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The Incremental Predictive Information Associated with Using Theoretical New Keynesian DSGE Models vs. Simple Linear Econometric Models

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  • Oleg Korenok
  • Norman R. Swanson

Abstract

In this paper we construct output gap and inflation predictions using a variety of dynamic stochastic general equilibrium (DSGE) sticky price models. Predictive density accuracy tests related to the test discussed in Corradi and Swanson ["Journal of Econometrics" (2005a), forthcoming] as well as predictive accuracy tests due to Diebold and Mariano ["Journal of Business and Economic Statistics" (1995), Vol. 13, pp. 253-263]; and West ["Econometrica" (1996), Vol. 64, pp. 1067-1084] are used to compare the alternative models. A number of simple time-series prediction models (such as autoregressive and vector autoregressive (VAR) models) are additionally used as strawman models. Given that DSGE model restrictions are routinely nested within VAR models, the addition of our strawman models allows us to indirectly assess the usefulness of imposing theoretical restrictions implied by DSGE models on unrestricted econometric models. With respect to predictive density evaluation, our results suggest that the standard sticky price model discussed in Calvo ["Journal of Monetary Economics" (1983), Vol. XII, pp. 383-398] is not outperformed by the same model augmented either with information or indexation, when used to predict the output gap. On the other hand, there are clear gains to using the more recent models when predicting inflation. Results based on mean square forecast error analysis are less clear-cut, although the standard sticky price model fares best at our longest forecast horizon of 3 years, it performs relatively poorly at shorter horizons. When the strawman time-series models are added to the picture, we find that the DSGE models still fare very well, often outperforming our forecast competitions, suggesting that theoretical macroeconomic restrictions yield useful additional information for forming macroeconomic forecasts. Copyright 2005 Blackwell Publishing Ltd.

Suggested Citation

  • Oleg Korenok & Norman R. Swanson, 2005. "The Incremental Predictive Information Associated with Using Theoretical New Keynesian DSGE Models vs. Simple Linear Econometric Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(s1), pages 905-930, December.
  • Handle: RePEc:bla:obuest:v:67:y:2005:i:s1:p:905-930
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    References listed on IDEAS

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    1. Marco Del Negro & Frank Schorfheide, 2009. "Monetary Policy Analysis with Potentially Misspecified Models," American Economic Review, American Economic Association, vol. 99(4), pages 1415-1450, September.
    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. GalĂ­, Jordi, 2002. "New Perspectives on Monetary Policy, Inflation and the Business Cycle," CEPR Discussion Papers 3210, C.E.P.R. Discussion Papers.
    4. Bhardwaj, Geetesh & Corradi, Valentina & Swanson, Norman R., 2008. "A Simulation-Based Specification Test for Diffusion Processes," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 176-193, April.
    5. Hashmat Khan & Zhenhua Zhu, 2002. "Estimates of the Sticky-Information Phillips Curve for the United States, Canada, and the United Kingdom," Staff Working Papers 02-19, Bank of Canada.
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    Cited by:

    1. Korenok, Oleg, 2008. "Empirical comparison of sticky price and sticky information models," Journal of Macroeconomics, Elsevier, vol. 30(3), pages 906-927, September.
    2. N. Gregory Mankiw & Ricardo Reis, 2002. "Sticky Information versus Sticky Prices: A Proposal to Replace the New Keynesian Phillips Curve," The Quarterly Journal of Economics, Oxford University Press, vol. 117(4), pages 1295-1328.
    3. Ghent, Andra C., 2009. "Comparing DSGE-VAR forecasting models: How big are the differences?," Journal of Economic Dynamics and Control, Elsevier, vol. 33(4), pages 864-882, April.
    4. N. Gregory Mankiw & Ricardo Reis, 2007. "Sticky Information in General Equilibrium," Journal of the European Economic Association, MIT Press, vol. 5(2-3), pages 603-613, 04-05.
    5. Ali Dib & Mohamed Gammoudi & Kevin Moran, 2008. "Forecasting Canadian time series with the New Keynesian model," Canadian Journal of Economics, Canadian Economics Association, vol. 41(1), pages 138-165, February.
    6. Ricardo Reis, 2009. "A Sticky-information General Equilibrium Model por Policy Analysis," Central Banking, Analysis, and Economic Policies Book Series,in: Klaus Schmidt-Hebbel & Carl E. Walsh & Norman Loayza (Series Editor) & Klaus Schmidt-Hebbel (Series (ed.), Monetary Policy under Uncertainty and Learning, edition 1, volume 13, chapter 8, pages 227-283 Central Bank of Chile.
    7. Rubaszek, Michal & Skrzypczynski, Pawel, 2008. "On the forecasting performance of a small-scale DSGE model," International Journal of Forecasting, Elsevier, vol. 24(3), pages 498-512.
    8. Oleg Korenok & Stanislav Radchenko & Norman R. Swanson, 2010. "International evidence on the efficacy of new-Keynesian models of inflation persistence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 31-54.
    9. repec:hrv:faseco:33907956 is not listed on IDEAS
    10. Ghent, Andra, 2006. "Comparing Models of Macroeconomic Fluctuations: How Big Are the Differences?," MPRA Paper 180, University Library of Munich, Germany.

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