An Analysis of Vertical Mismatch of College Graduates in Central Java in 2025 from a Gender Perspective Using a Multinomial Logistic Regression
DOI:
https://doi.org/10.36456/jstat.vol19.no1.a11635Keywords:
Vertical Mismatch, Gender, Multinomial Logistic Regression, Average Marginal EffectAbstract
Vertical mismatch is a condition in which an individual's level of education does not match the qualifications of the job being undertaken. Although various studies have examined the factors affecting vertical mismatch, empirical evidence regarding gender differences in college graduates at the provincial level is still limited, especially in Central Java Province. This research offers novelty by examining gender differences in match status, overeducation, and undereducation at the provincial level using multinomial logistic regression and Average Marginal Effects (AME). This research aims to analyze the effect of gender on the vertical mismatch of college graduates in Central Java Province in 2025. The data used were Sakernas microdata in 2025. The sample was 4,100 college graduates who worked in Central Java Province. The data analysis was carried out using multinomial logistic regression and AME. The research results showed that overeducation was the most dominant form of vertical maladjustment. Gender had a significant effect on the probability of an individual being in each category of vertical nonconformity. The AME results showed that women had a lower probability of experiencing overeducation of 16.11%, a higher probability of being in a match condition of 14.43%, and a higher probability of experiencing undereducation of 1.68% compared to men. These findings can provide input for universities and policymakers in strengthening the link between higher education and labor market needs by considering gender differences.
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