Abstract
This thesis studies an otherwise scarcely studied, but increasingly relevant, topic of pensions. Specifically, the purpose of this master’s thesis is to investigate the gender pension gap in Denmark based on Danish administrative data on the full population. The contribution of this paper is twofold in an academic perspective. Firstly, using linear regression analysis, it examines which explanatory factors are relevant in determining the gender pension gap to obtain a well-specified model. Secondly, an Oaxaca-Blinder decomposition is applied, which is commonly used in wage studies, but scarcely seen in pension studies in Denmark. The decomposition attributes part of the Danish gender pension gap to differences in observable characteristics, and part to an unexplained effect, which is referred to as discrimination. The main finding of this thesis is that the significant gender pension gap in Denmark can in large be attributed to discrimination. It was found that marital status and educational level are significant determinants of the unexplained component. Especially, married females increase the unexplained gender pension gap, which could be driven by unobservable explanations, such as cultural and gender norms. Highly educated females also receive less pension income than what they should in a non-discriminatory setting, enlarging the gender pension gap. In addition, it was found that Danish females on average are overrepresented in many characteristics. Females dominate industrial sectors relating to administration and service, while males dominate managerial sectors, which in part can explain why there are gender differences in pension income in Denmark. Yet, whether the gender pension gap in Denmark is due to actual discrimination or other unexplained effects, such as life choices and the design of the Danish pension system, is difficult to establish, and it is likely that both have some degree of influence.
Educations | MSc in Applied Economics and Finance, (Graduate Programme) Final Thesis |
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Language | English |
Publication date | 2021 |
Number of pages | 134 |
Supervisors | Katja Mann |