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Loss function-based evaluation of DSGE models

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  • Frank Schorfheide

    (Department of Economics, University of Pennsylvania, 3718 Locust Walk, Philadelphia, PA 19104-6297, USA)

Abstract

In this paper we propose a Bayesian econometric procedure for the evaluation and comparison of DSGE models. Unlike in many previous econometric approaches we explicitly take into account the possibility that the DSGE models are misspecified and introduce a reference model to complete the model space. Three loss functions are proposed to assess the discrepancy between DSGE model predictions and an overall posterior distribution of population characteristics that the researcher is trying to match. The evaluation procedure is applied to the comparison of a standard cash-in-advance (CIA) and a portfolio adjustment cost (PAC) model. We find that the CIA model has higher posterior probability than the PAC model and achieves a better in-sample time series fit. Both models overpredict the magnitude of the negative correlation between output growth and inflation. However, unlike the PAC model, the CIA model is not able to generate a positive real effect of money growth shocks on aggregate output. Overall, the impulse response dynamics of the PAC model resemble the posterior mean impulse response functions more closely than the responses of the CIA model. Copyright © 2000 John Wiley & Sons, Ltd.

Suggested Citation

  • Frank Schorfheide, 2000. "Loss function-based evaluation of DSGE models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(6), pages 645-670.
  • Handle: RePEc:jae:japmet:v:15:y:2000:i:6:p:645-670
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    File URL: http://qed.econ.queensu.ca:80/jae/2000-v15.6/
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    1. Blanchard, Olivier Jean & Quah, Danny, 1989. "The Dynamic Effects of Aggregate Demand and Supply Disturbances," American Economic Review, American Economic Association, vol. 79(4), pages 655-673, September.
    2. Francis X. Diebold & Lee E. Ohanian & Jeremy Berkowitz, 1998. "Dynamic Equilibrium Economies: A Framework for Comparing Models and Data," Review of Economic Studies, Oxford University Press, vol. 65(3), pages 433-451.
    3. Canova, Fabio, 1994. "Statistical Inference in Calibrated Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 9(S), pages 123-144, Suppl. De.
    4. Cogley, Timothy & Nason, James M, 1995. "Output Dynamics in Real-Business-Cycle Models," American Economic Review, American Economic Association, vol. 85(3), pages 492-511, June.
    5. Kim, Jinill, 2000. "Constructing and estimating a realistic optimizing model of monetary policy," Journal of Monetary Economics, Elsevier, vol. 45(2), pages 329-359, April.
    6. Finn E. Kydland & Edward C. Prescott, 1996. "The Computational Experiment: An Econometric Tool," Journal of Economic Perspectives, American Economic Association, vol. 10(1), pages 69-85, Winter.
    7. Martin Crowder, 1988. "Asymptotic expansions of posterior expectations, distributions and densities for stochastic processes," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 40(2), pages 297-309, June.
    8. Christiano, Lawrence J & Eichenbaum, Martin, 1992. "Current Real-Business-Cycle Theories and Aggregate Labor-Market Fluctuations," American Economic Review, American Economic Association, vol. 82(3), pages 430-450, June.
    9. Christiano, Lawrence J & Eichenbaum, Martin, 1992. "Liquidity Effects and the Monetary Transmission Mechanism," American Economic Review, American Economic Association, vol. 82(2), pages 346-353, May.
    10. John Geweke, 1999. "Using simulation methods for bayesian econometric models: inference, development,and communication," Econometric Reviews, Taylor & Francis Journals, vol. 18(1), pages 1-73.
    11. Ireland, Peter N., 2004. "A method for taking models to the data," Journal of Economic Dynamics and Control, Elsevier, vol. 28(6), pages 1205-1226, March.
    12. Nason, James M & Cogley, Timothy, 1994. "Testing the Implications of Long-Run Neutrality for Monetary Business Cycle Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 9(S), pages 37-70, Suppl. De.
    13. Altug, Sumru, 1989. "Time-to-Build and Aggregate Fluctuations: Some New Evidence," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 30(4), pages 889-920, November.
    14. Rotemberg, Julio J & Woodford, Michael, 1996. "Real-Business-Cycle Models and the Forecastable Movements in Output, Hours, and Consumption," American Economic Review, American Economic Association, vol. 86(1), pages 71-89, March.
    15. Fuerst, Timothy S., 1992. "Liquidity, loanable funds, and real activity," Journal of Monetary Economics, Elsevier, vol. 29(1), pages 3-24, February.
    16. Taylor, John B & Uhlig, Harald, 1990. "Solving Nonlinear Stochastic Growth Models: A Comparison of Alternative Solution Methods," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 1-17, January.
    17. Smith, A A, Jr, 1993. "Estimating Nonlinear Time-Series Models Using Simulated Vector Autoregressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(S), pages 63-84, Suppl. De.
    18. Phillips, Peter C B, 1996. "Econometric Model Determination," Econometrica, Econometric Society, vol. 64(4), pages 763-812, July.
    19. John Geweke, 1999. "Computational Experiments and Reality," Computing in Economics and Finance 1999 401, Society for Computational Economics.
    20. Christopher A. Sims, 1996. "Macroeconomics and Methodology," Journal of Economic Perspectives, American Economic Association, vol. 10(1), pages 105-120, Winter.
    21. DeJong, David N. & Ingram, Beth F. & Whiteman, Charles H., 2000. "A Bayesian approach to dynamic macroeconomics," Journal of Econometrics, Elsevier, vol. 98(2), pages 203-223, October.
    22. DeJong, David N & Ingram, Beth Fisher & Whiteman, Charles H, 1996. "A Bayesian Approach to Calibration," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(1), pages 1-9, January.
    23. Lawrence J. Christiano, 1991. "Modeling the liquidity effect of a money shock," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Win, pages 3-34.
    24. Soderlind, Paul, 1994. "Cyclical Properties of a Real Business Cycle Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 9(S), pages 113-122, Suppl. De.
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