Although policymakers and practitioners are particularly interested in dynamic stochastic general equilibrium (DSGE) models, these are typically too stylized to be applied directly to the data and often yield weak prediction results. Very recently, hybrid DSGE models have become popular for dealing with some of the model misspecifications. Major advances in estimation methodology could allow these models to outperform well-known time series models and effectively deal with more complex real-world problems as richer sources of data become available. In this study we introduce a Bayesian approach to estimate a novel factor augmented DSGE model that extends the model of Consolo et al. [Consolo, A., Favero, C.A., and Paccagnini, A., 2009. On the Statistical Identification of DSGE Models. Journal of Econometrics, 150, 99–115]. We perform a comparative predictive evaluation of point and density forecasts for many different specifications of estimated DSGE models and various classes of VAR models, using datasets from the US economy including real-time data. Simple and hybrid DSGE models are implemented, such as DSGE-VAR and tested against standard, Bayesian and factor augmented VARs. The results can be useful for macro-forecasting and monetary policy analysis.
Adolfson, M., M. Andersson, J. Linde, M. Villani, and A. Vredin. 2007. “Modern Forecasting Models in Action: Improving Macroeconomic Analyses at Central Banks.” International Journal of Central Banking 3 (4): 111–144.
Adolfson, M., M. Andersson, J. Linde, M. Villani, and A. Vredin. 2007. “Modern Forecasting Models in Action: Improving Macroeconomic Analyses at Central Banks.” International Journal of Central Banking 3 (4): 111–144.10.2139/ssrn.980666)| false
Adolfson, M., L. Stefan, L. Jesper, and V. Mattias. 2008. “Evaluating an Estimated New Keynesian Small Open Economy Model.” Journal of Economic Dynamics and Control 32(8): 2690–2721.
Altug, S. 1989. “Time-to-Build and Aggregate Fluctuations: Some New Evidence.” International Economic Review 30 (4): 889–920.
Bernanke, B. S., and J. Boivin. 2003. “Monetary Policy in a Data-Rich Environment.” Journal of Monetary Economics 50 (3): 525–546.10.1016/S0304-3932(03)00024-2)| false
Bernanke, B. S., J. Boivin, and P. Eliasz. 2005. “Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach.” The Quarterly Journal of Economics, MIT Press, 120 (1): 387–422.
Boivin, J., and M. P. Giannoni. 2006. “DSGE Models in a Data-Rich Environment.” NBER Working Papers 12772.
Boivin, J., M. P. Giannoni, and I. Mihov. 2009. “Sticky Prices and Monetary Policy: Evidence from Disaggregated US Data.” American Economic Review, American Economic Association 99 (1): 350–384.10.1257/aer.99.1.350)| false
Brüggemann, R., H. Lütkepohl, and M. Marcellino. 2008. “Forecasting Euro Area Variables with German Pre-EMU Data.” Journal of Forecasting 27 (6): 465–481.
Christiano, L. J., M. Eichenbaum, and C. Evans. 2005. “Nominal Rigidities and the Dynamic effects of a Shock to Monetary Policy.” Journal of Political Economy 113: 1–45.10.1086/426038)| false
Christoffel, K., C. Günter, and W. Anders. 2008. “The New Area-Wide Model of the Euro Area – A Micro-Founded Open-Economy Model for Forecasting and Policy Analysis.” European Central Bank Working Paper Series n. 944.
Chudik, A., and M. H. Pesaran. 2011. “Infinite-Dimensional VARs and Factor Models.” Journal of Econometrics 163 (1): 4–22.
Clarida, R., J. Gal, and M. Gertler. 2000. “Monetary Policy Rules And Macroeconomic Stability: Evidence And Some Theory.” The Quarterly Journal of Economics 115 (1): 147–180.10.1162/003355300554692)| false
Consolo, A., C. A. Favero, and A. Paccagnini. 2009. “On the Statistical Identification of DSGE Models.” Journal of Econometrics 150: 99–115.
Dua, P., and S. C. Ray. 1995. “A BVAR Model for the Connecticut Economy.” Journal of Forecasting 14 (3): 167–180.10.1002/for.3980140303)| false
Edge, R., M. Kiley, and J.-P. Laforte. 2010. “A Comparison of Forecast Performance Between Federal Reserve Staff Forecasts, Simple Reduced-Form Models, and a DSGE Model.” Journal of Applied Econometrics 25 (4): 720–754.
Edge, R., M. Kiley, and J.-P. Laforte. 2010. “A Comparison of Forecast Performance Between Federal Reserve Staff Forecasts, Simple Reduced-Form Models, and a DSGE Model.” Journal of Applied Econometrics 25 (4): 720–754.10.1002/jae.1175)| false
Elder, R., G. Kapetanios, T. Taylor and T. Yates. 2005. “Assessing the MPC’s fan charts.” Bank of England Quarterly Bulletin (Autumn): 326–348.
Fernández-de-Córdoba, G., and J. L. Torres. 2010. “Forecasting the Spanish Economy with a DSGE Model: An Augmented VAR Approach.” Journal of the Spanish Economic Association 2 (3): 379–399.
