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.

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Ester Faia, Gianmarco I. P. Ottaviano and Saverio Spinella

10 February 2023     Paper Number CEPDP1902

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This CEP discussion paper is published under the centre's Labour markets programme, Trade programme.

This publication comes under the following theme: Labour market inequality