Hence, it is also common to measure gender gaps by comparing earnings for the individuals at the median or middle of the earnings distribution. 57, 662688. The results document that economic freedom positively affects the gender pay gap. Table 3), they do not associate strongly with societal affluence (GDP), so they cannot account for GEP (cf. Table 3. The results from this study are shown in the chart. Sociol. The societal affluence effect on the gender gap in STEM preferences and choices, i.e., GEP, has theoretically been explained by greater economic opportunities for gender-essentialist self-expression in more advanced societies (Charles and Bradley, 2002, 2009). Gender pay-gaps. 2 McDaniel, 2016, p. 124). New York: Cambridge University Press. Multilevel regressions of 15-year-old students' intentions to study math rather than language in 60 countries from PISA 2012 display that the economic opportunity/need mechanism does not hold at the micro level. The Gender-Equality Paradox (GEP) describes the phenomenon that the gender gap in the preference for and choice of science, technology, engineering, and mathematics (STEM) majors is larger in more affluent and gender-egalitarian societies. The main independent micro-level variable in my analysis is household wealth. The previous discussion focused on particularly aspects one by one. Human Res. (2008). Eur. For each specification, Blau and Kahn (2017) perform regression analyses on data from the PSID (the Michigan Panel Study of Income Dynamics), which includes information on labor-market experience and considers men and women ages 25-64 who were full-time, non-farm, wage and salary workers. In 2010, unionization and education show negative values; this reflects the fact that women have surpassed men in educational attainment, and unionization in the US has been in general decline with a greater effect on men. Higher-educated families, for example, are wealthier but also hold more egalitarian gender-role attitudes (Boehnke, 2011). This study tests (a) whether household wealth is associated with a greater male-favorable gender gap in student's math intentions, (b) whether this association, if any, is different in size and shape in more affluent and less affluent countries, and (c) whether household wealth can account for GEP regarding math intentions. This larger gap is due to weaker math intentions among girls and stronger math intentions among boys from the poorest wealth decile. The findings are inconsistent. Yet, the change in the coefficient is small and for boys even smaller (cf. Analysis of Binary Data. 111, 19101949. Although household wealth is higher in more affluent countries, if household wealth is not associated with a greater gender gap in math intentions, it cannot explain why in more affluent countries, the gender gap in these math intentions is generally higher. For workers without a college degree, the within-establishment gap is not a significant contributor to the change in the earnings gap over time. The second point is crucial to understand the gender pay gap: the gap is a statistic that changes during the life of a worker. In poorer contexts, on the other hand, women have to forego gender-essentialist attitudes out of economic need and more often opt for the financially more lucrative STEM pathways. They have fully accounted for GEP regarding students' math intentions by stronger math gender stereotypes in more affluent societies. Similarly, household wealth is not unrelated to boys' math intentions (H1b) but is positively associated with it.7 Still, the effects of household wealth are small: a one standard deviation change in household wealth raises math intentions for boys and girls by less than one percentage point. On the contrary, when the gap is calculated after accounting for underlying differences in education, experience, etc., then the result is the adjusted pay gap. This definition largely overlaps with a measure of OECD membership.5 I do not use the Human Development Index (HDI) as a societal affluence measure, as some scholars do (e.g., Charles, 2017), since this factor is less clearly related to the economic opportunity argument. These are unstandardized. Our World in Data is free and accessible for everyone. 64, 6790. How big is the US gender pay gap? In these more prosperous conditions, people willcongruent with Inglehart's theory of post-materialistic value orientations (Inglehart and Welzel, 2005)aspire stronger to (gendered) self-realization. A. A hike would be likely to directly affect almost six million employees in Germany. The economic opportunity explanation argues that with greater economic development, men and women have more individual-level economic opportunities to make choices in line with their gender-essentialist attitudes. The set of three maps here, taken from the World Development Report (2012), shows that today gender pay differences are much better explained by occupation than by education. Rev. 1. IV Evidence from IVF Treatments. In developing, less affluent countries, only children from the richest households differ from the rest by displaying a greater gender gap in math intentions (H2b). (We explore the ILO data above.) The regressions in Table 2 also display that the gender gap in math intentions is unaffected by household wealth. HDI includes per capita income, life expectancy, and national educational levels. A cross-national study of sex segregation in higher education. GEP has theoretically been explained by greater economic opportunities for gender-essentialist self-expression in more advanced societies, yet this explanation lacks a proper test on the individual level. Does gender equality cause gender differences in values? Yet, the difference in the gap is not large, a 6 percentage point gap in the richest deciles and a 4 to 5 percentage point gap in other deciles. The gender pay gap for full-time employees in 2016 was 9.4%. Barinaga, M. (1994). doi: 10.1177/0956797617741719, Traynor, A., and Raykov, T. (2013). unobservable worker characteristics that cannot be controlled for in a regression), while the explained factors may themselves be vehicles of discrimination. Given this outcome and the fact that we do not have school-level hypotheses, we proceeded with the more parsimonious two-level models (students nested within countries). Marriage bars: Discrimination against married women workers, 1920s to 1950s. Figure 1A plots estimated girls' and boys' math intentions by household wealth deciles, where higher deciles are coded to be wealthier (average marginal effects, where we controlled for all other variables). Figures 2AD display that this finding, the insignificant effect of household wealth on the gender gap in math intentions, also shows separately for less affluent and affluent countries. The proportion of women is lower the higher you look up the income distribution. Descriptive statistics (N = 60 countries, N = 273,833 students). 