India’s GDP per capita grew threefold between 1987 and 2019, coinciding with rapid urbanization. During this period, female labor force participation (FLFP) declined significantly. Consistent with this observation, we document a pronounced urban-rural participation gap, where FLFP is higher in poorer, rural labor markets. Using time-use data, we show that this is primarily driven by an extensive margin: in rural districts, women often engage in part-time activities, typically related to agriculture and informal family businesses. These activities are less common in urban areas, where some women take formal jobs, but a larger share withdraws from the labor market to focus on home production. We propose and estimate a model of household labor supply that aligns with these trends. The main drivers of the urban-rural participation gap are higher spousal incomes in cities, which reduce the marginal utility of female labor, and labor market distortions that depress women’s urban wages below their marginal product. Counterfactual simulations show that economic growth is unlikely to provide a sharp reversal of this trend in future decades unless it is accompanied by changes in gender norms and labor market institutions.
We develop a framework for quantifying barriers to labor force participation (LFP) and entrepreneurship faced by women in India. We find substantial barriers to LFP, and higher costs of expanding businesses through hiring workers for women entrepreneurs. However, there is one area where female entrepreneurs have an advantage: the hiring of female workers. We show that this is not driven by the sectoral composition of female employment. Consistent with this pattern, policies promoting female entrepreneurship can significantly increase female LFP even without explicitly targeting female LFP. Counterfactual simulations indicate that removing all excess barriers faced by women entrepreneurs would substantially increase the fraction of female‐owned firms, female LFP, earnings, and generate substantial gains for the economy. These gains are due to higher LFP, higher real wages and profits, and reallocation: low productivity male‐owned firms previously sheltered from female competition are replaced by higher productivity female‐owned firms previously excluded from the economy.
Access to smartphones and mobile internet is increasingly necessary to participate in the modern economy. Yet women significantly lag men in digital access, especially in lower-income settings with gender gaps that span other dimensions - and where digital gaps threaten to deepen existing analog inequities. We study the short- and long-term effects of a large-scale state-sponsored program in India that aimed to close digital gender gaps by transferring free smartphones to women while constructing 4G towers to bring rural areas online. The program was well implemented, reversing gender gaps in smartphone ownership in the short run. However, many women lost ownership and gender gaps in use quickly worsened as men made use of the new phones. Nearly 5 years after the program began, we find limited evidence of persistent effects across a range of outcomes, including phone ownership and use, gender norms, access to information, and local economic activity, although we do find some evidence of sectoral reallocation in the labor market. Despite widespread increase in smartphone adoption across households, digital gender gaps persist and were not affected by the program. Our findings suggest that in gender-unequal, resource-constrained settings, addressing affordability alone may not close digital gender gaps.
The extent to which women participate in the labor market and have access to formal employment differs greatly across Indian states. In this paper we build on the methodology developed by Hsieh, Hurst, Jones, and Klenow (2019) to estimate the productivity consequences of such differences. Using rich microdata on occupational sorting and earnings, our theory allows to separately identify labor demand distortions (e.g., discrimination in hiring for formal jobs) from labor supply distortions (e.g., frictions that discourage women’s labor force participation). We find that both demand distortions and supply distortions are negatively related to state-level economic development. Equalizing distortions across Indian states could raise state-level productivity by up to 15%.
Wealth accumulation is critical for advancing women's and men's economic opportunities, and yet is understudied in developing countries. Leveraging new, nationally-representative, cross-country comparable surveys where men and women self-reported on their personal asset ownership, we show that individual-level wealth inequality is significantly higher vis-à-vis comparators based on per capita household consumption expenditure, and per capita household wealth. Intra-household wealth inequality explains about 12–30 percent of overall wealth inequality, depending on the country context. The analysis further demonstrates how survey design choices, in particular respondent selection, matter for individual wealth inequality estimates.
