1. Women, work, and gender roles in Latin America Hugo Ñopo Washington, Dec. 6 2011

2. Fact 1: The schooling gap reversed Source: Duryea et al. (2004)

3. Fact 1: The schooling gap reversed  For those born by 1940: 6 vs. 5 years of schooling, favoring boys  For those born by 1980: 9.5 vs. 9.2 years of schooling favoring girls  The improvement in female schooling occurred at the higher end of the distribution.  By 1992: 16.35% of working females and 10.66% percent of working males had some tertiary education  By 2007: 26.05% and 17.26% respectively.

4. Fact 2: FLFP ↑ while MLFP almost constant.  By the early 1990s around one-half, nowadays around two out of three women either work or are looking for a ob  Most of the increase in FLFP occurred among young married woman with no children  During the same period MLFP remained almost constant in the region.  However, males still dominate labor markets  Three out of five workers are males

5. Fact 3: Female-headship ↑  By the beginning of the 1990s females headed 1.2% of complete households (those where there are both husband and wife present) and 79.8% of single-headed households.  Nowadays that has increased to 9.2% and 82.3%.  Such new female headship occurs at both extremes of the earnings distribution  Young professionals  Low-educated single mothers

6. Fact 4: Fertility ↓ (although there is important cross-country heterogeneity)  By the beginning of the 1990s, 11% of working women lived in a household where there was at least one child (age six or younger), by 2007 such percentage almost halved.  Delays in women’s age at first child  Alleviation of household responsibilities  For countries that began demographic transition early, however, the responsibilities are shifting to the care of the elderly and the sick.

7. Fact 5: Marriage, education and work decisions have evolved.  Skilled woman are less likely to be married than:  Unskilled women and skilled man  The married skilled are less likely to work than unmarried skilled women  They are also more likely to marry a less skilled husband than in other world’s regions  When “marrying down”  They are more likely to work than when marrying at par  They marry males with better unobservables for wages Source: Hausmann et al. (2010)

8. However, women are still lagging behind men in labor earnings  The earnings gap is around 9%  However when comparing males and females with the same schooling the gap achieves 22%  For different possible comparisons the earnings gap is between 21% and 30%  The earnings gap dropped around 7pp during the last 15 years, but the unexplained component of it only 3pp

9. Results from a forthcoming book: “New Century Old Disparities. Gender and Ethnic Earnings Gaps in Latin America and the Caribbean”…

10. Evolution of the Unexplained Gender Earnings Gap (from the early 1990’s to the late 2000’s) for different Specifications

11. Unexplained Gender Earnings Gaps at different Segments of the Labor Markets

16. Unexplained Gender Wage Gaps by Percentiles of the Wage Distribution

17. Females have more schooling, but they do not earn more

18. Unexplained Gender Wage Gaps by Percentiles of the Wage Distribution

27. The gender earnings disparities are more pronounced:  In the self-employment,  In small firms,  In the informal sector  In part-time jobs  Among the poor  … → Flexibility that comes at a cost…

28. Development and Gender Inequalities Just looking at some correlations, (in levels and changes)

29. GDP per capita shows some correlation with wage differentials but not with FLFP Wage Gap (Male-Female) circa 2007FLFP in the circa 2007

30. GDP growth 1990-2010, however, is related to the reduction of gender differentials Wage Gap (Male-Female) Change along the Period FLFP Change along the Period

31. There are reasons to be optimistic  Economic development and the reduction of gender disparities have been aligned.  The speed at which gender disparities (especially those regarding earnings) have been reducing, however, call for some extra action

32. From (imperfect) data to policy What/Where to prioritize?

33. Prioritize on three (linked) areas  Culture  Discrimination, gender roles, violence against women (and the offspring) that limits FLFP  Education  The extra schooling women are getting seems to show only weak effects on the labor markets (participation and wages)  Flexibilty  There is a “part-time” penalty.  Is it because part-time could be a choice for men but not for women?

34. Culture  Gender roles (more on this later)  Intra-household violence. The fear of violence against the offspring is an important limitation for female work (Aritomi, 2010)  Good news: stigmas/stereotypes can change… and rapidly! (Duflo, 2004; Castillo et al., 2008)  Information and exposure (the “contact hypothesis”)

35. Education  Women are achieving more schooling than men  What are our kids learning in school?  Stereotyping  Gender roles  An analysis of images in 4 th and 6 th grades textbooks…

36. Females’ Visibility. How often do we see women in our kids’ textbooks?

37. Stereotypes. When we actually see them, what do they do compared to men? (4 th Grade)  In the fourth grade, proportionally more men are related to school and labor activities, and more women to domestic and leisure activities

38. Stereotypes. Are images different across subjects? (4 th Grade)  And the patterns differ by the book’s topic

39. Stereotypes. When we actually see them, what do they do compared to men? (6 th Grade)  Not much changes as kids age. Women’s images are again concentrated in “leisure” and “other” activities

40. Policies to facilitate flexible labor force participation  Child care (with the golden opportunity to work on the most profitable social investment in the long-run: ECD)  But don’t forget that our populations are also aging → Elder care  A more balanced gender split of household responsibilities  Regulation (paternity leaves)  Information

41. Thanks! hugon@iadb.org