Better Workers Move to Better Firms: A Simple Test to Identify Sorting

Collegio Carlo Alberto Working Paper No. 259

46 Pages Posted: 30 Sep 2012

See all articles by Cristian Bartolucci

Cristian Bartolucci

University of Turin - Collegio Carlo Alberto

Francesco Devicienti

University of Turin - Collegio Carlo Alberto; University of Turin - Department of Economics and Financial Sciences G. Prato

Multiple version iconThere are 2 versions of this paper

Date Written: July 29, 2012

Abstract

We propose a test that uses information on workers’ mobility, wages and firms’ profits to identify the sign and strength of assortative matching. The basic intuition underlying our empirical strategy is that, in the presence of positive (negative) assortative matching, good workers are more (less) likely to move to better firms than bad workers. Assuming that agents’ payoffs are increasing in their own types allows us to use within-firm variation on wages to rank workers by their types and firm profits to rank firms. We exploit a panel data set that combines Social Security earnings records for workers in the Veneto region of Italy with detailed balance-sheet information for employers. We find robust evidence that positive assortative matching is a pervasive phenomenon in the labor market. This result is in contrast with what we find from correlating the worker and firm fixed effects in standard Mincerian wage equations.

Keywords: Assortative matching, workers’ mobility, matched employer-employee data

JEL Classification: J6, J31, L2

Suggested Citation

Bartolucci, Cristian and Devicienti, Francesco, Better Workers Move to Better Firms: A Simple Test to Identify Sorting (July 29, 2012). Collegio Carlo Alberto Working Paper No. 259. Available at SSRN: https://ssrn.com/abstract=2154322 or http://dx.doi.org/10.2139/ssrn.2154322

Cristian Bartolucci

University of Turin - Collegio Carlo Alberto ( email )

via Real Collegio 30
Moncalieri, Torino 10024
Italy

Francesco Devicienti (Contact Author)

University of Turin - Collegio Carlo Alberto ( email )

via Real Collegio 30
Moncalieri, Torino 10024
Italy

University of Turin - Department of Economics and Financial Sciences G. Prato ( email )

C. so Unione Sovietica, 218 Bis
Torino, 13820-4020
Italy

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