Employment Inequalities Between Central Asian Migrants and Local Residents Across the Regions of Russia: Evidence From Binary Logistic Regression
Abstract
This article examines the differences in employment probability between international migrants and native residents in Russia, with a focus on labor migrants from Central Asia. Using nationally representative microdata on working-age individuals (15–64) in Russia and applying binary logistic regression, the analysis compares the odds of being employed for Central Asian migrant workers versus native Russians. The model controls for key demographic and human capital factors (age, sex, marital status, and education). Contrary to some expectations, the results show that migrants from Central Asia exhibit equal or slightly higher odds of employment compared to natives, after accounting for other factors. The model also identifies a statistically significant gender gap in employment, with women having lower odds of employment than men after controlling for other factors. This finding suggests that migrant–native comparisons should be interpreted with caution, since aggregate results may mask important heterogeneity within the migrant population itself. Age effects follow a curvilinear pattern, with employment odds rising through middle working ages and declining at older ages. Education and marital status also show strong influences: higher educational attainment and being married are associated with significantly higher employment odds. These findings are situated within the broader literature on migrant labor market integration. While Central Asian migrants in Russia achieve high rates of employment, they are often concentrated in lower-paying and informal jobs, and gender disparities persist.
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