Empirical evidence on models of rational inattention

At low inflation rates, the main motivation for price changes is idiosyncratic shocks to firms and industries. In standard models of sticky prices, the existence of these idiosyncratic shocks makes prices more flexible and hence monetary policy less powerful to affect real variables (and less needed for offsetting other shocks). In some new "rational inattention" models (e.g., Sims 2004), in contrast, idiosyncratic shocks can make monetary policy more powerful (and more helpful). Idiosyncratic shocks can preoccupy managers so that they devote fewer resources to adjusting to aggregate economic conditions. We plan to compare these new rational inattention theories to the pricing patterns in the micro data collected by the U.S. Bureau of Labor Statistics for the Consumer Price Index. The BLS data will allow us to calculate the size of idiosyncratic firm and industry shocks at the level of 200 to 300 categories of consumption. One cannot do this using the average frequency of price changes for these sectors, as reported in Bils and Klenow (2004). Our primary interest is to use the data to address the question: does a firm's price respond less quickly to aggregate shocks if it faces larger idiosyncratic shocks in its industry, as predicted by rational inattention models? We can condition this on the estimated menu costs in the industry, and can also investigate whether menu costs themselves correlate with more or less rapid responses to aggregate shocks. Importantly, the comparison between models and evidence will be quantitative: we care not just whether the sign goes in the direction predicted by the theory, but the magnitude of the relationship