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The Informal Sector Wage Gap: New Evidence using Quantile Estimations on Panel Data

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  • Olivier Bargain

    (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique, IZA - Institute for the Study of Labor)

  • Prudence Kwenda

    (WITS - University of the Witwatersrand [Johannesburg])

Abstract

We estimate the informal-formal sector pay gap throughout the conditional wage distribution using panel data from Brazil, Mexico and South Africa. We control for time-invariant unobservables and identification is stemming from inter-sector movers. We control for observables in a non-linear way using propensity score reweighting and carefully check for potential measurement errors. Using similar definitions of informality, we obtain consistent results for all three countries: Informally employed workers earn much less than formal workers primarily because of lower observable and unobservable skills. Estimates of the conditional wage gap show that they are also underpaid compared to their formal sector counterparts. In all three countries, the informal wage penalty is larger in the lower part of the conditional distribution and tends to disappear at the top, i.e., the informal sector increases wage dispersion. The magnitudes of these effects vary across countries, with the largest penalties in lower conditional quantiles of South Africa and more modest wage gaps in Latin America. We suggest explanations in line with different legal and labor market conditions.

Suggested Citation

  • Olivier Bargain & Prudence Kwenda, 2013. "The Informal Sector Wage Gap: New Evidence using Quantile Estimations on Panel Data," Working Papers halshs-00967324, HAL.
  • Handle: RePEc:hal:wpaper:halshs-00967324
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    More about this item

    Keywords

    wage gap; fixed effects; propensity score; conditional random effects; informal sector; quantile regression;
    All these keywords.

    JEL classification:

    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • J23 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Demand
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • O17 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Formal and Informal Sectors; Shadow Economy; Institutional Arrangements

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