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Correlated Disturbances and U.S. Business Cycles

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  • Cúrdia, Vasco
  • Reis, Ricardo

Abstract

The dynamic stochastic general equilibrium (DSGE) models that are used to study business cycles typically assume that exogenous disturbances are independent autoregressions of order one. 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 make the estimation of DSGE models with correlated disturbances feasible and quick. Our second contribution is a re-examination 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.

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Bibliographic Info

Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 7712.

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Date of creation: Feb 2010
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Handle: RePEc:cpr:ceprdp:7712

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Keywords: Bayesian estimation; DSGE; Robustness;

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  1. King, R.G. & Baxter, M., 1990. "Fiscal Policy In General Equilibrium," RCER Working Papers 244, University of Rochester - Center for Economic Research (RCER).
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Citations

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Cited by:
  1. Christoffel, Kai & Jaccard, Ivan & Kilponen, Juha, 2011. "Government bond risk premia and the cyclicality of fiscal policy," Working Paper Series 1411, European Central Bank.
  2. Woong Yong Park & Jae Won Lee & Saroj Bhattarai, 2012. "Policy Regimes, Policy Shifts, and U.S. Business Cycles," 2012 Meeting Papers 287, Society for Economic Dynamics.
  3. Gospodinov, Nikolay & Lkhagvasuren, Damba, 2013. "A moment-matching method for approximating vector autoregressive processes by finite-state Markov chains," Working Paper 2013-05, Federal Reserve Bank of Atlanta.
  4. Milani, Fabio, 2010. "Expectation Shocks and Learning as Drivers of the Business Cycle," CEPR Discussion Papers 7743, C.E.P.R. Discussion Papers.
  5. István Kónya, 2011. "Convergence and Distortions: the Czech Republic, Hungary and Poland between 1996–2009," MNB Working Papers 2011/6, Magyar Nemzeti Bank (the central bank of Hungary).

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