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Expected work experience and the gender wage gap: A new human capital measure

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  • Zveglich, Joseph E.
  • van der Meulen Rodgers, Yana
  • Laviña, Editha A.

Abstract

Work experience is a key variable in earnings function estimates and wage gap decompositions. Because data on actual work experience are rare, studies commonly use proxies, such as potential experience. But potential experience is identical for all individuals of the same age and level of education, so it ignores labor market intermittency because of childbirth and child rearing—a critical omission when analyzing gender differences in earnings. This paper constructs a better proxy: expected work experience, which is the sum of the annual probabilities that an individual worked in the past. This measure can be generated using commonly available data on labor force participation rates by age and gender to gauge the probability of past work. Applying the measure to labor force survey data from the Philippines shows that conventional proxies underestimate the contribution of gender differences in work experience in explaining the gender wage gap.

Suggested Citation

  • Zveglich, Joseph E. & van der Meulen Rodgers, Yana & Laviña, Editha A., 2019. "Expected work experience and the gender wage gap: A new human capital measure," Economic Modelling, Elsevier, vol. 83(C), pages 372-383.
    • Handle: RePEc:eee:ecmode:v:83:y:2019:i:c:p:372-383
    DOI: 10.1016/j.econmod.2019.09.003
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    Cited by:

    1. Rouselle F. LAVADO & Keiko NOWACKA & David A. RAITZER & Yana van der Meulen RODGERS & Joseph E. ZVEGLICH, 2022. "COVID‐19 disparities by gender and income: Evidence from the Philippines," International Labour Review, International Labour Organization, vol. 161(1), pages 107-123, March.
    2. Kenneth A. Couch & Robert W. Fairlie & Huanan Xu, 2022. "The evolving impacts of the COVID‐19 pandemic on gender inequality in the US labor market: The COVID motherhood penalty," Economic Inquiry, Western Economic Association International, vol. 60(2), pages 485-507, April.
    3. Yana Van Der Meulen Rodgers & Joseph E. Zveglich, 2021. "Gender Differences in Access to Health Care among the Elderly: Evidence from Southeast Asia," Asian Development Review (ADR), World Scientific Publishing Co. Pte. Ltd., vol. 38(02), pages 59-92, September.
    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. Oswald-Egg, Maria Esther & Renold, Ursula, 2021. "No experience, no employment: The effect of vocational education and training work experience on labour market outcomes after higher education," Economics of Education Review, Elsevier, vol. 80(C).

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    More about this item

    Keywords

    Potential experience; Gender wage gap; Philippines; Women’s relative earnings; Wage regressions;
    All these keywords.

    JEL classification:

    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination
    • 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
    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration
    • O53 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Asia including Middle East

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