The Effect of Education on Labor Wages in Iranian Urban Households Based on Quantile Regression

The purpose of this article is to examine the impact of education and work experience on earning. For this purpose, Mincer’s wage equation, quantile regression estimation method and the microdata from Iranian survey of household income and expenses in 2016 have been used. Estimation results show that education returns are positive in all income quantiles, and education in lower-income quantiles has a stronger positive effect than in higher-income quantiles. Also, the average experience have a positive effect on the earnings of individuals, with a stronger effects in low-income quantiles than high-income quantiles. Gender coefficients show that female earnings in all income quantiles are much lower than males, but this negative effect was much bigger in lower-income quantiles, implying gender-based discrimination against women in low-income quantiles. According to Machado and Mata's decomposition, gender discrimination (against females) was estimated, -30% in the first decile, and -4.5% in the ninth decile. Women's education has narrowed the gap somewhat on behalf of women. According to the results, education efficiency in Iran is far lower than many other countries in the world. Therefore, it is necessary to reform educational structures, in particular to guide them towards labor market needs and economic benefits.