Robot adoption, worker-firm sorting and wage inequality: evidence from administrative panel data

Ester Faia, Gianmarco Ireo Paolo Ottaviano and Saverio Spinella

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

Abstract: Leveraging the geographic dimension of a large administrative panel on employer-employee contracts, we study the impact of robot adoption on wage inequality through changes in worker-firm assortativity. Using recently developed methods to correctly and robustly estimate worker and firm unobserved characteristics, we find that robot adoption increases wage inequality by fostering both horizontal and vertical task specialization across firms. In local economies where robot penetration has been more pronounced, workers performing similar tasks have disproportionately clustered in the same firms ('segregation'). Moreover, such clustering has been characterized by the concentration of higher earners performing more complex tasks in firms paying higher wages ('sorting'). These firms are more productive and poach more aggressively. We rationalize these findings through a simple extension of a well-established class of models with two-sided heterogeneity, on-the-job search, rent sharing and employee Bertrand poaching, where we allow robot adoption to strengthen the complementarities between firm and worker characteristics.

Keywords: robot adoption; worker-firm sorting; wage inequality; technological change; finite mixture models (search for similar items in EconPapers)
JEL-codes: D31 E21 J22 J23 J31 J62 (search for similar items in EconPapers)
Pages: 62 pages
Date: 2023-02-10
New Economics Papers: this item is included in nep-bec, nep-hrm, nep-inv, nep-tid and nep-ure
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http://eprints.lse.ac.uk/121328/ Open access version. (application/pdf)

Related works:
Working Paper: Robot adoption, worker-firm sorting and wage inequality: evidence from administrative panel data (2023)
Working Paper: Robot Adoption, Worker-Firm Sorting and Wage Inequality: Evidence from Administrative Panel Data (2022)
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Persistent link: https://EconPapers.repec.org/RePEc:ehl:lserod:121328

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