Three hundred million of the world’s rural poor suffer from seasonal income insecurity, which often occurs between planting and harvest when the demand for agricultural labor falls and the price of food rises. Those who undergo a lean season typically miss meals for a two- to three-month period. This is especially problematic for pregnant women and young children since poor nutrition for even a short time can limit long-term cognitive and physical development. Seasonal hunger and deprivation is perhaps the biggest challenge to the reduction of global poverty that has remained largely under the radar.
Members of some families in poor rural areas migrate to urban areas for work to cope with seasonal deprivation. In Bangladesh, however, researchers observed that many vulnerable households, who could potentially reap large benefits from temporary migration, didn’t send anyone away to work, thereby risking hunger. Why weren’t more people migrating? Would these households improve food security if they were to send a migrant to these areas during the lean season? More broadly, why were so many people sticking around in relatively unproductive rural areas, in the face of persistent gaps in wages and productivity between urban and rural areas? Was this akin to the proverbial $100 bills being left on the sidewalk?
A research team from Yale University, the London School of Economics, the University of Sydney, and Innovations for Poverty Action investigated these questions in Northern Bangladesh during 2008-2011, testing whether providing information or small financial incentives, worth about the cost of a bus ticket, increased migration and in turn, improved household welfare. They found that households offered either a grant or loan to migrate were substantially more likely to send someone to work outside the village during the lean season, and those families increased caloric intake relative to those not offered the incentives. Many of those households chose to re-migrate on their own a year later. A replication and expansion of the study during 2014-2016 not only confirmed these findings, it also showed that larger scale emigration increases wages and work hours in the village of origin, indirectly benefiting other residents who stay back.
Read about Evidence Action's scale-up of the program here.
A clustered randomized trial in Bangladesh examines alternative strategies to reduce child marriage and teenage childbearing and increase girls’ education. Communities were randomized into three treatment and one control group in a 2:1:1:2 ratio. From 2008, girls in treatment communities received either i) a six-month empowerment program, ii) a financial incentive to delay marriage, or iii) empowerment plus incentive. Data from 19,060 girls 4.5 years after program completion show that girls eligible for the incentive for at least two years were 22% (-9.9ppts, p<0.01) less likely to be married under 18, 14% (-5.2ppts, p<0.01) less likely to have given birth under 20, and 21% (5.6ppts, p<0.05) more likely to be in school at age 22. Unlike other incentive programs that are conditional on girls staying in school, an incentive conditional on marriage alone has the potential to benefit out-of-school girls. We find insignificantly different effects for girls in and out of school at baseline. The empowerment program did not decrease child marriage or teenage childbearing. However, girls eligible for the empowerment program were 12% (3.1ppts, p<0.05) more likely to be in-school and had completed 2.9 months (0.24 years, p<0.10) of additional schooling.
Targeted interventions that sustainably improve the lives of the poor will be a critical component in eliminating extreme poverty by 2030. The poorest households tend to be physically and socially isolated and face disadvantages across multiple dimensions, which makes moving out of extreme poverty challenging and costly. This paper compares the cost-effectiveness of three strands of anti-poverty social protection interventions by reviewing 30 livelihood development programs, 11 lump-sum unconditional cash transfers, and seven graduation programs. All the selected graduation initiatives focused on the extreme poor, while the livelihood development and cash transfer programs targeted a broader set of beneficiaries. Impacts on annual household consumption (or on income when consumption data were not available) per dollar spent were used to benchmark cost-effectiveness across programs. Among all 48 programs reviewed, lump-sum cash transfers were found to have the highest benefit-cost ratio, though there are very few lump-sum cash transfer programs that serve the extreme poor or measure long-term impacts. Livelihood programs that targeted the extreme poor had much lower benefit-cost ratios. Graduation programs are more cost-effective than the livelihood programs that targeted the extreme poor and measured long-term impacts (i.e., at least one year after end of interventions). More evidence is needed, especially on long-term impacts of lump-sum cash transfers to the extreme poor, to make better comparisons among the three types of programs for sustainable reduction of extreme poverty.
In 2010, IPA opened an office in Bangladesh to apply our tradition of rigorous, applicable research and gain insights into effective solutions for the country’s poor. IPA Bangladesh has since collaborated with governments, NGOs, and world-renowned researchers on over 20 evaluations across sectors. Our 35 full-time employees—who boast diverse expertise in research and questionnaire design, field and data management, and research quality control—work on-the-ground in districts as far reaching as Rangpur, Barishal, and Kurigram to ensure the quality of every evaluation.
Theoretically, weather-index insurance is an effective risk reduction option for small-scale farmers in low-income countries. Renewed policy and donor emphasis on bridging gender gaps in development also emphasizes the potential social safety net benefits that weather-index insurance could bring to women farmers who are disproportionately vulnerable to climate change risk and have low adaptive capacity. To date, no quantitative studies have experimentally explored weather-index insurance preferences through a gender lens, and little information exists regarding gender-specific preferences for (and constraints to) smallholder investment in agricultural weather-index insurance. This study responds to this gap, and advances the understanding of preference heterogeneity for weather-index insurance by analysing data collected from 433 male and female farmers living on a climate change vulnerable coastal island in Bangladesh, where an increasing number of farmers are adopting maize as a potentially remunerative, but high-risk cash crop. We implemented a choice experiment designed to investigate farmers’ valuations for, and trade-offs among, the key attributes of a hypothetical maize crop weatherindex insurance program that offered different options for bundling insurance with financial saving mechanisms. Our results reveal significant insurance aversion among female farmers, irrespective of the attributes of the insurance scheme. Heterogeneity in insurance choices could however not be explained by differences in men’s and women’s risk and time preferences, or agency in making agriculturally related decisions. Rather, gendered differences in farmers’ level of trust in insurance institutions and financial literacy were the key factors driving the heterogeneous preferences observed between men and women. Efforts to fulfill gender equity mandates in climate-smart agricultural development programs that rely on weather-index insurance as a risk-abatement tool are therefore likely to require a strengthening of institutional credibility, while coupling such interventions with financial literacy programs for female farmers.
We study political economy responses to a large scale intervention in Bangladesh, where four sub-districts consisting of 100 villages (12,000 households) were randomly assigned to control, information or subsidy treatments to encourage investments in improved sanitation. In theory, leaders may endogenously respond to large interventions by changing their allocation of effort, and their constituents’ views about the leader may rationally change as a result. In one intervention where the leaders’ role in program allocation was not clear to constituents, constituents appear to attribute credit to their local leader for a randomly assigned program. However, when subsidy assignment is clearly and transparently random, the lottery winners do not attribute any extra credit to the politician relative to lottery losers. The theory can rationalize these observations if we model leaders’ actions and constituent reactions under imperfect information about leader ability. A third intervention returns to program villages to inform a subset of subsidy recipients that the program was run by NGOs using external funds. This eliminates the excess credit that leaders received from treated households after the first intervention. These results suggest that while politicians may try to take credit for development programs, it is not easy for them do so. Political accountability is not easily undermined by development aid.