Gender Diversity in Economics Summer School : Program content

by Raquel Fernández

This course focuses on cultural change and gender. It discusses the role of culture, focusing on female labor force participation, fertility, and human capital investment. Cultural practices related to the family affect decision-making within the family and interact with policy. Diverse forces, including new policies and technologies, have led family institutions and culture to change.

Structure

• Focus on Cultural Change and Gender
• How culture shapes female labor force participation, fertility and human capital investment
• How diverse forces, including new policies and technologies, have led family institutions and culture to change

Selected key references

• Bau N. & Fernández R., 2021, The Family as a Social Institution, CEPR Discussion Paper No. 16263.
• Fernández R., 2007, “Women, Work, and Culture”, Journal of the European Economic Association, 5(2-3), pp 305-332.
• Fernández R., 2014, “Women’s rights and development”, Journal of Economic Growth, 19, pp 37-80.
• Fernández R., Parsa S. & Viarengo M., 2024, “Coming out in America: AIDS, Politics, and Cultural Change”, Journal of Law, Economics and Organization.
• Fernández R. & Parsa S, 2022, “Gay Politics Goes Mainstream: Democrats, Republicans and Same-sex Relationships”, Economica, 89, pp 86-109.

by Elena Stancanelli

Women are still under-represented in economics, and especially so among full professors. Role model interventions are general effective in attracting more women into economics, but they are not sufficient to redress the gender balance in economics. How can economics be made more inclusive and gender diverse?

Structure

• Why are women under-represented in economics?
• Why do female speakers at economics seminars tend to receive patronising questions?
• Why does the inclusion of more women in academic committees not improve the promotion chances of female candidates?

Selected key references

• Bagues M., Sylos Labini M. & Zinovyeva N., 2017, “Does the Gender Composition of Scientific Committees Matter”, American Economic Review, 107 (4), pp 1207-1238.
• Dupas P., Sasser Modestino A., Niederle M., Wolfers J. & The Seminar Dynamics Collective, 2021., Gender and the Dynamics of Economics Seminars, NBER WP No. 28494.
• Lundberg S., 2022, “Gender Economics and the Meaning of Discrimination”, American Economic Association Papers and Proceedings, 112, pp 588-91.
• Porter C. & Serra D., 2020, “Gender Differences in the Choice of Major: The Importance of Female Role Models”, American Economic Journal: Applied Economics, 12(3), pp 226-254.
• Stevenson B. & Zlotnik H., 2018, “Representations of Men and Women in Introductory Economics Textbooks”, American Economic Association Papers and Proceedings, 108, pp 180-85.
• Wu A., 2018, “Gendered Language on the Economics Job Market Rumors Forum”, American Economic Association Papers and Proceedings, 108, pp 175-179.

by Elena Stancanelli

This course will present the concepts and practice of the gendered allocation of time, which is at the roots of gender biases and inequality. Conceptual and measurement issues in the economics of time allocation will be tackled. Time Use Diaries, which are the unique data tool to measure the hours devoted to paid work, unpaid domestic work, parental time, and leisure time will be illustrated with an application for the American Time Use Survey.

Structure

• The gendered allocation of time
• How to measure (unpaid) household work and childcare?
• What are the pros and cons of time diaries?
• An application with the American Time Use Survey

Selected key references

• Kabatek J., Stancanelli E. & Van Soest A., 2014, “Income taxation, labour supply and housework: a discrete choice model for French couples”, Labour Economics, 27, pp 30-43.
• Ramey V., 2009, “Time Spent in Home Production in the 20^th Century: New Estimates from Old Data”, The Journal of Economic History, 69(1), pp 1-47.
• Stancanelli E. & Van Soest A., 2012, “Retirement and Home Production: A Regression Discontinuity approach”, American Economic Review, ,102(3), pp 600-605.
• Stancanelli E. & Van Soest A., 2016, “Partners’ Leisure Time Truly Together Upon Retirement”, IZA J Labor Policy, 5(12).

by Thomas Breda

This course will provide a general overview on the extent of gender inequality in the labour market, its evolution over the past decades and its main possible determinants. Starting from a description of unconditional and conditional gender wage gaps in various countries, it will discuss in turn the possible causes of these gaps: discrimination, segregation across occupations and firms, working time and career trajectories around child birth, differences in preferences or “psychological traits”, etc. Existing and possible policy interventions will finally be discussed along with their justification.

