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Estimating the parameters of a small open economy DSGE model: identifiability and inferential validity

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  • Daniel O. Beltran
  • David Draper

Abstract

This paper estimates the parameters of a stylized dynamic stochastic general equilibrium model using maximum likelihood and Bayesian methods, paying special attention to the issue of weak parameter identification. Given the model and the available data, the posterior estimates of the weakly identified parameters are very sensitive to the choice of priors. We provide a set of tools to diagnose weak identification, which include surface plots of the log-likelihood as a function of two parameters, heat plots of the log-likelihood as a function of three parameters, Monte Carlo simulations using artificial data, and Bayesian estimation using three sets of priors. We find that the policy coefficients and the parameter governing the elasticity of labor supply are weakly identified by the data, and posterior predictive distributions remind us that DSGE models may make poor forecasts even when they fit the data well. Although parameter identification is model- and data-specific, the lack of identification of some key structural parameters in a small-scale DSGE model such as the one we examine should raise a red flag to researchers trying to estimate--and draw valid inferences from--large-scale models featuring many more parameters.

Suggested Citation

  • Daniel O. Beltran & David Draper, 2008. "Estimating the parameters of a small open economy DSGE model: identifiability and inferential validity," International Finance Discussion Papers 955, Board of Governors of the Federal Reserve System (U.S.).
  • Handle: RePEc:fip:fedgif:955
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    Cited by:

    1. Milani, Fabio & Park, Sung Ho, 2015. "The effects of globalization on macroeconomic dynamics in a trade-dependent economy: The case of Korea," Economic Modelling, Elsevier, vol. 48(C), pages 292-305.
    2. D. Siena, 2014. "The European Monetary Union and Imbalances: Is it an Anticipation Story ?," Working papers 501, Banque de France.
    3. Stefan Leist & Klaus Neusser, 2010. "Measuring the Natural Output Level by DSGE Models: An Empirical Investigation for Switzerland," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 146(I), pages 275-300, March.
    4. Marco A. F. H. Cavalcanti & Luciano Vereda, 2011. "Propriedades Dinâmicas de Um Modelo DSGE Com Parametrizações Alternativas Para o Brasil," Discussion Papers 1588, Instituto de Pesquisa Econômica Aplicada - IPEA.
    5. Stefan Leist, 2013. "Driving Forces of the Swiss Output Gap," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 149(IV), pages 493-531, December.
    6. Barbara Rudolf & Mathias Zurlinden, 2014. "A compact open economy DSGE model for Switzerland," Economic Studies 2014-08, Swiss National Bank.
    7. Melecky, Martin, 2012. "Macroeconomic dynamics in Macedonia and Slovakia: Structural estimation and comparison," Economic Modelling, Elsevier, vol. 29(4), pages 1377-1387.
    8. Dungey, Mardi & Vehbi, Tugrul, 2015. "The influences of international output shocks from the US and China on ASEAN economies," Journal of Asian Economics, Elsevier, vol. 39(C), pages 59-71.
    9. Georgiadis, Georgios & Jančoková, Martina, 2017. "Financial globalisation, monetary policy spillovers and macro-modelling: tales from 1001 shocks," Working Paper Series 2082, European Central Bank.
    10. Bernhard Herz & Stefan Hohberger, 2013. "Fiscal Policy, Monetary Regimes and Current Account Dynamics," Review of International Economics, Wiley Blackwell, vol. 21(1), pages 118-136, February.
    11. Grazzini, Jakob & Richiardi, Matteo, 2015. "Estimation of ergodic agent-based models by simulated minimum distance," Journal of Economic Dynamics and Control, Elsevier, vol. 51(C), pages 148-165.
    12. Petre Caraiani, 2009. "An Estimation of Output Gap in Romanian Economy Using the DSGE Approach," Prague Economic Papers, University of Economics, Prague, vol. 2009(4), pages 366-379.
    13. Guillermo Escudé, 2010. "Dynamic Stochastic General Equilibrium Models (DSGE): An Introduction," Ensayos Económicos, Central Bank of Argentina, Economic Research Department, vol. 1(59), pages 25-79, July - Se.
    14. Jakob Grazzini & Matteo G. Richiardi, 2013. "Consistent Estimation of Agent-Based Models by Simulated Minimum Distance," LABORatorio R. Revelli Working Papers Series 130, LABORatorio R. Revelli, Centre for Employment Studies.

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    Keywords

    Econometric models ; Bayesian statistical decision theory ; Macroeconomics;

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