We study the response of an economy to an unexpected epidemic. Households mitigate the spread of the disease by reducing consumption, reducing hours worked, and working from home. Working from home is subject to learning-by-doing and the capacity of the health care system is limited. A social planner worries about two externalities, an infection externality and a healthcare congestion externality. Private agents' mitigation incentives are weak and biased. We show that private safety incentives can even decline at the onset of the epidemic. The planner, on the other hand, implements front-loaded mitigation policies and encourages working from home immediately. In our calibration, assuming a CFR of 1% and an initial infection rate of 0.1%, private mitigation reduces the cumulative death rate from 2.5% of the initially susceptible population to about 1.75%. The planner optimally imposes a drastic suppression policy and reduces the death rate to 0.15% at the cost of an initial drop in consumption of around 25%.

We propose a theory linking imperfect information to resource misallocation and hence to aggregate productivity and output. In our setup, firms look to a variety of noisy information sources when making input decisions. We devise a novel empirical strategy that uses a combination of firm-level production and stock market data to pin down the information structure in the economy. Even when only capital is chosen under imperfect information, applying this methodology to data from the United States, China, and India reveals substantial losses in productivity and output due to the informational friction. Our estimates for these losses range from 7% to 10% for productivity and 10% to 14% for output in China and India, and are smaller, though still significant, in the United States. Losses are substantially higher when labor decisions are also made under imperfect information. We find that firms turn primarily to internal sources for information; learning from financial markets contributes little, even in the United States.

We develop a methodology to disentangle sources of capital 'misallocation', i.e. dispersion in value-added/capital. It measures the contributions of technological/informational frictions and a rich class of firm-specific factors. An application to Chinese manufacturing firms reveals that adjustment costs and uncertainty, while significant, explain only a modest fraction of the dispersion, which stems largely from other factors: a component correlated with productivity and a fixed effect. Adjustment costs are more salient for large US firms, though other factors still account for bulk of the dispersion. Technological/ markup heterogeneity explains a limited fraction in China, but a potentially large share in the US.

The views expressed are those of the authors and do not necessarily reflect official positions of the Federal Reserve Bank of St. Louis, the Federal Reserve System, the Board of Governors, or the National Bureau of Economic Research. We thank Dean Corbae and Pablo D'Erasmo for sharing data on corporate defaults. At least one co-author has disclosed a financial relationship of potential relevance for this research. Further information is available online at http://www.nber.org/papers/w27439.ack NBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

We develop a methodology to disentangle sources of capital “mis-allocation,” i.e., dispersion in value-added/capital. It measures the contributions of technological/informational frictions and a rich class of firm-specific factors. An application to Chinese manufacturing firms reveals that adjustment costs and uncertainty, while significant, explain only a modest fraction of the dispersion, which stems largely from other factors: a component correlated with productivity and a fixed effect. Adjustment costs are more salient for large US firms, though other factors still account for the bulk of the dispersion. Technological/markup heterogeneity explains a limited fraction in China, but a potentially large share in the United States. (JEL D22, D24, D25, E22, G31, L60, O11, O14, O47, P31)

We consider a model of nominal price adjustment with firm-specific and aggregate shocks to economic fundamentals and incomplete, dispersed information. Firms update their expectations about fundamentals based on their own cash flows (revenues and wages). We show that in a model with realistic levels of product-level price dispersion, the firms' inference about aggregate shocks is very gradual, yet in the aggregate prices adjust rapidly in response to aggregate nominal shocks. When an aggregate shock occurs, firms mistakenly attribute it to firm-specific shocks, but adjust prices nevertheless, since the exact nature of the shock matters little for its optimal pricing decision.

When limited commitment hinders unsecured credit, assets help by serving as collateral. We study models where assets differ in pledgability-the extent to which they can be used to secure loansand hence liquidity. Although many previous analyses of imperfect credit focus on producers, we emphasize consumers. Household debt limits are determined by the cost households incur when assets are seized in the event of default. The framework, which nests standard growth and asset-pricing theory, is calibrated to analyze the effects of monetary policy and financial innovation. We show that inflation can raise output, employment and investment, plus improve housing and stock markets. For the baseline calibration, optimal inflation is positive. Increases in pledgability can generate booms and busts in economic activity, but may still be good for welfare.

We study an economy’s response to an unexpected epidemic. The spread of the disease can be mitigated by reducing consumption and hours worked in the office. Working from home is subject to learning-by-doing. Private agents’ rational incentives are relatively weak and fatalistic. The planner recognizes infection and congestion externalities and implements front-loaded mitigation. Under our calibration, the planner reduces cumulative fatalities by 48% compared to 24% by private agents, although with a sharper drop in consumption. Our model can replicate key industry and/or occupational-level patterns and explain how large variations in outcomes across regions can stem from small initial differences.