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Does Field of Study Shape the Hourly Wage Distribution? Evidence from Quantile Regression

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  • Hayriye Özgül Özkan Değirmenci

    (Muğla Sıtkı Koçman University)

Abstract

Higher education expansion in Türkiye has sharply increased the supply of bachelor’s degree graduates, yet how field of study is associated with wages across the conditional wage distribution remains insufficiently examined. Using 2024 Household Labour Force Survey microdata, this study estimates weighted conditional quantile regressions for bachelor’s degree wage workers. Fields are grouped using ISCED-F 2013, with Business and Law as the reference category. Results reveal substantial distributional heterogeneity in field-of-study wage associations. Science, Technology, Engineering, and Mathematics graduates show the largest and most distribution-sensitive conditional wage advantage, increasing from lower to upper conditional quantiles. Education graduates exhibit a hump-shaped profile peaking at Q75, while Health and Veterinary graduates show a declining association from Q10 to Q90. These patterns are consistent with differences in sectoral allocation, public-sector concentration, and institutionally structured wage-setting, but should be interpreted as conditional associations rather than causal returns. Humanities and Arts graduates do not display statistically significant wage associations at individual quantiles. Overall, the findings show that OLS estimates mask important distributional differences and support more systematic monitoring of field-specific labor market outcomes in higher education planning and career guidance.

Suggested Citation

  • Hayriye Özgül Özkan Değirmenci, 2026. "Does Field of Study Shape the Hourly Wage Distribution? Evidence from Quantile Regression," Business and Economics Research Journal, Bursa Uludag University, Faculty of Economics and Administrative Sciences, vol. 17(3), pages 377-401, July.
    • Handle: RePEc:ris:buecrj:023235
    DOI: 10.20409/berj.2026.503
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    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • I26 - Health, Education, and Welfare - - Education - - - Returns to Education
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

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