nep-gen New Economics Papers
on Gender
Issue of 2022‒11‒28
ten papers chosen by
Jan Sauermann
Institutet för Arbetsmarknads- och Utbildningspolitisk Utvärdering

  1. Gender norms, violence and adolescent girls' trajectories: evidence from a field experiment in India By Alison Andrew; Sonya Krutikova; Gabriela Smarrelli; Hemlata Verma
  2. Measuring Gender Differences in Personalities through Natural Language in the Labor Force: Application of the 5-Factor Model By Dania Eugenidis; David Lenz
  3. Explaining gender differences in migrant sorting: evidence from Canada-US migration By Escamilla Guerrero, David; Lepistö, Miko; Minns, Chris
  4. Gender inequalities at work in Southern Europe By Ren, Yijun; Guglielmi, Alessandra; Maestripieri, Lara
  5. Addressing gender disparities in education and employment: A necessary step for achieving sustainable development in the Caribbean By Abdulkadri, Abdullahi; John-Aloye, Samantha; Mkrtchyan, Iskuhi; Gonzales, Candice; Johnson, Shari; Floyd, Shirelle
  6. Infrastructure and Girls’ Education: Bicycles, Roads, and the Gender Education Gap in India By Moritz Seebacher
  7. The Critical Role of Social Leaders in the Spread of Social Movements against Gender-Based Violence on Twitter By Britta Rude
  8. Violence against women at work By Abi Adams-Prassl; Kristiina Huttunen; Emily Nix; Ning Zhang
  9. Gender gaps in STEM occupations in Costa Rica, El Salvador and Mexico By David Cuberes; Florencia Saravia; Marc Teignier
  10. Gender, Sex, and the Constraints of Machine Learning Methods By Lockhart, Jeffrey W

  1. By: Alison Andrew; Sonya Krutikova; Gabriela Smarrelli; Hemlata Verma
    Abstract: Striking gender gaps persist in fundamental aspects of human welfare. In India, the setting of this paper, these gaps are particularly large. Interventions often target adolescent girls with the aim of empowering them to make choices that go against the status quo - to remain in school longer or marry later, for example. This approach may inadvertently expose girls, who are often marginalized within their communities, to new risks if it encourages them to violate prevailing gender norms. In this study, we design an experiment to compare the effectiveness of targeting only adolescent girls with an approach that additionally engages with the enforcers of gender norms in the wider community. We find that both arms of the trial led to a reduction in school dropout and early marriage. We see large improvements in girls' mental health but only in the arm which engages with the wider community. Improvements in mental health can be explained by community engagement causing gender norms to become more progressive and causing a reduction in the severity of sanctions that girls face for breaking norms. Both adolescent girls and their mothers perceived these shifts in norms and sanctions. Our results demonstrate that in settings where unequal outcomes are sustained through restrictive gender norms, change in the attitudes and behavior of the enforcers of these norms is critical for achieving meaningful improvements in womens well-being.
    Date: 2022–09–08
  2. By: Dania Eugenidis (Justus Liebig University Giessen); David Lenz (Justus Liebig University Giessen)
    Abstract: Gender stereotypes still play a major role in the perception and representation of people in the workplace. Measuring the effects of those stereotypes quantitatively is very hard though. Traditional methods, such as questionnaires, struggle to provide the full picture, for example through misunderstanding, omission or incorrect answering of questions. However, evidence-based policy making requires accurate indicators of gender inequalities to promote equality. We present a framework measuring gender stereotypes on company level using publicly available big data. Specifically, we analyse the one million websites of all German companies using natural language processing with regard to differences in their portrayal of genders through the use of certain terms. We then contextualize the gender stereotype measures following the personality traits of the Five Factor Model and their sublevels. Statistical analysis of the results indicates significant stereotypes within personality traits for large portions of the sample. The qualitative differences in gender presentation are mostly consistent with those found in the literature, which serves as a validation for the presented framework. The presented approach complements traditional quantitative measurement techniques by capturing a mainly latent level of inequality. The fully automated and comprehensive analysis of the linguistic portrayal of gender stereotypes in a corporate context is at low cost, with little delay and at a granular basis.
