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Public Sector Wage Gaps over the Long-Run: Evidence from Panel Administrative Data

Author

Listed:
  • Bargain, Olivier

    (Université Montesquieu Bordeaux IV)

  • Etienne, Audrey

    (Aix-Marseille University)

  • Melly, Blaise

    (Brown University)

Abstract

With the increase in national debts, pay freezes are imposed for several years in the public sector of some countries, at the risk of decreasing the quality of public services. Since public wage setting policies should account for relevant comparisons with the private sector, we provide novel evidence on the public sector wage gap throughout the wage distribution in France, taking a long-term perspective. We exploit a long administrative panel dataset (1988-2013) and suggest methodological innovations. We estimate the public sector premia/penalties on the unconditional wage distribution while accounting for quantile-specific fixed effects and a jackknife correction for the potential incidental parameter bias. We find that the public wage gap is broadly negative in France, with larger penalties at the top, which contribute to a compression of the wage distribution by the public sector. We show that this compression effect is partly concealed by the incidental parameter bias. Time changes in the wage gap over 25 years are consistently explained by a mix of political and business cycles. The unobserved skill gap between sectors reveals the extent of positive selection into public jobs. It tends to decline in the 1990s, a period characterized by the growth of public employment and a move towards less selective recruitment schemes. More critically, it totally disappears among top earners in the recent period, suggesting the detrimental effect of nominal wage freeze and the absence of performance-based remuneration among public sector executives.

Suggested Citation

  • Bargain, Olivier & Etienne, Audrey & Melly, Blaise, 2018. "Public Sector Wage Gaps over the Long-Run: Evidence from Panel Administrative Data," IZA Discussion Papers 11924, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp11924
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    References listed on IDEAS

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    Cited by:

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    2. Rattsø, Jørn & Stokke, Hildegunn E., 2020. "Private-public wage gap and return to experience: Role of geography, gender and education," Regional Science and Urban Economics, Elsevier, vol. 84(C).
    3. Gindling, T.H. & Hasnain, Zahid & Newhouse, David & Shi, Rong, 2020. "Are public sector workers in developing countries overpaid? Evidence from a new global dataset," World Development, Elsevier, vol. 126(C).
    4. Bonaccolto-Töpfer, Marina & Castagnetti, Carolina & Prümer, Stephanie, 2022. "Understanding the public-private sector wage gap in Germany: New evidence from a Fixed Effects quantile Approach∗," Economic Modelling, Elsevier, vol. 116(C).
    5. Bonaccolto-Töpfer, Marina & Castagnetti, Carolina & Prümer, Stephanie, 2021. "Does it pay to go public? Understanding the public-private sector wage gap in Germany," Discussion Papers 116, Friedrich-Alexander University Erlangen-Nuremberg, Chair of Labour and Regional Economics.
    6. Carolina Castagnetti & Luisa Rosti & Marina Töpfer, 2019. "The Public-Private Sector Wage Differential Across Gender in Italy: a New Quantile-Based Decomposition Approach," Economics Bulletin, AccessEcon, vol. 39(4), pages 2533-2539.
    7. Jørn Rattsø & Hildegunn E Stokke, 2022. "Public sector wage compression and wage inequality: Gender and geographic heterogeneity," Working Paper Series 19522, Department of Economics, Norwegian University of Science and Technology.
    8. Martina Pons & Blaise Melly, 2022. "Stata commands to estimate quantile regression with panel and grouped data," Swiss Stata Conference 2022 05, Stata Users Group.

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    More about this item

    Keywords

    public wage gap; unconditional quantile regression; fixed effects; incidental parameter bias; jackknife;
    All these keywords.

    JEL classification:

    • 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

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