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Cognitive, Non-Cognitive Skills and Gender Wage Gaps: Evidence from Linked Employer-Employee Data in Bangladesh

Author

Listed:
  • Christophe Nordman

    (IRD, UMR 225 DIAL, PSL, Université Paris Dauphine, LEDa)

  • Leopold R. Sarr

    (The World Bank, South Asia Human Development Unit, Washington DC, USA)

  • Smriti Sharma

    (UNU-WIDER, Helsinki, Finland)

Abstract

(english) We use a first-hand linked employer-employee dataset representing the formal sector of Bangladesh to explain gender wage gaps by the inclusion of measures of cognitive skills and personality traits. Our results show that while cognitive skills are important in determining mean wages, personality traits have little explanatory power. However, quantile regressions indicate that personality traits do matter in certain parts of the conditional wage distribution, especially for wages of females. Cognitive skills as measured by reading and numeracy also confer different benefits across the wage distribution to females and males respectively. Quantile decompositions indicate that these skills and traits reduce the unexplained gender gap, mainly in the upper parts of the wage distribution. Finally, results suggest that employers place greater consideration on observables such as academic background and prior work experience, and may also make assumptions about the existence of sex-specific skills of their workers, which could then widen the within-firm gender wage gap. _________________________________ (français) A partir de données liées employeurs-employés de première main couvrant le secteur formel du Bangladesh, nous expliquons l'écart salarial de genre en introduisant des mesures des compétences cognitives et des traits de personnalité des employés. Tandis que les compétences cognitives s'avèrent être d'importants déterminants des salaires lorsque ceux-ci sont observés au point moyen, les traits de personnalité présentent en revanche à ce niveau peu de pouvoir explicatif. Néanmoins, l'emploi de régressions quantiles sur les salaires indiquent que ces traits de personnalité jouent à certains endroits de la distribution conditionnelle, en particulier lorsqu'il s'agit des salaires des femmes. Les compétences cognitives, approchées par des scores en lecture et en calcul des salariés, montrent elles aussi des effets différenciés selon le sexe le long de la distribution des salaires. Des décompositions en quantile indiquent ensuite que ces compétences et traits de personnalité réduisent la part inexpliquée de l'écart salarial de genre, et ce principalement dans la partie haute de la distribution des salaires. Enfin, les résultats suggèrent que les employeurs privilégieraient davantage dans leurs pratiques de recrutement et politique salariale l'acquis scolaire et l’expérience professionnelle antérieure. Ils ont aussi tendance à faire usage de stéréotypes sur l'existence de compétences spécifiques selon le sexe des salariés, ce qui a tendance à creuser l'écart salarial de genre au sein même de l'entreprise.

Suggested Citation

  • Christophe Nordman & Leopold R. Sarr & Smriti Sharma, 2015. "Cognitive, Non-Cognitive Skills and Gender Wage Gaps: Evidence from Linked Employer-Employee Data in Bangladesh," Working Papers DT/2015/19, DIAL (Développement, Institutions et Mondialisation).
  • Handle: RePEc:dia:wpaper:dt201519
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    3. Rami Galal & Mona Said & Susan Joekes & Mina Sami, 2018. "Gender Diversity, Productivity, and Wages in Egyptian Firms," Working Papers 1207, Economic Research Forum, revised 12 Jun 2018.
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    More about this item

    Keywords

    gender wage gap; cognitive skills; personality traits; matched worker-firm data; quantile decompositions; Bangladesh;
    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
    • J71 - Labor and Demographic Economics - - Labor Discrimination - - - Hiring and Firing
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • O12 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Microeconomic Analyses of Economic Development

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