regis de Oliveira Lima & Wagner Piazza Gaglianone, 2012. "Constructing Optimal Density Forecasts from Point Forecast Combinations," Série Textos para Discussão (Working Papers) 5, Programa de Pós-Graduação em Economia - PPGE, Universidade Federal da Paraíba.
    45. 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.
    46. 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.
    47. 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.
    48. Daisuke Fujii & Taisuke Nakata, 2021. "Covid-19 and Output in Japan," CARF F-Series CARF-F-505, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    49. Joshua C. C. Chan, 2020. "Large Bayesian VARs: A Flexible Kronecker Error Covariance Structure," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(1), pages 68-79, January.
    50. Florian Huber & Daniel Kaufmann, 2015. "Trend Fundamentals and Exchange Rate Dynamics," KOF Working papers 15-393, KOF Swiss Economic Institute, ETH Zurich.
    51. Frank Schorfheide & Dongho Song, 2024. "Real-Time Forecasting with a (Standard) Mixed-Frequency VAR During a Pandemic," International Journal of Central Banking, International Journal of Central Banking, vol. 20(4), pages 275-320, October.
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    55. Todd E. Clark & Saeed Zaman, 2013. "Forecasting implications of the recent decline in inflation," Economic Commentary, Federal Reserve Bank of Cleveland, issue Nov.
    56. Niko Hauzenberger, 2020. "Flexible Mixture Priors for Large Time-varying Parameter Models," Papers 2006.10088, arXiv.org, revised Nov 2020.
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    63. Barbara Rossi & Tatevik Sekhposyan, 2014. "Alternative tests for correct specification of conditional predictive densities," Economics Working Papers 1416, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2017.
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    65. Piergiorgio Alessandri & Haroon Mumtaz, 2022. "The macroeconomic cost of climate volatility," BCAM Working Papers 2202, Birkbeck Centre for Applied Macroeconomics.
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    250. Clements, Michael P. & Galvão, Ana Beatriz, 2013. "Forecasting with vector autoregressive models of data vintages: US output growth and inflation," International Journal of Forecasting, Elsevier, vol. 29(4), pages 698-714.
    251. Sebastian Ankargren & Måns Unosson & Yukai Yang, 2018. "A mixed-frequency Bayesian vector autoregression with a steady-state prior," CREATES Research Papers 2018-32, Department of Economics and Business Economics, Aarhus University.
    252. Clark, Todd E. & Doh, Taeyoung, 2014. "Evaluating alternative models of trend inflation," International Journal of Forecasting, Elsevier, vol. 30(3), pages 426-448.
    253. Kilic, Erdem, 2017. "Contagion effects of U.S. Dollar and Chinese Yuan in forward and spot foreign exchange markets," Economic Modelling, Elsevier, vol. 62(C), pages 51-67.
    254. Kohns, David & Potjagailo, Galina, 2023. "Flexible Bayesian MIDAS: time‑variation, group‑shrinkage and sparsity," Bank of England working papers 1025, Bank of England.
    255. Michael P. Clements, 2020. "Are Some Forecasters’ Probability Assessments of Macro Variables Better Than Those of Others?," Econometrics, MDPI, vol. 8(2), pages 1-16, May.
    256. 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.
    257. Dimitrios P. Louzis, 2016. "Macroeconomic forecasting and structural changes in steady states," Working Papers 204, Bank of Greece.
    258. 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.).

