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We analyze the role of education as a determinant of mental health. To do this, we leverage the age-specific exposure to an educational reform as an instrument for years of education and find that the treated cohorts gained more education. This increase in education had an effect on mental health more than 2 decades later. An extra year of education led to a lower likelihood of reporting any symptoms related to depression (11.3%) and anxiety (9.8%). More educated people also suffered less severe symptoms - depression (6.1%) and anxiety (5.6%). These protective effects are higher among women and rural residents. The effects of education on mental well-being that we document are potentially mediated through better physical health, improved health behavior and knowledge, and an increase in women's empowerment.

India's mass vaccination efforts have been slow due to high levels of vaccine hesitancy. This study uses data from an online discrete choice experiment with 1371 respondents to rigorously examine the factors shaping vaccine preference in the country. We find that vaccine efficacy, presence of side effects, protection duration, distance to vaccination centre and vaccination rates within social network play a critical role in determining vaccine demand. We apply a non-parametric model to uncover heterogeneity in the effects of these factors. We derive two novel insights from this analysis. First, even though, on average, domestically developed vaccines are preferred, around 30% of the sample favours foreign-developed vaccines. Second, vaccine preference of around 15% of the sample is highly sensitive to the presence of side effects and vaccination uptake among their peer group. These results provide insights for the ongoing policy debate around vaccine adoption in India.

Background: It is widely considered that women have less diverse diets than other household members. However, it has been challenging to establish this empirically since women’s diet diversity is measured differently from that of other household members. Objective: In this article, we compare women’s dietary diversity with that of their respective households and thereby generate a measure of “dietary gap.” Methods: We measure women’s “dietary gap” by using the difference of homogenized household and woman dietary scores (using the same scales). This is done using primary data on 3600 households from 4 districts in India. Additionally, we show the robustness of our results to variations in scale and recall periods used to construct the diet diversity scores. Results: Mean difference tests indicate that women consistently consume 0.1 to 0.5 fewer food groups relative to other household members, with the results being statistically significant at the 1% level. The food groups driving this dietary gap are nonstaples like Vitamin A-rich fruits and vegetables, meat/fish/poultry, and dairy. Conclusions: Results point toward the discrimination faced by women in the variety of the food consumed, the importance of considering comparability in creating indices of diet diversity, and the need to collect more detailed information on diets. To our knowledge, this is one of the first studies to examine dietary discrimination faced by women using common scales.

Background: Recent literature, largely from Africa, shows mixed effects of own-production on diet diversity. However, the role of own-production, relative to markets, in influencing food consumption becomes more pronounced as market integration increases. Objective: This paper investigates the relative importance of two factors - production diversity and household market integration - for the intake of a nutritious diet by women and households in rural India. Methods: Data analysis is based on primary data from an extensive agriculture-nutrition survey of 3600 Indian households that was collected in 2017. Dietary diversity scores are constructed for women and households is based on 24-hour and 7-day recall periods. Household market integration is measured as monthly household expenditure on key non-staple food groups. We measure production diversity in two ways - field-level and on-farm production diversity - in order to account for the cereal centric rice-wheat cropping system found in our study locations. The analysis is based on Ordinary Least Squares regressions where we control for a variety of village, household, and individual level covariates that affect food consumption, and village fixed effects. Robustness checks are done by way of using a Poisson regression specifications and 7-day recall period. Results: Conventional measures of field-level production diversity, like the number of crops or food groups grown, have no significant association with diet diversity. In contrast, it is on-farm production diversity (the field-level cultivation of pulses and on-farm livestock management, and kitchen gardens in the longer run) that is significantly associated with improved dietary diversity scores, thus suggesting the importance of non-staples in improving both individual and household dietary diversity. Furthermore, market purchases of non-staples like pulses and dairy products are associated with a significantly higher dietary diversity. Other significant determinants of dietary diversity include women’s literacy and awareness of nutrition. These results mostly remain robust to changes in the recall period of the diet diversity measure and the nature of the empirical specification. Conclusions: This study contributes to the scarce empirical evidence related to diets in India. Additionally, our results indicate some key intervention areas - promoting livestock rearing, strengthening households’ market integration (for purchase of non-staples) and increasing women’s awareness about nutrition. These are more impactful than raising production diversity.

