Female Causes
What Same-Sex Adoption Laws Can Tell Us About the Gender Wage Gap in the United States
John Levendis & Aaron Lowen
Journal of Family and Economic Issues, June 2023, Pages 473–489
Abstract:
Gender wage gaps are frequently explained as resulting from direct discrimination, employers’ preferences over personality traits, and differing labor force attachment. We rely on a natural quasi-experiment using exogenous changes in state-level, same-sex adoption laws to distinguish between the competing explanations of the gender wage gap. Estimates from a differences-in-differences model show the wage gap between lesbians and heterosexual women shrank or inverted in those states which legalized adoption by same-sex couples. The wage gap did not change for men. This supports the parenthood hypothesis as a viable explanation for a portion of the gender wage gap.
Locked-in at Home: The Gender Difference in Analyst Forecasts after the COVID-19 School Closures
Mengqiao Du
Journal of Accounting and Economics, forthcoming
Abstract:
This paper explores the shock of school closures caused by the COVID-19 pandemic to study the effect of childcare responsibilities on analyst forecasts. With manually collected data on whether analysts have children, I find that female analysts with children (mother analysts) are less likely to issue timely forecasts after school closures, compared to male analysts with children (father analysts). Mother analysts’ forecasts also become less accurate after school closures, but the negative effect only exists among forecasts for firms with relatively low institutional ownership, suggesting that mother analysts prioritize maintaining the forecast accuracy for firms that are more important to their careers. Additionally, mother analysts shift forecast release times to avoid childcare hours. My findings imply that childcare responsibilities hurt the productivity of mother analysts more than that of father analysts, even though these women have established themselves in a competitive industry.
Exploring Gender Bias in Six Key Domains of Academic Science: An Adversarial Collaboration
Stephen Ceci, Shulamit Kahn & Wendy Williams
Psychological Science in the Public Interest, forthcoming
Abstract:
We synthesized the vast, contradictory scholarly literature on gender bias in academic science from 2000 to 2020. In the most prestigious journals and media outlets, which influence many people’s opinions about sexism, bias is frequently portrayed as an omnipresent factor limiting women’s progress in the tenure-track academy. Claims and counterclaims regarding the presence or absence of sexism span a range of evaluation contexts. Our approach relied on a combination of meta-analysis and analytic dissection. We evaluated the empirical evidence for gender bias in six key contexts in the tenure-track academy: (a) tenure-track hiring, (b) grant funding, (c) teaching ratings, (d) journal acceptances, (e) salaries, and (f) recommendation letters. We also explored the gender gap in a seventh area, journal productivity, because it can moderate bias in other contexts. We focused on these specific domains, in which sexism has most often been alleged to be pervasive, because they represent important types of evaluation, and the extensive research corpus within these domains provides sufficient quantitative data for comprehensive analysis. Contrary to the omnipresent claims of sexism in these domains appearing in top journals and the media, our findings show that tenure-track women are at parity with tenure-track men in three domains (grant funding, journal acceptances, and recommendation letters) and are advantaged over men in a fourth domain (hiring). For teaching ratings and salaries, we found evidence of bias against women; although gender gaps in salary were much smaller than often claimed, they were nevertheless concerning. Even in the four domains in which we failed to find evidence of sexism disadvantaging women, we nevertheless acknowledge that broad societal structural factors may still impede women’s advancement in academic science. Given the substantial resources directed toward reducing gender bias in academic science, it is imperative to develop a clear understanding of when and where such efforts are justified and of how resources can best be directed to mitigate sexism when and where it exists.
Non-College Occupations, Workplace Routinization, and the Gender Gap in College Enrollment
Amanda Chuan & Weilong Zhang
Michigan State University Working Paper, April 2023
Abstract:
This paper explores how non-college occupations contributed to the gender gap in college enrollment, where women overtook men in college-going. Using instrumental variation from routinization, we show that the decline of routine-intensive occupations displaced the non-college occupations of women, raising female enrollment. Embedding this instrumental variation into a dynamic Roy model, we find that routinization decreased returns to the non-college occupations of women, increasing their college premium. In contrast, men's non-college occupations were less susceptible to routinization. Our model estimates that workplace routinization accounted for 44% of the growth in female enrollment during 1980-2000.
