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An Information-Based Explanation for Industry Comovement

Author

Listed:
  • Laura Veldkamp

    () (Stern, Department of Economics New York University)

  • Justin Wolfers

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

Suggested Citation

  • Laura Veldkamp & Justin Wolfers, 2006. "An Information-Based Explanation for Industry Comovement," 2006 Meeting Papers 359, Society for Economic Dynamics.
  • Handle: RePEc:red:sed006:359
    as

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    More about this item

    Keywords

    business cycles; comovement puzzle; information markets;

    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; Mechanism Design

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