In predominantly agrarian economies with limited irrigation, rainfall plays a critical role in shaping households’ incomes and subsequently their spending decisions. This study uses household-level panel data from a nationally representative survey in India to estimate the effect of agricultural productivity shocks – as proxied by exogenous annual rainfall deviations from long-term average – on education expenditures and children’s work status in rural Indian households. Our results show that a transitory increase in rainfall significantly reduces education expenditures and increases the likelihood of child labor across a range of work activities. Additionally, we show that productivity-enhancing inputs such as land ownership and credit access do not mitigate these countercyclical effects of rainfall variations, indicating the importance of market imperfections (in labor and land markets). We also find that the effects of productivity shocks are reinforced for historically marginalized castes, and moderated for more educated households. These highlight that the average effects mask considerable heterogeneity based on household and regional characteristics

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This paper contributes to the relatively scant literature on the impacts of inequality on the efficacy of public works programmes. We study this in the context of India. In particular, we examine the effect of land inequality on the implementation of the world’s largest workfare programme – the National Rural Employment Guarantee Act (NREGA). Our OLS estimates demonstrate that the concentration of land ownership reduces the efficacy of NREGA. An instrumental variable (IV) analysis, where we use the historical land tenure system as an IV for contemporaneous land inequality, further corroborates our findings. This negative relationship is consistent with the hypothesis that public work schemes raise agricultural wages in the private labour market, thereby incentivising big landlords to use their political power to oppose such programmes. We exclude the possibility that the higher provision of public jobs in more equal areas is driven by a higher demand for public jobs or by caste or religious differences. This study suggests that the concentration of land ownership, a proxy for power asymmetries, could hinder effective implementation of development policies.

I use a nationally representative dataset for Uganda to estimate the impact of marriage age on later life outcomes for women and also on their children’s health outcomes. I use plausibly exogenous variation in the age of menarche of women to instrument for their mar- riage age. A delay of one year in physical maturation of women leads to an increase of 0.45 years in their marriage age. Using age at menarche as an instrument in a Two Stage Least Squares (2SLS) framework, I find that a one year delay in marriage leads to an increase of 0.5-0.75 years of education and an increase of about 5-10 percent in the chance of being fully literate. I also find large and significant negative effects of earlier marriage on other out- comes such as labour force participation, decision making power, perceived social status, contraceptive use and spousal characteristics. Additionally, In terms of intergenerational effects of early marriage, I find significant negative effects of early marriage on the child’s hemoglobin levels, probability of being anemic and severely anemic. I also find negligible negative effects on Body Mass Index (BMI), height and weight. Using diagnostic checks and several robustness checks, I provide evidence that the instrument satisfies the inclusion and exclusion restrictions, thus raising the causal nature of the estimates.

The Multinomial Logit (MNL) model is popular, but a semi-parametric specification of its link/utility function has seldom been used in empirical applications. This is primarily because of the resource intensive nature of semi-parametric estimation. In this paper we propose and implement a parallel computation algorithm to estimate the semi-parametric kernel MNL model. This algorithm reduces model estimation time by a factor of 2–10, depending on the size of the dataset and the available resources for computation. These computational gains make the estimation of this model feasible for large datasets. Additionally, using a Monte Carlo study we show that the kernel MNL outperforms the traditional linear MNL model in terms of fit and predicted choice probabilities. We demonstrate how kernel-based specification can unearth important heterogeneities in the effect of covariates through an empirical exercise. We use data from a nationally representative household survey (N = 157,804) to analyze the factors associated with institutional births (as opposed to home births) in India. Our revealed-preference results indicate that maternal education, household assets, distance to formal health facility, and birth order play an essential role in determining birth location choice. Although the directions of impact are similar across both the linear and the kernel MNL specifications, there are significant differences in the marginal effects of different factors across the two models. These differences, which arise due to the flexibility afforded by the semi-parametric specification, potentially bring additional nuance to policy discussions.

