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Barbara Rossi

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. Barbara Rossi, 2013. "Exchange rate predictability," Economics Working Papers 1369, Department of Economics and Business, Universitat Pompeu Fabra.

    Mentioned in:

    1. Is Redwood right?
      by chris in Stumbling and Mumbling on 2017-11-13 19:03:40

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Raffaella Giacomini & Barbara Rossi, 2010. "Forecast comparisons in unstable environments," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 595-620.

    Mentioned in:

    1. Forecast comparisons in unstable environments (Journal of Applied Econometrics 2010) in ReplicationWiki ()
  2. Yu-Chin Chen & Kenneth S. Rogoff & Barbara Rossi, 2010. "Can Exchange Rates Forecast Commodity Prices?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 125(3), pages 1145-1194.

    Mentioned in:

    1. Can Exchange Rates Forecast Commodity Prices? (QJE 2010) in ReplicationWiki ()

Working papers

  1. Barbara Rossi, 2022. "Local projections in unstable environments: How effective is fiscal policy?," Economics Virtual Symposium 2022 02, Stata Users Group.

    Cited by:

    1. Barbara Rossi & Atsushi Inoue & Yiru Wang, 2024. "Has the Phillips curve flattened?," French Stata Users' Group Meetings 2024 22, Stata Users Group.
    2. Francisco Blasques & Noah Stegehuis, 2024. "A Score-Driven Filter for Causal Regression Models with Time- Varying Parameters and Endogenous Regressors," Tinbergen Institute Discussion Papers 24-016/III, Tinbergen Institute.

  2. Kenneth S. Rogoff & Barbara Rossi & Paul Schmelzing, 2022. "Long-Run Trends in Long-Maturity Real Rates 1311-2021," NBER Working Papers 30475, National Bureau of Economic Research, Inc.

    Cited by:

    1. Stewart, Kenneth G., 2024. "The simple macroeconometrics of the quantity theory and the welfare cost of inflation," Journal of Economic Dynamics and Control, Elsevier, vol. 162(C).
    2. Kathryn Holston & Thomas Laubach & John C. Williams, 2023. "Measuring the Natural Rate of Interest after COVID-19," Staff Reports 1063, Federal Reserve Bank of New York.

  3. Rossi, Barbara & Ganics, Gergely & Sekhposyan, Tatevik, 2020. "From Fixed-event to Fixed-horizon Density Forecasts: Obtaining Measures of Multi-horizon Uncertainty from Survey Density Foreca," CEPR Discussion Papers 14267, C.E.P.R. Discussion Papers.

    Cited by:

    1. 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.
    2. De Santis, Roberto A. & Van der Veken, Wouter, 2020. "Forecasting macroeconomic risk in real time: Great and Covid-19 Recessions," Working Paper Series 2436, European Central Bank.
    3. Manzan, Sebastiano, 2021. "Are professional forecasters Bayesian?," Journal of Economic Dynamics and Control, Elsevier, vol. 123(C).
    4. Clements, Michael P., 2021. "Rounding behaviour of professional macro-forecasters," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1614-1631.
    5. Fabian Kruger & Hendrik Plett, 2022. "Prediction intervals for economic fixed-event forecasts," Papers 2210.13562, arXiv.org, revised Mar 2024.

  4. Lukas Hoesch & Barbara Rossi & Tatevik Sekhposyan, 2020. "Has the Information Channel of Monetary Policy Disappeared? Revisiting the Empirical Evidence," Working Papers 1158, Barcelona School of Economics.

    Cited by:

    1. Andersson, Fredrik N. G. & Kilman, Josefin, 2021. "A Study of the Romer and Romer Monetary Policy Shocks Using Revised Data," Working Papers 2021:19, Lund University, Department of Economics.
    2. Wenting Liao & Jun Ma & Chengsi Zhang, 2023. "Identifying exchange rate effects and spillovers of US monetary policy shocks in the presence of time‐varying instrument relevance," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(7), pages 989-1006, November.
    3. Taeyoung Doh & Dongho Song & Shu-Kuei X. Yang, 2020. "Deciphering Federal Reserve Communication via Text Analysis of Alternative FOMC Statements," Research Working Paper RWP 20-14, Federal Reserve Bank of Kansas City.
    4. Dimitrios Kanelis & Pierre L. Siklos, 2022. "Emotion in Euro Area Monetary Policy Communication and Bond Yields: The Draghi Era," CAMA Working Papers 2022-75, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, revised Jun 2024.
    5. Christopher S Sutherland, 2022. "Forward guidance and expectation formation: A narrative approach," BIS Working Papers 1024, Bank for International Settlements.
    6. Margaret M. Jacobson & Christian Matthes & Todd B. Walker, 2022. "Inflation Measured Every Day Keeps Adverse Responses Away: Temporal Aggregation and Monetary Policy Transmission," Finance and Economics Discussion Series 2022-054, Board of Governors of the Federal Reserve System (U.S.).
    7. Michael D. Bauer & Eric T. Swanson, 2023. "An Alternative Explanation for the "Fed Information Effect"," American Economic Review, American Economic Association, vol. 113(3), pages 664-700, March.
    8. Michael D. Bauer & Eric T. Swanson, 2020. "The Fed's Response to Economic News Explains the “Fed Information Effect”," Working Paper Series 2020-06, Federal Reserve Bank of San Francisco.
    9. Benjamin Gardner & Chiara Scotti & Clara Vega, 2021. "Words Speak as Loudly as Actions: Central Bank Communication and the Response of Equity Prices to Macroeconomic Announcements," Finance and Economics Discussion Series 2021-074, Board of Governors of the Federal Reserve System (U.S.).
    10. Bennett Schmanski & Chiara Scotti & Clara Vega, 2023. "Fed Communication, News, Twitter, and Echo Chambers," Finance and Economics Discussion Series 2023-036, Board of Governors of the Federal Reserve System (U.S.).
    11. Parle, Conor, 2021. "The financial market impact of ECB monetary policy press conferences - a text based approach," Research Technical Papers 4/RT/21, Central Bank of Ireland.
    12. Ma, Liang, 2024. "Using stock prices to help identify unconventional monetary policy shocks for external instrument SVAR," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 1234-1247.
    13. Goodhead, Robert, 2024. "The economic impact of yield curve compression: Evidence from euro area forward guidance and unconventional monetary policy," European Economic Review, Elsevier, vol. 164(C).
    14. Jarociński, Marek, 2022. "Central bank information effects and transatlantic spillovers," Journal of International Economics, Elsevier, vol. 139(C).
    15. Karnaukh, Nina & Vokata, Petra, 2022. "Growth forecasts and news about monetary policy," Journal of Financial Economics, Elsevier, vol. 146(1), pages 55-70.
    16. Oliver Holtemöller & Alexander Kriwoluzky & Boreum Kwak, 2020. "Exchange Rates and the Information Channel of Monetary Policy," Discussion Papers of DIW Berlin 1906, DIW Berlin, German Institute for Economic Research.
    17. Holtemöller, Oliver & Kriwoluzky, Alexander & Kwak, Boreum, 2024. "Is there an information channel of monetary policy?," IWH Discussion Papers 17/2020, Halle Institute for Economic Research (IWH), revised 2024.
    18. Christopher S. Sutherland, 2023. "Forward guidance and expectation formation: A narrative approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(2), pages 222-241, March.
    19. Ester Faiaa & Sören Karau, 2021. "Systemic Bank Risk and Monetary Policy," International Journal of Central Banking, International Journal of Central Banking, vol. 17(71), pages 1-40, December.
    20. Jochen Güntner, 2020. "Central bank information and private-sector Expectations," Economics working papers 2020-07, Department of Economics, Johannes Kepler University Linz, Austria.
    21. Karau, Sören, 2021. "Monetary policy and Bitcoin," Discussion Papers 41/2021, Deutsche Bundesbank.
    22. Laséen, Stefan, 2020. "Monetary Policy Surprises, Central Bank Information Shocks, and Economic Activity in a Small Open Economy," Working Paper Series 396, Sveriges Riksbank (Central Bank of Sweden).
    23. 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.
    24. Christopher S. Sutherland, 2020. "Forward Guidance and Expectation Formation: A Narrative Approach," Staff Working Papers 20-40, Bank of Canada.
    25. Eminidou, Snezana & Zachariadis, Marios, 2022. "Firms’ expectations and monetary policy shocks in the euro area," Journal of International Money and Finance, Elsevier, vol. 122(C).
    26. Mariana García-Schmidt, 2024. "Is the Information Channel of Monetary Policy Alive in Emerging Markets?," Working Papers Central Bank of Chile 1017, Central Bank of Chile.
    27. Luca Fanelli & Antonio Marsi, 2021. "Unconventional Monetary Policy in the Euro Area: A Tale of Three Shocks," Working Papers wp1164, Dipartimento Scienze Economiche, Universita' di Bologna.
    28. Fanelli, Luca & Marsi, Antonio, 2022. "Sovereign spreads and unconventional monetary policy in the Euro area: A tale of three shocks," European Economic Review, Elsevier, vol. 150(C).
    29. Han, Zhao, 2024. "Asymmetric information and misaligned inflation expectations," Journal of Monetary Economics, Elsevier, vol. 143(C).

  5. Barbara Rossi & Yiru Wang, 2019. "VAR-Based Granger-Causality Test in the Presence of Instabilities," Working Papers 1083, Barcelona School of Economics.

    Cited by:

    1. Mehmet Balcilar & Edmond Berisha & Oguzhan Cepni & Rangan Gupta, 2019. "The Predictive Power of the Term Spread on Inequality in the United Kingdom: An Empirical Analysis," Working Papers 201981, University of Pretoria, Department of Economics.
    2. Demirer, Riza & Gupta, Rangan & Salisu, Afees A. & van Eyden, Reneé, 2023. "Firm-level business uncertainty and the predictability of the aggregate U.S. stock market volatility during the COVID-19 pandemic," The Quarterly Review of Economics and Finance, Elsevier, vol. 88(C), pages 295-302.
    3. Chevaughn van der Westhuizen & Renee van Eyden & Goodness C. Aye, 2022. "Is Inflation Uncertainty a Self-Fulfilling Prophecy? The Inflation-Inflation Uncertainty Nexus and Inflation Targeting in South Africa," Working Papers 202254, University of Pretoria, Department of Economics.
    4. 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.
    5. 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.
    6. Nicholas Apergis & Konstantinos Gavriilidis & Rangan Gupta, 2021. "Does Climate Policy Uncertainty Affect Tourism Demand? Evidence from Time-Varying Causality Tests," Working Papers 202186, University of Pretoria, Department of Economics.
    7. 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.
    8. Mehmet Balcilar & Edmond Berisha & Rangan Gupta & Christian Pierdzioch, 2020. "Time-Varying Evidence of Predictability of Financial Stress in the United States over a Century: The Role of Inequality," Working Papers 202054, University of Pretoria, Department of Economics.
    9. 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.
    10. Yuvana Jaichand & Renee van Eyden & Rangan Gupta, 2024. "Presidential Approval Ratings and Stock Market Performance in Latin America," Working Papers 202411, University of Pretoria, Department of Economics.
    11. Caraiani, Petre & Gupta, Rangan & Nel, Jacobus & Nielsen, Joshua, 2023. "Monetary policy and bubbles in G7 economies using a panel VAR approach: Implications for sustainable development," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 133-155.
    12. David Gabauer & Rangan Gupta & Jacobus Nel & Woraphon Yamaka, 2021. "Time-Varying Predictability of Labor Productivity on Inequality in United Kingdom," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 155(3), pages 771-788, June.

  6. Barbara Rossi, 2019. "Forecasting in the Presence of Instabilities: How Do We Know Whether Models Predict Well and How to Improve Them," Working Papers 1162, Barcelona School of Economics.

    Cited by:

    1. Carola Conces Binder & Rodrigo Sekkel, 2023. "Central Bank Forecasting: A Survey," Staff Working Papers 23-18, Bank of Canada.
    2. Nicolás Magner & Nicolás Hardy, 2022. "Cryptocurrency Forecasting: More Evidence of the Meese-Rogoff Puzzle," Mathematics, MDPI, vol. 10(13), pages 1-27, July.
    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. Li, Dongxin & Zhang, Li & Li, Lihong, 2023. "Forecasting stock volatility with economic policy uncertainty: A smooth transition GARCH-MIDAS model," International Review of Financial Analysis, Elsevier, vol. 88(C).
    5. 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.
    6. 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.
    7. 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.
    8. Graziano Moramarco, 2021. "Financial-cycle ratios and medium-term predictions of GDP: Evidence from the United States," Papers 2111.00822, arXiv.org, revised Jan 2024.
    9. Ryan Thompson & Yilin Qian & Andrey L. Vasnev, 2022. "Flexible global forecast combinations," Papers 2207.07318, arXiv.org, revised Mar 2024.
    10. Konstantin Boss & Andre Groeger & Tobias Heidland & Finja Krueger & Conghan Zheng, 2023. "Forecasting Bilateral Refugee Flows with High-dimensional Data and Machine Learning Techniques," Working Papers 1387, Barcelona School of Economics.
    11. 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.
    12. 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.
    13. Eric Hillebrand & Jakob Guldbæk Mikkelsen & Lars Spreng & Giovanni Urga, 2023. "Exchange rates and macroeconomic fundamentals: Evidence of instabilities from time‐varying factor loadings," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(6), pages 857-877, September.
    14. Bobeica, Elena & Hartwig, Benny, 2021. "The COVID-19 shock and challenges for time series models," Working Paper Series 2558, European Central Bank.
    15. Kishor, N. Kundan, 2024. "Does Zillow Rent Measure Help Predict CPI Rent Inflation?," MPRA Paper 120818, University Library of Munich, Germany.
    16. Korobilis, Dimitris & Landau, Bettina & Musso, Alberto & Phella, Anthoulla, 2021. "The time-varying evolution of inflation risks," Working Paper Series 2600, European Central Bank.
    17. Yu Jeffrey Hu & Jeroen Rombouts & Ines Wilms, 2023. "Fast Forecasting of Unstable Data Streams for On-Demand Service Platforms," Papers 2303.01887, arXiv.org, revised May 2024.
    18. Yolanda S. Stander, 2024. "A News Sentiment Index to Inform International Financial Reporting Standard 9 Impairments," JRFM, MDPI, vol. 17(7), pages 1-23, July.
    19. Eric Hillebrand & Jakob Mikkelsen & Lars Spreng & Giovanni Urga, 2020. "Exchange Rates and Macroeconomic Fundamentals: Evidence of Instabilities from Time-Varying Factor Loadings," CREATES Research Papers 2020-19, Department of Economics and Business Economics, Aarhus University.
    20. Friedrich, Marina & Lin, Yicong, 2024. "Sieve bootstrap inference for linear time-varying coefficient models," Journal of Econometrics, Elsevier, vol. 239(1).
    21. 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.
    22. Bennett, Donyetta & Mekelburg, Erik & Strauss, Jack & Williams, T.H., 2024. "Unlocking the black box of sentiment and cryptocurrency: What, which, why, when and how?," Global Finance Journal, Elsevier, vol. 60(C).
    23. Fabrizio Iacone & Luca Rossini & Andrea Viselli, 2024. "Comparing predictive ability in presence of instability over a very short time," Papers 2405.11954, arXiv.org.
    24. Ray C. Fair, 2022. "A note on the fed’s power to lower inflation," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 57(2), pages 56-63, April.

  7. Atsushi Inoue & Barbara Rossi, 2019. "A New Approach to Measuring Economic Policy Shocks, with an Application to Conventional and Unconventional Monetary Policy," Working Papers 1082, Barcelona School of Economics.

    Cited by:

    1. Luisa Corrado & Daniela Fantozzi & Simona Giglioli, 2022. "Real-time ineuqalities and policies during the pandemic in the US," Temi di discussione (Economic working papers) 1396, Bank of Italy, Economic Research and International Relations Area.
    2. Mathias Krogh & Giovanni Pellegrino, "undated". "Real Activity and Uncertainty Shocks: The Long and the Short of It," "Marco Fanno" Working Papers 0310, Dipartimento di Scienze Economiche "Marco Fanno".
    3. Yoosoon Chang & Ana María Herrera & Elena Pesavento, 2023. "Oil Prices Uncertainty, Endogenous Regime Switching, and Inflation Anchoring," CAMA Working Papers 2023-14, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    4. Lance A. Fisher & Hyeon-seung Huh, 2022. "Systematic Monetary Policy in a SVAR for Australia," Working papers 2022rwp-194, Yonsei University, Yonsei Economics Research Institute.
    5. Yoosoon Chang & Fabio Gómez-Rodríguez & Christian Matthes, 2023. "The Influence of Fiscal and Monetary Policies on the Shape of the Yield Curve," CAMA Working Papers 2023-65, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    6. Hilde C. Bjornland & Yoosoon Chang & Jamie L. Cross, 2023. "Oil and the Stock Market Revisited: A Mixed Functional VAR Approach," CAEPR Working Papers 2023-005 Classification-1, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    7. Atsushi Inoue & Barbara Rossi, 2019. "A New Approach to Measuring Economic Policy Shocks, with an Application to Conventional and Unconventional Monetary Policy," Working Papers 1082, Barcelona School of Economics.
    8. De Santis, Roberto A., 2020. "Impact of the Asset Purchase Programme on euro area government bond yields using market news," Economic Modelling, Elsevier, vol. 86(C), pages 192-209.
    9. Rasmus Fatum & Naoko Hara & Yohei Yamamoto, 2019. "Negative Interest Rate Policy and the Influence of Macroeconomic News on Yields," IMES Discussion Paper Series 19-E-02, Institute for Monetary and Economic Studies, Bank of Japan.
    10. Ca' Zorzi, Michele & Dedola, Luca & Georgiadis, Georgios & Jarociński, Marek & Stracca, Livio & Strasser, Georg, 2020. "Monetary policy and its transmission in a globalised world," Working Paper Series 2407, European Central Bank.
    11. Robert Adamek & Stephan Smeekes & Ines Wilms, 2024. "Local projection inference in high dimensions," The Econometrics Journal, Royal Economic Society, vol. 27(3), pages 323-342.
    12. Leonardo Nogueira Ferreira, 2023. "Monetary Policy Surprises, Financial Conditions, and the String Theory Revisited," Working Papers Series 573, Central Bank of Brazil, Research Department.
    13. Eo, Yunjong & Kang, Kyu Ho, 2020. "The effects of conventional and unconventional monetary policy on forecasting the yield curve," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    14. Chunya Bu & John Rogers & Wenbin Wu, 2019. "A Unified Measure of Fed Monetary Policy Shocks," Finance and Economics Discussion Series 2019-043, Board of Governors of the Federal Reserve System (U.S.).
    15. Jarociński, Marek, 2024. "Estimating the Fed’s unconventional policy shocks," Journal of Monetary Economics, Elsevier, vol. 144(C).
    16. Alisdair McKay & Christian K. Wolf, 2023. "What Can Time‐Series Regressions Tell Us About Policy Counterfactuals?," Econometrica, Econometric Society, vol. 91(5), pages 1695-1725, September.
    17. Christina Anderl & Guglielmo Maria Caporale, 2024. "Functional Oil Price Expectations Shocks and Inflation," CESifo Working Paper Series 10998, CESifo.
    18. 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. Rüth, Sebastian K., 2020. "Shifts in monetary policy and exchange rate dynamics: Is Dornbusch's overshooting hypothesis intact, after all?," Journal of International Economics, Elsevier, vol. 126(C).
    20. Shixuan Wang & Rangan Gupta & Matteo Bonato & Oguzhan Cepni, 2022. "The Effects of Conventional and Unconventional Monetary Policy Shocks on US REITs Moments: Evidence from VARs with Functional Shocks," Working Papers 202219, University of Pretoria, Department of Economics.
    21. Brubakk, Leif & ter Ellen, Saskia & Robstad, Ørjan & Xu, Hong, 2019. "The macroeconomic effects of forward communication," Working Paper 2019/20, Norges Bank.
    22. Goodhead, Robert, 2024. "The economic impact of yield curve compression: Evidence from euro area forward guidance and unconventional monetary policy," European Economic Review, Elsevier, vol. 164(C).
    23. Thi Bich Ngoc Tran & Hoang Cam Huong Pham, 2020. "The Spillover Effects of the US Unconventional Monetary Policy: New Evidence from Asian Developing Countries," JRFM, MDPI, vol. 13(8), pages 1-26, July.
    24. Zoe Venter, 2019. "The Interaction Between ConventionalMonetary Policy and Financial Stability: Chile, Colombia, Japan, Portugal and the UK," Working Papers REM 2019/96, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    25. Eva Ortega & Chiara Osbat, 2020. "Exchange rate pass-through in the euro area and EU countries," Occasional Papers 2016, Banco de España.
    26. Jamie L. Cross & Lennart Hoogerheide & Paul Labonne & Herman K. van Dijk, 2023. "Bayesian Mode Inference for Discrete Distributions in Economics and Finance," Working Papers No 11/2023, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    27. Oliver Holtemöller & Alexander Kriwoluzky & Boreum Kwak, 2020. "Exchange Rates and the Information Channel of Monetary Policy," Discussion Papers of DIW Berlin 1906, DIW Berlin, German Institute for Economic Research.
    28. Yuriy Kitsul & Oleg Sokolinskiy & Jonathan H. Wright, 2022. "Market Effects of Central Bank Credit Markets Support Programs in Europe," International Finance Discussion Papers 1357, Board of Governors of the Federal Reserve System (U.S.).
    29. Yoosoon Chang & Yongok Choi & Chang Sik Kim & J. Isaac Miller & Joon Y. Park, 2024. "Common Trends and Country Specific Heterogeneities in Long-Run World Energy Consumption," CAMA Working Papers 2024-04, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    30. 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.
    31. Stavrakeva, Vania & Tang, Jenny, 2019. "The Dollar During the Great Recession: US Monetary Policy Signaling and The Flight To Safety," CEPR Discussion Papers 14034, C.E.P.R. Discussion Papers.
    32. Endong Wang, 2024. "Structural counterfactual analysis in macroeconomics: theory and inference," Papers 2409.09577, arXiv.org.
    33. Robert Kirkby & Huong Ngoc Vu, 2024. "Impacts of Monetary Policy Shocks on Inflation and Output in New Zealand," The Economic Record, The Economic Society of Australia, vol. 100(329), pages 160-187, June.
    34. Daniel J. Lewis, 2019. "Announcement-Specific Decompositions of Unconventional Monetary Policy Shocks and Their Macroeconomic Effects," Staff Reports 891, Federal Reserve Bank of New York.
    35. Fisher, Lance A. & Huh, Hyeon-seung, 2023. "Systematic monetary policy in a SVAR for Australia," Economic Modelling, Elsevier, vol. 128(C).

  8. Rossi, Barbara & Wang, Yiru, 2019. "Vector autoregressive-based Granger causality test in the presence of instabilities," MPRA Paper 101492, University Library of Munich, Germany.

    Cited by:

    1. Sibande, Xolani & Demirer, Riza & Balcilar, Mehmet & Gupta, Rangan, 2023. "On the pricing effects of bitcoin mining in the fossil fuel market: The case of coal," Resources Policy, Elsevier, vol. 85(PB).
    2. Elżbieta Szaruga & Elżbieta Załoga, 2022. "Environmental Management from the Point of View of the Energy Intensity of Road Freight Transport and Shocks," IJERPH, MDPI, vol. 19(21), pages 1-22, November.
    3. Desiree M. Kunene & Renee van Eyden & Petre Caraiani & Rangan Gupta, 2023. "The Predictive Impact of Climate Risk on Total Factor Productivity Growth: 1880-2020," Working Papers 202321, University of Pretoria, Department of Economics.
    4. 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.
    5. Gulcin Kendirkiran & Furkan Emirmahmutoglu, 2022. "Does Change over Time the Causal Relationship between Economic Growth and Foreign Trade in Turkey?," EKOIST Journal of Econometrics and Statistics, Istanbul University, Faculty of Economics, vol. 0(36), pages 43-62, June.
    6. 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).
    7. Antonio Afonso & Valérie Mignon & Jamel Saadaoui, 2024. "On the time-varying impact of China’s bilateral political relations on its trading partners: “doux commerce” or “trade follows the flag”?," Working Papers of BETA 2024-17, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    8. Andisheh Saliminezhad & Huseyin Ozdeser & Dahiru Alhaji Bala Birnintsaba, 2022. "Environmental degradation and economic growth: time-varying and nonlinear evidence from Nigeria," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(5), pages 6288-6301, May.
    9. Oguzhan Cepni, Duc Khuong Nguyen, and Ahmet Sensoy, 2022. "News Media and Attention Spillover across Energy Markets: A Powerful Predictor of Crude Oil Futures Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Special I).
    10. Oguzhan Cepni & Tarik Dogru & Ozgur Ozdemir, 2023. "The contagion effect of COVID-19-induced uncertainty on US tourism sector: Evidence from time-varying granger causality test," Tourism Economics, , vol. 29(4), pages 906-928, June.
    11. Cooray, Arusha & Gangopadhyay, Partha & Das, Narasingha, 2023. "Causality between volatility and the weekly economic index during COVID-19: The predictive power of efficient markets and rational expectations," International Review of Financial Analysis, Elsevier, vol. 89(C).
    12. Akyildirim, Erdinc & Cepni, Oguzhan & Pham, Linh & Uddin, Gazi Salah, 2022. "How connected is the agricultural commodity market to the news-based investor sentiment?," Energy Economics, Elsevier, vol. 113(C).
    13. Celso-Arellano, Pedro & Gualajara, Victor & Coronado, Semei & Martinez, Jose N. & Venegas-Martínez, Francisco, 2023. "Impact of the global fear index (covid-19 panic) on the S&P global indices associated with natural resources, agribusiness, energy, metals and mining: Granger Causality and Shannon and Rényi Transfer ," MPRA Paper 117138, University Library of Munich, Germany, revised 06 Feb 2023.
    14. Hong, Yanran & Ma, Feng & Wang, Lu & Liang, Chao, 2022. "How does the COVID-19 outbreak affect the causality between gold and the stock market? New evidence from the extreme Granger causality test," Resources Policy, Elsevier, vol. 78(C).
    15. Lin, Boqiang & Zhao, Hengsong, 2023. "Tracking policy uncertainty under climate change," Resources Policy, Elsevier, vol. 83(C).
    16. Badics, Milan Csaba & Huszar, Zsuzsa R. & Kotro, Balazs B., 2023. "The impact of crisis periods and monetary decisions of the Fed and the ECB on the sovereign yield curve network," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 88(C).
    17. Raggad, Bechir, 2021. "Time varying causal relationship between renewable energy consumption, oil prices and economic activity: New evidence from the United States," Resources Policy, Elsevier, vol. 74(C).
    18. Zhou, Xiaoran & Enilov, Martin & Parhi, Mamata, 2024. "Does oil spin the commodity wheel? Quantile connectedness with a common factor error structure across energy and agricultural markets," Energy Economics, Elsevier, vol. 132(C).
    19. Cepni, Oguzhan & Emirmahmutoglu, Furkan & Guney, Ibrahim Ethem & Yilmaz, Muhammed Hasan, 2023. "Do the carry trades respond to geopolitical risks? Evidence from BRICS countries," Economic Systems, Elsevier, vol. 47(2).
    20. Lin, Xudong & Meng, Yiqun & Zhu, Hao, 2023. "How connected is the crypto market risk to investor sentiment?," Finance Research Letters, Elsevier, vol. 56(C).
    21. Pham, Linh & Cepni, Oguzhan, 2022. "Extreme directional spillovers between investor attention and green bond markets," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 186-210.
    22. Liang Xie & Xianzhong Mu & Kuanyuting Lu & Dongou Hu & Guangwen Hu, 2023. "The time-varying relationship between CO2 emissions, heterogeneous energy consumption, and economic growth in China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(8), pages 7769-7793, August.
    23. Harrison, Andre & Liu, Xiaochun & Stewart, Shamar L., 2023. "Structural sources of oil market volatility and correlation dynamics," Energy Economics, Elsevier, vol. 121(C).
    24. Yonglian Wang & Lijun Wang & Changchun Pan, 2022. "Tourism–Growth Nexus in the Presence of Instability," Sustainability, MDPI, vol. 14(4), pages 1-11, February.

  9. 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.

    Cited by:

    1. Sophocles Mavroeidis, 2021. "Identification at the Zero Lower Bound," Econometrica, Econometric Society, vol. 89(6), pages 2855-2885, November.
    2. Belke, Ansgar & Gros, Daniel, 2021. "QE in the euro area: Has the PSPP benefited peripheral bonds?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 73(C).
    3. Aßhoff, Sina & Belke, Ansgar & Osowski, Thomas, 2021. "Unconventional monetary policy and inflation expectations in the Euro area," Economic Modelling, Elsevier, vol. 102(C).
    4. Elien Meuleman & Rudi Vander Vennet, 2020. "Macroprudential policy, monetary policy and Eurozone bank risk," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 20/1004, Ghent University, Faculty of Economics and Business Administration.
    5. Nicolas Soenen & Rudi Vander Vennet, 2020. "ECB Monetary Policy and Bank Default Risk," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 20/997, Ghent University, Faculty of Economics and Business Administration.
    6. Kortela, Tomi & Nelimarkka, Jaakko, 2020. "The effects of conventional and unconventional monetary policy: Identification through the yield curve," Bank of Finland Research Discussion Papers 3/2020, Bank of Finland.
    7. Di Casola, Paola & Stockhammar, Pär, 2021. "When domestic and foreign QE overlap: evidence from Sweden," Working Paper Series 404, Sveriges Riksbank (Central Bank of Sweden).
    8. Martin Baumgärtner & Jens Klose, 2021. "Why central banks announcing liquidity injections is more effective than forward guidance," International Finance, Wiley Blackwell, vol. 24(2), pages 236-256, August.
    9. Cecchetti, Stephen & Feroli, Michael & Kashyap, Anil & Mann, Catherine L. & Schoenholtz, Kermit L., 2020. "Monetary Policy in the Next Recession?," CEPR Discussion Papers 15365, C.E.P.R. Discussion Papers.
    10. Oliver Holtemöller & Alexander Kriwoluzky & Boreum Kwak, 2020. "Exchange Rates and the Information Channel of Monetary Policy," Discussion Papers of DIW Berlin 1906, DIW Berlin, German Institute for Economic Research.
    11. van der Zwan, Terri & Kole, Erik & van der Wel, Michel, 2024. "Heterogeneous macro and financial effects of ECB asset purchase programs," Journal of International Money and Finance, Elsevier, vol. 143(C).
    12. Carvalho, Alexandre & Valle e Azevedo, João & Pires Ribeiro, Pedro, 2024. "Permanent and temporary monetary policy shocks and the dynamics of exchange rates," Journal of International Economics, Elsevier, vol. 147(C).
    13. Holtemöller, Oliver & Kriwoluzky, Alexander & Kwak, Boreum, 2024. "Is there an information channel of monetary policy?," IWH Discussion Papers 17/2020, Halle Institute for Economic Research (IWH), revised 2024.
    14. Fabio Canova & Filippo Ferroni, 2020. "Mind the gap! Stylized Dynamic Facts and Structural Models," Working Paper Series WP-2020-29, Federal Reserve Bank of Chicago.
    15. Lhuissier Stéphane & Nguyen Benoît, 2021. "The Dynamic Effects of the ECB’s Asset Purchases: a Survey-Based Identification," Working papers 806, Banque de France.

  10. Rossi, Barbara, 2019. "Identifying and Estimating the Effects of Unconventional Monetary Policy: How to Do It And What Have We Learned?," CEPR Discussion Papers 14064, C.E.P.R. Discussion Papers.

    Cited by:

    1. Sophocles Mavroeidis, 2021. "Identification at the Zero Lower Bound," Econometrica, Econometric Society, vol. 89(6), pages 2855-2885, November.
    2. Aßhoff, Sina & Belke, Ansgar & Osowski, Thomas, 2021. "Unconventional monetary policy and inflation expectations in the Euro area," Economic Modelling, Elsevier, vol. 102(C).
    3. Elien Meuleman & Rudi Vander Vennet, 2020. "Macroprudential policy, monetary policy and Eurozone bank risk," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 20/1004, Ghent University, Faculty of Economics and Business Administration.
    4. Kortela, Tomi & Nelimarkka, Jaakko, 2020. "The effects of conventional and unconventional monetary policy: Identification through the yield curve," Bank of Finland Research Discussion Papers 3/2020, Bank of Finland.
    5. Martin Baumgärtner & Jens Klose, 2021. "Why central banks announcing liquidity injections is more effective than forward guidance," International Finance, Wiley Blackwell, vol. 24(2), pages 236-256, August.
    6. Cecchetti, Stephen & Feroli, Michael & Kashyap, Anil & Mann, Catherine L. & Schoenholtz, Kermit L., 2020. "Monetary Policy in the Next Recession?," CEPR Discussion Papers 15365, C.E.P.R. Discussion Papers.
    7. Oliver Holtemöller & Alexander Kriwoluzky & Boreum Kwak, 2020. "Exchange Rates and the Information Channel of Monetary Policy," Discussion Papers of DIW Berlin 1906, DIW Berlin, German Institute for Economic Research.
    8. Carvalho, Alexandre & Valle e Azevedo, João & Pires Ribeiro, Pedro, 2024. "Permanent and temporary monetary policy shocks and the dynamics of exchange rates," Journal of International Economics, Elsevier, vol. 147(C).
    9. Holtemöller, Oliver & Kriwoluzky, Alexander & Kwak, Boreum, 2024. "Is there an information channel of monetary policy?," IWH Discussion Papers 17/2020, Halle Institute for Economic Research (IWH), revised 2024.
    10. Fabio Canova & Filippo Ferroni, 2020. "Mind the gap! Stylized Dynamic Facts and Structural Models," Working Paper Series WP-2020-29, Federal Reserve Bank of Chicago.

  11. 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," Working Papers 1947, Banco de España.

    Cited by:

    1. Dalhaus, Tatjana & Schaumburg, Julia & Sekhposyan, Tatevik, 2021. "Networking the yield curve: implications for monetary policy," Working Paper Series 2532, European Central Bank.
    2. Patrick A. Adams & Tobias Adrian & Nina Boyarchenko & Domenico Giannone, 2020. "Forecasting Macroeconomic Risks," Staff Reports 914, Federal Reserve Bank of New York.
    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. De Santis, Roberto A. & Van der Veken, Wouter, 2020. "Forecasting macroeconomic risk in real time: Great and Covid-19 Recessions," Working Paper Series 2436, European Central Bank.
    5. Manzan, Sebastiano, 2021. "Are professional forecasters Bayesian?," Journal of Economic Dynamics and Control, Elsevier, vol. 123(C).
    6. Clements, Michael P., 2021. "Rounding behaviour of professional macro-forecasters," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1614-1631.
    7. Fabian Kruger & Hendrik Plett, 2022. "Prediction intervals for economic fixed-event forecasts," Papers 2210.13562, arXiv.org, revised Mar 2024.

  12. Atsushi Inoue & Barbara Rossi, 2018. "The Effects of Conventional and Unconventional Monetary Policy on Exchange Rates," Working Papers 1078, Barcelona School of Economics.

    Cited by:

    1. Bhattarai, Saroj & Chatterjee, Arpita & Park, Woong Yong, 2018. "Effects of US Quantitative Easing on Emerging Market Economies," ADBI Working Papers 803, Asian Development Bank Institute.
    2. Refet S. Gürkaynak & Burcin Kisacikoglu & Sang Seok Lee, 2022. "Exchange Rate and Inflation under Weak Monetary Policy: Turkey Verifies Theory," CESifo Working Paper Series 9748, CESifo.
    3. Callum Jones & Mariano Kulish & Daniel M. Rees, 2018. "International Spillovers of Forward Guidance Shocks," IMF Working Papers 2018/114, International Monetary Fund.
    4. Philipp Hartman & Frank Smets, 2018. "The European Central Bank’s Monetary Policy during Its First 20 Years," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 49(2 (Fall)), pages 1-146.
    5. Gelfer, Sacha & Gibbs, Christopher G., 2023. "Measuring the effects of large-scale asset purchases: The role of international financial markets and the financial accelerator," Journal of International Money and Finance, Elsevier, vol. 131(C).
    6. De Santis, Roberto A., 2020. "Impact of the Asset Purchase Programme on euro area government bond yields using market news," Economic Modelling, Elsevier, vol. 86(C), pages 192-209.
    7. Daisuke Ikeda & Shangshang Li & Sophocles Mavroeidis & Francesco Zanetti, 2020. "Testing the Effectiveness of Unconventional Monetary Policy in Japan and the United States," IMES Discussion Paper Series 20-E-10, Institute for Monetary and Economic Studies, Bank of Japan.
    8. Albagli, Elias & Ceballos, Luis & Claro, Sebastian & Romero, Damian, 2024. "UIP deviations: Insights from event studies," Journal of International Economics, Elsevier, vol. 148(C).
    9. Hassanniakalager, Arman & Sermpinis, Georgios & Stasinakis, Charalampos, 2021. "Trading the foreign exchange market with technical analysis and Bayesian Statistics," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 230-251.
    10. Silvia Miranda-Agrippino & Tsvetelina Nenova, 2021. "A Tale of Two Global Monetary Policies," NBER Chapters, in: NBER International Seminar on Macroeconomics 2021, National Bureau of Economic Research, Inc.
    11. Rasmus Fatum & Naoko Hara & Yohei Yamamoto, 2019. "Negative Interest Rate Policy and the Influence of Macroeconomic News on Yields," IMES Discussion Paper Series 19-E-02, Institute for Monetary and Economic Studies, Bank of Japan.
    12. Kerstin Bernoth & Helmut Herwartz & Lasse Trienens, 2023. "The Impacts of Global Risk and US Monetary Policy on US Dollar Exchange Rates and Excess Currency Returns," Discussion Papers of DIW Berlin 2037, DIW Berlin, German Institute for Economic Research.
    13. Pinchetti, Marco & Szczepaniak, Andrzej, 2021. "Global spillovers of the Fed information effect," Bank of England working papers 952, Bank of England.
    14. Maximilian Böck & Martin Feldkircher & Pierre L. Siklos, 2021. "International Effects of Euro Area Forward Guidance," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(5), pages 1066-1110, October.
    15. Jorge Fornero & Markus Kirchner & Carlos Molina, 2021. "Estimating Shadow Policy Rates in a Small Open Economy and the Role of Foreign Factors," Working Papers Central Bank of Chile 915, Central Bank of Chile.
    16. 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.
    17. Dalhaus, Tatjana & Schaumburg, Julia & Sekhposyan, Tatevik, 2021. "Networking the yield curve: implications for monetary policy," Working Paper Series 2532, European Central Bank.
    18. Ca' Zorzi, Michele & Dedola, Luca & Georgiadis, Georgios & Jarociński, Marek & Stracca, Livio & Strasser, Georg, 2020. "Monetary policy and its transmission in a globalised world," Working Paper Series 2407, European Central Bank.
    19. Teti̇k, Metin, 2020. "Testing of leader-follower interaction between fed and emerging countries’ central banks," The Journal of Economic Asymmetries, Elsevier, vol. 22(C).
    20. Gábor Dávid Kiss & Mercédesz Mészáros, 2020. "Gravity Among Central Bank Balance Sheets: Monetary Policy Spill-Over on FX Volatility," Econometric Research in Finance, SGH Warsaw School of Economics, Collegium of Economic Analysis, vol. 5(1), pages 33-57, June.
    21. Kortela, Tomi & Nelimarkka, Jaakko, 2020. "The effects of conventional and unconventional monetary policy: Identification through the yield curve," Bank of Finland Research Discussion Papers 3/2020, Bank of Finland.
    22. Radeef Chundakkadan & Subash Sasidharan, 2022. "Monetary Policy Announcement and Stock Returns - Evidence From Long-Term Repo Operations in India," Asian Economics Letters, Asia-Pacific Applied Economics Association, vol. 3(2), pages 1-6.
    23. Eo, Yunjong & Kang, Kyu Ho, 2020. "The effects of conventional and unconventional monetary policy on forecasting the yield curve," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    24. Chunya Bu & John Rogers & Wenbin Wu, 2019. "A Unified Measure of Fed Monetary Policy Shocks," Finance and Economics Discussion Series 2019-043, Board of Governors of the Federal Reserve System (U.S.).
    25. Julian di Giovanni & Galina Hale, 2020. "Stock Market Spillovers Via the Global Production Network: Transmission of U.S. Monetary Policy," Working Papers 1213, Barcelona School of Economics.
    26. Carlos Esteban Posada, 2023. "Inflation targeting strategy and its credibility," Papers 2301.11207, arXiv.org.
    27. Schmitt-Grohé, Stephanie & Uribe, Martín, 2022. "The effects of permanent monetary shocks on exchange rates and uncovered interest rate differentials," Journal of International Economics, Elsevier, vol. 135(C).
    28. Prabheesh, K.P. & Padhan, Rakesh & Bhat, Javed Ahmad, 2024. "Do financial markets react to emerging economies’ asset purchase program? Evidence from the COVID-19 pandemic period," Journal of Asian Economics, Elsevier, vol. 90(C).
    29. 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).
    30. Itamar Caspi & Amit Friedman & Sigal Ribon, 2024. "Shocks and Currents: Monetary Policy and Israel’s Foreign Exchange Market," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 66(3), pages 454-481, September.
    31. Rüth, Sebastian K., 2020. "Shifts in monetary policy and exchange rate dynamics: Is Dornbusch's overshooting hypothesis intact, after all?," Journal of International Economics, Elsevier, vol. 126(C).
    32. Shixuan Wang & Rangan Gupta & Matteo Bonato & Oguzhan Cepni, 2022. "The Effects of Conventional and Unconventional Monetary Policy Shocks on US REITs Moments: Evidence from VARs with Functional Shocks," Working Papers 202219, University of Pretoria, Department of Economics.
    33. Brubakk, Leif & ter Ellen, Saskia & Robstad, Ørjan & Xu, Hong, 2019. "The macroeconomic effects of forward communication," Working Paper 2019/20, Norges Bank.
    34. Behera, Harendra & Gunadi, Iman & Rath, Badri Narayan, 2023. "COVID-19 uncertainty, financial markets and monetary policy effects in case of two emerging Asian countries," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 173-189.
    35. Thi Bich Ngoc Tran & Hoang Cam Huong Pham, 2020. "The Spillover Effects of the US Unconventional Monetary Policy: New Evidence from Asian Developing Countries," JRFM, MDPI, vol. 13(8), pages 1-26, July.
    36. Shahriyar Aliyev & Evžen Kočenda, 2023. "ECB monetary policy and commodity prices," Review of International Economics, Wiley Blackwell, vol. 31(1), pages 274-304, February.
    37. Daniel Gründler & Eric Mayer & Johann Scharler, 2021. "Monetary Policy Announcements, Information Schocks, and Exchange Rate Dynamics," Working Papers 2021-16, Faculty of Economics and Statistics, Universität Innsbruck.
    38. 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).
    39. Mirela Miescu, 2022. "Forward guidance shocks," Working Papers 352591340, Lancaster University Management School, Economics Department.
    40. Zoe Venter, 2019. "The Interaction Between ConventionalMonetary Policy and Financial Stability: Chile, Colombia, Japan, Portugal and the UK," Working Papers REM 2019/96, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    41. Eva Ortega & Chiara Osbat, 2020. "Exchange rate pass-through in the euro area and EU countries," Occasional Papers 2016, Banco de España.
    42. Oliver Holtemöller & Alexander Kriwoluzky & Boreum Kwak, 2020. "Exchange Rates and the Information Channel of Monetary Policy," Discussion Papers of DIW Berlin 1906, DIW Berlin, German Institute for Economic Research.
    43. Wei, Xiaoyun & Han, Liyan, 2021. "The impact of COVID-19 pandemic on transmission of monetary policy to financial markets," International Review of Financial Analysis, Elsevier, vol. 74(C).
    44. 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.).
    45. Coenen, Günter & Montes-Galdón, Carlos & Saint Guilhem, Arthur & Hutchinson, John & Motto, Roberto, 2022. "Rate forward guidance in an environment of large central bank balance sheets: a Eurosystem stock-taking assessment," Occasional Paper Series 290, European Central Bank.
    46. Holtemöller, Oliver & Kriwoluzky, Alexander & Kwak, Boreum, 2024. "Is there an information channel of monetary policy?," IWH Discussion Papers 17/2020, Halle Institute for Economic Research (IWH), revised 2024.
    47. De Rezende, Rafael B. & Ristiniemi, Annukka, 2018. "A shadow rate without a lower bound constraint," Working Paper Series 355, Sveriges Riksbank (Central Bank of Sweden).
    48. Gan‐Ochir Doojav & Davaasukh Damdinjav, 2023. "The macroeconomic effects of unconventional monetary policies in a commodity‐exporting economy: Evidence from Mongolia," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 4627-4654, October.
    49. David KRIZEK & Josef BRCAK, 2021. "Support for export as a non-standard Central Bank policy: foreign exchange interventions in the case of the Czech Republic," Eastern Journal of European Studies, Centre for European Studies, Alexandru Ioan Cuza University, vol. 12, pages 191-218, June.
    50. Luo, Tao & Sun, Huaping & Zhang, Lixia & Bai, Jiancheng, 2024. "Do the dynamics of macroeconomic attention drive the yen/dollar exchange market volatility?," International Review of Economics & Finance, Elsevier, vol. 89(PB), pages 597-611.
    51. Luisa Corrado & Stefano Grassi & Enrico Minnella, 2021. "The Transmission Mechanism of Quantitative Easing: A Markov-Switching FAVAR Approach," CEIS Research Paper 520, Tor Vergata University, CEIS, revised 21 Oct 2021.
    52. Ryuzo Miyao & Tatsuyoshi Okimoto, 2020. "Regime shifts in the effects of Japan’s unconventional monetary policies," Manchester School, University of Manchester, vol. 88(6), pages 749-772, December.
    53. Stavrakeva, Vania & Tang, Jenny, 2019. "The Dollar During the Great Recession: US Monetary Policy Signaling and The Flight To Safety," CEPR Discussion Papers 14034, C.E.P.R. Discussion Papers.
    54. Jean-Guillaume Sahuc & Grégory Levieuge & José Garcia-Revelo, 2024. "Revisiting 15 Years of Unusual Transatlantic Monetary Policies," Working Papers hal-04563708, HAL.
    55. Stylianos Asimakopoulos & Marco Lorusso & Francesco Ravazzolo, 2023. "A Bayesian DSGE Approach to Modelling Cryptocurrency," Working Papers No 09/2023, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    56. Lucélia Vaz & Rodrigo Raad, 2021. "Functional data analysis for brazilian term structure of interest rate," Textos para Discussão Cedeplar-UFMG 638, Cedeplar, Universidade Federal de Minas Gerais.
    57. Bernoth, Kerstin & Herwartz, Helmut & Trienens, Lasse, 2024. "Interest Rates, Global Risk and Inflation Expectations: Drivers of US Dollar Exchange Rates," VfS Annual Conference 2024 (Berlin): Upcoming Labor Market Challenges 302351, Verein für Socialpolitik / German Economic Association.
    58. Yusuke Tanahara & Kento Tango & Yoshiyuki Nakazono, 2023. "Information Effects of Monetary Policy," TUPD Discussion Papers 41, Graduate School of Economics and Management, Tohoku University.
    59. Nagao, Ryoya & Kondo, Yoshihiro & Nakazono, Yoshiyuki, 2021. "The macroeconomic effects of monetary policy: Evidence from Japan," Journal of the Japanese and International Economies, Elsevier, vol. 61(C).
    60. Dr. Enzo Rossi & Vincent Wolff, 2020. "Spillovers to exchange rates from monetary and macroeconomic communications events," Working Papers 2020-18, Swiss National Bank.
    61. Chaturvedi, Priya & Kumar, Kuldeep, 2022. "Econometric modelling of exchange rate volatility using mixed-frequency data," MPRA Paper 115222, University Library of Munich, Germany.
    62. Dossani, Asad, 2024. "Monetary policy and currency variance risk premia," Research in International Business and Finance, Elsevier, vol. 69(C).
    63. Kim, Kyoung-Gon, 2022. "Financial Crisis and the Global Transmission of U.S. Monetary Policy Surprises," Hitotsubashi Journal of Economics, Hitotsubashi University, vol. 63(2), pages 104-125, December.
    64. Yang, Jinyu & Dong, Dayong & Liang, Chao & Cao, Yang, 2024. "Monetary policy uncertainty and the price bubbles in energy markets," Energy Economics, Elsevier, vol. 133(C).
    65. Meng, Xiangcai & Huang, Chia-Hsing, 2021. "The time-frequency analysis of conventional and unconventional monetary policy: Evidence from Japan," Japan and the World Economy, Elsevier, vol. 59(C).
    66. Ur Rehman, Mobeen & Al Rababa'a, Abdel Razzaq & El-Nader, Ghaith & Alkhataybeh, Ahmad & Vo, Xuan Vinh, 2022. "Modelling the quantile cross-coherence between exchange rates: Does the COVID-19 pandemic change the interlinkage structure?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 76(C).
    67. Daniel J. Lewis, 2019. "Announcement-Specific Decompositions of Unconventional Monetary Policy Shocks and Their Macroeconomic Effects," Staff Reports 891, Federal Reserve Bank of New York.
    68. Wan Wei & Susan Pozo & Evan Lau, 2021. "The effects of conventional and unconventional monetary policy on exchange rate volatility," Cogent Economics & Finance, Taylor & Francis Journals, vol. 9(1), pages 1997425-199, January.

  13. Gergely Ganics & Atsushi Inoue & Barbara Rossi, 2018. "Confidence intervals for bias and size distortion in IV and local projections — IV models," Working Papers 1841, Banco de España.

