IDEAS home Printed from https://ideas.repec.org/a/wly/iecrev/v63y2022i4p1829-1859.html
   My bibliography  Save this article

Learning About Regime Change

Author

Listed:
  • Andrew Foerster
  • Christian Matthes

Abstract

Total factor productivity (TFP) and investment specific technology (IST) growth both exhibit regime‐switching behavior, but the regime at any given time is difficult to infer. We build a rational expectations real business cycle model where the underlying TFP and IST regimes are unobserved. We develop a general perturbation solution algorithm for a wide class of models with unobserved regime‐switching. Using our method, we show learning about regime‐switching fits the data, affect the responses to regime shifts and intraregime shocks, increase asymmetries in the responses, generate forecast error bias even with rational agents, and raise the welfare cost of fluctuations.

Suggested Citation

  • Andrew Foerster & Christian Matthes, 2022. "Learning About Regime Change," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 63(4), pages 1829-1859, November.
  • Handle: RePEc:wly:iecrev:v:63:y:2022:i:4:p:1829-1859
    DOI: 10.1111/iere.12585
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/iere.12585
    Download Restriction: no

    File URL: https://libkey.io/10.1111/iere.12585?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Andrew Foerster & Juan F. Rubio‐Ramírez & Daniel F. Waggoner & Tao Zha, 2016. "Perturbation methods for Markov‐switching dynamic stochastic general equilibrium models," Quantitative Economics, Econometric Society, vol. 7(2), pages 637-669, July.
    2. Christopher Otrok & Andrew Foerster & Alessandro Rebucci & Gianluca Benigno, 2017. "Estimating Macroeconomic Models of Financial Crises: An Endogenous Regime Switching Approach," 2017 Meeting Papers 572, Society for Economic Dynamics.
    3. Alejandro Justiniano & Giorgio Primiceri & Andrea Tambalotti, 2011. "Investment Shocks and the Relative Price of Investment," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 14(1), pages 101-121, January.
    4. Francesco Bianchi & Leonardo Melosi, 2016. "Modeling The Evolution Of Expectations And Uncertainty In General Equilibrium," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 57(2), pages 717-756, May.
    5. Davig, Troy, 2004. "Regime-switching debt and taxation," Journal of Monetary Economics, Elsevier, vol. 51(4), pages 837-859, May.
    6. Troy Davig & Eric M. Leeper, 2007. "Generalizing the Taylor Principle," American Economic Review, American Economic Association, vol. 97(3), pages 607-635, June.
    7. Alpanda, Sami, 2021. "Regime-Switching Productivity Growth And Bayesian Learning In Real Business Cycles," Macroeconomic Dynamics, Cambridge University Press, vol. 25(2), pages 462-488, March.
    8. David Andolfatto & Paul Gomme, 2003. "Monetary Policy Regimes and Beliefs," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(1), pages 1-30, February.
    9. Schmitt-Grohe, Stephanie & Uribe, Martin, 2004. "Solving dynamic general equilibrium models using a second-order approximation to the policy function," Journal of Economic Dynamics and Control, Elsevier, vol. 28(4), pages 755-775, January.
    10. Barthélemy, Jean & Marx, Magali, 2017. "Solving endogenous regime switching models," Journal of Economic Dynamics and Control, Elsevier, vol. 77(C), pages 1-25.
    11. Milani, Fabio, 2007. "Expectations, learning and macroeconomic persistence," Journal of Monetary Economics, Elsevier, vol. 54(7), pages 2065-2082, October.
    12. John Conlisk, 1996. "Why Bounded Rationality?," Journal of Economic Literature, American Economic Association, vol. 34(2), pages 669-700, June.
    13. Richter, Alexander W. & Throckmorton, Nathaniel A., 2015. "The consequences of an unknown debt target," European Economic Review, Elsevier, vol. 78(C), pages 76-96.
    14. James Bullard & Aarti Singh, 2012. "Learning And The Great Moderation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 53(2), pages 375-397, May.
    15. Farmer, Roger E.A. & Waggoner, Daniel F. & Zha, Tao, 2009. "Understanding Markov-switching rational expectations models," Journal of Economic Theory, Elsevier, vol. 144(5), pages 1849-1867, September.
    16. Jason G. Cummins & Giovanni L. Violante, 2002. "Investment-Specific Technical Change in the US (1947-2000): Measurement and Macroeconomic Consequences," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 5(2), pages 243-284, April.
    17. Kydland, Finn E & Prescott, Edward C, 1982. "Time to Build and Aggregate Fluctuations," Econometrica, Econometric Society, vol. 50(6), pages 1345-1370, November.
    18. Simon Gilchrist & Masashi Saito, 2008. "Expectations, Asset Prices, and Monetary Policy: The Role of Learning," NBER Chapters, in: Asset Prices and Monetary Policy, pages 45-102, National Bureau of Economic Research, Inc.
    19. Lewis, Karen K, 1989. "Changing Beliefs and Systematic Rational Forecast Errors with Evidence from Foreign Exchange," American Economic Review, American Economic Association, vol. 79(4), pages 621-636, September.
    20. Frank Schorfheide, 2005. "Learning and Monetary Policy Shifts," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 8(2), pages 392-419, April.
    21. Kim, Chang-Jin, 1994. "Dynamic linear models with Markov-switching," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 1-22.
