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

Ebru Çaglayan Akay and Fulden Komuryakan ()
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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

Journal of Economy Culture and Society, 2021, vol. 64, issue 64, 257-277

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.

Keywords: Mincer wage equation; wage inequality; conditional quantile regression; unconditional quantile regression; Turkey (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:ist:iujecs:v:64:y:2021:i:0:p:257-277

DOI: 10.26650/JECS2021-865861

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