  33. 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.
  34. 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. Granziera, Eleonora & Sekhposyan, Tatevik, 2019. "Predicting relative forecasting performance: An empirical investigation," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1636-1657.
    2. 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.
    3. 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.
    4. Nima Nonejad, 2021. "Crude oil price point forecasts of the Norwegian GDP growth rate," Empirical Economics, Springer, vol. 61(5), pages 2913-2930, November.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. Sander, Magnus, 2018. "Market timing over the business cycle," Journal of Empirical Finance, Elsevier, vol. 46(C), pages 130-145.
    11. 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.
    12. Todd E. Clark & Michael W. McCracken, 2011. "Advances in forecast evaluation," Working Papers (Old Series) 1120, Federal Reserve Bank of Cleveland.
    13. 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.
    14. 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.
    15. 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.
    16. Andrea Carriero & Davide Pettenuzzo & Shubhranshu Shekhar, 2024. "Macroeconomic Forecasting with Large Language Models," Papers 2407.00890, arXiv.org, revised Jan 2025.
    17. 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.
    18. Daniel Borup & Jonas N. Eriksen & Mads M. Kjær & Martin Thyrsgaard, 2024. "Predicting Bond Return Predictability," Management Science, INFORMS, vol. 70(2), pages 931-951, February.
    19. Amélie Charles & Olivier Darné & Jae H Kim, 2017. "International Stock Return Predictability: Evidence from New Statistical Tests," Post-Print hal-01626101, HAL.
    20. 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.
    21. 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.
    22. 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.
    23. Ahmed, Shamim & Tsvetanov, Daniel, 2016. "The predictive performance of commodity futures risk factors," Journal of Banking & Finance, Elsevier, vol. 71(C), pages 20-36.
    24. 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.
    25. Grégory Levieuge, 2017. "Explaining and forecasting bank loans. Good times and crisis," Post-Print hal-03529226, HAL.
    26. 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.
    27. 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).
    28. Zeng-Hua Lu, 2019. "Extended MinP Tests for Global and Multiple testing," Papers 1911.04696, arXiv.org, revised Aug 2024.
    29. 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.
    30. Khalaf, Lynda & Saunders, Charles J., 2017. "Monte Carlo forecast evaluation with persistent data," International Journal of Forecasting, Elsevier, vol. 33(1), pages 1-10.
    31. 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.
    32. 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).
    33. Enoch Cheng & Clemens C. Struck, 2019. "Time-Series Momentum: A Monte-Carlo Approach," Working Papers 201906, School of Economics, University College Dublin.
    34. 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.
    35. Arbués, Ignacio & Matilla-García, Mariano, 2024. "Multibenchmark reality checks," Economic Modelling, Elsevier, vol. 140(C).
    36. Xiaojie Xu, 2020. "Corn Cash Price Forecasting," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(4), pages 1297-1320, August.
    37. 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.

  35. 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.
  36. 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.
  37. 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.
  38. 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.
  39. 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.

    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. Demetrescu, Matei & Salish, Nazarii, 2024. "(Structural) VAR models with ignored changes in mean and volatility," International Journal of Forecasting, Elsevier, vol. 40(2), pages 840-854.
    9. Demetrescu, Matei & Hacıoğlu Hoke, Sinem, 2019. "Predictive regressions under asymmetric loss: Factor augmentation and model selection," International Journal of Forecasting, Elsevier, vol. 35(1), pages 80-99.
    10. 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, March.
    11. 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.
    12. 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.
    13. Máximo Camacho & Gabriel Pérez Quirós & Hugo Rodríguez Mendizábal, 2011. "High-growth recoveries, inventories and the great moderation," Post-Print hal-00828978, HAL.
    14. Hanck, Christoph & Demetrescu, Matei & Tarcolea, Adina, 2012. "IV-Based Cointegration Testing in Dependent Panels with Time-Varying Variance," VfS Annual Conference 2012 (Goettingen): New Approaches and Challenges for the Labor Market of the 21st Century 62072, Verein für Socialpolitik / German Economic Association.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. 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.
    23. 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.
    24. James Morley & Aarti Singh, 2012. "Inventory Mistakes and the Great Moderation," Discussion Papers 2012-42, School of Economics, The University of New South Wales.
    25. 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.
    26. David Harris & Hsein Kew & A. M. Robert Taylor, 2020. "Level Shift Estimation in the Presence of Non-stationary Volatility with an Application to the Unit Root Testing Problem," Monash Econometrics and Business Statistics Working Papers 8/20, Monash University, Department of Econometrics and Business Statistics.
    27. 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.
    28. 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.
    29. 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.
    30. 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.
    31. 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.
    32. 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.
    33. 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.
    34. 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.
    35. 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.

