Progress and Challenges for an Evidence-Based Gender Equality Policy: a Focus in Latin America and the Caribbean

Abstract

Women in Latin America and the Caribbean (LAC) made important progress towards labor participation in the past century. However, the labor sex gap has remained largely stable in the last 10 years. We reflect on what the remaining gaps in LAC represent. To do that, we introduce a lifecycle perspective to describe the gender gaps in the region. We show some patterns that connect the adult gender gap in labor force participation to choices early in life. Next, we collect the lessons learnt from recent policies adopted in the region, while introducing the work of the contributing authors to this numbers. We discuss the challenges remaining to design evidence-based policy. Finally, we warn researchers of challenges ahead resulting from data limitations and unconscious bias.

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Notes

  1. 1.

    The meeting was part of an initiative to support efforts to attain the Sustainable Development Goal to achieve gender equality and empower all women and girls (OECD 2018b).

  2. 2.

    Gender refers to a social construct. Gender denotes a group of behaviors that society considers appropriate for men and women. Sex denotes the biological and physiological characteristics that separate men and women defined by chromosomes. “Male” and “female” are sex categories. “Masculine” and “feminine” are gender categories.

  3. 3.

    International Labour Organization estimates are used for LFP, based on employment surveys and censuses. The estimates include people who are either employed or actively looking for a job. They also include both the formal and informal sectors, but do not include family and unpaid workers. When specific age ranges are not specified, adult LFP refers to person 25 to 64 years old. As noted in the methodological notes of ILO (2013), labor force activity among young people (15 to 24 years old) reflects the availability of educational opportunities, while labor force activity among older adults (65 and over) provides an indication of attitudes towards retirement and the existence of social safety nets. UNDESA (2017a) lists the retirement age by gender for the largest 17 countries in LAC. In the case of men, the retirement age is always between 60 and 65; for women, it is between 52 and 65. However, in more than three-quarters of LAC countries the retirement age for women is also between 60 and 65.

  4. 4.

    The worldwide statistic is a population-weighted average of all countries in the world and thus includes LAC countries. Note that LAC only represents 8.6% of the world population according to the World Bank’s 2018 World Development Indicators.

  5. 5.

    Child labor force participation as shown in Figure 2 is a proxy for the share of children ages 5 to 17 working in 2012.

  6. 6.

    The International Labour Organization does not measure child labor regularly. Typically, labor surveys do not include individuals under 15 years old, so child labor estimates from UNICEF are used here. Those estimates measure the percentage of children ages 5–17 involved in paid or unpaid labor. Children considered to be involved in child labor include the following: (1) children 5–11 years old who, during the reference week, did at least one hour of economic activity or at least 28 h of household chores; (2) children 12–14 years old who, during the reference week, did at least 14 h of economic activity or at least 28 h of household chores; (3) children 15–17 years old who, during the reference week, did at least 43 h of economic activity or household chores; and (4) children 5–17 years old in hazardous working conditions.

  7. 7.

    Figure A1.2 in Annex 1 plots the LFP gender gap by country in LAC.

  8. 8.

    Following the World Bank criteria, seven regions in the world are considered: East Asia and Pacific, Europe and Central Asia, Latin America and the Caribbean, the Middle East and North Africa, North America, South Asia, and sub-Saharan Africa. Figure A1.1 in Annex 1 shows LFP gender gap dynamics from 1990 to 2017. In addition, Table A1.1 in Annex 1 shows how the current LFP gender gap varies across different age groups. The next section contextualizes LAC gender gaps in other welfare dimensions such as education, health, and early marriage by comparing them to other regions in the world.

  9. 9.

    Calculations by the authors based on the variable proportion of time spent on unpaid domestic and care work from the World Development Indicators (World Bank 2018). Information has been collected in multiple surveys and does not necessarily correspond to the same year for each country or region.

  10. 10.

