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Acknowledgement Misspecification in Macroeconomic Theory

Author

Listed:
  • Hansen, Lars-Peter

    (U Chicago)

  • Sargent, Thomas-J

    (Stanford U)

Abstract

We explore methods for confronting model misspecification in macroeconomics. We construct dynamic equilibria in which private agents and policy makers recognize that models are approximations. We explore two generalizations of rational expectations equilibria. In one of these equilibria, decision makers use dynamic evolution equations that are imperfect statistical approximations, and in the other misspecification is impossible to detect even from infinite samples of time-series data. In the first of these equilibria, decision rules are tailored to be robust to the allowable statistical discrepancies. Using frequency domain methods, we show that robust decision makers treat model misspecification like time-series econometricians.

Suggested Citation

  • Hansen, Lars-Peter & Sargent, Thomas-J, 2001. "Acknowledgement Misspecification in Macroeconomic Theory," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 19(S1), pages 213-227, February.
  • Handle: RePEc:ime:imemes:v:19:y:2001:i:s1:p:213-227
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    Cited by:

    1. Gonçalo Faria & João Correia-da-Silva, 2014. "A closed-form solution for options with ambiguity about stochastic volatility," Review of Derivatives Research, Springer, vol. 17(2), pages 125-159, July.
    2. Q. Farooq Akram & Yakov Ben-Haim & Øyvind Eitrheim, 2008. "Robust-satisficing monetary policy under parameter uncertainty," Working Paper 2007/14, Norges Bank.
    3. Anmol Bhandari & Jaroslav Borovička & Paul Ho, 2016. "Identifying Ambiguity Shocks in Business Cycle Models Using Survey Data," NBER Working Papers 22225, National Bureau of Economic Research, Inc.
    4. Nabil Al-Najjar & Jonathan Weinstein, 2015. "A Bayesian model of Knightian uncertainty," Theory and Decision, Springer, vol. 78(1), pages 1-22, January.
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    6. Ekaterina Pirozhkova, 2017. "Financial frictions and robust monetary policy in the models of New Keynesian framework," BCAM Working Papers 1701, Birkbeck Centre for Applied Macroeconomics.
    7. W. A. Brock & A. Xepapadeas, 2015. "Modeling Coupled Climate, Ecosystems, and Economic Systems," Working Papers 2015.66, Fondazione Eni Enrico Mattei.
    8. Q. Farooq Akram & Ragnar Nymoen, 2009. "Model Selection for Monetary Policy Analysis: How Important is Empirical Validity?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(1), pages 35-68, February.
    9. Dow, Sheila, 2016. "Uncertainty: A diagrammatic treatment," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy (IfW), vol. 10, pages 1-25.
    10. Epstein, Larry G. & Schneider, Martin, 2003. "Recursive multiple-priors," Journal of Economic Theory, Elsevier, vol. 113(1), pages 1-31, November.
    11. Dirk Bergemann & Benjamin Brooks & Stephen Morris, 2016. "Informationally Robust Optimal Auction Design," Working Papers 084_2016, Princeton University, Department of Economics, Econometric Research Program..
    12. Li, Jing, 2018. "Essays on model uncertainty in financial models," Other publications TiSEM 202cd910-7ef1-4db4-94ae-d, Tilburg University, School of Economics and Management.
    13. Agnieszka Markiewicz, 2012. "Model Uncertainty And Exchange Rate Volatility," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 53(3), pages 815-844, August.
    14. Vipin P. Veetil, 2016. "Out-of-Equilibrium Dynamics with Heterogeneous Capital Goods," New Mathematics and Natural Computation (NMNC), World Scientific Publishing Co. Pte. Ltd., vol. 12(02), pages 157-173, July.
    15. Anastasios Xepapadeas & Athanasios Yannacopoulos, 2018. "Spatially Structured Deep Uncertainty, Robust Control, and Climate Change Policies," DEOS Working Papers 1807, Athens University of Economics and Business.
    16. Jordan, Steven J. & Vivian, Andrew & Wohar, Mark E., 2016. "Can commodity returns forecast Canadian sector stock returns?," International Review of Economics & Finance, Elsevier, vol. 41(C), pages 172-188.
    17. de Castro, Luciano I. & Liu, Zhiwei & Yannelis, Nicholas C., 2017. "Implementation under ambiguity," Games and Economic Behavior, Elsevier, vol. 101(C), pages 20-33.
    18. Saleem Bahaj & Angus Foulis, 2017. "Macroprodential Policy under Uncertainty," International Journal of Central Banking, International Journal of Central Banking, vol. 13(3), pages 119-154, September.
    19. Iverson, Terrence, 2012. "Communicating Trade-offs amid Controversial Science: Decision Support for Climate Policy," Ecological Economics, Elsevier, vol. 77(C), pages 74-90.
    20. Leitemo, Kai & Söderström, Ulf, 2005. "Robust monetary policy in a small open economy," Research Discussion Papers 20/2005, Bank of Finland.
    21. Dilip Nachane, 2017. "Dynamic Stochastic General Equilibrium (DSGE) Modelling :Theory And Practice," Working Papers id:11699, eSocialSciences.
    22. Frank Smets, 2005. "Monetary policy and imperfect knowledge," Research Bulletin, European Central Bank, vol. 2, pages 2-5.
    23. Zhong, Zhuo, 2016. "Reducing opacity in over-the-counter markets," Journal of Financial Markets, Elsevier, vol. 27(C), pages 1-27.

    More about this item

    JEL classification:

    • E61 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Policy Objectives; Policy Designs and Consistency; Policy Coordination
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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