  40. 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.
  41. 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. 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.
    2. Kose,Ayhan & Matsuoka,Hideaki & Panizza,Ugo G. & Vorisek,Dana Lauren, 2019. "Inflation Expectations : Review and Evidence," Policy Research Working Paper Series 8785, The World Bank.
    3. 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 715-749, October.
    4. Ricardo M. Masolo & Francesca Monti, 2017. "Ambiguity, Monetary Policy and Trend Inflation," Discussion Papers 1709, Centre for Macroeconomics (CFM).
    5. 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.
    6. 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.
    7. 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.
    8. 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).
    9. 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.
    10. 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.
    11. 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.
    12. Bosworth, Barry & Flaaen, Aaron, 2009. "America's Financial Crisis: The End of an Era," ADBI Working Papers 142, Asian Development Bank Institute.

  42. 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.
  43. 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.
  44. 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.
  45. 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.
  46. 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.

  47. 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.
  48. 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. Yin, Anwen, 2015. "Forecasting and model averaging with structural breaks," ISU General Staff Papers 201501010800005727, Iowa State University, Department of Economics.
    3. Galvão, Ana Beatriz, 2013. "Changes in predictive ability with mixed frequency data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 395-410.
    4. 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.
    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. 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.
    7. 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.
    8. 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.
    9. 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.
    10. Barbara Rossi, 2005. "Are Exchange Rates Really Random Walks? Some Evidence Robust to Parameter Instability," International Finance 0503006, University Library of Munich, Germany.
    11. 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.
    12. Alessandro Casini, 2018. "Tests for Forecast Instability and Forecast Failure under a Continuous Record Asymptotic Framework," Papers 1803.10883, arXiv.org, revised Dec 2018.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2013. "Food versus Fuel: Causality and Predictability in Distribution," Working Papers 2013.23, Fondazione Eni Enrico Mattei.
    19. Dudek, Sławomir, 2008. "Consumer Survey Data and short-term forecasting of households consumption expenditures in Poland," MPRA Paper 19818, University Library of Munich, Germany.
    20. Todd E. Clark & Michael W. McCracken, 2011. "Advances in forecast evaluation," Working Papers (Old Series) 1120, Federal Reserve Bank of Cleveland.
    21. 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.
    22. Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2013. "Biofuels and Food Prices: Searching for the Causal Link," IEFE Working Papers 55, IEFE, Center for Research on Energy and Environmental Economics and Policy, Universita' Bocconi, Milano, Italy.
    23. 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.
    24. Marilena Furno, 2011. "Goodness of Fit and Misspecification in Quantile Regressions," Journal of Educational and Behavioral Statistics, , vol. 36(1), pages 105-131, February.
    25. 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.
    26. Rossi, Barbara & Giacomini, Raffaella, 2005. "How Stable is the Forecasting Performance of the Yield Curve for Outpot Growth?," Working Papers 05-08, Duke University, Department of Economics.
    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.
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    41. 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.
    42. 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.
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    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. Galvão, Ana Beatriz, 2013. "Changes in predictive ability with mixed frequency data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 395-410.
