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What Do Conditional and Unconditional Quantile Regression Models Tell Us Something Different About Wage Inequality in Turkey?

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  • Ebru Çaglayan Akay

    (Marmara University, Department of Econometrics, Istanbul, Turkey)

  • Fulden Komuryakan

    (Bandirma Onyedi Eylul University, Department of Econometrics, Balikesir, Turkey)

Abstract

This study comparatively analyzes wage inequality in the Turkish labor force by estimating the generalized Mincer wage equation with quantile regression methods using the 2018 Turkish Household Budget Survey data. This is the first study on wage inequality in Turkey that includes a comparative analysis of conditional and unconditional quantile regression methods. The results indicate that conditional quantile regression estimates wage inequality to be lower than it actually is. In contrast, in unconditional quantile regression, wage inequality is higher. The results further provide evidence of wage inequality in the Turkish labor market and suggest that wage inequality is higher in low-wage segments.

Suggested Citation

  • Ebru Çaglayan Akay & Fulden Komuryakan, 2021. "What Do Conditional and Unconditional Quantile Regression Models Tell Us Something Different About Wage Inequality in Turkey?," Journal of Economy Culture and Society, Istanbul University, Faculty of Economics, vol. 64(64), pages 257-277, December.
    • Handle: RePEc:ist:iujecs:v:64:y:2021:i:0:p:257-277
    DOI: 10.26650/JECS2021-865861
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    References listed on IDEAS

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    3. Aysit Tansel & Elif Oznur Acar, 2016. "The Formal/Informal Employment Earnings Gap: Evidence from Turkey," Research on Economic Inequality, in: Inequality after the 20th Century: Papers from the Sixth ECINEQ Meeting, volume 24, pages 121-154, Emerald Group Publishing Limited.
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