    Date: 2022
  3. By: Escamilla Guerrero, David; Lepistö, Miko; Minns, Chris
    Abstract: This paper uses newly digitized border crossing records from the early 20th century to study the destination choice of female and male French Canadian migrants to the United States. Immigrant sorting across destinations was strikingly different between women and men. Absolute returns to skill dominate in explaining sorting among men, while job search costs and access to ethnic networks were more important for single women. Married women were typically tied to a spouse whose labour market opportunities determined the joint destination, and were much less responsive to destination characteristics as a result.
    Keywords: migration; sorting; gender; Canada; United States
    JEL: J61 N31 N32
    Date: 2022–11–03
  4. By: Ren, Yijun; Guglielmi, Alessandra; Maestripieri, Lara
    Abstract: Despite a long-term trend towards reduction, the gender gap in employment keeps standing in Southern Europe. Numerous potential causes have been individuated, such as the household configuration, the human capital of the women, or the institutions that regulate the labour market. Less is know about the role of the locality. This paper explores what covariates influence women’s access to labour markets, and whether it is unevenly distributed across different countries and regions in the Southern Europe. The analysis is based on the dataset round 9 (2018) from the European Social Survey. We focus on the following countries available in the dataset: Cyprus, Italy, Spain and Portugal. Italy and Spain are further differentiated into vulnerable and affluent regions according to the regional GDP in 2018. We apply a regression model for the binary response that is the indicator of having been doing paid work for the last seven days of each individual in the sample. We adopt the Bayesian approach, in order to derive conclusions via a whole probability distribution, i.e., the posterior of all parameters, given data. The statistical goal is the selection of the most important covariates for access to labour market, focusing on gender differences. Our analysis finds out that the individual characteristics are mediated by household composition. Even though a higher education increases women’s employment, the presence of children and having an employed partner reduce such involvement. Moreover, a larger gender gap is detected in vulnerable regions rather than in affluent ones, especially in Italy.
    Date: 2022–11–03
  5. By: Abdulkadri, Abdullahi; John-Aloye, Samantha; Mkrtchyan, Iskuhi; Gonzales, Candice; Johnson, Shari; Floyd, Shirelle
    Abstract: Considering the vital importance of gender equality to development and the specific promise of the 2030 Agenda for Sustainable Development to leave no one behind, girls and boys should be provided with equal opportunities to achieve their fullest potential as promoted in specific Sustainable Development Goals (SDGs) and related targets. Noting that the 2020–2029 decade has been termed the “Decade of Action” for sustainable development, there is the need for the Caribbean to urgently address its human capital development challenge even as the subregion deals with many economic, social, and environmental challenges facing it as small island developing States (SIDS). In this study, we examine data on school enrolment and academic performance to discern any gender disparity in access to education and academic performance of students.
    Date: 2022–09–21
  6. By: Moritz Seebacher
    Abstract: How can infrastructure help to reduce the gender education gap in developing countries? In this paper, I analyze the complementarity of all-weather roads and a bicycle program in Bihar, India, which aimed to increase girls’ secondary school enrollment rate. Using Indian household survey data combined with a quadrupledifference estimation strategy, I find that the program’s main beneficiaries are girls living at least 3km away from secondary schools whose villages are connected with all-weather roads. Their net secondary school enrollment rate increased by over 87 percent, reducing the respective gender education gap by around 45 percent. I find no effect for girls living in villages without an all-weather road, suggesting that allweather roads are not just complementary to the bicycle program but a precondition for its success. The findings highlight the importance of well-functioning infrastructure for the accessibility of secondary schools and the empowering of girls in India.
