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.
Poor entrepreneurs must frequently choose between business investment and children's education. To examine this trade-off, we exploit experimental variation in short-run microenterprise growth among a sample of Indian households and track schooling and business out-comes over eleven years. Treated households, who experience higher initial microenterprise growth, are on average one-third more likely to send children to college. However, educational investment and schooling gains are concentrated among literate-parent households, whose enterprises eventually stagnate. In contrast, illiterate-parent households experience long-run business gains but declines in children's education. Our findings suggest that microenterprise growth has the potential to reduce relative intergenerational educational mobility.
Two years prior to elections, two-thirds of Delhi municipal councillors learned they had been randomly chosen for a preelection newspaper report card. Treated councillors in high-slum areas increased pro-poor spending, relative both to control counterparts and treated counterparts from low-slum areas. Treated incumbents ineligible to rerun in home wards because of randomly assigned gender quotas were substantially likelier to run elsewhere only if their report card showed a strong pro-poor spending record. Parties also benefited electorally from councillors' high pro-poor spending. In contrast, in a cross-cut experiment, councillors did not react to actionable information that was not publicly disclosed.
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.
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.
Background:India's abrupt nationwide Covid-19 lockdown internally displaced millions of migrant workers, who returned to distant rural homes. Documenting their labour market reintegration is a critical aspect of understanding the economic costs of the pandemic for India's poor. In a country marked by low and declining female labour force participation, identifying gender gaps in labour market reintegration – as a marker of both women's vulnerability at times of crisis and setbacks in women's agency – is especially important. Yet most studies of pandemic-displaced internal migrants in India are small, rely on highly selected convenience samples, and lack a gender focus.
Methods: Beginning in April 2020 we enrolled roughly 4,600 displaced migrants who had, during the lockdown, returned to two of India's poorest states into a cohort observational study which tracked enrolees through July 2021. Survey respondents were randomly selected from the states’ official databases of return migrants, with sampling stratified by state and gender. 85% of enrolees (3950) were working prior to the pandemic. Our difference-in-means analysis uses three survey waves conducted in July to August 2020, January to March 2021, and June to July 2021. Our analysis focuses on a balanced panel of 1780 previously working enrolees (the 45% of respondents present in the first wave that also participated in the subsequent two survey rounds). Primary outcomes of interest include labour market re-entry, earnings, and measures of vulnerability by gender.
Findings: Before the March 2020 national lockdown, 98% (95% CI [97,99]) of workers were employed in the non-agricultural sector. In July 2020, one month after the end of the lockdown, incomes plummet, with both genders earning roughly 17% of their pre-pandemic incomes. 47% (95% CI [45,49]) were employed in agriculture and 37% (95% CI [35,39]) were unemployed. Remigration is critical to regaining income – by January 2021, male re-migrants report earnings on par with their pre-pandemic incomes, while men remaining in rural areas earn only 23% (95% CI [19,27]) of their pre-pandemic income. Remigration benefits women to a lesser extent – female re-migrants regain no more than 65% (95% CI [57,73]) of their pre-pandemic income at any point. Yet men and women struggle to remigrate throughout – by July 2021, no more than 63% (95% CI [60,66]) of men and 55% (95% CI [51,59]) of women had left their home villages since returning. Gender gaps in income recovery largely reflect higher rates of unemployment among women, both among those remaining in rural areas (9 percentage points (95% CI [6,13]) higher than men across waves) and among those who remigrate (13 percentage points (95% CI [9,17]) higher than men across waves). As a result, we observe gender gaps in well-being: relative to male counterparts, women across waves were 7 percentage points (95% CI [4,10]) more likely to report reduced consumption of essential goods and fared 6 percentage points (95% CI [4,7]) worse on a food insecurity index.
Interpretation: Displaced migrants of both genders experienced persistent hardships for over a year after the initial pandemic lockdown. Women fare worse, driven by both lower rates of remigration and lower rates of labour market re-entry both inside and outside home villages. Some women drop out of the labour force entirely, but most unemployed report seeking or being available to work. In short, pandemic-induced labour market displacement has far-reaching, long-term consequences for migrant workers, especially women.
Funding: Survey costs were funded by research grants from IZA/FCDO Gender, Growth, and Labour Markets in Low Income Countries Programme, J-PAL Jobs and Opportunity Initiative, and the Evidence-based Measures of Empowerment for Research on Gender Equality (EMERGE) program at University of California San Diego.
