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Bayesian prior elicitation in DSGE models: Macro- vs micropriors

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  • Lombardi, Marco J.
  • Nicoletti, Giulio

Abstract

Bayesian approaches to the estimation of DSGE models are becoming increasingly popular. Prior knowledge is normally formalized either directly on deep parameters' values (‘microprior’) or indirectly, on macroeconomic indicators, e.g. moments of observable variables (‘macroprior’). We introduce a non-parametric macroprior which is elicited from impulse response functions and assess its performance in shaping posterior estimates. We find that using a macroprior can lead to substantially different posterior estimates. We probe into the details of our result, showing that model misspecification is likely to be responsible of that. In addition, we assess to what extent the use of macropriors is impaired by the need of calibrating some hyperparameters.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Economic Dynamics and Control.

Volume (Year): 36 (2012)
Issue (Month): 2 ()
Pages: 294-313

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Handle: RePEc:eee:dyncon:v:36:y:2012:i:2:p:294-313

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

Related research

Keywords: DSGE models; Bayesian estimation; Prior distribution; Impulse response function;

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References

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  1. Sungbae An & Frank Schorfheide, 2007. "Bayesian Analysis of DSGE Models—Rejoinder," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 211-219.
  2. Lawrence J. Christiano & Martin Eichenbaum & Charles L. Evans, 2005. "Nominal Rigidities and the Dynamic Effects of a Shock to Monetary Policy," Journal of Political Economy, University of Chicago Press, vol. 113(1), pages 1-45, February.
  3. Rabanal, Pau & Rubio-Ramirez, Juan F., 2005. "Comparing New Keynesian models of the business cycle: A Bayesian approach," Journal of Monetary Economics, Elsevier, vol. 52(6), pages 1151-1166, September.
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  5. Canova, Fabio & Sala, Luca, 2009. "Back to square one: Identification issues in DSGE models," Journal of Monetary Economics, Elsevier, vol. 56(4), pages 431-449, May.
  6. Uhlig, Harald, 1999. "What are the Effects of Monetary Policy on Output? Results from an Agnostic Identification Procedure," CEPR Discussion Papers 2137, C.E.P.R. Discussion Papers.
  7. Marco Del Negro & Frank Schorfheide, 2006. "Forming priors for DSGE models (and how it affects the assessment of nominal rigidities)," Working Paper 2006-16, Federal Reserve Bank of Atlanta.
  8. Taylor, John B., 1993. "Discretion versus policy rules in practice," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 39(1), pages 195-214, December.
  9. Durbin, James & Koopman, Siem Jan, 2001. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, number 9780198523543.
  10. Sungbae An & Frank Schorfheide, 2007. "Bayesian Analysis of DSGE Models," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 113-172.
  11. J. M�ller & A. N. Pettitt & R. Reeves & K. K. Berthelsen, 2006. "An efficient Markov chain Monte Carlo method for distributions with intractable normalising constants," Biometrika, Biometrika Trust, vol. 93(2), pages 451-458, June.
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Citations

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Cited by:
  1. Jang, Tae-Seok & Sacht, Stephen, 2012. "Identification of animal spirits in a bounded rationality model: An application to the euro area," Economics Working Papers 2012-12, Christian-Albrechts-University of Kiel, Department of Economics.
  2. Sacht, Stephen, 2014. "Identification of prior information via moment-matching," Economics Working Papers 2014-04, Christian-Albrechts-University of Kiel, Department of Economics.
  3. Dario Caldara & Richard Harrison & Anna Lipinska, 2012. "Practical tools for policy analysis in DSGE models with missing channels," Finance and Economics Discussion Series 2012-72, Board of Governors of the Federal Reserve System (U.S.).

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