20, 165180. Goldin, C., & Rouse, C. (2000). 362, eaas9899. The gender pay gap across countries and over time, Representation of women in senior managerial positions, Representation of women at the top of the income distribution, Representation of women in low-paying jobs, Multidimensional indices of gender inequality. On this front there is again a great deal of evidence in support of the so-called motherhood penalty. Available online at: http://siteresources.worldbank.org/INTWDR2012/Resources/7778105-1299699968583/7786210-1315936222006/Complete-Report.pdf. 's interpretation can be doubted since their measure of gender stereotypes is not an independent measure (it is obtained from the students themselves and concerns math attitudes, just as the dependent variable analyzed), potentially biased (students assessing the extent their parents believe that math is important for their career), and not assessed with proper multilevel analyses techniques (mostly their analyses are on the country level).1. Pathways to science and engineering bachelor's degrees for men and women. And fourth, the green bars grew substantially in the 1980s, but stayed fairly constant thereafter. For example, maternity leave coverage can contribute by raising womens retention over the period of childbirth, which in turn raises womens wages through the maintenance of work experience and job tenure.21, Similarly, early education and childcare can increase the labor force participation of women and reduce gender pay gaps by alleviating the unpaid care work undertaken by mothers.22, Additionally, the experience of womens historical advance in specific professions (e.g. But this was not the case for men with children, nor the case for women without children. In this case male and female pseudo-job-seekers were given similar CVs to apply for jobs waiting on tables at the same set of restaurants in Philadelphia. These two processes may have offsetting effects on offspring's math and STEM orientation: wealth may decrease girls' math/STEM preferences, and egalitarian gender-role attitudes may increase these preferences. Nat. In May 2023, Frontiers adopted a new reporting platform to be Counter 5 compliant, in line with industry standards. World Bank Publications. Multilevel regressions of boys' and girls' intentions to study math rather than language display evidence against the micro-level hypotheses derived from the economic opportunity/need explanation. Age, grade level, and math test scores are control variables in the analyses. Indeed, since differences in education partly contribute to explain differences in wages, it is common to distinguish between unadjusted and adjusted pay differences. Sociol. gender wage gap, in many industrialized countries, systemic differences between the average wages or salaries of men and those of women. The gender wage gap is often measured as the difference between average earnings of men and average earnings of women expressed as a percentage of average earnings of men. Notwithstanding, it is questionable whether the presumed positive association of household wealth with the gender gap in math intentions is functionally the same in each context. The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/feduc.2023.1155492/full#supplementary-material. Equal Pay Day is based on average pay for all women, as compared to average pay for all men. One of the most important economic trends of the late 20th century was the dramatic increase in the number of women entering the paid labour force. You can read more about this in our blog post dedicated to answer the question How well do innate gender differences explain the gender pay gap?. This pattern of household wealth effects does not differ between more affluent and less affluent countries, and household wealth cannot account for GEP regarding math intentions. Econ. In addition, multilevel linear regressions provide less biased estimates of cross-level interactions than logistic variants (ibid.). Children from poorer households may disproportionally aspire to such studies, a pattern we cannot study with our data. For example, family-friendly labor-market policies that lead to higher labor-force attachment and salaries for women, will raise the returns to womens investment in education so women in future generations will be more likely to invest in education, which will also help narrow gender gaps in labor market outcomes down the line.25. Modernization, Cultural Change, and Democracy: The Human Development Sequence. (2021). by Dave Makichuk March 10, 2020. ), Comparisons of averages can often be misleading because averages are very sensitive to extreme data points. Available online here. You have the permission to use, distribute, and reproduce these in any medium, provided the source and authors are credited. Contexts. doi: 10.1353/jhr.2008.0030, PubMed Abstract | CrossRef Full Text | Google Scholar, Blasko, Z., Pokropek, A., and Sikora, J. Social norms and culture remain at the heart of family choices and the gender distribution of labor. They tested the effect of family income on the choice of female-dominated majors and observed no effect of family income net of ability measures. This means the observable characteristics of workers and their jobs explain wage differences better today than a couple of decades ago. Above we show that there are large gender gaps in land ownership across low-income countries. The implication is that observing differences in pay between men and women is neither necessary nor sufficient to prove discrimination in the workplace. First, the unadjustedgender pay gap in the US shrunk over this period. Charles and colleagues observed a larger gender gap in math aspirations and STEM graduation in economically more developed countries (Charles and Bradley, 2009; Charles, 2011, 2017; Charles et al., 2014). Stoet and Geary, 2018) is remarkable because of greater gender equality in economic and political