    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. Forni, Mario & Gambetti, Luca, 2016. "Government spending shocks in open economy VARs," Journal of International Economics, Elsevier, vol. 99(C), pages 68-84.
    7. 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.
    8. Pablo Pincheira Brown & Nicolás Hardy, 2024. "Correlation‐based tests of predictability," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 1835-1858, September.
    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. 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.
    11. 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.
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    20. 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.
    21. Chava, Sudheer & Gallmeyer, Michael & Park, Heungju, 2015. "Credit conditions and stock return predictability," Journal of Monetary Economics, Elsevier, vol. 74(C), pages 117-132.
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    38. 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).
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    44. Ayse Kabukcuoglu & Enrique Martínez-García & Mehmet Ali Soytas, 2017. "Exploring the Nexus between Inflation and Globalization under Inflation Targeting through the Lens of New Zealand’s Experience," Koç University-TUSIAD Economic Research Forum Working Papers 1709, Koc University-TUSIAD Economic Research Forum.
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    47. Todd E. Clark & Michael W. McCracken, 2014. "Evaluating Conditional Forecasts from Vector Autoregressions," Working Papers 2014-25, Federal Reserve Bank of St. Louis.
    48. 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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    50. 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.
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    61. Pincheira, Pablo & Selaive, Jorge & Nolazco, Jose Luis, 2017. "Forecasting Inflation in Latin America with Core Measures," MPRA Paper 80496, University Library of Munich, Germany.
    62. Ana Sequeira, 2013. "Predicting aggregate returns using valuation ratios out-of-sample," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.
    63. Kenneth S. Rogoff & Vania Stavrakeva, 2008. "The Continuing Puzzle of Short Horizon Exchange Rate Forecasting," NBER Working Papers 14071, National Bureau of Economic Research, Inc.
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    112. 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.
    113. 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.
    114. Arbués, Ignacio & Matilla-García, Mariano, 2024. "Multibenchmark reality checks," Economic Modelling, Elsevier, vol. 140(C).
    115. Richard A. Ashley & Kwok Ping Tsang, 2014. "Credible Granger-Causality Inference with Modest Sample Lengths: A Cross-Sample Validation Approach," Econometrics, MDPI, vol. 2(1), pages 1-20, March.
    116. Jack Fosten, 2016. "Forecast evaluation with factor-augmented models," University of East Anglia School of Economics Working Paper Series 2016-05, School of Economics, University of East Anglia, Norwich, UK..
    117. Peter Reinhard Hansen & Allan Timmermann, 2015. "Comment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(1), pages 17-21, January.
    118. Panopoulou, Ekaterini, 2007. "Predictive financial models of the euro area: A new evaluation test," International Journal of Forecasting, Elsevier, vol. 23(4), pages 695-705.
    119. Clements, Michael P. & Galvão, Ana Beatriz, 2013. "Forecasting with vector autoregressive models of data vintages: US output growth and inflation," International Journal of Forecasting, Elsevier, vol. 29(4), pages 698-714.
    120. Ekaterini Panopoulou & Sotiria Plastira, 2014. "Fama French factors and US stock return predictability," Journal of Asset Management, Palgrave Macmillan, vol. 15(2), pages 110-128, April.

  50. 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. 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.
    2. Gernot Pehnelt, 2007. "Globalisation and Inflation in OECD Countries," Jena Economics Research Papers 2007-055, Friedrich-Schiller-University Jena.
    3. 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.
    4. 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.
    5. Cobb, Marcus P A, 2018. "Improving Underlying Scenarios for Aggregate Forecasts: A Multi-level Combination Approach," MPRA Paper 88593, University Library of Munich, Germany.
    6. 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.