Structure

• Overview of gender inequality at work across countries and time
• Review of possible explanations
• General discussion of possible policy intervention

Selected key references

• Blau F. D. & Kahn L. M., 2000, “Gender differences in pay”, Journal of Economic Perspectives, 14(4), pp 75-99.
• Blau F. D. & Kahn L. M., 1992, “The gender earnings gap: learning from international comparisons”, The American Economic Review, 82(2), pp 533-538.
• Blau F. D. & Kahn L. M., 2020, “The gender pay gap: Have women gone as far as they can?”, Inequality in the United States: A Reader, pp 345-362.
• Breda T., Dutronc-Postel P., Parraud J. S. & Tô M., 2021, Gender pay gaps within companies, IPP Policy Brief n°68.
• Goldin C., 2014, “A Grand Gender Convergence: Its Last Chapter”, American Economic Review, 104(4), pp 1091-1119.

by Thomas Breda

Fewer women than men specialize in Science Technology, Engineering and Mathematics (STEM) fields. Why women do not enter math-intensive fields such as physics or computer science? Is this due to underlying discrimination, or to gender differences in academic performance, or to differences in educational choices made by students earlier on? What is the role of gender norms in explaining these facts?

Structure

• Why should we care about the underrepresentation of women in STEM?
• Are women particularly discriminated against in STEM careers (in and outside academia)?
• Have women and men different abilities for math and science? When do these differences
• emerge and can they explain differences in educational choices?
• Do female and male students of similar abilities make different educational choices and why
• is this the case?
• What are the possible policies to foster female participation in STEM?

Selected key reference

• Breda T., Grenet J., Monnet M. & Van Effenterre C., “Do female role models reduce the gender gap in science? Evidence from French high schools”, Economic Journal, forthcoming.
• Breda T. & Hillion M., 2016, “Teaching accreditation exams reveal grading biases favor women in male-dominated disciplines in France”, Science, 353(6298), pp 474-478.
• Breda T., Jouini E., & Napp C., 2018, “Societal inequalities amplify gender gaps in math”, Science, 359(6381), pp 1219-1220.
• Breda T., Jouini E., Napp C. & Thebault G., 2020, Gender stereotypes can explain the gender-equality paradox, Proceedings of the National Academy of Sciences.
• Breda T. & Napp C., 2019, Girls’ comparative advantage in reading can largely explain the gender gap in math-related fields, Proceedings of the National Academy of Sciences.
• Ceci S. J., Ginther D. K., Kahn S. & Williams W. M., 2014, “Women in academic science: A changing landscape”, Psychological science in the public interest, 15(3), pp 75-141.

by Anne Boring

Student evaluations of teaching (SET) are used widely in decisions about hiring, promoting, and firing instructors. Measuring teaching effectiveness is difficult – for students, faculty, and administrators alike. Universities generally treat SET as if they primarily measure teaching effectiveness or teaching quality. While it may seem natural to think that students’ answers to questions like “How effective was the instructor?” measure teaching effectiveness, it is not a foregone conclusion that they do. Indeed, the best evidence so far shows that they do not: they have biases that are stronger than any connection they might have with effectiveness.

Structure

• How SET are affected by gender biases and stereotypes
• How the bias varies by discipline and by student gender, among other things
• Why it is not possible to adjust for the bias, because it depends on so many factors
• How to design survey experiments

Selected key references

• Boring A. & Philippe A., 2021, “Reducing discrimination in the field: Evidence from an awareness raising intervention targeting gender biases in student evaluations of teaching”, Journal of Public Economics, 193, 104323.
• Boring A., 2017, “Gender biases in student evaluations of teaching”, Journal of Public Economics, 145, pp 27-41.
• Boring A., Ottoboni K. & Stark P., 2016, Student evaluations of teaching (mostly) do not measure teaching effectiveness, ScienceOpen Research.

by Elena Stancanelli

Gender stereotypes cause behaviours which impede gender equality. There is solid evidence of gender stereotypes significantly affecting behaviours of all population groups. Stereotypical behaviours and judgemental biases may have significant adverse consequences for the trajectories of women and LGBTQI people in the labour market and behind. How effective are gender quotas to break gender stereotypes and biases?

