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Decomposing Gender Wage Differentials Using Quantile Regression: Evidence from the Lebanese Banking Sector

Author

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  • Abdallah Dah

    (Lebanese American University)

  • Ali Fakih

    (Lebanese American University)

Abstract

This paper investigates gender pay inequality in the labor market of a developing country. Our empirical investigation uses data derived from a sample of employees in the Lebanese banking sector for the years 2008 and 2014. Using Blinder-Oaxaca decomposition, the results reveal that the unexplained component of the gender wage gap, attributed to discrimination, represents a substantial share of the total gap. A surprising result is that the contribution of human capital to the gender wage gap is negative, suggesting that wage discrimination is the main explanation for the gap. Utilizing the Machado-Mata methodology to decompose the wage gap across the entire wage distribution, our findings indicate that the unexplained component of the raw gender wage gap is more pronounced at the low and middle ranges of the distribution. However, the explained component dominates at the top of the distribution, suggesting that earnings gaps are fully explained by observed characteristics.

Suggested Citation

  • Abdallah Dah & Ali Fakih, 2016. "Decomposing Gender Wage Differentials Using Quantile Regression: Evidence from the Lebanese Banking Sector," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 22(2), pages 171-185, May.
    • Handle: RePEc:kap:iaecre:v:22:y:2016:i:2:d:10.1007_s11294-016-9574-z
    DOI: 10.1007/s11294-016-9574-z
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