    Calculations by the authors based on the Socio-Economic Database for Latin America and the Caribbean of the Centro de Estudios, Laborales, Distributivos y Sociales (CEDLAS), Universidad Nacional de la Plata, Argentina.

  11. 11.

    An individual is considered an informal worker if he or she pertains to any of the following categories: (1) unskilled self-employed, (2) salaried worker in a small private firm, or (3) zero-income worker. In this framework, labor informality is closely related to self-employment.

  12. 12.

    The completion rate aims to capture the probability of finishing lower secondary school. It is calculated as the number of new entrants in the last grade of lower secondary education, regardless of age, divided by the population at the entrance age for the last grade of lower secondary education (World Bank 2018).

  13. 13.

    Calculations by the authors based on 2016 data from World Bank (2018).

  14. 14.

    Determinants such as exposure to crime can influence mortality. In LAC, while the female intentional homicide rate is 4.2 per 100,000 population, it is 10 times higher for men (41.6 per 100,000 population). Indicators calculated by the authors based on the United Nations Office on Drugs and Crime Database for 2015 (UNODC 2017).

  15. 15.

    Malnutrition indices have been calculated by the World Health Organization (WHO) for 2016. Note that the definition of malnutrition changes by cohort. Overweight (Underweight) for cohort 0 to 4: Weight for height is greater (lower) than +2 standard deviations. With respect to the median for the international reference population, for cohorts ages 5–9 and 10–19, Body mass index (BMI) is greater (lower) than +2 standard deviations; for cohort 18 years and older, BMI is greater than 30 (lower than 18).

  16. 16.

    According to UNICEF global databases based on Demographic and Health Surveys, Multiple indicator Cluster Surveys, and other nationally representative surveys. See UNICEF, Adolescent Health, December 2017. https://data.unicef.org/topic/maternal-health/adolescent-health/ (accessed 27 March 2019).

  17. 17.

    See UNICEF, Adolescent Health, December 2017. https://data.unicef.org/topic/maternal-health/adolescent-health/ (accessed 27 March 2019).

  18. 18.

    The case of Mexico is a curious one. Although the female early marriage rate was 23% in 2009 (World Bank 2018), early childbearing was 39% (UNICEF data for 2010). This evidence suggests that many female adolescents are single mothers. A key dimension to understanding the impact of early childbearing on female labor force participation is whether the young woman has the support of her partner, other relatives, or neither. The Mexican context seems appropriate for further research in this regard.

  19. 19.

    Interestingly, the largest progress in female LFP participation is concentrated among low-educated and married women (Figures A3.1 and A3.2 in Annex 3).

  20. 20.

    Note that outmigration plays a minor role in explaining the current LFP gap in the region. According to UNDESA (2017b), approximately 39 million country-migrants in the world come from LAC, which is equivalent to 6% of the region’s population. Among those who migrate to other countries in the Americas, 45% are women (OAS 2015).

  21. 21.

    Using the set of harmonized household surveys from the World Bank’s Global Monitoring Database, Buitrago et al. (2018) defined poor households as those whose level of per capita consumption is under US$1.90 a day (2011 purchasing power parity), which is typically the definition of an extremely poor household. Women or men are then defined as poor if they live in a poor household.

  22. 22.

    Estimates of living arrangements are from UNDESA (2017a).

  23. 23.

    However, policies to augment the provision of childcare services will not always favor female labor participation. In Chile, nurseries are mandatory in firms that employee 20 or more women (Vezza 2015), but Escobar et al. (2017) estimate that this policy reduces female employment by 1 percentage point.

  24. 24.

    An alternative approach to engaging more women in nontraditional jobs would be to adopt affirmative action policies. However, no LAC government has used this type of policy in the labor market. LAC countries have only adopted gender quotas for Congress. Since Argentina pioneered this policy in 1991, another 18 countries have followed in the region. According to the World Bank’s World Development Indicators, LAC had the highest female participation rate in terms of legislative power (23%) among world regions in 2016 – higher than in Europe (22%) and North America (19%) (World Bank 2018).

