Measuring the Gains from Labor Specialization: Theory and Evidence

41 Pages Posted: 29 Jun 2018

Date Written: June 28, 2018

Abstract

We estimate the productivity effects of labor specialization using a judicial environment that offers a quasi-experimental setting well suited to this purpose. Judges in this environment are randomly assigned many different types of cases. This assignment generates random streaks of same-type cases which create mini-specialization events unrelated to the characteristics of judges or cases. We estimate that when judges receive more cases of a certain type they become faster, i.e., more likely to close cases of that type in any one of the corresponding hearings. Quality, as measured by probability of an appeal, is not negatively affected. We conclude that the channel through which these effects operate is learning-by-doing and that it can be generalised to other types of jobs.

Suggested Citation

Coviello, Decio and Ichino, Andrea and Persico, Nicola, Measuring the Gains from Labor Specialization: Theory and Evidence (June 28, 2018). Available at SSRN: https://ssrn.com/abstract=3204848 or http://dx.doi.org/10.2139/ssrn.3204848

Decio Coviello (Contact Author)

HEC Montreal ( email )

3000, chemin de la Cote-Saint-Catherine,
montreal, Quebec H2V3P7
Canada

Andrea Ichino

University of Bologna ( email )

Piazza Scaravilli 1
40126 Bologna, fc 47100
Italy
+39 349 5965919 (Phone)

Nicola Persico

Northwestern University - Kellogg School of Management ( email )

2001 Sheridan Road
Evanston, IL 60208
United States

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