Department Field Paper
Abstract: I quantify the importance of stigma costs against the gender wage gap in explaining the absence of married women from the workforce in India. I estimate a model of household choice where the agents make labor market decisions and allocate time between leisure and home production. Women’s market work carries a stigma cost - a disutility caused by her market work to the household - when her husband has a preference against it. I use the variation in gender norms across North and South of India to identify stigma costs. Counterfactual exercises suggest that in the absence of stigma costs, female employment rate would be higher by 7.7 percentage points in the North, a 58% improvement over the observed rate of 13.3% in 2018-19. Estimated stigma cost, and its impact on employment, is negligible in the South.
Presented at Population Association of America (PAA), 2020 (Poster Session)
Abstract: It is well established that social capital is an important contributor to economic development. In this paper, we ask if working makes individuals more socially engaged. We ask this question in the context of a group which has relatively low labour force participation-women in rural India. Using a survey of adult health and the aged in India collected by the WHO, we estimate the impact of whether a women has ever worked on self-reported social engagement. We use exogenous variation in soil texture that has been shown in the literature to affect female rural employment to undertake instrumental variable estimation. Our results show that women who have worked are more likely to have a high value on a social cohesion index that includes engagement in public meetings, meeting community leaders, attending groups, engagement with friends inside and outside the house. In particular, we find work makes women more likely to increase an especially positive aspect of social capital: one of "horizontal" social engagements (Putnam (1993)).
Abstract: I seek to extend Calvi (2020)'s analysis by replicating it on a panel dataset (Consumer Pyramid Household Survey, 2014-2024). Calvi (2020) uses a cross-sectional dataset to estimate the age-profile of resource shares for Indian women and thus cannot separately identify age effect and cohort effect. I identify the age profile of resource shares by estimating the within-household change in resource shares of women with average age of women in the household. This controls for any cohort effects. Preliminary findings suggest support for Calvi (2020)'s main result: significant reduction in resource shares is observed for women as they age.