opportunities and rights in more developed countries and more egalitarian gender-role attitudes. (This map from the World Development Report (2012) provides a more fine-grained overview of different property regimes operating in different countries.). Future studies, therefore, may investigate the distinct pathways by which parents of higher social origin influence offspring's math and STEM preferences. So, rather than reflect greater equality, the lower wage gaps observed in some countries could indicate that only women with certain characteristics for instance, with no husband or children are entering the workforce. When the gender pay gap is calculated by comparing all male workers to all female workers irrespective of differences along these additional dimensions the result is the raw or unadjusted pay gap. And, globally, only about 18% of firms have a female manager. In particular, over the last couple of decades most high-income countries have seen sizeable reductions in the gender pay gap. Thus, working for an exporting firm is associated with closing almost a fifth of the observed gender wage gap. less government spending, stronger trade liberalization conditions and levels of corruption lead to higher gaps; stronger legal and property rights and a sounder money system have no . Thus, I expect that in both affluent and less affluent countries, the association of household wealth with the gender gap in math intentions is positive but with a functionally different form. Only among the children from the poorest families may an economic need exist to prefer STEM pathways. Girls' and boys' math intentions only weakly increase over household wealth deciles, and they do so to the same extent (Figure 1A), so the gender gap in math intentions hardly changes over wealth deciles (Figure 1B). This is because more non-STEM jobs often pay below acceptable living conditions (unfortunately, there is no data on STEM vs. non-STEM wages in developing countries). Women are greatly under-represented in top income groups they make up much less than 50% across each of the nine countries. The Journal of Economic Perspectives, 12(1), 137-156. doi: 10.1525/sop.2009.52.2.211, Maltese, A. V., and Tai, R. H. (2011). For example, if we consider that more educated people tend to have higher earnings, it is natural to expect that the narrowing of the pay gap across the world can be partly explained by the fact that women have been catching up with men in terms of educational attainment, in particular years of schooling. Factors that influence persistence in science and engineering career aspirations. doi: 10.1126/science.aas9899, Fors Connolly, F., Goossen, M., and Hjerm, M. (2020). The American Economic Review, 104(4), 1091-1119. Values closer to 100% reflect a lower gap. Within-establishment and between-establishment gaps affect different types of workers differently. In this chart we can also see that the unexplained residual has gone down. Schwab Foundation for Social Entrepreneurship, Centre for the Fourth Industrial Revolution, A 5,000-year-old history of the gender gap, It will take another 136 years to close the global gender gap, Gender gap: This is how we can build an equal economic recovery. Our World In Data is a project of the Global Change Data Lab, a registered charity in England and Wales (Charity Number 1186433). Heisig and Schaeffer, 2019). The latest edition of our research report, " The Simple Truth about the Gender Pay Gap ," presents the facts about the pay gap between women and men . This so-called Gender-Equality Paradox (GEP; cf. The Human Development Report produced by the UN includes a composite index that captures gender inequalities across several dimensions, including economic status. Educ. Studies have shown the 'motherhood penalty' makes up 80% of the gender pay gap. The chart shows the percentage of men and women who report borrowing any money in the past 12 months to start, operate, or expand a farm or business. Math test scores are particularly important to control because they associate positively with the intention to study harder in math and also associate with parental wealth (Xie et al., 2015). We explain the decline in hourly earnings, which is often referred to as the motherhood penalty, by women moving to lower-paid jobs that are closer to home.. By tracking womens fertility and employment status through detailed periodic surveys, these researchers were able to establish that women who had a successful in vitro fertilization treatment, ended up having lower earnings down the line than similar women who, by chance, were unsuccessfully treated. By this measure, the gender wage gap is expressed as a percent (median earnings of women as share of median earnings of men) and it is always positive. 121, 168183. In addition, in these contexts, there may be family pressure on girls to pursue STEM as a safe option in terms of career choice (Marsh et al., 2021, p. 180181). Cent. Interestingly, this chart also shows that in Eastern Europe there was important progress in the period 1950-1980, but there was a reversal after the fall of the Soviet Union. This would mean that in the adjusted specification, we would see that occupation and industry are important contributing factors but that is precisely because discrimination is embedded in occupational differences! The second question regarding this study's outcomes is how to explain GEP when economic opportunity at the individual level is not the responsible mechanism. 2017. The scatter plot here shows available ILO estimates on the gender pay gap (vertical axis) vs GDP per capita (on a logarithmic scale along the horizontal axis). In contrast, the evidence does suggest that social norms and culture, which in turn affect preferences, behaviour and incentives to foster specific skills, are key factors in understanding gender differences in labor force participation and wages. Available online here. Paris: PISA, OECD Publishing, OECD (2014b). Sociol. B., and Bosker, R. J. The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. In most countries the gender pay gap has decreased in the last couple of decades. Supplementary Table A4 for a country list). I obtained this measure from Breda et al. The gender wage gap, as measured by women's share of men's hourly wages at the median, ranges from 74.8 percent (in Wyoming) to 92.9 percent (in Washington, D.C.; Figure O).
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