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An Information-Based Explanation for Industry Comovement

Listed author(s):
  • Laura Veldkamp


    (Stern, Department of Economics New York University)

  • Justin Wolfers

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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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
Handle: RePEc:red:sed006:359
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Society for Economic Dynamics Marina Azzimonti Department of Economics Stonybrook University 10 Nicolls Road Stonybrook NY 11790 USA

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