Abstract
AbstractThis study examines the effects of educational mismatch on earnings using cross‐sectional data from three rounds of the Ghana Living Standards Survey. There are gender‐earnings differentials, with women suffering a penalty for undereducation that is almost twice that paid by men for having less than the required years of education, although the premium associated with overeducation is higher for women. While the penalty associated with deficit schooling decreases for men over time, this penalty increases for women. Women but not men experience significant increases in returns for attaining the required education. On the contrary, the lack of significance of returns to overeducation over time suggests that human capital beyond the required level is unproductive and may represent a waste of public resources.
Highlights
This study examines the incidence and effects of educational mismatch on earnings in Ghana between 1998 and 2013
This study examines the effects of educational mismatch on earnings using cross-sectional data from three rounds of the Ghana Living Standards Survey
There are gender-earnings differentials, with women suffering a penalty for undereducation that is almost twice that paid by men for having less than the required years of education, the premium associated with overeducation is higher for women
Summary
This study examines the incidence and effects of educational mismatch on earnings in Ghana between 1998 and 2013. GLSS data, the realized matches method is appropriate for this analysis Using this method, the mismatch variables for the pooled sample are constructed by taking the modal value of years of completed schooling for individuals who ever attended school across the different occupations. As shown, for both men and women, the proportion of workers in jobs that match their educational attainment consistently fell. Realizing some of the limitations inherent in measuring educational mismatch using, for instance, self-reported measures, and the possibility for the representative worker to be overeducated or undereducated in some occupations, we adopt an approach as an additional measure of (mis)match that reflects the outcome of supply and demand in the labor market (Boualam, 2014). We are mindful of this caveat and refrain from making any causal claims from our findings and instead interpret all coefficients as associations
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.