Structure

• How to detect, measure, and change (implicit) gender biases?
• Why are women and other minority “punished” harsher than the average man for similar “mistakes”?
• Do gender quotas impact change? What are their pros and cons?  

Selected key references

• Abbate N. et al., 2024, “Discrimination Against Gay and Transgender People in Latin America: A Correspondence Study in the Rental Housing Market”, Labour Economics, 87.
• Avitzour E. et al., 2020, On the Origins of Gender-Biased Behavior: The Role of Explicit and Implicit Stereotypes, NBER Working Paper No. w27818.
• Bagues M. et al., 2015, “Does the Gender Composition of Scientific Committees Matter?”, American Economic Review, 107(4), pp 1207-38.
• Bertrand M. et al., 2019, “Breaking the Glass Ceiling? The Effect of Board Quotas on Female Labour Market Outcomes in Norway”, The Review of Economic Studies, 86(1), pp 191-239.
• Egan M. et al., 2022, “When Harry Fired Sally: The Double Standard in Punishing Misconduct”, Journal of Political Economy, 130(5), pp 1184-1248.
• Moreau N., Stancanelli E. & Van Soest A., 2024, A Vignette Study of Gender Biases in Couples, mimeo.
• Sarsons H., 2024, Interpreting Signals in the Labor Market: Evidence from Medical Referrals, mimeo.

by Anne Boring

Many organizations have implemented Diversity, Equity, and Inclusion (DEI) policies aimed at fostering inclusive, equitable workplaces. These initiatives often include diversity training, inclusive hiring practices, and equitable pay structures. However, some studies find that some DEI initiatives may not yield the desired outcomes and can even backfire. Do workers support these policies?

Structure

• Gender and negotiations: from “Women don´t ask” to gender differences in negotiation
• Laboratory methods: how to use the laboratory elicitation to study gender and negotiation
• Ambiguity: key element to understand gender differences in negotiation
• Usual suspects: risk preferences, confidence and stereotypes

Selected key references

• Azmat G. & Boring A., 2020, “Gender Diversity in Firms”, Oxford Review of Economic Policy, 36(4), pp 760-782.
• Boring A. & Delfgaauw J., 2024, “Social desirability bias in attitudes towards sexism and DEI policies in the workplace”, Journal of Economic Behavior & Organization, 225, pp 465-482.
• Aksoy B., Carpenter C. & Sansone D., 2024, “Understanding labor market discrimination against transgender people: Evidence from a double list experiment and a survey”, Management Science, 0(0).
• Chang E.H. et al., 2019, “The mixed effects of online diversity training”, Proceedings of the National Academy of Sciences, 116(16), pp 7778-7783.
• Dobbin F. & Kalev A., 2016, “Why diversity programs fail”, Behavioral science, 94(7).
• Dobbin F. & Kalev A., 2022, Getting to Diversity: What Works and What Doesn’t, Harvard University Press.

by Elena Stancanelli

Gender Based Violence (GBV) encompasses physical and verbal violence, including harassment, as well as cyberviolence and bullying. One of the most studied forms of GBV is Domestic Violence, also known as Intimate Partner Violence (IPV), which sadly entails high feminicide rates. The economics costs of GBV are huge for the targets as well as for society. Yet often GBV targets do not report GBV to the police/the authorities. Retaliation, backlash, and institutional failure to address GBV are salient. What is the role of policing?

Structure

• The economic costs of GBV
• Why do the targets do not report to the police?
• How to counter backlash and retaliations?
• What is the role of policing in preventing feminicides?
• Should we have more female police officers? 

Selected key references

• Amaral S. et al., 2023, Deterrence or Backlash? Arrests and the Dynamics of Domestic Violence, NBER Working Paper 30855.
• Bhalotra S. et al., 2021, Job displacement, unemployment benefits and domestic violence, CEPR Discussion Paper 16350.
• Miller A. R. & Carmit S., 2019, “Do Female Officers Improve Law Enforcement Quality?”, The Review of Economic Studies, 86, 5(310), pp 2220-2247.
• Rees D., Sabia J. & Kumpas G., 2020, Anti-Bullying Laws and Suicidal Behaviors among Teenagers, NBER Working Paper 26777.
• Stancanelli E., 2024, Terrorism, Crime, and Policing, mimeo.