Does economic growth close labor market-linked gender gaps that disadvantage women? Conversely, do gender inequalities in the labor market impede growth? To inform these questions, we conduct two analyses. First, we estimate regressions using data on gender gaps in a range of labor market outcomes from 153 countries spanning two decades (1998-2018). Second, we conduct a systematic review of the recent economics literature on gender gaps in labor markets, examining 16 journals over 21 years. Our empirical analysis demonstrates that growth is not a panacea. While economic gender gaps have narrowed and growth is associated with gender gap closures specifically in incidence of paid work, the relationship between growth and labor market gaps is otherwise mixed, and results vary by specification. This result reflects, in part, the gendered nature of structural transformation, in which growth leads men to transition from agriculture to industry and services while many women exit the labor force. Disparities in hours worked and wages persist despite growth, and heterogeneity in trends and levels between regions highlight the importance of local institutions. To better understand whether gender inequalities impeded growth, we explore a nascent literature that shows that reducing gender gaps in labor markets increases aggregate productivity. Our broader review highlights how traditional explanations for gender differences do not adequately explain existing gaps and how policy responses need to be sensitive to the changing nature of economic growth. We conclude by posing open questions for future research.
Does a woman’s take-up of government benefits vary with her perception of how they will be shared within the household? Using randomized assignment to alternative information treatments, we examine this question in the context of Saudi women’s willingness to apply for unemployment assistance (Hafiz). We compare the take-up among women who receive no program information to three groups: those who receive information on program eligibility conditions (Eligibility group) and those who receive additional information that their registration status is broadly confidential (Privacy group) or that they fully control registering and accessing benefits (Agency group). Three months later, the treatments, on average, doubled Hafiz applications, with the treatment impacts largest for the Agency group. Women from poorer households and married women are most responsive to the Agency and Privacy interventions respectively. These findings are consistent with collective household bargaining models where family members’ spending preferences differ; we predict larger treatment impacts when there is more competition for resources.
Time use data facilitate understanding of labor supply, especially for women who often undertake unpaid care and home production. Although assisted diary-based time use surveys are suitable for low-literacy populations, they are costly and rarely used. We create a low-cost, scalable alternative that captures contextually-determined broad time categories; here, allocations across market work, household labor, and leisure. Using fewer categories and larger time intervals takes 33% less time than traditional modules. Field experiments show the module measures average time across the broader categories as well as the traditional approach, particularly for our target female population. The module can also capture multitasking for a specific category of interest. Its shortcomings are short duration activity capture and the need for careful category selection. The module’s brevity and low cost make it a viable method to use in household and labor force surveys, facilitating tracking of work and leisure patterns as economies develop.
Structural transformation in most currently developing countries takes the form of a rapid rise in services but limited industrialization. In this paper, we propose a new methodology to structurally estimate productivity growth in service industries that circumvents the notorious difficulties in measuring quality improvements. In our theory, the expansion of the service sector is both a consequence – due to income effects – and a cause – due to productivity growth – of the development process. We estimate the model using Indian household data. We find that productivity growth in non-tradable consumer services such as retail, restaurants, or residential real estate, was an important driver of structural transformation and rising living standards between 1987 and 2011. However, the welfare gains were heavily skewed toward high-income urban dwellers.
Millions of children are at risk for developmental deficits in low and-middle-income countries (LMICs). Reviews find that psychosocial interventions for children aged <3 years improve short-run child cognition and language (0.28–0.47 SD). Similarly, a meta-regression analysis of 54 preschool interventions for children aged ≥3 years found significant improvements in children’s cognitive skills (0.15 SD), executive functioning, social–emotional learning, and behavior (0.12 SD). Only 18 of these interventions were from LMICs, with 2 from India, which has the world’s largest population of children attending preschool (36 million children enrolled in Integrated Childhood Development Services [ICDS]). Interventions have had benefits in math and language. However, a survey of 298 Indian preschools found generally poor quality. Although short-run impacts of some interventions fade, some rigorous studies with long-term follow-ups found later benefits in educational attainment, reduced crime, and increased income.
