Education-Job Mismatch and Gender Wage Gap: Evidence from Recent College Graduates in Korea

This article aims to explore the gender wage gap among recent college graduates in Korea by analyzing whether educational mismatch affects the gender wage gap. Unlike much prior research in the literature, two types of educational mismatch are considered in the analysis: vertical and horizontal mismatches. The Oaxaca and Ransom-type generalized decomposition is applied to examine the gender wage gap, using data from the 2015 GOMS dataset. The case of Korea may be of particular interest for the research of educational mismatch and the gender wage gap, given that on the one hand, as social and labor policies such as affirmative action have contributed to more equal opportunities between men and women, women are getting better opportunities to access the labor market, but significant gender wage inequality still remains, and on the other hand, considering the demand-side of the labor market, a non-negligible proportion of young college graduates face educational mismatch associated with a significant wage penalty. This study finds a large proportion of recent college graduates being mismatched in education, with more than 35%. By estimating the wage returns to educational mismatch, the analysis finds evidence on the contribution of educational mismatch in determining wages, and thus a source of the gender wage gap. When the analysis is run by gender, it is found that the wage effects associated with educational mismatch differ by gender, i.e., female graduates get higher wage penalties than their male counterparts for educational mismatch. A significant gender wage gap is not explained by the differences in productive characteristics but by differences in returns. Moreover, women's greater wage penalties to educational mismatch translate into greater differences in returns among educationally mismatched workers, with the component of the gender pay gap attributed to differences in returns being greater among educationally mismatched workers.