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Confronting Model Misspecification in Macroeconomics

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  • Daniel F. Waggoner
  • Tao Zha

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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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 17791.

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Date of creation: Jan 2012
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Publication status: published as Waggoner, Daniel F. & Zha, Tao, 2012. "Confronting model misspecification in macroeconomics," Journal of Econometrics, Elsevier, vol. 171(2), pages 167-184.
Handle: RePEc:nbr:nberwo:17791

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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. Shaun P Vahey & Elizabeth C Wakerly, 2013. "Moving towards probability forecasting," BIS Papers chapters, in: Bank for International Settlements (ed.), Globalisation and inflation dynamics in Asia and the Pacific, volume 70, pages 3-8 Bank for International Settlements.
  2. Robert Tetlow & Kirstin Hubrich, 2013. "Financial stress and economic dynamics: The transmission of crises," 2013 Meeting Papers 571, Society for Economic Dynamics.
  3. N. Fawcett & G. Kapetanios & J. Mitchell & S. Price, 2014. "Generalised Density Forecast Combinations," CAMA Working Papers 2014-24, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  4. Amisano, Gianni & Geweke, John, 2013. "Prediction using several macroeconomic models," Working Paper Series 1537, European Central Bank.
  5. Marco Del Negro & Frank Schorfheide, 2012. "DSGE model-based forecasting," Staff Reports 554, Federal Reserve Bank of New York.

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