Correlated disturbances and U.S. business cycles
Vasco Cúrdia and
Ricardo Reis
No 434, Staff Reports from Federal Reserve Bank of New York
Abstract:
The dynamic stochastic general equilibrium (DSGE) models used to study business cycles typically assume that exogenous disturbances are independent first-order autoregressions. This paper relaxes this tight and arbitrary restriction by allowing for disturbances that have a rich contemporaneous and dynamic correlation structure. Our first contribution is a new Bayesian econometric method that uses conjugate conditionals to allow for feasible and quick estimation of DSGE models with correlated disturbances. Our second contribution is a reexamination of U.S. business cycles. We find that allowing for correlated disturbances resolves some conflicts between estimates from DSGE models and those from vector autoregressions and that a key missing ingredient in the models is countercyclical fiscal policy. According to our estimates, government spending and technology disturbances play a larger role in the business cycle than previously ascribed, while changes in markups are less important.
Keywords: Government spending policy; Business cycles; Bayesian statistical decision theory; Fiscal policy; Vector autoregression; Equilibrium (Economics) (search for similar items in EconPapers)
Date: 2010
New Economics Papers: this item is included in nep-cba, nep-dge and nep-mac
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Related works:
Working Paper: Correlated Disturbances and U.S. Business Cycles (2010)
Working Paper: Correlated Disturbances and U.S. Business Cycles (2010)
Working Paper: Correlated Disturbances and U.S. Business Cycles (2009)
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