Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach

2007/05/01 by Frank Smets, Rafael Wouters · 4,690 citations
Economics, Econometrics and Finance · #Bayes estimator #Bayesian inference #Bayesian probability #Bayesian vector autoregression #Business cycle #Dynamic stochastic general equilibrium #Econometrics #Economic theories and models #Economics #Great Moderation #Inflation (cosmology) #Macroeconomics #Market Dynamics and Volatility #Monetary Policy and Economic Impact #Monetary policy #Statistics #Vector autoregression

paper · doi:10.1257/aer.97.3.586

published in American Economic Review 97(3), 586-606 (American Economic Association)

openalex publication_date 2007/05/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/04

Abstract

Using a Bayesian likelihood approach, we estimate a dynamic stochastic general equilibrium model for the US economy using seven macroeconomic time series. The model incorporates many types of real and nominal frictions and seven types of structural shocks. We show that this model is able to compete with Bayesian Vector Autoregression models in out-of-sample prediction. We investigate the relative empirical importance of the various frictions. Finally, using the estimated model, we address a number of key issues in business cycle analysis: What are the sources of business cycle fluctuations? Can the model explain the cross correlation between output and inflation? What are the effects of productivity on hours worked? What are the sources of the “Great Moderation”? (JEL D58, E23, E31, E32)

Citations

• Bayesian Methods for Dynamic Multivariate Models
• Sticky Prices and Monetary Policy: Evidence from Disaggregated US Data

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