Identifying Market Power in Production Data

43 Pages Posted: 3 Apr 2019

See all articles by Zach Flynn

Zach Flynn


Amit Gandhi

University of Wisconsin - Madison

James Traina

University of Chicago

Date Written: March 2019


Production-based estimates of markups require output elasticities for a flexible input, but these elasticities are not identified under the standard assumptions of proxy variable estimators. We show markups are identified given an additional economic restriction: constant returns to scale technology. We present Monte Carlo evidence that ignoring the identification problem, as in prior literature, introduces significant bias in estimated markups. Comparing estimators on US public firm data, we find that our approach is also more robust to testable forms of misspecification. Emerging macroeconomic models imply output and labor share wedges using our markup estimates of 1 and 11 percent for our baseline specification, half the size of non-identified estimators. A more demanding specification implies respective losses of 4 and 21 percent.

Keywords: Market Power, Markups, Production Functions, Productivity, Labor Share

JEL Classification: E2, L11, L13, D24

Suggested Citation

Flynn, Zach and Gandhi, Amit and Traina, James, Identifying Market Power in Production Data (March 2019). Available at SSRN: or

Zach Flynn

Afiniti ( email )

1701 Pennsylvania Ave
Washington, DC 20006
United States


Amit Gandhi

University of Wisconsin - Madison ( email )

716 Langdon Street
Madison, WI 53706-1481
United States

James Traina (Contact Author)

University of Chicago ( email )

5807 S. Woodlawn Avenue
Chicago, IL 60637
United States

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