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Gender, Welfare and Global Economics: an Empirical Perspective

Code: 106994
Credits: 6
2026/2027
Degree programme Type Course
Sociocultural Gender Studies OP 3

Contact lecturer

Name :
María José Fuentes Vasquez
Email :
mariajose.fuentes@uab.cat

Group languages

You can consult this information at the end of the document.

Prerequisites

Although there are no formal prerequisites, it is recommended to have completed the compulsory courses Feminist Theory and Critique (106990), Principles of Gender Theory (106988), Economics and Gender Inequality (106992) and Public Policies for Equality (106970), since this course assumes mastery of the fundamental theoretical frameworks (Sen, Nussbaum, Butler, Crenshaw) covered in them and focuses on their empirical application.

Objectives

This optional fourth-year course is based on the premise that students in the Degree in Sociocultural Gender Studies arrive with a solid theoretical grounding in fundamental feminist frameworks —acquired in the degree's compulsory courses— but with few opportunities to practise critical reading of empirical evidence, identifying causal mechanisms in the specialised literature, and producing data-based diagnoses.

The core objective of the course is to provide students with empirical literacy in gender: the ability to read indicators and databases critically, to distinguish between what a piece of data measures and what it claims to represent, to identify biases and proxies, and to translate evidence into defensible arguments before non-specialist institutional audiences. This includes identifying wellbeing indicators relevant to producing reports and studies on public policy —including its budgetary and fiscal dimension— from a gender perspective, and assessing the impact and sustainability of such policies on the population's wellbeing.

Unlike the degree's compulsory courses, this course does not address feminist theory itself, nor the structural analysis of feminist economics and the labour market, nor the public policy cycle from a general institutional perspective. Its added value lies in teaching students to produce and defend a gender diagnostic report using quantitative and qualitative evidence, a transversal competence in demand at equality offices, trade unions, international organisations and public policy consultancies.

On completing the course, students will be able to: (1) critically read gender inequality indicators and recognise their methodological limitations; (2) identify, in the empirical literature, the mechanisms that explain gender gaps in the labour market, education and care work; (3) build a gender diagnostic report combining open data sources and academic literature; and (4) orally defend that diagnosis before a simulated institutional audience.

Learning outcomes

  • CM21 (Evaluate the impact and sustainability of fiscal policies on the welfare of the population from a gender perspective.) Evaluate the impact and sustainability of fiscal policies on the welfare of the population from a gender perspective.
  • KM36 (Contextualise social events and legal repercussions related to gender equality from a historical perspective.) Contextualise social events and legal repercussions related to gender equality from a historical perspective.
  • SM33 (Identify welfare indicators that support studies and reports on public policies, including the gender perspective in the preparation of budgets.) Identify welfare indicators that support studies and reports on public policies, including the gender perspective in the preparation of budgets.
  • SM35 (Produce an organised and politically correct speech, orally and in writing, in the relevant language.) Produce an organised and politically correct speech, orally and in writing, in the relevant language.

Contents

Introduction

Introduction to the course and to the toolkit for gender data analysis.

Block 1 — How is gender inequality measured?

From indicators to proxies. Nussbaum's capabilities operationalised into data. Biases in gender data. The gender category in binary statistics.

Block 2 — What does the evidence say about the labour market?

Goldin's U-shaped curve. Institutions and norms: historical evidence as a laboratory. Child penalty and the gender pay gap.

Block 3 — What does the evidence say about resources?

Education: the convergence paradox. Urban space and mobility. The feminisation of poverty.

Block 4 — What works, and how is it defended?

Care work and the double shift. Health, sport and leisure. Synthesis: effective and fiscally sustainable policies.

Closing

Preparatory tutorials, public defences before a simulated institutional audience, and the final practical exam.