    Cited by:

    1. Barbara Rossi & Atsushi Inoue & Yiru Wang, 2024. "Has the Phillips curve flattened?," French Stata Users' Group Meetings 2024 22, Stata Users Group.
    2. Germano Ruisi, 2019. "Time-Varying Local Projections," Working Papers 891, Queen Mary University of London, School of Economics and Finance.
    3. Gergely Ganics & Atsushi Inoue & Barbara Rossi, 2018. "Confidence Intervals for Bias and Size Distortion in IV and Local Projections–IV Models," Working Papers 1077, Barcelona School of Economics.
    4. Christis Katsouris, 2023. "Structural Analysis of Vector Autoregressive Models," Papers 2312.06402, arXiv.org, revised Feb 2024.
    5. Daniel J. Lewis & Karel Mertens, 2022. "A Robust Test for Weak Instruments for 2SLS with Multiple Endogenous Regressors," Working Papers 2208, Federal Reserve Bank of Dallas, revised 26 Sep 2024.
    6. Rossi, Barbara, 2019. "Identifying and Estimating the Effects of Unconventional Monetary Policy: How to Do It And What Have We Learned?," CEPR Discussion Papers 14064, C.E.P.R. Discussion Papers.
    7. Barbara Rossi, 2018. "Identifying and estimating the effects of unconventional monetary policy in the data: How to do It and what have we learned?," Economics Working Papers 1641, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2020.
    8. Daniel J. Lewis & Karel Mertens, 2022. "A Robust Test for Weak Instruments with Multiple Endogenous Regressors," Staff Reports 1020, Federal Reserve Bank of New York.
    9. Zhenhong Huang & Chen Wang & Jianfeng Yao, 2023. "The First-stage F Test with Many Weak Instruments," Papers 2302.14423, arXiv.org, revised Sep 2024.

  14. Barbara Rossi & Tatevik Sekhposyan & Matthieu Soupre, 2016. "Understanding the Sources of Macroeconomic Uncertainty," Working Papers 920, Barcelona School of Economics.

    Cited by:

    1. Bush, Georgia & López Noria, Gabriela, 2021. "Uncertainty and exchange rate volatility: Evidence from Mexico," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 704-722.
    2. Pierdzioch Christian & Gupta Rangan, 2020. "Uncertainty and Forecasts of U.S. Recessions," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(4), pages 1-20, September.
    3. Giovanni Dosi & Mauro Napoletano & Andrea Roventini & Joseph E. Stiglitz & Tania Treibich, 2020. "Rational Heuristics? Expectations And Behaviors In Evolving Economies With Heterogeneous Interacting Agents," Economic Inquiry, Western Economic Association International, vol. 58(3), pages 1487-1516, July.
    4. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2019. "Assessing International Commonality in Macroeconomic Uncertainty and Its Effects," Working Papers 18-03R, Federal Reserve Bank of Cleveland.
    5. Goodness C. Aye & Rangan Gupta, 2019. "Macroeconomic Uncertainty And The Comovement In Buying Versus Renting In The Usa," Advances in Decision Sciences, Asia University, Taiwan, vol. 23(3), pages 93-121, September.
    6. Sumru Altug & Cem Cakmakli & Fabrice Collard & Sujoy Mukerji & Han Ozsoylev, 2020. "Ambiguous Business Cycles: A Quantitative Assessment," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 38, pages 220-237, October.
    7. Ana Beatriz Galvão & James Mitchell, 2019. "Measuring Data Uncertainty: An Application using the Bank of England's "Fan Charts" for Historical GDP Growth," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2019-08, Economic Statistics Centre of Excellence (ESCoE).
    8. 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.
    9. Artur Tarassow, 2017. "Forecasting growth of U.S. aggregate and household-sector M2 after 2000 using economic uncertainty measures," Macroeconomics and Finance Series 201702, University of Hamburg, Department of Socioeconomics.
    10. 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.
    11. Ana Beatriz Galvão & James Mitchell, 2023. "Real‐Time Perceptions of Historical GDP Data Uncertainty," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 457-481, June.
    12. Ibrahim D. Raheem & Sara le Roux & Simplice A. Asongu, 2019. "The Role of Asymmetry and Uncertainties in the Capital Flows- Economic Growth Nexus," Working Papers of the African Governance and Development Institute. 19/047, African Governance and Development Institute..
    13. Petar Sorić & Blanka Škrabić Perić & Marina Matošec, 2022. "Breaking new grounds: a fresh insight into the leading properties of business and consumer survey indicators," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(6), pages 4511-4535, December.
    14. Evren Erdogan Cosar & Sayg�n Sahinoz, 2018. "Quantifying Uncertainty and Identifying its Impacts on the Turkish Economy," Working Papers 1806, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    15. Yin, Libo & Su, Zhi & Lu, Man, 2022. "Is oil risk important for commodity-related currency returns?," Research in International Business and Finance, Elsevier, vol. 60(C).
    16. Galvao, Ana Beatriz & Mitchell, James, 2020. "Real-Time Perceptions of Historical GDP Data Uncertainty," EMF Research Papers 35, Economic Modelling and Forecasting Group.
    17. Ferrara, L. & Istrefi, K., 2016. "Impact des chocs d’incertitude sur l’économie mondiale – Synthèse de conférence," Bulletin de la Banque de France, Banque de France, issue 206, pages 61-68.
    18. Nowzohour, Laura & Stracca, Livio, 2017. "More than a feeling: confidence, uncertainty and macroeconomic fluctuations," Working Paper Series 2100, European Central Bank.
    19. Galvao, Ana Beatriz & Mitchell, James, 2019. "Measuring Data Uncertainty : An Application using the Bank of England’s “Fan Charts” for Historical GDP Growth," EMF Research Papers 24, Economic Modelling and Forecasting Group.
    20. Danilo Cascaldi-Garcia & Ana Beatriz Galvao, 2018. "News and Uncertainty Shocks," International Finance Discussion Papers 1240, Board of Governors of the Federal Reserve System (U.S.).
    21. Berg, Kimberly A. & Mark, Nelson C., 2018. "Measures of global uncertainty and carry-trade excess returns," Journal of International Money and Finance, Elsevier, vol. 88(C), pages 212-227.
    22. Meinen, Philipp & Röhe, Oke, 2016. "On measuring uncertainty and its impact on investment: Cross-country evidence from the euro area," Discussion Papers 48/2016, Deutsche Bundesbank.
    23. Barbara Rossi & Tatevik Sekhposyan & Matthieu Soupre, 2016. "Understanding the sources of macroeconomic uncertainty," Economics Working Papers 1531, Department of Economics and Business, Universitat Pompeu Fabra, revised Dec 2018.
    24. Maxime Leroux & Rachidi Kotchoni & Dalibor Stevanovic, 2017. "Forecasting economic activity in data-rich environment," Working Papers hal-04141668, HAL.
    25. Douglas de Medeiros Franco, 2022. "Expectations, Economic Uncertainty, and Sentiment," RAC - Revista de Administração Contemporânea (Journal of Contemporary Administration), ANPAD - Associação Nacional de Pós-Graduação e Pesquisa em Administração, vol. 26(5), pages 210029-2100.
    26. Goodness C. Aye & Rangan Gupta, 2018. "Macroeconomic Uncertainty and the Comovement in Buying versus Renting in the United States," Working Papers 201832, University of Pretoria, Department of Economics.
    27. Barbara Rossi & Tatevik Sekhposyan, 2017. "Macroeconomic uncertainty indices for the Euro Area and its individual member countries," Empirical Economics, Springer, vol. 53(1), pages 41-62, August.
    28. Ambrocio, Gene, 2019. "Measuring household uncertainty in EU countries," Bank of Finland Research Discussion Papers 17/2019, Bank of Finland.
    29. Bucci, Andrea & Palomba, Giulio & Rossi, Eduardo, 2023. "The role of uncertainty in forecasting volatility comovements across stock markets," Economic Modelling, Elsevier, vol. 125(C).
    30. Barnett, William & Ftiti, Zied & Jawadi, Fredj, 2018. "The Causal Relationships between Inflation and Inflation Uncertainty," MPRA Paper 86478, University Library of Munich, Germany.
    31. Ambrocio, Gene, 2017. "The real effects of overconfidence and fundamental uncertainty shocks," Bank of Finland Research Discussion Papers 37/2017, Bank of Finland.
    32. Wojciech CHAREMZA & Carlos DÍAZ & Svetlana MAKAROVA, 2019. "Conditional Term Structure of Inflation Forecast Uncertainty: The Copula Approach," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 5-18, March.
    33. MORIKAWA Masayuki, 2022. "Firms' Knightian Uncertainty during the COVID-19 Crisis," Discussion papers 22089, Research Institute of Economy, Trade and Industry (RIETI).
    34. Ambrocio, Gene, 2020. "Inflationary household uncertainty shocks," Bank of Finland Research Discussion Papers 5/2020, Bank of Finland.
    35. Cascaldi-Garcia, Danilo & Galvao, Ana Beatriz, 2016. "News and Uncertainty Shocks," EMF Research Papers 12, Economic Modelling and Forecasting Group.
    36. MORIKAWA Masayuki, 2018. "Measuring Firm-level Uncertainty: New evidence from a business outlook survey," Discussion papers 18030, Research Institute of Economy, Trade and Industry (RIETI).
    37. Helena Chuliá & Rangan Gupta & Jorge M. Uribe & Mark E. Wohar, 2016. "Impact of US Uncertainties on Emerging and Mature Markets: Evidence from a Quantile-Vector Autoregressive Approach," Working Papers 201656, University of Pretoria, Department of Economics.
    38. Gupta, Rangan & Ma, Jun & Risse, Marian & Wohar, Mark E., 2018. "Common business cycles and volatilities in US states and MSAs: The role of economic uncertainty," Journal of Macroeconomics, Elsevier, vol. 57(C), pages 317-337.
    39. Jonas Dovern & Geoff Kenny, 2020. "Anchoring Inflation Expectations in Unconventional Times: Micro Evidence for the Euro Area," International Journal of Central Banking, International Journal of Central Banking, vol. 16(5), pages 309-347, October.
    40. Graziano Moramarco, 2022. "Measuring Global Macroeconomic Uncertainty and Cross-Country Uncertainty Spillovers," Econometrics, MDPI, vol. 11(1), pages 1-29, December.
    41. Laurentiu Dumitru ANDREI & Petre BREZEANU, 2019. "Optimizing the Financial Structure of the State Treasury in Romania," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 180-195, June.
    42. Rangan Gupta & Chi Keung Marco Lau & Mark E. Wohar, 2016. "The Impact of US Uncertainty on the Euro Area in Good and Bad Times: Evidence from a Quantile Structural Vector Autoregressive Model," Working Papers 201681, University of Pretoria, Department of Economics.
    43. Carola Binder & Tucker S. Mcelroy & Xuguang S. Sheng, 2022. "The Term Structure of Uncertainty: New Evidence from Survey Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(1), pages 39-71, February.
    44. Saskia ter Ellen & Willem F.C. Verschoor & Remco C.J. Zwinkels, 2016. "Agreeing on disagreement: heterogeneity or uncertainty?," Working Paper 2016/4, Norges Bank.
    45. Ismailov, Adilzhan & Rossi, Barbara, 2018. "Uncertainty and deviations from uncovered interest rate parity," Journal of International Money and Finance, Elsevier, vol. 88(C), pages 242-259.

  15. Rossi, Barbara & Carrasco, Marine, 2016. "In-sample Inference and Forecasting in Misspecified Factor Models," CEPR Discussion Papers 11388, C.E.P.R. Discussion Papers.

    Cited by:

    1. Oxana Babecka Kucharcukova & Jan Bruha, 2016. "Nowcasting the Czech Trade Balance," Working Papers 2016/11, Czech National Bank.
    2. Andrii Babii & Eric Ghysels & Jonas Striaukas, 2022. "Machine Learning Time Series Regressions With an Application to Nowcasting," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 1094-1106, June.
    3. Rahul Singh, 2021. "Kernel Ridge Riesz Representers: Generalization, Mis-specification, and the Counterfactual Effective Dimension," Papers 2102.11076, arXiv.org, revised Jul 2024.
    4. Manuel Lukas & Eric Hillebrand, 2014. "Bagging Weak Predictors," CREATES Research Papers 2014-01, Department of Economics and Business Economics, Aarhus University.
    5. Chen, Qitong & Hong, Yongmiao & Li, Haiqi, 2024. "Time-varying forecast combination for factor-augmented regressions with smooth structural changes," Journal of Econometrics, Elsevier, vol. 240(1).
    6. Andrii Babii & Eric Ghysels & Jonas Striaukas, 2024. "High-Dimensional Granger Causality Tests with an Application to VIX and News," Journal of Financial Econometrics, Oxford University Press, vol. 22(3), pages 605-635.
    7. Galbraith, John W. & Zinde-Walsh, Victoria, 2020. "Simple and reliable estimators of coefficients of interest in a model with high-dimensional confounding effects," Journal of Econometrics, Elsevier, vol. 218(2), pages 609-632.
    8. 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.
    9. Luca Barbaglia & Sebastiano Manzan & Elisa Tosetti, 2023. "Forecasting Loan Default in Europe with Machine Learning," Journal of Financial Econometrics, Oxford University Press, vol. 21(2), pages 569-596.
    10. Laurent Ferrara & Anna Simoni, 2020. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," EconomiX Working Papers 2020-11, University of Paris Nanterre, EconomiX.
    11. Matteo Mogliani & Anna Simoni, 2020. "Bayesian MIDAS penalized regressions: Estimation, selection, and prediction," Post-Print hal-03089878, HAL.
    12. Norman R. Swanson & Weiqi Xiong, 2018. "Big data analytics in economics: What have we learned so far, and where should we go from here?," Canadian Journal of Economics, Canadian Economics Association, vol. 51(3), pages 695-746, August.
    13. Andrii Babii & Eric Ghysels & Jonas Striaukas, 2023. "Econometrics of Machine Learning Methods in Economic Forecasting," Papers 2308.10993, arXiv.org.
    14. Kihwan Kim & Hyun Hak Kim & Norman R. Swanson, 2023. "Mixing mixed frequency and diffusion indices in good times and in bad: an assessment based on historical data around the great recession of 2008," Empirical Economics, Springer, vol. 64(3), pages 1421-1469, March.
    15. Antoine A. Djogbenou, 2021. "Model selection in factor-augmented regressions with estimated factors," Econometric Reviews, Taylor & Francis Journals, vol. 40(5), pages 470-503, April.
    16. Marine Carrasco & Guy Tchuente, 2016. "Regularization Based Anderson Rubin Tests for Many Instruments," Studies in Economics 1608, School of Economics, University of Kent.
    17. Andrii Babii & Marine Carrasco & Idriss Tsafack, 2024. "Functional Partial Least-Squares: Optimal Rates and Adaptation," Papers 2402.11134, arXiv.org.
    18. Rachidi Kotchoni & Maxime Leroux & Dalibor Stevanovic, 2019. "Macroeconomic Forecast Accuracy in data-rich environment," Post-Print hal-02435757, HAL.
    19. Marijn A. Bolhuis & Brett Rayner, 2020. "Deus ex Machina? A Framework for Macro Forecasting with Machine Learning," IMF Working Papers 2020/045, International Monetary Fund.
    20. Norman R. Swanson & Weiqi Xiong & Xiye Yang, 2020. "Predicting interest rates using shrinkage methods, real‐time diffusion indexes, and model combinations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(5), pages 587-613, August.
    21. Pablo Guerrón-Quintana & Alexey Khazanov & Molin Zhong, 2023. "Financial and Macroeconomic Data Through the Lens of a Nonlinear Dynamic Factor Model," Finance and Economics Discussion Series 2023-027, Board of Governors of the Federal Reserve System (U.S.).
    22. Wang, Yudong & Pan, Zhiyuan & Liu, Li & Wu, Chongfeng, 2019. "Oil price increases and the predictability of equity premium," Journal of Banking & Finance, Elsevier, vol. 102(C), pages 43-58.
    23. Smeekes, Stephan & Wijler, Etiënne, 2016. "Macroeconomic Forecasting Using Penalized Regression Methods," Research Memorandum 039, Maastricht University, Graduate School of Business and Economics (GSBE).
    24. Iason Kynigakis & Ekaterini Panopoulou, 2022. "Does model complexity add value to asset allocation? Evidence from machine learning forecasting models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(3), pages 603-639, April.
    25. Yousuf, Kashif & Ng, Serena, 2021. "Boosting high dimensional predictive regressions with time varying parameters," Journal of Econometrics, Elsevier, vol. 224(1), pages 60-87.
    26. Rahul Singh, 2020. "Kernel Methods for Unobserved Confounding: Negative Controls, Proxies, and Instruments," Papers 2012.10315, arXiv.org, revised Mar 2023.
    27. Zhang, Qin & Ni, He & Xu, Hao, 2023. "Nowcasting Chinese GDP in a data-rich environment: Lessons from machine learning algorithms," Economic Modelling, Elsevier, vol. 122(C).
    28. James H. Stock & Mark W. Watson, 2017. "Twenty Years of Time Series Econometrics in Ten Pictures," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 59-86, Spring.
    29. Rahul Singh & Liyuan Xu & Arthur Gretton, 2020. "Kernel Methods for Causal Functions: Dose, Heterogeneous, and Incremental Response Curves," Papers 2010.04855, arXiv.org, revised Oct 2022.
    30. Cheng, Mingmian & Swanson, Norman R. & Yang, Xiye, 2021. "Forecasting volatility using double shrinkage methods," Journal of Empirical Finance, Elsevier, vol. 62(C), pages 46-61.

  16. Barbara Rossi & Tatevik Sekhposyan, 2015. "Macroeconomic uncertainty indices based on nowcast and forecast error distributions," Economics Working Papers 1477, Department of Economics and Business, Universitat Pompeu Fabra.

    Cited by:

    1. Chatterjee Pratiti, 2019. "Asymmetric impact of uncertainty in recessions: are emerging countries more vulnerable?," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 23(2), pages 1-27, April.
    2. 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.
    3. Angus Moore, 2016. "Measuring Economic Uncertainty and Its Effects," RBA Research Discussion Papers rdp2016-01, Reserve Bank of Australia.
    4. Pratiti Chatterjee & Fabio Milani, 2020. "Perceived Uncertainty Shocks, Excess Optimism-Pessimism, and Learning in the Business Cycle," Working Papers 202101, University of California-Irvine, Department of Economics.
    5. Michael Clements, 2016. "Are Macroeconomic Density Forecasts Informative?," ICMA Centre Discussion Papers in Finance icma-dp2016-02, Henley Business School, University of Reading.
    6. Laurent Ferrara & Stéphane Lhuissier & Fabien Tripier, 2017. "Uncertainty Fluctuations: Measures, Effects and Macroeconomic Policy Challenges," CEPII Policy Brief 2017-20, CEPII research center.
    7. Jackson Laura E. & Kliesen Kevin L. & Owyang Michael T., 2020. "The nonlinear effects of uncertainty shocks," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(4), pages 1-19, September.
    8. Bonciani, Dario, 2015. "Estimating the effects of uncertainty over the business cycle," MPRA Paper 65921, University Library of Munich, Germany.
    9. Granziera, Eleonora & Sekhposyan, Tatevik, 2019. "Predicting relative forecasting performance: An empirical investigation," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1636-1657.
    10. 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.
    11. Pierdzioch Christian & Gupta Rangan, 2020. "Uncertainty and Forecasts of U.S. Recessions," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(4), pages 1-20, September.
    12. Jonathan Benchimol & Makram El-Shagi & Yossi Saadon, 2020. "Do Expert Experience and Characteristics Affect Inflation Forecasts?," Bank of Israel Working Papers 2020.11, Bank of Israel.
    13. Markus Leippold & Felix Matthys, 2022. "Economic Policy Uncertainty and the Yield Curve [Pricing the term structure with linear regressions]," Review of Finance, European Finance Association, vol. 26(4), pages 751-797.
    14. Jingjing Xu, 2022. "Does culture play a role in the stock market's response to uncertainty?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 2530-2548, April.
    15. Berg, Tim Oliver, 2019. "Business Uncertainty And The Effectiveness Of Fiscal Policy In Germany," Macroeconomic Dynamics, Cambridge University Press, vol. 23(4), pages 1442-1470, June.
    16. Fabio Bertolotti & Massimiliano Marcellino, 2019. "Tax shocks with high and low uncertainty," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(6), pages 972-993, September.
    17. Meinen, Philipp & Röhe, Oke, 2018. "To sign or not to sign? On the response of prices to financial and uncertainty shocks," Discussion Papers 33/2018, Deutsche Bundesbank.
    18. 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.
    19. Laurent Ferrara & Pierre Guérin, 2015. "What Are The Macroeconomic Effects of High-Frequency Uncertainty Shocks?," EconomiX Working Papers 2015-12, University of Paris Nanterre, EconomiX.
    20. Cross, Jamie L. & Hou, Chenghan & Koop, Gary & Poon, Aubrey, 2023. "Large stochastic volatility in mean VARs," Journal of Econometrics, Elsevier, vol. 236(1).
    21. Balcilar, Mehmet & Demirer, Riza & Gupta, Rangan & van Eyden, Reneé, 2017. "The impact of US policy uncertainty on the monetary effectiveness in the Euro area," Journal of Policy Modeling, Elsevier, vol. 39(6), pages 1052-1064.
    22. Luca Rossi, 2020. "Indicators of uncertainty: a brief user’s guide," Questioni di Economia e Finanza (Occasional Papers) 564, Bank of Italy, Economic Research and International Relations Area.
    23. Goodness C. Aye & Rangan Gupta, 2019. "Macroeconomic Uncertainty And The Comovement In Buying Versus Renting In The Usa," Advances in Decision Sciences, Asia University, Taiwan, vol. 23(3), pages 93-121, September.
    24. Bonciani, Dario & Ricci, Martino, 2020. "The global effects of global risk and uncertainty," Bank of England working papers 863, Bank of England.
    25. Oscar Claveria, 2021. "Uncertainty indicators based on expectations of business and consumer surveys," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 48(2), pages 483-505, May.
    26. Mirela Miescu, 2019. "Uncertainty shocks in emerging economies," Working Papers 277077821, Lancaster University Management School, Economics Department.
    27. Olli Palm'en, 2022. "Macroeconomic Effect of Uncertainty and Financial Shocks: a non-Gaussian VAR approach," Papers 2202.10834, arXiv.org.
    28. Efrem Castelnuovo & Trung Duc Tran, 2017. "Google It Up! A Google Trends-based Uncertainty Index for the United States and Australia," CESifo Working Paper Series 6695, CESifo.
    29. Miescu, Mirela S., 2023. "Uncertainty shocks in emerging economies: A global to local approach for identification," European Economic Review, Elsevier, vol. 154(C).
    30. Ana Beatriz Galvão & James Mitchell, 2019. "Measuring Data Uncertainty: An Application using the Bank of England's "Fan Charts" for Historical GDP Growth," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2019-08, Economic Statistics Centre of Excellence (ESCoE).
    31. Wensheng Kang & Ronald A. Ratti & Joaquin Vespignani, 2020. "Impact of global uncertainty on the global economy and large developed and developing economies," Applied Economics, Taylor & Francis Journals, vol. 52(22), pages 2392-2407, May.
    32. Knüppel, Malte & Schultefrankenfeld, Guido, 2018. "Assessing the uncertainty in central banks' inflation outlooks," Discussion Papers 56/2018, Deutsche Bundesbank.
    33. Feng, Zhuozhao & Lin, Juan, 2023. "Macroeconomic uncertainty and firms’ investment in China," Economics Letters, Elsevier, vol. 226(C).
    34. Nina Biljanovska & Mr. Francesco Grigoli & Martina Hengge, 2017. "Fear Thy Neighbor: Spillovers from Economic Policy Uncertainty," IMF Working Papers 2017/240, International Monetary Fund.
    35. Ines Fortin & Jaroslava Hlouskova & Leopold Sögner, 2023. "Financial and economic uncertainties and their effects on the economy," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 50(2), pages 481-521, May.
    36. Tosapol Apaitan & Pongsak Luangaram & Pym Manopimoke, 2020. "Uncertainty and Economic Activity: Does it Matter for Thailand?," PIER Discussion Papers 130, Puey Ungphakorn Institute for Economic Research.
    37. Fetzer, Thiemo & Yotzov, Ivan, 2023. "(How) Do electoral surprises drive business cycles? Evidence from a new dataset," CAGE Online Working Paper Series 672, Competitive Advantage in the Global Economy (CAGE).
    38. Andrew B. Martinez, 2020. "Forecast Accuracy Matters for Hurricane Damages," Working Papers 2020-003, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    39. Oscar Claveria, 2021. "On the Aggregation of Survey-Based Economic Uncertainty Indicators Between Different Agents and Across Variables," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(1), pages 1-26, April.
    40. Cipollini, Andrea & Mikaliunaite, Ieva, 2020. "Macro-uncertainty and financial stress spillovers in the Eurozone," Economic Modelling, Elsevier, vol. 89(C), pages 546-558.
    41. Śmiech, Sławomir & Papież, Monika & Shahzad, Syed Jawad Hussain, 2020. "Spillover among financial, industrial and consumer uncertainties. The case of EU member states," International Review of Financial Analysis, Elsevier, vol. 70(C).
    42. 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.
    43. Hannes Mueller & Christopher Rauh, 2019. "The hard problem of prediction for conflict prevention," Cahiers de recherche 2019-02, Universite de Montreal, Departement de sciences economiques.
    44. MORIKAWA Masayuki, 2019. "Uncertainty in Long-Term Macroeconomic Forecasts: Ex post Evaluation of Forecasts by Economics Researchers," Discussion papers 19084, Research Institute of Economy, Trade and Industry (RIETI).
    45. Rossmann, Tobias, 2019. "Economic Uncertainty and Subjective Inflation Expectations," Rationality and Competition Discussion Paper Series 160, CRC TRR 190 Rationality and Competition.
    46. 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.
    47. Mehmet Balcilar & Rangan Gupta & Clement Kyei & Mark Wohar, 2015. "Does Economic Policy Uncertainty Predict Exchange Rate Returns and Volatility? Evidence from a Nonparametric Causality-in-Quantiles Test," Working Papers 201599, University of Pretoria, Department of Economics.
    48. Hossein Asgharian & Charlotte Christiansen & Ai Jun Hou, 2017. "Economic Policy Uncertainty and Long-Run Stock Market Volatility and Correlation," CREATES Research Papers 2018-12, Department of Economics and Business Economics, Aarhus University.
    49. Mario Forni & Luca Gambetti & Luca Sala, 2020. "Macroeconomic Uncertainty and Vector Autoregressions," Center for Economic Research (RECent) 148, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
    50. 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).
    51. Julius Loermann, 2021. "The impact of CHF/EUR exchange rate uncertainty on Swiss exports to the Eurozone: evidence from a threshold VAR," Empirical Economics, Springer, vol. 60(3), pages 1363-1385, March.
    52. Liu, Wei & Garrett, Ian, 2023. "Regime-dependent effects of macroeconomic uncertainty on realized volatility in the U.S. stock market," Economic Modelling, Elsevier, vol. 128(C).
    53. Mikhail Stolbov & Alexander Karminsky & Maria Shchepeleva, 2018. "Does Economic Policy Uncertainty Lead Systemic Risk? A Comparative Analysis of Selected European Countries," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 60(3), pages 332-360, September.
    54. Evren Erdogan Cosar & Sayg�n Sahinoz, 2018. "Quantifying Uncertainty and Identifying its Impacts on the Turkish Economy," Working Papers 1806, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    55. Zied Ftiti & Fredj Jawadi, 2019. "Forecasting Inflation Uncertainty in the United States and Euro Area," Computational Economics, Springer;Society for Computational Economics, vol. 54(1), pages 455-476, June.
    56. Gloria Gonzalez-Rivera & Esther Ruiz & Javier Vicente, 2018. "Growth in Stress," Working Papers 201805, University of California at Riverside, Department of Economics.
    57. Cesa-Bianchi, Ambrogio & Pesaran, M Hashem & Rebucci, Alessandro, 2018. "Uncertainty and economic activity: a multi-country perspective," Bank of England working papers 730, Bank of England.
    58. Chini, Emilio Zanetti, 2023. "Can we estimate macroforecasters’ mis-behavior?," Journal of Economic Dynamics and Control, Elsevier, vol. 149(C).
    59. Ezgi O. Ozturk & Xuguang Simon Sheng, 2017. "Measuring Global and Country-Specific Uncertainty," IMF Working Papers 2017/219, International Monetary Fund.
    60. Mohamed Sadok Gassouma & Adel Benhamed, 2023. "The Impact of the Islamic System on Economic and Social Factors: A Macroeconomic Uncertainty Context," Economies, MDPI, vol. 11(12), pages 1-18, December.
    61. Tihana Škrinjarić, 2023. "Credit-to-GDP Gap Estimates in Real Time: A Stable Indicator for Macroprudential Policy Making in Croatia," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 65(3), pages 582-614, September.
    62. Giovanni Caggiano & Efrem Castelnuovo & Gabriela Nodari, 2017. "Uncertainty and Monetary Policy in Good and Bad Times," RBA Research Discussion Papers rdp2017-06, Reserve Bank of Australia.
    63. Vasilios Plakandaras & Rangan Gupta & Mark E. Wohar, 2018. "Persistence of Economic Uncertainty: A Comprehensive Analysis," Working Papers 201810, University of Pretoria, Department of Economics.
    64. Francisco Serranito & Nicolas Himounet & Julien Vauday, 2023. "Uncertainty is bad for Business. Really?," Working Papers hal-04219283, HAL.
    65. Corinna Ghirelli & María Gil & Javier J. Pérez & Alberto Urtasun, 2021. "Measuring economic and economic policy uncertainty and their macroeconomic effects: the case of Spain," Empirical Economics, Springer, vol. 60(2), pages 869-892, February.
    66. Peter Claeys, 2017. "Uncertainty spillover and policy reactions," Revista ESPE - Ensayos sobre Política Económica, Banco de la Republica de Colombia, vol. 35(82), pages 64-77, April.
    67. 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.
    68. Kawamura, Kohei & Kobashi, Yohei & Shizume, Masato & Ueda, Kozo, 2019. "Strategic central bank communication: Discourse analysis of the Bank of Japan’s Monthly Report," Journal of Economic Dynamics and Control, Elsevier, vol. 100(C), pages 230-250.
    69. Balcilar, Mehmet & Gupta, Rangan & Kim, Won Joong & Kyei, Clement, 2019. "The role of economic policy uncertainties in predicting stock returns and their volatility for Hong Kong, Malaysia and South Korea," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 150-163.
    70. Jacopo Bizzotto & Davide Cipullo & André Reslow, 2024. "Biased Forecasts and Voting: The Brexit Referendum Case," CESifo Working Paper Series 11221, CESifo.
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    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. Jonas Dovern & Hans Manner, 2018. "Order Invariant Tests for Proper Calibration of Multivariate Density Forecasts," CESifo Working Paper Series 7023, CESifo.
    3. Simon Lloyd & Ed Manuel & Konstantin Panchev, 2024. "Foreign Vulnerabilities, Domestic Risks: The Global Drivers of GDP-at-Risk," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 72(1), pages 335-392, March.
    4. Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2019. "How is Machine Learning Useful for Macroeconomic Forecasting?," CIRANO Working Papers 2019s-22, CIRANO.
    5. James Mitchell & Martin Weale, 2021. "Censored Density Forecasts: Production and Evaluation," Working Papers 21-12R, Federal Reserve Bank of Cleveland, revised 16 Aug 2022.
    6. Boyarchenko, Nina & Adrian, Tobias & Giannone, Domenico, 2020. "Multimodality in Macro-Financial Dynamics," CEPR Discussion Papers 15088, C.E.P.R. Discussion Papers.
    7. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2022. "Using hierarchical aggregation constraints to nowcast regional economic aggregates," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2022-04, Economic Statistics Centre of Excellence (ESCoE).
    8. 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.
    9. Fabio Busetti & Michele Caivano & Davide Delle Monache & Claudia Pacella, 2020. "The time-varying risk of Italian GDP," Temi di discussione (Economic working papers) 1288, Bank of Italy, Economic Research and International Relations Area.
    10. Richard K. Crump & Miro Everaert & Domenico Giannone & Sean Hundtofte, 2018. "Changing Risk-Return Profiles," Staff Reports 850, Federal Reserve Bank of New York.
    11. David Kohns & Tibor Szendrei, 2021. "Decoupling Shrinkage and Selection for the Bayesian Quantile Regression," Papers 2107.08498, arXiv.org.
    12. Knüppel, Malte & Krüger, Fabian & Pohle, Marc-Oliver, 2022. "Score-based calibration testing for multivariate forecast distributions," Discussion Papers 50/2022, Deutsche Bundesbank.
    13. 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.
    14. Banerjee, Ryan & Contreras, Juan & Mehrotra, Aaron & Zampolli, Fabrizio, 2024. "Inflation at risk in advanced and emerging market economies," Journal of International Money and Finance, Elsevier, vol. 142(C).
    15. Barbara Rossi, 2019. "Forecasting in the presence of instabilities: How do we know whether models predict well and how to improve them," Economics Working Papers 1711, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2021.
    16. Jean-Guillaume Sahuc & Matteo Mogliani & Laurent Ferrara, 2022. "High-frequency monitoring of growth at risk," Post-Print hal-03361425, HAL.
    17. Antolín-Díaz, Juan & Drechsel, Thomas & Petrella, Ivan, 2024. "Advances in nowcasting economic activity: The role of heterogeneous dynamics and fat tails," Journal of Econometrics, Elsevier, vol. 238(2).
    18. Rossi, Barbara & Ganics, Gergely & Sekhposyan, Tatevik, 2020. "From Fixed-event to Fixed-horizon Density Forecasts: Obtaining Measures of Multi-horizon Uncertainty from Survey Density Foreca," CEPR Discussion Papers 14267, C.E.P.R. Discussion Papers.
    19. J. David López-Salido & Francesca Loria, 2020. "Inflation at Risk," Finance and Economics Discussion Series 2020-013, Board of Governors of the Federal Reserve System (U.S.).
    20. Ana Beatriz Galvão & James Mitchell, 2023. "Real‐Time Perceptions of Historical GDP Data Uncertainty," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 457-481, June.
    21. Plakandaras, Vasilios & Gogas, Periklis & Papadimitriou, Theophilos & Gupta, Rangan, 2019. "A re-evaluation of the term spread as a leading indicator," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 476-492.
    22. Patrick A. Adams & Tobias Adrian & Nina Boyarchenko & Domenico Giannone, 2020. "Forecasting Macroeconomic Risks," Staff Reports 914, Federal Reserve Bank of New York.
    23. 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.
    24. 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).
    25. 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.
    26. Galvao, Ana Beatriz & Mitchell, James, 2020. "Real-Time Perceptions of Historical GDP Data Uncertainty," EMF Research Papers 35, Economic Modelling and Forecasting Group.
    27. Lhuissier Stéphane, 2022. "Financial Conditions and Macroeconomic Downside Risks in the Euro Area," Working papers 863, Banque de France.
    28. Koop, Gary & McIntyre, Stuart & Mitchell, James & Poon, Aubrey, 2024. "Using stochastic hierarchical aggregation constraints to nowcast regional economic aggregates," International Journal of Forecasting, Elsevier, vol. 40(2), pages 626-640.
    29. Tobias Adrian & Nina Boyarchenko & Domenico Giannone, 2019. "Vulnerable Growth," American Economic Review, American Economic Association, vol. 109(4), pages 1263-1289, April.
    30. Michael W. McCracken, 2019. "Diverging Tests of Equal Predictive Ability," Working Papers 2019-018, Federal Reserve Bank of St. Louis, revised 09 Mar 2020.
    31. Taylor, James W., 2020. "A strategic predictive distribution for tests of probabilistic calibration," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1380-1388.
    32. Marcus P. A. Cobb, 2020. "Aggregate density forecasting from disaggregate components using Bayesian VARs," Empirical Economics, Springer, vol. 58(1), pages 287-312, January.
    33. Yunyun Wang & Tatsushi Oka & Dan Zhu, 2024. "Inflation Target at Risk: A Time-varying Parameter Distributional Regression," Papers 2403.12456, arXiv.org.
    34. Alex Tagliabracci, 2020. "Asymmetry in the conditional distribution of euro-area inflation," Temi di discussione (Economic working papers) 1270, Bank of Italy, Economic Research and International Relations Area.
    35. Nikoleta Anesti & Ana Beatriz Galvão & Silvia Miranda‐Agrippino, 2022. "Uncertain Kingdom: Nowcasting Gross Domestic Product and its revisions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 42-62, January.
    36. Tony Chernis & Taylor Webley, 2022. "Nowcasting Canadian GDP with Density Combinations," Discussion Papers 2022-12, Bank of Canada.
    37. Alessandro Giovannelli & Marco Lippi & Tommaso Proietti, 2023. "Band-Pass Filtering with High-Dimensional Time Series," CEIS Research Paper 559, Tor Vergata University, CEIS, revised 15 Jun 2023.
    38. Yunyun Wang & Tatsushi Oka & Dan Zhu, 2023. "Distributional Vector Autoregression: Eliciting Macro and Financial Dependence," Papers 2303.04994, arXiv.org.
    39. Wojciech Charemza & Carlos Diaz Vela & Svetlana Makarova, 2013. "Too many skew normal distributions? The practitioner’s perspective," Discussion Papers in Economics 13/07, Division of Economics, School of Business, University of Leicester.
    40. Niango Ange Joseph Yapi, 2020. "Exchange rate predictive densities and currency risks: A quantile regression approach," EconomiX Working Papers 2020-16, University of Paris Nanterre, EconomiX.
    41. Tomás Marinozzi, 2023. "Forecasting Inflation in Argentina: A Probabilistic Approach," Ensayos Económicos, Central Bank of Argentina, Economic Research Department, vol. 1(81), pages 81-110, May.
    42. Niko Hauzenberger & Florian Huber & Karin Klieber, 2020. "Real-time Inflation Forecasting Using Non-linear Dimension Reduction Techniques," Papers 2012.08155, arXiv.org, revised Dec 2021.
    43. Korobilis, Dimitris & Landau, Bettina & Musso, Alberto & Phella, Anthoulla, 2021. "The time-varying evolution of inflation risks," Working Paper Series 2600, European Central Bank.
    44. Gara Afonso & Domenico Giannone & Gabriele La Spada & John C. Williams, 2022. "Scarce, Abundant, or Ample? A Time-Varying Model of the Reserve Demand Curve," Staff Reports 1019, Federal Reserve Bank of New York.
    45. Nina Boyarchenko & Domenico Giannone & Or Shachar, 2018. "Flighty liquidity," Staff Reports 870, Federal Reserve Bank of New York.
    46. López-Salido, J David & Loria, Francesca, 2019. "Inflation at Risk," CEPR Discussion Papers 14074, C.E.P.R. Discussion Papers.
    47. Lan Bai & Xiafei Li & Yu Wei & Guiwu Wei, 2022. "Does crude oil futures price really help to predict spot oil price? New evidence from density forecasting," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3694-3712, July.
    48. 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.
    49. Garratt, Anthony & Petrella, Ivan, 2019. "Commodity Prices and Inflation Risk," EMF Research Papers 23, Economic Modelling and Forecasting Group.
    50. James Mitchell & Saeed Zaman, 2023. "The Distributional Predictive Content of Measures of Inflation Expectations," Working Papers 23-31, Federal Reserve Bank of Cleveland.

  18. Atsushi Inoue & Chun-Huong Kuo & Barbara Rossi, 2015. "Identifying the Sources of Model Misspecification," Working Papers 821, Barcelona School of Economics.

    Cited by:

    1. F. Canova & F. Ferroni & C. Matthes, 2015. "Approximating time varying structural models with time invariant structures," Working papers 578, Banque de France.
    2. Francesca Monti, 2015. "Can a data-rich environment help identify the sources of model misspecification?," Discussion Papers 1505, Centre for Macroeconomics (CFM).
    3. Paccagnini, Alessia, 2017. "Dealing with Misspecification in DSGE Models: A Survey," MPRA Paper 82914, University Library of Munich, Germany.
    4. Barbara Rossi & Atsushi Inoue & Yiru Wang, 2024. "Has the Phillips curve flattened?," French Stata Users' Group Meetings 2024 22, Stata Users Group.
    5. Filippo Ferroni & Jonas D. M. Fisher & Leonardo Melosi, 2022. "Usual Shocks in our Usual Models," Working Paper Series WP 2022-39, Federal Reserve Bank of Chicago.
    6. Guido Ascari & Qazi Haque & Leandro M. Magnusson & Sophocles Mavroeidis, 2021. "Empirical evidence on the Euler equation for investment in the US," CAMA Working Papers 2021-65, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    7. Fabio Canova & Christian Matthes, 2021. "Dealing with misspecification in structural macroeconometric models," Quantitative Economics, Econometric Society, vol. 12(2), pages 313-350, May.
    8. Loria, Francesca & Matthes, Christian & Wang, Mu-Chun, 2022. "Economic theories and macroeconomic reality," Journal of Monetary Economics, Elsevier, vol. 126(C), pages 105-117.
    9. Helena Marques & Gabriel Pino & J. D. Tena, 2018. "Voting with your feet: migration flows and happiness," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 9(2), pages 163-187, June.
    10. Den Haan, Wouter & Drechsel, Thomas, 2018. "Agnostic Structural Disturbances (ASDs): Detecting and Reducing Misspecification in Empirical Macroeconomic Models," CEPR Discussion Papers 13145, C.E.P.R. Discussion Papers.
    11. 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).
    12. Filippo Ferroni & Stefano Grassi & Miguel A. León-Ledesma, 2017. "Selecting Primal Innovations in DSGE models," Working Paper Series WP-2017-20, Federal Reserve Bank of Chicago.
    13. Filippo Ferroni & Stefano Grassi & Miguel A. Leon-Ledesma, 2015. "Fundamental shock selection in DSGE models," Studies in Economics 1508, School of Economics, University of Kent.
    14. Hatcher, Michael & Minford, Patrick, 2023. "Chameleon models in economics: A note," Cardiff Economics Working Papers E2023/10, Cardiff University, Cardiff Business School, Economics Section.

  19. Domenico Ferraro & Kenneth Rogoff & Barbara Rossi, 2015. "Can Oil Prices Forecast Exchange Rates?," Working Papers 803, Barcelona School of Economics.

    Cited by:

    1. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    2. Virginie Coudert & Valérie Mignon, 2016. "Reassessing the empirical relationship between the oil price and the dollar," EconomiX Working Papers 2016-2, University of Paris Nanterre, EconomiX.
    3. Rossi, José Luiz Júnior, 2013. "Liquidity and Exchange Rates," Insper Working Papers wpe_325, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    4. Bush, Georgia & López Noria, Gabriela, 2021. "Uncertainty and exchange rate volatility: Evidence from Mexico," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 704-722.
    5. Afees A. Salisu & Rangan Gupta, 2019. "How do Housing Returns in Emerging Countries Respond to Oil Shocks? A MIDAS Touch," Working Papers 201946, University of Pretoria, Department of Economics.
    6. Degiannakis, Stavros & Filis, George, 2017. "Forecasting oil price realized volatility using information channels from other asset classes," MPRA Paper 96276, University Library of Munich, Germany.
    7. Haoyuan Ding & Yuying Jin & Cong Qin & Jiezhou Ying, 2020. "Tail Causality between Crude Oil Price and RMB Exchange Rate," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 28(3), pages 116-134, May.
    8. Stijn Claessens & M Ayhan Kose, 2018. "Frontiers of macrofinancial linkages," BIS Papers, Bank for International Settlements, number 95.
    9. Hem C. Basnet & Puneet Vatsa & Subhash Sharma, 2014. "Common Trends and Common Cycles in Oil Price and Real Exchange Rate," Global Economy Journal (GEJ), World Scientific Publishing Co. Pte. Ltd., vol. 14(2), pages 249-263, June.
    10. Breen, John David & Hu, Liang, 2021. "The predictive content of oil price and volatility: New evidence on exchange rate forecasting," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
    11. Gina Christelle Pieters, 2017. "Bitcoin Reveals Exchange Rate Manipulation and Detects Capital Controls," 2017 Papers ppi307, Job Market Papers.
    12. Yang, Lu & Cai, Xiao Jing & Hamori, Shigeyuki, 2018. "What determines the long-term correlation between oil prices and exchange rates?," The North American Journal of Economics and Finance, Elsevier, vol. 44(C), pages 140-152.
    13. Adrien Verdelhan, 2012. "The Share of Systematic Variation in Bilateral Exchange Rates," 2012 Meeting Papers 763, Society for Economic Dynamics.
    14. Ahmed, Shamim & Tsvetanov, Daniel, 2016. "The predictive performance of commodity futures risk factors," Journal of Banking & Finance, Elsevier, vol. 71(C), pages 20-36.
    15. 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.
    16. Jean-François Carpantier, 2019. "Commodity Prices In Empirical Research," LIDAM Discussion Papers IRES 2020021, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
    17. Krzysztof Drachal, 2018. "Exchange Rate and Oil Price Interactions in Selected CEE Countries," Economies, MDPI, vol. 6(2), pages 1-21, May.
    18. Dunis, Christian & Kellard, Neil M. & Snaith, Stuart, 2013. "Forecasting EUR–USD implied volatility: The case of intraday data," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 4943-4957.
    19. Marco J. Lombardi & Francesco Ravazzolo, 2012. "Oil price density forecasts: exploring the linkages with stock markets," Working Paper 2012/24, Norges Bank.
    20. Fernanda Fuentes & Rodrigo Herrera & Adam Clements, 2016. "Modelling Extreme Risks in Commodities and Commodity Currencies," NCER Working Paper Series 115, National Centre for Econometric Research.
    21. Laurent Ferrara & Pierre Guérin, 2015. "What Are The Macroeconomic Effects of High-Frequency Uncertainty Shocks?," EconomiX Working Papers 2015-12, University of Paris Nanterre, EconomiX.
    22. 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.
    23. Tsiakas, Ilias & Zhang, Haibin, 2021. "Economic fundamentals and the long-run correlation between exchange rates and commodities," Global Finance Journal, Elsevier, vol. 49(C).
    24. Bermpei, Theodora & Ferrara, Laurent & Karadimitropoulou, Aikaterini & Triantafyllou, Athanasios, 2024. "Commodity currencies revisited: The role of global commodity price uncertainty," Journal of International Money and Finance, Elsevier, vol. 145(C).
    25. Branko Bošković & Andrew Leach, 2020. "Leave it in the ground? Oil sands development under carbon pricing," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 53(2), pages 526-562, May.
    26. Xiaojie Xu, 2019. "Price dynamics in corn cash and futures markets: cointegration, causality, and forecasting through a rolling window approach," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 33(2), pages 155-181, June.
    27. Ferraro, Domenico & Rogoff, Kenneth & Rossi, Barbara, 2015. "Can oil prices forecast exchange rates? An empirical analysis of the relationship between commodity prices and exchange rates," Journal of International Money and Finance, Elsevier, vol. 54(C), pages 116-141.
    28. Lombardi, Marco J. & Ravazzolo, Francesco, 2016. "On the correlation between commodity and equity returns: Implications for portfolio allocation," Journal of Commodity Markets, Elsevier, vol. 2(1), pages 45-57.
    29. Salisu, Afees A. & Adekunle, Wasiu & Alimi, Wasiu A. & Emmanuel, Zachariah, 2019. "Predicting exchange rate with commodity prices: New evidence from Westerlund and Narayan (2015) estimator with structural breaks and asymmetries," Resources Policy, Elsevier, vol. 62(C), pages 33-56.
    30. Ron Alquist & Reinhard Ellwanger & Jianjian Jin, 2020. "The effect of oil price shocks on asset markets: Evidence from oil inventory news," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(8), pages 1212-1230, August.
    31. Khyati Kathuria & Nand Kumar, 2022. "Pandemic‐induced fear and government policy response as a measure of uncertainty in the foreign exchange market: Evidence from (a)symmetric wild bootstrap likelihood ratio test," Pacific Economic Review, Wiley Blackwell, vol. 27(4), pages 361-379, October.
    32. Hui Jun ZHANG & Jean-Marie DUFOUR & John W. GALBRAITH, 2013. "Exchange Rates and Commodity Prices : Measuring Causality at Multiple Horizons," Cahiers de recherche 14-2013, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    33. Afees A. Salisu & Juncal Cuñado & Kazeem Isah & Rangan Gupta, 2021. "Stock markets and exchange rate behavior of the BRICS," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1581-1595, December.
    34. Chuffart, Thomas & Hooper, Emma, 2019. "An investigation of oil prices impact on sovereign credit default swaps in Russia and Venezuela," Energy Economics, Elsevier, vol. 80(C), pages 904-916.
    35. Julián Caballero, 2020. "Corporate dollar debt and depreciations: all's well that ends well?," BIS Working Papers 879, Bank for International Settlements.
    36. Salisu, Afees A. & Olaniran, Abeeb & Tchankam, Jean Paul, 2022. "Oil tail risk and the tail risk of the US Dollar exchange rates," Energy Economics, Elsevier, vol. 109(C).
    37. Yin, Libo & Su, Zhi & Lu, Man, 2022. "Is oil risk important for commodity-related currency returns?," Research in International Business and Finance, Elsevier, vol. 60(C).
    38. Abdulrahman, Alhassan & Syed Abul, Basher & M. Kabir, Hassan, 2019. "Oil subsidies and the risk exposure of oil-user stocks: Evidence from net oil producers," MPRA Paper 97080, University Library of Munich, Germany.
    39. Wen, Shaobo & An, Haizhong & Chen, Zhihua & Liu, Xueyong, 2017. "Driving factors of interactions between the exchange rate market and the commodity market: A wavelet-based complex network perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 299-308.
    40. Djeutem, Edouard & Dunbar, Geoffrey R., 2022. "Uncovered return parity: Equity returns and currency returns," Journal of International Money and Finance, Elsevier, vol. 128(C).
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    43. 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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    45. Marcel Fratzscher & Daniel Schneider & Ine Van Robays, 2013. "Oil Prices, Exchange Rates and Asset Prices," CESifo Working Paper Series 4264, CESifo.
    46. Emanuel Kohlscheen & Fernando Avalos & Andreas Schrimpf, 2017. "When the Walk Is Not Random: Commodity Prices and Exchange Rates," International Journal of Central Banking, International Journal of Central Banking, vol. 13(2), pages 121-158, June.
    47. 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.
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    50. Salem Boubakri & Cyriac Guillaumin & Alexandre Silanine, 2019. "Non-linear relationship between real commodity price volatility and real effective exchange rate: The case of commodity-exporting countries," Post-Print halshs-02157574, HAL.
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    55. Rehman, Mobeen Ur & Ahmad, Nasir & Vo, Xuan Vinh, 2022. "Asymmetric multifractal behaviour and network connectedness between socially responsible stocks and international oil before and during COVID-19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 587(C).
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    59. Kose, M. Ayhan & Claessens, Stijn, 2017. "Asset Prices and Macroeconomic Outcomes: A Survey," CEPR Discussion Papers 12460, C.E.P.R. Discussion Papers.
    60. Bonato, Matteo & Cepni, Oguzhan & Gupta, Rangan & Pierdzioch, Christian, 2023. "Climate risks and realized volatility of major commodity currency exchange rates," Journal of Financial Markets, Elsevier, vol. 62(C).
    61. Meng, Juan & Nie, He & Mo, Bin & Jiang, Yonghong, 2020. "Risk spillover effects from global crude oil market to China’s commodity sectors," Energy, Elsevier, vol. 202(C).
    62. Takamitsu Kurita & Patrick James, 2022. "The Canadian–US dollar exchange rate over the four decades of the post‐Bretton Woods float: An econometric study allowing for structural breaks," Metroeconomica, Wiley Blackwell, vol. 73(3), pages 856-883, July.
    63. Han, Liyan & Wan, Li & Xu, Yang, 2020. "Can the Baltic Dry Index predict foreign exchange rates?," Finance Research Letters, Elsevier, vol. 32(C).
    64. Thomas Theobald & Peter Hohlfeld, 2017. "Why have the recent oil price declines not stimulated global economic growth?," IMK Working Paper 185-2017, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
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    121. Joseph Zhi Bin Ling & Albert K. Tsui & Zhaoyong Zhang, 2021. "Trading Macro-Cycles of Foreign Exchange Markets Using Hybrid Models," Sustainability, MDPI, vol. 13(17), pages 1-20, September.
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    134. Anatolyev, Stanislav & Gospodinov, Nikolay & Jamali, Ibrahim & Liu, Xiaochun, 2017. "Foreign exchange predictability and the carry trade: A decomposition approach," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 199-211.
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    136. Adetutu, Morakinyo O. & Odusanya, Kayode A. & Ebireri, John E. & Murinde, Victor, 2020. "Oil booms, bank productivity and natural resource curse in finance," Economics Letters, Elsevier, vol. 186(C).
    137. Theodosios Perifanis & Athanasios Dagoumas, 2018. "Price and Volatility Spillovers Between the US Crude Oil and Natural Gas Wholesale Markets," Energies, MDPI, vol. 11(10), pages 1-25, October.
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    141. Polbin, Andrey & Shumilov, Andrei, 2020. "Модель Зависимости Обменного Курса Рубля От Цен На Нефть С Марковскими Переключениями Режимов [Modeling the relationship between the Russian ruble exchange rate and oil prices: A Markov regime swit," MPRA Paper 102450, University Library of Munich, Germany.
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  20. Emily Anderson & Atsushi Inoue & Barbara Rossi, 2015. "Heterogeneous Consumers and Fiscal Policy Shocks," Working Papers 822, Barcelona School of Economics.

