Identifying Labor Market Sorting with Firm Dynamics
Additional contact information
Andreas Gulyas: University of Mannheim
No 856, 2018 Meeting Papers from Society for Economic Dynamics
Studying wage inequality requires understanding how workers and firms match. I propose a novel strategy to identify the complementarities in production between unobserved worker and firm attributes, based on the idea that positive (negative) sorting implies that firms upgrade (downgrade) their workforce quality when they grow in size. I use German matched employer-employee data to estimate a search and matching model with worker-firm complementarities, job-to-job transitions, and firm dynamics. The relationship between changes in workforce quality and firm growth rates in the data informs the strength of complementarities in the model. Thus, this strategy bypasses the lack of identification inherent to environments with constant firm types. I find evidence of negative sorting and a significant dampening effect of worker-firm complementarities on wage inequality. Worker and firm heterogeneity, differential bargaining positions, and sorting contribute 71%, 20%, 32% and -23% to wage dispersion, respectively. Reallocating workers across firms to the first-best allocation without mismatch yields an output gain of less than one percent.
New Economics Papers: this item is included in nep-bec, nep-dge and nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:red:sed018:856
Access Statistics for this paper
More papers in 2018 Meeting Papers from Society for Economic Dynamics Society for Economic Dynamics Marina Azzimonti Department of Economics Stonybrook University 10 Nicolls Road Stonybrook NY 11790 USA. Contact information at EDIRC.
Bibliographic data for series maintained by Christian Zimmermann ().