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.

This paper analyzes earnings inequality and earnings dynamics in Sweden over 1985–2016. The deep recession in the early 1990s marks a historic turning point with a massive increase in earnings inequality and earnings volatility, and the impact of the recession and the recovery from it lasted for decades. In the aftermath of the recession, we find steady growth in real earnings across the entire distribution for men and women and decreasing inequality over more than 20 years. Despite the positive trend, large gender differences in earnings dynamics persist. While earnings growth for men is more closely tied to the business cycle, women face much higher volatility overall. Earnings volatility is also substantially higher among foreign-born workers, reflecting weaker labor market attachment and high risk of large negative shocks for low-income immigrants. We document an important role of social benefits usage for the overall trends and for differences across subpopulations. Higher benefits enrollment, especially for women and immigrants, is associated with higher earnings volatility. As the generosity and usage of benefit programs declined over time, we find stronger earnings growth among low-income workers, consistent with higher self-sufficiency.

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 labor force participation, identifying gender gaps in labor 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 enrollees (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 enrollees (the 45% of respondents present in the first wave that also participated in the subsequent two survey rounds). Primary outcomes of interest include labor 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 labor market re-entry both inside and outside home villages. Some women drop out of the labor force entirely, but most unemployed report seeking or being available to work. In short, pandemic-induced labor 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.

We examine the employment effects of 3G mobile internet expansion in developing countries. We find that 3G significantly increases the labor force participation rate of women and the employment rates of both men and women. Our results suggest that 3G affects the type of jobs and there is a distinct gender dimension to these effects. Men transition away from unpaid agricultural work into operating small agricultural enterprises, while women take more unpaid jobs, especially in agriculture, and operate more small businesses in all sectors. Both men and women are more likely to work in wage jobs in the service sector.

Many children in developing countries grow up in environments that lack stimulation, leading to deficiencies in early years of development. Several efficacy trials of early childhood care and education (ECCE) programmes have demonstrated potential to improve child development; evidence on whether these effects can be sustained once programmes are scaled is much more mixed. This study evaluates whether an ECCE programme shown to be effective in an efficacy trial maintains effectiveness when taken to scale by the Government of Ghana (GoG). The findings will provide critical evidence to the GoG on effectiveness of a programme it is investing in, as well as a blueprint for design and scale-up of ECCE programmes in other developing countries, which are expanding their investment in ECCE programmes.

Children's experiences during early childhood are critical for their cognitive and socioemotional development, two key dimensions of human capital. However, children from low-income backgrounds often grow up lacking stimulation and basic investments, which leads to developmental deficits that are difficult, if not impossible, to reverse later in life without intervention. The existence of these deficits is a key driver of inequality and contributes to the intergenerational transmission of poverty. In this article, we discuss the framework used in economics to model parental investments and early childhood development and use it as an organizing tool to review some of the empirical evidence on early childhood research. We then present results from various important early childhoods interventions, with an emphasis on developing countries. Bringing these elements together, we draw conclusions on what we have learned and provide some directions for future research.