Macroeconomic outcomes depend on the distribution of markups across firms and over time, making firm‐level markup estimates key for macroeconomic analysis. Methods to obtain these estimates require data on the prices that firms charge. Firm‐level data with wide coverage, however, primarily come from financial statements, which lack information on prices. We use an analytical framework to show that trends in markups over time or the dispersion of markups across firms can still be well‐measured with such data. Measuring the average level of the markup does require pricing data, and we propose a consistent estimator for such settings. We validate the analytical results using simulations of a quantitative macroeconomic model and offer supporting evidence from firm‐level administrative production and pricing data. Our analysis supports the use of financial data to measure trends in aggregate markups.

Do large firm dynamics drive the business cycle? We answer this question by developing a quantitative theory of aggregate fluctuations caused by firm-level disturbances alone. We show that a standard heterogeneous firm dynamics setup already contains in it a theory of the business cycle, without appealing to aggregate shocks. We offer an analytical characterization of the law of motion of the aggregate state in this class of models, the firm size distribution, and show that aggregate output and productivity dynamics display: (i ) persistence, (ii ) volatility, and (iii ) time-varying second moments. We explore the key role of moments of the firm size distribution, and, in particular, the role of large firm dynamics, in shaping aggregate fluctuations, theoretically, quantitatively, and in the data. (JEL D21, D22, D24, E32, L11)

Abstract We study markup cyclicality in a granular macroeconomic model with oligopolistic competition. We first characterize how firm, sectoral, and aggregate markups comove with output at different levels of aggregation in response to firm-level shocks. We quantify the model’s ability to reproduce salient features of the cyclical properties of measured markups in French administrative firm-level data from the bottom (firm) level to the aggregate level. We document that (i) firm-level markups rise with market share and sector-level markups with concentration, (ii) the relationship between markups and sectoral output varies by firm size—negative for small firms but positive for large ones, (iii) sector-level markups move positively with sectoral output, and (iv) sectoral markups show no systematic relationship with aggregate output. Our model helps rationalize these seemingly conflicting patterns of markup cyclicality in the data.

We study whether state-level mandatory business closures implemented in response to the outbreak of the Covid-19 causally affect economic and health outcomes. Using plausibly exogenous variations in exposure to these restrictions, we find that they impose substantial losses to firms and workers, the former bearing approximately two thirds of the cost, consistent with firms partially insuring their workers. We show that mandatory business closures have a significant negative causal effect on mortality rates, particularly in areas featuring contact-intensive occupations. We discuss the assumptions under which the health benefits of business closures exceed their associated economic costs.