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What's News in Business Cycles

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  • Stephanie Schmitt‐Grohé
  • Martín Uribe

Abstract

In this paper, we perform a structural Bayesian estimation of the contribution of anticipated shocks to business cycles in the postwar United States. Our theoretical framework is a real-business-cycle model augmented with four real rigidities: investment adjustment costs, variable capacity utilization, habit formation in consumption, and habit formation in leisure. Business cycles are assumed to be driven by permanent and stationary neutral productivity shocks, permanent investment-specific shocks, and government spending shocks. Each of these shocks is buffeted by four types of structural innovations: unanticipated innovations and innovations anticipated one, two, and three quarters in advance. We find that anticipated shocks account for more than two thirds of predicted aggregate fluctuations. This result is robust to estimating a variant of the model featuring a parametric wealth elasticity of labor supply.
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Suggested Citation

  • Stephanie Schmitt‐Grohé & Martín Uribe, 2012. "What's News in Business Cycles," Econometrica, Econometric Society, vol. 80(6), pages 2733-2764, November.
  • Handle: RePEc:ecm:emetrp:v:80:y:2012:i:6:p:2733-2764
    DOI: ECTA8050
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    File URL: http://hdl.handle.net/10.3982/ECTA8050
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    References listed on IDEAS

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    1. Prescott, Edward C., 1986. "Theory ahead of business-cycle measurement," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 25(1), pages 11-44, January.
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    More about this item

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • E13 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Neoclassical
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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