How Much Should We Trust Estimates of Firm Effects and Worker Sorting?

76 Pages Posted: 15 Jun 2020 Last revised: 13 Oct 2022

See all articles by Stephane Bonhomme

Stephane Bonhomme

University of Chicago

Kerstin Holzheu

Sciences Po

Thibaut Lamadon

University of Chicago

Elena Manresa

Massachusetts Institute of Technology (MIT) - Sloan School of Management

Magne Mogstad

University of Chicago

Bradley Setzler

University of Chicago

Date Written: June 2020

Abstract

Many studies use matched employer-employee data to estimate a statistical model of earnings determination where log-earnings are expressed as the sum of worker effects, firm effects, covariates, and idiosyncratic error terms. Estimates based on this model have produced two influential yet controversial conclusions. First, firm effects typically explain around 20% of the variance of log-earnings, pointing to the importance of firm-specific wage-setting for earnings inequality. Second, the correlation between firm and worker effects is often small and sometimes negative, indicating little if any sorting of high-wage workers to high-paying firms. The objective of this paper is to assess the sensitivity of these conclusions to the biases that arise because of limited mobility of workers across firms. We use employer-employee data from the US and several European countries while taking advantage of both fixed-effects and random-effects methods for bias-correction. We find that limited mobility bias is severe and that bias-correction is important. Once one corrects for limited mobility bias, firm effects dispersion matters less for earnings inequality and worker sorting becomes always positive and typically strong.

Suggested Citation

Bonhomme, Stephane and Holzheu, Kerstin and Lamadon, Thibaut and Manresa, Elena and Mogstad, Magne and Setzler, Bradley, How Much Should We Trust Estimates of Firm Effects and Worker Sorting? (June 2020). NBER Working Paper No. w27368, Available at SSRN: https://ssrn.com/abstract=3626869

Stephane Bonhomme (Contact Author)

University of Chicago

1101 East 58th Street
Chicago, IL 60637
United States

Kerstin Holzheu

Sciences Po

Thibaut Lamadon

University of Chicago ( email )

1101 East 58th Street
Chicago, IL 60637
United States

Elena Manresa

Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )

77 Massachusetts Ave. E62-663
Cambridge, MA 02142
United States

Magne Mogstad

University of Chicago ( email )

1101 East 58th Street
Chicago, IL 60637
United States

Bradley Setzler

University of Chicago ( email )

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