    Cited by:

    1. Bernd Hayo & Matthias Uhl, 2015. "Regional effects of federal tax shocks," Southern Economic Journal, John Wiley & Sons, vol. 82(2), pages 343-360, October.
    2. Pedro Brinca & Miguel H. Ferreira & Francesco Franco & Hans A. Holter & Laurence Malafry, 2017. "Fiscal Consolidation Programs and Income Inequality," CEF.UP Working Papers 1703, Universidade do Porto, Faculdade de Economia do Porto.
    3. Thorsten Drautzburg & Pooyan Amir-Ahmadi, 2017. "Identification through Heterogeneity," 2017 Meeting Papers 1087, Society for Economic Dynamics.
    4. Piotr Krajewski & Agata Szymanska, 2019. "The effectiveness of fiscal policy within business cycle-Ricardians vs. non-Ricardians approach," Baltic Journal of Economics, Baltic International Centre for Economic Policy Studies, vol. 19(2), pages 195-215.
    5. Rossi, Barbara & Inoue, Atsushi & Anderson, Emily, 2013. "Heterogeneous Consumers and Fiscal Policy Shocks," CEPR Discussion Papers 9631, C.E.P.R. Discussion Papers.
    6. Mauro Napoletano & Andrea Roventini & Jean-Luc Gaffard, 2015. "Time-Varying Fiscal Multipliers in an Agent-Based Model with Credit Rationing," LEM Papers Series 2015/19, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    7. Minsu Chang & Frank Schorfheide, 2024. "On the Effects of Monetary Policy Shocks on Income and Consumption Heterogeneity," PIER Working Paper Archive 24-003, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    8. Agovino, Massimiliano & Ferrara, Maria, 2015. "Disabilità e povertà: il ruolo delle pensioni di invalidità civile. Un'analisi DSGE per i dati italiani [Disability and poverty: the role of civilian disability pensions. A DSGE analysis for Italia," MPRA Paper 65616, University Library of Munich, Germany.
    9. Eunseong Ma, 2023. "Monetary Policy And Inequality: How Does One Affect The Other?," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 64(2), pages 691-725, May.
    10. Puonti, Päivi, 2023. "Effective Fiscal Policy in an Aging Economy: Evidence from a BVAR Analysis," ETLA Working Papers 110, The Research Institute of the Finnish Economy.
    11. Giorgio Motta & Patrizio Tirelli, 2013. "Limited Asset Market Participation, Income Inequality and Macroeconomic Volatility," Working Papers 261, University of Milano-Bicocca, Department of Economics, revised Dec 2013.
    12. 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.
    13. Heer, Burkhard & Scharrer, Christian, 2018. "The age-specific burdens of short-run fluctuations in government spending," Journal of Economic Dynamics and Control, Elsevier, vol. 90(C), pages 45-75.
    14. Christian Bredemeier & Falko Juessen & Roland Winkler, 2023. "Bringing Back the Jobs Lost to Covid‐19: The Role of Fiscal Policy," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 55(7), pages 1703-1747, October.
    15. Pedro Brinca & Hans A. Holter & Per Krusell and Laurence Malafry, 2014. "Fiscal Multipliers in the 21st Century," RSCAS Working Papers 2014/119, European University Institute.
    16. Bessho, Shun-ichiro, 2021. "Local fiscal multipliers and population aging in Japan," Japan and the World Economy, Elsevier, vol. 60(C).
    17. Steven Fazzari & James Morley & Irina Panovska, 2014. "State-Dependent Effects of Fiscal Policy," Discussion Papers 2012-27C, School of Economics, The University of New South Wales.
    18. Fonseca, Miguel, 2020. "Fiscal Consolidations: Welfare Effects of the Adjustment Speed," MPRA Paper 98902, University Library of Munich, Germany, revised 02 Mar 2020.
    19. Givens, Gregory, 2019. "Unemployment, Partial Insurance, and the Multiplier Effects of Government Spending," MPRA Paper 96811, University Library of Munich, Germany.
    20. Klein, Mathias & Winkler, Roland, 2019. "Austerity, inequality, and private debt overhang," European Journal of Political Economy, Elsevier, vol. 57(C), pages 89-106.
    21. Maria Ferrara & Patrizio Tirelli, 2014. "Fiscal Consolidations: Can We Reap the Gain and Escape the Pain?," Working Papers 283, University of Milano-Bicocca, Department of Economics, revised Oct 2014.
    22. Cloyne, James & Surico, Paolo, 2014. "Household debt and the dynamic effects of income tax changes," Bank of England working papers 491, Bank of England.
    23. Masud Alam, 2021. "Output, Employment, and Price Effects of U.S. Narrative Tax Changes: A Factor-Augmented Vector Autoregression Approach," Papers 2106.10844, arXiv.org.
    24. Eunseong Ma, 2019. "The Heterogeneous Responses of Consumption between Poor and Rich to Government Spending Shocks," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 51(7), pages 1999-2028, October.
    25. Henrique S. Basso & Omar Rachedi, 2021. "The Young, the Old, and the Government: Demographics and Fiscal Multipliers," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(4), pages 110-141, October.
    26. Luisa Corrado & Edgar Silgado-Gómez, 2018. "Assessing the Effects of Fiscal Policy News under Imperfect Information: Evidence from Aggregate and Individual Data," CEIS Research Paper 447, Tor Vergata University, CEIS, revised 06 Nov 2018.
    27. Morita, Hiroshi, 2020. "Fiscal multipliers in the most aged country: Empirical evidence and theoretical interpretation," Discussion paper series HIAS-E-100, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    28. Bredemeier, Christian & Juessen, Falko & Winkler, Roland, 2017. "Fiscal Policy and Occupational Employment Dynamics," IZA Discussion Papers 10466, Institute of Labor Economics (IZA).
    29. Javier Andres & Jose E. Bosca & Javier Ferri & Cristina Fuentes-Albero, 2018. "Household's Balance Sheets and the Effect of Fiscal Policy," Finance and Economics Discussion Series 2018-012r1, Board of Governors of the Federal Reserve System (U.S.), revised 29 Jun 2020.
    30. Aursland, Thor Andreas & Frankovic, Ivan & Kanik, Birol & Saxegaard, Magnus, 2020. "State-dependent fiscal multipliers in NORA - A DSGE model for fiscal policy analysis in Norway," Economic Modelling, Elsevier, vol. 93(C), pages 321-353.
    31. Kerim Peren Arin & Juan A. Lacomba & Francisco Lagos & Ana I. Moro-Egido & Marcel Thum, 2021. "Socio-Economic Attitudes in the Era of Social Distancing and Lockdowns," CESifo Working Paper Series 8845, CESifo.
    32. Rüth, Sebastian K. & Simon, Camilla, 2022. "How do income and the debt position of households propagate fiscal stimulus into consumption?," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    33. Ferrara, Maria & Tirelli, Patrizio, 2017. "Equitable fiscal consolidations," Economic Modelling, Elsevier, vol. 61(C), pages 207-223.
    34. Alica Ida Bonk & Laure Simon, 2022. "From He-Cession to She-Stimulus? The labor market impact of fiscal policy across gender," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 13(1), pages 309-334, May.
    35. Massimiliano Agovino & Maria Ferrara, 2017. "Can civilian disability pensions overcome the poverty issue? A DSGE analysis for Italian data," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(4), pages 1469-1491, July.
    36. Wifag Adnan & Kerim Peren Arin & Aysegul Corakci & Nicola Spagnolo, 2022. "On the heterogeneous effects of tax policy on labor market outcomes," Southern Economic Journal, John Wiley & Sons, vol. 88(3), pages 991-1036, January.
    37. Kopiec, Paweł, 2024. "The aggregate and distributional effects of fiscal stimuli," Economic Modelling, Elsevier, vol. 134(C).
    38. Grancini, Stefano, 2021. "Risk Aversion and Fiscal Consolidation Programs," MPRA Paper 105500, University Library of Munich, Germany.
    39. Alice Albonico & Alessia Paccagnini & Patrizio Tirelli, 2014. "Estimating a DSGE model with Limited Asset Market Participation for the Euro Area," Working Papers 286, University of Milano-Bicocca, Department of Economics, revised Nov 2014.
    40. Laure Simon, 2023. "Fiscal Stimulus and Skill Accumulation over the Life Cycle," Staff Working Papers 23-9, Bank of Canada.
    41. Patrizio Tirelli & Maria Ferrara, 2020. "Disinflation, Inequality, And Welfare In A Tank Model," Economic Inquiry, Western Economic Association International, vol. 58(3), pages 1297-1313, July.
    42. Daniel R. Carroll, 2014. "Why Do Economists Still Disagree over Government Spending Multipliers?," Economic Commentary, Federal Reserve Bank of Cleveland, issue May.
    43. Samuel Federico Kaplan & Arin Kerim Peren & Polyzos Efstathios & Spagnolo Nicola, 2022. "Stock Market Responses to Monetary Policy Shocks: Universal Firm-Level Evidence," Asociación Argentina de Economía Política: Working Papers 4571, Asociación Argentina de Economía Política.
    44. Freitas, Bruno, 2020. "Labour Share Heterogeneity and Fiscal Consolidation Programs," MPRA Paper 98973, University Library of Munich, Germany.
    45. Massimiliano Agovino & Maria Ferrara, 2022. "Disabilit?: diseguaglianza sociale ed economica. Un?analisi empirica e teorica," ECONOMIA PUBBLICA, FrancoAngeli Editore, vol. 2022(1), pages 11-42.
    46. Polyzos, Efstathios, 2022. "Examining the asymmetric impact of macroeconomic policy in the UAE: Evidence from quartile impulse responses and machine learning," The Journal of Economic Asymmetries, Elsevier, vol. 26(C).

  21. Barbara Rossi & Tatevik Sekhposyan, 2015. "Macroeconomic Uncertainty Indices for the Euro Area and Individual Member Countries," Working Papers 820, Barcelona School of Economics.

    Cited by:

    1. Michael Clements, 2016. "Are Macroeconomic Density Forecasts Informative?," ICMA Centre Discussion Papers in Finance icma-dp2016-02, Henley Business School, University of Reading.
    2. Bonciani, Dario, 2015. "Estimating the effects of uncertainty over the business cycle," MPRA Paper 65921, University Library of Munich, Germany.
    3. Berg, Tim Oliver, 2019. "Business Uncertainty And The Effectiveness Of Fiscal Policy In Germany," Macroeconomic Dynamics, Cambridge University Press, vol. 23(4), pages 1442-1470, June.
    4. Laurent Ferrara & Pierre Guérin, 2015. "What Are The Macroeconomic Effects of High-Frequency Uncertainty Shocks?," EconomiX Working Papers 2015-12, University of Paris Nanterre, EconomiX.
    5. 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.
    6. Wensheng Kang & Ronald A. Ratti & Joaquin Vespignani, 2016. "Global uncertainty and the global economy: Decomposing the impact of uncertainty shocks," CAMA Working Papers 2016-39, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    7. Michele Piffer & Maximilian Podstawski, 2017. "Identifying Uncertainty Shocks Using the Price of Gold," CESifo Working Paper Series 6327, CESifo.
    8. Maurizio Bovi, 2016. "The tale of two expectations," Quality & Quantity: International Journal of Methodology, Springer, vol. 50(6), pages 2677-2705, November.
    9. Christina Christou & Rangan Gupta, 2016. "Forecasting Equity Premium in a Panel of OECD Countries: The Role of Economic Policy Uncertainty," Working Papers 201622, University of Pretoria, Department of Economics.
    10. Meinen, Philipp & Röhe, Oke, 2016. "On measuring uncertainty and its impact on investment: Cross-country evidence from the euro area," Discussion Papers 48/2016, Deutsche Bundesbank.
    11. M. E. Bontempi & R. Golinelli & M. Squadrani, 2016. "A New Index of Uncertainty Based on Internet Searches: A Friend or Foe of Other Indicators?," Working Papers wp1062, Dipartimento Scienze Economiche, Universita' di Bologna.
    12. Christina Christou & Rangan Gupta & Christis Hassapis, 2016. "Does Economic Policy Uncertainty Forecast Real Housing Returns in a Panel of OECD Countries? A Bayesian Approach," Working Papers 201637, University of Pretoria, Department of Economics.
    13. Chow Sheung-Chi & Cunado Juncal & Gupta Rangan & Wong Wing-Keung, 2018. "Causal relationships between economic policy uncertainty and housing market returns in China and India: evidence from linear and nonlinear panel and time series models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(2), pages 1-15, April.
    14. Mehmet Balcilar & Riza Demirer & Rangan Gupta & Reneé van Eyden, 2016. "Effectiveness of Monetary Policy in the Euro Area: The Role of US Economic Policy Uncertainty," Working Papers 201620, University of Pretoria, Department of Economics.
    15. Sylwia Nowak & Pratiti Chatterjee, 2016. "Forecast Errors and Uncertainty Shocks," IMF Working Papers 2016/228, International Monetary Fund.
    16. Helena Chuliá & Rangan Gupta & Jorge M. Uribe & Mark E. Wohar, 2016. "Impact of US Uncertainties on Emerging and Mature Markets: Evidence from a Quantile-Vector Autoregressive Approach," Working Papers 201656, University of Pretoria, Department of Economics.
    17. Balcilar, Mehmet & Gupta, Rangan & Pierdzioch, Christian, 2016. "Does uncertainty move the gold price? New evidence from a nonparametric causality-in-quantiles test," Resources Policy, Elsevier, vol. 49(C), pages 74-80.

  22. Raffaella Giacomini & Barbara Rossi, 2014. "Forecasting in Nonstationary Environments: What Works and What Doesn't in Reduced-Form and Structural Models," Working Papers 819, Barcelona School of Economics.

    Cited by:

    1. Alessandro Casini & Pierre Perron, 2018. "Structural Breaks in Time Series," Boston University - Department of Economics - Working Papers Series WP2019-02, Boston University - Department of Economics.
    2. Roberta Cardani & Alessia Paccagnini & Stefania Villa, 2019. "Forecasting with instabilities: an application to DSGE models with financial frictions," Temi di discussione (Economic working papers) 1234, Bank of Italy, Economic Research and International Relations Area.
    3. Alessandro Casini, 2021. "Theory of Evolutionary Spectra for Heteroskedasticity and Autocorrelation Robust Inference in Possibly Misspecified and Nonstationary Models," Papers 2103.02981, arXiv.org, revised Aug 2024.
    4. Elliott, Graham & Timmermann, Allan G, 2016. "Forecasting in Economics and Finance," University of California at San Diego, Economics Working Paper Series qt6z55v472, Department of Economics, UC San Diego.

  23. Raffaella Giacomini & Barbara Rossi, 2014. "Model Comparisons in Unstable Environments," Working Papers 784, Barcelona School of Economics.

    Cited by:

    1. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    2. Rossi, José Luiz Júnior, 2013. "Liquidity and Exchange Rates," Insper Working Papers wpe_325, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    3. Yin, Anwen, 2015. "Forecasting and model averaging with structural breaks," ISU General Staff Papers 201501010800005727, Iowa State University, Department of Economics.
    4. Giacomini, Raffaella, 2014. "Economic theory and forecasting: lessons from the literature," CEPR Discussion Papers 10201, C.E.P.R. Discussion Papers.
    5. Raffaella Giacomini & Barbara Rossi, 2014. "Forecasting in Nonstationary Environments: What Works and What Doesn't in Reduced-Form and Structural Models," Working Papers 819, Barcelona School of Economics.
    6. Ana Beatriz Galvão & Liudas Giraitis & George Kapetanios & Katerina Petrova, 2015. "A Bayesian Local Likelihood Method for Modelling Parameter Time Variation in DSGE Models," Working Papers 770, Queen Mary University of London, School of Economics and Finance.
    7. 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.
    8. 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.
    9. Alexandra Horobet & Irina Mnohoghitnei & Emanuela Marinela Luminita Zlatea & Lucian Belascu, 2022. "The Interplay between Digitalization, Education and Financial Development: A European Case Study," JRFM, MDPI, vol. 15(3), pages 1-23, March.
    10. Giacomini, Raffaella & Rossi, Barbara, 2008. "Forecast Comparisons in Unstable Environments," Working Papers 08-04, Duke University, Department of Economics.
    11. Roberta Cardani & Alessia Paccagnini & Stefania Villa, 2019. "Forecasting with instabilities: an application to DSGE models with financial frictions," Temi di discussione (Economic working papers) 1234, Bank of Italy, Economic Research and International Relations Area.
    12. Chollete, Loran & Schmeidler, David, 2014. "Extreme Events and the Origin of Central Bank Priors," UiS Working Papers in Economics and Finance 2014/15, University of Stavanger.
    13. Chang Liu & Biqian Zhang & Xuefei Wang & Min Guo, 2022. "Account-level analytic hierarchical mixing modeling for credit risk of Chinese Government financing vehicle portfolios," Empirical Economics, Springer, vol. 62(6), pages 2771-2798, June.
    14. Rossi, José Luiz Júnior, 2014. "The Usefulness of Financial Variables in Predicting Exchange Rate Movements," Insper Working Papers wpe_332, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    15. Raffaella Giacomini, 2014. "Economic theory and forecasting: lessons from the literature," CeMMAP working papers 41/14, Institute for Fiscal Studies.
    16. Leandro M. Magnusson & Sophocles Mavroeidis, 2014. "Identification Using Stability Restrictions," Econometrica, Econometric Society, vol. 82, pages 1799-1851, September.
    17. Rossi, Barbara & Gürkaynak, Refet & Kısacıkoğlu, Burçin, 2013. "Do DSGE Models Forecast More Accurately Out-of-Sample than VAR Models?," CEPR Discussion Papers 9576, C.E.P.R. Discussion Papers.
    18. Weber, Enzo & Zika, Gerd, 2013. "Labour market forecasting : is disaggregation useful?," IAB-Discussion Paper 201314, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    19. 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.

  24. Rossi, Barbara & Inoue, Atsushi & Jin, Lu, 2014. "Window Selection for Out-of-Sample Forecasting with Time-Varying Parameters," CEPR Discussion Papers 10168, C.E.P.R. Discussion Papers.

    Cited by:

    1. Xiu Xu & Andrija Mihoci & Wolfgang Karl Hardle, 2020. "lCARE -- localizing Conditional AutoRegressive Expectiles," Papers 2009.13215, arXiv.org.
    2. Fernando Fernández-Rodríguez & Marta Gómez-Puig & Simón Sosvilla-Rivero, 2015. "Financial stress transmission in EMU sovereign bond market volatility: A connectedness analysis," Working Papers del Instituto Complutense de Estudios Internacionales 1501, Universidad Complutense de Madrid, Instituto Complutense de Estudios Internacionales.
    3. Tan, Xueping & Sirichand, Kavita & Vivian, Andrew & Wang, Xinyu, 2020. "How connected is the carbon market to energy and financial markets? A systematic analysis of spillovers and dynamics," Energy Economics, Elsevier, vol. 90(C).
    4. Fernando Fernández-Rodríguez & Marta Gómez-Puig & Simón Sosvilla-Rivero, 2015. "Volatility spillovers in EMU sovereign bond markets," Working Papers del Instituto Complutense de Estudios Internacionales 1504, Universidad Complutense de Madrid, Instituto Complutense de Estudios Internacionales.
    5. Xu, Xiu & Mihoci, Andrija & Härdle, Wolfgang Karl, 2018. "lCARE - localizing conditional autoregressive expectiles," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 198-220.
    6. Mehmet Sahiner, 2022. "Forecasting volatility in Asian financial markets: evidence from recursive and rolling window methods," SN Business & Economics, Springer, vol. 2(10), pages 1-74, October.
    7. Mariia Artemova & Francisco Blasques & Siem Jan Koopman & Zhaokun Zhang, 2021. "Forecasting in a changing world: from the great recession to the COVID-19 pandemic," Tinbergen Institute Discussion Papers 21-006/III, Tinbergen Institute.

  25. Atsushi Inoue & Lu Jin & Barbara Rossi, 2014. "Rolling Window Selection for Out-of-Sample Forecasting with Time-Varying Parameters," Working Papers 768, Barcelona School of Economics.

    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. Cai, Yuxin & Lu, Xinsheng & Ren, Yongping & Qu, Ling, 2019. "Exploring the dynamic relationship between crude oil price and implied volatility indices: A MF-DCCA approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    3. Zhang, Jiaming & Xiang, Yitian & Zou, Yang & Guo, Songlin, 2024. "Volatility forecasting of Chinese energy market: Which uncertainty have better performance?," International Review of Financial Analysis, Elsevier, vol. 91(C).
    4. 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.
    5. Chen, Guojin & Liu, Yanzhen & Zhang, Yu, 2020. "Can systemic risk measures predict economic shocks? Evidence from China," China Economic Review, Elsevier, vol. 64(C).
    6. Tae-Hwy Lee & Ekaterina Seregina & Yaojue Xu, 2023. "Elicitability and Encompassing for Volatility Forecasts by Bregman Functions," Working Papers 202311, University of California at Riverside, Department of Economics.
    7. Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2019. "How is Machine Learning Useful for Macroeconomic Forecasting?," CIRANO Working Papers 2019s-22, CIRANO.
    8. Xiu Xu & Andrija Mihoci & Wolfgang Karl Hardle, 2020. "lCARE -- localizing Conditional AutoRegressive Expectiles," Papers 2009.13215, arXiv.org.
    9. Chen, Qitong & Hong, Yongmiao & Li, Haiqi, 2024. "Time-varying forecast combination for factor-augmented regressions with smooth structural changes," Journal of Econometrics, Elsevier, vol. 240(1).
    10. Giovannelli, Alessandro & Massacci, Daniele & Soccorsi, Stefano, 2021. "Forecasting stock returns with large dimensional factor models," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 252-269.
    11. Rudrani Bhattacharya & Parma Chakravartti & Sudipto Mundle, 2019. "Forecasting India’s economic growth: a time-varying parameter regression approach," Macroeconomics and Finance in Emerging Market Economies, Taylor & Francis Journals, vol. 12(3), pages 205-228, September.
    12. Fernando Fernández-Rodríguez & Marta Gómez-Puig & Simón Sosvilla-Rivero, 2015. "Financial stress transmission in EMU sovereign bond market volatility: A connectedness analysis," Working Papers del Instituto Complutense de Estudios Internacionales 1501, Universidad Complutense de Madrid, Instituto Complutense de Estudios Internacionales.
    13. Luca Nocciola, "undated". "Finite sample forecast properties and window length under breaks in cointegrated systems," Discussion Papers 19/07, University of Nottingham, Granger Centre for Time Series Econometrics.
    14. Yi, Yongsheng & He, Mengxi & Zhang, Yaojie, 2022. "Out-of-sample prediction of Bitcoin realized volatility: Do other cryptocurrencies help?," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    15. Yaojie Zhang & Yudong Wang & Feng Ma & Yu Wei, 2022. "To jump or not to jump: momentum of jumps in crude oil price volatility prediction," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-31, December.
    16. Feng, Lingbing & Qi, Jiajun & Lucey, Brian, 2024. "Enhancing cryptocurrency market volatility forecasting with daily dynamic tuning strategy," International Review of Financial Analysis, Elsevier, vol. 94(C).
    17. Sun, Yuying & Hong, Yongmiao & Wang, Shouyang & Zhang, Xinyu, 2023. "Penalized time-varying model averaging," Journal of Econometrics, Elsevier, vol. 235(2), pages 1355-1377.
    18. Artur Tarassow, 2017. "Forecasting growth of U.S. aggregate and household-sector M2 after 2000 using economic uncertainty measures," Macroeconomics and Finance Series 201702, University of Hamburg, Department of Socioeconomics.
    19. Peng, Zhen & Dong, Chaohua, 2022. "Augmented cointegrating linear models with possibly strongly correlated stationary and nonstationary regressors," Finance Research Letters, Elsevier, vol. 47(PB).
    20. Philip Hans Franses & Eva Janssens, 2018. "This Time It Is Different! Or Not? Discounting Past Data When Predicting The Future," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 13(02), pages 1-34, June.
    21. Xu Xiaojie, 2018. "Using Local Information to Improve Short-Run Corn Price Forecasts," Journal of Agricultural & Food Industrial Organization, De Gruyter, vol. 16(1), pages 1-15, January.
    22. Deryugina, Elena & Ponomarenko, Alexey & Rozhkova, Anna, 2020. "When are credit gap estimates reliable?," Economic Analysis and Policy, Elsevier, vol. 67(C), pages 221-238.
    23. Sixian Tang & Jackie Li & Leonie Tickle, 2022. "A New Fourier Approach under the Lee-Carter Model for Incorporating Time-Varying Age Patterns of Structural Changes," Risks, MDPI, vol. 10(8), pages 1-24, July.
    24. Algieri, Bernardina & Leccadito, Arturo, 2019. "Ask CARL: Forecasting tail probabilities for energy commodities," Energy Economics, Elsevier, vol. 84(C).
    25. Tan, Xueping & Sirichand, Kavita & Vivian, Andrew & Wang, Xinyu, 2020. "How connected is the carbon market to energy and financial markets? A systematic analysis of spillovers and dynamics," Energy Economics, Elsevier, vol. 90(C).
    26. Reikard, Gordon & Hansen, Clifford, 2019. "Forecasting solar irradiance at short horizons: Frequency and time domain models," Renewable Energy, Elsevier, vol. 135(C), pages 1270-1290.
    27. Zhang, Yaojie & Wang, Yudong, 2023. "Forecasting crude oil futures market returns: A principal component analysis combination approach," International Journal of Forecasting, Elsevier, vol. 39(2), pages 659-673.
    28. Nikodinoska, Dragana & Käso, Mathias & Müsgens, Felix, 2022. "Solar and wind power generation forecasts using elastic net in time-varying forecast combinations," Applied Energy, Elsevier, vol. 306(PA).
    29. Dellas, Harris & Gibson, Heather D. & Hall, Stephen G. & Tavlas, George S., 2018. "The macroeconomic and fiscal implications of inflation forecast errors," Journal of Economic Dynamics and Control, Elsevier, vol. 93(C), pages 203-217.
    30. Khowaja, Kainat & Saef, Danial & Sizov, Sergej & Härdle, Wolfgang Karl, 2020. "Data Analytics Driven Controlling: bridging statistical modeling and managerial intuition," IRTG 1792 Discussion Papers 2020-026, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    31. Ghani, Usman & Zhu, Bo & Ghani, Maria & Khan, Nasir & khan, Raja Danish Akbar, 2023. "Role of oil shocks in US stock market volatility: A new insight from GARCH-MIDAS perspective," Resources Policy, Elsevier, vol. 85(PB).
    32. Wen, Danyan & Liu, Li & Wang, Yudong & Zhang, Yaojie, 2022. "Forecasting crude oil market returns: Enhanced moving average technical indicators," Resources Policy, Elsevier, vol. 76(C).
    33. Sun, Yuying & Wang, Shouyang & Zhang, Xun, 2018. "How efficient are China's macroeconomic forecasts? Evidences from a new forecasting evaluation approach," Economic Modelling, Elsevier, vol. 68(C), pages 506-513.
    34. Chang, Chih-Hao & Chen, Zih-Bing & Huang, Shih-Feng, 2022. "Forecasting of high-resolution electricity consumption with stochastic climatic covariates via a functional time series approach," Applied Energy, Elsevier, vol. 309(C).
    35. Carlo Fezzi & Luca Mosetti, 2018. "Size matters: Estimation sample length and electricity price forecasting accuracy," DEM Working Papers 2018/10, Department of Economics and Management.
    36. 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.
    37. Shikha Gupta & Nand Kumar, 2022. "Globalization Versus Slowbalization: A Perspective on the Indian Economy," Journal of South Asian Development, , vol. 17(1), pages 84-107, April.
    38. Giovanni Ballarin & Petros Dellaportas & Lyudmila Grigoryeva & Marcel Hirt & Sophie van Huellen & Juan-Pablo Ortega, 2022. "Reservoir Computing for Macroeconomic Forecasting with Mixed Frequency Data," Papers 2211.00363, arXiv.org, revised Jan 2024.
    39. Stephen G. Hall & George S. Tavlas & Yongli Wang, 2023. "Forecasting inflation: the use of dynamic factor analysis and nonlinear combinations," Working Papers 314, Bank of Greece.
    40. Andrew B. Martinez & Jennifer L. Castle & David F. Hendry, 2021. "Smooth Robust Multi-Horizon Forecasts," Economics Papers 2021-W01, Economics Group, Nuffield College, University of Oxford.
    41. 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.
    42. Li, Xishu & Zuidwijk, Rob & de Koster, M.B.M, 2023. "Optimal competitive capacity strategies: Evidence from the container shipping market," Omega, Elsevier, vol. 115(C).
    43. Davide De Gaetano, 2018. "Forecast Combinations in the Presence of Structural Breaks: Evidence from U.S. Equity Markets," Mathematics, MDPI, vol. 6(3), pages 1-19, March.
    44. Liu, Guangqiang & Guo, Xiaozhu, 2022. "Forecasting stock market volatility using commodity futures volatility information," Resources Policy, Elsevier, vol. 75(C).
    45. Christis Katsouris, 2023. "Predictability Tests Robust against Parameter Instability," Papers 2307.15151, arXiv.org.
    46. Liu, Jing & Ma, Feng & Yang, Ke & Zhang, Yaojie, 2018. "Forecasting the oil futures price volatility: Large jumps and small jumps," Energy Economics, Elsevier, vol. 72(C), pages 321-330.
    47. Dong Hwan Oh & Andrew J. Patton, 2021. "Better the Devil You Know: Improved Forecasts from Imperfect Models," Finance and Economics Discussion Series 2021-071, Board of Governors of the Federal Reserve System (U.S.).
    48. Prakash, Navendu & Srivastava, Bhavya & Singh, Shveta & Sharma, Seema & Jain, Sonali, 2022. "Effectiveness of social distancing interventions in containing COVID-19 incidence: International evidence using Kalman filter," Economics & Human Biology, Elsevier, vol. 44(C).
    49. Zhu, Haibin & Bai, Lu & He, Lidan & Liu, Zhi, 2023. "Forecasting realized volatility with machine learning: Panel data perspective," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 251-271.
    50. Fernando Fernández-Rodríguez & Marta Gómez-Puig & Simón Sosvilla-Rivero, 2015. "Volatility spillovers in EMU sovereign bond markets," Working Papers del Instituto Complutense de Estudios Internacionales 1504, Universidad Complutense de Madrid, Instituto Complutense de Estudios Internacionales.
    51. Hany Guirguis & Vaneesha Boney Dutra & Zoe McGreevy, 2022. "The impact of global economies on US inflation: A test of the Phillips curve," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 46(3), pages 575-592, July.
    52. Mengxi He & Yudong Wang & Yaojie Zhang, 2023. "The predictability of iron ore futures prices: A product‐material lead–lag effect," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(9), pages 1289-1304, September.
    53. Jeronymo Marcondes Pinto & Emerson Fernandes Marçal, 2023. "An artificial intelligence approach to forecasting when there are structural breaks: a reinforcement learning-based framework for fast switching," Empirical Economics, Springer, vol. 65(4), pages 1729-1759, October.
    54. Davide De Gaetano, 2017. "Forecasting With Garch Models Under Structural Breaks: An Approach Based On Combinations Across Estimation Windows," Departmental Working Papers of Economics - University 'Roma Tre' 0219, Department of Economics - University Roma Tre.
    55. Kim, Young Min & Lee, Seojin, 2020. "Exchange rate predictability: A variable selection perspective," International Review of Economics & Finance, Elsevier, vol. 70(C), pages 117-134.
    56. Shahriyar Aliyev & Evžen Kočenda, 2023. "ECB monetary policy and commodity prices," Review of International Economics, Wiley Blackwell, vol. 31(1), pages 274-304, February.
    57. Gaies, Brahim & Nakhli, Mohamed Sahbi & Sahut, Jean-Michel & Schweizer, Denis, 2023. "Interactions between investors’ fear and greed sentiment and Bitcoin prices," The North American Journal of Economics and Finance, Elsevier, vol. 67(C).
    58. Zhang, Yue-Jun & Li, Zhao-Chen, 2021. "Forecasting the stock returns of Chinese oil companies: Can investor attention help?," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 531-555.
    59. Xiafei Li & Yu Wei & Xiaodan Chen & Feng Ma & Chao Liang & Wang Chen, 2022. "Which uncertainty is powerful to forecast crude oil market volatility? New evidence," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4279-4297, October.
    60. Chao Liang & Yu Wei & Yaojie Zhang, 2020. "Is implied volatility more informative for forecasting realized volatility: An international perspective," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(8), pages 1253-1276, December.
    61. Hirano, Keisuke & Wright, Jonathan H., 2022. "Analyzing cross-validation for forecasting with structural instability," Journal of Econometrics, Elsevier, vol. 226(1), pages 139-154.
    62. Wang, Yudong & Hao, Xianfeng & Wu, Chongfeng, 2021. "Forecasting stock returns: A time-dependent weighted least squares approach," Journal of Financial Markets, Elsevier, vol. 53(C).
    63. Shikha Gupta & Nand Kumar, 2023. "Time varying dynamics of globalization effect in India," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 22(1), pages 81-97, January.
    64. Hengzhen Lu & Qiujin Gao & Ling Xiao & Gurjeet Dhesi, 2024. "Forecasting EUA futures volatility with geopolitical risk: evidence from GARCH-MIDAS models," Review of Managerial Science, Springer, vol. 18(7), pages 1917-1943, July.
    65. Zhang, Yaojie & He, Mengxi & Wen, Danyan & Wang, Yudong, 2023. "Forecasting crude oil price returns: Can nonlinearity help?," Energy, Elsevier, vol. 262(PB).
    66. Peng, Huan & Chen, Ruoxun & Mei, Dexiang & Diao, Xiaohua, 2018. "Forecasting the realized volatility of the Chinese stock market: Do the G7 stock markets help?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 501(C), pages 78-85.
    67. Liang, Chao & Ma, Feng & Li, Ziyang & Li, Yan, 2020. "Which types of commodity price information are more useful for predicting US stock market volatility?," Economic Modelling, Elsevier, vol. 93(C), pages 642-650.
    68. Tae-Hwy Lee & Shahnaz Parsaeian & Aman Ullah, 2022. "Optimal Forecast under Structural Breaks," Working Papers 202208, University of California at Riverside, Department of Economics.
    69. Rachid Guennouni Hassani & Alexis Gilles & Emmanuel Lassalle & Arthur D'enouveaux, 2020. "Predicting Stock Returns with Batched AROW," Papers 2003.03076, arXiv.org, revised Mar 2020.
    70. Skander Slim & Ibrahim Tabche & Yosra Koubaa & Mohamed Osman & Andreas Karathanasopoulos, 2023. "Forecasting realized volatility of Bitcoin: The informative role of price duration," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1909-1929, November.
    71. Zhang, Yaojie & Ma, Feng & Wei, Yu, 2019. "Out-of-sample prediction of the oil futures market volatility: A comparison of new and traditional combination approaches," Energy Economics, Elsevier, vol. 81(C), pages 1109-1120.
    72. Stephen G. Hall & George S. Tavlas & Yongli Wang & Deborah Gefang, 2024. "Inflation forecasting with rolling windows: An appraisal," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(4), pages 827-851, July.
    73. Wang, Ping & Han, Wei & Huang, Chengcheng & Duong, Duy, 2022. "Forecasting realised volatility from search volume and overnight sentiment: Evidence from China," Research in International Business and Finance, Elsevier, vol. 62(C).
    74. Zhang, Yaojie & Wei, Yu & Zhang, Yi & Jin, Daxiang, 2019. "Forecasting oil price volatility: Forecast combination versus shrinkage method," Energy Economics, Elsevier, vol. 80(C), pages 423-433.
    75. Mikihito Nishi, 2024. "Estimating Time-Varying Parameters of Various Smoothness in Linear Models via Kernel Regression," Papers 2406.14046, arXiv.org, revised Oct 2024.
    76. Oh, Juhyun & Suh, Dong Hee, 2024. "Exploring the import allocation of wood pellets: Insights from price and policy influences under the renewable portfolio standard," Forest Policy and Economics, Elsevier, vol. 161(C).
    77. He, Mengxi & Wang, Yudong & Zeng, Qing & Zhang, Yaojie, 2023. "Forecasting aggregate stock market volatility with industry volatilities: The role of spillover index," Research in International Business and Finance, Elsevier, vol. 65(C).
    78. Xu, Xiu & Mihoci, Andrija & Härdle, Wolfgang Karl, 2018. "lCARE - localizing conditional autoregressive expectiles," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 198-220.
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    98. Wen, Danyan & Wang, Yudong & Zhang, Yaojie, 2021. "Intraday return predictability in China’s crude oil futures market: New evidence from a unique trading mechanism," Economic Modelling, Elsevier, vol. 96(C), pages 209-219.
    99. Zhang, Yaojie & Ma, Feng & Liao, Yin, 2020. "Forecasting global equity market volatilities," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1454-1475.
    100. Dent, Kieran & Hacioglu Hoke, Sinem & Panagiotopoulos, Apostolos, 2017. "Solvency and wholesale funding cost interactions at UK banks," Bank of England working papers 681, Bank of England.
    101. Liang, Chao & Luo, Qin & Li, Yan & Huynh, Luu Duc Toan, 2023. "Global financial stress index and long-term volatility forecast for international stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 88(C).
    102. Zhang, Yaojie & Lei, Likun & Wei, Yu, 2020. "Forecasting the Chinese stock market volatility with international market volatilities: The role of regime switching," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    103. Niu, Zibo & Demirer, Riza & Suleman, Muhammad Tahir & Zhang, Hongwei & Zhu, Xuehong, 2024. "Do industries predict stock market volatility? Evidence from machine learning models," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 90(C).
    104. Luo, Qin & Bu, Jinfeng & Xu, Weiju & Huang, Dengshi, 2023. "Stock market volatility prediction: Evidence from a new bagging model," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 445-456.
    105. Zhang, Zhikai & He, Mengxi & Zhang, Yaojie & Wang, Yudong, 2021. "Realized skewness and the short-term predictability for aggregate stock market volatility," Economic Modelling, Elsevier, vol. 103(C).
    106. Zongwu Cai & Chaoqun Ma & Xianhua Mi, 2020. "Realized Volatility Forecasting Based on Dynamic Quantile Model Averaging," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202016, University of Kansas, Department of Economics, revised Sep 2020.
    107. Mariia Artemova & Francisco Blasques & Siem Jan Koopman & Zhaokun Zhang, 2021. "Forecasting in a changing world: from the great recession to the COVID-19 pandemic," Tinbergen Institute Discussion Papers 21-006/III, Tinbergen Institute.
    108. Zhang, Xingmin & Zhang, Shuai, 2021. "Optimal time-varying tail risk network with a rolling window approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 580(C).
    109. Liang, Chao & Tang, Linchun & Li, Yan & Wei, Yu, 2020. "Which sentiment index is more informative to forecast stock market volatility? Evidence from China," International Review of Financial Analysis, Elsevier, vol. 71(C).
    110. Subhamitra Patra & Gourishankar S. Hiremath, 2022. "An Entropy Approach to Measure the Dynamic Stock Market Efficiency," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 20(2), pages 337-377, June.
    111. Chien-Ho Wang & Ming-Hui Ko & Wan-Jiun Chen, 2019. "Effects of Kyoto Protocol on CO 2 Emissions: A Five-Country Rolling Regression Analysis," Sustainability, MDPI, vol. 11(3), pages 1-20, January.
    112. Dong, Dayong & Yue, Sishi & Cao, Jiawei, 2020. "Site visit information content and return predictability: Evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    113. Wei, Jie & Zhang, Yonghui, 2020. "A time-varying diffusion index forecasting model," Economics Letters, Elsevier, vol. 193(C).
    114. Li, Xiafei & Guo, Qiang & Liang, Chao & Umar, Muhammad, 2023. "Forecasting gold volatility with geopolitical risk indices," Research in International Business and Finance, Elsevier, vol. 64(C).
    115. Yuntong Liu & Yu Wei & Yi Liu & Wenjuan Li, 2020. "Forecasting Oil Price by Hierarchical Shrinkage in Dynamic Parameter Models," Discrete Dynamics in Nature and Society, Hindawi, vol. 2020, pages 1-12, December.

  26. Barbara Rossi & Tatevik Sekhposyany, 2014. "Forecast Rationality Tests in the Presence of Instabilities, With Applications to Federal Reserve and Survey Forecasts," Working Papers 765, Barcelona School of Economics.

    Cited by:

    1. Carola Conces Binder & Rodrigo Sekkel, 2023. "Central Bank Forecasting: A Survey," Staff Working Papers 23-18, Bank of Canada.
    2. Barbara Rossi & Tatevik Sekhposyan, 2015. "Alternative Tests for Correct Specification of Conditional Predictive Densities," Working Papers 758, Barcelona School of Economics.
    3. Jonathan Benchimol & Makram El-Shagi, 2019. "Forecast Performance in Times of Terrorism," Bank of Israel Working Papers 2019.08, Bank of Israel.
    4. Timmermann, Allan & Pettenuzzo, Davide, 2016. "Forecasting Macroeconomic Variables under Model Instability," CEPR Discussion Papers 11355, C.E.P.R. Discussion Papers.
    5. Andrew C. Chang & Trace J. Levinson, 2023. "Raiders of the lost high‐frequency forecasts: New data and evidence on the efficiency of the Fed's forecasting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(1), pages 88-104, January.
    6. Laura Carabotta & Peter Claeys, 2015. "Combine to compete: improving fiscal forecast accuracy over time," UB School of Economics Working Papers 2015/320, University of Barcelona School of Economics.
    7. 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.
    8. Barbara Rossi & Tatevik Sekhposyan, 2014. "Forecast rationality tests in the presence of instabilities, with applications to Federal Reserve and survey forecasts," Economics Working Papers 1426, Department of Economics and Business, Universitat Pompeu Fabra, revised Nov 2014.
    9. Emmanuel Joel Aikins Abakah & Guglielmo Maria Caporale & Luis A. Gil-Alana, 2020. "Economic Policy Uncertainty: Persistence and Cross-Country Linkages," CESifo Working Paper Series 8289, CESifo.
    10. Panpan Zhu & Qingjie Zhou & Yinpeng Zhang, 2024. "Investor attention and consumer price index inflation rate: Evidence from the United States," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-12, December.
    11. Lukas Hoesch & Barbara Rossi & Tatevik Sekhposyan, 2023. "Has the Information Channel of Monetary Policy Disappeared? Revisiting the Empirical Evidence," American Economic Journal: Macroeconomics, American Economic Association, vol. 15(3), pages 355-387, July.
    12. Christopher S Sutherland, 2022. "Forward guidance and expectation formation: A narrative approach," BIS Working Papers 1024, Bank for International Settlements.
    13. Julien Champagne & Guillaume Poulin-Bellisle & Rodrigo Sekkel, 2018. "Evaluating the Bank of Canada Staff Economic Projections Using a New Database of Real-Time Data and Forecasts," Staff Working Papers 18-52, Bank of Canada.
    14. Lenza, Michele & Moutachaker, Inès & Paredes, Joan, 2023. "Density forecasts of inflation: a quantile regression forest approach," Working Paper Series 2830, European Central Bank.
    15. Martinez-Martin Jaime & Morris Richard & Onorante Luca & Piersanti Fabio Massimo, 2024. "Merging Structural and Reduced-Form Models for Forecasting," The B.E. Journal of Macroeconomics, De Gruyter, vol. 24(1), pages 399-437, January.
    16. Raffaella Giacomini & Barbara Rossi, 2014. "Forecasting in Nonstationary Environments: What Works and What Doesn't in Reduced-Form and Structural Models," Working Papers 819, Barcelona School of Economics.
    17. 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.).
    18. Monique Reid & Pierre Siklos, 2023. "Rationality and biases insights from disaggregated firm level inflation expectations data," Working Papers 11050, South African Reserve Bank.
    19. Robert P. Lieli & Augusto Nieto-Barthaburu, 2023. "Forecasting with Feedback," Papers 2308.15062, arXiv.org, revised Aug 2024.
    20. 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.
    21. Atsushi Inoue & Barbara Rossi, 2018. "The effects of conventional and unconventional monetary policy on exchange rates," Economics Working Papers 1639, Department of Economics and Business, Universitat Pompeu Fabra.
    22. Bianchi, Francesco & Lettau, Martin & Ludvigson, Sydney, 2017. "Monetary Policy and Asset Valuation," CEPR Discussion Papers 12275, C.E.P.R. Discussion Papers.
    23. G. Kontogeorgos & K. Lambrias, 2022. "Evaluating the Eurosystem/ECB staff macroeconomic projections: The first 20 years," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 213-229, March.
    24. 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.
    25. Julien Champagne & Guillaume Poulin‐Bellisle & Rodrigo Sekkel, 2020. "Introducing the Bank of Canada staff economic projections database," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 114-129, January.
    26. El-Shagi, Makram, 2019. "Rationality tests in the presence of instabilities in finite samples," Economic Modelling, Elsevier, vol. 79(C), pages 242-246.
    27. Paul Hubert & Becky Maule, 2021. "Policy and Macro Signals from Central Bank Announcements," International Journal of Central Banking, International Journal of Central Banking, vol. 17(2), pages 255-296, June.
    28. Li, Mengheng & Koopman, Siem Jan & Lit, Rutger & Petrova, Desislava, 2020. "Long-term forecasting of El Niño events via dynamic factor simulations," Journal of Econometrics, Elsevier, vol. 214(1), pages 46-66.
    29. Rossi, Barbara, 2019. "Identifying and Estimating the Effects of Unconventional Monetary Policy: How to Do It And What Have We Learned?," CEPR Discussion Papers 14064, C.E.P.R. Discussion Papers.
    30. Christopher S. Sutherland, 2023. "Forward guidance and expectation formation: A narrative approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(2), pages 222-241, March.
    31. Michée A. Lachaud & Boris E. Bravo‐Ureta & Carlos E. Ludena, 2022. "Economic effects of climate change on agricultural production and productivity in Latin America and the Caribbean (LAC)," Agricultural Economics, International Association of Agricultural Economists, vol. 53(2), pages 321-332, March.
    32. Barbara Rossi, 2018. "Identifying and estimating the effects of unconventional monetary policy in the data: How to do It and what have we learned?," Economics Working Papers 1641, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2020.
    33. Tae-Hwy Lee & Yiyao Wang, 2019. "Evaluation of the Survey of Professional Forecasters in the Greenbook’s Loss Function," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 17(2), pages 345-360, June.
    34. 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.
    35. Tae-Hwy Lee & Yiyao Wang, 2015. "Finding SPF Percentiles Closest to Greenbook," Working Papers 201503, University of California at Riverside, Department of Economics.
    36. Christopher S. Sutherland, 2020. "Forward Guidance and Expectation Formation: A Narrative Approach," Staff Working Papers 20-40, Bank of Canada.
    37. Lillian R. Gaeto & Sandeep Mazumder, 2019. "Measuring the Accuracy of Federal Reserve Forecasts," Southern Economic Journal, John Wiley & Sons, vol. 85(3), pages 960-984, January.
    38. J. Daniel Aromí & Martín Llada, 2024. "Are professional forecasters inattentive to public discussions? The case of inflation in Argentina," Working Papers 300, Red Nacional de Investigadores en Economía (RedNIE).
    39. Wang, Lu & Zhao, Chenchen & Liang, Chao & Jiu, Song, 2022. "Predicting the volatility of China's new energy stock market: Deep insight from the realized EGARCH-MIDAS model," Finance Research Letters, Elsevier, vol. 48(C).
    40. Martínez-Martin, Jaime & Morris, Richard & Onorante, Luca & Piersanti, Fabio M., 2019. "Merging structural and reduced-form models for forecasting: opening the DSGE-VAR box," Working Paper Series 2335, European Central Bank.
    41. Carlos Henrique Dias Cordeiro de Castro & Fernando Antonio Lucena Aiube, 2023. "Forecasting inflation time series using score‐driven dynamic models and combination methods: The case of Brazil," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 369-401, March.
    42. 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.