Corporate Leadership and Inherited Beliefs about Gender Roles
David McLean, Christo Pirinsky & Mengxin Zhao
Journal of Financial and Quantitative Analysis, forthcoming
Abstract:
Some U.S. firms have women directors and executives, while many do not. We seek to explain this heterogeneity. Using U.S. Census data from 1900, we find that firms in regions with populations originating from countries with more gender-egalitarian beliefs have more women executives and directors, and more women chairing important board committees. These same regions also have more women in the labor market and in STEM occupations, and lower gender-pay gaps. Our findings show that regional differences in beliefs about gender roles are persistent and have significant impacts on corporate leadership and the labor market.
Surviving Racism and Sexism: What Votes in the Television Program Survivor Reveal About Discrimination
Erin O’Mara Kunz, Jennifer Howell & Nicole Beasley
Psychological Science, forthcoming
Abstract:
We examined whether there is evidence for racial and gender bias in the voting patterns of contestants on Survivor, a reality-television zero-sum game in which contestants compete for up to 39 days to win $1 million. Among 731 contestants across 40 seasons, we found evidence of racial and gender bias at multiple stages of Survivor. Compared with men, women were more likely to be voted out of their tribe first and were less likely to make it to the individual-competition stage of the game (i.e., the “merge”). They were also less likely to win Survivor. Black, Indigenous, and people of color (BIPOC) contestants, compared with White contestants, were more likely to be voted out of their tribe first and were less likely to make it to the individual-competition stage of the game. These findings suggest a systemic bias in favor of White men and against women of color.
Gender match and negotiation: Evidence from angel investment on Shark Tank
Michael Jetter & Kieran Stockley
Empirical Economics, April 2023, Pages 1947–1977
Abstract:
Using comprehensive data of 4893 interactions from the popular television show Shark Tank, we test whether gender match with entrepreneurs correlates with investors’ likelihood to extend funding offers. We find female investors are 35% more likely to engage with female (rather than male) entrepreneurs, while less systematic gender preferences emerge for male investors. Heterogeneity analyses suggest this result remains exclusive to non-male-dominated product categories, lending support to the industry representation hypothesis. We also find it is exclusive to ventures with lower asking valuations. Estimates are robust to the inclusion of a comprehensive set of control variables (such as asking valuation, investor-, and season-fixed effects) and a range of alternative specifications.
Gender productivity gap: Does gender-equal ownership compensate for female entrepreneurs’ lack of prior industry experience?
Douwere Grekou, Jenny Watt & Horatio Morgan
Small Business Economics, April 2023, Pages 1543–1571
Abstract:
Female entrepreneurs often have less prior industry knowledge or experience than male entrepreneurs. To ameliorate the adverse consequences for business performance, they could equally co-own ventures with their experienced male peers. Using a representative sample of 183,358 new ventures in Canada, we explore this under-investigated issue by analyzing the labour productivity of women-owned and equally-owned ventures, relative to men-owned ventures, from 2006 to 2017. We also quantify the influence of the principal owners’ prior industry experience on the relative labour productivity of women-owned and equally-owned ventures. Our regression analyses show that women-owned and equally-owned ventures are 16.5% and 5.9% less productive than men-owned ventures, respectively. We also confirm that women-owned ventures realize productivity gains from having experienced female owners. Meanwhile, we find that equally-owned ventures yield productivity gains only when they comprise experienced male co-owners and inexperienced female co-owners. More generally, we contribute new evidence-based insights on the gender productivity gap and why gender-equal ownership can help.
Gender-Neutral Language and Gender Disparities
Alma Cohen et al.
