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.

Natural disasters often have high economic costs, setting back years of investment in developing countries. This paper develops a multi-sector DSGE model to study the macroeconomic and welfare implications of financing resilience-building using different fiscal instruments. The model includes developing countries’ macroeconomic and distributional features, such as a large unproductive rural sector, an incomplete credit market, and an informal sector. The results indicate that investing in resilience capital in a disaster-prone country improves welfare despite its high economic cost, but the financial instrument used to mobilize revenue matters.

This paper examines the macroeconomic implications of information frictions within a quantitative business cycle model. We develop a general solution method that allows enriching a standard medium-scale DSGE model with dispersed information. We estimate the model using Bayesian methods, incorporating comprehensive macroeconomic and expectation data, and revisit crucial questions about business cycles. Expectations data identifies strong information frictions, which dampen general equilibrium effects and change the relative importance of various shocks in driving business cycles. We find that information frictions complement standard inertial frictions rather than being alternatives. The former is crucial for generating sluggishness in inflation, whereas the latter is important for inertia in real macroeconomic aggregates.