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An Information-Based Explanation for Industry Comovement

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Author Info
Laura Veldkamp () (Stern, Department of Economics New York University)
Justin Wolfers

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Abstract

The covariance of sectoral and aggregate U.S. output is significantly higher than the covariance of sectoral and aggregate productivity. Explaining this industry comovement is a challenge for business cycle theory. We propose an explanation based on costly information about productivity (TFP). Because information has a high fixed cost of production and a low marginal cost of replication, information producers charge more for low-demand signals to cover their high average cost. Forecasts of macroeconomic aggregates, relevant to many producers, are cheap; sector-specific forecasts are more expensive. If many managers use the inexpensive aggregate data to infer their industry TFP, their expected industry TFP will be more correlated than true industry TFP. Since hiring and investment decisions depend on expected TFP, they will also be highly correlated. As a result, sectoral output comoves more than TFP alone would predict

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Publisher Info
Paper provided by Society for Economic Dynamics in its series 2006 Meeting Papers with number 359.

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Date of creation: 03 Dec 2006
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Handle: RePEc:red:sed006:359

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Postal: Society for Economic Dynamics Anne Stubing CV Starr Center for Applied Economics 269 Mercer Street, Room 303 New York University New York, NY 10003
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Related research
Keywords: business cycles; comovement puzzle; information markets;

Find related papers by JEL classification:
E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information

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This page was last updated on 2009-11-26.


This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.