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, firms’ inflation forecast accuracy depends on their attention to marginal costs, the comovement between their marginal cost and aggregate inflation, and the change in the marginal cost. When calibrated to US input-output data, the model replicates the cross-sectoral relationship between forecast accuracy, Domar weights, and price flexibility. Quantitatively, we find that production networks endogenously increase nominal rigidity. This channel accounts for about 30 percent of the networks’ attenuation of the inflation response to monetary shocks, deepening the standard flattening of the Phillips curve from input-output linkages.

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.

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 show that investing in resilience capital in a disaster-prone country improves welfare despite its high economic costs, but the financial instrument used to mobilize revenue matters. The benefits of resilience building are disproportionately concentrated among wealthier households employed in capital-intensive sectors, while rural and unskilled workers, who lack access to credit markets and work in sectors that do not directly employ public capital, experience smaller gains. Income inequality, as measured by the Gini index, increases slightly with resilience investment, suggesting a role for complementary redistributive policies.

This paper shows that sectoral price stickiness, the repricing frequency governing monetary non-neutrality, is in part an equilibrium outcome of the production network. In a menu-cost model with input-output linkages, sticky suppliers dampen a sector’s input-cost volatility, reducing the variance of its desired price and so its repricing frequency even with its own menu costs fixed. This propagated component is a property of the stationary equilibrium, in closed form in the network and sectoral price moments, that linearized models miss. Consistent with the mechanism, across 341 US sectors repricing frequency rises nearly one-for-one with suppliers’ flexibility, explaining a third of the cross-sectional variation. The propagated component accounts for about 20% of observed stickiness for the typical sector and over half in oil-linked sectors. A monetary policy that weights sectors by their intrinsic rather than observed stickiness lowers the welfare loss by 1% of per-period GDP.