Data and code for: "Informal Labor and the Efficiency Cost of Social Programs: Evidence from Unemployment Insurance in Brazil"

Principal Investigator(s): View help for Principal Investigator(s) Francois Gerard, Queen Mary University of London; Gustavo Gonzaga, Pontifical Catholic University of Rio de Janeiro

Version: View help for Version V1

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README.pdf	application/pdf	78.1 KB	11/13/2020 05:09:AM

Project Citation:

Gerard, Francois, and Gonzaga, Gustavo. Data and code for: “Informal Labor and the Efficiency Cost of Social Programs: Evidence from Unemployment Insurance in Brazil” . Nashville, TN: American Economic Association [publisher], 2021. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2021-07-20. https://doi.org/10.3886/E123461V1

Project Description

Summary: It is widely believed that the presence of a large informal sector increases the efficiency cost of social programs in developing countries. We evaluate such claims for the case of Unemployment Insurance (UI) by combining an optimal UI framework with comprehensive data from Brazil. Using quasi-experimental variation in potential UI duration, we find clear evidence for the usual moral hazard problem that UI reduces incentives to return to a formal job. Yet, the associated efficiency cost is lower than in the U.S., and is lower in labor markets with higher informality within Brazil. This is because formal reemployment rates are lower to begin with where informality is higher, so that a larger share of workers would draw UI benefits absent any moral hazard. In sum, efficiency concerns may actually become more relevant as an economy formalizes.

Scope of Project

Subject Terms: informal labor; unemployment insurance; efficiency cost; social programs; Brazil

JEL Classification:
      J46 Informal Labor Markets
      J64 Unemployment: Models, Duration, Incidence, and Job Search
      J65 Unemployment Insurance; Severance Pay; Plant Closings

Geographic Coverage: Brazil

Time Period(s): 2002 – 2010 (Main data window for analysis samples)

Data Type(s): program source code; survey data

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Published Versions

V1 [2021-07-20]

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