    Keywords: Roads, bicycles, infrastructure, girls’ education, gender education gap, India
    JEL: I21 I28 H42 J16
    Date: 2022
  7. By: Britta Rude
    Abstract: This paper asks how social movements against gender-based violence (GBV) spread on Twitter. To this end, I construct a novel dataset measuring 10 large social movements against GBV on Twitter. I show that these movements start suddenly and fade out quickly and that there is considerable variation at the sub-national level in the US. Twitter users are more likely to share content created by other users instead of creating original content. Text mining the text of tweets reveals that polarization is low and that most users express fear and sadness. Neither polarized nor emotional content does generate more traction in form of likes, retweets, replies or quotes. I develop a novel instrumental variable strategy and show that Twitter users with an established network play a major role in the spread of tweets. An analysis of users’ profile pictures and names reveals low social inclusiveness of these movements. Users are on average female, young, and White. Tweets posted by non-white users generate less traction. Moreover, women are more prone to reference content by women, while the reverse applies to men.
    Keywords: Economics of gender, non-labor discrimination, demographic economics, public policy, social choice, clubs, committees, associations, economic sociology
    JEL: J16 J18 D71 Z13
    Date: 2022
  8. By: Abi Adams-Prassl; Kristiina Huttunen; Emily Nix; Ning Zhang
    Abstract: Between-colleague conflicts are common. We link every police report in Finland to administrative data to identify assaults between colleagues, and economic outcomes for victims, perpetrators, and firms. We document large, persistent labor market impacts of between colleague violence on victims and perpetrators. Male perpetrators experience substantially weaker consequences after attacking women compared to men. Perpetrators’ economic power in male-female violence partly explains this asymmetry. Male-female violence causes a decline in women at the firm. There is no change in within-network hiring, ruling out supplyside explanations via "whisper networks". Only male-managed firms lose women. Female managers do one important thing differently: fire perpetrators.
    Date: 2022–07–13
  9. By: David Cuberes (Clark University); Florencia Saravia (Universitat de Barcelona); Marc Teignier (Universitat de Barcelona and BEAT)
    Abstract: This paper documents the existence of significant gender gaps in STEM occupations in Costa Rica, El Salvador, and Mexico and estimates the aggregate costs associated with these gaps in Mexico. For Mexico we calibrate and simulate a version of the general equilibrium occupational choice model of Hsieh et al. (2019) to estimate the output losses associated with these differences since 1992. We find that if barriers in STEM occupations were eliminated aggregate output would have been between 1% and 10% larger, depending on the year. If female-specific social norms were also eliminated, the rise in aggregate output would be between 1.4% and 14%. For comparison purposes, we also compute the gains of eliminating all the distortions in high-skilled occupations as well as in all occupations. We find that aggregate output would rise between 16.5% and 3.6% in the former group of occupations and between 36.7% and 12% in the latter.
    Keywords: Talent misallocation, STEM occupations, aggregate productivity.
    JEL: E2 J21 J24 O40
    Date: 2022
  10. By: Lockhart, Jeffrey W (University of Chicago)
    Abstract: Machine learning interacts with gender and sex in myriad ways, intentionally, unintentionally, and sometimes even against practitioner's concerted efforts. Some of these interactions are born out of the allure of a seemingly simple, unambiguous, binary, variable ideally aligned with the technical needs and sensibilities of ML. Most of the time, gender lurks in ML systems without any explicit invitation, simply because these systems mine data for associations, and gendered associations are ubiquitous. And in a growing body of work, scholars are using ML to actively interrogate gender and sexuality, in turn shaping what they mean and how we think about them. Machine learning brings with it new paradigms of quantitative reasoning which hold the potential to either reinscribe or revolutionize gender in not only technical systems, but scientific knowledge as well. Throughout, the key is for people in and around machine learning to pay close attention to what the technology is actually doing with gender and sex.
    Date: 2022–11–03

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