Inflation Inattention on the Production Network: Firm-Level Evidence and Macro Implications
Torres Prize for Best Third-Year Paper. Draft available upon request.
We study the determinants and macroeconomic consequences of heterogeneity in firms’ inflation expectations, focusing on industry differences. Relying on a micro-level dataset of US firms’ inflation expectations, we document that firms in industries with larger Domar weights and more flexible prices have more accurate inflation forecasts. To explain these patterns, we develop a rational inattention model of price-setting firms within a production network. In equilibrium, inattention compounds downstream through input-output linkages, and firms’ forecast accuracy depends on their attention to marginal costs and the comovement between marginal costs and aggregate inflation. When calibrated to US input-output data, the model replicates the cross-sectoral relationship between forecast accuracy, Domar weights, and price flexibility. Quantitatively, we show that a selection effect of rational inattention steepens the Phillips curve relative to the exogenous-attention benchmark, partially offsetting the standard flattening effect of input-output linkages.