  27. Barbara Rossi & Tatevik Sehkposyan, 2013. "Evaluating Predictive Densities of US Output Growth and Inflation in a Large Macroeconomic Data Set," Working Papers 689, Barcelona School of Economics.

    Cited by:

    1. Marine Carrasco & Barbara Rossi, 2016. "In-sample inference and forecasting in misspecified factor models," Economics Working Papers 1530, Department of Economics and Business, Universitat Pompeu Fabra.
    2. 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.
    3. Barnett, William & Park, Sohee, 2021. "Forecasting Inflation and Output Growth with Credit-Card-Augmented Divisia Monetary Aggregates," MPRA Paper 110298, University Library of Munich, Germany.
    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. Berg, Tim O. & Henzel, Steffen R., 2015. "Point and density forecasts for the euro area using Bayesian VARs," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1067-1095.
    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. 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.
    8. 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.
    9. Barbara Rossi, 2019. "Forecasting in the presence of instabilities: How do we know whether models predict well and how to improve them," Economics Working Papers 1711, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2021.
    10. 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.
    11. 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.
    12. Rossi, Barbara & Ganics, Gergely & Sekhposyan, Tatevik, 2020. "From Fixed-event to Fixed-horizon Density Forecasts: Obtaining Measures of Multi-horizon Uncertainty from Survey Density Foreca," CEPR Discussion Papers 14267, C.E.P.R. Discussion Papers.
    13. Matteo Mogliani & Anna Simoni, 2020. "Bayesian MIDAS penalized regressions: Estimation, selection, and prediction," Post-Print hal-03089878, HAL.
    14. Raffaella Giacomini & Barbara Rossi, 2014. "Forecasting in Nonstationary Environments: What Works and What Doesn't in Reduced-Form and Structural Models," Working Papers 819, Barcelona School of Economics.
    15. Barbara Rossi & Tatevik Sekhposyan, 2015. "Macroeconomic uncertainty indices based on nowcast and forecast error distributions," Economics Working Papers 1477, Department of Economics and Business, Universitat Pompeu Fabra.
    16. Peter Claeys, 2017. "Uncertainty spillover and policy reactions," Revista ESPE - Ensayos sobre Política Económica, Banco de la Republica de Colombia, vol. 35(82), pages 64-77, April.
    17. 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.
    18. Justyna Wróblewska & Anna Pajor, 2019. "One-period joint forecasts of Polish inflation, unemployment and interest rate using Bayesian VEC-MSF models," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 11(1), pages 23-45, March.
    19. 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.
    20. Edward S. Knotek & Saeed Zaman, 2020. "Real-Time Density Nowcasts of US Inflation: A Model-Combination Approach," Working Papers 20-31, Federal Reserve Bank of Cleveland.
    21. Graziano Moramarco, 2021. "Financial-cycle ratios and medium-term predictions of GDP: Evidence from the United States," Papers 2111.00822, arXiv.org, revised Jan 2024.
    22. Gergely Akos Ganics, 2017. "Optimal density forecast combinations," Working Papers 1751, Banco de España.
    23. Ouysse, Rachida, 2016. "Bayesian model averaging and principal component regression forecasts in a data rich environment," International Journal of Forecasting, Elsevier, vol. 32(3), pages 763-787.
    24. Andrea Carriero & Galvao, Ana Beatriz & Kapetanios, George, 2016. "A comprehensive evaluation of macroeconomic forecasting methods," EMF Research Papers 10, Economic Modelling and Forecasting Group.
    25. 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.
    26. 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.
    27. 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.
    28. Taylor, James W., 2020. "A strategic predictive distribution for tests of probabilistic calibration," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1380-1388.
    29. Marcus P. A. Cobb, 2020. "Aggregate density forecasting from disaggregate components using Bayesian VARs," Empirical Economics, Springer, vol. 58(1), pages 287-312, January.
    30. Korobilis, Dimitris, 2017. "Quantile regression forecasts of inflation under model uncertainty," International Journal of Forecasting, Elsevier, vol. 33(1), pages 11-20.
    31. Graziano Moramarco, 2021. "Regime-Switching Density Forecasts Using Economists' Scenarios," Papers 2110.13761, arXiv.org, revised Feb 2024.
    32. 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.
    33. 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.
    34. Matei Demetrescu & Robinson Kruse-Becher, 2021. "Is U.S. real output growth really non-normal? Testing distributional assumptions in time-varying location-scale models," CREATES Research Papers 2021-07, Department of Economics and Business Economics, Aarhus University.
    35. Foltas, Alexander & Pierdzioch, Christian, 2020. "On the efficiency of German growth forecasts: An empirical analysis using quantile random forests," Working Papers 21, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    36. Carriero, Andrea & Galvão, Ana Beatriz & Kapetanios, George, 2019. "A comprehensive evaluation of macroeconomic forecasting methods," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1226-1239.
    37. Sebastiano Manzan, 2015. "Forecasting the Distribution of Economic Variables in a Data-Rich Environment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(1), pages 144-164, January.
    38. Magnus Reif, 2018. "Macroeconomic Uncertainty and Forecasting Macroeconomic Aggregates," ifo Working Paper Series 265, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    39. Stephen McKnight & Alexander Mihailov & Fabio Rumler, 2018. "NKPC-Based Inflation Forecasts with a Time-Varying Trend," Serie documentos de trabajo del Centro de Estudios Económicos 2018-05, El Colegio de México, Centro de Estudios Económicos.
    40. 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.
    41. Federico Bassetti & Roberto Casarin & Francesco Ravazzolo, 2019. "Density Forecasting," BEMPS - Bozen Economics & Management Paper Series BEMPS59, Faculty of Economics and Management at the Free University of Bozen.

  28. Barbara Rossi, 2013. "Exchange Rate Predictability," Working Papers 690, Barcelona School of Economics.

    Cited by:

    1. Teona Shugliashvili, 2023. "The words have power: the impact of news on exchange rates," FFA Working Papers 5.006, Prague University of Economics and Business, revised 31 Jul 2023.
    2. Serna, Gregorio, 2023. "On the predictive ability of conditional market skewness," The Quarterly Review of Economics and Finance, Elsevier, vol. 91(C), pages 186-191.
    3. Kang, Wensheng & Ratti, Ronald. A. & Vespignani, Joaquin, 2016. "The implications of liquidity expansion in China for the US dollar," Working Papers 2016-02, University of Tasmania, Tasmanian School of Business and Economics.
    4. Rossi, José Luiz Júnior, 2013. "Liquidity and Exchange Rates," Insper Working Papers wpe_325, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    5. Bush, Georgia & López Noria, Gabriela, 2021. "Uncertainty and exchange rate volatility: Evidence from Mexico," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 704-722.
    6. Yuchen Zhang & Shigeyuki Hamori, 2020. "The Predictability of the Exchange Rate When Combining Machine Learning and Fundamental Models," JRFM, MDPI, vol. 13(3), pages 1-16, March.
    7. Huber, Florian, 2017. "Structural breaks in Taylor rule based exchange rate models — Evidence from threshold time varying parameter models," Economics Letters, Elsevier, vol. 150(C), pages 48-52.
    8. Refet S. Gürkaynak & Burcin Kisacikoglu & Sang Seok Lee, 2022. "Exchange Rate and Inflation under Weak Monetary Policy: Turkey Verifies Theory," CESifo Working Paper Series 9748, CESifo.
    9. Park, Cheolbeom & Park, Suyeon, 2020. "Rare disaster risk and exchange rates: An empirical investigation of South Korean exchange rates under tension between the two Koreas," Finance Research Letters, Elsevier, vol. 36(C).
    10. Maggiori, Matteo & Lilley, Andrew & Neiman, Brent & Schreger, Jesse, 2020. "Exchange Rate Reconnect," CEPR Discussion Papers 13869, C.E.P.R. Discussion Papers.
    11. Ibrahim D. Raheem & Xuan Vinh Vo, 2022. "A new approach to exchange rate forecast: The role of global financial cycle and time‐varying parameters," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 2836-2848, July.
    12. 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.
    13. Stijn Claessens & M Ayhan Kose, 2018. "Frontiers of macrofinancial linkages," BIS Papers, Bank for International Settlements, number 95.
    14. Fratzscher, Marcel & Rime, Dagfinn & Sarno, Lucio & Zinna, Gabriele, 2015. "The scapegoat theory of exchange rates: the first tests," Journal of Monetary Economics, Elsevier, vol. 70(C), pages 1-21.
    15. 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.
    16. Timo Dimitriadis & Andrew J. Patton & Patrick W. Schmidt, 2019. "Testing Forecast Rationality for Measures of Central Tendency," Papers 1910.12545, arXiv.org, revised Jul 2024.
    17. Ondrej Bednar, 2021. "The Causal Impact of the Rapid Czech Interest Rate Hike on the Czech Exchange Rate Assessed by the Bayesian Structural Time Series Model," International Journal of Economic Sciences, European Research Center, vol. 10(2), pages 1-17, December.
    18. Raheem, Ibrahim, 2020. "Global financial cycles and exchange rate forecast: A factor analysis," MPRA Paper 105358, University Library of Munich, Germany.
    19. Biswas, Rita & Li, Xiao & Piccotti, Louis R., 2023. "Do macroeconomic variables drive exchange rates independently?," Finance Research Letters, Elsevier, vol. 52(C).
    20. Breen, John David & Hu, Liang, 2021. "The predictive content of oil price and volatility: New evidence on exchange rate forecasting," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
    21. Božović, Miloš & Ivanović, Jelena, 2017. "Adverse risk interaction: An integrated approach," Economic Modelling, Elsevier, vol. 65(C), pages 67-74.
    22. Pozo, Jorge, 2023. "Sectoral credit reallocation: An excessive bank risk-taking explanation," Emerging Markets Review, Elsevier, vol. 54(C).
    23. Pinto, Jeronymo Marcondes & Marçal, Emerson Fernandes, 2019. "Cross-validation based forecasting method: a machine learning approach," Textos para discussão 498, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    24. 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.
    25. Martin Evans & Dagfinn Rime, 2015. "Order Flow Information and Spot Rate Dynamics," Working Papers gueconwpa~15-15-02, Georgetown University, Department of Economics.
    26. Chen, Shiu-Sheng & Chou, Yu-Hsi, 2023. "Liquidity yield and exchange rate predictability," Journal of International Money and Finance, Elsevier, vol. 137(C).
    27. Beckmann, Joscha & Czudaj, Robert L., 2020. "Fundamental determinants of exchange rate expectations," VfS Annual Conference 2020 (Virtual Conference): Gender Economics 224617, Verein für Socialpolitik / German Economic Association.
    28. Wenting Liao & Jun Ma & Chengsi Zhang, 2023. "Identifying exchange rate effects and spillovers of US monetary policy shocks in the presence of time‐varying instrument relevance," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(7), pages 989-1006, November.
    29. Michał Brzozowski & Grzegorz Tchorek, 2017. "Exchange Rate Risk as an Obstacle to Export Activity," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 3, pages 115-141.
    30. Byrne, Joseph P. & Ibrahim, Boulis Maher & Sakemoto, Ryuta, 2022. "The time-varying risk price of currency portfolios," Journal of International Money and Finance, Elsevier, vol. 124(C).
    31. Wellmann, Dennis & Trück, Stefan, 2018. "Factors of the term structure of sovereign yield spreads," Journal of International Money and Finance, Elsevier, vol. 81(C), pages 56-75.
    32. Pablo Pincheira & Nicolas Hardy & Andrea Bentancor, 2022. "A Simple Out-of-Sample Test of Predictability against the Random Walk Benchmark," Mathematics, MDPI, vol. 10(2), pages 1-20, January.
    33. Sakemoto, Ryuta, 2019. "Currency carry trades and the conditional factor model," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 198-208.
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    2. Barbara Rossi & Tatevik Sekhposyan, 2015. "Alternative Tests for Correct Specification of Conditional Predictive Densities," Working Papers 758, Barcelona School of Economics.
    3. Michał Rubaszek, 2019. "Forecasting crude oil prices with DSGE models," GRU Working Paper Series GRU_2019_024, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
    4. Boneva, Lena & Fawcett, Nicholas & Masolo, Riccardo M. & Waldron, Matt, 2019. "Forecasting the UK economy: Alternative forecasting methodologies and the role of off-model information," International Journal of Forecasting, Elsevier, vol. 35(1), pages 100-120.
    5. Gulan, Adam, 2018. "Paradise lost? A brief history of DSGE macroeconomics," Bank of Finland Research Discussion Papers 22/2018, Bank of Finland.
    6. Gelfer, Sacha, 2021. "Evaluating the forecasting power of an open-economy DSGE model when estimated in a data-Rich environment," Journal of Economic Dynamics and Control, Elsevier, vol. 129(C).
    7. Martinez-Martin Jaime & Morris Richard & Onorante Luca & Piersanti Fabio Massimo, 2024. "Merging Structural and Reduced-Form Models for Forecasting," The B.E. Journal of Macroeconomics, De Gruyter, vol. 24(1), pages 399-437, January.
    8. Nasir, Muhammad Ali, 2020. "Forecasting inflation under uncertainty: The forgotten dog and the frisbee," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    9. Marcin Kolasa & Michał Rubaszek, 2018. "Does the foreign sector help forecast domestic variables in DSGE models?," NBP Working Papers 282, Narodowy Bank Polski.
    10. 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.
    11. Gergely Akos Ganics, 2017. "Optimal density forecast combinations," Working Papers 1751, Banco de España.
    12. Ca' Zorzi, Michele & Kolasa, Marcin & Rubaszek, Michał, 2016. "Exchange rate forecasting with DSGE models," Working Paper Series 1905, European Central Bank.
    13. 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.
    14. Ángel Estrada & Luis Guirola & Iván Kataryniuk & Jaime Martínez-Martín, 2020. "The use of BVARs in the analysis of emerging economies," Occasional Papers 2001, Banco de España.
    15. Luca Fanelli & Marco M. Sorge, 2015. "Indeterminacy, Misspecification and Forecastability: Good Luck in Bad Policy?," CSEF Working Papers 402, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    16. Fakhri J. Hasanov & Noha Razek, 2023. "Oil and Non-Oil Determinants of Saudi Arabia’s International Competitiveness: Historical Analysis and Policy Simulations," Sustainability, MDPI, vol. 15(11), pages 1-39, June.
    17. Minford, Patrick & Zhou, Peng & Xu, Yongdeng, 2014. "How good are out of sample forecasting Tests on DSGE models?," CEPR Discussion Papers 10239, C.E.P.R. Discussion Papers.
    18. Barbara Rossi, 2014. "Comment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(4), pages 510-514, October.
    19. Roberta Cardani & Alessia Paccagnini & Stefania Villa, 2019. "Forecasting with instabilities: an application to DSGE models with financial frictions," Temi di discussione (Economic working papers) 1234, Bank of Italy, Economic Research and International Relations Area.
    20. Pami Dua, 2023. "Macroeconomic Modelling and Bayesian Methods," Springer Books, in: Pami Dua (ed.), Macroeconometric Methods, chapter 0, pages 19-37, Springer.
    21. Michael Wickens, 2014. "How did we get to where we are now? Reflections on 50 years of macroeconomic and financial econometrics," Discussion Papers 14/17, Department of Economics, University of York.
    22. Ian Borg & Germano Ruisi, 2018. "Forecasting using Bayesian VARs: A Benchmark for STREAM," CBM Working Papers WP/04/2018, Central Bank of Malta.
    23. Roberta Cardani & Alessia Paccagnini & Stefania Villa, 2015. "Forecasting in a DSGE Model with Banking Intermediation: Evidence from the US," Working Papers 292, University of Milano-Bicocca, Department of Economics, revised Feb 2015.
    24. Michael Wickens, 2015. "How Did We Get to Where We Are Now? Reflections on 50 Years of Macroeconomic and Financial Econometrics," Manchester School, University of Manchester, vol. 83, pages 60-82, December.
    25. Ohnsorge,Franziska Lieselotte & Stocker,Marc & Some,Modeste Y., 2016. "Quantifying uncertainties in global growth forecasts," Policy Research Working Paper Series 7770, The World Bank.
    26. Domit, Sílvia & Monti, Francesca & Sokol, Andrej, 2019. "Forecasting the UK economy with a medium-scale Bayesian VAR," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1669-1678.
    27. Chatterjee, Sidharta, 2014. "Equilibrium Models of Macroeconomic Science: What to Look For in (DSGE) Models?," MPRA Paper 53893, University Library of Munich, Germany.
    28. Eric Jondeau & Michael Rockinger, 2019. "Predicting Long‐Term Financial Returns: VAR versus DSGE Model—A Horse Race," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 51(8), pages 2239-2291, December.
    29. 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.

  30. Barbara Rossi & Tatevik Sehkposyan, 2013. "Conditional Predictive Density Evaluation in the Presence of Instabilities," Working Papers 688, Barcelona School of Economics.

    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. Jonas Dovern & Hans Manner, 2018. "Order Invariant Tests for Proper Calibration of Multivariate Density Forecasts," CESifo Working Paper Series 7023, CESifo.
    3. Michael Clements, 2016. "Are Macroeconomic Density Forecasts Informative?," ICMA Centre Discussion Papers in Finance icma-dp2016-02, Henley Business School, University of Reading.
    4. Emilio Zanetti Chini, 2018. "Forecaster’s utility and forecasts coherence," CREATES Research Papers 2018-01, Department of Economics and Business Economics, Aarhus University.
    5. Rossi, Barbara, 2013. "Exchange Rate Predictability," CEPR Discussion Papers 9575, C.E.P.R. Discussion Papers.
    6. João Henrique G. Mazzeu & Gloria González-Rivera & Esther Ruiz & Helena Veiga, 2020. "A bootstrap approach for generalized Autocontour testing Implications for VIX forecast densities," Econometric Reviews, Taylor & Francis Journals, vol. 39(10), pages 971-990, November.
    7. Gloria Gonzalez-Rivera & Yingying Sun, 2016. "Density Forecast Evaluation in Unstable Environments," Working Papers 201606, University of California at Riverside, Department of Economics.
    8. Barbara Rossi & Tatevik Sekhposyan, 2013. "Evaluating predictive densities of U.S. output growth and inflation in a large macroeconomic data set," Economics Working Papers 1370, Department of Economics and Business, Universitat Pompeu Fabra.
    9. 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.
    10. Barbara Rossi, 2019. "Forecasting in the presence of instabilities: How do we know whether models predict well and how to improve them," Economics Working Papers 1711, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2021.
    11. Rossi, Barbara & Ganics, Gergely & Sekhposyan, Tatevik, 2020. "From Fixed-event to Fixed-horizon Density Forecasts: Obtaining Measures of Multi-horizon Uncertainty from Survey Density Foreca," CEPR Discussion Papers 14267, C.E.P.R. Discussion Papers.
    12. Tommaso Proietti & Martyna Marczak & Gianluigi Mazzi, 2015. "EuroMInd-D: A Density Estimate of Monthly Gross Domestic Product for the Euro Area," CEIS Research Paper 340, Tor Vergata University, CEIS, revised 10 Apr 2015.
    13. Raffaella Giacomini & Barbara Rossi, 2014. "Forecasting in Nonstationary Environments: What Works and What Doesn't in Reduced-Form and Structural Models," Working Papers 819, Barcelona School of Economics.
    14. Zdeněk Zmeškal & Dana Dluhošová & Karolina Lisztwanová & Antonín Pončík & Iveta Ratmanová, 2023. "Distribution Prediction of Decomposed Relative EVA Measure with Levy-Driven Mean-Reversion Processes: The Case of an Automotive Sector of a Small Open Economy," Forecasting, MDPI, vol. 5(2), pages 1-19, May.
    15. Gergely Akos Ganics, 2017. "Optimal density forecast combinations," Working Papers 1751, Banco de España.
    16. Davide Delle Monache & Ivan Petrella, 2014. "Adaptive Models and Heavy Tails," Working Papers 720, Queen Mary University of London, School of Economics and Finance.
    17. 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.
    18. Barbara Rossi, 2014. "Comment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(4), pages 510-514, October.
    19. Gregor Bäurle & Elizabeth Steiner & Gabriel Züllig, 2021. "Forecasting the production side of GDP," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 458-480, April.
    20. Barbara Rossi, 2018. "Identifying and estimating the effects of unconventional monetary policy in the data: How to do It and what have we learned?," Economics Working Papers 1641, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2020.
    21. Clements, Michael P. & Galvao, Ana Beatriz, 2020. "Density Forecasting with BVAR Models under Macroeconomic Data Uncertainty," EMF Research Papers 36, Economic Modelling and Forecasting Group.
    22. Federico Bassetti & Roberto Casarin & Francesco Ravazzolo, 2019. "Density Forecasting," BEMPS - Bozen Economics & Management Paper Series BEMPS59, Faculty of Economics and Management at the Free University of Bozen.

  31. Barbara Rossi, 2012. "The changing relationship between commodity prices and equity prices in commodity exporting," Economics Working Papers 1405, Department of Economics and Business, Universitat Pompeu Fabra.

    Cited by:

    1. Bharat Kumar Meher & Iqbal Thonse Hawaldar & Santosh Kumar & Abhishek Kumar Gupta, 2022. "Modelling Market Indices, Commodity Market Prices and Stock Prices of Energy Sector using VAR with Variance Decomposition Model," International Journal of Energy Economics and Policy, Econjournals, vol. 12(4), pages 122-130, July.
    2. Rossi, José Luiz Júnior, 2013. "Liquidity and Exchange Rates," Insper Working Papers wpe_325, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    3. Shernaz Bodhanwala & Harsh Purohit & Nidhi Choudhary, 2020. "The Causal Dynamics in Indian Agriculture Commodity Prices and Macro-Economic Variables in the Presence of a Structural Break," Global Business Review, International Management Institute, vol. 21(1), pages 241-261, February.
    4. Martin Hodula & Jan Janku & Simona Malovana & Ngoc Anh Ngo, 2024. "Geopolitical Risks and Their Impact on Global Macro-Financial Stability: Literature and Measurements," Working Papers 2024/8, Czech National Bank.
    5. Pincheira, Pablo & Hardy, Nicolás, 2019. "Forecasting Aluminum Prices with Commodity Currencies," MPRA Paper 97005, University Library of Munich, Germany.
    6. Shiu-Sheng Chen, 2016. "Commodity prices and related equity prices," Canadian Journal of Economics, Canadian Economics Association, vol. 49(3), pages 949-967, August.
    7. 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.
    8. Lajis, Siti & Masih, Mansur, 2018. "Is the islamic equity market independent of the influence of primary commodities ? Malaysian evidence," MPRA Paper 104766, University Library of Munich, Germany.
    9. Rangga Handika & Rangga Handika & Sigit Triandaru, 2016. "Is the Best Generalized Autoregressive Conditional Heteroskedasticity(p,q) Value-at-risk Estimate also the Best in Reality? An Evidence from Australian Interconnected Power Markets," International Journal of Energy Economics and Policy, Econjournals, vol. 6(4), pages 814-821.
    10. Omura, Akihiro & Todorova, Neda & Li, Bin & Chung, Richard, 2016. "Steel scrap and equity market in Japan," Resources Policy, Elsevier, vol. 47(C), pages 115-124.
    11. Felício, Wilson Rafael de Oliveira & Rossi, José Luiz Júnior, 2013. "Common factors and the exchange rate: results from the Brazilian case," Insper Working Papers wpe_318, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    12. Rangga Handika & Sania Ashraf, 2018. "Financialized Commodities and Stock Indices Volatilities," European Research Studies Journal, European Research Studies Journal, vol. 0(1), pages 153-164.
    13. 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).
    14. Pablo Pincheira-Brown & Nicolás Hardy & Cristobal Henrriquez & Ignacio Tapia & Andrea Bentancor, 2023. "Forecasting Base Metal Prices with an International Stock Index," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 73(3), pages 277-302, October.
    15. Rose Mary K. Abraham, 2022. "Financialisation of Commodity Markets: Evidence from India," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 16(1), pages 106-131, February.
    16. Boako, Gideon & Alagidede, Imhotep Paul & Sjo, Bo & Uddin, Gazi Salah, 2020. "Commodities price cycles and their interdependence with equity markets," Energy Economics, Elsevier, vol. 91(C).
    17. Rossi, José Luiz Júnior, 2014. "The Usefulness of Financial Variables in Predicting Exchange Rate Movements," Insper Working Papers wpe_332, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    18. Sohag, Kazi & Shams, S.M. Riad & Gainetdinova, Anna & Nappo, Fabio, 2023. "Frequency connectedness and cross-quantile dependence among medicare, medicine prices and health-tech equity," Technovation, Elsevier, vol. 120(C).

  32. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.

    Cited by:

    1. Marine Carrasco & Barbara Rossi, 2016. "In-sample inference and forecasting in misspecified factor models," Economics Working Papers 1530, Department of Economics and Business, Universitat Pompeu Fabra.
    2. Yin, Anwen, 2015. "Forecasting and model averaging with structural breaks," ISU General Staff Papers 201501010800005727, Iowa State University, Department of Economics.
    3. 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.
    4. Granziera, Eleonora & Sekhposyan, Tatevik, 2019. "Predicting relative forecasting performance: An empirical investigation," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1636-1657.
    5. Manuel Lukas & Eric Hillebrand, 2014. "Bagging Weak Predictors," CREATES Research Papers 2014-01, Department of Economics and Business Economics, Aarhus University.
    6. Timmermann, Allan & Pettenuzzo, Davide, 2016. "Forecasting Macroeconomic Variables under Model Instability," CEPR Discussion Papers 11355, C.E.P.R. Discussion Papers.
    7. Xiaojie Xu, 2017. "The rolling causal structure between the Chinese stock index and futures," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 31(4), pages 491-509, November.
    8. Chen, Qitong & Hong, Yongmiao & Li, Haiqi, 2024. "Time-varying forecast combination for factor-augmented regressions with smooth structural changes," Journal of Econometrics, Elsevier, vol. 240(1).
    9. Wolters, Maik Hendrik, 2012. "Evaluating point and density forecasts of DSGE models," MPRA Paper 36147, University Library of Munich, Germany.
    10. Tae-Hwy Lee & Shahnaz Parsaeian & Aman Ullah, 2022. "Forecasting under Structural Breaks Using Improved Weighted Estimation," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202212, University of Kansas, Department of Economics.
    11. Boriss Siliverstovs & Daniel S. Wochner, 2021. "State‐dependent evaluation of predictive ability," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 547-574, April.
    12. Bordo, Michael D. & Haubrich, Joseph G., 2022. "Some international evidence on the causal impact of the yield curve," Finance Research Letters, Elsevier, vol. 45(C).
    13. 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.
    14. 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.
    15. Korobilis, Dimitris & Koop, Gary, 2020. "Bayesian dynamic variable selection in high dimensions," MPRA Paper 100164, University Library of Munich, Germany.
    16. Verena Monschang & Bernd Wilfling, 2022. "A procedure for upgrading linear-convex combination forecasts with an application to volatility prediction," CQE Working Papers 9722, Center for Quantitative Economics (CQE), University of Muenster.
    17. Stefanos Bennett & Jase Clarkson, 2022. "Time Series Prediction under Distribution Shift using Differentiable Forgetting," Papers 2207.11486, arXiv.org.
    18. Eugster, Patrick & Uhl, Matthias W., 2024. "Forecasting inflation using sentiment," Economics Letters, Elsevier, vol. 236(C).
    19. Sun, Yuying & Hong, Yongmiao & Wang, Shouyang & Zhang, Xinyu, 2023. "Penalized time-varying model averaging," Journal of Econometrics, Elsevier, vol. 235(2), pages 1355-1377.
    20. Rossi, Barbara & Wang, Yiru, 2019. "Vector autoregressive-based Granger causality test in the presence of instabilities," MPRA Paper 101492, University Library of Munich, Germany.
    21. Boriss Siliverstovs & Daniel Wochner, 2019. "Recessions as Breadwinner for Forecasters State-Dependent Evaluation of Predictive Ability: Evidence from Big Macroeconomic US Data," KOF Working papers 19-463, KOF Swiss Economic Institute, ETH Zurich.
    22. Jari Hännikäinen, 2016. "Selection of an Estimation Window in the Presence of Data Revisions and Recent Structural Breaks," Working Papers 1692, Tampere University, Faculty of Management and Business, Economics.
    23. 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.
    24. Barbara Rossi & Yiru Wang, 2019. "VAR-Based Granger-Causality Test in the Presence of Instabilities," Working Papers 1083, Barcelona School of Economics.
    25. Hännikäinen, Jari, 2014. "Multi-step forecasting in the presence of breaks," MPRA Paper 55816, University Library of Munich, Germany.
    26. Kajal Lahiri & George Monokroussos & Yongchen Zhao, 2016. "Forecasting Consumption: the Role of Consumer Confidence in Real Time with many Predictors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1254-1275, November.
    27. Fouliard, Jeremy & Howell, Michael & Rey, Hélène & Stavrakeva, Vania, 2022. "Answering the Queen: Machine Learning and Financial Crises," CEPR Discussion Papers 15618, C.E.P.R. Discussion Papers.
    28. Hännikäinen, Jari, 2016. "When does the yield curve contain predictive power? Evidence from a data-rich environment," MPRA Paper 70489, University Library of Munich, Germany.
    29. Dellas, Harris & Gibson, Heather D. & Hall, Stephen G. & Tavlas, George S., 2018. "The macroeconomic and fiscal implications of inflation forecast errors," Journal of Economic Dynamics and Control, Elsevier, vol. 93(C), pages 203-217.
    30. Hännikäinen, Jari, 2014. "Zero lower bound, unconventional monetary policy and indicator properties of interest rate spreads," MPRA Paper 56737, University Library of Munich, Germany.
    31. Galvao, Ana Beatriz & Garratt, Anthony & Mitchell, James, 2020. "Does Judgment Improve Macroeconomic Density Forecasts?," EMF Research Papers 33, Economic Modelling and Forecasting Group.
    32. Koo, Bonsoo & Anderson, Heather M. & Seo, Myung Hwan & Yao, Wenying, 2020. "High-dimensional predictive regression in the presence of cointegration," Journal of Econometrics, Elsevier, vol. 219(2), pages 456-477.
    33. Mwasi Paza Mboya & Philipp Sibbertsen, 2023. "Optimal forecasts in the presence of discrete structural breaks under long memory," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1889-1908, November.
    34. Dagher, Leila & Jamali, Ibrahim & badra, nasser, 2018. "The Predictive Power of Oil and Commodity Prices for Equity Markets," MPRA Paper 116055, University Library of Munich, Germany.
    35. Stephen G. Hall & George S. Tavlas & Yongli Wang, 2023. "Forecasting inflation: the use of dynamic factor analysis and nonlinear combinations," Working Papers 314, Bank of Greece.
    36. Giacomo Sbrana & Andrea Silvestrini & Fabrizio Venditti, 2015. "Short term inflation forecasting: the M.E.T.A. approach," Temi di discussione (Economic working papers) 1016, Bank of Italy, Economic Research and International Relations Area.
    37. Ouysse, Rachida, 2016. "Bayesian model averaging and principal component regression forecasts in a data rich environment," International Journal of Forecasting, Elsevier, vol. 32(3), pages 763-787.
    38. 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.
    39. George Kapetanios & Stephen Millard & Katerina Petrova & Simon Price, 2018. "Time varying cointegration and the UK great ratios," CAMA Working Papers 2018-53, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    40. 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.
    41. Kapetanios, George & Price, Simon & Young, Garry, 2017. "A UK financial conditions index using targeted data reduction: forecasting and structural identification," Bank of England working papers 699, Bank of England.
    42. Pesaran, M. Hashem & Pick, Andreas & Pranovich, Mikhail, 2013. "Optimal forecasts in the presence of structural breaks," Journal of Econometrics, Elsevier, vol. 177(2), pages 134-152.
    43. Pincheira-Brown, Pablo & Neumann, Federico, 2020. "Can we beat the Random Walk? The case of survey-based exchange rate forecasts in Chile," Finance Research Letters, Elsevier, vol. 37(C).
    44. Rossi, Barbara & Inoue, Atsushi & Jin, Lu, 2014. "Window Selection for Out-of-Sample Forecasting with Time-Varying Parameters," CEPR Discussion Papers 10168, C.E.P.R. Discussion Papers.
    45. Zhu, Yinchu & Timmermann, Allan, 2022. "Conditional rotation between forecasting models," Journal of Econometrics, Elsevier, vol. 231(2), pages 329-347.
    46. 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.
    47. Cederburg, Scott & O’Doherty, Michael S. & Wang, Feifei & Yan, Xuemin (Sterling), 2020. "On the performance of volatility-managed portfolios," Journal of Financial Economics, Elsevier, vol. 138(1), pages 95-117.
    48. Timmermann, Allan & Zhu, Yinchu, 2021. "Conditional Rotation Between Forecasting Models," CEPR Discussion Papers 15917, C.E.P.R. Discussion Papers.
    49. Till Weigt & Bernd Wilfling, 2018. "An approach to increasing forecast-combination accuracy through VAR error modeling," CQE Working Papers 6818, Center for Quantitative Economics (CQE), University of Muenster.
    50. Kley, Tobias & Preuss, Philip & Fryzlewicz, Piotr, 2019. "Predictive, finite-sample model choice for time series under stationarity and non-stationarity," LSE Research Online Documents on Economics 101748, London School of Economics and Political Science, LSE Library.
    51. 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.
    52. Inoue, Atsushi & Jin, Lu & Rossi, Barbara, 2017. "Rolling window selection for out-of-sample forecasting with time-varying parameters," Journal of Econometrics, Elsevier, vol. 196(1), pages 55-67.
    53. Julien Champagne & Guillaume Poulin‐Bellisle & Rodrigo Sekkel, 2020. "Introducing the Bank of Canada staff economic projections database," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 114-129, January.
    54. 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.
    55. Barbara Rossi, 2014. "Comment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(4), pages 510-514, October.
    56. Yusupova, Alisa & Pavlidis, Nicos G. & Pavlidis, Efthymios G., 2023. "Dynamic linear models with adaptive discounting," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1925-1944.
    57. Marcus P. A. Cobb, 2020. "Aggregate density forecasting from disaggregate components using Bayesian VARs," Empirical Economics, Springer, vol. 58(1), pages 287-312, January.
    58. Smith, Simon C. & Timmermann, Allan & Zhu, Yinchu, 2019. "Variable selection in panel models with breaks," Journal of Econometrics, Elsevier, vol. 212(1), pages 323-344.
    59. Gregor Bäurle & Elizabeth Steiner & Gabriel Züllig, 2021. "Forecasting the production side of GDP," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 458-480, April.
    60. Yousuf, Kashif & Ng, Serena, 2021. "Boosting high dimensional predictive regressions with time varying parameters," Journal of Econometrics, Elsevier, vol. 224(1), pages 60-87.
    61. Jeffrey C. Chen & Abe Dunn & Kyle Hood & Alexander Driessen & Andrea Batch, 2019. "Off to the Races: A Comparison of Machine Learning and Alternative Data for Predicting Economic Indicators," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 373-402, National Bureau of Economic Research, Inc.
    62. Bloem da Silveira Junior, Luiz A. & Vasconcellos, Eduardo & Vasconcellos Guedes, Liliana & Guedes, Luis Fernando A. & Costa, Renato Machado, 2018. "Technology roadmapping: A methodological proposition to refine Delphi results," Technological Forecasting and Social Change, Elsevier, vol. 126(C), pages 194-206.
    63. Ciner, Cetin, 2017. "Predicting white metal prices by a commodity sensitive exchange rate," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 309-315.
    64. Juergen Amann & Paul Middleditch, 2017. "Growth in a time of austerity: evidence from the UK," Scottish Journal of Political Economy, Scottish Economic Society, vol. 64(4), pages 349-375, September.
    65. Jiun-Hua Su, 2021. "No-Regret Forecasting with Egalitarian Committees," Papers 2109.13801, arXiv.org.
    66. Peter Reinhard Hansen & Allan Timmermann, 2015. "Comment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(1), pages 17-21, January.
    67. Elliott, Graham & Timmermann, Allan G, 2016. "Forecasting in Economics and Finance," University of California at San Diego, Economics Working Paper Series qt6z55v472, Department of Economics, UC San Diego.
    68. Gaglianone, Wagner Piazza & Marins, Jaqueline Terra Moura, 2017. "Evaluation of exchange rate point and density forecasts: An application to Brazil," International Journal of Forecasting, Elsevier, vol. 33(3), pages 707-728.
    69. Procasky, William J. & Yin, Anwen, 2023. "The impact of COVID-19 on the relative market efficiency and forecasting ability of credit derivative and equity markets," International Review of Financial Analysis, Elsevier, vol. 90(C).
    70. Cecilia Frale & Stefano Grassi & Massimiliano Marcellino & Gianluigi Mazzi & Tommaso Proietti, 2013. "EuroMInd-C: a Disaggregate Monthly Indicator of Economic Activity for the Euro Area and member countries," CEIS Research Paper 287, Tor Vergata University, CEIS, revised 01 Oct 2013.
    71. Alisa Yusupova & Nicos G. Pavlidis & Efthymios G. Pavlidis, 2019. "Adaptive Dynamic Model Averaging with an Application to House Price Forecasting," Papers 1912.04661, arXiv.org.
    72. Rossi, Barbara & Gürkaynak, Refet & Kısacıkoğlu, Burçin, 2013. "Do DSGE Models Forecast More Accurately Out-of-Sample than VAR Models?," CEPR Discussion Papers 9576, C.E.P.R. Discussion Papers.
    73. Jari Hännikäinen, 2015. "Zero lower bound, unconventional monetary policy and indicator properties of interest rate spreads," Review of Financial Economics, John Wiley & Sons, vol. 26(1), pages 47-54, September.
    74. Xiaojie Xu, 2018. "Cointegration and price discovery in US corn cash and futures markets," Empirical Economics, Springer, vol. 55(4), pages 1889-1923, December.
    75. Daria Loginova & Stefan Mann, 2023. "Measuring stability and structural breaks: Applications in social sciences," Journal of Economic Surveys, Wiley Blackwell, vol. 37(2), pages 302-320, April.
    76. Daniel Wochner, 2020. "Dynamic Factor Trees and Forests – A Theory-led Machine Learning Framework for Non-Linear and State-Dependent Short-Term U.S. GDP Growth Predictions," KOF Working papers 20-472, KOF Swiss Economic Institute, ETH Zurich.
    77. Mariia Artemova & Francisco Blasques & Siem Jan Koopman & Zhaokun Zhang, 2021. "Forecasting in a changing world: from the great recession to the COVID-19 pandemic," Tinbergen Institute Discussion Papers 21-006/III, Tinbergen Institute.
    78. Nonejad, Nima, 2022. "Equity premium prediction using the price of crude oil: Uncovering the nonlinear predictive impact," Energy Economics, Elsevier, vol. 115(C).
    79. Byrne, Joseph P. & Cao, Shuo & Korobilis, Dimitris, 2017. "Forecasting the term structure of government bond yields in unstable environments," Journal of Empirical Finance, Elsevier, vol. 44(C), pages 209-225.
    80. 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.

  33. Barbara Rossi & Sarah Zubairy, 2011. "What is the Importance of Monetary and Fiscal Shocks in Explaining US Macroeconomic Fluctuations?," Working Papers 11-02, Duke University, Department of Economics.

    Cited by:

    1. Guglielmo Maria Caporale & Mauro Costantini & Antonio Paradiso, 2012. "Re-examining the Decline in the US Saving Rate: The Impact of Mortgage Equity Withdrawal," CESifo Working Paper Series 3897, CESifo.
    2. Hajar Fanchy & Amal El Mzabi & Ahmed Hefnaoui, 2023. "Identification of fluctuations origins in the Business Cycle in Morocco: Reduced DSGE modelling," Post-Print hal-04304857, HAL.
    3. Babecký, Jan & Franta, Michal & Ryšánek, Jakub, 2018. "Fiscal policy within the DSGE-VAR framework," Economic Modelling, Elsevier, vol. 75(C), pages 23-37.
    4. Monacelli, Tommaso & Perotti, Roberto & Trigari, Antonella, 2010. "Unemployment fiscal multipliers," Journal of Monetary Economics, Elsevier, vol. 57(5), pages 531-553, July.
    5. J. Andrés & J. E. Boscá & J. Ferri, 2015. "Household Debt and Fiscal Multipliers," Economica, London School of Economics and Political Science, vol. 82, pages 1048-1081, December.
    6. Rossi, Barbara & Inoue, Atsushi & Anderson, Emily, 2013. "Heterogeneous Consumers and Fiscal Policy Shocks," CEPR Discussion Papers 9631, C.E.P.R. Discussion Papers.
    7. Alfred A.Haug & Tomasz Jędrzejowicz & Anna Sznajderska, 2013. "Combining monetary and fiscal policy in an SVAR for a small open economy," NBP Working Papers 168, Narodowy Bank Polski.
    8. Gerald Carlino & Robert P. Inman, 2014. "Fiscal Stimulus in Economic Unions: What Role for States?," NBER Chapters, in: Tax Policy and the Economy, Volume 30, pages 1-50, National Bureau of Economic Research, Inc.
    9. Alemu Lambamo Hawitibo, 2023. "Explaining macroeconomic fluctuations in Ethiopia: the role of monetary and fiscal policies," Economic Change and Restructuring, Springer, vol. 56(2), pages 1033-1061, April.
    10. Bachmann, Rüdiger & Sims, Eric R., 2012. "Confidence and the transmission of government spending shocks," Journal of Monetary Economics, Elsevier, vol. 59(3), pages 235-249.
    11. Thorsten Drautzburg, 2016. "A narrative approach to a fiscal DSGE model," Working Papers 16-11, Federal Reserve Bank of Philadelphia.
    12. Popiel Michal Ksawery, 2020. "Fiscal policy uncertainty and US output," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(2), pages 1-26, April.
    13. Gerald A. Carlino & Robert P. Inman, 2014. "Macro fiscal policy in economic unions: states as agents," Working Papers 14-20, Federal Reserve Bank of Philadelphia.
    14. U. Devrim Demirel, 2020. "Labor Market Effects of Tax Changes in Times of High and Low Unemployment: Working Paper 2020-05," Working Papers 56522, Congressional Budget Office.
    15. Ellington, Michael, 2018. "Financial market illiquidity shocks and macroeconomic dynamics: Evidence from the UK," Journal of Banking & Finance, Elsevier, vol. 89(C), pages 225-236.
    16. Miranda-Pinto, Jorge & Murphy, Daniel & Walsh, Kieran James & Young, Eric R., 2023. "Saving constraints, inequality, and the credit market response to fiscal stimulus," European Economic Review, Elsevier, vol. 151(C).
    17. Afonso, António & Gonçalves, Luis, 2020. "The policy mix in the US and EMU: Evidence from a SVAR analysis," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    18. Efrem Castelnuovo & Guay Lim, 2019. "What Do We Know About the Macroeconomic Effects of Fiscal Policy? A Brief Survey of the Literature on Fiscal Multipliers," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 52(1), pages 78-93, March.
    19. Hodula Martin & Pfeifer Lukáš, 2018. "Fiscal-Monetary-Financial Stability Interactions in a Data-Rich Environment," Review of Economic Perspectives, Sciendo, vol. 18(3), pages 195-224, September.
    20. Giovanni Angelini & Giovanni Caggiano & Efrem Castelnuovo & Luca Fanelli, 2023. "Are Fiscal Multipliers Estimated with Proxy‐SVARs Robust?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(1), pages 95-122, February.
    21. Margaux MacDonald & Michal Ksawery Popiel, 2016. "Unconventional Monetary Policy In A Small Open Economy," Working Paper 1367, Economics Department, Queen's University.
    22. Daniel P. Murphy, 2013. "How does government spending stimulate consumption?," Globalization Institute Working Papers 157, Federal Reserve Bank of Dallas.
    23. Hafedh Bouakez & Foued Chihi & Michel Normandin, 2010. "Measuring the Effects of Fiscal Policy," Cahiers de recherche 1016, CIRPEE.
    24. Dajčman Silvo, 2020. "Economic policy and confidence of economic agents – a causal relationship?," Review of Economic Perspectives, Sciendo, vol. 20(4), pages 471-484, December.
    25. Li, Rong & Zhou, Yijiang, 2021. "Estimating local fiscal multipliers using political connections," China Economic Review, Elsevier, vol. 66(C).
    26. Lorenzo Bretscher & Alex Hsu & Andrea Tamoni, 2017. "Level and Volatility Shocks to Fiscal Policy: Term Structure Implications," 2017 Meeting Papers 258, Society for Economic Dynamics.
    27. Georgios Georgiadis & Martina Jancokova, 2017. "Financial Globalisation, Monetary Policy Spillovers and Macro-modelling: Tales from 1001 Shocks," Globalization Institute Working Papers 314, Federal Reserve Bank of Dallas.
    28. Chen, Yong & Liu, Dingming, 2018. "Government spending shocks and the real exchange rate in China: Evidence from a sign-restricted VAR model," Economic Modelling, Elsevier, vol. 68(C), pages 543-554.
    29. Povilas Lastauskas & Julius Stakénas, 2019. "Does It Matter When Labor Market Reforms Are Implemented? The Role of the Monetary Policy Environment," CESifo Working Paper Series 7844, CESifo.
    30. Givens, Gregory & Tavoy, Reid, 2024. "Entry, unemployment, and the transmission of government spending shocks," MPRA Paper 121894, University Library of Munich, Germany.
    31. Dean Croushore & Simon van Norden, 2016. "Fiscal Forecasts at the FOMC: Evidence from the Greenbooks," CIRANO Working Papers 2016s-17, CIRANO.
    32. Eddie Gerba & Klemens Hauzenberger, 2013. "Estimating US Fiscal and Monetary Interactions in a Time Varying VAR," Studies in Economics 1303, School of Economics, University of Kent.
    33. Bredemeier, Christian & Juessen, Falko & Winkler, Roland, 2017. "Fiscal Policy and Occupational Employment Dynamics," IZA Discussion Papers 10466, Institute of Labor Economics (IZA).
    34. Matteo Ciccarelli & Fulvia Marotta, 2021. "Demand or Supply? An empirical exploration of the effects of climate change on the macroeconomy," Working Papers 933, Queen Mary University of London, School of Economics and Finance.
    35. Daniel Murphy, 2015. "How Can Government Spending Stimulate Consumption?," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 18(3), pages 551-574, July.
    36. 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.
    37. Rong Li, 2017. "Putting Government Spending Shocks under the Microscope: Standard Vector Autoregression versus the Narrative Approach," FinanzArchiv: Public Finance Analysis, Mohr Siebeck, Tübingen, vol. 73(3), pages 237-254, September.
    38. IWAISAKO Tokuo & NAKATA Hayato, 2016. "Impacts of Oil Shocks on Exchange Rates and Macroeconomic Variables: A multi-country analysis," Discussion papers 16039, Research Institute of Economy, Trade and Industry (RIETI).
    39. Joonyoung Hur & Jong-Suk Han, 2020. "Effect of Monetary Policy on Government Spending Multiplier," Working Papers 2004, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    40. Radeef Chundakkadan & Subash Sasidharan & Ketan Reddy, 2023. "The Role of Export Incentives and Bank Credit on the Export Survival of Firms in India During COVID-19," Working Papers DP-2023-12, Economic Research Institute for ASEAN and East Asia (ERIA).
    41. Min, Feng & Wen, Fenghua & Wang, Xiong, 2022. "Measuring the effects of monetary and fiscal policy shocks on domestic investment in China," International Review of Economics & Finance, Elsevier, vol. 77(C), pages 395-412.
    42. Jan Babecky & Michal Franta & Jakub Rysanek, 2016. "Effects of Fiscal Policy in the DSGE-VAR Framework: The Case of the Czech Republic," Working Papers 2016/09, Czech National Bank.
    43. Salvatore Perdichizzi, 2017. "Estimating Fiscal multipliers in the Eurozone. A Nonlinear Panel Data Approach," DISCE - Working Papers del Dipartimento di Economia e Finanza def058, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    44. Cardi, Olivier & Restout, Romain, 2023. "Sectoral fiscal multipliers and technology in open economy," Journal of International Economics, Elsevier, vol. 144(C).
    45. Paulo M.M. Rodrigues & Gabriel Zsurkis, 2020. "The expected time to cross a threshold and its determinants: A simple and flexible framework," Working Papers w202006, Banco de Portugal, Economics and Research Department.
    46. Chen, Peng & Miao, Xinru, 2024. "Understanding the role of China's factors in international commodity price fluctuations: A perspective of monetary-fiscal policy interaction," Economic Analysis and Policy, Elsevier, vol. 81(C), pages 1464-1483.
    47. Portier, Franck & Beaudry, Paul & Hou, Chenyu, 2020. "Monetary Policy when the Phillips Curve is Locally Quite Flat," CEPR Discussion Papers 15184, C.E.P.R. Discussion Papers.
    48. Liu, Xiaochun, 2021. "On fiscal and monetary policy-induced macroeconomic volatility dynamics," Journal of Economic Dynamics and Control, Elsevier, vol. 127(C).
    49. Gan‐Ochir Doojav & Davaasukh Damdinjav, 2023. "The macroeconomic effects of unconventional monetary policies in a commodity‐exporting economy: Evidence from Mongolia," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 4627-4654, October.
    50. Herrera, Ana María & Rangaraju, Sandeep Kumar, 2019. "The quantitative effects of tax foresight: Not all states are equal," Journal of Economic Dynamics and Control, Elsevier, vol. 107(C), pages 1-1.
    51. Kang, Jihye & Kim, Soyoung, 2022. "Government spending news and surprise shocks: It’s the timing and persistence," Journal of Macroeconomics, Elsevier, vol. 73(C).
    52. Chen, Yong & Liu, Dingming & Zhuang, Ziguan, 2023. "The spillover effects of China's monetary policy shock: Evidence from B&R countries," Emerging Markets Review, Elsevier, vol. 55(C).
    53. Assia Elgouacem & Riccardo Zago, 2020. "Share Buybacks, Monetary Policy and the Cost of Debt," Working papers 773, Banque de France.
    54. Lastauskas, Povilas & Stakėnas, Julius, 2020. "Labor market reforms and the monetary policy environment," European Economic Review, Elsevier, vol. 128(C).
    55. Ong, Kian, 2018. "Do fiscal spending news shocks generate financial spillovers?," Economics Letters, Elsevier, vol. 164(C), pages 46-49.
    56. Alfan Mansur, 2023. "Simultaneous identification of fiscal and monetary policy shocks," Empirical Economics, Springer, vol. 65(2), pages 697-728, August.
    57. Valerie A. Ramey, 2009. "Identifying Government Spending Shocks: It's All in the Timing," NBER Working Papers 15464, National Bureau of Economic Research, Inc.
    58. Andrea Boitani & Salvatore Perdichizzi, 2018. "Public Expenditure Multipliers in recessions. Evidence from the Eurozone," DISCE - Working Papers del Dipartimento di Economia e Finanza def068, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    59. Jorge Miranda-Pinto & Daniel Murphy & Eric Young & Kieran Walsh, 2018. "Debt Burdens and the Interest Rate Response to Fiscal Stimulus: Theory and Cross-Country Evidence," 2018 Meeting Papers 936, Society for Economic Dynamics.
    60. Jorge Miranda-Pinto & Daniel Murphy & Kieran James Walsh & Eric R. Young, 2019. "Saving Constraints, Debt, and the Credit Market Response to Fiscal Stimulus: Theory and Cross-Country Evidence," Discussion Papers Series 609, School of Economics, University of Queensland, Australia.
    61. Ankargren, Sebastian & Shahnazarian, Hovick, 2019. "The Interaction Between Fiscal and Monetary Policies: Evidence from Sweden," Working Paper Series 365, Sveriges Riksbank (Central Bank of Sweden), revised 01 Apr 2019.
    62. Cosmas Dery & Apostolos Serletis, 2023. "Macroeconomic Fluctuations in the United States: The Role of Monetary and Fiscal Policy Shocks," Open Economies Review, Springer, vol. 34(5), pages 961-977, November.
    63. Assia Elgouacem, 2018. "Essays on investment and saving [Essais sur l’investissement et l’épargne]," SciencePo Working papers Main tel-03419405, HAL.
    64. Assia Elgouacem & Riccardo Zago, 2023. "Share Buybacks, Monetary Policy and the Cost of Debt," International Journal of Central Banking, International Journal of Central Banking, vol. 19(2), pages 295-349, June.
    65. Haug, Alfred A. & Sznajderska, Anna, 2024. "Government spending multipliers: Is there a difference between government consumption and investment purchases?," Journal of Macroeconomics, Elsevier, vol. 79(C).
    66. Povilas Lastauskas & Julius Stak.enas, 2024. "Labor Market Policies in High- and Low-Interest Rate Environments: Evidence from the Euro Area," Papers 2410.12024, arXiv.org.
    67. Haug, Alfred A. & Jędrzejowicz, Tomasz & Sznajderska, Anna, 2019. "Monetary and fiscal policy transmission in Poland," Economic Modelling, Elsevier, vol. 79(C), pages 15-27.
    68. Christian Bredemeier & Falko Juessen & Andreas Schabert, 2017. "Fiscal Multipliers and Monetary Policy: Reconciling Theory and Evidence," Working Paper Series in Economics 95, University of Cologne, Department of Economics.
    69. 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.).
    70. NAM, Deokwoo & LI, Xiaole, 2024. "The Stimulative Effects of Anticipated Government Spending Expansions : Evidence from Survey Forecasts," Hitotsubashi Journal of Economics, Hitotsubashi University, vol. 65(1), pages 1-31, June.
    71. Rant, Vasja & Puc, Anja & Čok, Mitja & Verbič, Miroslav, 2024. "Macroeconomic impacts of monetary and fiscal policy in the euro area in times of shifting policies: A SVAR approach," Finance Research Letters, Elsevier, vol. 64(C).
    72. Jorge Miranda-Pinto & Daniel P. Murphy & Kieran Walsh & Eric Young, 2020. "Saving Constraints, Debt, and the Credit Market Response to Fiscal Stimulus," Working Papers 20-07, Federal Reserve Bank of Cleveland.
    73. Alfred A. Haug & India Power, 2022. "Government Spending Multipliers in Times of Tight and Loose Monetary Policy in New Zealand," The Economic Record, The Economic Society of Australia, vol. 98(322), pages 249-270, September.
    74. Christian Bredemeier & Babette Jansen & Roland Winkler, 2023. "Labor Market Power and the Effects of Fiscal Policy," Jena Economics Research Papers 2023-015, Friedrich-Schiller-University Jena.

