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Empirical and policy performance of a forward‐looking monetary model

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  • Alexei Onatski
  • Noah Williams

Abstract

In this paper we consider the implications of a fully specified dynamic general equilibrium model, developed by Smets and Wouters (2003). This is a relatively large‐scale forward‐looking model, which was shown to provide a good fit to the data. We show that systematically accounting for prior uncertainty may lead to substantially different parameter estimates. However many of the qualitative features of the model remain similar under the alternative estimates that we find. We then formulate and analyze optimal policy rules in the model, focusing on a simple loss function which is commonly used and is independent of the estimates. We determine the optimal equilibrium dynamics for our estimates as well as those of Smets and Wouters, and find that they imply largely similar behavior. We then analyze simple policy rules, finding that these rules perform relatively well and are robust to our different sets of parameter estimates. Overall, our results suggest that the model may be relatively robust in its ability to capture certain aspects of the data. However some caution should be exercised in basing inference on the structural estimates, as these seem to be only weakly identified. Copyright © 2009 John Wiley & Sons, Ltd.

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  • Alexei Onatski & Noah Williams, 2010. "Empirical and policy performance of a forward‐looking monetary model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 145-176, January.
  • Handle: RePEc:wly:japmet:v:25:y:2010:i:1:p:145-176
    DOI: 10.1002/jae.1131
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    3. Christoffel, Kai & Kuester, Keith & Linzert, Tobias, 2009. "The role of labor markets for euro area monetary policy," European Economic Review, Elsevier, vol. 53(8), pages 908-936, November.
    4. Magda Kandil, 2010. "Demand Shocks and the Cyclical Behavior of the Real Wage: Some International Evidence," Journal of Applied Economics, Taylor & Francis Journals, vol. 13(1), pages 135-158, May.
    5. Carla Soares, 2008. "Impact on Welfare of Country Heterogeneity in a Currency Union," Working Papers w200814, Banco de Portugal, Economics and Research Department.
    6. Den Haan, Wouter J. & Drechsel, Thomas, 2021. "Agnostic Structural Disturbances (ASDs): Detecting and reducing misspecification in empirical macroeconomic models," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 258-277.
    7. Daichi Shirai, 2014. "A note on hump-shaped output in the RBC model," CIGS Working Paper Series 14-009E, The Canon Institute for Global Studies.
    8. Patrick Minford & Zhirong Ou & Michael Wickens, 2015. "Revisiting the Great Moderation: Policy or Luck?," Open Economies Review, Springer, vol. 26(2), pages 197-223, April.
    9. Givens, Gregory E., 2016. "On the gains from monetary policy commitment under deep habits," Journal of Macroeconomics, Elsevier, vol. 50(C), pages 19-36.
    10. John B. Taylor & Volker Wieland, 2012. "Surprising Comparative Properties of Monetary Models: Results from a New Model Database," The Review of Economics and Statistics, MIT Press, vol. 94(3), pages 800-816, August.
    11. Costantini, Mauro & Gunter, Ulrich & Kunst, Robert M., 2012. "Forecast Combination Based on Multiple Encompassing Tests in a Macroeconomic DSGE-VAR System," Economics Series 292, Institute for Advanced Studies.
    12. Kolasa, Marcin, 2009. "Structural heterogeneity or asymmetric shocks? Poland and the euro area through the lens of a two-country DSGE model," Economic Modelling, Elsevier, vol. 26(6), pages 1245-1269, November.
    13. IIBOSHI Hirokuni, 2012. "Measuring the Effects of Monetary Policy: A DSGE-DFM Approach," ESRI Discussion paper series 292, Economic and Social Research Institute (ESRI).
    14. Marc P. Giannoni & Jean Boivin, 2005. "DSGE Models in a Data-Rich Environment," Computing in Economics and Finance 2005 431, Society for Computational Economics.
    15. Daniel O. Beltran & David Draper, 2018. "Estimating dynamic macroeconomic models: how informative are the data?," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(2), pages 501-520, February.
    16. Gregory E. Givens, 2012. "Estimating Central Bank Preferences under Commitment and Discretion," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(6), pages 1033-1061, September.
    17. Mauro Costantini & Ulrich Gunter & Robert M. Kunst, 2017. "Forecast Combinations in a DSGE‐VAR Lab," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(3), pages 305-324, April.
    18. Ben Ali, Samir, 2010. "A New Keynesian Phillips curve for Tunisia : Estimation and analysis of sensitivity," MPRA Paper 29624, University Library of Munich, Germany.
    19. Jensen, Henrik & Ravn, Søren Hove & Santoro, Emiliano, 2019. "Kinks and Gains from Credit Cycles," CEPR Discussion Papers 13795, C.E.P.R. Discussion Papers.
    20. Iiboshi, Hirokuni & Matsumae, Tatsuyoshi & Namba, Ryoichi & Nishiyama, Shin-Ichi, 2015. "Estimating a DSGE model for Japan in a data-rich environment," Journal of the Japanese and International Economies, Elsevier, vol. 36(C), pages 25-55.

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