The use of air quality monitoring networks to inform urban policies is critical especially where urban populations are exposed to unprecedented levels of air pollution. High costs, however, limit city governments’ ability to deploy reference grade air quality monitors at scale; for instance, only 33 reference grade monitors are available for the entire territory of Delhi, India, spanning 1500 sq km with 15 million residents. In this paper, we describe a high-precision spatio-temporal prediction model that can be used to derive fine-grained pollution maps. We utilize two years of data from a low-cost monitoring network of 28 custom-designed low-cost portable air quality sensors covering a dense region of Delhi. The model uses a combination of message-passing recurrent neural networks combined with conventional spatio-temporal geostatistics models to achieve high predictive accuracy in the face of high data variability and intermittent data availability from low-cost sensors (due to sensor faults, network, and power issues). Using data from reference grade monitors for validation, our spatio-temporal pollution model can make predictions within 1-hour time-windows at 9.4, 10.5, and 9.6% Mean Absolute Percentage Error (MAPE) over our low-cost monitors, reference grade monitors, and the combined monitoring network respectively. These accurate fine-grained pollution sensing maps provide a way forward to build citizen-driven low-cost monitoring systems that detect hazardous urban air quality at fine-grained granularities.
Alfred Marshall and Mary Paley Marshall are often described as the first academic economist couple. Both studied at the University of Cambridge, where Paley became one of the first women to take the Tripos exam and the first female lecturer in economics, with Marshall’s encouragement. But in later life, Marshall opposed granting Cambridge degrees to women and their participation in academic economics. This paper recounts Alfred Marshall’s use of gender norms, born out of a separate spheres ideology, to promote and ingrain women’s exclusion in academic economics and beyond. We demonstrate the persistence of this ideology and resultant norms, drawing parallels between gendered inequities in labor market outcomes for Cambridge graduates in the UK post-Industrial Revolution and those apparent in cross-country data today. We argue that the persistence of the norms produced by separate spheres ideologies is likely to reflect, at least in part, the rents associated with preferential access to better paid, high-skilled labor market opportunities. In doing so, we ask who benefits from gender norms, who enforces them, and suggest relevant policy work and areas for future research.
Can increasing control over earnings incentivize a woman to work, and thereby influence norms around gender roles? We randomly varied whether rural Indian women received bank accounts, training in account use, and direct deposit of public sector wages into their own (versus husbands') accounts. Relative to the accounts only group, women who also received direct deposit and training worked more in public and private sector jobs. The private sector result suggests gender norms initially constrained female employment. Three years later, direct deposit and training broadly liberalized women's own work-related norms, and shifted perceptions of community norms.
Can increasing control over earnings incentivize a woman to work, and thereby influence norms around gender roles? We randomly varied whether rural Indian women received bank accounts, training in account use, and direct deposit of public sector wages into their own (versus husbands') accounts. Relative to the accounts only group, women who also received direct deposit and training worked more in public and private sector jobs. The private sector result suggests gender norms initially constrained female employment. Three years later, direct deposit and training broadly liberalized women's own work-related norms, and shifted perceptions of community norms.
The prevalence of vote-buying is widely identified as a cause of poor governance in the developing world; potential mechanisms for this relationship include the selection of lower quality politicians, and the reduced accountability experienced by politicians once elected. In this paper, we present the first experimental evidence in support of the second channel of reduced accountability. Using data from laboratory experiments conducted in the U.S. and Kenya, we find that vote payments reduce voters' willingness to hold politicians accountable: holding fixed politician identity, voters who receive payments are less willing to punish the politician for rent-seeking, and this reduction in punishment is larger in magnitude when payments are widely targeted. Unsurprisingly, the politician then engages in a higher level of rent-seeking. A simple model of multi-faceted social preferences encompassing reciprocity and inequality aversion is consistent with these findings.
Can e-governance reforms improve government policy? By making information available on a real-time basis, information technologies may reduce the theft of public funds. We analyze a large field experiment and the nationwide scale-up of a reform to India's workfare program. Advance payments were replaced by "just-in-time" payments, triggered by e-invoicing, making it easier to detect misreporting. Leakages went down: program expenditures dropped by 24 percent, while employment slightly increased; there were fewer fake households in the official database; and program officials' personal wealth fell by 10 percent. However, payment delays increased. The nationwide scale-up resulted in a persistent 19 percent reduction in program expenditure.
Millions of the world’s poorest people now live in middle-income democracies that, in theory, could use their resources to end extreme poverty. However, citizens in those countries have not succeeded in using the vote to ensure adequate progressive redistribution. Interventions aiming to provide the economically vulnerable with needed resources must go beyond assisting them directly, they must also improve democratic institutions so that vulnerable populations themselves can push their representatives to implement redistributive policies. Here, I review the literature on such interventions and then consider the “democracy catch-22”: How can the poor secure greater democratic influence when the existing democratic playing field is tilted against them?