References

  1. Alzua M, Cruces G, Ripani L. Labor market equilibrium and conditional cash transfers: experimental evidence from Latin America. CEDLAS Working Paper No. 95, Centro de Estudios, Laborales, Distributivos y Sociales, Universidad de la Plata, Argentina; 2010.

  2. Arceo-Gomez EO, Campos-Vazquez RM. Race and marriage in the labor market: a discrimination correspondence study in a developing country. Am Econ Rev. 2014;104(5):376–80. https://doi.org/10.1257/aer.104.5.376.

    Article  Google Scholar 

  3. Bando R, Galiani S, Gertler P. The effects of non-contributory pensions on material and subjective wellbeing. IDB Working Paper No. IDB-WP-840, Inter-American Development Bank, Washington, DC; 2017.

  4. Barford A, Dorling D, Smith GD, Shaw M. Life expectancy: women now on top everywhere. BMJ. 2006;332:808. https://doi.org/10.1136/bmj.332.7545.808.

    Article  Google Scholar 

  5. Barro R, Lee JW. A new data set of educational attainment in the world, 1950-2010. J Dev Econ. 2013;104:184–98.

    Article  Google Scholar 

  6. Behrman JR, Parker SW, Todd PE. Do conditional cash transfers for schooling generate lasting benefits? A five-year follow-up of PROGRESA/Oportunidades. J Hum Resour. 2011;46(1):93–122.

    Article  Google Scholar 

  7. Belfield CR, Nores M, Barnett S, Schweinhart L. The high/scope Perry preschool program cost–benefit analysis using data from the age-40 follow-up. J Hum Resour. 2006;41(1):162–90.

    Article  Google Scholar 

  8. Berlinski S, Galiani S. The effect of a large expansion of pre-primary school facilities on preschool attendance and maternal employment. Labour Econ. 2007;14(3):665–80.

    Article  Google Scholar 

  9. Berthelon ME, Kruger DI. Risky behavior among youth: incapacitation effects of school on adolescent motherhood and crime in Chile. J Public Econ. 2011;95(1–2):41–53.

    Article  Google Scholar 

  10. Bettendorf LJH, Jongen ELW, Muller P. Childcare subsidies and labour supply – evidence from a Dutch reform. Labour Econ. 2015;36:112–23.

    Article  Google Scholar 

  11. Binstock G, Naslund-Hadley E. The miseducation of Latin American girls: poor schooling makes pregnancy a rational choice. IDB technical note no. IDB-TN-204, Inter-American Development Bank, Washington, DC; 2010.

  12. Blau F, Kahn D, Lawrence M. The gender wage gap: extent, trends, and explanations. J Econ Lit. 2017;55(3):789–865.

    Article  Google Scholar 

  13. Bobonis GJ, González-Brenes M, Castro R. Public transfers and domestic violence: the roles of private information and spousal control. Am Econ J Econ Pol. 2013;5(1):179–205.

    Article  Google Scholar 

  14. Buitrago P, de la Briere BL, Newhouse D, Muñoz AM, Rubiano E, Scott K, Suarez-Becerra P. Gender differences in poverty and household composition through the life-cycle: a global perspective. Policy research working paper No. 8360, World Bank, Washington, DC; 2018.

  15. Busso M, Romero Fonseca D. Determinants of female labor force participation. In: Gasparini L, Marchioni M, editors. Bridging gender gaps? The rise and deceleration of female labor force participation in Latin America. Centro de Estudios, Laborales, Distributivos y Sociales (CEDLAS), Universidad de la Plata, Argentina; 2015.

  16. Bustelo M, Martinez S, Pérez M, Rodríguez SJ. Evaluación de impacto del Proyecto Ciudad Mujer en El Salvador. Washington, DC: Inter-American Development Bank; 2016.

