Measuring Markups with Production Data

41 Pages Posted: 3 Apr 2019 Last revised: 16 Jun 2019

See all articles by Zach Flynn

Zach Flynn

Afiniti

James Traina

University of Chicago

Amit Gandhi

University of Pennsylvania; Microsoft Corporation

Date Written: June 13, 2019

Abstract

We show standard methods to estimate production functions do not identify markups.
This nonidentification creates spurious skewness in estimated markup distributions.
We also show that ex-ante structure on the returns to scale solves the identification
problem. In US public firm data and in a Monte Carlo experiment, we find that
applying constant returns to scale performs remarkably well and reduces the skewness
in the markup distribution among public-firm by as much as half in comparison to
nonidentified estimates. This results in half the efficiency losses in output and labor
shares when calibrated to a recent macroeconomic model.

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

JEL Classification: E2, L11, L13, D24

Suggested Citation

Flynn, Zach and Traina, James and Gandhi, Amit, Measuring Markups with Production Data (June 13, 2019). Available at SSRN: https://ssrn.com/abstract=3358472 or http://dx.doi.org/10.2139/ssrn.3358472

Zach Flynn

Afiniti ( email )

1701 Pennsylvania Ave
Washington, DC 20006
United States

HOME PAGE: http://zflynn.com

James Traina (Contact Author)

University of Chicago ( email )

5807 S. Woodlawn Avenue
Chicago, IL 60637
United States

Amit Gandhi

University of Pennsylvania ( email )

Philadelphia, PA 19104
United States

Microsoft Corporation ( email )

One Microsoft Way
Redmond, WA 98052
United States

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