  34. Barbara Rossi & Tatevik Sekhposyan, 2011. "Forecast Optimality Tests in the Presence of Instabilities," Working Papers 11-18, Duke University, Department of Economics.

    Cited by:

    1. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    2. Gloria Gonzalez-Rivera & Yingying Sun, 2016. "Density Forecast Evaluation in Unstable Environments," Working Papers 201606, University of California at Riverside, Department of Economics.
    3. Jung, Alexander & El-Shagi, Makram & Giesen, Sebastian, 2013. "Does Central Bank Staff Beat Private Forecasters?," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79925, Verein für Socialpolitik / German Economic Association.
    4. Jung, Alexander & El-Shagi, Makram & Giesen, Sebastian, 2014. "Does the federal reserve staff still beat private forecasters?," Working Paper Series 1635, European Central Bank.
    5. Barbara Rossi, 2014. "Comment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(4), pages 510-514, October.
    6. Barbara Rossi, 2011. "Comment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 25-29, August.
    7. Rossi, Barbara & Gürkaynak, Refet & Kısacıkoğlu, Burçin, 2013. "Do DSGE Models Forecast More Accurately Out-of-Sample than VAR Models?," CEPR Discussion Papers 9576, C.E.P.R. Discussion Papers.

  35. Barbara Rossi & Atsushi Inoue, 2011. "Out-of-Sample Forecast Tests Robust to Window Size Choice," Working Papers 11-04, Duke University, Department of Economics.

    Cited by:

    1. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    2. Tae-Hwy Lee & Weiping Yang, 2012. "Money–Income Granger-Causality in Quantiles," Advances in Econometrics, in: 30th Anniversary Edition, pages 385-409, Emerald Group Publishing Limited.
    3. Dai, Zhifeng & Zhang, Xiaotong & Li, Tingyu, 2023. "Forecasting stock return volatility in data-rich environment: A new powerful predictor," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    4. 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.
    5. 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.
    6. Peter Reinhard Hansen & Allan Timmermann, 2012. "Choice of Sample Split in Out-of-Sample Forecast Evaluation," CREATES Research Papers 2012-43, Department of Economics and Business Economics, Aarhus University.
    7. Caio Almeida & Kym Ardison & Daniela Kubudi & Axel Simonsen & José Vicente, 2018. "Forecasting Bond Yields with Segmented Term Structure Models," Journal of Financial Econometrics, Oxford University Press, vol. 16(1), pages 1-33.
    8. Barbara Rossi, 2012. "Comment on "Taylor Rule Exchange Rate Forecasting during the Financial Crisis"," NBER Chapters, in: NBER International Seminar on Macroeconomics 2012, pages 106-116, National Bureau of Economic Research, Inc.
    9. Yuntong Liu & Yu Wei & Yi Liu & Wenjuan Li, 2020. "Forecasting Oil Price by Hierarchical Shrinkage in Dynamic Parameter Models," Discrete Dynamics in Nature and Society, Hindawi, vol. 2020, pages 1-12, December.

  36. Rossi, Barbara & Inoue, Atsushi, 2011. "Out-of-Sample Forecast Tests Robust to the Choice of Window Size," CEPR Discussion Papers 8542, C.E.P.R. Discussion Papers.

    Cited by:

    1. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    2. Zhang, Xiaoyun & Guo, Qiang, 2024. "How useful are energy-related uncertainty for oil price volatility forecasting?," Finance Research Letters, Elsevier, vol. 60(C).
    3. Rossi, José Luiz Júnior, 2013. "Liquidity and Exchange Rates," Insper Working Papers wpe_325, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    4. Claudio, João C. & Heinisch, Katja & Holtemöller, Oliver, 2019. "Nowcasting East German GDP growth: A MIDAS approach," IWH Discussion Papers 24/2019, Halle Institute for Economic Research (IWH).
    5. Tae-Hwy Lee & Weiping Yang, 2012. "Money–Income Granger-Causality in Quantiles," Advances in Econometrics, in: 30th Anniversary Edition, pages 385-409, Emerald Group Publishing Limited.
    6. Rossi, Barbara, 2013. "Exchange Rate Predictability," CEPR Discussion Papers 9575, C.E.P.R. Discussion Papers.
    7. Barbara Rossi & Tatevik Sekhposyan, 2015. "Alternative Tests for Correct Specification of Conditional Predictive Densities," Working Papers 758, Barcelona School of Economics.
    8. Dai, Zhifeng & Zhang, Xiaotong & Li, Tingyu, 2023. "Forecasting stock return volatility in data-rich environment: A new powerful predictor," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    9. Mengxi He & Xianfeng Hao & Yaojie Zhang & Fanyi Meng, 2021. "Forecasting stock return volatility using a robust regression model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1463-1478, December.
    10. Breen, John David & Hu, Liang, 2021. "The predictive content of oil price and volatility: New evidence on exchange rate forecasting," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
    11. Nicolás Magner & Nicolás Hardy, 2022. "Cryptocurrency Forecasting: More Evidence of the Meese-Rogoff Puzzle," Mathematics, MDPI, vol. 10(13), pages 1-27, July.
    12. Chen, Shiu-Sheng & Chou, Yu-Hsi, 2023. "Liquidity yield and exchange rate predictability," Journal of International Money and Finance, Elsevier, vol. 137(C).
    13. 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.
    14. Nonejad, Nima, 2021. "Predicting equity premium using news-based economic policy uncertainty: Not all uncertainty changes are equally important," International Review of Financial Analysis, Elsevier, vol. 77(C).
    15. Avraham Turgeman & Claudiu Botoc & Marilen Pirtea & Octavian Jude, 0000. "Modelling Intraday Realized Volatility: The Role Of Vix, Oil And Gold," Proceedings of Economics and Finance Conferences 14115804, International Institute of Social and Economic Sciences.
    16. Lu Wang & Feng Ma & Guoshan Liu & Qiaoqi Lang, 2023. "Do extreme shocks help forecast oil price volatility? The augmented GARCH‐MIDAS approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(2), pages 2056-2073, April.
    17. Theologos Dergiades & Panos K. Pouliasis, 2021. "Should Stock Returns Predictability be hooked on Long Horizon Regressions?," Discussion Paper Series 2021_03, Department of Economics, University of Macedonia, revised Feb 2021.
    18. Rodrigo Sekkel, 2014. "Balance Sheets of Financial Intermediaries: Do They Forecast Economic Activity?," Staff Working Papers 14-40, Bank of Canada.
    19. 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.
    20. Li, Dongxin & Zhang, Li & Li, Lihong, 2023. "Forecasting stock volatility with economic policy uncertainty: A smooth transition GARCH-MIDAS model," International Review of Financial Analysis, Elsevier, vol. 88(C).
    21. Yi, Yongsheng & He, Mengxi & Zhang, Yaojie, 2022. "Out-of-sample prediction of Bitcoin realized volatility: Do other cryptocurrencies help?," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    22. Martin Enilov & Yuan Wang, 2022. "Tourism and economic growth: Multi-country evidence from mixed-frequency Granger causality tests," Tourism Economics, , vol. 28(5), pages 1216-1239, August.
    23. Ferraro, Domenico & Rogoff, Kenneth & Rossi, Barbara, 2015. "Can oil prices forecast exchange rates? An empirical analysis of the relationship between commodity prices and exchange rates," Journal of International Money and Finance, Elsevier, vol. 54(C), pages 116-141.
    24. 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.
    25. Alessandro Casini & Pierre Perron, 2018. "Structural Breaks in Time Series," Boston University - Department of Economics - Working Papers Series WP2019-02, Boston University - Department of Economics.
    26. Chen, Jian & Jiang, Fuwei & Liu, Yangshu & Tu, Jun, 2017. "International volatility risk and Chinese stock return predictability," Journal of International Money and Finance, Elsevier, vol. 70(C), pages 183-203.
    27. Dimitrios D. Thomakos & Fotis Papailias, 2013. "Covariance Averaging for Improved Estimation and Portfolio Allocation," Working Paper series 66_13, Rimini Centre for Economic Analysis.
    28. Barbara Rossi & Tatevik Sekhposyan, 2014. "Forecast rationality tests in the presence of instabilities, with applications to Federal Reserve and survey forecasts," Economics Working Papers 1426, Department of Economics and Business, Universitat Pompeu Fabra, revised Nov 2014.
    29. Basistha, Arabinda & Kurov, Alexander & Wolfe, Marketa Halova, 2019. "Volatility Forecasting: The Role of Internet Search Activity and Implied Volatility," MPRA Paper 111037, University Library of Munich, Germany.
    30. 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.
    31. Hoang, Khoa & Cannavan, Damien & Huang, Ronghong & Peng, Xiaowen, 2021. "Predicting stock returns with implied cost of capital: A partial least squares approach," Journal of Financial Markets, Elsevier, vol. 53(C).
    32. Domenico Ferraro & Kenneth S. Rogoff & Barbara Rossi, 2012. "Can Oil Prices Forecast Exchange Rates?," NBER Working Papers 17998, National Bureau of Economic Research, Inc.
    33. Jannik Kreye & Philipp Sibbertsen, 2024. "Testing for a Forecast Accuracy Breakdown under Long Memory," Papers 2409.07087, arXiv.org.
    34. Joseph Agyapong, 2021. "Application of Taylor Rule Fundamentals in Forecasting Exchange Rates," Economies, MDPI, vol. 9(2), pages 1-27, June.
    35. Sun, Yuying & Hong, Yongmiao & Wang, Shouyang & Zhang, Xinyu, 2023. "Penalized time-varying model averaging," Journal of Econometrics, Elsevier, vol. 235(2), pages 1355-1377.
    36. Chen, Jian & Tang, Guohao & Yao, Jiaquan & Zhou, Guofu, 2023. "Employee sentiment and stock returns," Journal of Economic Dynamics and Control, Elsevier, vol. 149(C).
    37. Peter Reinhard Hansen & Allan Timmermann, 2012. "Equivalence Between Out-of-Sample Forecast Comparisons and Wald Statistics," CREATES Research Papers 2012-45, Department of Economics and Business Economics, Aarhus University.
    38. 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.
    39. Shiu-Sheng Chen, 2016. "Commodity prices and related equity prices," Canadian Journal of Economics, Canadian Economics Association, vol. 49(3), pages 949-967, August.
    40. Xing, Li-Min & Zhang, Yue-Jun, 2022. "Forecasting crude oil prices with shrinkage methods: Can nonconvex penalty and Huber loss help?," Energy Economics, Elsevier, vol. 110(C).
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  37. Barbara Rossi & Atsushi Inoue, 2010. "Testing for Weak Identification in Possibly Nonlinear Models," Working Papers 10-92, Duke University, Department of Economics.

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    1. Khalaf, Lynda & Lin, Zhenjiang, 2021. "Projection-based inference with particle swarm optimization," Journal of Economic Dynamics and Control, Elsevier, vol. 128(C).
    2. Inoue, Atsushi & Kuo, Chun-Hung & Rossi, Barbara, 2020. "Identifying the sources of model misspecification," Journal of Monetary Economics, Elsevier, vol. 110(C), pages 1-18.
    3. Yuya Sasaki & Yulong Wang, 2020. "Testing Finite Moment Conditions for the Consistency and the Root-N Asymptotic Normality of the GMM and M Estimators," Papers 2006.02541, arXiv.org, revised Sep 2020.
    4. Dufour, Jean-Marie & Khalaf, Lynda & Kichian, Maral, 2013. "Identification-robust analysis of DSGE and structural macroeconomic models," Journal of Monetary Economics, Elsevier, vol. 60(3), pages 340-350.
    5. Jean-Jacques Forneron, 2019. "Detecting Identification Failure in Moment Condition Models," Papers 1907.13093, arXiv.org, revised Oct 2023.
    6. Zisimos Koustas & Jean-Francois Lamarche, 2009. "Instrumental variable estimation of a nonlinear Taylor rule," Working Papers 0909, Brock University, Department of Economics, revised Jul 2010.
    7. Xiaohong Chen & David Jacho-Chávez & Oliver Linton, 2012. "Averaging of moment condition estimators," CeMMAP working papers CWP26/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    8. Giovanni Angelini & Giuseppe Cavaliere & Luca Fanelli, 2022. "Bootstrap inference and diagnostics in state space models: With applications to dynamic macro models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 3-22, January.
    9. Antoine, Bertille & Renault, Eric, 2020. "Testing identification strength," Journal of Econometrics, Elsevier, vol. 218(2), pages 271-293.
    10. Dimitris Hatzinikolaou & Agathi Tsoka, 2016. "Modeling and Estimating the Effects of Institutional Variables on a Pay-as-you-go Social Security System and on Household Saving," Public Finance Review, , vol. 44(5), pages 589-609, September.
    11. Arthur Lewbel, 2018. "The Identification Zoo - Meanings of Identification in Econometrics," Boston College Working Papers in Economics 957, Boston College Department of Economics, revised 14 Dec 2019.
    12. Morris, Stephen D., 2017. "DSGE pileups," Journal of Economic Dynamics and Control, Elsevier, vol. 74(C), pages 56-86.
    13. Rachida Ouysse, 2014. "On the performance of block-bootstrap continuously updated GMM for a class of non-linear conditional moment models," Computational Statistics, Springer, vol. 29(1), pages 233-261, February.

  38. Barbara Rossi & Tatevik Sekhposyan, 2010. "Understanding Models' Forecasting Performance," Working Papers 10-56, Duke University, Department of Economics.

    Cited by:

    1. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    2. 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.
    3. Ibrahim D. Raheem & Xuan Vinh Vo, 2022. "A new approach to exchange rate forecast: The role of global financial cycle and time‐varying parameters," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 2836-2848, July.
    4. 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.
    5. Rossi, Barbara, 2013. "Exchange Rate Predictability," CEPR Discussion Papers 9575, C.E.P.R. Discussion Papers.
    6. Breen, John David & Hu, Liang, 2021. "The predictive content of oil price and volatility: New evidence on exchange rate forecasting," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
    7. 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.
    8. Demetrescu, Matei & Rodrigues, Paulo M.M. & Taylor, A.M. Robert, 2023. "Transformed regression-based long-horizon predictability tests," Journal of Econometrics, Elsevier, vol. 237(2).
    9. Karlsson, Sune & Österholm, Pär, 2018. "A Note on the Stability of the Swedish Philips Curve," Working Papers 2018:6, Örebro University, School of Business.
    10. 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.
    11. Liu, Xiaochun, 2019. "On tail fatness of macroeconomic dynamics," Journal of Macroeconomics, Elsevier, vol. 62(C).
    12. Yongmiao Hong & Tae-Hwy Lee & Yuying Sun & Shouyang Wang & Xinyu Zhang, 2017. "Time-varying Model Averaging," Working Papers 202001, University of California at Riverside, Department of Economics.
    13. Liu, Xiaochun, 2011. "Modeling the time-varying skewness via decomposition for out-of-sample forecast," MPRA Paper 41248, University Library of Munich, Germany.
    14. Byrne, Joseph P & Korobilis, Dimitris & Ribeiro, Pinho J, 2014. "On the Sources of Uncertainty in Exchange Rate Predictability," MPRA Paper 58956, University Library of Munich, Germany.
    15. Eicher, Theo S. & Rollinson, Yuan Gao, 2023. "The accuracy of IMF crises nowcasts," International Journal of Forecasting, Elsevier, vol. 39(1), pages 431-449.
    16. Rachidi Kotchoni & Maxime Leroux & Dalibor Stevanovic, 2019. "Macroeconomic Forecast Accuracy in data-rich environment," Post-Print hal-02435757, HAL.
    17. Norman R. Swanson & Weiqi Xiong & Xiye Yang, 2020. "Predicting interest rates using shrinkage methods, real‐time diffusion indexes, and model combinations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(5), pages 587-613, August.
    18. Feng, Wenjun & Zhang, Zhengjun, 2023. "Currency exchange rate predictability: The new power of Bitcoin prices," Journal of International Money and Finance, Elsevier, vol. 132(C).
    19. Chao, Shih-Wei, 2016. "Do economic variables improve bond return volatility forecasts?," International Review of Economics & Finance, Elsevier, vol. 46(C), pages 10-26.
    20. Bloem da Silveira Junior, Luiz A. & Vasconcellos, Eduardo & Vasconcellos Guedes, Liliana & Guedes, Luis Fernando A. & Costa, Renato Machado, 2018. "Technology roadmapping: A methodological proposition to refine Delphi results," Technological Forecasting and Social Change, Elsevier, vol. 126(C), pages 194-206.
    21. 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.
    22. 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.
    23. Wang, Yudong & Ma, Feng & Wei, Yu & Wu, Chongfeng, 2016. "Forecasting realized volatility in a changing world: A dynamic model averaging approach," Journal of Banking & Finance, Elsevier, vol. 64(C), pages 136-149.

  39. Yu-chin Chen & Kenneth Rogoff & Barbara Rossi, 2009. "Predicting Agri-Commodity Prices: an Asset Pricing Approach," Working Papers UWEC-2010-02, University of Washington, Department of Economics.

    Cited by:

    1. Anna Szczepańska-Przekota, 2022. "Causality in Relation to Futures and Cash Prices in the Wheat Market," Agriculture, MDPI, vol. 12(6), pages 1-10, June.
    2. Kieran Burgess & Nicholas Rohde, 2013. "Can Exchange Rates Forecast Commodity Prices? Recent Evidence using Australian Data," Economics Bulletin, AccessEcon, vol. 33(1), pages 511-518.

  40. Tatevik Sekhposyan & Barbara Rossi, 2009. "Has Economic Modelsí Forecasting Performance for US Output Growth and Inflation Changed Over Time, and When?," Working Papers 09-06, Duke University, Department of Economics.

    Cited by:

    1. Galvão, Ana Beatriz, 2013. "Changes in predictive ability with mixed frequency data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 395-410.
    2. 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.

  41. Giacomini, Raffaella & Rossi, Barbara, 2008. "Forecast Comparisons in Unstable Environments," Working Papers 08-04, Duke University, Department of Economics.

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    1. Juan Carlos Pérez-Velasco Pavón, 2009. "Determinantes de la demanda por la denominación promedio de billete: el caso de México," Monetaria, CEMLA, vol. 0(4), pages 523-548, octubre-d.
    2. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    3. Marine Carrasco & Barbara Rossi, 2016. "In-sample inference and forecasting in misspecified factor models," Economics Working Papers 1530, Department of Economics and Business, Universitat Pompeu Fabra.
    4. 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.
    5. Constantin Bürgi, 2023. "How to Deal With Missing Observations in Surveys of Professional Forecasters," CESifo Working Paper Series 10203, CESifo.
    6. 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.
    7. Galvão, Ana Beatriz, 2013. "Changes in predictive ability with mixed frequency data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 395-410.
    8. 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.
    9. Bańbura, Marta & Leiva-Leon, Danilo & Menz, Jan-Oliver, 2021. "Do inflation expectations improve model-based inflation forecasts?," Working Paper Series 2604, European Central Bank.
    10. Yuchen Zhang & Shigeyuki Hamori, 2020. "The Predictability of the Exchange Rate When Combining Machine Learning and Fundamental Models," JRFM, MDPI, vol. 13(3), pages 1-16, March.
    11. El-Shagi, Makram & Giesen, Sebastian & Jung, Alexander, 2016. "Revisiting the relative forecast performances of Fed staff and private forecasters: A dynamic approach," International Journal of Forecasting, Elsevier, vol. 32(2), pages 313-323.
    12. 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).
    13. 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.
    14. Congressional Budget Office, 2022. "A Markov-Switching Model of the Unemployment Rate: Working Paper 2022-05," Working Papers 57582, Congressional Budget Office.
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    16. Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2019. "How is Machine Learning Useful for Macroeconomic Forecasting?," CIRANO Working Papers 2019s-22, CIRANO.
    17. Matteo Bonato & Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2020. "Investor Happiness and Predictability of the Realized Volatility of Oil Price," Working Papers 202009, University of Pretoria, Department of Economics.
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    22. Jonathan Benchimol & Makram El-Shagi, 2019. "Forecast Performance in Times of Terrorism," Bank of Israel Working Papers 2019.08, Bank of Israel.
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    33. Giacomini, Raffaella, 2014. "Economic theory and forecasting: lessons from the literature," CEPR Discussion Papers 10201, C.E.P.R. Discussion Papers.
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    38. Florens Odendahl & Barbara Rossi & Tatevik Sekhposyan, 2021. "Evaluating Forecast Performance with State Dependence," Working Papers 1295, Barcelona School of Economics.
    39. Sergio Consoli & Luca Tiozzo Pezzoli & Elisa Tosetti, 2022. "Neural forecasting of the Italian sovereign bond market with economic news," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(S2), pages 197-224, December.
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    42. Emilio Colombo & Matteo Pelagatti, 2019. "Statistical Learning and Exchange Rate Forecasting," DISEIS - Quaderni del Dipartimento di Economia internazionale, delle istituzioni e dello sviluppo dis1901, Università Cattolica del Sacro Cuore, Dipartimento di Economia internazionale, delle istituzioni e dello sviluppo (DISEIS).
    43. El-Shagi, Makram, 2011. "Inflation expectations: Does the market beat econometric forecasts?," The North American Journal of Economics and Finance, Elsevier, vol. 22(3), pages 298-319.
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    46. Pawel Krolikowski & Kurt Graden Lunsford, 2020. "Advance Layoff Notices and Aggregate Job Loss," Working Papers 20-03R, Federal Reserve Bank of Cleveland, revised 02 Feb 2022.
    47. Knüppel, Malte & Krüger, Fabian & Pohle, Marc-Oliver, 2022. "Score-based calibration testing for multivariate forecast distributions," Discussion Papers 50/2022, Deutsche Bundesbank.
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    49. 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.
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    51. Ravazzolo, Francesco & Vespignani, Joaquin, 2015. "A new monthly indicator of global real economic activity," Working Papers 2015-07, University of Tasmania, Tasmanian School of Business and Economics.
    52. Ferraro, Domenico & Rogoff, Kenneth & Rossi, Barbara, 2015. "Can oil prices forecast exchange rates? An empirical analysis of the relationship between commodity prices and exchange rates," Journal of International Money and Finance, Elsevier, vol. 54(C), pages 116-141.
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    58. 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.
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    230. Barnichon, Regis & Garda, Paula, 2015. "Forecasting Unemployment across Countries: the Ins and Outs," CEPR Discussion Papers 10910, C.E.P.R. Discussion Papers.
    231. 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.
    232. Calice, Giovanni & Chen, Jing & Williams, Julian, 2013. "Liquidity spillovers in sovereign bond and CDS markets: An analysis of the Eurozone sovereign debt crisis," Journal of Economic Behavior & Organization, Elsevier, vol. 85(C), pages 122-143.
    233. Nonejad, Nima, 2020. "A comprehensive empirical analysis of the predictive impact of the price of crude oil on aggregate equity return volatility," Journal of Commodity Markets, Elsevier, vol. 20(C).
    234. Clark, Todd E. & Doh, Taeyoung, 2014. "Evaluating alternative models of trend inflation," International Journal of Forecasting, Elsevier, vol. 30(3), pages 426-448.
    235. Sebastiano Manzan & Dawit Zerom, 2015. "Asymmetric Quantile Persistence and Predictability: the Case of US Inflation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(2), pages 297-318, April.
    236. Andrea Carriero & Raffaella Giacomini, 2011. "How useful are no-arbitrage restrictions for forecasting the term structure of interest rates?," Post-Print hal-00844809, HAL.
    237. Liu, Li & Tan, Siming & Wang, Yudong, 2020. "Can commodity prices forecast exchange rates?," Energy Economics, Elsevier, vol. 87(C).
    238. 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.
    239. Ricardo Gimeno & José Manuel Marqués-Sevillano, 2009. "Incertidumbre y el precio del riesgo en un proceso de convergencia nominal," Monetaria, CEMLA, vol. 0(4), pages 451-489, octubre-d.
    240. Smith Paul, 2016. "Nowcasting UK GDP during the depression," Working Papers 1606, University of Strathclyde Business School, Department of Economics.
    241. Andrés Schneider, 2009. "Regímenes de flotación administrada: un enfoque de cartera," Monetaria, CEMLA, vol. 0(4), pages 549-584, octubre-d.
    242. Nonejad, Nima, 2022. "Understanding the conditional out-of-sample predictive impact of the price of crude oil on aggregate equity return volatility," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    243. Constantin Anghelache & Madalina-Gabriela Anghel & Alina-Georgiana Solomon, 2017. "National Accounts System: Source of Information in Macroeconomic Forecast," International Journal of Academic Research in Accounting, Finance and Management Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Accounting, Finance and Management Sciences, vol. 7(2), pages 76-82, April.
    244. Rossi, Barbara & Gürkaynak, Refet & Kısacıkoğlu, Burçin, 2013. "Do DSGE Models Forecast More Accurately Out-of-Sample than VAR Models?," CEPR Discussion Papers 9576, C.E.P.R. Discussion Papers.
    245. Martínez-Martin, Jaime & Morris, Richard & Onorante, Luca & Piersanti, Fabio M., 2019. "Merging structural and reduced-form models for forecasting: opening the DSGE-VAR box," Working Paper Series 2335, European Central Bank.
    246. Fabrizio Iacone & Luca Rossini & Andrea Viselli, 2024. "Comparing predictive ability in presence of instability over a very short time," Papers 2405.11954, arXiv.org.
    247. Jari Hännikäinen, 2015. "Zero lower bound, unconventional monetary policy and indicator properties of interest rate spreads," Review of Financial Economics, John Wiley & Sons, vol. 26(1), pages 47-54, September.
    248. Carlos Henrique Dias Cordeiro de Castro & Fernando Antonio Lucena Aiube, 2023. "Forecasting inflation time series using score‐driven dynamic models and combination methods: The case of Brazil," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 369-401, March.
    249. Vermeulen, Philip, 2014. "An evaluation of business survey indices for short-term forecasting: Balance method versus Carlson–Parkin method," International Journal of Forecasting, Elsevier, vol. 30(4), pages 882-897.
    250. 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.
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    258. Byron Botha & Tim Olds & Geordie Reid & Daan Steenkamp & Rossouw van Jaarsveld, 2021. "Nowcasting South African gross domestic product using a suite of statistical models," South African Journal of Economics, Economic Society of South Africa, vol. 89(4), pages 526-554, December.
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  42. Inoue, Atsushi & Rossi, Barbara, 2008. "Which Structural Parameters Are "Structural"? Identifying the Sources of Instabilities in Economic Models," Working Papers 08-02, Duke University, Department of Economics.

    Cited by:

    1. Samuel Hurtado, 2013. "DSGE Models and the Lucas critique," Working Papers 1310, Banco de España.
    2. Emilian DOBRESCU, 2017. "Modelling an Emergent Economy and Parameter Instability Problem," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 5-28, June.
    3. Philippe Bacchetta & Eric van Wincoop, 2009. "On the Unstable Relationship between Exchange Rates and Macroeconomic Fundamentals," Working Papers 272009, Hong Kong Institute for Monetary Research.

  43. Tatevik Sekhposyan & Barbara Rossi, 2008. "Has modelsí forecasting performance for US output growth and inflation changed over time, and when?," Working Papers 09-02, Duke University, Department of Economics.

    Cited by:

    1. Juan Carlos Pérez-Velasco Pavón, 2009. "Determinantes de la demanda por la denominación promedio de billete: el caso de México," Monetaria, CEMLA, vol. 0(4), pages 523-548, octubre-d.
    2. Barnett, William & Park, Sohee, 2021. "Forecasting Inflation and Output Growth with Credit-Card-Augmented Divisia Monetary Aggregates," MPRA Paper 110298, University Library of Munich, Germany.
    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. Granziera, Eleonora & Sekhposyan, Tatevik, 2019. "Predicting relative forecasting performance: An empirical investigation," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1636-1657.
    5. Niu, Linlin & Xu, Xiu & Chen, Ying, 2015. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," BOFIT Discussion Papers 12/2015, Bank of Finland Institute for Emerging Economies (BOFIT).
    6. Carlos Barros & Luis Gil-Alana, 2012. "Inflation forecasting in Angola: a fractional approach," CEsA Working Papers 103, CEsA - Centre for African and Development Studies.
    7. 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.
    8. Serena Ng & Jonathan H. Wright, 2013. "Facts and Challenges from the Great Recession for Forecasting and Macroeconomic Modeling," NBER Working Papers 19469, National Bureau of Economic Research, Inc.
    9. Giannone, Domenico & D’Agostino, Antonello & Gambetti, Luca, 2009. "Macroeconomic Forecasting and Structural Change," CEPR Discussion Papers 7542, C.E.P.R. Discussion Papers.
    10. Bel, K. & Paap, R., 2013. "Modeling the impact of forecast-based regime switches on macroeconomic time series," Econometric Institute Research Papers EI 2013-25, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    11. Gloria Gonzalez-Rivera & Yingying Sun, 2016. "Density Forecast Evaluation in Unstable Environments," Working Papers 201606, University of California at Riverside, Department of Economics.
    12. Barbara Rossi & Tatevik Sekhposyan, 2013. "Evaluating predictive densities of U.S. output growth and inflation in a large macroeconomic data set," Economics Working Papers 1370, Department of Economics and Business, Universitat Pompeu Fabra.
    13. Rodrigo Sekkel, 2014. "Balance Sheets of Financial Intermediaries: Do They Forecast Economic Activity?," Staff Working Papers 14-40, Bank of Canada.
    14. Anna Florio, 2016. "The central bank as shaper and observer of events: The case of the yield spread," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 49(1), pages 320-346, February.
    15. 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.
    16. Rusnák, Marek, 2016. "Nowcasting Czech GDP in real time," Economic Modelling, Elsevier, vol. 54(C), pages 26-39.
    17. 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.
    18. Koop, Gary, 2014. "Forecasting with dimension switching VARs," International Journal of Forecasting, Elsevier, vol. 30(2), pages 280-290.
    19. Plakandaras, Vasilios & Gogas, Periklis & Papadimitriou, Theophilos & Gupta, Rangan, 2019. "A re-evaluation of the term spread as a leading indicator," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 476-492.
    20. Kirdan Lees, 2009. "Overview of a recent Reserve Bank workshop: nowcasting with model combination," Reserve Bank of New Zealand Bulletin, Reserve Bank of New Zealand, vol. 72, pages 31-33, March.
    21. Vasilios Plakandaras & Periklis Gogas & Theophilos Papadimitriou & Rangan Gupta, 2017. "The Informational Content of the Term Spread in Forecasting the US Inflation Rate: A Nonlinear Approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(2), pages 109-121, March.
    22. Vasilios Plakandaras & Periklis Gogas & Theophilos Papadimitriou & Rangan Gupta, 2016. "The Term Premium as a Leading Macroeconomic Indicator," Working Papers 201613, University of Pretoria, Department of Economics.
    23. Hännikäinen, Jari, 2014. "Zero lower bound, unconventional monetary policy and indicator properties of interest rate spreads," MPRA Paper 56737, University Library of Munich, Germany.
    24. Pierre Perron & Yohei Yamamoto, 2008. "Estimating and Testing Multiple Structural Changes in Models with Endogenous Regressors," Boston University - Department of Economics - Working Papers Series wp2008-017, Boston University - Department of Economics.
    25. Pierre Perron & Yohei Yamamoto, 2015. "Using OLS to Estimate and Test for Structural Changes in Models with Endogenous Regressors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(1), pages 119-144, January.
    26. Burgess, Matthew G. & Langendorf, Ryan E. & Ippolito, Tara & Pielke, Roger Jr, 2020. "Optimistically biased economic growth forecasts and negatively skewed annual variation," SocArXiv vndqr, Center for Open Science.
    27. Juan Díaz Maureira & Gustavo Leyva Jiménez, 2009. "Proyección de la inflación chilena en tiempos difíciles," Monetaria, CEMLA, vol. 0(4), pages 491-522, octubre-d.
    28. Primiceri, Giorgio & Giannone, Domenico & Lenza, Michele, 2016. "Priors for the Long Run," CEPR Discussion Papers 11261, C.E.P.R. Discussion Papers.
    29. Faust, Jon & Wright, Jonathan H., 2013. "Forecasting Inflation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 2-56, Elsevier.
    30. Strauss, Jack, 2013. "Does housing drive state-level job growth? Building permits and consumer expectations forecast a state’s economic activity," Journal of Urban Economics, Elsevier, vol. 73(1), pages 77-93.
    31. Carstensen Kai & Wohlrabe Klaus & Ziegler Christina, 2011. "Predictive Ability of Business Cycle Indicators under Test: A Case Study for the Euro Area Industrial Production," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 82-106, February.
    32. 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).
    33. Li, You & Tay, Anthony, 2021. "The role of macroeconomic and policy uncertainty in density forecast dispersion," Journal of Macroeconomics, Elsevier, vol. 67(C).
    34. Marcus P. A. Cobb, 2020. "Aggregate density forecasting from disaggregate components using Bayesian VARs," Empirical Economics, Springer, vol. 58(1), pages 287-312, January.
    35. Barnett, Alina & Mumtaz, Haroon & Theodoridis, Konstantinos, 2014. "Forecasting UK GDP growth and inflation under structural change. A comparison of models with time-varying parameters," International Journal of Forecasting, Elsevier, vol. 30(1), pages 129-143.
    36. Rachidi Kotchoni & Maxime Leroux & Dalibor Stevanovic, 2019. "Macroeconomic Forecast Accuracy in data-rich environment," Post-Print hal-02435757, HAL.
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    38. Benjamin Beckers & Konstantin A. Kholodilin & Dirk Ulbricht, 2017. "Reading between the Lines: Using Media to Improve German Inflation Forecasts," Discussion Papers of DIW Berlin 1665, DIW Berlin, German Institute for Economic Research.
    39. Liebermann, Joelle, 2012. "Real-time forecasting in a data-rich environment," Research Technical Papers 07/RT/12, Central Bank of Ireland.
    40. 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.
    41. Yousuf, Kashif & Ng, Serena, 2021. "Boosting high dimensional predictive regressions with time varying parameters," Journal of Econometrics, Elsevier, vol. 224(1), pages 60-87.
    42. Denis Shibitov & Mariam Mamedli, 2021. "Forecasting Russian Cpi With Data Vintages And Machine Learning Techniques," Bank of Russia Working Paper Series wps70, Bank of Russia.
    43. Nonejad, Nima, 2020. "Crude oil price changes and the United Kingdom real gross domestic product growth rate: An out-of-sample investigation," The Journal of Economic Asymmetries, Elsevier, vol. 21(C).
    44. Joseph G. Haubrich, 2020. "Does the Yield Curve Predict Output?," Working Papers 20-34, Federal Reserve Bank of Cleveland.
    45. Richard Ashley & Randal J. Verbrugge, 2019. "The Intermittent Phillips Curve: Finding a Stable (But Persistence-Dependent) Phillips Curve Model Specification," Working Papers 19-09R2, Federal Reserve Bank of Cleveland, revised 14 Feb 2023.
    46. Bel, Koen & Paap, Richard, 2016. "Modeling the impact of forecast-based regime switches on US inflation," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1306-1316.
    47. Fossati, Sebastian, 2017. "Testing for State-Dependent Predictive Ability," Working Papers 2017-9, University of Alberta, Department of Economics.
    48. Stephen McKnight & Alexander Mihailov & Fabio Rumler, 2018. "NKPC-Based Inflation Forecasts with a Time-Varying Trend," Serie documentos de trabajo del Centro de Estudios Económicos 2018-05, El Colegio de México, Centro de Estudios Económicos.
    49. 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.
    50. Nonejad, Nima, 2020. "A comprehensive empirical analysis of the predictive impact of the price of crude oil on aggregate equity return volatility," Journal of Commodity Markets, Elsevier, vol. 20(C).
    51. Ricardo Gimeno & José Manuel Marqués-Sevillano, 2009. "Incertidumbre y el precio del riesgo en un proceso de convergencia nominal," Monetaria, CEMLA, vol. 0(4), pages 451-489, octubre-d.
    52. Andrés Schneider, 2009. "Regímenes de flotación administrada: un enfoque de cartera," Monetaria, CEMLA, vol. 0(4), pages 549-584, octubre-d.
    53. Martínez-Martin, Jaime & Morris, Richard & Onorante, Luca & Piersanti, Fabio M., 2019. "Merging structural and reduced-form models for forecasting: opening the DSGE-VAR box," Working Paper Series 2335, European Central Bank.
    54. Jari Hännikäinen, 2015. "Zero lower bound, unconventional monetary policy and indicator properties of interest rate spreads," Review of Financial Economics, John Wiley & Sons, vol. 26(1), pages 47-54, September.
    55. Harun Özkan & M. Yazgan, 2015. "Is forecasting inflation easier under inflation targeting?," Empirical Economics, Springer, vol. 48(2), pages 609-626, March.

  44. Chen, Yu-chin & Rogoff, Kenneth & Rossi, Barbara, 2008. "Can Exchange Rates Forecast Commodity Prices?," Working Papers 08-03, Duke University, Department of Economics.

    Cited by:

    1. Park, Sunjin, 2022. "Heterogeneous beliefs in macroeconomic growth prospects and the carry risk premium," Journal of Banking & Finance, Elsevier, vol. 136(C).
    2. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    3. Arezki, Rabah & Dumitrescu, Elena & Freytag, Andreas & Quintyn, Marc, 2014. "Commodity prices and exchange rate volatility: Lessons from South Africa's capital account liberalization," Emerging Markets Review, Elsevier, vol. 19(C), pages 96-105.
    4. Mehmet Balcilar & Rangan Gupta & Christian Pierdzioch, 2015. "On Exchange-Rate Movements and Gold-Price Fluctuations: Evidence for Gold-Producing Countries from a Nonparametric Causality-in-Quantiles Test," Working Papers 201598, University of Pretoria, Department of Economics.
    5. Virginie Coudert & Valérie Mignon, 2016. "Reassessing the empirical relationship between the oil price and the dollar," EconomiX Working Papers 2016-2, University of Paris Nanterre, EconomiX.
    6. Matteo Manera & Marcella Nicolini & Ilaria Vignati, 2012. "Returns in Commodities Futures Markets and Financial Speculation: A Multivariate GARCH Approach," Working Papers 2012.23, Fondazione Eni Enrico Mattei.
    7. Chen, Shiu-Sheng, 2013. "Forecasting Crude Oil Price Movements with Oil-Sensitive Stocks," MPRA Paper 49240, University Library of Munich, Germany.
    8. Dimitrios Bakas & Athanasios Triantafyllou, 2018. "The Impact of Uncertainty Shocks on the Volatility of Commodity Prices," NBS Discussion Papers in Economics 2018/02, Economics, Nottingham Business School, Nottingham Trent University.
    9. Rossi, José Luiz Júnior, 2013. "Liquidity and Exchange Rates," Insper Working Papers wpe_325, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    10. Bush, Georgia & López Noria, Gabriela, 2021. "Uncertainty and exchange rate volatility: Evidence from Mexico," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 704-722.
    11. Nikolay Gospodinov & Ibrahim Jamali, 2013. "Monetary policy surprises, positions of traders, and changes in commodity futures prices," FRB Atlanta Working Paper 2013-12, Federal Reserve Bank of Atlanta.
    12. Maggiori, Matteo & Lilley, Andrew & Neiman, Brent & Schreger, Jesse, 2020. "Exchange Rate Reconnect," CEPR Discussion Papers 13869, C.E.P.R. Discussion Papers.
    13. Beckmann, Joscha & Czudaj, Robert, 2013. "Oil prices and effective dollar exchange rates," International Review of Economics & Finance, Elsevier, vol. 27(C), pages 621-636.
    14. Timo Korkeamaki & Danielle Xu, 2015. "Institutional Investors and Foreign Exchange Risk," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 5(03), pages 1-33, September.
    15. Degiannakis, Stavros & Filis, George, 2017. "Forecasting oil price realized volatility using information channels from other asset classes," MPRA Paper 96276, University Library of Munich, Germany.
    16. Haoyuan Ding & Yuying Jin & Cong Qin & Jiezhou Ying, 2020. "Tail Causality between Crude Oil Price and RMB Exchange Rate," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 28(3), pages 116-134, May.
    17. Hedi Ben Haddad & Imed Mezghani & Abdessalem Gouider, 2021. "The Dynamic Spillover Effects of Macroeconomic and Financial Uncertainty on Commodity Markets Uncertainties," Economies, MDPI, vol. 9(2), pages 1-22, June.
    18. Stijn Claessens & M Ayhan Kose, 2018. "Frontiers of macrofinancial linkages," BIS Papers, Bank for International Settlements, number 95.
    19. 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.
    20. Wang, Yudong & Liu, Li & Wu, Chongfeng, 2020. "Forecasting commodity prices out-of-sample: Can technical indicators help?," International Journal of Forecasting, Elsevier, vol. 36(2), pages 666-683.
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    5. Giovanni Pellegrino & Efrem Castelnuovo & Giovanni Caggiano, 2021. "Uncertainty and Monetary Policy during the Great Recession," Economics Working Papers 2021-05, Department of Economics and Business Economics, Aarhus University.
    6. Ruge-Murcia, Francisco, 2020. "Estimating nonlinear dynamic equilibrium models by matching impulse responses," Economics Letters, Elsevier, vol. 197(C).
    7. Pablo Guerron-quintana & Atsushi Inoue & Lutz Kilian, 2014. "Impulse response matching estimators for DSGE models," Vanderbilt University Department of Economics Working Papers 14-00014, Vanderbilt University Department of Economics.
    8. Meenagh, David & Minford, Patrick & Wickens, Michael & Xu, Yongdeng, 2018. "Testing DSGE Models by indirect inference: a survey of recent findings," Cardiff Economics Working Papers E2018/14, Cardiff University, Cardiff Business School, Economics Section.
    9. Luca Brugnolini, 2018. "About Local Projection Impulse Response Function Reliability," CEIS Research Paper 440, Tor Vergata University, CEIS, revised 09 Jun 2018.
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    15. Giovanni Pellegrino & Efrem Castelnuovo & Giovanni Caggiano, 2020. "Uncertainty and Monetary Policy during Extreme Events," Economics Working Papers 2020-11, Department of Economics and Business Economics, Aarhus University.
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    20. Theodoridis, Konstantinos, 2011. "An efficient minimum distance estimator for DSGE models," Bank of England working papers 439, Bank of England.
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    22. Poghosyan, Karen & Boldea, Otilia, 2013. "Structural versus matching estimation: Transmission mechanisms in Armenia," Economic Modelling, Elsevier, vol. 30(C), pages 136-148.
    23. Lucy Minford & David Meenagh, 2020. "Supply-Side Policy and Economic Growth: A Case Study of the UK," Open Economies Review, Springer, vol. 31(1), pages 159-193, February.
    24. Anna Kormilitsina, 2009. "Oil Price Shocks and the Optimality of Monetary Policy," Departmental Working Papers 0901, Southern Methodist University, Department of Economics.
    25. Jacob, Punnoose & Uusküla, Lenno, 2019. "Deep habits and exchange rate pass-through," Journal of Economic Dynamics and Control, Elsevier, vol. 105(C), pages 67-89.
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    27. Özer Karagedikli & Troy Matheson & Christie Smith & Shaun Vahey, 2008. "RBCs and DSGEs: The Computational Approach to Business Cycle Theory and Evidence," Working Paper 2008/17, Norges Bank.
    28. Fève, Patrick & Matheron, Julien & Sahuc, Jean-Guillaume, 2007. "Optimal Monetary Policy and Technological Shocks in the Post-War US Business Cycle," IDEI Working Papers 484, Institut d'Économie Industrielle (IDEI), Toulouse.
    29. Rui Faustino, 2019. "Endogenous Quality and Firm Entry," Working Papers REM 2019/0107, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
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    32. Tayebeh Sadat Tabatabaei & Pedram Asef, 2021. "Evaluation of Energy Price Liberalization in Electricity Industry: A Data-Driven Study on Energy Economics," Energies, MDPI, vol. 14(22), pages 1-19, November.
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    34. Kilian, Lutz & Kim, Yun Jung, 2009. "Do Local Projections Solve the Bias Problem in Impulse Response Inference?," CEPR Discussion Papers 7266, C.E.P.R. Discussion Papers.
    35. Castelnuovo, Efrem & Pellegrino, Giovanni, 2018. "Uncertainty-dependent effects of monetary policy shocks: A new-Keynesian interpretation," Journal of Economic Dynamics and Control, Elsevier, vol. 93(C), pages 277-296.
    36. Guay, Alain & Pelgrin, Florian, 2023. "Structural VAR models in the Frequency Domain," Journal of Econometrics, Elsevier, vol. 236(1).
    37. Poghosyan, K., 2012. "Structural and reduced-form modeling and forecasting with application to Armenia," Other publications TiSEM ad1a24c3-15e6-4f04-b338-3, Tilburg University, School of Economics and Management.
    38. Prosper Donovon & Alastair R. Hall, 2015. "GMM and Indirect Inference: An appraisal of their connections and new results on their properties under second order identification," Economics Discussion Paper Series 1505, Economics, The University of Manchester.
    39. Matteo Barigozzi & Roxana Halbleib & David Veredas, 2012. "Which model to match?," Working Papers 1229, Banco de España.
    40. Ronayne, David, 2011. "Which Impulse Response Function?," Economic Research Papers 270753, University of Warwick - Department of Economics.
    41. Minford, Patrick & Wickens, Michael R. & Davidson, James & Meenagh, David, 2010. "Why crises happen - nonstationary macroeconomics," CEPR Discussion Papers 8157, C.E.P.R. Discussion Papers.
    42. Riccardo DiCecio & Edward Nelson, 2007. "An estimated DSGE model for the United Kingdom," Review, Federal Reserve Bank of St. Louis, vol. 89(Jul), pages 215-232.
    43. Mario Martinoli & Raffaello Seri & Fulvio Corsi, 2024. "Generalized Optimization Algorithms for Complex Models," LEM Papers Series 2024/18, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    44. Anna Mikusheva, 2014. "Estimation of dynamic stochastic general equilibrium models (in Russian)," Quantile, Quantile, issue 12, pages 1-21, February.
    45. Òscar Jordà & Sharon Kozicki, 2007. "Estimation and Inference by the Method of Projection Minimum Distance," Staff Working Papers 07-56, Bank of Canada.
    46. Meenagh, David & Minford, Patrick & Wickens, Michael & Xu, Yongdeng, 2018. "The small sample properties of Indirect Inference in testing and estimating DSGE models," Cardiff Economics Working Papers E2018/7, Cardiff University, Cardiff Business School, Economics Section.
    47. Jang, Tae-Seok, 2012. "Structural estimation of the New-Keynesian Model: a formal test of backward- and forward-looking expectations," MPRA Paper 40278, University Library of Munich, Germany.
    48. 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.
    49. Michiru Sakane, 2010. "News-Driven International Business Cycles: Effects of the US News Shock on the Canadian Economy," Global COE Hi-Stat Discussion Paper Series gd09-129, Institute of Economic Research, Hitotsubashi University.
    50. Jang, Tae-Seok, 2012. "Structural estimation of the New-Keynesian model: A formal test of backward- and forward-looking behavior," Economics Working Papers 2012-07, Christian-Albrechts-University of Kiel, Department of Economics.
    51. Cengiz Tunc & Denis Pelletier, 2013. "Endogenous Life-Cycle Housing Investment and Portfolio Allocation," Working Papers 1345, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    52. Morten O. Ravn & Karel Mertens, 2009. "Understanding the Aggregate Effects of Anticipated and Unanticipated Tax Policy shocks," 2009 Meeting Papers 480, Society for Economic Dynamics.
    53. Daniil Lomonosov, 2023. "Shocks of Business Activity and Specific Shocks to Oil Market in DSGE Model of Russian Economy and Their Influence Under Different Monetary Policy Regimes," Russian Journal of Money and Finance, Bank of Russia, vol. 82(4), pages 44-79, December.
    54. Francisco RUGE-MURCIA, 2014. "Indirect Inference Estimation of Nonlinear Dynamic General Equilibrium Models : With an Application to Asset Pricing under Skewness Risk," Cahiers de recherche 15-2014, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    55. Xu Cheng & Zhipeng Liao, 2012. "Select the Valid and Relevant Moments: A One-Step Procedure for GMM with Many Moments," PIER Working Paper Archive 12-045, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    56. Jang, Tae-Seok, 2012. "Structural estimation of the New-Keynesian Model: a formal test of backward- and forward-looking expectations," MPRA Paper 39669, University Library of Munich, Germany.

