nep-gen New Economics Papers
on Gender
Issue of 2019‒06‒10
four papers chosen by
Jan Sauermann
Stockholms universitet

  1. It’s not just for boys! Understanding Gender Differences in STEM By Judith M. Delaney; Paul J. Devereux
  2. Gender Differences in Competitiveness: Experimental Evidence from China By Carlsson, Fredrik; Lampi, Elina; Martinsson, Peter; Yang, Xiaojun
  3. Inequality and the Economic Participation of Women in Sub-Saharan Africa: An Empirical Investigation By Simplice A. Asongu; Nicholas M. Odhiambo
  4. Accumulation of Human and Market Capital in the United States, 1975-2012: An Analysis by Gender By Barbara M. Fraumeni; Michael S. Christian

  1. By: Judith M. Delaney; Paul J. Devereux
    Abstract: While education levels of women have increased dramatically relative to men, women are still greatly underrepresented in Science, Technology, Engineering, and Mathematics (STEM) college programmes. We use unique data on preference rankings for all secondary school students who apply for college in Ireland and detailed information on school subjects and grades to decompose the sources of the gender gap in STEM. We find that, of the 22 percentage points raw gap, about 13 percentage points is explained by differential subject choices and grades in secondary school. Subject choices are more important than grades -- we estimate male comparative advantage in STEM (as measured by subject grades) explains about 3 percentage points of the gender gap. Additionally, differences in overall achievement between girls and boys have a negligible effect. Strikingly, there remains a gender gap of 9 percentage points even for persons who have identical preparation at the end of secondary schooling (in terms of both subjects studied and grades achieved); however, this gap is only 4 percentage points for STEM-ready students. We find that gender gaps are smaller among high-achieving students and for students who go to school in more affluent areas. There is no gender gap in science (the large gaps are in engineering and technology), and we also find a smaller gender gap when we include nursing degrees in STEM, showing that the definition of STEM used is an important determinant of the conclusions reached.
    Keywords: Education levels; Science, Technology, Engineering, and Mathematics (STEM); Gender gap; Subject choices; Gender differences
    JEL: I20 I23
    Date: 2019–02
  2. By: Carlsson, Fredrik (Department of Economics, School of Business, Economics and Law, Göteborg University); Lampi, Elina (Department of Economics, School of Business, Economics and Law, Göteborg University); Martinsson, Peter (Department of Economics, School of Business, Economics and Law, Göteborg University); Yang, Xiaojun (School of Public Policy and Administration, Xi’an Jiaotong University, Xi’an, China)
    Abstract: Experimental evidence from both the lab and the field shows that women on average have a lower propensity to enter a competitive environment. In this paper, we investigate gender differences in competitiveness using a lab-in-the-field experiment and a subject pool consisting of Chinese adults. China provides an interesting environment to study in this regard since the country has promoted gender equality for a long time and the gender gap in earnings is small in a cross-country comparison. However, in many respects, China is still a patriarchal society. Our experimental results show that women perform equally well as men in a piece-rate task and significantly better in a competitive payment environment. Despite this, men are more than twice as likely to voluntarily choose a competitive environment. This gender difference cannot be explained by differences in risk preferences or overconfidence.
    Keywords: Competition; Gender Difference; Experiments; China
    JEL: C91 D03 D10 I31 P30
    Date: 2019–06
  3. By: Simplice A. Asongu (Yaoundé/Cameroon); Nicholas M. Odhiambo (Pretoria, South Africa)
    Abstract: This study investigates the effect of inequality on female employment in 42 countries in sub-Saharan Africa for the period 2004-2014. Three inequality indicators are used, namely, the: Gini coefficient, Atkinson index and Palma ratio. Two indicators of gender inclusion are also employed, namely: female employment and female unemployment rates. The empirical analysis is based on the Generalised Method of Moments (GMM).The following main findings are established. First, inequality increases female unemployment in regressions based on the Palma ratio. Second, from the robustness checks, inequality reduces female employment within the frameworks of the Gini coefficient and Palma ratio.
    Keywords: Africa; Gender; Inclusive development
    JEL: G20 I10 I32 O40 O55
    Date: 2019–01
  4. By: Barbara M. Fraumeni; Michael S. Christian
    Abstract: This paper covers a continuous and longer time period than previously possible to examine human and market capital because of research by Christian (2017). This paper focuses on the presentation and analysis of trends in human capital by gender. During 1975-2012 there were significant changes in participation by women, the wage gender gap, and educational attainment and time in household production by both women and men. Both the market and nonmarket sectors will be covered as well as multifactor productivity with and without human capital. (A previous paper (Fraumeni, et al. 2017) described the national income accounting system which underlies both this paper and the much earlier paper by Jorgenson and Fraumeni (1989).) New insights will be gained by looking in detail at the 1975-2012 time period.
    JEL: J16 J22 J24 O47
    Date: 2019–05

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