    Google Scholar 

  17. Cascio EU, Haider SJ, Nielsen HS. The effectiveness of policies that promote labor force participation of women with children: a collection of national studies. Labour Econ. 2015;36:64–71.

    Article  Google Scholar 

  18. Catino J, Colom A, Ruiz MJ. Equipping Mayan girls to improve their lives: transitions to adulthood. Brief No. 5, Population Council; 2011.

  19. Cianelli R, Ferrer L, McElmurry BJ. HIV prevention and low-income Chilean women: machismo, marianismo, and HIV misconceptions. Cult Health Sex. 2008;10:297–306.

    Article  Google Scholar 

  20. Cruces G, Galiani S. Fertility and female labor supply in Latin America: new causal evidence. Labour Econ. 2007;14(3):565–73.

    Article  Google Scholar 

  21. De Hoyos R, Rogers H, Székely M. Ninis en América Latina: 20 millones de jóvenes en búsqueda de oportunidades. Washington, DC: World Bank; 2016.

    Google Scholar 

  22. Economic Commission for Latin America and Caribbean (ECLAC). Sexual harassment in public spaces: the city in debt with the rights of women. Observatory for Latin America and the Caribbean briefing note. ECLAC, Santiago; 2015.

  23. Ellis J, Fosdick BK, Rasmussen C. Women 1.5 times more likely to leave STEM pipeline after calculus compared to men: lack of mathematical confidence a potential culprit. PLoS One 2016;11(7).

    Article  Google Scholar 

  24. Escobar Loza F, Martínez Wilde S, Mendizábal Córdova J. El impacto de la Renta Dignidad: política de redistribución del ingreso, consumo y reducción de la pobreza en hogares con personas adultas mayores. Unidad de Análisis de Políticas Sociales y Económicas (UDAPE), La Paz; 2013.

  25. Escobar D, Lafortune J, Rubini L, Tessada J. The distortionary effect of size and factor dependent policies: the role of factor substitutability in measuring the impact of a child-care subsidy policy in Chile. CAF working paper no.2017/17, Development Bank of Latin America; 2017.

  26. Galiani S, Gertler P, Bando R. Non-contributory pensions. Labour Econ. 2016;38:47–58.

    Article  Google Scholar 

  27. Gasparini L, Marchionni M. Bridging gender gaps? The rise and deceleration of female labor force participation in Latin America. Centro de Estudios, Laborales, Distributivos y Sociales (CEDLAS), Universidad de la Plata, Argentina; 2015.

  28. Gasparini L, Garganta S, Marchionni M. Cash transfers and female LFP: the case of AUH in Argentina. Working Paper, Centro de Estudios, Laborales, Distributivos y Sociales (CEDLAS), Universidad de la Plata, Argentina; 2015.

  29. Giles JW, Heyman GD. Young children's beliefs about the relationship between gender and aggressive behavior. Child Dev. 2005;76(1):107–21.

    Article  Google Scholar 

  30. Givord P, Marbot C. Does the cost of child care affect female labor market participation? An evaluation of a French reform of childcare subsidies. Labour Econ. 2015;36:99–111.

    Article  Google Scholar 

  31. Goldin C, Mitchell J. The new life cycle of women's employment: disappearing humps, sagging middles, expanding tops. J Econ Perspect. 2017;31(1):161–82.

    Article  Google Scholar 

  32. Goldin C, Rouse C. Orchestrating impartiality: the impact of blind auditions on female musicians. Am Econ Rev. 2000;90(4):715–41.

    Article  Google Scholar 

  33. Haeck C, Lefebvre P, Merrigan P. Canadian evidence on ten years of universal preschool policies: the good and the bad. Labour Econ. 2015;36:137–57.

    Article  Google Scholar 

  34. Halpern DF, Benbow CP, Geary DC, Gur RC, Hyde JS, Gernsbacher MA. The science of gender differences in science and mathematics. Psychol Sci Public Interest. 2007;8(1):1–51.