  46. Jim Nason & Barbara Rossi & Atsushi Inoue & Alastair Hall, 2007. "Information Criteria for Impulse Response Function Matching Estimation," 2007 Meeting Papers 293, Society for Economic Dynamics.

    Cited by:

    1. Patrick Fève & Julien Matheron & Jean‐Guillaume Sahuc, 2009. "Minimum Distance Estimation and Testing of DSGE Models from Structural VARs," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(6), pages 883-894, December.
    2. Rochelle M. Edge & Thomas Laubach & John C. Williams, 2010. "Welfare‐maximizing monetary policy under parameter uncertainty," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 129-143, January.
    3. Danthine, Jean-Pierre & Kurmann, André, 2010. "The business cycle implications of reciprocity in labor relations," Journal of Monetary Economics, Elsevier, vol. 57(7), pages 837-850, October.
    4. Hall, Alastair R. & Inoue, Atsushi & Nason, James M. & Rossi, Barbara, 2012. "Information criteria for impulse response function matching estimation of DSGE models," Journal of Econometrics, Elsevier, vol. 170(2), pages 499-518.
    5. Morten O. Ravn & Karel Mertens, 2008. "The Aggregate Effects of Anticipated and Unanticipated U.S. Tax Policy Shocks: Theory and Empirical Evidence," 2008 Meeting Papers 575, Society for Economic Dynamics.
    6. Theodoridis, Konstantinos, 2011. "An efficient minimum distance estimator for DSGE models," Bank of England working papers 439, Bank of England.
    7. Anna Kormilitsina, 2009. "Oil Price Shocks and the Optimality of Monetary Policy," Departmental Working Papers 0901, Southern Methodist University, Department of Economics.
    8. Morten O. Ravn & Stephanie Schmitt-Grohe & Martín Uribe & Lenno Uuskula, 2008. "Deep Habits and the Dynamic Effects of Monetary Policy Shocks," Economics Working Papers ECO2008/40, European University Institute.
    9. Özer Karagedikli & Troy Matheson & Christie Smith & Shaun Vahey, 2008. "RBCs and DSGEs: The Computational Approach to Business Cycle Theory and Evidence," Working Paper 2008/17, Norges Bank.
    10. Fève, Patrick & Matheron, Julien & Sahuc, Jean-Guillaume, 2007. "Optimal Monetary Policy and Technological Shocks in the Post-War US Business Cycle," IDEI Working Papers 484, Institut d'Économie Industrielle (IDEI), Toulouse.
    11. Karel Mertens & Morten Overgaard Ravn, 2011. "Understanding the Aggregate Effects of Anticipated and Unanticipated Tax Policy Shocks," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 14(1), pages 27-54, January.
    12. Kilian, Lutz & Kim, Yun Jung, 2009. "Do Local Projections Solve the Bias Problem in Impulse Response Inference?," CEPR Discussion Papers 7266, C.E.P.R. Discussion Papers.
    13. Ronayne, David, 2011. "Which Impulse Response Function?," Economic Research Papers 270753, University of Warwick - Department of Economics.
    14. Riccardo DiCecio & Edward Nelson, 2007. "An estimated DSGE model for the United Kingdom," Review, Federal Reserve Bank of St. Louis, vol. 89(Jul), pages 215-232.
    15. Òscar Jordà & Sharon Kozicki, 2007. "Estimation and Inference by the Method of Projection Minimum Distance," Staff Working Papers 07-56, Bank of Canada.

  47. Pesavento, Elena & Rossi, Barbara, 2006. "Impulse Response Confidence Intervals for Persistent Data: What Have We Learned?," Working Papers 06-03, Duke University, Department of Economics.

    Cited by:

    1. Richard T. Baillie & George Kapetanios & Fotis Papailias, 2017. "Inference for impulse response coefficients from multivariate fractionally integrated processes," Econometric Reviews, Taylor & Francis Journals, vol. 36(1-3), pages 60-84, March.
    2. Neil Kellard & Denise Osborn & Jerry Coakley & Simone D. Grose & Gael M. Martin & Donald S. Poskitt, 2015. "Bias Correction of Persistence Measures in Fractionally Integrated Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(5), pages 721-740, September.
    3. Fernández-Villaverde, J. & Rubio-Ramírez, J.F. & Schorfheide, F., 2016. "Solution and Estimation Methods for DSGE Models," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 527-724, Elsevier.
    4. K. Azim Ozdemir, 2015. "Interest Rate Surprises and Transmission Mechanism in Turkey: Evidence from Impulse Response Analysis," Working Papers 1504, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    5. Òscar Jordà & Alan M. Taylor, 2024. "Local Projections," Working Paper Series 2024-24, Federal Reserve Bank of San Francisco.
    6. Atsushi Inoue & Lutz Kilian, 2019. "The uniform validity of impulse response inference in autoregressions," Vanderbilt University Department of Economics Working Papers 19-00001, Vanderbilt University Department of Economics.
    7. Kilian, Lutz & Kim, Yun Jung, 2009. "Do Local Projections Solve the Bias Problem in Impulse Response Inference?," CEPR Discussion Papers 7266, C.E.P.R. Discussion Papers.
    8. José Luis Montiel Olea & Mikkel Plagborg‐Møller, 2021. "Local Projection Inference Is Simpler and More Robust Than You Think," Econometrica, Econometric Society, vol. 89(4), pages 1789-1823, July.
    9. Andres Elberg, 2014. "Temporal Aggregation and Convergence to the Law of One Price: Evidence from Micro Data," Working Papers 53, Facultad de Economía y Empresa, Universidad Diego Portales.
    10. Lieb, Lenard & Smeekes, Stephan, 2017. "Inference for Impulse Responses under Model Uncertainty," Research Memorandum 022, Maastricht University, Graduate School of Business and Economics (GSBE).

  48. Rossi, Barbara, 2005. "Expectations Hypotheses Tests and Predictive Regressions at Long Horizons," Working Papers 05-03, Duke University, Department of Economics.

    Cited by:

    1. Alex Maynard, 2006. "The forward premium anomaly: statistical artefact or economic puzzle? New evidence from robust tests," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 39(4), pages 1244-1281, November.

  49. 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.

    Cited by:

    1. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke 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. 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. Zolotoy, Leon & Frederickson, James R. & Lyon, John D., 2017. "Aggregate earnings and stock market returns: The good, the bad, and the state-dependent," Journal of Banking & Finance, Elsevier, vol. 77(C), pages 157-175.
    5. Kajal Lahiri & Cheng Yang, 2022. "ROC approach to forecasting recessions using daily yield spreads," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 57(4), pages 191-203, October.
    6. Argyropoulos Efthymios & Tzavalis Elias, 2015. "Term spread regressions of the rational expectations hypothesis of the term structure allowing for risk premium effects," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(1), pages 49-70, February.
    7. Zagaglia, Paolo, 2006. "Does the Yield Spread Predict the Output Gap in the U.S.?," Research Papers in Economics 2006:5, Stockholm University, Department of Economics.
    8. Lorenzo Boldrini & Eric Hillebrand, 2015. "The Forecasting Power of the Yield Curve, a Supervised Factor Model Approach," CREATES Research Papers 2015-39, Department of Economics and Business Economics, Aarhus University.
    9. Aguiar-Conraria, Luís & Martins, Manuel M.F. & Soares, Maria Joana, 2012. "The yield curve and the macro-economy across time and frequencies," Journal of Economic Dynamics and Control, Elsevier, vol. 36(12), pages 1950-1970.
    10. Yasmeen Idilbi-Bayaa & Mahmoud Qadan, 2021. "Forecasting Commodity Prices Using the Term Structure," JRFM, MDPI, vol. 14(12), pages 1-39, December.
    11. Barbara Rossi, 2019. "Forecasting in the presence of instabilities: How do we know whether models predict well and how to improve them," Economics Working Papers 1711, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2021.
    12. Roberto Santis, 2015. "Quantity theory is alive: the role of international portfolio shifts," Empirical Economics, Springer, vol. 49(4), pages 1401-1430, December.
    13. Dong Jin Lee, 2021. "Bootstrap tests for structural breaks when the regressors and the serially correlated error term are unstable," Bulletin of Economic Research, Wiley Blackwell, vol. 73(2), pages 212-229, April.
    14. Shuping Shi & Peter C. B. Phillips & Stan Hurn, 2018. "Change Detection and the Causal Impact of the Yield Curve," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 966-987, November.
    15. Cendejas Bueno, José Luis, 2023. "Recessions and flattening of the yield curve (1960–2021): A two-way road under a regime switching approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 88(C), pages 8-20.
    16. Panopoulou, Ekaterini, 2009. "Financial variables and euro area growth: A non-parametric causality analysis," Economic Modelling, Elsevier, vol. 26(6), pages 1414-1419, November.
    17. Schrimpf, Andreas & Wang, Qingwei, 2010. "A reappraisal of the leading indicator properties of the yield curve under structural instability," International Journal of Forecasting, Elsevier, vol. 26(4), pages 836-857, October.
    18. Kuosmanen, Petri & Nabulsi, Nasib & Vataja, Juuso, 2015. "Financial variables and economic activity in the Nordic countries," International Review of Economics & Finance, Elsevier, vol. 37(C), pages 368-379.
    19. Raffaella Giacomini & Barbara Rossi, 2014. "Forecasting in Nonstationary Environments: What Works and What Doesn't in Reduced-Form and Structural Models," Working Papers 819, Barcelona School of Economics.
    20. Bordo, Michael D. & Haubrich, Joseph G., 2024. "Low interest rates and the predictive content of the yield curve," The North American Journal of Economics and Finance, Elsevier, vol. 71(C).
    21. Hännikäinen, Jari, 2016. "When does the yield curve contain predictive power? Evidence from a data-rich environment," MPRA Paper 70489, University Library of Munich, Germany.
    22. Bellégo, C. & Ferrara, L., 2009. "Forecasting Euro-area recessions using time-varying binary response models for financial," Working papers 259, Banque de France.
    23. Hännikäinen, Jari, 2014. "Zero lower bound, unconventional monetary policy and indicator properties of interest rate spreads," MPRA Paper 56737, University Library of Munich, Germany.
    24. Herman O. Stekler & Tianyu Ye, 2017. "Evaluating a leading indicator: an application—the term spread," Empirical Economics, Springer, vol. 53(1), pages 183-194, August.
    25. Dovern, Jonas & Ziegler, Christina, 2008. "Predicting growth rates and recessions: assessing US leading indicators under real-time conditions," Kiel Working Papers 1397, Kiel Institute for the World Economy (IfW Kiel).
    26. Thomas B. King & Andrew T. Levin & Roberto Perli, 2007. "Financial market perceptions of recession risk," Finance and Economics Discussion Series 2007-57, Board of Governors of the Federal Reserve System (U.S.).
    27. Kajal Lahiri & Cheng Yang, 2023. "ROC and PRC Approaches to Evaluate Recession Forecasts," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 19(2), pages 119-148, September.
    28. Junttila, Juha & Vataja, Juuso, 2018. "Economic policy uncertainty effects for forecasting future real economic activity," Economic Systems, Elsevier, vol. 42(4), pages 569-583.
    29. Markku Lanne & Henri Nyberg, 2014. "Generalized Forecast Error Variance Decomposition for Linear and Nonlinear Multivariate Models," CREATES Research Papers 2014-17, Department of Economics and Business Economics, Aarhus University.
    30. Raffaella Giacomini & Barbara Rossi, 2013. "Forecasting in macroeconomics," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 17, pages 381-408, Edward Elgar Publishing.
    31. Gebka, Bartosz & Wohar, Mark E., 2018. "The predictive power of the yield spread for future economic expansions: Evidence from a new approach," Economic Modelling, Elsevier, vol. 75(C), pages 181-195.
    32. Kuosmanen, Petri & Vataja, Juuso, 2019. "Time-varying predictive content of financial variables in forecasting GDP growth in the G-7 countries," The Quarterly Review of Economics and Finance, Elsevier, vol. 71(C), pages 211-222.
    33. Chauvet, Marcelle & Senyuz, Zeynep, 2008. "A Joint Dynamic Bi-Factor Model of the Yield Curve and the Economy as a Predictor of Business Cycles," MPRA Paper 15076, University Library of Munich, Germany, revised Apr 2009.
    34. 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.
    35. Zagaglia, Paolo, 2006. "The Predictive Power of the Yield Spread under the Veil of Time," Research Papers in Economics 2006:4, Stockholm University, Department of Economics.
    36. De Santis, Roberto A., 2012. "Quantity theory is alive: the role of international portfolio shifts," Working Paper Series 1435, European Central Bank.
    37. Vasilios Plakandaras & Juncal Cunado & Rangan Gupta & Mark E. Wohar, 2016. "Do Leading Indicators Forecast U.S. Recessions? A Nonlinear Re-Evaluation Using Historical Data," Working Papers 201685, University of Pretoria, Department of Economics.
    38. He, Zhongfang, 2009. "Forecasting output growth by the yield curve: the role of structural breaks," MPRA Paper 28208, University Library of Munich, Germany.
    39. Pesaran, M. Hashem & Pick, Andreas & Pranovich, Mikhail, 2013. "Optimal forecasts in the presence of structural breaks," Journal of Econometrics, Elsevier, vol. 177(2), pages 134-152.
    40. Abdymomunov, Azamat, 2013. "Predicting output using the entire yield curve," Journal of Macroeconomics, Elsevier, vol. 37(C), pages 333-344.
    41. De Pace, Pierangelo & Weber, Kyle D., 2016. "The time-varying leading properties of the high yield spread in the United States," International Journal of Forecasting, Elsevier, vol. 32(1), pages 203-230.
    42. Jonathan H. Wright, 2006. "The yield curve and predicting recessions," Finance and Economics Discussion Series 2006-07, Board of Governors of the Federal Reserve System (U.S.).
    43. Pesaran, M.H. & Pick, A. & Pranovich, M., 2011. "Optimal Forecasts in the Presence of Structural Breaks (Updated 14 November 2011)," Cambridge Working Papers in Economics 1163, Faculty of Economics, University of Cambridge.
    44. Gross, Marco, 2011. "Corporate bond spreads and real activity in the euro area - Least Angle Regression forecasting and the probability of the recession," Working Paper Series 1286, European Central Bank.
    45. 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.
    46. Pierre Perron & Yohei Yamamoto, 2008. "On the Usefulness or Lack Thereof of Optimality Criteria for Structural Change Tests," Boston University - Department of Economics - Working Papers Series wp2008-006, Boston University - Department of Economics.
    47. 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.
    48. Knut Lehre Seip & Dan Zhang, 2021. "The Yield Curve as a Leading Indicator: Accuracy and Timing of a Parsimonious Forecasting Model," Forecasting, MDPI, vol. 3(2), pages 1-16, May.
    49. Zongwu Cai & Gunawan, 2023. "A Combination Forecast for Nonparametric Models with Structural Breaks," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202310, University of Kansas, Department of Economics, revised Sep 2023.
    50. Marcelle Chauvet & Zeynep Senyuz, 2012. "A Dynamic Factor Model of the Yield Curve as a Predictor of the Economy," Finance and Economics Discussion Series 2012-32, Board of Governors of the Federal Reserve System (U.S.).
    51. Argyropoulos, Efthymios & Tzavalis, Elias, 2015. "Real term structure forecasts of consumption growth," Journal of Empirical Finance, Elsevier, vol. 33(C), pages 208-222.
    52. Morell, Joseph, 2018. "The decline in the predictive power of the US term spread: A structural interpretation," Journal of Macroeconomics, Elsevier, vol. 55(C), pages 314-331.
    53. Boriss Siliverstovs, 2015. "Dissecting Models' Forecasting Performance," KOF Working papers 15-397, KOF Swiss Economic Institute, ETH Zurich.
    54. David Alan Peel & Pantelis Promponas, 2016. "Forecasting the nominal exchange rate movements in a changing world. The case of the U.S. and the U.K," Working Papers 144439514, Lancaster University Management School, Economics Department.
    55. Joseph G. Haubrich, 2020. "Does the Yield Curve Predict Output?," Working Papers 20-34, Federal Reserve Bank of Cleveland.
    56. 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.
    57. David C. Wheelock & Mark E. Wohar, 2009. "Can the term spread predict output growth and recessions? a survey of the literature," Review, Federal Reserve Bank of St. Louis, vol. 91(Sep), pages 419-440.
    58. Smith Aaron, 2012. "Markov Breaks in Regression Models," Journal of Time Series Econometrics, De Gruyter, vol. 4(1), pages 1-35, May.
    59. Ronald Ravinesh Kumar & Peter Josef Stauvermann & Hang Thi Thu Vu, 2021. "The Relationship between Yield Curve and Economic Activity: An Analysis of G7 Countries," JRFM, MDPI, vol. 14(2), pages 1-23, February.
    60. Dalu Zhang & Peter Moffatt, 2013. "Time series non-linearity in the real growth / recession-term spread relationship," University of East Anglia Applied and Financial Economics Working Paper Series 047, School of Economics, University of East Anglia, Norwich, UK..
    61. 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.
    62. Chauvet, Marcelle & Senyuz, Zeynep, 2016. "A dynamic factor model of the yield curve components as a predictor of the economy," International Journal of Forecasting, Elsevier, vol. 32(2), pages 324-343.
    63. Kuosmanen, Petri & Rahko, Jaana & Vataja, Juuso, 2019. "Predictive ability of financial variables in changing economic circumstances," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 37-47.
    64. Jari Hännikäinen, 2015. "Zero lower bound, unconventional monetary policy and indicator properties of interest rate spreads," Review of Financial Economics, John Wiley & Sons, vol. 26(1), pages 47-54, September.
    65. Ciner, Cetin, 2020. "Causality dynamics from equities to economic growth," Finance Research Letters, Elsevier, vol. 34(C).

  50. Barbara Rossi, 2005. "Are Exchange Rates Really Random Walks? Some Evidence Robust to Parameter Instability," Data 0503001, University Library of Munich, Germany.

    Cited by:

    1. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    2. Lucio Sarno & Giorgio Valente, 2009. "Exchange Rates and Fundamentals: Footloose or Evolving Relationship?," Journal of the European Economic Association, MIT Press, vol. 7(4), pages 786-830, June.
    3. Boldea, Otilia & Hall, Alastair R., 2013. "Estimation and inference in unstable nonlinear least squares models," Journal of Econometrics, Elsevier, vol. 172(1), pages 158-167.
    4. Rossi, José Luiz Júnior, 2013. "Liquidity and Exchange Rates," Insper Working Papers wpe_325, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    5. Ibrahim D. Raheem & Xuan Vinh Vo, 2022. "A new approach to exchange rate forecast: The role of global financial cycle and time‐varying parameters," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 2836-2848, July.
    6. Rime, Dagfinn & Sarno, Lucio & Sojli, Elvira, 2010. "Exchange rate forecasting, order flow and macroeconomic information," Journal of International Economics, Elsevier, vol. 80(1), pages 72-88, January.
    7. Rossi, Barbara, 2013. "Exchange Rate Predictability," CEPR Discussion Papers 9575, C.E.P.R. Discussion Papers.
    8. Kelly Burns, 2016. "A Reconsideration of the Meese-Rogoff Puzzle: An Alternative Approach to Model Estimation and Forecast Evaluation," Multinational Finance Journal, Multinational Finance Journal, vol. 20(1), pages 41-83, March.
    9. Rossi, Barbara & Odendahl, Florens & Sekhposyan, Tatevik, 2020. "Comparing Forecast Performance with State Dependence," CEPR Discussion Papers 15217, C.E.P.R. Discussion Papers.
    10. Fratzscher, Marcel & Rime, Dagfinn & Sarno, Lucio & Zinna, Gabriele, 2015. "The scapegoat theory of exchange rates: the first tests," Journal of Monetary Economics, Elsevier, vol. 70(C), pages 1-21.
    11. Nicolás Magner & Nicolás Hardy, 2022. "Cryptocurrency Forecasting: More Evidence of the Meese-Rogoff Puzzle," Mathematics, MDPI, vol. 10(13), pages 1-27, July.
    12. 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.
    13. Stéphane GOUTTE & Benteng Zou, 2011. "Foreign exchange rates under Markov Regime switching model," DEM Discussion Paper Series 11-16, Department of Economics at the University of Luxembourg.
    14. Wenting Liao & Jun Ma & Chengsi Zhang, 2023. "Identifying exchange rate effects and spillovers of US monetary policy shocks in the presence of time‐varying instrument relevance," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(7), pages 989-1006, November.
    15. Gloria Gonzalez-Rivera & Yingying Sun, 2016. "Density Forecast Evaluation in Unstable Environments," Working Papers 201606, University of California at Riverside, Department of Economics.
    16. Florens Odendahl & Barbara Rossi & Tatevik Sekhposyan, 2021. "Evaluating Forecast Performance with State Dependence," Working Papers 1295, Barcelona School of Economics.
    17. Emilio Colombo & Matteo Pelagatti, 2019. "Statistical Learning and Exchange Rate Forecasting," DISEIS - Quaderni del Dipartimento di Economia internazionale, delle istituzioni e dello sviluppo dis1901, Università Cattolica del Sacro Cuore, Dipartimento di Economia internazionale, delle istituzioni e dello sviluppo (DISEIS).
    18. Avouyi-Dovi, S. & Sahuc, J-G., 2009. "Comportement du banquier central en environnement incertain," Working papers 241, Banque de France.
    19. 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.
    20. Kenneth Rogoff & Barbara Rossi & Yu-chin Chen, 2008. "Can Exchange Rates Forecast Commodity Prices?," 2008 Meeting Papers 540, Society for Economic Dynamics.
    21. T. G. Saji, 2019. "Can BRICS Form a Currency Union? An Analysis under Markov Regime-Switching Framework," Global Business Review, International Management Institute, vol. 20(1), pages 151-165, February.
    22. Demetrescu, Matei & Rodrigues, Paulo M.M. & Taylor, A.M. Robert, 2023. "Transformed regression-based long-horizon predictability tests," Journal of Econometrics, Elsevier, vol. 237(2).
    23. 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.
    24. Jolanta Pasionek, 2021. "Response of the USD/MXN Exchange Rate to Macroeconomic Data," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 3), pages 914-927.
    25. Javier Gómez Biscarri & Javier Hualde, 2014. "A Residual-Based ADF Test for Stationary Cointegration in I (2) Settings," Working Papers 779, Barcelona School of Economics.
    26. Domenico Ferraro & Kenneth S. Rogoff & Barbara Rossi, 2012. "Can Oil Prices Forecast Exchange Rates?," NBER Working Papers 17998, National Bureau of Economic Research, Inc.
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    69. Kouwenberg, Roy & Markiewicz, Agnieszka & Verhoeks, Ralph & Zwinkels, Remco C. J., 2017. "Model Uncertainty and Exchange Rate Forecasting," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 52(1), pages 341-363, February.
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    74. P. Manasse & G. Moramarco & G. Trigilia, 2020. "Exchange Rates and Political Uncertainty: The Brexit Case," Working Papers wp1141, Dipartimento Scienze Economiche, Universita' di Bologna.
    75. Chuluun, Tuugi & Eun, Cheol S. & Kiliç, Rehim, 2011. "Investment intensity of currencies and the random walk hypothesis: Cross-currency evidence," Journal of Banking & Finance, Elsevier, vol. 35(2), pages 372-387, February.
    76. Pincheira-Brown, Pablo & Bentancor, Andrea & Hardy, Nicolás & Jarsun, Nabil, 2022. "Forecasting fuel prices with the Chilean exchange rate: Going beyond the commodity currency hypothesis," Energy Economics, Elsevier, vol. 106(C).
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    Cited by:

    1. Andrea Cipollini & George Kapetanios, 2005. "Forecasting Financial Crises and Contagion in Asia Using Dynamic Factor Analysis," Working Papers 538, Queen Mary University of London, School of Economics and Finance.
    2. Ryota Nakatani, 2014. "The Effects of Financial and Real Shocks, Structural Vulnerability and Monetary Policy on Exchange Rates from the Perspective of Currency Crises Models," UTokyo Price Project Working Paper Series 043, University of Tokyo, Graduate School of Economics.
    3. Boonman, Tjeerd M. & Jacobs, Jan P.A.M. & Kuper, Gerard H., 2012. "The Global Financial Crisis and currency crises in Latin America," Research Report 12005-EEF, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    4. Mirjana Jemović & Srđan Marinković, 2021. "Determinants of financial crises—An early warning system based on panel logit regression," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 103-117, January.
    5. Hyeyoen Kim, 2011. "Large Data Sets, Nonlinearity and the Speed of Adjustment to Real Exchange Rate Shocks," Post-Print hal-00665456, HAL.
    6. Teuta Ismaili Muharremi, 2015. "Currency Crisis Revisited: A Literature Review," Acta Universitatis Danubius. OEconomica, Danubius University of Galati, issue 11(6), pages 117-124, December.
    7. Yucel, Eray, 2011. "A Review and Bibliography of Early Warning Models," MPRA Paper 32893, University Library of Munich, Germany.
    8. Gatopoulos, Georgios & Loubergé, Henri, 2013. "Combined use of foreign debt and currency derivatives under the threat of currency crises: The case of Latin American firms," Journal of International Money and Finance, Elsevier, vol. 35(C), pages 54-75.

  52. Raffella Giacomini & Barbara Rossi, 2005. "Detecting and Predicting Forecast Breakdowns," UCLA Economics Working Papers 845, UCLA Department of Economics.

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    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. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    3. Yin, Anwen, 2015. "Forecasting and model averaging with structural breaks," ISU General Staff Papers 201501010800005727, Iowa State University, Department of Economics.
    4. Timmermann, Allan & Pettenuzzo, Davide, 2016. "Forecasting Macroeconomic Variables under Model Instability," CEPR Discussion Papers 11355, C.E.P.R. Discussion Papers.
    5. Pablo M. Pincheira & Carlos A. Medel, 2016. "Forecasting with a Random Walk," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 66(6), pages 539-564, December.
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    7. 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.
    8. Giacomini, Raffaella, 2014. "Economic theory and forecasting: lessons from the literature," CEPR Discussion Papers 10201, C.E.P.R. Discussion Papers.
    9. Calhoun, Gray, 2014. "Out-Of-Sample Comparisons of Overfit Models," Staff General Research Papers Archive 32462, Iowa State University, Department of Economics.
    10. 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.
    11. Casini, Alessandro, 2023. "Theory of evolutionary spectra for heteroskedasticity and autocorrelation robust inference in possibly misspecified and nonstationary models," Journal of Econometrics, Elsevier, vol. 235(2), pages 372-392.
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    13. Tom Boot & Andreas Pick, 2017. "A near optimal test for structural breaks when forecasting under square error loss," Tinbergen Institute Discussion Papers 17-039/III, Tinbergen Institute.
    14. Alessandro Casini & Pierre Perron, 2018. "Structural Breaks in Time Series," Boston University - Department of Economics - Working Papers Series WP2019-02, Boston University - Department of Economics.
    15. Salisu, Afees A. & Adekunle, Wasiu & Alimi, Wasiu A. & Emmanuel, Zachariah, 2019. "Predicting exchange rate with commodity prices: New evidence from Westerlund and Narayan (2015) estimator with structural breaks and asymmetries," Resources Policy, Elsevier, vol. 62(C), pages 33-56.
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    18. Barbara Rossi & Tatevik Sekhposyan, 2014. "Forecast rationality tests in the presence of instabilities, with applications to Federal Reserve and survey forecasts," Economics Working Papers 1426, Department of Economics and Business, Universitat Pompeu Fabra, revised Nov 2014.
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    20. Jannik Kreye & Philipp Sibbertsen, 2024. "Testing for a Forecast Accuracy Breakdown under Long Memory," Papers 2409.07087, arXiv.org.
    21. Timmermann, Allan, 2018. "Forecasting Methods in Finance," CEPR Discussion Papers 12692, C.E.P.R. Discussion Papers.
    22. Alessandro Casini, 2018. "Tests for Forecast Instability and Forecast Failure under a Continuous Record Asymptotic Framework," Papers 1803.10883, arXiv.org, revised Dec 2018.
    23. Döhrn, Roland & Schmidt, Christoph M. & Zimmermann, Tobias, 2008. "Inflation Forecasting with Inflation Sentiment Indicators," Ruhr Economic Papers 80, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    24. Raffaella Giacomini & Barbara Rossi, 2006. "How Stable is the Forecasting Performance of the Yield Curve for Output Growth?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(s1), pages 783-795, December.
    25. Lenza, Michele & Moutachaker, Inès & Paredes, Joan, 2023. "Density forecasts of inflation: a quantile regression forest approach," Working Paper Series 2830, European Central Bank.
    26. Li, Haixi & Sheng, Xuguang Simon & Yang, Jingyun, 2021. "Monitoring recessions: A Bayesian sequential quickest detection method," International Journal of Forecasting, Elsevier, vol. 37(2), pages 500-510.
    27. Raffaella Giacomini & Barbara Rossi, 2014. "Forecasting in Nonstationary Environments: What Works and What Doesn't in Reduced-Form and Structural Models," Working Papers 819, Barcelona School of Economics.
    28. John Cotter & Emmanuel Eyiah-Donkor & Valerio Potì, 2023. "Commodity futures return predictability and intertemporal asset pricing," Post-Print hal-04192933, HAL.
    29. 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.
    30. Sainan Jin & Valentina Corradi & Norman Swanson, 2015. "Robust Forecast Comparison," Departmental Working Papers 201502, Rutgers University, Department of Economics.
    31. Chiu, Ching-Wai (Jeremy) & Hayes, Simon & Kapetanios, George & Theodoridis, Konstantinos, 2019. "A new approach for detecting shifts in forecast accuracy," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1596-1612.
    32. mamatzakis, e & Christodoulakis, G, 2013. "Behavioural Asymmetries in the G7 Foreign Exchange Market," MPRA Paper 51615, University Library of Munich, Germany.
    33. Michael Dotsey & Shigeru Fujita & Tom Stark, 2011. "Do Phillips curves conditionally help to forecast inflation?," Working Papers 11-40, Federal Reserve Bank of Philadelphia.
    34. Todd E. Clark & Michael W. McCracken, 2010. "Testing for unconditional predictive ability," Working Papers 2010-031, Federal Reserve Bank of St. Louis.
    35. Alessandro Casini & Pierre Perron, 2021. "Prewhitened Long-Run Variance Estimation Robust to Nonstationarity," Papers 2103.02235, arXiv.org, revised Aug 2024.
    36. Mwasi Paza Mboya & Philipp Sibbertsen, 2023. "Optimal forecasts in the presence of discrete structural breaks under long memory," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1889-1908, November.
    37. Norman R. Swanson & Weiqi Xiong, 2018. "Big data analytics in economics: What have we learned so far, and where should we go from here?," Canadian Journal of Economics, Canadian Economics Association, vol. 51(3), pages 695-746, August.
    38. 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.
    39. Li, Jia & Patton, Andrew J., 2018. "Asymptotic inference about predictive accuracy using high frequency data," Journal of Econometrics, Elsevier, vol. 203(2), pages 223-240.
    40. Mamatzakis, Emmanuel & Tsionas, Mike G., 2015. "How are market preferences shaped? The case of sovereign debt of stressed euro-area countries," Journal of Banking & Finance, Elsevier, vol. 61(C), pages 106-116.
    41. E. Mamatzakis, 2014. "Revealing asymmetries in the loss function of WTI oil futures market," Empirical Economics, Springer, vol. 47(2), pages 411-426, September.
    42. Gibbs, Christopher G. & Vasnev, Andrey L., 2024. "Conditionally optimal weights and forward-looking approaches to combining forecasts," International Journal of Forecasting, Elsevier, vol. 40(4), pages 1734-1751.
    43. Michael P. Clements, 2020. "Do Survey Joiners and Leavers Differ from Regular Participants? The US SPF GDP Growth and Inflation Forecasts," ICMA Centre Discussion Papers in Finance icma-dp2020-01, Henley Business School, University of Reading.
    44. Chevillon, Guillaume, 2016. "Multistep forecasting in the presence of location shifts," International Journal of Forecasting, Elsevier, vol. 32(1), pages 121-137.
    45. Pesaran, M. Hashem & Pick, Andreas & Pranovich, Mikhail, 2013. "Optimal forecasts in the presence of structural breaks," Journal of Econometrics, Elsevier, vol. 177(2), pages 134-152.
    46. Afees A. Salisu & Wasiu Adekunle & Zachariah Emmanuel & Wasiu A. Alimi, 2018. "Predicting exchange rate with commodity prices: The role of structural breaks and asymmetries," Working Papers 055, Centre for Econometric and Allied Research, University of Ibadan.
    47. 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.
    48. Rossi, Barbara & Inoue, Atsushi & Jin, Lu, 2014. "Window Selection for Out-of-Sample Forecasting with Time-Varying Parameters," CEPR Discussion Papers 10168, C.E.P.R. Discussion Papers.
    49. Pierre Perron & Yohei Yamamoto, 2021. "Testing for Changes in Forecasting Performance," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(1), pages 148-165, January.
    50. Federico Belotti & Alessandro Casini & Leopoldo Catania & Stefano Grassi & Pierre Perron, 2021. "Simultaneous Bandwidths Determination for DK-HAC Estimators and Long-Run Variance Estimation in Nonparametric Settings," Papers 2103.00060, arXiv.org.
    51. Mamatzakis, E. & Koutsomanoli-Filippaki, A., 2014. "Testing the rationality of DOE's energy price forecasts under asymmetric loss preferences," Energy Policy, Elsevier, vol. 68(C), pages 567-575.
    52. De Pace, Pierangelo & Weber, Kyle D., 2016. "The time-varying leading properties of the high yield spread in the United States," International Journal of Forecasting, Elsevier, vol. 32(1), pages 203-230.
    53. Todd E. Clark & Michael W. McCracken, 2008. "Tests of equal predictive ability with real-time data," Working Papers 2008-029, Federal Reserve Bank of St. Louis.
    54. Bin Jiang & George Athanasopoulos & Rob J Hyndman & Anastasios Panagiotelis & Farshid Vahid, 2017. "Macroeconomic forecasting for Australia using a large number of predictors," Monash Econometrics and Business Statistics Working Papers 2/17, Monash University, Department of Econometrics and Business Statistics.
    55. Barbara Rossi & Tatevik Sekhposyan, 2010. "Understanding Models' Forecasting Performance," Working Papers 10-56, Duke University, Department of Economics.
    56. 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.
    57. Corradi, Valentina & Swanson, Norman R., 2014. "Testing for structural stability of factor augmented forecasting models," Journal of Econometrics, Elsevier, vol. 182(1), pages 100-118.
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    59. Chad Fulton & Kirstin Hubrich, 2021. "Forecasting US Inflation in Real Time," Finance and Economics Discussion Series 2021-014, Board of Governors of the Federal Reserve System (U.S.).
    60. Pesaran, M.H. & Pick, A. & Pranovich, M., 2011. "Optimal Forecasts in the Presence of Structural Breaks (Updated 14 November 2011)," Cambridge Working Papers in Economics 1163, Faculty of Economics, University of Cambridge.
    61. 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.
    62. Inoue, Atsushi & Jin, Lu & Rossi, Barbara, 2017. "Rolling window selection for out-of-sample forecasting with time-varying parameters," Journal of Econometrics, Elsevier, vol. 196(1), pages 55-67.
    63. Wang, Yudong & Hao, Xianfeng & Wu, Chongfeng, 2021. "Forecasting stock returns: A time-dependent weighted least squares approach," Journal of Financial Markets, Elsevier, vol. 53(C).
    64. Barbara Rossi, 2014. "Comment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(4), pages 510-514, October.
    65. Rachidi Kotchoni & Maxime Leroux & Dalibor Stevanovic, 2019. "Macroeconomic Forecast Accuracy in data-rich environment," Post-Print hal-02435757, HAL.
    66. Giovanni Calice & Christos Ioannidis & Julian Williams, 2012. "Credit Derivatives and the Default Risk of Large Complex Financial Institutions," Journal of Financial Services Research, Springer;Western Finance Association, vol. 42(1), pages 85-107, October.
    67. Lyócsa, Štefan & Molnár, Peter, 2018. "Exploiting dependence: Day-ahead volatility forecasting for crude oil and natural gas exchange-traded funds," Energy, Elsevier, vol. 155(C), pages 462-473.
    68. Chollete, Loran & Schmeidler, David, 2014. "Extreme Events and the Origin of Central Bank Priors," UiS Working Papers in Economics and Finance 2014/15, University of Stavanger.
    69. Alessandro Casini, 2021. "Theory of Evolutionary Spectra for Heteroskedasticity and Autocorrelation Robust Inference in Possibly Misspecified and Nonstationary Models," Papers 2103.02981, arXiv.org, revised Aug 2024.
    70. Siddhartha S. Bora & Ani L. Katchova & Todd H. Kuethe, 2021. "The Rationality of USDA Forecasts under Multivariate Asymmetric Loss," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(3), pages 1006-1033, May.
    71. Argyropoulos, Efthymios & Tzavalis, Elias, 2015. "Real term structure forecasts of consumption growth," Journal of Empirical Finance, Elsevier, vol. 33(C), pages 208-222.
    72. Christodoulakis, George, 2020. "Estimating the term structure of commodity market preferences," European Journal of Operational Research, Elsevier, vol. 282(3), pages 1146-1163.
    73. Yu Jeffrey Hu & Jeroen Rombouts & Ines Wilms, 2023. "Fast Forecasting of Unstable Data Streams for On-Demand Service Platforms," Papers 2303.01887, arXiv.org, revised May 2024.
    74. Salisu, Afees A. & Swaray, Raymond & Oloko, Tirimisiyu F., 2019. "Improving the predictability of the oil–US stock nexus: The role of macroeconomic variables," Economic Modelling, Elsevier, vol. 76(C), pages 153-171.
    75. Jakob Krause, 2019. "A convergence-speed-dependent data quantity definition and its effect on risk estimation," Journal of Asset Management, Palgrave Macmillan, vol. 20(6), pages 469-475, October.
    76. Valentina Corradi & Sainan Jin & Norman R. Swanson, 2023. "Robust forecast superiority testing with an application to assessing pools of expert forecasters," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 596-622, June.
    77. Alessandro Casini & Taosong Deng & Pierre Perron, 2021. "Theory of Low Frequency Contamination from Nonstationarity and Misspecification: Consequences for HAR Inference," Papers 2103.01604, arXiv.org, revised Sep 2024.
    78. Michael W. McCracken, 2019. "Tests of Conditional Predictive Ability: Some Simulation Evidence," Working Papers 2019-11, Federal Reserve Bank of St. Louis.
    79. 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.
    80. Argyropoulos, Efthymios & Tzavalis, Elias, 2016. "Forecasting economic activity from yield curve factors," The North American Journal of Economics and Finance, Elsevier, vol. 36(C), pages 293-311.
    81. Pincheira-Brown, Pablo & Selaive, Jorge & Nolazco, Jose Luis, 2019. "Forecasting inflation in Latin America with core measures," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1060-1071.
    82. Byron Botha & Geordie Reid & Tim Olds & Daan Steenkamp & Rossouw van Jaarsveld, 2021. "Nowcasting South African GDP using a suite of statistical models," Working Papers 11001, South African Reserve Bank.
    83. 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.
    84. Michael W. McCracken, 2020. "Tests of Conditional Predictive Ability: Existence, Size, and Power," Working Papers 2020-050, Federal Reserve Bank of St. Louis.
    85. Christopher G. Gibbs, 2015. "Overcoming the Forecast Combination Puzzle: Lessons from the Time-Varying Effciency of Phillips Curve Forecasts of U.S. Inflation," Discussion Papers 2015-09, School of Economics, The University of New South Wales.
    86. Peter Reinhard Hansen & Allan Timmermann, 2015. "Comment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(1), pages 17-21, January.
    87. Elliott, Graham & Timmermann, Allan G, 2016. "Forecasting in Economics and Finance," University of California at San Diego, Economics Working Paper Series qt6z55v472, Department of Economics, UC San Diego.
    88. Travis J. Berge, 2011. "Forecasting disconnected exchange rates," Research Working Paper RWP 11-12, Federal Reserve Bank of Kansas City.
    89. Raffaella Giacomini, 2014. "Economic theory and forecasting: lessons from the literature," CeMMAP working papers 41/14, Institute for Fiscal Studies.
    90. Boot, Tom & Pick, Andreas, 2020. "Does modeling a structural break improve forecast accuracy?," Journal of Econometrics, Elsevier, vol. 215(1), pages 35-59.
    91. David C. Wheelock & Mark E. Wohar, 2009. "Can the term spread predict output growth and recessions? a survey of the literature," Review, Federal Reserve Bank of St. Louis, vol. 91(Sep), pages 419-440.
    92. Procasky, William J. & Yin, Anwen, 2023. "The impact of COVID-19 on the relative market efficiency and forecasting ability of credit derivative and equity markets," International Review of Financial Analysis, Elsevier, vol. 90(C).
    93. Allan Timmermann, 2018. "Forecasting Methods in Finance," Annual Review of Financial Economics, Annual Reviews, vol. 10(1), pages 449-479, November.
    94. KUROZUMI, Eiji & 黒住, 英司, 2016. "Monitoring Parameter Constancy with Endogenous Regressors," Discussion Papers 2016-01, Graduate School of Economics, Hitotsubashi University.
    95. 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.
    96. Chollete, Lor & Schmeidler, David, 2014. "Misspecification Aversion and Selection of Initial Priors," UiS Working Papers in Economics and Finance 2014/13, University of Stavanger.
    97. Alisa Yusupova & Nicos G. Pavlidis & Efthymios G. Pavlidis, 2019. "Adaptive Dynamic Model Averaging with an Application to House Price Forecasting," Papers 1912.04661, arXiv.org.
    98. Mike Buckle & Jing Chen & Julian Williams, 2014. "How Predictable Are Equity Covariance Matrices? Evidence from High‐Frequency Data for Four Markets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(7), pages 542-557, November.
    99. Salisu, Afees A. & Ndako, Umar B. & Oloko, Tirimisiyu F., 2019. "Assessing the inflation hedging of gold and palladium in OECD countries," Resources Policy, Elsevier, vol. 62(C), pages 357-377.
    100. Mariia Artemova & Francisco Blasques & Siem Jan Koopman & Zhaokun Zhang, 2021. "Forecasting in a changing world: from the great recession to the COVID-19 pandemic," Tinbergen Institute Discussion Papers 21-006/III, Tinbergen Institute.
    101. Yin, Xiao-Cui & Li, Xin & Wang, Min-Hui & Qin, Meng & Shao, Xue-Feng, 2021. "Do economic policy uncertainty and its components predict China's housing returns?," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    102. Doyle, Matthew, 2006. "Empirical Phillips Curves in OECD Countries: Has There Been A Common Breakdown?," Staff General Research Papers Archive 12684, Iowa State University, Department of Economics.
    103. Byron Botha & Tim Olds & Geordie Reid & Daan Steenkamp & Rossouw van Jaarsveld, 2021. "Nowcasting South African gross domestic product using a suite of statistical models," South African Journal of Economics, Economic Society of South Africa, vol. 89(4), pages 526-554, December.
    104. 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.

  53. Rossi, Barbara & Pesavento, Elena, 2004. "Small Sample Confidence Intervals for Multivariate Impulse Response Functions at Long Horizons," CEPR Discussion Papers 4536, C.E.P.R. Discussion Papers.

