Sorting Between and Within Industries: A Testable Model of Assortative Matching
Abowd, John M.; Kramarz, Francis; Perez-Duarte, Sebastien; Schmutte, Ian M.
We test Shimer's (2005) theory of the sorting of workers between and within industrial sectors based on directed search with coordination frictions, deliberately maintaining its static general equilibrium framework. We fit the model to sector-specific wage, vacancy and output data, including publicly-available statistics that characterize the distribution of worker and employer wage heterogeneity across sectors. Our empirical method is general and can be applied to a broad class of assignment models. The results indicate that industries are the loci of sorting--more productive workers are employed in more productive industries. The evidence confirms that strong assortative matching can be present even when worker and employer components of wage heterogeneity are weakly correlated.
Replication code can be found at https://doi.org/10.3886/E100830V1 and at our Github repository at https://github.com/labordynamicsinstitute/endogenous-mobility-replication. Any opinions and conclusions expressed herein are those of the authors and do not necessarily represent the views of the U.S. Census Bureau. All results have been reviewed to ensure that no confidential information is disclosed. For helpful comments, we thank John Eltinge and seminar participants at Duke University, Louisiana State University, the University of Virginia, SOLE 2015, and AEA 2017. All remaining errors are our own. The data used in this paper were derived from confidential data produced by the LEHD Program at the U.S. Census Bureau. All estimation was performed on public-use versions of these data, which are permanently archived with OpenICPSR and available via https://doi.org/10.3886/E100830V1.
This work received support from National Science Foundation Grants SES-9978093, SES-0339191 and ITR-0427889; National Institute on Aging Grant AG018854; and grants from the Alfred P. Sloan Foundation. Abowd also acknowledges direct support from NSF Grants SES-0339191, CNS-0627680, SES-0922005, TC-1012593, SES-1131848, and NSF Grants SES-0339191, CNS-0627680, SES-0922005, TC-1012593, and SES-1131848.
Annals of Economics and Statistics
Social Statistics; Sorting; Census
An earlier version is available: https://hdl.handle.net/1813/89094
Previously Published As
Forthcoming Annals of Economics and Statistics (2018).