Harvard Working Paper, April 2023
Abstract:
This study investigates empirically whether and how the use of gender-neutral language affects the performance of women and men in real high-stakes exams. We make use of a natural experiment in which the institute administering Israel’s standardized college admission tests amended the language used in its exams, making test language more gender neutral. We find that the change to a more gender-neutral language was associated with a significant improvement in the performance of women on quantitative questions, which meaningfully reduced the gender gap between male and female performance on these questions. However, the change did not affect female performance on verbal questions nor male performance on either quantitative or verbal questions. Our findings are consistent with the hypothesis that gendered language may introduce a "stereotype threat" that adversely affects women’s performance in tasks in which they are stereotypically perceived to underperform. Our findings have significant implications for the ongoing academic and policy discussions regarding the use and effects of gender-neutral language.
Inventor Gender and Patent Undercitation: Evidence from Causal Text Estimation
Yael Hochberg et al.
Rice University Working Paper, April 2023
Abstract:
Implementing a state-of-the-art machine learning technique for causal identification from text data, we document that patents lead-authored by female inventors are under-cited relative to their quality. For the equivalent patent with a lead female inventor, a patent with a male lead inventor would have received 28% more citations. Male lead inventors in particular tend to undercite patents with female lead inventors, while patent examiners of both genders appear to be more even-handed. Market-based measures of patent value load on the citation counts that would be predicted for a female lead inventor patent had it been lead-authored by a male, rather than on actual citation counts. The under-recognition of female-authored patents likely has implications for the allocation of talent in the economy.
Country-level gender inequality is associated with structural differences in the brains of women and men
André Zugman et al.
Proceedings of the National Academy of Sciences, 16 May 2023
Abstract:
Gender inequality across the world has been associated with a higher risk to mental health problems and lower academic achievement in women compared to men. We also know that the brain is shaped by nurturing and adverse socio-environmental experiences. Therefore, unequal exposure to harsher conditions for women compared to men in gender-unequal countries might be reflected in differences in their brain structure, and this could be the neural mechanism partly explaining women’s worse outcomes in gender-unequal countries. We examined this through a random-effects meta-analysis on cortical thickness and surface area differences between adult healthy men and women, including a meta-regression in which country-level gender inequality acted as an explanatory variable for the observed differences. A total of 139 samples from 29 different countries, totaling 7,876 MRI scans, were included. Thickness of the right hemisphere, and particularly the right caudal anterior cingulate, right medial orbitofrontal, and left lateral occipital cortex, presented no differences or even thicker regional cortices in women compared to men in gender-equal countries, reversing to thinner cortices in countries with greater gender inequality. These results point to the potentially hazardous effect of gender inequality on women’s brains and provide initial evidence for neuroscience-informed policies for gender equality.
Racial and Gender Biases in Customer Satisfaction Surveys: Evidence from a Restaurant Chain
Masoud Kamalahmadi, Qiuping Yu & Yong-Pin Zhou
University of Washington Working Paper, April 2023
Abstract:
Despite the passage of the Civil Right Act and other anti-discrimination legislation, racial and gender inequalities are ubiquitous in the workplace. Whereas previous studies have primarily focused on how employer discrimination contributes to workplace inequalities, much less is known about the role of customers in the persistence of such inequalities, especially in occupations that are female-dominated and racially-diverse. We fill this gap by exploring whether, and how, customers discriminate against service workers based on the workers' race and gender. Using a data set of 1,444,044 transactions and 257,656 customer satisfaction surveys from a full-service casual-dining restaurant chain in the U.S., we study racial and gender biases in customer rating of restaurant servers, an occupation where women hold historical majority and racial minorities have a strong presence. We find that customer ratings are biased against racial minority servers, and, interestingly, that customer ratings are biased against female servers despite their majority status in this occupation. We further show that racial biases diminish as the uncertainty about the servers' ability decreases, while gender biases may even increase. These results along with the discrimination theories in the economic and sociology literature suggest that statistical discrimination is the primary driver for racial biases, while status-based discrimination is likely to be the main driver for gender biases. Given the different underlying mechanisms, we propose tailored strategies to mitigate customer racial and gender biases.