    Cited by:

    1. Yuriy Gorodnichenko & Anna Mikusheva & Serena Ng, 2011. "Estimators for Persistent and Possibly Non-Stationary Data with Classical Properties," NBER Working Papers 17424, National Bureau of Economic Research, Inc.
    2. Josep Lluís Carrion‐i‐Silvestre & María Dolores Gadea & Antonio Montañés, 2021. "Nearly Unbiased Estimation of Autoregressive Models for Bounded Near‐Integrated Stochastic Processes," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(1), pages 273-297, February.
    3. Alfred A. Haug & Christie Smith, 2007. "Local linear impulse responses for a small open economy," Working Papers 0707, University of Otago, Department of Economics, revised Apr 2007.
    4. Constantin Anghelache & Madalina-Gabriela Anghel & Stefan Virgil Iacob, 2022. "Theoretical Aspects Regarding The Models Of The Financial - Monetary Analysis," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 1, pages 52-58, February.
    5. Barbara Rossi, 2007. "Expectations hypotheses tests at Long Horizons," Econometrics Journal, Royal Economic Society, vol. 10(3), pages 554-579, November.
    6. Juan F. Rubio-Ramirez & Daniel F. Waggoner & Tao Zha, 2008. "Structural vector autoregressions: theory of identification and algorithms for inference," FRB Atlanta Working Paper 2008-18, Federal Reserve Bank of Atlanta.
    7. Barbara Rossi & Elena Pesavento, 2004. "Do Technology Shocks Drive Hours Up or Down?," Econometric Society 2004 North American Summer Meetings 96, Econometric Society.
    8. Fernández-Villaverde, J. & Rubio-Ramírez, J.F. & Schorfheide, F., 2016. "Solution and Estimation Methods for DSGE Models," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 527-724, Elsevier.
    9. Ulrich Mueller & Mark W. Watson, 2013. "Measuring Uncertainty about Long-Run Prediction," NBER Working Papers 18870, National Bureau of Economic Research, Inc.
    10. Amaze Lusompa, 2021. "Local Projections, Autocorrelation, and Efficiency," Research Working Paper RWP 21-01, Federal Reserve Bank of Kansas City.
    11. Mardi Dungey & Denise R. Osborn, 2020. "The Gains from Catch‐up for China and the USA: An Empirical Framework," The Economic Record, The Economic Society of Australia, vol. 96(314), pages 350-365, September.
    12. Dag Kolsrud, 2007. "Time-simultaneous prediction band for a time series," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(3), pages 171-188.
    13. Stefano Puddu, 2013. "Real Sector and Banking System: Real and Feedback Effects. A Non-Linear VAR Approach," IRENE Working Papers 13-01, IRENE Institute of Economic Research.
    14. Ho, Paul & Lubik, Thomas A. & Matthes, Christian, 2024. "Averaging impulse responses using prediction pools," Journal of Monetary Economics, Elsevier, vol. 146(C).
    15. Constantin ANGHELACHE & Ion PARTACHI & Madalina-Gabriela ANGHEL & Gyorgy BODO & Radu STOIAN, 2016. "General theoretical notions on univariate regression," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 64(11), pages 136-144, November.
    16. Ulrich K. Müller & Mark W. Watson, 2020. "Low-Frequency Analysis of Economic Time Series," Working Papers 2020-13, Princeton University. Economics Department..
    17. Òscar Jordà & Alan M. Taylor, 2024. "Local Projections," Working Paper Series 2024-24, Federal Reserve Bank of San Francisco.
    18. Elena Pesavento, Barbara Rossi, 2006. "Impulse Response Confidence Intervals for Persistent Data: What Have We Learned?," Economics Working Papers ECO2006/19, European University Institute.
    19. Atsushi Inoue & Lutz Kilian, 2019. "The uniform validity of impulse response inference in autoregressions," Vanderbilt University Department of Economics Working Papers 19-00001, Vanderbilt University Department of Economics.
    20. Kilian, Lutz & Kim, Yun Jung, 2009. "Do Local Projections Solve the Bias Problem in Impulse Response Inference?," CEPR Discussion Papers 7266, C.E.P.R. Discussion Papers.
    21. Demirel, Ufuk Devrim & Otterson, James, 2023. "Quantifying the uncertainty of long-term macroeconomic projections," Journal of Macroeconomics, Elsevier, vol. 75(C).
    22. Helmut Luetkepohl, 2011. "Vector Autoregressive Models," Economics Working Papers ECO2011/30, European University Institute.
    23. Christian Kascha & Karel Mertens, 2006. "Business Cycle Analysis and VARMA models," Economics Working Papers ECO2006/37, European University Institute.
    24. José Luis Montiel Olea & Mikkel Plagborg‐Møller, 2021. "Local Projection Inference Is Simpler and More Robust Than You Think," Econometrica, Econometric Society, vol. 89(4), pages 1789-1823, July.
    25. Gospodinov, Nikolay & Maynard, Alex & Pesavento, Elena, 2011. "Sensitivity of Impulse Responses to Small Low-Frequency Comovements: Reconciling the Evidence on the Effects of Technology Shocks," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(4), pages 455-467.
    26. Lieb, Lenard & Smeekes, Stephan, 2017. "Inference for Impulse Responses under Model Uncertainty," Research Memorandum 022, Maastricht University, Graduate School of Business and Economics (GSBE).
    27. Ramona-Maria DIMITROV, 2023. "Forecasts On Some Financial Indicators: A Case Study For S.C.D.A Simnic," Management and Marketing Journal, University of Craiova, Faculty of Economics and Business Administration, vol. 0(2), pages 185-211, November.

  54. Barbara Rossi & Elena Pesavento, 2004. "Do Technology Shocks Drive Hours Up or Down?," Econometric Society 2004 North American Summer Meetings 96, Econometric Society.

    Cited by:

    1. Luis Alberiko Gil-Alana & Antonio Moreno, 2006. "Technology Shocks and Hours Worked: A Fractional Integration Perspective," Faculty Working Papers 03/06, School of Economics and Business Administration, University of Navarra.
    2. Ghent, Andra, 2006. "Comparing Models of Macroeconomic Fluctuations: How Big Are the Differences?," MPRA Paper 180, University Library of Munich, Germany.
    3. Riccardo DiCecio & Neville Francis & Michael T. Owyang & Jennifer E. Roush, 2010. "A flexible finite-horizon alternative to long-run restrictions with an application to technology shock," Working Papers 2005-024, Federal Reserve Bank of St. Louis.
    4. Cristiano Cantore & Miguel León-Ledesma & Peter McAdam & Alpo Willman, 2014. "Shocking Stuff: Technology, Hours, And Factor Substitution," Journal of the European Economic Association, European Economic Association, vol. 12(1), pages 108-128, February.
    5. Neville Francis & Michael T. Owyang & Jennifer E. Roush, 2005. "A Flexible Finite-Horizon Identification of Technology Shocks," International Finance Discussion Papers 832, Board of Governors of the Federal Reserve System (U.S.).

  55. Rossi, Barbara & Pesavento, Elena, 2003. "Do Technology Shocks Drive Hours Up or Down? A Little Evidence from an Agnostic Procedure," Working Papers 03-23, Duke University, Department of Economics.

    Cited by:

    1. Patrick Fève & Alain Guay, 2010. "Identification of Technology Shocks in Structural Vars," Economic Journal, Royal Economic Society, vol. 120(549), pages 1284-1318, December.
    2. Luis Alberiko Gil-Alana & Antonio Moreno, 2006. "Technology Shocks and Hours Worked: A Fractional Integration Perspective," Faculty Working Papers 03/06, School of Economics and Business Administration, University of Navarra.
    3. Mr. Jordi Gali Garreta & Mr. Pau Rabanal, 2004. "Technology Shocks and Aggregate Fluctuations: How Well Does the RBC Model Fit Postwar U.S. Data?," IMF Working Papers 2004/234, International Monetary Fund.
    4. Guglielmo Maria Caporale & Luis A. Gil-Alana, 2012. "Persistence and Cycles in US Hours Worked," CESifo Working Paper Series 3767, CESifo.
    5. Rossi, Barbara & Pesavento, Elena, 2003. "Small Sample Confidence Intervals for Multivariate Impulse Response Functions at Long Horizons," Working Papers 03-19, Duke University, Department of Economics.
    6. Ghent, Andra, 2006. "Comparing Models of Macroeconomic Fluctuations: How Big Are the Differences?," MPRA Paper 180, University Library of Munich, Germany.
    7. Ulrich K. Müller & Mark W. Watson, 2008. "Testing Models of Low-Frequency Variability," Econometrica, Econometric Society, vol. 76(5), pages 979-1016, September.
    8. Chevillon, Guillaume & Mavroeidis, Sophocles & Zhan, Zhaoguo, 2016. "Robust inference in structural VARs with long-run restrictions," ESSEC Working Papers WP1702, ESSEC Research Center, ESSEC Business School.
    9. Ravn, Morten & Simonelli, Saverio, 2007. "Labour Market Dynamics and the Business Cycle: Structural Evidence for the United States," CEPR Discussion Papers 6409, C.E.P.R. Discussion Papers.
    10. Cristiano Cantore & Miguel León-Ledesma & Peter McAdam & Alpo Willman, 2014. "Shocking Stuff: Technology, Hours, And Factor Substitution," Journal of the European Economic Association, European Economic Association, vol. 12(1), pages 108-128, February.
    11. Christoph Gortz & Christopher Gunn & Thomas Lubik, 2022. "Split Personalities: The Changing Nature of Technology Shocks," Carleton Economic Papers 22-06, Carleton University, Department of Economics.
    12. Ghent, Andra C., 2009. "Comparing DSGE-VAR forecasting models: How big are the differences?," Journal of Economic Dynamics and Control, Elsevier, vol. 33(4), pages 864-882, April.
    13. Ali YOUSEFI & Sadegh KHALILIAN & Mohammad Hadi HAJIAN, 2010. "The Role of Water Sector in Iranian Economy: A CGE Modeling Approach," EcoMod2010 259600173, EcoMod.
    14. Beate Schirwitz, 2013. "Business Fluctuations, Job Flows and Trade Unions - Dynamics in the Economy," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 47.
    15. Lovcha, Yuliya & Pérez Laborda, Alejandro, 2016. "Frequency-Domain Estimation as an Alternative to Pre-Filtering External Cycles in Structural VAR Analysis," Working Papers 2072/290743, Universitat Rovira i Virgili, Department of Economics.
    16. Rujin, Svetlana, 2024. "Labor market institutions and technology-induced labor adjustment along the extensive and intensive margins," Journal of Macroeconomics, Elsevier, vol. 79(C).
    17. Gospodinov, Nikolay & Maynard, Alex & Pesavento, Elena, 2011. "Sensitivity of Impulse Responses to Small Low-Frequency Comovements: Reconciling the Evidence on the Effects of Technology Shocks," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(4), pages 455-467.
    18. Lovcha, Yuliya & Pérez Laborda, Àlex, 2016. "The Variance-Frequency Decomposition as an Instrument for VAR Identification: an Application to Technology Shocks," Working Papers 2072/261537, Universitat Rovira i Virgili, Department of Economics.
    19. Riccardo DiCecio & Michael T. Owyang, 2010. "Identifying technology shocks in the frequency domain," Working Papers 2010-025, Federal Reserve Bank of St. Louis.
    20. Hutter, Christian & Weber, Enzo, 2021. "Labour market miracle, productivity debacle: Measuring the effects of skill-biased and skill-neutral technical change," Economic Modelling, Elsevier, vol. 102(C).
    21. Rujin, Svetlana, 2019. "What are the effects of technology shocks on international labor markets?," Ruhr Economic Papers 806, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.

  56. Rossi, Barbara & Inoue, Atsushi, 2003. "Recursive Predictability Tests for Real-Time Data," Working Papers 03-24, Duke University, Department of Economics.

    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. Clark, Todd & McCracken, Michael, 2013. "Advances in Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1107-1201, Elsevier.
    3. Kenneth Kasa & In-Koo Cho, 2011. "Learning and Model Validation," 2011 Meeting Papers 1086, Society for Economic Dynamics.
    4. 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.
    5. 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.
    6. Paulo M.M. Rodrigues & Matei Demetrescu, 2019. "Testing for Episodic Predictability in Stock Returns," Working Papers w201906, Banco de Portugal, Economics and Research Department.
    7. Luca FANELLI & Giulio PALOMBA, 2007. "Simulation-Based Tests of Forward-Looking Models Under VAR Learning Dynamics," Working Papers 298, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    8. 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.
    9. Stanislav Anatolyev & Grigory Kosenok, 2011. "Sequential Testing with Uniformly Distributed Size," Working Papers w0123, New Economic School (NES).
    10. Dean Croushore, 2011. "Frontiers of Real-Time Data Analysis," Journal of Economic Literature, American Economic Association, vol. 49(1), pages 72-100, March.
    11. 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.
    12. Stanislav Anatolyev, 2006. "Nonparametric retrospection and monitoring of predictability of financial returns," Working Papers w0071, Center for Economic and Financial Research (CEFIR).
    13. Nicolau, Mihaela & Palomba, Giulio, 2015. "Dynamic relationships between spot and futures prices. The case of energy and gold commodities," Resources Policy, Elsevier, vol. 45(C), pages 130-143.
    14. Valentina Corradi & Norman Swanson, 2004. "Bootstrap Procedures for Recursive Estimation Schemes With Applications to Forecast Model Selection," Departmental Working Papers 200418, Rutgers University, Department of Economics.
    15. Mihaela NICOLAU & Giulio PALOMBA & Ilaria TRAINI, 2013. "Are Futures Prices Influenced by Spot;Prices or Vice-versa? An Analysis of Crude;Oil, Natural Gas and Gold Markets," Working Papers 394, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    16. 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.
    17. Fanelli, Luca, 2008. "Evaluating the New Keynesian Phillips Curve under VAR-Based Learning," Economics Discussion Papers 2008-15, Kiel Institute for the World Economy (IfW Kiel).

  57. Rossi, Barbara, 2002. "Optimal Tests for Nested Model Selection with Underlying Parameter Instability," Working Papers 02-05, Duke University, Department of Economics.

    Cited by:

    1. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    2. Yin, Anwen, 2015. "Forecasting and model averaging with structural breaks," ISU General Staff Papers 201501010800005727, Iowa State University, Department of Economics.
    3. Mehmet Balcilar & Edmond Berisha & Oguzhan Cepni & Rangan Gupta, 2019. "The Predictive Power of the Term Spread on Inequality in the United Kingdom: An Empirical Analysis," Working Papers 201981, University of Pretoria, Department of Economics.
    4. El-Shagi, Makram & Giesen, Sebastian & Jung, Alexander, 2016. "Revisiting the relative forecast performances of Fed staff and private forecasters: A dynamic approach," International Journal of Forecasting, Elsevier, vol. 32(2), pages 313-323.
    5. Goodness C. Aye & Rangan Gupta & Mampho P. Modise, 2012. "Structural Breaks and Predictive Regressions Models of South African Equity Premium," Working Papers 201209, University of Pretoria, Department of Economics.
    6. Rossi, Barbara, 2013. "Exchange Rate Predictability," CEPR Discussion Papers 9575, C.E.P.R. Discussion Papers.
    7. Aye, Goodness C. & Balcilar, Mehmet & El Montasser, Ghassen & Gupta, Rangan & Manjez, Nangamso C., 2016. "Can debt ceiling and government shutdown predict us real stock returns? A bootstrap rolling window approach. - Gli effetti sui rendimenti azionari reali negli USA del tetto del debito pubblico e del b," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, vol. 69(1), pages 11-32.
    8. Nicolás Magner & Nicolás Hardy, 2022. "Cryptocurrency Forecasting: More Evidence of the Meese-Rogoff Puzzle," Mathematics, MDPI, vol. 10(13), pages 1-27, July.
    9. Stéphane GOUTTE & Benteng Zou, 2011. "Foreign exchange rates under Markov Regime switching model," DEM Discussion Paper Series 11-16, Department of Economics at the University of Luxembourg.
    10. Rossi, Barbara & Sekhposyan, Tatevik, 2013. "Conditional predictive density evaluation in the presence of instabilities," Journal of Econometrics, Elsevier, vol. 177(2), pages 199-212.
    11. Raffella Giacomini & Barbara Rossi, 2005. "Detecting and Predicting Forecast Breakdowns," UCLA Economics Working Papers 845, UCLA Department of Economics.
    12. Bordo, Michael D. & Haubrich, Joseph G., 2022. "Some international evidence on the causal impact of the yield curve," Finance Research Letters, Elsevier, vol. 45(C).
    13. Sibande, Xolani & Demirer, Riza & Balcilar, Mehmet & Gupta, Rangan, 2023. "On the pricing effects of bitcoin mining in the fossil fuel market: The case of coal," Resources Policy, Elsevier, vol. 85(PB).
    14. Chevaughn van der Westhuizen & Renee van Eyden & Goodness C. Aye, 2022. "Is Inflation Uncertainty a Self-Fulfilling Prophecy? The Inflation-Inflation Uncertainty Nexus and Inflation Targeting in South Africa," Working Papers 202254, University of Pretoria, Department of Economics.
    15. 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.
    16. Zagaglia, Paolo, 2006. "Does the Yield Spread Predict the Output Gap in the U.S.?," Research Papers in Economics 2006:5, Stockholm University, Department of Economics.
    17. Byrne, Joseph & Cao, Shuo & Korobilis, Dimitris, 2015. "Term Structure Dynamics, Macro-Finance Factors and Model Uncertainty," MPRA Paper 63844, University Library of Munich, Germany.
    18. Carneiro, Pedro & Locatelli, Andrea & Ghebremeskel, Tewolde & Keating, Joseph, 2012. "Do Public Health Interventions Crowd Out Private Health Investments? Malaria Control Policies in Eritrea," IZA Discussion Papers 6560, Institute of Labor Economics (IZA).
    19. Desiree M. Kunene & Renee van Eyden & Petre Caraiani & Rangan Gupta, 2023. "The Predictive Impact of Climate Risk on Total Factor Productivity Growth: 1880-2020," Working Papers 202321, University of Pretoria, Department of Economics.
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    7. Lopez, Claude & Murray, Chris & Papell, David, 2009. "Median-Unbiased Estimation in DF-GLS Regressions and the PPP Puzzle," MPRA Paper 26091, University Library of Munich, Germany.
    8. Josep Lluís Carrion‐i‐Silvestre & María Dolores Gadea & Antonio Montañés, 2021. "Nearly Unbiased Estimation of Autoregressive Models for Bounded Near‐Integrated Stochastic Processes," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(1), pages 273-297, February.
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    66. Jayasuriya, Sisira & Kim, Jae H. & Kumar, Parmod, 2007. "International and Internal Market Integration in Indian agriculture: A study of the Indian Rice Market," 106th Seminar, October 25-27, 2007, Montpellier, France 7935, European Association of Agricultural Economists.
    67. Bernard Njindan Iyke, 2019. "A Test Of The Efficiency Of The Foreign Exchange Market In Indonesia," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 21(12th BMEB), pages 439-464, January.
    68. Barumshah, Ahmad Zubaidi & Chan, Tze-Haw & Fountas, Stilianos, 2004. "Re-examining Purchasing Power Parity for East-Asian Currencies: 1976-2002," MPRA Paper 2025, University Library of Munich, Germany, revised 2006.
    69. Kim, Jae H. & Ji, Philip Inyeob, 2011. "Mean-reversion in international real interest rates," Economic Modelling, Elsevier, vol. 28(4), pages 1959-1966, July.
    70. Caroline Duburcq, 2010. "The Impact of Exchange Rate Regime on Interest Rates in Latin America," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 47(135), pages 91-124.
    71. Ming-Jen Chang & Chang-Ching Lin & Shou-Yung Yin, 2013. "The Behaviour of Real Exchange Rates: The Case of Japan," Pacific Economic Review, Wiley Blackwell, vol. 18(4), pages 530-545, October.
    72. Caroline Duburcq & Eric Girardin, 2010. "Domestic and external factors in interest rate determination: the minor role of the exchange rate regime," Economics Bulletin, AccessEcon, vol. 30(1), pages 624-635.
    73. Sekioua, Sofiane H., 2008. "Real interest parity (RIP) over the 20th century: New evidence based on confidence intervals for the largest root and the half-life," Journal of International Money and Finance, Elsevier, vol. 27(1), pages 76-101, February.
    74. Sanghamitra Bandyopadhyay, 2021. "The persistence of inequality across Indian states: A time series approach," Review of Development Economics, Wiley Blackwell, vol. 25(3), pages 1150-1171, August.
    75. Jae Kim & Param Silvapulle & Rob J. Hyndman, 2006. "Half-Life Estimation based on the Bias-Corrected Bootstrap: A Highest Density Region Approach," Monash Econometrics and Business Statistics Working Papers 11/06, Monash University, Department of Econometrics and Business Statistics.
    76. Gil-Alana, Luis Alberiko & Trani, Tommaso, 2019. "An examination of trade-weighted real exchange rates based on fractional integration," International Economics, Elsevier, vol. 158(C), pages 64-76.
    77. Choi, Chi-Young & Matsubara, Kiyoshi, 2007. "Heterogeneity in the persistence of relative prices: What do the Japanese cities tell us?," Journal of the Japanese and International Economies, Elsevier, vol. 21(2), pages 260-286, June.
    78. Philip Inyeob Ji & Sangbae Kim, 2013. "Mean-reversion in closed-end fund discount: evidence from half-life," Applied Economics, Taylor & Francis Journals, vol. 45(32), pages 4503-4515, November.
    79. Chien-Chiang Lee & Mei-Se Chien, 2011. "Empirical Modelling of Regional House Prices and the Ripple Effect," Urban Studies, Urban Studies Journal Limited, vol. 48(10), pages 2029-2047, August.
    80. Atanu Ghoshray, 2013. "Dynamic Persistence of Primary Commodity Prices," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 95(1), pages 153-164.
    81. D. Ventosa-Santaul a & M. G -Zald & F. H. Wallace, 2015. "The real exchange rate, regime changes and volatility shifts," Applied Economics, Taylor & Francis Journals, vol. 47(24), pages 2445-2454, May.
    82. Baharumshah, Ahmad Zubaidi & Soon, Siew-Voon & Boršič, Darja, 2013. "Real interest parity in Central and Eastern European countries: Evidence on integration into EU and the US markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 25(C), pages 163-180.
    83. Murry, Donald & Zhu, Zhen, 2008. "Asymmetric price responses, market integration and market power: A study of the U.S. natural gas market," Energy Economics, Elsevier, vol. 30(3), pages 748-765, May.
    84. Chan, Tze-Haw, 2008. "International Parities among China and Her Major Trading Partners in Asia Pacific," MPRA Paper 15504, University Library of Munich, Germany, revised 06 Apr 2009.
    85. Charles Engel & Feng Zhu, 2019. "Exchange rate puzzles: evidence from rigidly fixed nominal exchange rate systems," BIS Working Papers 805, Bank for International Settlements.
    86. Sofiane H. Sekioua, 2004. "Real interest parity (RIP) over the 20th century: New evidence based on confidence intervals for the dominant root and half-lives of shocks," Money Macro and Finance (MMF) Research Group Conference 2004 91, Money Macro and Finance Research Group.
    87. Lo Ming Chien, 2008. "Nonlinear PPP Deviations: A Monte Carlo Investigation of Their Unconditional Half-Life," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(4), pages 1-31, December.

  59. Rossi, Barbara, 2002. "Testing Long-horizon Predictive Ability with High Persistence, and the Meese-Rogoff Puzzle," Working Papers 02-10, Duke University, Department of Economics.

    Cited by:

    1. Lucio Sarno & Giorgio Valente, 2009. "Exchange Rates and Fundamentals: Footloose or Evolving Relationship?," Journal of the European Economic Association, MIT Press, vol. 7(4), pages 786-830, June.
    2. Rossi, José Luiz Júnior, 2013. "Liquidity and Exchange Rates," Insper Working Papers wpe_325, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    3. Rime, Dagfinn & Sarno, Lucio & Sojli, Elvira, 2010. "Exchange rate forecasting, order flow and macroeconomic information," Journal of International Economics, Elsevier, vol. 80(1), pages 72-88, January.
    4. Rossi, Barbara, 2013. "Exchange Rate Predictability," CEPR Discussion Papers 9575, C.E.P.R. Discussion Papers.
    5. Fratzscher, Marcel & Rime, Dagfinn & Sarno, Lucio & Zinna, Gabriele, 2015. "The scapegoat theory of exchange rates: the first tests," Journal of Monetary Economics, Elsevier, vol. 70(C), pages 1-21.
    6. Raheem, Ibrahim, 2020. "Global financial cycles and exchange rate forecast: A factor analysis," MPRA Paper 105358, University Library of Munich, Germany.
    7. 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.
    8. Marçal, Emerson Fernandes & Zimmermann, Beatrice & de Prince, Diogo & Merlin, Giovanni, 2018. "Assessing interdependence among countries' fundamentals and its implications for exchange rate misalignment estimates: An empirical exercise based on GVAR," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 72(4), December.
    9. 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.
    10. Ferraro, Domenico & Rogoff, Kenneth & Rossi, Barbara, 2015. "Can oil prices forecast exchange rates? An empirical analysis of the relationship between commodity prices and exchange rates," Journal of International Money and Finance, Elsevier, vol. 54(C), pages 116-141.
    11. Robinson Kruse & Christian Leschinski & Michael Will, 2016. "Comparing Predictive Accuracy under Long Memory - With an Application to Volatility Forecasting," CREATES Research Papers 2016-17, Department of Economics and Business Economics, Aarhus University.
    12. Kenneth Rogoff & Barbara Rossi & Yu-chin Chen, 2008. "Can Exchange Rates Forecast Commodity Prices?," 2008 Meeting Papers 540, Society for Economic Dynamics.
    13. Cerra, Valerie & Saxena, Sweta Chaman, 2010. "The monetary model strikes back: Evidence from the world," Journal of International Economics, Elsevier, vol. 81(2), pages 184-196, July.
    14. Rossi, Barbara & Pesavento, Elena, 2003. "Small Sample Confidence Intervals for Multivariate Impulse Response Functions at Long Horizons," Working Papers 03-19, Duke University, Department of Economics.
    15. Michael Sager & Mark P. Taylor, 2008. "Commercially Available Order Flow Data and Exchange Rate Movements: "Caveat Emptor"," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(4), pages 583-625, June.
    16. Barbara Rossi, 2007. "Expectations hypotheses tests at Long Horizons," Econometrics Journal, Royal Economic Society, vol. 10(3), pages 554-579, November.
    17. Domenico Ferraro & Kenneth S. Rogoff & Barbara Rossi, 2012. "Can Oil Prices Forecast Exchange Rates?," NBER Working Papers 17998, National Bureau of Economic Research, Inc.
    18. 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.
    19. Ryan Greenaway-McGrevy & Nelson C. Mark & Donggyu Sul & Jyh-Lin Wu, 2012. "Exchange Rates as Exchange Rate Common Factors," Working Papers 212012, Hong Kong Institute for Monetary Research.
    20. Kenneth Rogoff, 2008. "Comment on "Exchange Rate Models Are Not As Bad As You Think"," NBER Chapters, in: NBER Macroeconomics Annual 2007, Volume 22, pages 443-452, National Bureau of Economic Research, Inc.
    21. Chevillon, Guillaume, 2007. "Inference in the Presence of Stochastic and Deterministic Trends," ESSEC Working Papers DR 07021, ESSEC Research Center, ESSEC Business School.
    22. Bhardwaj, Geetesh & Swanson, Norman R., 2006. "An empirical investigation of the usefulness of ARFIMA models for predicting macroeconomic and financial time series," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 539-578.
    23. 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.
    24. Todd E. Clark & Michael W. McCracken, 2010. "Testing for unconditional predictive ability," Working Papers 2010-031, Federal Reserve Bank of St. Louis.
    25. Pasquale Della Corte & Lucio Sarno & Giulia Sestieri, 2012. "The Predictive Information Content of External Imbalances for Exchange Rate Returns: How Much Is It Worth?," The Review of Economics and Statistics, MIT Press, vol. 94(1), pages 100-115, February.
    26. Erik Hjalmarsson, 2006. "Inference in Long-Horizon Regressions," International Finance Discussion Papers 853, Board of Governors of the Federal Reserve System (U.S.).
    27. 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.
    28. Primiceri, Giorgio & Giannone, Domenico & Lenza, Michele, 2016. "Priors for the Long Run," CEPR Discussion Papers 11261, C.E.P.R. Discussion Papers.
    29. Ryan Greenaway‐McGrevy & Nelson C. Mark & Donggyu Sul & Jyh‐Lin Wu, 2018. "Identifying Exchange Rate Common Factors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 59(4), pages 2193-2218, November.
    30. Takashi Matsuki & Ming-Jen Chang, 2016. "Out-of-Sample Exchange Rate Forecasting and Macroeconomic Fundamentals: The Case of Japan," Australian Economic Papers, Wiley Blackwell, vol. 55(4), pages 409-433, December.
    31. Dick, Christian D. & MacDonald, Ronald & Menkhoff, Lukas, 2014. "Exchange rate forecasts and expected fundamentals," Kiel Working Papers 1974, Kiel Institute for the World Economy (IfW Kiel).
    32. Chevillon, Guillaume, 2017. "Robustness of Multistep Forecasts and Predictive Regressions at Intermediate and Long Horizons," ESSEC Working Papers WP1710, ESSEC Research Center, ESSEC Business School.
    33. E Pavlidis & I Paya & D Peel, 2009. "Forecasting the Real Exchange Rate using a Long Span of Data. A Rematch: Linear vs Nonlinear," Working Papers 601190, Lancaster University Management School, Economics Department.
    34. Robert P. Flood & Andrew K. Rose, 2010. "Forecasting International Financial Prices with Fundamentals: How do Stocks and Exchange Rates Compare?," Chapters, in: Noel Gaston & Ahmed M. Khalid (ed.), Globalization and Economic Integration, chapter 6, Edward Elgar Publishing.
    35. 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.
    36. Felício, Wilson Rafael de Oliveira & Rossi, José Luiz Júnior, 2013. "Common factors and the exchange rate: results from the Brazilian case," Insper Working Papers wpe_318, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    37. Giacomini, Raffaella & Rossi, Barbara, 2008. "Forecast Comparisons in Unstable Environments," Working Papers 08-04, Duke University, Department of Economics.
    38. Todd E. Clark & Michael W. McCracken, 2008. "Tests of equal predictive ability with real-time data," Working Papers 2008-029, Federal Reserve Bank of St. Louis.
    39. Charles Engel & Steve Pak Yeung Wu, 2021. "Forecasting the U.S. Dollar in the 21st Century," NBER Working Papers 28447, National Bureau of Economic Research, Inc.
    40. Caraiani, Petre, 2017. "Evaluating exchange rate forecasts along time and frequency," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 60-81.
    41. Hansen, Peter Reinhard & Lunde, Asger, 2006. "Consistent ranking of volatility models," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 97-121.
    42. Baur, Dirk G. & Beckmann, Joscha & Czudaj, Robert, 2014. "Gold Price Forecasts in a Dynamic Model Averaging Framework – Have the Determinants Changed Over Time?," Ruhr Economic Papers 506, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    43. Khalaf, Lynda & Saunders, Charles J., 2017. "Monte Carlo forecast evaluation with persistent data," International Journal of Forecasting, Elsevier, vol. 33(1), pages 1-10.
    44. Takumi Ito & Motoki Masuda & Ayaka Naito & Fumiko Takeda, 2021. "Application of Google Trends‐based sentiment index in exchange rate prediction," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(7), pages 1154-1178, November.
    45. Molodtsova, Tanya & Papell, David H., 2009. "Out-of-sample exchange rate predictability with Taylor rule fundamentals," Journal of International Economics, Elsevier, vol. 77(2), pages 167-180, April.
    46. Charles Engel & Nelson C. Mark & Kenneth D. West, 2007. "Exchange Rate Models Are Not as Bad as You Think," NBER Working Papers 13318, National Bureau of Economic Research, Inc.
    47. 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.
    48. Wu, Jyh-Lin & Hu, Yu-Hau, 2009. "New evidence on nominal exchange rate predictability," Journal of International Money and Finance, Elsevier, vol. 28(6), pages 1045-1063, October.
    49. André Mollick & Tibebe Assefa, 2013. "Carry-trades on the yen and the Swiss franc: are they different?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 37(3), pages 402-423, July.
    50. Rossi, José Luiz Júnior, 2014. "The Usefulness of Financial Variables in Predicting Exchange Rate Movements," Insper Working Papers wpe_332, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    51. Travis J. Berge, 2011. "Forecasting disconnected exchange rates," Research Working Paper RWP 11-12, Federal Reserve Bank of Kansas City.
    52. Baur, Dirk G. & Beckmann, Joscha & Czudaj, Robert, 2016. "A melting pot — Gold price forecasts under model and parameter uncertainty," International Review of Financial Analysis, Elsevier, vol. 48(C), pages 282-291.
    53. Agnieszka Przybylska-Mazur, 2014. "Selected Tests Comparing the Accuracy of Inflation Rate Forecasts Constructed by Different Methods," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 15(2), pages 299-308, March.
    54. Jean-Yves Pitarakis, 2020. "A Novel Approach to Predictive Accuracy Testing in Nested Environments," Papers 2008.08387, arXiv.org, revised Oct 2023.
    55. Dick, Christian D. & MacDonald, Ronald & Menkhoff, Lukas, 2011. "Individual exchange rate forecasts and expected fundamentals," ZEW Discussion Papers 11-062, ZEW - Leibniz Centre for European Economic Research.
    56. Jin Lee, 2005. "Long horizon regressions with moderate deviations from a unit root," Economics Bulletin, AccessEcon, vol. 3(52), pages 1-11.

Articles

  1. Inoue, Atsushi & Kuo, Chun-Hung & Rossi, Barbara, 2020. "Identifying the sources of model misspecification," Journal of Monetary Economics, Elsevier, vol. 110(C), pages 1-18.
    See citations under working paper version above.
  2. Rossi, Barbara & Sekhposyan, Tatevik, 2019. "Alternative tests for correct specification of conditional predictive densities," Journal of Econometrics, Elsevier, vol. 208(2), pages 638-657.
    See citations under working paper version above.
  3. Inoue, Atsushi & Rossi, Barbara, 2019. "The effects of conventional and unconventional monetary policy on exchange rates," Journal of International Economics, Elsevier, vol. 118(C), pages 419-447.
    See citations under working paper version above.
  4. Barbara Rossi & Yiru Wang, 2019. "Vector autoregressive-based Granger causality test in the presence of instabilities," Stata Journal, StataCorp LP, vol. 19(4), pages 883-899, December.
    See citations under working paper version above.
  5. Ismailov, Adilzhan & Rossi, Barbara, 2018. "Uncertainty and deviations from uncovered interest rate parity," Journal of International Money and Finance, Elsevier, vol. 88(C), pages 242-259.

    Cited by:

    1. Ramirez-Rondan, N.R. & Terrones, Marco E., 2019. "Uncertainty and the Uncovered Interest Parity Condition: How Are They Related?," MPRA Paper 97524, University Library of Munich, Germany.
    2. Yamani, Ehab, 2019. "Diversification role of currency momentum for carry trade: Evidence from financial crises," Journal of Multinational Financial Management, Elsevier, vol. 49(C), pages 1-19.
    3. Gole, Purva & Perego, Erica & Turcu, Camelia, 2024. "UIP deviations in times of uncertainty: Not all countries behave alike," Economics Letters, Elsevier, vol. 242(C).
    4. Rossi, Barbara & Odendahl, Florens & Sekhposyan, Tatevik, 2020. "Comparing Forecast Performance with State Dependence," CEPR Discussion Papers 15217, C.E.P.R. Discussion Papers.
    5. Hambuckers, J. & Ulm, M., 2023. "On the role of interest rate differentials in the dynamic asymmetry of exchange rates," Economic Modelling, Elsevier, vol. 129(C).
    6. Muhammad Omer & Jakob de Haan & Bert Scholtens, 2019. "Does Uncovered Interest Rate Parity Hold After All?," Lahore Journal of Economics, Department of Economics, The Lahore School of Economics, vol. 24(2), pages 49-72, July-Dec.
    7. Engel, Charles & Kazakova, Ekaterina & Wang, Mengqi & Xiang, Nan, 2021. "A Reconsideration of the Failure of Uncovered Interest Parity for the U.S. Dollar," CEPR Discussion Papers 15872, C.E.P.R. Discussion Papers.
    8. Erdem, F. Pinar & Geyikci, Utku Bora, 2021. "Local, global and regional shocks indices in emerging exchange rate markets," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 98-113.
    9. Lu Yang & Lei Yang & Xue Cui, 2023. "Sovereign default network and currency risk premia," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-22, December.
    10. FATUM, Rasmus & YAMAMOTO, Yohei & CHEN, Binwei, 2023. "The Trend Effect of Foreign Exchange Intervention," Discussion paper series HIAS-E-132, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    11. Francisco Serranito & Nicolas Himounet & Julien Vauday, 2023. "Uncertainty is bad for Business. Really?," Working Papers hal-04219283, HAL.
    12. Fernanda Gonçalves & Giuliano Ferreira & Alex Ferreira & Pedro Scatimburgo, 2022. "Currency returns and systematic risk," Manchester School, University of Manchester, vol. 90(6), pages 609-647, December.
    13. Andrea Carolina Vargas-Páez & Carlos David Ardila-Dueñas, 2021. "Efecto del riesgo de tipo de cambio en la rentabilidad de los bonos soberanos en Colombia," Borradores de Economia 1165, Banco de la Republica de Colombia.
    14. 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).
    15. Nicolas Himounet, 2021. "Searching for the Nature of Uncertainty: Macroeconomic VS Financial," Working Papers 2021.05, International Network for Economic Research - INFER.
    16. Laurent Ferrara & Joseph Yapi, 2020. "Measuring exchange rate risks during periods of uncertainty," CAMA Working Papers 2020-60, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    17. Zhang, Ziyun & Chen, Su & Li, Bo, 2022. "Does previous carry trade position affect following investors' decision-making and carry returns?," International Review of Financial Analysis, Elsevier, vol. 80(C).
    18. Lucas F. Husted & John H. Rogers & Bo Sun, 2017. "Uncertainty, Curreny Exess Returns, and Risk Reversals," International Finance Discussion Papers 1196, Board of Governors of the Federal Reserve System (U.S.).
    19. Matthieu Bussiere & Menzie D. Chinn & Laurent Ferrara & Jonas Heipertz, 2018. "The New Fama Puzzle," NBER Working Papers 24342, National Bureau of Economic Research, Inc.
      • Matthieu Bussière & Menzie Chinn & Laurent Ferrara & Jonas Heipertz, 2022. "The New Fama Puzzle," Post-Print hal-04459560, HAL.
      • Matthieu Bussière & Menzie Chinn & Laurent Ferrara & Jonas Heipertz, 2022. "The New Fama Puzzle," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 70(3), pages 451-486, September.
    20. Yin-Wong Cheung & Wenhao Wang, 2020. "Uncovered Interest Rate Parity Redux: Non- Uniform Effects," GRU Working Paper Series GRU_2020_004, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
    21. P. Manasse & G. Moramarco & G. Trigilia, 2020. "Exchange Rates and Political Uncertainty: The Brexit Case," Working Papers wp1141, Dipartimento Scienze Economiche, Universita' di Bologna.
    22. Gholipour, Hassan F. & Tajaddini, Reza & Farzanegan, Mohammad Reza & Yam, Sharon, 2021. "Responses of REITs index and commercial property prices to economic uncertainties: A VAR analysis," Research in International Business and Finance, Elsevier, vol. 58(C).
    23. David Alaminos & M. Belén Salas & Manuel Á. Fernández-Gámez, 2023. "Quantum Monte Carlo simulations for estimating FOREX markets: a speculative attacks experience," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-21, December.
    24. Stylianos Asimakopoulos & Marco Lorusso & Francesco Ravazzolo, 2023. "A Bayesian DSGE Approach to Modelling Cryptocurrency," Working Papers No 09/2023, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    25. Ulm, M. & Hambuckers, J., 2022. "Do interest rate differentials drive the volatility of exchange rates? Evidence from an extended stochastic volatility model," Journal of Empirical Finance, Elsevier, vol. 65(C), pages 125-148.
    26. Marek A. Dąbrowski & Jakub Janus, 2024. "Does the Interest Parity Puzzle Hold for Central and Eastern European Economies?," Open Economies Review, Springer, vol. 35(3), pages 421-456, July.
    27. Yamani, Ehab, 2021. "Foreign exchange market efficiency and the global financial crisis: Fundamental versus technical information," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 74-89.
    28. Dąbrowski, Marek A. & Janus, Jakub, 2021. "Does the interest parity puzzle hold for Central and Eastern European economies?," MPRA Paper 107558, University Library of Munich, Germany.
    29. Beckmann, Joscha, 2021. "Measurement and effects of euro/dollar exchange rate uncertainty," Journal of Economic Behavior & Organization, Elsevier, vol. 183(C), pages 773-790.
    30. 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.
    31. Ziyun Zhang & Sen Guo, 2021. "What Factors Affect the RMB Carry Trade Return for Sustainability? An Empirical Analysis by Using an ARDL Model," Sustainability, MDPI, vol. 13(24), pages 1-19, December.
    32. Simiso MSOMI & Harold NGALAWA, 2023. "The Movement of Exchange Rate and Expected Income: Case of South Africa," Journal of Economics and Financial Analysis, Tripal Publishing House, vol. 7(2), pages 65-89.
    33. Kumar, Satish, 2019. "Does risk premium help uncover the uncovered interest parity failure?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).

  6. Barbara Rossi & Matthieu Soupre, 2017. "Implementing tests for forecast evaluation in the presence of instabilities," Stata Journal, StataCorp LP, vol. 17(4), pages 850-865, December.

    Cited by:

    1. Monique Reid & Pierre Siklos, 2023. "Rationality and biases insights from disaggregated firm level inflation expectations data," Working Papers 11050, South African Reserve Bank.
    2. Carlos Henrique Dias Cordeiro de Castro & Fernando Antonio Lucena Aiube, 2023. "Forecasting inflation time series using score‐driven dynamic models and combination methods: The case of Brazil," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 369-401, March.

  7. Inoue, Atsushi & Jin, Lu & Rossi, Barbara, 2017. "Rolling window selection for out-of-sample forecasting with time-varying parameters," Journal of Econometrics, Elsevier, vol. 196(1), pages 55-67.
    See citations under working paper version above.
  8. Barbara Rossi & Tatevik Sekhposyan, 2017. "Macroeconomic uncertainty indices for the Euro Area and its individual member countries," Empirical Economics, Springer, vol. 53(1), pages 41-62, August.

    Cited by:

    1. Richardson Kojo Edeme & Ekene ThankGod Emeka & Jonathan Emenike Ogbuabor, 2024. "Global Uncertainty, Climate Change and the Unemployment-Economic Growth Relationship in Nigeria," Journal of Development Policy and Practice, , vol. 9(2), pages 238-256, July.
    2. Michael Pfarrhofer, 2019. "Measuring international uncertainty using global vector autoregressions with drifting parameters," Papers 1908.06325, arXiv.org, revised Dec 2019.
    3. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2019. "Assessing International Commonality in Macroeconomic Uncertainty and Its Effects," Working Papers 18-03R, Federal Reserve Bank of Cleveland.
    4. Luca Rossi, 2020. "Indicators of uncertainty: a brief user’s guide," Questioni di Economia e Finanza (Occasional Papers) 564, Bank of Italy, Economic Research and International Relations Area.
    5. Oscar Claveria, 2021. "Uncertainty indicators based on expectations of business and consumer surveys," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 48(2), pages 483-505, May.
    6. Oscar Claveria, 2021. "On the Aggregation of Survey-Based Economic Uncertainty Indicators Between Different Agents and Across Variables," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(1), pages 1-26, April.
    7. Cipollini, Andrea & Mikaliunaite, Ieva, 2020. "Macro-uncertainty and financial stress spillovers in the Eurozone," Economic Modelling, Elsevier, vol. 89(C), pages 546-558.
    8. Śmiech, Sławomir & Papież, Monika & Shahzad, Syed Jawad Hussain, 2020. "Spillover among financial, industrial and consumer uncertainties. The case of EU member states," International Review of Financial Analysis, Elsevier, vol. 70(C).
    9. 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).
    10. Tihana Škrinjarić & Zrinka Orlović, 2020. "Economic Policy Uncertainty and Stock Market Spillovers: Case of Selected CEE Markets," Mathematics, MDPI, vol. 8(7), pages 1-33, July.
    11. Zied Ftiti & Fredj Jawadi, 2019. "Forecasting Inflation Uncertainty in the United States and Euro Area," Computational Economics, Springer;Society for Computational Economics, vol. 54(1), pages 455-476, June.
    12. Giovanni Caggiano & Efrem Castelnuovo & Gabriela Nodari, 2017. "Uncertainty and Monetary Policy in Good and Bad Times," RBA Research Discussion Papers rdp2017-06, Reserve Bank of Australia.
    13. Vasilios Plakandaras & Rangan Gupta & Mark E. Wohar, 2018. "Persistence of Economic Uncertainty: A Comprehensive Analysis," Working Papers 201810, University of Pretoria, Department of Economics.
    14. Ioannis Dokas & Georgios Oikonomou & Minas Panagiotidis & Eleftherios Spyromitros, 2023. "Macroeconomic and Uncertainty Shocks’ Effects on Energy Prices: A Comprehensive Literature Review," Energies, MDPI, vol. 16(3), pages 1-35, February.
    15. Sheen, Jeffrey & Wang, Ben Zhe, 2021. "Measuring macroeconomic disagreement – A mixed frequency approach," Journal of Economic Behavior & Organization, Elsevier, vol. 189(C), pages 547-566.
    16. Cagli, Efe Caglar & Mandaci, Pinar Evrim, 2023. "Time and frequency connectedness of uncertainties in cryptocurrency, stock, currency, energy, and precious metals markets," Emerging Markets Review, Elsevier, vol. 55(C).
    17. Efrem Castelnuovo, 2019. "Yield Curve and Financial Uncertainty: Evidence Based on US Data," "Marco Fanno" Working Papers 0234, Dipartimento di Scienze Economiche "Marco Fanno".
    18. Costantini, Mauro & Sousa, Ricardo M., 2022. "What uncertainty does to euro area sovereign bond markets: Flight to safety and flight to quality," Journal of International Money and Finance, Elsevier, vol. 122(C).
    19. Goemans, Pascal, 2023. "The impact of public consumption and investment in the euro area during periods of high and normal uncertainty," Economic Modelling, Elsevier, vol. 126(C).
    20. Claveria, Oscar, 2022. "Global economic uncertainty and suicide: Worldwide evidence," Social Science & Medicine, Elsevier, vol. 305(C).
    21. 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.
    22. Oscar Claveria, 2020. "Measuring and assessing economic uncertainty," IREA Working Papers 202011, University of Barcelona, Research Institute of Applied Economics, revised Jul 2020.
    23. Ambrocio, Gene, 2017. "The real effects of overconfidence and fundamental uncertainty shocks," Bank of Finland Research Discussion Papers 37/2017, Bank of Finland.
    24. Glas, Alexander, 2020. "Five dimensions of the uncertainty–disagreement linkage," International Journal of Forecasting, Elsevier, vol. 36(2), pages 607-627.
    25. Jia, Wenbo & Lyu, Yiqing & Zhu, Zixiang, 2024. "The tail risk of crude oil Price_Based on EPU and geopolitical risk perspective," Resources Policy, Elsevier, vol. 92(C).
    26. Ambrocio, Gene, 2020. "Inflationary household uncertainty shocks," Bank of Finland Research Discussion Papers 5/2020, Bank of Finland.
    27. Jonathan Rice, 2020. "Policy Uncertainty Shocks and Small Open Economies in Monetary Union: a Case Study of Ireland," Trinity Economics Papers tep1020, Trinity College Dublin, Department of Economics.
    28. Gupta, Rangan & Ma, Jun & Risse, Marian & Wohar, Mark E., 2018. "Common business cycles and volatilities in US states and MSAs: The role of economic uncertainty," Journal of Macroeconomics, Elsevier, vol. 57(C), pages 317-337.
    29. Niels Gillmann & Alexander Hilgenberg, 2021. "Wie man wirtschaftliche Unsicherheit empirisch messen kann – Eine Darstellung am Beispiel von Deutschland," ifo Dresden berichtet, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 28(02), pages 24-29, April.
    30. Christina Christou & Rangan Gupta & Christis Hassapis & Tahir Suleman, 2018. "The role of economic uncertainty in forecasting exchange rate returns and realized volatility: Evidence from quantile predictive regressions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(7), pages 705-719, November.
    31. Alessio Anzuini & Luca Rossi, 2021. "Fiscal policy in the US: a new measure of uncertainty and its effects on the American economy," Empirical Economics, Springer, vol. 61(5), pages 2613-2634, November.
    32. Vasilios Plakandaras & Rangan Gupta & Periklis Gogas & Theophilos Papadimitriou, 2018. "Macroeconomic uncertainty, growth and inflation in the Eurozone: a causal approach," Applied Economics Letters, Taylor & Francis Journals, vol. 25(14), pages 1029-1033, August.
    33. Graziano Moramarco, 2022. "Measuring Global Macroeconomic Uncertainty and Cross-Country Uncertainty Spillovers," Econometrics, MDPI, vol. 11(1), pages 1-29, December.
    34. Oscar Claveria, 2021. "Disagreement on expectations: firms versus consumers," SN Business & Economics, Springer, vol. 1(12), pages 1-23, December.
    35. Svetlana Makarova, 2018. "European Central Bank Footprints On Inflation Forecast Uncertainty," Economic Inquiry, Western Economic Association International, vol. 56(1), pages 637-652, January.
    36. Dibiasi, Andreas & Sarferaz, Samad, 2023. "Measuring macroeconomic uncertainty: A cross-country analysis," European Economic Review, Elsevier, vol. 153(C).
    37. Nong, Huifu, 2021. "Have cross-category spillovers of economic policy uncertainty changed during the US–China trade war?," Journal of Asian Economics, Elsevier, vol. 74(C).
    38. Kranz Tobias, 2019. "Non-Linearities and the Euler Equation: Does Uncertainty Have an Effect on the Approximation Quality?," Review of Economics, De Gruyter, vol. 70(3), pages 267-293, December.
    39. Mr. Tobias Adrian & Andrea Deghi & Mitsuru Katagiri & Mr. Sohaib Shahid & Nico Valckx, 2020. "Predicting Downside Risks to House Prices and Macro-Financial Stability," IMF Working Papers 2020/011, International Monetary Fund.
    40. Bańbura, Marta & Albani, Maria & Ambrocio, Gene & Bursian, Dirk & Buss, Ginters & de Winter, Jasper & Gavura, Miroslav & Giordano, Claire & Júlio, Paulo & Le Roux, Julien & Lozej, Matija & Malthe-Thag, 2018. "Business investment in EU countries," Occasional Paper Series 215, European Central Bank.
    41. Angelini Giovanni & Costantini Mauro & Easaw Joshy, 2024. "Estimating uncertainty spillover effects across euro area using a regime dependent VAR model," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 28(1), pages 39-59, February.

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    See citations under working paper version above.
  10. Marine Carrasco & Barbara Rossi, 2016. "In-Sample Inference and Forecasting in Misspecified Factor Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(3), pages 313-338, July.
    See citations under working paper version above.
  11. Marine Carrasco & Barbara Rossi, 2016. "Rejoinder: In-Sample Inference and Forecasting in Misspecified Factor Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(3), pages 353-356, July.

