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Confronting model misspecification in macroeconomics

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  • Waggoner, Daniel F.
  • Zha, Tao

Abstract

We estimate a Markov-switching mixture of two familiar macroeconomic models: A richly parameterized DSGE model and a corresponding BVAR model. We show that the Markov-switching mixture model dominates both individual models and improves the fit considerably. Our estimation indicates that the DSGE model plays an important role only in the late 1970s and the early 1980s. We show how to use the mixture model as a data filter for estimation of the DSGE model when the BVAR model is not identified. Moreover, we show how to compute the impulse responses to the same type of shock shared by the DSGE and BVAR models when the shock is identified in the BVAR model. Our exercises demonstrate the importance of integrating model uncertainty and parameter uncertainty to address potential model misspecification in macroeconomics.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 171 (2012)
Issue (Month): 2 ()
Pages: 167-184

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Handle: RePEc:eee:econom:v:171:y:2012:i:2:p:167-184

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Web page: http://www.elsevier.com/locate/jeconom

Related research

Keywords: Markov-switching mixture; Heterogenous models; Regime-dependent weights; Model uncertainty; Parameter uncertainty; Impulse responses; Policy analysis;

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References

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  1. Gordon, Robert J., 1990. "The Measurement of Durable Goods Prices," National Bureau of Economic Research Books, University of Chicago Press, edition 1, number 9780226304557, Septiembr.
  2. Christopher A. Sims & Daniel F. Waggoner & Tao Zha, 2006. "Methods for inference in large multiple-equation Markov-switching models," Working Paper 2006-22, Federal Reserve Bank of Atlanta.
  3. Zheng Liu & Daniel F. Waggoner & Tao Zha, 2010. "Sources Of Macroeconomic Fluctuations: A Regime-Switching Dsge Approach," Emory Economics 1002, Department of Economics, Emory University (Atlanta).
  4. Robert J. Gordon, 1990. "The Measurement of Durable Goods Prices," NBER Books, National Bureau of Economic Research, Inc, number gord90-1, October.
  5. James D. Hamilton & Daniel F. Waggoner & Tao Zha, 2007. "Normalization in Econometrics," Econometric Reviews, Taylor and Francis Journals, vol. 26(2-4), pages 221-252.
  6. John Geweke & Gianni Amisano, 2009. "Optimal Prediction Pools," Working Paper Series 1017, European Central Bank.
  7. Chib, Siddhartha, 1996. "Calculating posterior distributions and modal estimates in Markov mixture models," Journal of Econometrics, Elsevier, vol. 75(1), pages 79-97, November.
  8. Geweke, John & Amisano, Gianni, 2011. "Optimal prediction pools," Journal of Econometrics, Elsevier, vol. 164(1), pages 130-141, September.
  9. Eric M. Leeper & Christopher A. Sims & Tao Zha, 1996. "What Does Monetary Policy Do?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 27(2), pages 1-78.
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Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Confronting Model Misspecification in Macroeconomics
    by Christian Zimmermann in NEP-DGE blog on 2011-01-06 00:58:27
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
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Cited by:
  1. Marco Del Negro & Frank Schorfheide, 2012. "DSGE model-based forecasting," Staff Reports 554, Federal Reserve Bank of New York.
  2. Kirstin Hubrich & Robert J. Tetlow, 2012. "Financial stress and economic dynamics: the transmission of crises," Finance and Economics Discussion Series 2012-82, Board of Governors of the Federal Reserve System (U.S.).

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