Replication data for: Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach
Principal Investigator(s): View help for Principal Investigator(s) Frank Smets; Rafael Wouters
Version: View help for Version V1
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Project Citation:
Smets, Frank, and Wouters, Rafael. Replication data for: Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach. Nashville, TN: American Economic Association [publisher], 2007. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2019-12-07. https://doi.org/10.3886/E116269V1
Project Description
Summary:
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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)
Scope of Project
JEL Classification:
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D58 Computable and Other Applied General Equilibrium Models
E23 Macroeconomics: Production
E31 Price Level; Inflation; Deflation
E32 Business Fluctuations; Cycles
D58 Computable and Other Applied General Equilibrium Models
E23 Macroeconomics: Production
E31 Price Level; Inflation; Deflation
E32 Business Fluctuations; Cycles
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