Micro and Macro Perspectives on Production-Based Markups

2026-04-14

AI Summary

This study addresses the challenge of accurately estimating firm-level price markups—the ratio of price to marginal cost—in the absence of explicit demand or market structure models. Treating markup estimates derived from production-based approaches as production residuals akin to Solow residuals, the paper leverages large-scale firm-level panel data to systematically examine their variation across industries and over time. It demonstrates that existing markup estimates are highly sensitive to model specification and measurement error, and that much of the apparent disagreement in the literature regarding trends in markups stems from misattributing technical misspecifications to shifts in market power. By reframing estimation discrepancies through a residual-based perspective, the analysis underscores the critical need to disentangle technological factors from genuine changes in market power and calls for greater methodological transparency in empirical practice.

Technology Category

Game Theory and Economic Paradigms: Auctions and Market-Based SystemsSearch and Optimization: Other Foundations of Search & OptimizationPlanning, Routing, and Scheduling: Planning with Markov Models (MDPs, POMDPs)

Application Category

Economics, Online Markets and Human Computation: Cost models of using LLMs in production systemsGraph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphsSecurity and Privacy: Large-scale security measurements

Abstract

We review the "production approach" to estimating markups, the ratio of price to marginal cost. The approach is uniquely scalable: it requires no model of consumer demand or market structure and applies broadly across firms, industries, and time. Our organizing insight is that the production-based markup is a residual. Like the Solow residual, it is clean in theory but potentially contaminated by misspecification and mismeasurement. This framing helps explain why small differences in implementation can produce starkly different results from the same data. In some cases, markups have risen sharply. In others, they have not. Despite the disagreements in the literature, the importance of understanding and measuring market power cannot be overstated. We provide conceptual rationales for this disagreement, offer practical guidance on data and estimation, and call for greater transparency about how much of the variation attributed to markups may instead reflect technology.

Problem

• markups
• production approach
• market power
• Solow residual
• measurement

Innovation

• production-based markups
• Solow residual
• market power
• measurement error
• transparency