Learning activities and methodology

Title Hours ECTS Learning outcomes
Theoretical classes and practical workshops in the classroom 52 2.08 KM36, SM33, SM35
Follow-up tutorials for the diagnostic report 10 0.4 CM21, SM33
Critical reading, report writing and defence preparation 68 2.72 CM21, KM36, SM33, SM35

The course combines flipped-classroom teaching (Tuesday theoretical sessions based on prior reading; Thursday practical sessions devoted to data workshops) with Project-Based Learning (PBL): students, in groups of 2–3, incrementally build a gender diagnostic report, with one mid-term submission and one final submission, accompanied by ongoing group-by-group supervision from the lecturer during practical sessions.

Critical reading of the required texts is carried out through rotating 15-minute presentations: in each theoretical session, a different group or pair presents that week's reading, opening the floor for subsequent class discussion.

As a distinctive formative activity, an institutional simulation is incorporated: the final defence of the report takes place before a role-play audience made up of classmates playing the roles of a sceptical equality officer, an elected official with no gender training, and a trade union representative, bringing the academic experience closer to real professional contexts.

This process is complemented by a final practical exam in a more conventional written format: an individual two-hour test, without the use of AI, based on the critical reading of a previously unseen institutional report.

An 80% attendance requirement is set for practical sessions, given that the diagnostic report is built incrementally in class (authorisation confirmed by the degree coordination).

Submission and exam dates are set at the start of the course and communicated to all students in the first session. These dates cannot be changed except for duly justified reasons (e.g. an official medical certificate); in such cases, students proceed directly to the corresponding resit period.

15 minutes of one class session are reserved for students to complete the teaching and course evaluation surveys.


Topics for the Diagnostic Report

Each group of 2–3 students chooses one of the following topics (a topic of their own may also be proposed, subject to the lecturer's approval within the first two weeks). Topics cannot be repeated between groups in the same year.
  1. The leisure time gap between women and men and its effects on mental health (Block 4).
  2. The child penalty in Spain: how employment changes for women and men after the first child (Block 2).
  3. Horizontal segregation in Spanish universities: why are women still underrepresented in STEM? (Block 3).
  4. The gender pay gap in Spain: how much is explained by motherhood and how much by segregation? (Block 2).
  5. The feminisation of poverty in Spain after the pandemic: profiles, mechanisms and policies (Blocks 3–4).
  6. Urban mobility and gender in Barcelona or Madrid: who is public transport designed for? (Block 3).
  7. The gender gap in sport and active leisure in Spain: time, access and health (Block 4).
  8. Unpaid care work and access to the labour market: the case of women caring for elderly relatives (Block 4).
  9. The digital gender gap in Spain: access, use and digital skills (Block 3).
  10. The impact of paternity leave on shared responsibility: evidence from Spain and the Nordic countries (Blocks 2 and 4).


Annotation: within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.

Assessment

Continuous assessment activities

Title Weight Hours ECTS Learning outcomes
Oral defence 20% 2 0.08 CM21, SM35
Critical reading presentations 20% 6 0.24 KM36, SM35
Practical workshop follow-up 10% 0 0 SM33, SM35
Final practical exam 20% 2 0.08 KM36, SM33
Gender diagnostic report 30% 10 0.4 CM21, SM33
1. Critical reading presentations (20%)
Rotating 15-minute presentations: in each theoretical session, a different group or pair presents that week's required reading, opening the floor for subsequent class discussion. This activity can only be carried out in person and cannot be rescheduled without duly justified cause. Failure to deliver the assigned presentation results in a grade of 0 for this activity.
2. Gender diagnostic report (30%)
Report produced in groups of 2–3 students over the semester through Project-Based Learning, with one mid-term submission and one final submission, accompanied by ongoing supervision from the lecturer during practical sessions. Submission dates are communicated at the start of the course and cannot be changed except for duly justified cause.
3. Oral defence (20%)
Public defence of the report before a simulated institutional audience (sceptical equality officer, elected official with no gender training, trade union representative), assessed individually within the group. This activity is not eligible for resit.
4. Final practical exam (20%)
Individual written test, 2 hours, without the use of AI, based on the critical reading of a previously unseen institutional report. Same format as practised in the course's critical reading presentations.
5. Practical workshop follow-up (10%)
The lecturer's assessment of each student's work and progress within their group throughout the practical sessions (Thursdays). This activity is not eligible for resit.