    Cited by:

    1. Andrii Babii & Eric Ghysels & Jonas Striaukas, 2022. "Machine Learning Time Series Regressions With an Application to Nowcasting," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 1094-1106, June.
    2. 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.
    3. Laurent Ferrara & Anna Simoni, 2020. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," EconomiX Working Papers 2020-11, University of Paris Nanterre, EconomiX.
    4. Wang, Yudong & Pan, Zhiyuan & Liu, Li & Wu, Chongfeng, 2019. "Oil price increases and the predictability of equity premium," Journal of Banking & Finance, Elsevier, vol. 102(C), pages 43-58.
    5. Yousuf, Kashif & Ng, Serena, 2021. "Boosting high dimensional predictive regressions with time varying parameters," Journal of Econometrics, Elsevier, vol. 224(1), pages 60-87.

  12. Emily Anderson & Atsushi Inoue & Barbara Rossi, 2016. "Heterogeneous Consumers and Fiscal Policy Shocks," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 48(8), pages 1877-1888, December.
    See citations under working paper version above.
  13. Barbara Rossi & Tatevik Sekhposyan, 2015. "Macroeconomic Uncertainty Indices Based on Nowcast and Forecast Error Distributions," American Economic Review, American Economic Association, vol. 105(5), pages 650-655, May.
    See citations under working paper version above.
  14. Ferraro, Domenico & Rogoff, Kenneth & Rossi, Barbara, 2015. "Can oil prices forecast exchange rates? An empirical analysis of the relationship between commodity prices and exchange rates," Journal of International Money and Finance, Elsevier, vol. 54(C), pages 116-141.

    Cited by:

    1. Virginie Coudert & Valérie Mignon, 2016. "Reassessing the empirical relationship between the oil price and the dollar," EconomiX Working Papers 2016-2, University of Paris Nanterre, EconomiX.
    2. Bush, Georgia & López Noria, Gabriela, 2021. "Uncertainty and exchange rate volatility: Evidence from Mexico," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 704-722.
    3. Afees A. Salisu & Rangan Gupta, 2019. "How do Housing Returns in Emerging Countries Respond to Oil Shocks? A MIDAS Touch," Working Papers 201946, University of Pretoria, Department of Economics.
    4. Degiannakis, Stavros & Filis, George, 2017. "Forecasting oil price realized volatility using information channels from other asset classes," MPRA Paper 96276, University Library of Munich, Germany.
    5. Haoyuan Ding & Yuying Jin & Cong Qin & Jiezhou Ying, 2020. "Tail Causality between Crude Oil Price and RMB Exchange Rate," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 28(3), pages 116-134, May.
    6. Stijn Claessens & M Ayhan Kose, 2018. "Frontiers of macrofinancial linkages," BIS Papers, Bank for International Settlements, number 95.
    7. Bakas, Dimitrios & Ioakimidis, Marilou & Triantafyllou, Athanasios, 2020. "Commodity Price Uncertainty as a Leading Indicator of Economic Activity," Essex Finance Centre Working Papers 27361, University of Essex, Essex Business School.
    8. Breen, John David & Hu, Liang, 2021. "The predictive content of oil price and volatility: New evidence on exchange rate forecasting," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
    9. Gina Christelle Pieters, 2017. "Bitcoin Reveals Exchange Rate Manipulation and Detects Capital Controls," 2017 Papers ppi307, Job Market Papers.
    10. Yang, Lu & Cai, Xiao Jing & Hamori, Shigeyuki, 2018. "What determines the long-term correlation between oil prices and exchange rates?," The North American Journal of Economics and Finance, Elsevier, vol. 44(C), pages 140-152.
    11. Ahmed, Shamim & Tsvetanov, Daniel, 2016. "The predictive performance of commodity futures risk factors," Journal of Banking & Finance, Elsevier, vol. 71(C), pages 20-36.
    12. 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.
    13. Jean-François Carpantier, 2019. "Commodity Prices In Empirical Research," LIDAM Discussion Papers IRES 2020021, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
    14. Krzysztof Drachal, 2018. "Exchange Rate and Oil Price Interactions in Selected CEE Countries," Economies, MDPI, vol. 6(2), pages 1-21, May.
    15. Fernanda Fuentes & Rodrigo Herrera & Adam Clements, 2016. "Modelling Extreme Risks in Commodities and Commodity Currencies," NCER Working Paper Series 115, National Centre for Econometric Research.
    16. Laurent Ferrara & Pierre Guérin, 2015. "What Are The Macroeconomic Effects of High-Frequency Uncertainty Shocks?," EconomiX Working Papers 2015-12, University of Paris Nanterre, EconomiX.
    17. Tsiakas, Ilias & Zhang, Haibin, 2021. "Economic fundamentals and the long-run correlation between exchange rates and commodities," Global Finance Journal, Elsevier, vol. 49(C).
    18. Bermpei, Theodora & Ferrara, Laurent & Karadimitropoulou, Aikaterini & Triantafyllou, Athanasios, 2024. "Commodity currencies revisited: The role of global commodity price uncertainty," Journal of International Money and Finance, Elsevier, vol. 145(C).
    19. Branko Bošković & Andrew Leach, 2020. "Leave it in the ground? Oil sands development under carbon pricing," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 53(2), pages 526-562, May.
    20. Xiaojie Xu, 2019. "Price dynamics in corn cash and futures markets: cointegration, causality, and forecasting through a rolling window approach," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 33(2), pages 155-181, June.
    21. Lombardi, Marco J. & Ravazzolo, Francesco, 2016. "On the correlation between commodity and equity returns: Implications for portfolio allocation," Journal of Commodity Markets, Elsevier, vol. 2(1), pages 45-57.
    22. Salisu, Afees A. & Adekunle, Wasiu & Alimi, Wasiu A. & Emmanuel, Zachariah, 2019. "Predicting exchange rate with commodity prices: New evidence from Westerlund and Narayan (2015) estimator with structural breaks and asymmetries," Resources Policy, Elsevier, vol. 62(C), pages 33-56.
    23. Ron Alquist & Reinhard Ellwanger & Jianjian Jin, 2020. "The effect of oil price shocks on asset markets: Evidence from oil inventory news," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(8), pages 1212-1230, August.
    24. Khyati Kathuria & Nand Kumar, 2022. "Pandemic‐induced fear and government policy response as a measure of uncertainty in the foreign exchange market: Evidence from (a)symmetric wild bootstrap likelihood ratio test," Pacific Economic Review, Wiley Blackwell, vol. 27(4), pages 361-379, October.
    25. Afees A. Salisu & Juncal Cuñado & Kazeem Isah & Rangan Gupta, 2021. "Stock markets and exchange rate behavior of the BRICS," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1581-1595, December.
    26. Chuffart, Thomas & Hooper, Emma, 2019. "An investigation of oil prices impact on sovereign credit default swaps in Russia and Venezuela," Energy Economics, Elsevier, vol. 80(C), pages 904-916.
    27. Julián Caballero, 2020. "Corporate dollar debt and depreciations: all's well that ends well?," BIS Working Papers 879, Bank for International Settlements.
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    29. Yin, Libo & Su, Zhi & Lu, Man, 2022. "Is oil risk important for commodity-related currency returns?," Research in International Business and Finance, Elsevier, vol. 60(C).
    30. Wen, Shaobo & An, Haizhong & Chen, Zhihua & Liu, Xueyong, 2017. "Driving factors of interactions between the exchange rate market and the commodity market: A wavelet-based complex network perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 299-308.
    31. Abdulrahman, Alhassan & Syed Abul, Basher & M. Kabir, Hassan, 2019. "Oil subsidies and the risk exposure of oil-user stocks: Evidence from net oil producers," MPRA Paper 97080, University Library of Munich, Germany.
    32. Djeutem, Edouard & Dunbar, Geoffrey R., 2022. "Uncovered return parity: Equity returns and currency returns," Journal of International Money and Finance, Elsevier, vol. 128(C).
    33. Marek Szturo & Bogdan Włodarczyk & Ireneusz Miciuła & Karolina Szturo, 2021. "The Essence of Relationships between the Crude Oil Market and Foreign Currencies Market Based on a Study of Key Currencies," Energies, MDPI, vol. 14(23), pages 1-17, November.
    34. Beckmann, Joscha & Czudaj, Robert L. & Arora, Vipin, 2020. "The relationship between oil prices and exchange rates: Revisiting theory and evidence," Energy Economics, Elsevier, vol. 88(C).
    35. Albulescu, Claudiu Tiberiu & Demirer, Riza & Raheem, Ibrahim D. & Tiwari, Aviral Kumar, 2019. "Does the U.S. economic policy uncertainty connect financial markets? Evidence from oil and commodity currencies," Energy Economics, Elsevier, vol. 83(C), pages 375-388.
    36. Andrey G. Shulgin, 2017. "A Simple Theoretical Setup for the Evaluation of Sterilized Intervention Effectiveness in a Small Open Commodity Exporting Economy," HSE Working papers WP BRP 170/EC/2017, National Research University Higher School of Economics.
    37. Salem Boubakri & Cyriac Guillaumin & Alexandre Silanine, 2019. "Non-linear relationship between real commodity price volatility and real effective exchange rate: The case of commodity-exporting countries," Post-Print halshs-02157574, HAL.
    38. Li, Lei & Yin, Libo & Zhou, Yimin, 2016. "Exogenous shocks and the spillover effects between uncertainty and oil price," Energy Economics, Elsevier, vol. 54(C), pages 224-234.
    39. Kladívko, Kamil & Österholm, Pär, 2021. "Do market participants’ forecasts of financial variables outperform the random-walk benchmark?," Finance Research Letters, Elsevier, vol. 40(C).
    40. Nekhili, Ramzi & Mensi, Walid & Vo, Xuan Vinh, 2021. "Multiscale spillovers and connectedness between gold, copper, oil, wheat and currency markets," Resources Policy, Elsevier, vol. 74(C).
    41. Pincheira, Pablo & Hardy, Nicolas, 2021. "The Mean Squared Prediction Error Paradox," MPRA Paper 107403, University Library of Munich, Germany.
    42. Joseph P Byrne & Ryuta Sakemoto & Bing Xu, 2020. "Commodity price co-movement: heterogeneity and the time-varying impact of fundamentals [Oil price shocks and the stock market: evidence from Japan]," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 47(2), pages 499-528.
    43. Rehman, Mobeen Ur & Ahmad, Nasir & Vo, Xuan Vinh, 2022. "Asymmetric multifractal behaviour and network connectedness between socially responsible stocks and international oil before and during COVID-19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 587(C).
    44. Kunkler, Michael & MacDonald, Ronald, 2019. "The multilateral relationship between oil and G10 currencies," Energy Economics, Elsevier, vol. 78(C), pages 444-453.
    45. Michele Ca' Zorzi & Micha􏰀l Rubaszek, 2018. "Exchange rate forecasting on a napkin," GRU Working Paper Series GRU_2018_025, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
    46. Kose, M. Ayhan & Claessens, Stijn, 2017. "Asset Prices and Macroeconomic Outcomes: A Survey," CEPR Discussion Papers 12460, C.E.P.R. Discussion Papers.
    47. Bonato, Matteo & Cepni, Oguzhan & Gupta, Rangan & Pierdzioch, Christian, 2023. "Climate risks and realized volatility of major commodity currency exchange rates," Journal of Financial Markets, Elsevier, vol. 62(C).
    48. Meng, Juan & Nie, He & Mo, Bin & Jiang, Yonghong, 2020. "Risk spillover effects from global crude oil market to China’s commodity sectors," Energy, Elsevier, vol. 202(C).
    49. Takamitsu Kurita & Patrick James, 2022. "The Canadian–US dollar exchange rate over the four decades of the post‐Bretton Woods float: An econometric study allowing for structural breaks," Metroeconomica, Wiley Blackwell, vol. 73(3), pages 856-883, July.
    50. Han, Liyan & Wan, Li & Xu, Yang, 2020. "Can the Baltic Dry Index predict foreign exchange rates?," Finance Research Letters, Elsevier, vol. 32(C).
    51. Thomas Theobald & Peter Hohlfeld, 2017. "Why have the recent oil price declines not stimulated global economic growth?," IMK Working Paper 185-2017, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
    52. Chuffart Thomas & Flachaire Emmanuel & Péguin-Feissolle Anne, 2018. "Testing for misspecification in the short-run component of GARCH-type models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(5), pages 1-17, December.
    53. Michael B. Devereux & Gregor W. Smith, 2018. "Commodity Currencies and Monetary Policy," NBER Working Papers 25076, National Bureau of Economic Research, Inc.
    54. Thobekile Qabhobho, 2023. "Assessing the Asymmetric Effect of Local Realized Exchange Rate Volatility and Implied Volatilities in Energy Market on Exchange Rate Returns in BRICS," International Journal of Energy Economics and Policy, Econjournals, vol. 13(2), pages 231-239, March.
    55. Wang, Wenhao & Cheung, Yin-Wong, 2023. "Commodity price effects on currencies," Journal of International Money and Finance, Elsevier, vol. 130(C).
    56. Martin Baumgärtner & Jens Klose, 2019. "Forecasting exchange rates with commodity prices—a global country analysis," The World Economy, Wiley Blackwell, vol. 42(9), pages 2546-2565, September.
    57. Suyi Kim & So-Yeun Kim & Kyungmee Choi, 2020. "Effect of Oil Prices on Exchange Rate Movements in Korea and Japan Using Markov Regime-Switching Models," Energies, MDPI, vol. 13(17), pages 1-16, August.
    58. Sharma, Susan Sunila & Phan, Dinh Hoang Bach & Iyke, Bernard, 2019. "Do oil prices predict Indonesian macroeconomy?," Economic Modelling, Elsevier, vol. 82(C), pages 2-12.
    59. Salisu, Afees A. & Adediran, Idris, 2020. "Gold as a hedge against oil shocks: Evidence from new datasets for oil shocks," Resources Policy, Elsevier, vol. 66(C).
    60. Fakhri J. Hasanov & Noha Razek, 2023. "Oil and Non-Oil Determinants of Saudi Arabia’s International Competitiveness: Historical Analysis and Policy Simulations," Sustainability, MDPI, vol. 15(11), pages 1-39, June.
    61. Claudia Foroni & Francesco Ravazzolo & Barbara Sadaba, 2017. "Assessing the Predictive Ability of Sovereign Default Risk on Exchange Rate Returns," Staff Working Papers 17-19, Bank of Canada.
    62. Shamaila Butt & Suresh Ramakrishnan & Nanthakumar Loganathan & Muhammad Ali Chohan, 2020. "Evaluating the exchange rate and commodity price nexus in Malaysia: evidence from the threshold cointegration approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-19, December.
    63. Parul Bhatia, 2021. "Sustainability Of Exchange Rates And Crude Oil Prices Connection With Covid-19: An Investigation For Brics," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 5, pages 19-29, October.
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    65. Andrei Shulgin, 2018. "Sterilized Interventions in the Form of Foreign Currency Repos: VECM Analysis Using Russian Data," Russian Journal of Money and Finance, Bank of Russia, vol. 77(2), pages 68-80, June.
    66. Bork, Lasse & Kaltwasser, Pablo Rovira & Sercu, Piet, 2022. "Aggregation bias in tests of the commodity currency hypothesis," Journal of Banking & Finance, Elsevier, vol. 135(C).
    67. Alam, Md. Samsul & Shahzad, Syed Jawad Hussain & Ferrer, Román, 2019. "Causal flows between oil and forex markets using high-frequency data: Asymmetries from good and bad volatility," Energy Economics, Elsevier, vol. 84(C).
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    92. Ciner, Cetin, 2017. "Predicting white metal prices by a commodity sensitive exchange rate," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 309-315.
    93. Iwaisako, Tokuo & Nakata, Hayato, 2017. "Impact of exchange rate shocks on Japanese exports: Quantitative assessment using a structural VAR model," Journal of the Japanese and International Economies, Elsevier, vol. 46(C), pages 1-16.
    94. Davood Pirayesh Neghab & Mucahit Cevik & M. I. M. Wahab, 2023. "Explaining Exchange Rate Forecasts with Macroeconomic Fundamentals Using Interpretive Machine Learning," Papers 2303.16149, arXiv.org.
    95. Panopoulou, Ekaterini & Souropanis, Ioannis, 2019. "The role of technical indicators in exchange rate forecasting," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 197-221.
    96. Castro Rozo, César & Jiménez-Rodríguez, Rebeca, 2018. "Time-varying relationship between oil price and exchange rate," MPRA Paper 87879, University Library of Munich, Germany.
    97. Ready, Robert & Roussanov, Nikolai & Ward, Colin, 2017. "After the tide: Commodity currencies and global trade," Journal of Monetary Economics, Elsevier, vol. 85(C), pages 69-86.
    98. Hiroyuki Okawa, 2023. "Markov-Regime Switches in Oil Markets: The Fear Factor Dynamics," JRFM, MDPI, vol. 16(2), pages 1-20, January.
    99. Jiang, Yonghong & Feng, Qidi & Mo, Bin & Nie, He, 2020. "Visiting the effects of oil price shocks on exchange rates: Quantile-on-quantile and causality-in-quantiles approaches," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    100. Adetutu, Morakinyo O. & Odusanya, Kayode A. & Ebireri, John E. & Murinde, Victor, 2020. "Oil booms, bank productivity and natural resource curse in finance," Economics Letters, Elsevier, vol. 186(C).
    101. Theodosios Perifanis & Athanasios Dagoumas, 2018. "Price and Volatility Spillovers Between the US Crude Oil and Natural Gas Wholesale Markets," Energies, MDPI, vol. 11(10), pages 1-25, October.
    102. Cerqueti, Roy & Fanelli, Viviana & Rotundo, Giulia, 2019. "Long run analysis of crude oil portfolios," Energy Economics, Elsevier, vol. 79(C), pages 183-205.
    103. Baghestani, Hamid & Toledo, Hugo, 2019. "Oil prices and real exchange rates in the NAFTA region," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 253-264.
    104. Chaturvedi, Priya & Kumar, Kuldeep, 2022. "Econometric modelling of exchange rate volatility using mixed-frequency data," MPRA Paper 115222, University Library of Munich, Germany.
    105. Polbin, Andrey & Shumilov, Andrei, 2020. "Модель Зависимости Обменного Курса Рубля От Цен На Нефть С Марковскими Переключениями Режимов [Modeling the relationship between the Russian ruble exchange rate and oil prices: A Markov regime swit," MPRA Paper 102450, University Library of Munich, Germany.
    106. Oyetayo Oluwatosin J & Adeyeye Patrick Olufemi, 2017. "A Robust Application of the Arbitrage Pricing Theory: Evidence from Nigeria," Journal of Economics and Behavioral Studies, AMH International, vol. 9(1), pages 141-151.
    107. Liu, Li & Tan, Siming & Wang, Yudong, 2020. "Can commodity prices forecast exchange rates?," Energy Economics, Elsevier, vol. 87(C).
    108. Ma, Xiuying & Yang, Zhihua & Xu, Xiangyun & Wang, Chengqi, 2018. "The impact of Chinese financial markets on commodity currency exchange rates," Global Finance Journal, Elsevier, vol. 37(C), pages 186-198.
    109. Jung, Young Cheol & Das, Anupam & McFarlane, Adian, 2020. "The asymmetric relationship between the oil price and the US-Canada exchange rate," The Quarterly Review of Economics and Finance, Elsevier, vol. 76(C), pages 198-206.
    110. Gagnon, Marie-Hélène & Manseau, Guillaume & Power, Gabriel J., 2020. "They're back! Post-financialization diversification benefits of commodities," International Review of Financial Analysis, Elsevier, vol. 71(C).
    111. Meng, Xiangcai & Huang, Chia-Hsing, 2016. "Nonlinear models for the sources of real effective exchange rate fluctuations: Evidence from the Republic of Korea," Japan and the World Economy, Elsevier, vol. 40(C), pages 21-30.
    112. Chatziantoniou, Ioannis & Elsayed, Ahmed H. & Gabauer, David & Gozgor, Giray, 2023. "Oil price shocks and exchange rate dynamics: Evidence from decomposed and partial connectedness measures for oil importing and exporting economies," Energy Economics, Elsevier, vol. 120(C).
    113. Siddiqui, Aaliyah & Kautish, Pradeep & Sharma, Rajesh & Sinha, Avik & Siddiqui, Mujahid, 2022. "Evolving a policy framework discovering the dynamic association between determinants of oil consumption in India," Energy Policy, Elsevier, vol. 169(C).
    114. Changyu Liu & Muhammad Abubakr Naeem & Mobeen Ur Rehman & Saqib Farid & Syed Jawad Hussain Shahzad, 2020. "Oil as Hedge, Safe-Haven, and Diversifier for Conventional Currencies," Energies, MDPI, vol. 13(17), pages 1-19, August.
    115. Frömmel, Michael & Midiliç, Murat, 2021. "Daily currency interventions in an emerging market: Incorporating reserve accumulation to the reaction function," Economic Modelling, Elsevier, vol. 97(C), pages 461-476.

  15. Raffaella Giacomini & Barbara Rossi, 2015. "Forecasting in Nonstationary Environments: What Works and What Doesn't in Reduced-Form and Structural Models," Annual Review of Economics, Annual Reviews, vol. 7(1), pages 207-229, August.
    See citations under working paper version above.
  16. Rossi, Barbara & Sekhposyan, Tatevik, 2014. "Evaluating predictive densities of US output growth and inflation in a large macroeconomic data set," International Journal of Forecasting, Elsevier, vol. 30(3), pages 662-682.
    See citations under working paper version above.
  17. Barbara Rossi, 2013. "Exchange Rate Predictability," Journal of Economic Literature, American Economic Association, vol. 51(4), pages 1063-1119, December.
    See citations under working paper version above.
  18. Rossi, Barbara & Sekhposyan, Tatevik, 2013. "Conditional predictive density evaluation in the presence of instabilities," Journal of Econometrics, Elsevier, vol. 177(2), pages 199-212.
    See citations under working paper version above.
  19. Rossi, Barbara & Sekhposyan, Tatevik, 2011. "Understanding models' forecasting performance," Journal of Econometrics, Elsevier, vol. 164(1), pages 158-172, September.
    See citations under working paper version above.
  20. Barbara Rossi & Sarah Zubairy, 2011. "What Is the Importance of Monetary and Fiscal Shocks in Explaining U.S. Macroeconomic Fluctuations?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 43(6), pages 1247-1270, September.
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  21. Atsushi Inoue & Barbara Rossi, 2011. "Identifying the Sources of Instabilities in Macroeconomic Fluctuations," The Review of Economics and Statistics, MIT Press, vol. 93(4), pages 1186-1204, November.

    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. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    3. Bayar, Omer, 2018. "Weak instruments and estimated monetary policy rules," Journal of Macroeconomics, Elsevier, vol. 58(C), pages 308-317.
    4. In-Koo Cho & Kenneth Kasa, 2016. "Gresham’S Law Of Model Averaging," Discussion Papers dp16-06, Department of Economics, Simon Fraser University.
    5. 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.
    6. Paul Hubert & Harun Mirza, 2014. "Inflation expectation dynamics:the role of past, present and forward looking information," Documents de Travail de l'OFCE 2014-07, Observatoire Francais des Conjonctures Economiques (OFCE).
    7. Gürkaynak, Refet S. & Kantur, Zeynep & Tas, M. Anil & Yildirim, Secil, 2015. "Monetary policy in Turkey after Central Bank independence," CFS Working Paper Series 520, Center for Financial Studies (CFS).
    8. Paul Hubert & Harun Mirza, 2019. "The role of forward- and backward-looking information for inflation expectations formation," SciencePo Working papers Main hal-03403616, HAL.
    9. Paccagnini, Alessia, 2017. "Dealing with Misspecification in DSGE Models: A Survey," MPRA Paper 82914, University Library of Munich, Germany.
    10. Jürgen Jerger & Oke Röhe, 2012. "Testing for Parameter Stability in DSGE Models. The Cases of France, Germany, Italy, and Spain," Working Papers 118, Bavarian Graduate Program in Economics (BGPE).
    11. Lieven Baele & et al., 2012. "Macroeconomic Regimes," Faculty Working Papers 03/12, School of Economics and Business Administration, University of Navarra.
    12. Ana gomez-Loscos & M. Dolores Gadea (Universidad de Zaragoza) & Gabriel Perez-Quiros (Bank of Spain), 2015. "Great Moderation and Great Recession. From plain sailing to stormy seas?," EcoMod2015 8267, EcoMod.
    13. Giovanni Pellegrino & Efrem Castelnuovo & Giovanni Caggiano, 2020. "Uncertainty and Monetary Policy during Extreme Events," Economics Working Papers 2020-11, Department of Economics and Business Economics, Aarhus University.
    14. Tommaso Ferraresi & Andrea Roventini & Willi Semmler, 2016. "Macroeconomic regimes, technological shocks and employment dynamics," Documents de Travail de l'OFCE 2016-19, Observatoire Francais des Conjonctures Economiques (OFCE).
    15. Erdenebat Bataa & Marwan Izzeldin & Denise Osborn, 2015. "Changes in the global oil market," Working Papers 75761696, Lancaster University Management School, Economics Department.
    16. Gulan, Adam, 2018. "Paradise lost? A brief history of DSGE macroeconomics," Bank of Finland Research Discussion Papers 22/2018, Bank of Finland.
    17. Mariano Kulish & Adrian Pagan, 2012. "Estimation and Solution of Models with Expectations and Structural Changes," RBA Research Discussion Papers rdp2012-08, Reserve Bank of Australia.
    18. Martínez-García Enrique, 2018. "Modeling time-variation over the business cycle (1960–2017): an international perspective," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(5), pages 1-25, December.
    19. Yuelin Liu & James Morley, 2013. "Structural Evolution of the Postwar U.S. Economy," Discussion Papers 2013-15A, School of Economics, The University of New South Wales.
    20. Alessandro Casini, 2018. "Tests for Forecast Instability and Forecast Failure under a Continuous Record Asymptotic Framework," Papers 1803.10883, arXiv.org, revised Dec 2018.
    21. Jerger, Jürgen & Röhe, Oke, 2009. "Testing for Parameter Stability in DSGE Models. The Cases of France, Germany and Spain," University of Regensburg Working Papers in Business, Economics and Management Information Systems 453, University of Regensburg, Department of Economics.
    22. Marcellino, Massimiliano & Galvão, Ana Beatriz, 2010. "Endogenous Monetary Policy Regimes and the Great Moderation," CEPR Discussion Papers 7827, C.E.P.R. Discussion Papers.
    23. Raffaella Giacomini & Barbara Rossi, 2014. "Forecasting in Nonstationary Environments: What Works and What Doesn't in Reduced-Form and Structural Models," Working Papers 819, Barcelona School of Economics.
    24. 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.
    25. Mwasi Paza Mboya & Philipp Sibbertsen, 2023. "Optimal forecasts in the presence of discrete structural breaks under long memory," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1889-1908, November.
    26. Harun Mirza & Lidia Storjohann, 2014. "Making Weak Instrument Sets Stronger: Factor‐Based Estimation of Inflation Dynamics and a Monetary Policy Rule," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 46(4), pages 643-664, June.
    27. 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.).
    28. Givens, Gregory & Salemi, Michael, 2012. "Inferring monetary policy objectives with a partially observed state," MPRA Paper 39353, University Library of Munich, Germany.
    29. Yuelin Liu & James Morley, 2013. "Structural Evolution of the Postwar U.S. Economy," Discussion Papers 2013-15, School of Economics, The University of New South Wales.
    30. Mirza, Harun & Storjohann, Lidia, 2011. "Making a Weak Instrument Set Stronger: Factor-Based Estimation of the Taylor Rule," Bonn Econ Discussion Papers 13/2011, University of Bonn, Bonn Graduate School of Economics (BGSE).
    31. Pesaran, M. Hashem & Pick, Andreas & Pranovich, Mikhail, 2013. "Optimal forecasts in the presence of structural breaks," Journal of Econometrics, Elsevier, vol. 177(2), pages 134-152.
    32. Rossi, Barbara & Inoue, Atsushi & Jin, Lu, 2014. "Window Selection for Out-of-Sample Forecasting with Time-Varying Parameters," CEPR Discussion Papers 10168, C.E.P.R. Discussion Papers.
    33. Omer Bayar, 2022. "Reducing large datasets to improve the identification of estimated policy rules," Empirical Economics, Springer, vol. 63(1), pages 113-140, July.
    34. Castelnuovo, Efrem, 2013. "Monetary policy shocks and financial conditions: A Monte Carlo experiment," Journal of International Money and Finance, Elsevier, vol. 32(C), pages 282-303.
    35. M. Hashem Pesaran & Ron P. Smith, 2018. "Tests of Policy Interventions in DSGE Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 80(3), pages 457-484, June.
    36. Castelnuovo, Efrem & Pellegrino, Giovanni, 2018. "Uncertainty-dependent effects of monetary policy shocks: A new-Keynesian interpretation," Journal of Economic Dynamics and Control, Elsevier, vol. 93(C), pages 277-296.
    37. Francesca Marino, 2016. "The Italian productivity slowdown in a Real Business Cycle perspective," International Review of Economics, Springer;Happiness Economics and Interpersonal Relations (HEIRS), vol. 63(2), pages 171-193, June.
    38. Pesaran, M.H. & Pick, A. & Pranovich, M., 2011. "Optimal Forecasts in the Presence of Structural Breaks (Updated 14 November 2011)," Cambridge Working Papers in Economics 1163, Faculty of Economics, University of Cambridge.
    39. Inoue, Atsushi & Jin, Lu & Rossi, Barbara, 2017. "Rolling window selection for out-of-sample forecasting with time-varying parameters," Journal of Econometrics, Elsevier, vol. 196(1), pages 55-67.
    40. 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.
    41. Wang, Yudong & Hao, Xianfeng & Wu, Chongfeng, 2021. "Forecasting stock returns: A time-dependent weighted least squares approach," Journal of Financial Markets, Elsevier, vol. 53(C).
    42. Miguel Casares & Jesús Vázquez, 2018. "The Swings Of U.S. Inflation And The Gibson Paradox," Economic Inquiry, Western Economic Association International, vol. 56(2), pages 799-820, April.
    43. Roberta Cardani & Alessia Paccagnini & Stefania Villa, 2019. "Forecasting with instabilities: an application to DSGE models with financial frictions," Temi di discussione (Economic working papers) 1234, Bank of Italy, Economic Research and International Relations Area.
    44. Galvao Ana Beatriz & Marcellino Massimiliano, 2014. "The effects of the monetary policy stance on the transmission mechanism," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(3), pages 217-236, May.
    45. Imane El Ouadghiri & Remzi Uctum, 2020. "Macroeconomic expectations and time varying heterogeneity: Evidence from individual survey data," Post-Print hal-03319091, HAL.
    46. Aguirre, Idoia & Vázquez, Jesús, 2020. "Learning, parameter variability, and swings in US macroeconomic dynamics," Journal of Macroeconomics, Elsevier, vol. 66(C).
    47. De Lipsis Vincenzo, 2021. "Dating Structural Changes in UK Monetary Policy," The B.E. Journal of Macroeconomics, De Gruyter, vol. 21(2), pages 509-539, June.
    48. John W. Keating & Victor J. Valcarcel, 2012. "What's so Great about the Great Moderation? A Multi-Country Investigation of Time-Varying Volatilities of Output Growth and Inflation," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201204, University of Kansas, Department of Economics.
    49. Likai Chen & Ekaterina Smetanina & Wei Biao Wu, 2022. "Estimation of nonstationary nonparametric regression model with multiplicative structure [Income and wealth distribution in macroeconomics: A continuous-time approach]," The Econometrics Journal, Royal Economic Society, vol. 25(1), pages 176-214.
    50. Kilian, Lutz, 2011. "Structural Vector Autoregressions," CEPR Discussion Papers 8515, C.E.P.R. Discussion Papers.

  22. Inoue, Atsushi & Rossi, Barbara, 2011. "Testing for weak identification in possibly nonlinear models," Journal of Econometrics, Elsevier, vol. 161(2), pages 246-261, April.
    See citations under working paper version above.
  23. 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.

    Cited by:

    1. Barnett, William & Park, Sohee, 2021. "Forecasting Inflation and Output Growth with Credit-Card-Augmented Divisia Monetary Aggregates," MPRA Paper 110298, University Library of Munich, Germany.
    2. Granziera, Eleonora & Sekhposyan, Tatevik, 2019. "Predicting relative forecasting performance: An empirical investigation," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1636-1657.
    3. Niu, Linlin & Xu, Xiu & Chen, Ying, 2015. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," BOFIT Discussion Papers 12/2015, Bank of Finland Institute for Emerging Economies (BOFIT).
    4. Carlos Barros & Luis Gil-Alana, 2012. "Inflation forecasting in Angola: a fractional approach," CEsA Working Papers 103, CEsA - Centre for African and Development Studies.
    5. Serena Ng & Jonathan H. Wright, 2013. "Facts and Challenges from the Great Recession for Forecasting and Macroeconomic Modeling," NBER Working Papers 19469, National Bureau of Economic Research, Inc.
    6. Bordo, Michael D. & Haubrich, Joseph G., 2022. "Some international evidence on the causal impact of the yield curve," Finance Research Letters, Elsevier, vol. 45(C).
    7. Bel, K. & Paap, R., 2013. "Modeling the impact of forecast-based regime switches on macroeconomic time series," Econometric Institute Research Papers EI 2013-25, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    8. Gloria Gonzalez-Rivera & Yingying Sun, 2016. "Density Forecast Evaluation in Unstable Environments," Working Papers 201606, University of California at Riverside, Department of Economics.
    9. Barbara Rossi & Tatevik Sekhposyan, 2013. "Evaluating predictive densities of U.S. output growth and inflation in a large macroeconomic data set," Economics Working Papers 1370, Department of Economics and Business, Universitat Pompeu Fabra.
    10. Rodrigo Sekkel, 2014. "Balance Sheets of Financial Intermediaries: Do They Forecast Economic Activity?," Staff Working Papers 14-40, Bank of Canada.
    11. Anna Florio, 2016. "The central bank as shaper and observer of events: The case of the yield spread," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 49(1), pages 320-346, February.
    12. 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.
    13. 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.
    14. Rusnák, Marek, 2016. "Nowcasting Czech GDP in real time," Economic Modelling, Elsevier, vol. 54(C), pages 26-39.
    15. 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.
    16. Koop, Gary, 2014. "Forecasting with dimension switching VARs," International Journal of Forecasting, Elsevier, vol. 30(2), pages 280-290.
    17. Plakandaras, Vasilios & Gogas, Periklis & Papadimitriou, Theophilos & Gupta, Rangan, 2019. "A re-evaluation of the term spread as a leading indicator," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 476-492.
    18. Vasilios Plakandaras & Periklis Gogas & Theophilos Papadimitriou & Rangan Gupta, 2017. "The Informational Content of the Term Spread in Forecasting the US Inflation Rate: A Nonlinear Approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(2), pages 109-121, March.
    19. N. Kundan Kishor & Evan F. Koenig, 2022. "Finding a Role for Slack in Real-Time Inflation Forecasting," International Journal of Central Banking, International Journal of Central Banking, vol. 18(2), pages 245-282, June.
    20. Martinez-Martin Jaime & Morris Richard & Onorante Luca & Piersanti Fabio Massimo, 2024. "Merging Structural and Reduced-Form Models for Forecasting," The B.E. Journal of Macroeconomics, De Gruyter, vol. 24(1), pages 399-437, January.
    21. Raffaella Giacomini & Barbara Rossi, 2014. "Forecasting in Nonstationary Environments: What Works and What Doesn't in Reduced-Form and Structural Models," Working Papers 819, Barcelona School of Economics.
    22. Vasilios Plakandaras & Periklis Gogas & Theophilos Papadimitriou & Rangan Gupta, 2016. "The Term Premium as a Leading Macroeconomic Indicator," Working Papers 201613, University of Pretoria, Department of Economics.
    23. Marta Crispino & Vincenzo Mariani, 2023. "A tool to nowcast tourist overnight stays with payment data and complementary indicators," Questioni di Economia e Finanza (Occasional Papers) 746, Bank of Italy, Economic Research and International Relations Area.
    24. Hännikäinen, Jari, 2014. "Zero lower bound, unconventional monetary policy and indicator properties of interest rate spreads," MPRA Paper 56737, University Library of Munich, Germany.
    25. Nonejad, Nima, 2023. "Conditional out-of-sample predictability of aggregate equity returns and aggregate equity return volatility using economic variables," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 91-122.
    26. Burgess, Matthew G. & Langendorf, Ryan E. & Ippolito, Tara & Pielke, Roger Jr, 2020. "Optimistically biased economic growth forecasts and negatively skewed annual variation," SocArXiv vndqr, Center for Open Science.
    27. Primiceri, Giorgio & Giannone, Domenico & Lenza, Michele, 2016. "Priors for the Long Run," CEPR Discussion Papers 11261, C.E.P.R. Discussion Papers.
    28. 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.
    29. Kihwan Kim & Hyun Hak Kim & Norman R. Swanson, 2023. "Mixing mixed frequency and diffusion indices in good times and in bad: an assessment based on historical data around the great recession of 2008," Empirical Economics, Springer, vol. 64(3), pages 1421-1469, March.
    30. Carstensen Kai & Wohlrabe Klaus & Ziegler Christina, 2011. "Predictive Ability of Business Cycle Indicators under Test: A Case Study for the Euro Area Industrial Production," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 82-106, February.
    31. 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).
    32. Li, You & Tay, Anthony, 2021. "The role of macroeconomic and policy uncertainty in density forecast dispersion," Journal of Macroeconomics, Elsevier, vol. 67(C).
    33. Marcus P. A. Cobb, 2020. "Aggregate density forecasting from disaggregate components using Bayesian VARs," Empirical Economics, Springer, vol. 58(1), pages 287-312, January.
    34. Barnett, Alina & Mumtaz, Haroon & Theodoridis, Konstantinos, 2014. "Forecasting UK GDP growth and inflation under structural change. A comparison of models with time-varying parameters," International Journal of Forecasting, Elsevier, vol. 30(1), pages 129-143.
    35. Rachidi Kotchoni & Maxime Leroux & Dalibor Stevanovic, 2019. "Macroeconomic Forecast Accuracy in data-rich environment," Post-Print hal-02435757, HAL.
    36. Barbara Rossi, 2011. "Comment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 25-29, August.
    37. Benjamin Beckers & Konstantin A. Kholodilin & Dirk Ulbricht, 2017. "Reading between the Lines: Using Media to Improve German Inflation Forecasts," Discussion Papers of DIW Berlin 1665, DIW Berlin, German Institute for Economic Research.
    38. Liebermann, Joelle, 2012. "Real-time forecasting in a data-rich environment," Research Technical Papers 07/RT/12, Central Bank of Ireland.
    39. Yousuf, Kashif & Ng, Serena, 2021. "Boosting high dimensional predictive regressions with time varying parameters," Journal of Econometrics, Elsevier, vol. 224(1), pages 60-87.
    40. Denis Shibitov & Mariam Mamedli, 2021. "Forecasting Russian Cpi With Data Vintages And Machine Learning Techniques," Bank of Russia Working Paper Series wps70, Bank of Russia.
    41. Nonejad, Nima, 2020. "Crude oil price changes and the United Kingdom real gross domestic product growth rate: An out-of-sample investigation," The Journal of Economic Asymmetries, Elsevier, vol. 21(C).
    42. Joseph G. Haubrich, 2020. "Does the Yield Curve Predict Output?," Working Papers 20-34, Federal Reserve Bank of Cleveland.
    43. Richard Ashley & Randal J. Verbrugge, 2019. "The Intermittent Phillips Curve: Finding a Stable (But Persistence-Dependent) Phillips Curve Model Specification," Working Papers 19-09R2, Federal Reserve Bank of Cleveland, revised 14 Feb 2023.
    44. Bel, Koen & Paap, Richard, 2016. "Modeling the impact of forecast-based regime switches on US inflation," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1306-1316.
    45. Fossati, Sebastian, 2017. "Testing for State-Dependent Predictive Ability," Working Papers 2017-9, University of Alberta, Department of Economics.
    46. Stephen McKnight & Alexander Mihailov & Fabio Rumler, 2018. "NKPC-Based Inflation Forecasts with a Time-Varying Trend," Serie documentos de trabajo del Centro de Estudios Económicos 2018-05, El Colegio de México, Centro de Estudios Económicos.
    47. 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.
    48. Nonejad, Nima, 2020. "A comprehensive empirical analysis of the predictive impact of the price of crude oil on aggregate equity return volatility," Journal of Commodity Markets, Elsevier, vol. 20(C).
    49. Martínez-Martin, Jaime & Morris, Richard & Onorante, Luca & Piersanti, Fabio M., 2019. "Merging structural and reduced-form models for forecasting: opening the DSGE-VAR box," Working Paper Series 2335, European Central Bank.
    50. Fabrizio Iacone & Luca Rossini & Andrea Viselli, 2024. "Comparing predictive ability in presence of instability over a very short time," Papers 2405.11954, arXiv.org.
    51. Jari Hännikäinen, 2015. "Zero lower bound, unconventional monetary policy and indicator properties of interest rate spreads," Review of Financial Economics, John Wiley & Sons, vol. 26(1), pages 47-54, September.
    52. Harun Özkan & M. Yazgan, 2015. "Is forecasting inflation easier under inflation targeting?," Empirical Economics, Springer, vol. 48(2), pages 609-626, March.

  24. Raffaella Giacomini & Barbara Rossi, 2010. "Forecast comparisons in unstable environments," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 595-620.
    See citations under working paper version above.
  25. Yu-Chin Chen & Kenneth S. Rogoff & Barbara Rossi, 2010. "Can Exchange Rates Forecast Commodity Prices?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 125(3), pages 1145-1194.
    See citations under working paper version above.
  26. Raffaella Giacomini & Barbara Rossi, 2009. "Detecting and Predicting Forecast Breakdowns," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 76(2), pages 669-705.
    See citations under working paper version above.
  27. Massimiliano Marcellino & Barbara Rossi, 2008. "Model Selection for Nested and Overlapping Nonlinear, Dynamic and Possibly Mis‐specified Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(s1), pages 867-893, December.

    Cited by:

    1. Gospodinov, Nikolay & Kan, Raymond & Robotti, Cesare, 2013. "Chi-squared tests for evaluation and comparison of asset pricing models," Journal of Econometrics, Elsevier, vol. 173(1), pages 108-125.
    2. 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.
    3. Christophe Bontemps & Grayham E. Mizon, 2008. "Encompassing: Concepts and Implementation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(s1), pages 721-750, December.
    4. Lavergne, Pascal & Bertail, Patrice, 2020. "Bootstrapping Quasi Likelihood Ratio Tests under Misspecification," TSE Working Papers 20-1102, Toulouse School of Economics (TSE).
    5. Bu Ruijun & Cheng Jie & Hadri Kaddour, 2017. "Specification analysis in regime-switching continuous-time diffusion models for market volatility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(1), pages 65-80, February.
    6. Francesco Battaglia & Mattheos Protopapas, 2012. "An analysis of global warming in the Alpine region based on nonlinear nonstationary time series models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 21(3), pages 315-334, August.

  28. Atsushi Inoue & Barbara Rossi, 2008. "Monitoring and Forecasting Currency Crises," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(2-3), pages 523-534, March.
    See citations under working paper version above.
  29. Pesavento, Elena & Rossi, Barbara, 2007. "Impulse response confidence intervals for persistent data: What have we learned?," Journal of Economic Dynamics and Control, Elsevier, vol. 31(7), pages 2398-2412, July.
    See citations under working paper version above.
  30. Barbara Rossi, 2007. "Expectations hypotheses tests at Long Horizons," Econometrics Journal, Royal Economic Society, vol. 10(3), pages 554-579, November.

    Cited by:

    1. Rossi, Barbara, 2013. "Exchange Rate Predictability," CEPR Discussion Papers 9575, C.E.P.R. Discussion Papers.
    2. Jean Boivin & Marc P. Giannoni & Benoît Mojon, 2008. "How Has the Euro Changed the Monetary Transmission?," NBER Working Papers 14190, National Bureau of Economic Research, Inc.
    3. Kenneth Rogoff & Barbara Rossi & Yu-chin Chen, 2008. "Can Exchange Rates Forecast Commodity Prices?," 2008 Meeting Papers 540, Society for Economic Dynamics.
    4. Demetrescu, Matei & Rodrigues, Paulo M.M. & Taylor, A.M. Robert, 2023. "Transformed regression-based long-horizon predictability tests," Journal of Econometrics, Elsevier, vol. 237(2).
    5. Enrique Martínez García, 2008. "Globalization and monetary policy: an introduction," Globalization Institute Working Papers 11, Federal Reserve Bank of Dallas.
    6. Kostakis, Alexandros & Magdalinos, Tassos & Stamatogiannis, Michalis P., 2023. "Taking stock of long-horizon predictability tests: Are factor returns predictable?," Journal of Econometrics, Elsevier, vol. 237(2).
    7. Alex Maynard, 2006. "The forward premium anomaly: statistical artefact or economic puzzle? New evidence from robust tests," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 39(4), pages 1244-1281, November.
    8. Elena Pesavento, 2006. "Near-Optimal Unit Root Tests with Stationary Covariates with Better Finite Sample Size," Economics Working Papers ECO2006/18, European University Institute.
    9. Jean Boivin & Marc P. Giannoni & Benoît Mojon, 2009. "How Has the Euro Changed the Monetary Transmission Mechanism?," NBER Chapters, in: NBER Macroeconomics Annual 2008, Volume 23, pages 77-125, National Bureau of Economic Research, Inc.
    10. Darvas, Zsolt & Schepp, Zoltán, 2024. "Exchange rates and fundamentals: Forecasting with long maturity forward rates," Journal of International Money and Finance, Elsevier, vol. 143(C).
    11. Antoine Bouveret, 2010. "Economic policies, long run equilibrium and exchange rate dynamics [Politiques économiques, dynamique et équilibre de long terme du taux de change]," SciencePo Working papers Main tel-04097866, HAL.
    12. Erik Hjalmarsson & Tamas Kiss, 2022. "Long‐run predictability tests are even worse than you thought," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(7), pages 1334-1355, November.
    13. Ventosa-Santaulària, Daniel & Noriega, Antonio E., 2015. "Long-run monetary neutrality under stochastic and deterministic trends," Economic Modelling, Elsevier, vol. 47(C), pages 372-382.
    14. Ismailov, Adilzhan & Rossi, Barbara, 2018. "Uncertainty and deviations from uncovered interest rate parity," Journal of International Money and Finance, Elsevier, vol. 88(C), pages 242-259.

  31. Raffaella Giacomini & Barbara Rossi, 2006. "How Stable is the Forecasting Performance of the Yield Curve for Output Growth?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(s1), pages 783-795, December.
    See citations under working paper version above.
  32. Rossi, Barbara, 2006. "Are Exchange Rates Really Random Walks? Some Evidence Robust To Parameter Instability," Macroeconomic Dynamics, Cambridge University Press, vol. 10(1), pages 20-38, February.
    See citations under working paper version above.
  33. Barbara Rossi & Elena Pesavento, 2006. "Small-sample confidence intervals for multivariate impulse response functions at long horizons," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(8), pages 1135-1155.
    See citations under working paper version above.
  34. Inoue, Atsushi & Rossi, Barbara, 2005. "Recursive Predictability Tests for Real-Time Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 336-345, July.
    See citations under working paper version above.
  35. Pesavento, Elena & Rossi, Barbara, 2005. "Do Technology Shocks Drive Hours Up Or Down? A Little Evidence From An Agnostic Procedure," Macroeconomic Dynamics, Cambridge University Press, vol. 9(4), pages 478-488, September.
    See citations under working paper version above.
  36. Rossi, Barbara, 2005. "Optimal Tests For Nested Model Selection With Underlying Parameter Instability," Econometric Theory, Cambridge University Press, vol. 21(5), pages 962-990, October.
    See citations under working paper version above.
  37. Rossi, Barbara, 2005. "Confidence Intervals for Half-Life Deviations From Purchasing Power Parity," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 432-442, October.
    See citations under working paper version above.
  38. Barbara Rossi, 2005. "Testing Long-Horizon Predictive Ability With High Persistence, And The Meese-Rogoff Puzzle," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 46(1), pages 61-92, February.
    See citations under working paper version above.

Software components

    Sorry, no citations of software components recorded.

Chapters

  1. Atsushi Inoue & Barbara Rossi, 2018. "The Effects of Conventional and Unconventional Monetary Policy on Exchange Rates," NBER Chapters, in: NBER International Seminar on Macroeconomics 2018, pages 419-447, National Bureau of Economic Research, Inc.
    See citations under working paper version above.
  2. 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.

    Cited by:

    1. Jesus Lago & Grzegorz Marcjasz & Bart De Schutter & Rafa{l} Weron, 2020. "Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark," Papers 2008.08004, arXiv.org, revised Dec 2020.
    2. Alessandra Amendola & Vincenzo Candila & Antonio Scognamillo, 2017. "On the influence of US monetary policy on crude oil price volatility," Empirical Economics, Springer, vol. 52(1), pages 155-178, February.
    3. Nicolau, Mihaela & Palomba, Giulio, 2015. "Dynamic relationships between spot and futures prices. The case of energy and gold commodities," Resources Policy, Elsevier, vol. 45(C), pages 130-143.

  3. 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.
    See citations under working paper version above.
  4. Barbara Rossi, 2008. "Comment on "Exchange Rate Models Are Not As Bad As You Think"," NBER Chapters, in: NBER Macroeconomics Annual 2007, Volume 22, pages 453-470, National Bureau of Economic Research, Inc.

    Cited by:

    1. Dimitris Christopoulos & Miguel A. León-Ledesma, 2009. "On causal Relationships Between Exchange Rates and Fundamentals: Better Than You Think," Studies in Economics 0909, School of Economics, University of Kent.
    2. Kenneth Rogoff & Barbara Rossi & Yu-chin Chen, 2008. "Can Exchange Rates Forecast Commodity Prices?," 2008 Meeting Papers 540, Society for Economic Dynamics.
    3. Domenico Ferraro & Kenneth S. Rogoff & Barbara Rossi, 2012. "Can Oil Prices Forecast Exchange Rates?," NBER Working Papers 17998, National Bureau of Economic Research, Inc.

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