Working Paper: CEPR ID: DP17532
Authors: Maarten de Ridder; Basile Grassi; Giovanni Morzenti
Abstract: 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 comes from financial statements, which lack information on prices. We use an analytical framework to show that trends in markups or the dispersion of markups across firms can still be well-measured with such data. Finding the average level of the markup does require pricing data, and we propose a consistent estimator for such settings. We validate the analytical results with simulations of a quantitative macroeconomic model and firm-level administrative production and pricing data. Our analysis supports the use of financial data to measure trends in aggregate markups.
Keywords: Macroeconomics; Production Functions; Markups; Competition
JEL Codes: E23; D2; D4; L1; L4
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Revenue data as a proxy for output (E23) | Underestimation of output elasticities (E23) |
| Underestimation of output elasticities (E23) | Bias in markup estimates (C51) |
| Revenue data as a proxy for output (E23) | Bias in markup estimates (C51) |
| Revenue-based markup estimates correlate positively with true markups (L11) | Revenue-based markup estimates are misleading (L11) |
| Average revenue-based markup does not provide accurate information about average true markup (L11) | Average revenue-based markup retains informative value regarding markup dispersion (D39) |
| Assuming a Cobb-Douglas production function (E23) | Misrepresentation of the dispersion of markups (D39) |