Estimating DSGE model parameters in a small open economy: Do real-time data matter?

• Authors: Jan Capek
• Languages of publication: EN

Abstracts

EN

This paper investigates the differences between parameters estimated using real-time and those estimated with revised data. The models used are New Keynesian DSGE models of the Czech, Polish, Hungarian, Swiss, and Swedish small open economies in interaction with the euro area. The paper also offers an analysis of data revisions of GDP growth and inflation and trend revisions of interest rates. Data revisions are found to be unbiased and not autocorrelated in all countries. Inflation is usually measured more accurately in real-time than GDP growth, but this is not the case in the euro area. The results of the core analysis suggest that there are significant differences between parameter estimates using real-time data and those estimated using revised data. The model parameters that are most prone to significant differences between real-time and revised estimations are habit in consumption and persistence of domestic supply, of demand, and of world-wide technology shocks. The impulse response analysis suggests that the model behavior based on real-time and revised data is different.

Keywords

EN

real-time data; revision; DSGE model; Bayesian estimation; recursive estimation

• Publisher: Sciendo
• Journal: Review of Economic Perspectives
• Year: 2015
• Volume: 15
• Issue: 1
• Pages: 89-114

Dates

published

2015-03-01

online

2015-04-18

Contributors

author

Jan Capek

• Department of Economics, Faculty of Economics and Administration, Masaryk University,

References

• ARUOBA, S. B. (2008): Data Revisions Are Not Well Behaved, Journal of Money, Credit and Banking, 40, 319-340[WoS]
• AURELIO, M. M. (2005): Do we really know how inflation targeters set interest rates? FRB Kansas City Work. Pap. No. 05-02
• BELKE, A.; KLOSE, J. (2011): Does the ECB Rely on a Taylor Rule During the Financial Crisis? Comparing Ex-post and Real Time Data with Real Time Forecasts. Economic Analysis & Policy, 41:147-172.
• CAPEK, J. (2014): Historical Analysis of Monetary Policy Reaction Functions: Do Real-Time Data Matter? Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 64(6), pages 457-475, December.
• CASARES, M.; VÁZQUEZ, J. (2012): Data Revisions in the Estimation of DSGE models. DFAEII 2012.06
• CLEMENTS, M.; GALVÃO, A. (2011) Improving real-time estimates of output gaps and inflation trends with multiple-vintage VAR models. Working paper CROUSHORE, D. (2011): Frontiers of Real-Time Data Analysis, Journal of Economic Literature, 49, 72-100[WoS]
• CROUSHORE, D.; Stark, T. (2003): A real-time data set for macroeconomists: Does the data vintage matter? Review of Economics and Statistics, 85:605-617.
• CUSINATO, R.; MINELLA, A.; DA SILVA PÔRTO JÚNIOR, S. (2013): Output gap in Brazil: A real-time data analysis, Empirical Economics, 44, 1113-1127
• GALVÃO, A. (2013): Forecasting with DSGE models in the Presence of Data Revisions. 1-23. Working paper GELMAN, A.; RUBIN, D. B. (1992): Inference from Iterative Simulation Using Multiple Sequences, Statistical Science, Vol. 7, No. 4 (Nov., 1992), pp. 457-472
• GERBERDING, C.; SEITZ, F.; WORMS, A. (2005): How the Bundesbank really conducted monetary policy. North American Journal of Economics and Finance, 16:277-292. doi: 10.1016/j.najef.2005.05.003[Crossref]
• GERDESMEIER, D.; ROFFIA, B. (2005): The relevance of real-time data in estimating reaction functions for the euro area. North American Journal of Economics and Finance. Volume: 16, Issue: 3, Pages: 293-307
• HORVÁTH, R. (2009): The time-varying policy neutral rate in real-time: A predictor for future inflation? Economic Modelling, 26:71-81. doi: 10.1016/j.econmod.2008.05.005[WoS][Crossref]
• INCE, O.; PAPELL, D. (2013): The (un)reliability of real-time output gap estimates with revised data, Economic Modelling, 33, 713-721[WoS]
• KOLASA, M.; RUBASZEK, M.; SKRZYPCZYNSKI, P. (2012): Putting the New Keynesian DSGE Model to the Real-Time Forecasting Test. Journal of Money, Credit and Banking 44:1301-1324. doi: 10.1111/j.1538-4616.2012.00533.x [Crossref][WoS]
• LUBIK, T.; SCHORFHEIDE, F. (2006): A Bayesian Look at the New Open Economy Macroeconomics, NBER Macroeconomics Annual 2005, Volume 20, National Bureau of Economic Research, Inc, 313-382
• NERI, S.; ROPELE, T. (2012): Imperfect Information, Real-Time Data and Monetary Policy in the Euro Area. The Economic Journal, Volume 122, Issue 561, pages 651-674
• ORPHANIDES, A.; VAN NORDEN, S. (2002): The Unreliability of Output-Gap Estimates in Real Time, The Review of Economics and Statistics, 84, 569-583[WoS]
• ORPHANIDES, A. (2001): Monetary Policy Rules Based on Real-Time Data, The American Economic Review, American Economic Association, 91, pp. 964-985
• RUSNÁK, M. (2013): Revisions to the Czech National Accounts: Properties and Predictability, Czech Journal of Economics and Finance, 63, 244-261
• VÁZQUEZ, J.; MARÍA-DOLORES, R.; LONDOÑO, J. (2010) Data Revisions and the Monetary Policy Rule: An analysis based on an extension of the basic New Keynesian model. The University of the Basque Country, Mimeo.

Identifiers

DOI

10.1515/revecp-2015-0001