Working Paper: CEPR ID: DP6112
Authors: Frank Smets; Rafael Wouters
Abstract: Using a Bayesian likelihood approach, we estimate a dynamic stochastic general equilibrium model for the US economy using seven macro-economic 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??
Keywords: Business Cycle; DSGE Models; Monetary Policy
JEL Codes: E4; E5
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| demand shocks (E39) | output fluctuations (E39) |
| productivity shocks (O49) | decreased labor utilization (J29) |
| price markup shocks (D49) | inflation (E31) |
| wage markup shocks (J39) | inflation (E31) |
| structural shocks (E32) | cross-correlation between output and inflation (E31) |