  51. 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.
  52. 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.
  53. 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.
  54. 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. Kemp-Benedict, Eric, 2012. "Material needs and aggregate demand," MPRA Paper 39960, University Library of Munich, Germany.
    3. Bermingham, Colin, 2006. "How Useful is Core Inflation for Forecasting Headline Inflation?," Research Technical Papers 11/RT/06, Central Bank of Ireland.
    4. 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.
    5. 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).
    6. 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.
    7. Linda S. Goldberg & Michael W. Klein, 2005. "Establishing credibility: evolving perceptions of the European Central Bank," Staff Reports 231, Federal Reserve Bank of New York.
    8. 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.
    9. James H. Stock & Mark W. Watson, 2015. "Core Inflation and Trend Inflation," NBER Working Papers 21282, National Bureau of Economic Research, Inc.
    10. 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.
    11. 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.
    12. 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.
    13. 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).
    14. 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.
    15. Tierney, Heather L.R., 2010. "Real-Time Data Revisions and the PCE Measure of Inflation," MPRA Paper 22387, University Library of Munich, Germany, revised Apr 2010.
    16. 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.
    17. Wynne, Mark A., 1999. "Core inflation: a review of some conceptual issues," Working Paper Series 5, European Central Bank.
    18. 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.
    19. 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.
    20. Hervé Le Bihan & Danilo Leiva-León & Matías Pacce, 2023. "Underlying inflation and asymetric risks," Working Papers 2319, Banco de España.
    21. Gatt, William, 2014. "An evaluation of core inflation measures for Malta," MPRA Paper 61250, University Library of Munich, Germany.
    22. Pincheira, Pablo & Selaive, Jorge & Nolazco, Jose Luis, 2017. "Forecasting Inflation in Latin America with Core Measures," MPRA Paper 80496, University Library of Munich, Germany.
    23. Jushan Bai & Serena Ng, 2004. "A PANIC Attack on Unit Roots and Cointegration," Econometrica, Econometric Society, vol. 72(4), pages 1127-1177, July.
    24. Stephen G Cecchetti & Richhild Moessner, 2008. "Commodity prices and inflation dynamics," BIS Quarterly Review, Bank for International Settlements, December.
    25. 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.
    26. 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.
    27. 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.
    28. Philippe Goulet Coulombe & Karin Klieber & Christophe Barrette & Maximilian Goebel, 2024. "Maximally Forward-Looking Core Inflation," Papers 2404.05209, arXiv.org.
    29. Mazumder, Sandeep, 2017. "Output gains from accelerating core inflation," Journal of Macroeconomics, Elsevier, vol. 51(C), pages 63-74.
    30. Oğuz Atuk & Mustafa Utku Özmen, 2009. "Design and evaluation of core inflation measures for Turkey," IFC Working Papers 3, Bank for International Settlements.
    31. Bańbura, Marta & Bobeica, Elena, 2020. "PCCI – a data-rich measure of underlying inflation in the euro area," Statistics Paper Series 38, European Central Bank.
    32. Bermingham, Colin, 2010. "A critical assessment of existing estimates of US core inflation," Journal of Macroeconomics, Elsevier, vol. 32(4), pages 993-1007, December.
    33. 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.
    34. Jamie Armour, 2006. "An Evaluation of Core Inflation Measures," Staff Working Papers 06-10, Bank of Canada.
    35. Abdul Aleem & Amine Lahiani, 2011. "Estimation and evaluation of core inflation measures," Applied Economics, Taylor & Francis Journals, vol. 43(25), pages 3619-3629.
    36. Mazumder, Sandeep, 2014. "The sacrifice ratio and core inflation," Journal of Macroeconomics, Elsevier, vol. 40(C), pages 400-421.
    37. Basu, Abhishek & Mazumder, Sandeep, 2024. "Motor fuel and core inflation," Economics Letters, Elsevier, vol. 242(C).
    38. Virginie Traclet, 2004. "Monetary and Fiscal Policies in Canada: Some Interesting Principles for EMU?," Staff Working Papers 04-28, Bank of Canada.
    39. 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).
    40. 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.
    41. 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.
    42. 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.
    43. 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).
    44. 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.
    45. 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.