Forni, M., and Reichlin, L. 1996. “Dynamic Common Factors in Large Cross-Sections.” Empirical Economics 21: 27–42.
Forni, M., M. Hallin, M. Lippi, and L. Reichlin. 2000. “The Generalized Dynamic-Factor Model: Identification And Estimation.” The Review of Economic and Statistics MIT Press, 82 (4): 540–554.10.1162/003465300559037)| false
Gerard, H., and K. Nimark. 2008 “Combing Multivariate Density Forecasts Using Predictive Criteria.” Research Discussion Paper 2008-2, Reserve Bank of Australia.
Geweke, J. 1999. “Using Simulation Methods for Bayesian Econometric Models: Inference.” Development and Communication Econometric Reviews 18 (1): 1–126.
Ingram, B., and C. Whiteman. 1994. “Supplanting the Minnesota Prior – Forecasting Macroeconomics Time Series using Real Business Cycle Model Priors.” Journal of Monetary Economics 34: 497–510.10.1016/0304-3932(94)90030-2)| false
Ireland, P. 2004. “A Method for Taking Models to the Data.” Journal of Economic Dynamics and Control 28: 1205–1226.
Kolasa, M., M. Rubaszek and P. Skrzypczynski. 2012. “Putting the New Keynesian DSGE Model to the Real-Time Forecasting Test.” Journal of Money, Credit and Banking 44 (7): 1301–1324.10.1111/j.1538-4616.2012.00533.x)| false
Kydland, F. E., and E. C. Prescott. 1982. “Time to Build and Aggregate fluctuations.” Econometrica 50 (6): 1345–1370.
Kydland, F. E., and E. C. Prescott. 1982. “Time to Build and Aggregate fluctuations.” Econometrica 50 (6): 1345–1370.10.2307/1913386)| false
Leeper, E. M., and C. A. Sims. 1994. “Toward a modern macroeconomic model usable for policy analysis.” In NBER MAcroeconomics Annual 1994, edited by F. Stanley and J. J. Rotemberg, 81–118. Cambridge, MA: MIT Press.
Leeper, E. M., and C. A. Sims. 1994. “Toward a modern macroeconomic model usable for policy analysis.” In NBER MAcroeconomics Annual 1994, edited by F. Stanley and J. J. Rotemberg, 81–118. Cambridge, MA: MIT Press.10.1086/654239)| false
Litterman, R. B. 1981. “A Bayesian Procedure for Forecasting with Vector Autoregressions.” Working Paper, Federal Reserve Bank of Minneapolis.
Litterman, R. B. 1986. “Forecasting with Bayesian Vector Autoregressions: Five Years of Experience.” Journal of Business and Statistics 4 (1): 25–38.
Marcellino, M. 2004. “Forecasting EMU Macroeconomic Variables.” International Journal of Forecasting 20: 359–372.
Rosenblatt, M. 1952. “Remarks on a Multivariate Transformation.” Annals Mathematical Statistics 23: 470–472.10.1214/aoms/1177729394)| false
Rotemberg, J. J., and M. Woodford. 1997. “An Optimization-Based Econometric Framework For The Evaluation of Monetary Policy.” In NBER Macroeconomics Annual 1997, edited by B. S. Bernanke and J. J. Rotemberg, 297–346. Cambridge, MA: MIT Press.
Rotemberg, J. J., and M. Woodford. 1997. “An Optimization-Based Econometric Framework For The Evaluation of Monetary Policy.” In NBER Macroeconomics Annual 1997, edited by B. S. Bernanke and J. J. Rotemberg, 297–346. Cambridge, MA: MIT Press.10.1086/654340)| false
Rubaszek M, Skrzypczynski P (2008) On the Forecasting Perfomance of a Small-Scale DSGE Model, International Journal of Forecasting, 24, 498–512.
Smets, F., and R. Wouters. 2003. “An Estimated Stochastic Dynamic General Equilibrium Model of the Euro Area.” Journal of the European Economic Association 1: 1123–1175.10.1162/154247603770383415)| false
Smets, F., and R. Wouters. 2004. “Forecasting with a Bayesian DSGE Model: An Application to the Euro area.” Working Paper No. 389, European Central Bank, Frankfurt.
Corresponding author: Stelios Bekiros, Department of Economics, European University Institute (EUI), Via della Piazzuola, 43, I-50133, Florence, Italy, Phone: +39 055 4685 916, Fax: +39 055 4685 902, e-mail: ; and Rimini Centre for Economic Analysis (RCEA), Via Patara, 3, 47900, Rimini, Italy, Phone: +39 0541 434 142, Fax: +39 0541 55 431
SNDE recognizes that advances in statistics and dynamical systems theory can increase our understanding of economic and financial markets. The journal seeks both theoretical and applied papers that characterize and motivate nonlinear phenomena. Researchers are required to assist replication of empirical results by providing copies of data and programs online. Algorithms and rapid communications are also published.