    Article  Google Scholar 

  35. Hill K, Zimmerman L, Jamison D. Mortality risks in children aged 5-14 years in low income and middle-income countries: a systematic empirical analysis. Lancet Global Health. 2015;3(10):PE609–16.

    Article  Google Scholar 

  36. Huenchan S. Ageing, solidarity and social protection in Latin America and the Caribbean. Economic Commission for the Latin America and Caribbean (ECLAC), Santiago; 2017.

  37. International Labour Organization (ILO). Social protection for older persons: key policy trends and statistics. Geneva: ILO; 2014.

    Google Scholar 

  38. International Labour Organization (ILO). Women at work: trends 2016. Geneva: ILO; 2016.

    Google Scholar 

  39. International Labour Organization (ILO). World employment social outlook: trends for women 2017. Geneva: ILO; 2017.

    Google Scholar 

  40. Jayachandran S. The roots of gender inequality in developing countries. Annual Review of Economics. 2015;7(1):63–88.

    Article  Google Scholar 

  41. Kahn, Shulamit and Ginther, Donna. 2017. “Women and STEM,” NBER Working Papers 23525, National Bureau of Economic Research, Inc

  42. Kalben B. Why men die younger: causes of mortality differences by sex. North American Actuarial Journal. 2000;4(4):83–111.

    Article  Google Scholar 

  43. Lafortune J, Perticará M, Tessada J. The benefits of diversity: peer effects in an adult training program in Chile. Working Paper, Servicio Nacional de la Mujer (SERNAM), Chile; 2018.

  44. Larraín JR, Henoch P. Cuánto ha aumentado la tasa de ocupación de las mujeres con el programa Bono al Trabajo de la Mujer? Serie Informe Social No. 161, Libertad y Desarrollo; 2016.

  45. Lim J, Meer J. The impact of teacher–student gender matches: random assignment evidence from South Korea. J Hum Resour. 2017;52(4):979–97.

    Article  Google Scholar 

  46. Martínez C, Perticará M. Childcare effects on maternal employment: evidence from Chile. J Dev Econ. 2017;126:127–37.

    Article  Google Scholar 

  47. Molinos, C. “La Ley de protección a la maternidad como incentivo de participación laboral femenina: el caso colombiano.” Coyuntura Económica 2012. XLII(1): 93–116. Bogotá, Colombia: Fedesarrollo.

  48. Muralidharan K, Sheth K. Bridging education gender gaps in developing countries: the role of female teachers. J Hum Resour. 2016;51(2):269–97.

    Article  Google Scholar 

  49. Nandi A, Behrman JE, Kinra S, Laxminarayan R. Early-life nutrition is associated positively with schooling and labor market outcomes and negatively with marriage rates at age 20–25 years: evidence from the Andhra Pradesh children and parents study (APCAPS) in India. J Nutr. 2018;148(1):140–6.

    Article  Google Scholar 

  50. Nollenberger N, Rodríguez-Planas N. Full-time universal childcare in a context of low maternal employment: quasi-experimental evidence from Spain. Labour Econ. 2015;36(C):124–36.

    Article  Google Scholar 

  51. Nussbaum MC. Creating capabilities: the human development approach. Cambridge: Harvard University Press; 2011.

    Google Scholar 

  52. Organisation for Economic Co-operation and Development (OECD). Latin America and the Caribbean – social institutions and gender index regional report. Paris: OECD; 2017. http://www.oecd.org/dev/development-gender/Brochure_SIGI_LAC_web.pdf. Accessed 26 March 2019

    Google Scholar 

  53. Organisation for Economic Co-operation and Development (OECD). PISA 2015: results in focus. Paris: OECD; 2018a.

    Google Scholar 

  54. Organisation for Economic Co-operation and Development (OECD). Global leaders and companies pledge to reduce the gender pay gap by 2030. Paris: OECD; 2018b. http://www.oecd.org/social/global-leaders-and-companies-pledge-to-reduce-the-gender-pay-gap-by-2030.htm. Accessed 6 Oct 2018

    Google Scholar 

  55. Population Council. Abriendo oportunidades: theory of change: case study – empowering girls. Theory of change case study; 2016. https://www.girlsnotbrides.org/wp-content/uploads/2016/02/Case-Study-Empower-girls-Population-Council-Guatemala.pdf. Accessed 26 March 2019.