  55. 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.
  56. 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. 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.
    3. 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.
    4. Andrew Bauer & Nicholas Haltom & William B. Peterman, 2004. "Decomposing inflation," Economic Review, Federal Reserve Bank of Atlanta, vol. 89(Q 1), pages 39-51.
    5. Emmanuel Carré, 2013. "La cible d'inflation de la Fed : continuité ou rupture ?," Post-Print hal-01419130, HAL.
    6. 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.
    7. 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.
    8. Robert W. Rich & Donald Rissmiller, 2001. "Structural change in U.S. wage determination," Staff Reports 117, Federal Reserve Bank of New York.
    9. Hanson, Michael S., 2004. "The "price puzzle" reconsidered," Journal of Monetary Economics, Elsevier, vol. 51(7), pages 1385-1413, October.
    10. 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.
    11. 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.).
    12. 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.
    13. Fan Ding & Alexander L. Wolman, 2005. "Inflation and changing expenditure shares," Economic Quarterly, Federal Reserve Bank of Richmond, vol. 91(Win), pages 1-20.
    14. 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.
    15. Ricardo Reis, 2005. "A Dynamic Measure of Inflation," NBER Working Papers 11746, National Bureau of Economic Research, Inc.

  57. 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. 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.
    2. Clark, Todd E. & van Wincoop, Eric, 2001. "Borders and business cycles," Journal of International Economics, Elsevier, vol. 55(1), pages 59-85, October.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. Michael Owyang & Jeremy Piger & Howard Wall, 2011. "Discordant City Employment Cycles," ERSA conference papers ersa11p1525, European Regional Science Association.
    13. Marco Del Negro, 2000. "Asymmetric shocks among U.S. states," FRB Atlanta Working Paper 2000-27, Federal Reserve Bank of Atlanta.
    14. 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.
    15. Hubrich, Kirstin & Marcellino, Massimiliano & Beck, Günter, 2011. "On the importance of sectoral and regional shocks for price-setting," CEPR Discussion Papers 8357, C.E.P.R. Discussion Papers.
    16. 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.
    17. 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.
    18. 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.
    19. Coulson, N. Edward, 1999. "Sectoral sources of metropolitan growth," Regional Science and Urban Economics, Elsevier, vol. 29(6), pages 723-743, November.
    20. 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.
    21. 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.
    22. 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.
    23. Sari Pekkala & Aki Kangasharju, 2002. "Regional Labour Market Adjustment: Are Positive and Negative Shocks Different?," LABOUR, CEIS, vol. 16(2), pages 267-286, June.
    24. 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.
    25. 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.
    26. Michael T. Owyang & David E. Rapach & Howard J. Wall, 2008. "States and the business cycle," Working Papers 2007-050, Federal Reserve Bank of St. Louis.
    27. 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.
    28. 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.
    29. Wall, Howard J., 2011. "The Employment Cycles of Neighboring Cities," MPRA Paper 29410, University Library of Munich, Germany.
    30. 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.
    31. 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.
    32. 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.
    33. Carlos Lamarche & Alberto Porto & Walter Sosa Escudero, 1998. "Aspectos Regionales del Desempleo en la Argentina," Department of Economics, Working Papers 008, Departamento de Economía, Facultad de Ciencias Económicas, Universidad Nacional de La Plata.
    34. 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.
    35. 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.
    36. 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.
    37. 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.
    38. 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.
    39. Di Caro, Paolo, 2014. "Regional recessions and recoveries in theory and practice: a resilience-based overview," MPRA Paper 60300, University Library of Munich, Germany.
    40. 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.
    41. Kangasharju, Aki & Pekkala, Sari, 2002. "Adjustment to Regional Labour Market Shocks," Discussion Papers 274, VATT Institute for Economic Research.
    42. 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.
    43. Theodore M. Crone, 2004. "A redefinition of economic regions in the U.S," Working Papers 04-12, Federal Reserve Bank of Philadelphia.
    44. 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).
    45. 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.
    46. 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.
    47. 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.
    48. 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.
    49. 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.
    50. 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.
    51. 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.
    52. 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.
    53. 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.
    54. 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.
    55. 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.
    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. Steven Cassou & Jesús Vázquez, 2014. "Employment comovements at the sectoral level over the business cycle," Empirical Economics, Springer, vol. 46(4), pages 1301-1323, June.
    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.

