Critical determinants of gender inequality from five different perspectives

Abstract

Gender inequality (GI) still prevails due to multi-faceted reasons. Therefore, multi-dimensional approaches to examine the root-causes of GI are necessary. In this regard, with the adoption of multi-perspectives and multi-level analyses, i.e. macro- vs. micro-analysis (OECD membership, gender, and regions), the study aims to find out the key determinants affecting GI in five different models, comprised of 17 socio-economic and institutional determinants: the capability-related model (CRM), the livelihood-related model (LRM), the formal institution-related model (FIRM), the informal institution-related model (IIRM), and the power distance model (PDM). The models drew upon related theoretical bases: neoclassical growth theory and convergence theory for the CRM; human capital theory for the LRM; cultural theory for the IIRM and PDM; and new institutionalism for the FIRM. The study utilised secondary data from 34 countries (18 OECD countries and 16 non-OECD countries). All of the data followed by OECD membership, gender, and regions were tested using regression analyses in order to compare the different impacts from various dimensions. The research findings indicated that all of the factors from the CRM, LRM, FIRM, and PDM and one factor from the IIRM (the perception that men make a better boss than women) had impacts on the macro-level analyses. As for the micro-level analyses, 16 factors other than “perception of income” of the IIRM influenced GI. Among the five models, the CRM (fertility rates) affected inequality the most. Meanwhile, the LRM (percentage of wage and salaried workers) turned out to highly significantly affect all categories. The significance of the study is that little research has been carried out on a cross-country level by introducing multi-level and multi-perspective approaches. Three policy recommendations based on the results are suggested: reforming gender-related policies reflecting dominant gender-related issues; designing economic policy to improve gender equality; and mainstreaming gender issues.