In this paper we study the long run effects of the 1959–61 Chinese Famine on mental health outcomes. We focus on cohorts that were born during the famine and examine their mental health as adults, when they are roughly 55 years of age. We find that early-life exposure to this famine leads to a large statistically significant negative impact on women’s mental health, while there is limited effect on men. This gender differential effect is observed because male fetuses experience a stronger natural selection as compared to female fetuses, which implies that in the longer run, surviving females may exhibit larger detrimental effects of early-life famine exposure. Thus, the observed effects are a composite of two well-established factors, the survival of the fittest and the Fetal Origins hypothesis.

A nutrition-sensitive food system is one that goes beyond staple grain productivity and places emphasis on the consumption of micronutrient-rich nonstaples through a variety of market and nonmarket interventions. A nutrition-sensitive approach not only considers policies related to macrolevel availability and access to nutritious food, but it also focuses on household- and individual-level determinants of improved nutrition. In addition to agriculture, intrahousehold equity, behavior change, food safety, and access to clean water and sanitation are integral components of the food system. This article provides a detailed review, from an economic perspective, on the multisectoral pathways through which agriculture influences nutrition. A critical challenge is to identify and implement food and nutrition policies that are appropriate to the particular stage of structural transformation in the country of concern.

There is extensive evidence confirming the positive effect of maternal education on reducing child mortality. But, there is limited empirical evidence about the potential pathways through which this effect operates. In this paper I examine the role that maternal literacy has to play in mediating this relationship. I use detailed household survey data on about 2 million children born to nearly 500,000 mothers between 1990-2014 spread across 32 Sub-Saharan African countries to analyze the role of measured reading ability of the mother as a mediator for the effect of maternal education on child mortality. I find that in majority of the countries mother’s education and literacy individually have a significant positive impact on child mortality reduction. I also find evidence that literacy is an important mediator of this effect but limited evidence for it being the only mediator of this impact. In other words, maternal education impacts child mortality through more channels than just the enhanced reading ability of the mother. Results persists even after a variety of robustness checks.

This paper examines the impact of a large scale school construction program in India, the District Primary Education Programme (DPEP), on educational outcomes of direct beneficiaries and their children. Between the years 1993-2004, DPEP served over 50 million children and prioritized districts with below-average female literacy rates. This structure facilitates a fuzzy regression discontinuity design that compares outcomes of school-age children in districts near the average female literacy cutoff. In the analysis I combine data from multiple nationally representative household surveys with unique archival information. The results show that DPEP increased school access, enrollment, literacy and completed education for both male and female students. I then provide the first evidence of intergenerational effects of a school construction policy. Children whose mothers were DPEP beneficiaries had higher scores on standardized math (0.18 S.D.), vernacular (0.19 S.D.) and English (0.09 S.D.) tests. Daughters’ test scores went up by more than 17 to 22 percentage points higher than that of sons. Father’s DPEP exposure had no effect on children’s learning. The intergenerational impacts may be mediated through mother’s increased bargaining power, higher investments in children’s education and better health/health related behaviors.

Despite advances in medical technology and continued economic growth, child mortality is still one of the major issues facing the developing world. There is evidence exhibiting the positive effect that maternal education has on child mortality. In this paper I revisit this relationship and explore whether maternal literacy impacts the link between mother’s education and child mortality. In recent work, Smith-Greenaway [2013] using Nigeria Demographic and Health Survey (NDHS) data finds that the effect of mother’s education on child mortality becomes statistically insignificant when mother’s literacy is included as one of the covariates, suggesting that literacy explains all of the effect of maternal education on child mortality. Hence, I use Uganda Demographic and Health Survey (UDHS) data, to verify if that result holds in a comparable context. Using a Cox Proportional Hazards (Cox PH) method, I find that the effect of mother’s education on child mortality remains statistically significant even after the addition of mother’s literacy as one of the covariates. This result is robust to the addition of a variety of control variables. On further investigation, I find that for mothers with less than 3 years of education, literacy is significant in explaining the effect on mortality, whereas education is not. At the same time, it is exactly the opposite case for mothers with more than 3 years of education- education is significant but literacy is not. Based on these findings, I discuss potential threshold effects of the role of literacy in explaining the effect of maternal education on child mortality.