  58. 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.
  59. 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.
  60. 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. 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.
    2. 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.
    3. Emilio Bisetti & Stephen A. Karolyi, 2024. "Meeting Targets in Competitive Product Markets," Journal of Finance, American Finance Association, vol. 79(4), pages 2845-2884, August.
    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. 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).
    6. Robert Lehmann & Timo Wollmershäuser, 2017. "Die Inflation kommt zurück! Immer mehr Firmen in Deutschland wollen ihre Preise anheben," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 70(05), pages 16-21, March.
    7. 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.
    8. 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.
    9. 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.
    10. Ülke, Volkan & Ergun, Ugur, 2013. "The Relationship between Consumer Price and Producer Price Indices in Turkey," MPRA Paper 59437, University Library of Munich, Germany.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. Gibson, Heather D. & Lazaretou, Sophia, 2001. "Leading inflation indicators for Greece," Economic Modelling, Elsevier, vol. 18(3), pages 325-348, August.
    18. 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.
    19. 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.
    20. 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.
    21. 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.

  61. 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. 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. 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.
    3. 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.
    4. Waltl, Sofie R., 2018. "Estimating quantile-specific rental yields for residential housing in Sydney," Regional Science and Urban Economics, Elsevier, vol. 68(C), pages 204-225.
    5. Baltagi, Badi H. & Li, Jing, 2015. "Cointegration of matched home purchases and rental price indexes — Evidence from Singapore," Regional Science and Urban Economics, Elsevier, vol. 55(C), pages 80-88.
    6. 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.
    7. 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.
    8. Carmona, Juan & Lampe, Markus & Rosés, Joan, 2017. "Housing affordability during the urban transition in Spain," LSE Research Online Documents on Economics 68886, London School of Economics and Political Science, LSE Library.
    9. Dan S. Rickman & Mouhcine Guettabi, 2015. "The Great Recession And Nonmetropolitan America," Journal of Regional Science, Wiley Blackwell, vol. 55(1), pages 93-112, January.
    10. 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.
    11. 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.).
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. Arthur Grimes & Andrew Aitken, 2007. "House Prices and Rents: Socio-Economic Impacts and Prospects," Working Papers 07_01, Motu Economic and Public Policy Research.
    18. Winters, John V, 2010. "Differences in Quality of Life Estimates Using Rents and Home Values," MPRA Paper 22455, University Library of Munich, Germany.
    19. 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.
    20. 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.
    21. 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.
    22. 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.
    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.

  62. 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. 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.
    3. Billi, Roberto M., 2012. "Output Gaps and Robust Monetary Policy Rules," Working Paper Series 260, Sveriges Riksbank (Central Bank of Sweden).
    4. 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.
    5. Ray C. Fair, 2000. "Estimated, Calibrated, and Optimal Interest Rate Rules," Cowles Foundation Discussion Papers 1258, Cowles Foundation for Research in Economics, Yale University.
    6. Bilal Bagis, 2017. "Central Banking in the New Era," Eurasian Journal of Economics and Finance, Eurasian Publications, vol. 5(4), pages 197-225.
    7. Thornton, Saranna R., 1998. "Suitable policy instruments for monetary rules," Journal of Economics and Business, Elsevier, vol. 50(4), pages 379-397, July.
    8. 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.
    9. 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.

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.
  2. Todd E. Clark & Michael W. McCracken, 2008. "Chapter 3 Forecasting with Small Macroeconomic VARs in the Presence of Instabilities," Frontiers of Economics and Globalization, in: Forecasting in the Presence of Structural Breaks and Model Uncertainty, pages 93-147, Emerald Group Publishing Limited.

    Cited by:

    1. Duc Do, Nguyen, 2024. "Money/asset ratio as a predictor of inflation," The Quarterly Review of Economics and Finance, Elsevier, vol. 97(C).

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