  56. Ramírez Bustamante N, Tribin Uribe AM, Vargas CO. Maternity and labor markets: impact of legislation in Colombia. IDB Working Paper No. 583. Inter-American Development Bank, Washington, DC; 2015.

  57. Servicio Nacional de Capacitación y empleo (SENCE). Evaluación cualitativa y cuantitativa de la implementación del Programa Mujer Trabajadora Jefa de Hogar. SENCE, Chile; 2013.

  58. Sosa-Rubi S, Saavedra-Avedano B, Piras C, Van Buren J, Bautista-Arredondo S. True love: effectiveness of a school-based program to reduce dating violence among adolescents in Mexico City. Prev Sci. 2017;18(7):804–17.

    Article  Google Scholar 

  59. Teal CR, Gill AC, Green AR, Crandall S. Helping medical learners recognise and manage unconscious bias toward certain patient groups. Med Educ. 2012;46:80–8. https://doi.org/10.1111/j.1365-2923.2011.04101.x.

    Article  Google Scholar 

  60. United Nations, Department of Economic and Social Affairs, Population Division (UNDESA). Living arrangements of older persons: a report on an expanded international dataset. UNDESA; 2017a.

  61. United Nations, Department of Economic and Social Affairs, Population Division (UNDESA). Population facts no. 2017/5. UNDESA; 2017b.

  62. United Nations Development Programme (UNDP). UNDP’s gender equality seal certification Programme for public and private enterprises: Latin American companies pioneering gender equality. UNDP; 2016.

  63. United Nations Educational, Scientific and Cultural Organization (UNESCO). Comparison of results between the second and the third regional comparative and explanatory studies, SERCE and TERCE 2006-2013. UNESCO regional Bureau for Education in Latin America and the Caribbean; 2014.

  64. United Nations Office on Drugs and Crime (UNODC). United Nations Office on Drugs and Crime database. UNODC; 2017. https://dataunodc.un.org/crime/intentional-homicide-victims. Accessed 10 Aug 2017.

  65. Vezza E. Policies toward female labor force participation. In: Gasparini L, Marchioni M, editors. Bridging gender gaps? The rise and deceleration of female labor force participation in Latin America. Centro de Estudios, Laborales, Distributivos y Sociales, Universidad de la Plata; 2015.

  66. Wiig H. Gender experiments in Peru. World Development Report background paper. World Bank, Washington, DC; 2012.

  67. World Bank. World development report 2012: gender equality and development. Washington DC: World Bank; 2012.

    Google Scholar 

  68. World Bank. World development indicators. Washington, DC: World Bank; 2018. https://databank.worldbank.org/data/reports.aspx?source=wdi-database-archives- percent28beta percent29. Accessed 28 March 2019

    Google Scholar 

  69. Zarulli V, Barthold Jones J, Oksuzyan A, Lindahl-Jacobsen R, Christensen K, Vaupel JW. Women live longer than men even during crises. Proc Natl Acad Sci. 2018;115(4).

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Bando, R., Berlinski, S. & Carrasco, J.M. Progress and Challenges for an Evidence-Based Gender Equality Policy: a Focus in Latin America and the Caribbean. J Econ Race Policy 2, 187–201 (2019). https://doi.org/10.1007/s41996-019-00034-0

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Keywords

  • Gender inequality
  • Gender gaps
  • Latin America and the Caribbean

JEL Codes

  • J10
  • J16
  • J70
  • O54