An Information-Based Explanation for Industry Comovement

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