Use of Artificial Intelligence

During the course, Model 2 (restricted use) is permitted: students may use generative AI as support for literature searches, language correction or translation, always identifying the AI-generated parts, specifying the tools used, and including a critical reflection on their use. Lack of transparency results in a grade of 0 for the corresponding activity.
In the final practical exam, Model 1 (prohibited) applies: no use of generative AI tools is permitted. Any such use results in a non-recoverable grade of 0 for academic dishonesty.


Bibliography

Required readings by session

  • S2 — Cot, A. et al. (2020). "Gender gaps in urban mobility". Humanities and Social Sciences Communications, 7. (~10 pp., open access)
  • S3 — Nussbaum, M. (2000). Women and Human Development. Cambridge: CUP. Ch. 1 "In Defense of Universal Values" (pp. 1–33).
  • S4 — Criado-Perez, C. (2019). Invisible Women. London: Chatto & Windus. Ch. 1 "Daily Life" (pp. 15–40).
  • S5 — Butler, J. (1990/1999). Gender Trouble. New York: Routledge. 1999 Preface (pp. vii–xxvi, ~15 pp.).
  • S6 — Goldin, C. (1994). "The U-Shaped Female Labor Force Function". NBER Working Paper 4707, pp. 1–20 (open access). + Crenshaw, K. (1989). "Demarginalizing the Intersection of Race and Sex". University of Chicago Legal Forum, pp. 139–149 (open access).
  • S7 — España-Eljaiek, I. and Fuentes-Vásquez, M.J. (forthcoming, Oct. 2026). "Left Behind Twice: Gender and Territory in Colombian Schooling". In Pathways to Equity and Access to Education in the Caribbean and Beyond. London: Routledge. Introduction + three dynamics sections + conclusion (~25 pp.; manuscript available from the lecturer; restricted use to the edited volume).
  • S8 — Blau, F. and Kahn, L. (2017). "The Gender Wage Gap: Extent, Trends, and Explanations". Journal of Economic Literature, 55(3), pp. 789–810 (sect. I–III; open access at IZA DP 9656).
  • S9 — Fuentes-Vásquez, M.J. and España-Eljaiek, I. (2023). "Coffee tastes bitter: education and the coffee economy in Colombia". European Review of Economic History, 27(2), pp. 174–190.
  • S10 — Criado-Perez, C. (2019). Invisible Women. Ch. 3 "The Long Road" (pp. 63–90).
  • S11 — Folbre, N. (1994). Who Pays for the Kids? London: Routledge. Ch. 1 "The Politics of Reproduction" (pp. 1–28).
  • S12 — Hochschild, A.R. (1989). The Second Shift. New York: Viking. Ch. 1 "Joey's Problem" (pp. 1–21).
  • S13 — Criado-Perez, C. (2019). Invisible Women. Ch. 11 "The Drugs Don't Work" (pp. 199–224).
  • S14 — Kleven, H. et al. (2019). "Child Penalties Across Countries: Evidence and Explanations". AEA Papers and Proceedings, 109, pp. 122–126 (5 pp., open access).


Suggested readings (optional, organised by session)

For those who wish to go deeper or connect the content with their dissertation. It is not necessary to read them all — each student may choose according to their topic or interest.


S2: Stiglitz, J., Sen, A. and Fitoussi, J.-P. (2009). Report on the Measurement of Economic Performance. Preface (open access). · OECD (2021). Caregiving in Crisis. Executive summary (open access). · UNDP (2023). Human Development Report. Gender statistical annex (open access). · WEF (2023). Global Gender Gap Report (open access). · Strom, K.J. (2000). "Using Hospital Emergency Room Data to Assess Intimate Violence". Journal of Research and Practice.

S3: EIGE (2023). Gender Equality Index. Methodological note (open access). · Sen, A. (1999). Development as Freedom. Ch. 8 "Women's Agency and Social Change". · Robeyns, I. (2017). Wellbeing, Freedom and Social Justice. Open Book Publishers (open access).