    22. Andrew Binning & Junior Maih, 2015. "Sigma point filters for dynamic nonlinear regime switching models," Working Paper 2015/10, Norges Bank.
    23. Hamilton, J.D., 2016. "Macroeconomic Regimes and Regime Shifts," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 163-201, Elsevier.
    24. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    25. Francesco Bianchi & Leonardo Melosi, 2016. "Modeling The Evolution Of Expectations And Uncertainty In General Equilibrium," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 57, pages 717-756, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jason Choi & Andrew Foerster, 2021. "Optimal Monetary Policy Regime Switches," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 42, pages 333-346, October.
    2. Antonio Pacifico, 2021. "Structural Panel Bayesian VAR with Multivariate Time-Varying Volatility to Jointly Deal with Structural Changes, Policy Regime Shifts, and Endogeneity Issues," Econometrics, MDPI, vol. 9(2), pages 1-35, May.
    3. John G. Fernald & Huiyu Li, 2021. "The Impact of COVID on Potential Output," Working Paper Series 2021-09, Federal Reserve Bank of San Francisco.
    4. Janice C. dup Eberly & John dup Fernald, 2022. "Jackson Hole 2022 - Reassessing Economic Constraints: Potential Output (The Impact of COVID on Productivity and Potential Output)," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hamilton, J.D., 2016. "Macroeconomic Regimes and Regime Shifts," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 163-201, Elsevier.
    2. Chang, Yoosoon & Maih, Junior & Tan, Fei, 2021. "Origins of monetary policy shifts: A New approach to regime switching in DSGE models," Journal of Economic Dynamics and Control, Elsevier, vol. 133(C).
    3. Francesco Bianchi & Leonardo Melosi, 2018. "Constrained Discretion and Central Bank Transparency," The Review of Economics and Statistics, MIT Press, vol. 100(1), pages 187-202, March.
    4. Andrew Foerster & Juan F. Rubio‐Ramírez & Daniel F. Waggoner & Tao Zha, 2016. "Perturbation methods for Markov‐switching dynamic stochastic general equilibrium models," Quantitative Economics, Econometric Society, vol. 7(2), pages 637-669, July.
    5. Bianchi, Francesco, 2016. "Methods for measuring expectations and uncertainty in Markov-switching models," Journal of Econometrics, Elsevier, vol. 190(1), pages 79-99.
    6. Zakipour-Saber, Shayan, 2019. "State-dependent Monetary Policy Regimes," Research Technical Papers 4/RT/19, Central Bank of Ireland.
    7. Stéphane Lhuissier & Fabien Tripier, 2021. "Regime‐dependent effects of uncertainty shocks: A structural interpretation," Quantitative Economics, Econometric Society, vol. 12(4), pages 1139-1170, November.
    8. Dave, Chetan & Sorge, Marco, 2023. "Fat Tailed DSGE Models: A Survey and New Results," Working Papers 2023-3, University of Alberta, Department of Economics.
    9. Neusser, Klaus, 2019. "Time–varying rational expectations models," Journal of Economic Dynamics and Control, Elsevier, vol. 107(C), pages 1-1.
    10. Francesco Bianchi & Leonardo Melosi, 2016. "Modeling The Evolution Of Expectations And Uncertainty In General Equilibrium," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 57(2), pages 717-756, May.
    11. Shayan Zakipour-Saber, 2019. "Monetary policy regimes and inflation persistence in the United Kingdom," Working Papers 895, Queen Mary University of London, School of Economics and Finance.
    12. Andrew T. Foerster, 2016. "Monetary Policy Regime Switches And Macroeconomic Dynamics," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 57(1), pages 211-230, February.
    13. Carravetta, Francesco & Sorge, Marco M., 2013. "Model reference adaptive expectations in Markov-switching economies," Economic Modelling, Elsevier, vol. 32(C), pages 551-559.
    14. Xiaoshan Chen & Ronald Macdonald, 2012. "Realized and Optimal Monetary Policy Rules in an Estimated Markov‐Switching DSGE Model of the United Kingdom," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(6), pages 1091-1116, September.
    15. Tolga Özden, 2021. "Heterogeneous Expectations and the Business Cycle at the Effective Lower Bound," Working Papers 714, DNB.
    16. Timothy Cogley & Boyan Jovanovic, 2022. "Structural Breaks in an Endogenous Growth Model [Monetary Policy Regimes and Beliefs]," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 89(2), pages 666-694.
    17. McClung, Nigel, 2020. "E-stability vis-à-vis determinacy in regime-switching models," Journal of Economic Dynamics and Control, Elsevier, vol. 121(C).
    18. Amisano, Gianni & Tristani, Oreste, 2011. "Exact likelihood computation for nonlinear DSGE models with heteroskedastic innovations," Journal of Economic Dynamics and Control, Elsevier, vol. 35(12), pages 2167-2185.
    19. Piero Ferri, 2011. "Macroeconomics of Growth Cycles and Financial Instability," Books, Edward Elgar Publishing, number 14260.
    20. Carravetta, Francesco & Sorge, Marco M., 2011. "On the Solution of Markov-switching Rational Expectations Models," Bonn Econ Discussion Papers 05/2011, University of Bonn, Bonn Graduate School of Economics (BGSE).

    More about this item

    JEL classification:

    • E13 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Neoclassical
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:iecrev:v:63:y:2022:i:4:p:1829-1859. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/deupaus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.