S4: Criado-Perez, C. (2019). Invisible Women. Introduction (pp. 1–14). · Waring, M. (1988). If Women Counted. Ch. 1 (pp. 1–30). · INE (2024). Time Use Survey 2024–2025: methodology.

S5: INE (2021). "Estadísticas para el análisis de la realidad LGTBI". Methodological note (open access). · Eurostat (2023). "Gender statistics: methodology". Statistics Explained (open access).

S6: Goldin, C. (2014). "A Grand Gender Convergence: Its Last Chapter". AER, 104(4), pp. 1091–1100. · Goldin, C. (2021). Career and Family. Princeton: PUP. · Crenshaw, K. (1989). Full text (pp. 139–168). · España-Eljaiek, I., Fuentes-Vásquez, M.J. and Gaviria-Meléndez, N.S. (2022). "El valor económico de la mujer". Tiempo & Economía, 9(2), pp. 11–46 (open access).

S7: Eterovic, D.S. and Sweet, C.M. (2014). "Democracy and Education in Twentieth-Century Latin America". Economics & Politics, 26(2), pp. 237–262. · Aidt, T.S. and Dallal, B. (2008). "Female voting power". Public Choice, 134(3), pp. 391–417.

S8: Berniell, I. et al. (2023). "Motherhood and Flexible Jobs: Evidence from Latin American Countries". World Development, 167. · Kleven, H. et al. (2019). "Children and Gender Inequality: Evidence from Denmark". AEJ: Applied Economics, 11(4), pp. 181–209.

S9: González de San Román, A. and De la Rica, S. (2012). "Gender Gaps in PISA Test Scores". IZA DP 6338 (open access). · Eurydice (2023). Towards Gender Equality in Higher Education. European Commission (open access). · Voxdev (2023). "Education during commodity booms". Outreach column (open access).

S10: Spain, D. (1992). Gendered Spaces. Ch. 1 (pp. 1–28). · Jacobs, J. (1969). The Economy of Cities. Ch. 1–2. · Kern, L. (2020). Feminist City. London: Verso. · Sánchez de Madariaga, I. (2016). "Mobility of care". In Cities and Transport. Routledge.

S11: UN Women (2020). From Insights to Action. Executive summary + sect. 1–2 (open access). · Kabeer, N. (1994). Reversed Realities. London: Verso. · World Bank (2022). Women, Business and the Law (open access).

S12: Hochschild, A.R. (1989). The Second Shift. Conclusion (pp. 259–271). · Alon, T. et al. (2020). "The Impact of COVID-19 on Gender Equality". NBER WP 26947 (open access). · OECD (2023). Society at a Glance. Chapter on time use by gender (open access).

S13: Bird, C. and Rieker, P. (2008). Gender and Health. Ch. 1 (pp. 1–26). · Spanish Ministry of Health (2023). National Health Survey of Spain: Analysis by sex (open access). · Spanish Ministry of Culture and Sport (2022). Survey on Sports Habits in Spain (open access).

S14: Esping-Andersen, G. (2009). The Incomplete Revolution. Ch. 1 "The Gender Revolution" (pp. 1–26). · ILO (2022). Care Work and Care Jobs for the Future of Decent Work (open access). · Thévenon, O. (2011). "Family Policies in OECD Countries". Population and Development Review, 37(1), pp. 57–87.

Software

Excel (basic analysis and visualisation), Datawrapper (institutional-quality visualisation), Eurostat Data Browser, INE open data portal, AMB open data. Generative AI (strategic and critical use, subject to activity-specific conditions — see corresponding section).

Course groups and languages

The information provided is provisional until November 30. After this date, you will be able to consult the language of each group through this link. To access the information, you will need to enter the course CODE

Type of teaching Group Language Semester Shift
(TE) Theory 1 Catalan/Spanish second semester morning-mixed
(PAUL) Classroom practices 1 Catalan/Spanish second semester morning-mixed