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Antipoverty programs in developing countries are often difficult to implement; in particular, many governments lack the capacity to deliver payments securely to targeted beneficiaries. We evaluate the impact of biometrically authenticated payments infrastructure (\"Smartcards\") on beneficiaries of employment (NREGS) and pension (SSP) programs in the Indian state of Andhra Pradesh, using a large-scale experiment that randomized the rollout of Smartcards over 157 subdistricts and 19 million people. We find that, while incompletely implemented, the new system delivered a faster, more predictable, and less corrupt NREGS payments process without adversely affecting program access. For each of these outcomes, treatment group distributions first-order stochastically dominated those of the control group. The investment was cost-effective, as time savings to NREGS beneficiaries alone were equal to the cost of the intervention, and there was also a significant reduction in the \"leakage \"of funds between the government and beneficiaries in both NREGS and SSP programs. Beneficiaries overwhelmingly preferred the new system for both programs. Overall, our results suggest that investing in secure payments infrastructure can significantly enhance \"state capacity\" to implement welfare programs in developing countries.

Understanding and addressing the factors that affect progress in antipoverty interventions is central to achieving the Sustainable Development Goals. In Bangladesh this topic has been largely explored through quantitative approaches, and we believe in-depth qualitative analyses of household dynamics in the context of antipoverty interventions is lacking. This article addresses this lacuna. Based on 49 focus group discussions and 15 case studies, we analyse livelihood dynamics of beneficiary households within a national extreme poverty alleviation program. We identify five determining factors to the effectiveness of antipoverty interventions: 1) health shocks, natural hazards, and vulnerabilities; 2) household demography; 3) inappropriate IGA planning, implementation, and monitoring; 4) dependence/inaction; and 5) political and social instability. We argue that livelihood-based antipoverty initiatives often fail because they do not address these five factors, and call for a comprehensive approach that prioritises them in program design.

We use a randomized controlled trial to study the response of poor households in rural Kenya to unconditional cash transfers from the NGO GiveDirectly. The transfers differ from other programs in that they are explicitly unconditional, large, and concentrated in time. We randomized at both the village and household levels; furthermore, within the treatment group, we randomized recipient gender (wife versus husband), transfer timing (lump-sum transfer versus monthly installments), and transfer magnitude (US$404 PPP versus US$1,525 PPP). We find a strong consumption response to transfers, with an increase in household monthly consumption from $158 PPP to $193 PPP nine months after the transfer began. Transfer recipients experience large increases in psychological well-being. We find no overall effect on levels of the stress hormone cortisol, although there are differences across some subgroups. Monthly transfers are more likely than lump-sum transfers to improve food security, whereas lump-sum transfers are more likely to be spent on durables, suggesting that households face savings and credit constraints. Together, these results suggest that unconditional cash transfers have significant impacts on economic outcomes and psychological well-being.

Of the 17 Sustainable Development Goals articulated by the United Nations, number one is the elimination of extreme poverty by 2030. While future economic growth should continue to reduce poverty, it will not solve the problem by itself; thus, there is a potentially important role for national-level transfer programs that assist poor families in developing countries. Such programs are often run by developing country governments. Many countries have implemented transfer programs that seek to target beneficiaries: that is, to identify who is poor and then to restrict transfers to those individuals. Some people have begun to advocate for “universal basic income” programs, which dispense with trying to identify the poor and instead provide transfers to everyone. We begin by considering the universal basic income as part of the solution to an optimal income-taxation problem, focusing on the case of developing countries, where there is limited income data and inclusion in the formal tax system is low. We examine how the targeting of transfer programs is conducted in these settings, and provide empirical evidence on the tradeoffs involved between universal basic income and targeted transfer schemes using data from Indonesia and Peru—two countries that run nationwide transfer programs that are targeted to the poor. We conclude by linking our findings back to the broader policy debate on what tools should be preferred for redistribution, as well as the practical challenges of administering them in developing countries.

How large economic stimuli generate individual and aggregate responses is a central question in economics, but has not been studied experimentally. We provided one-time cash transfers of about USD 1000 to over 10,500 poor households across 653 randomized villages in rural Kenya. The implied fiscal shock was over 15 percent of local GDP. We find large impacts on consumption and assets for recipients. Importantly, we document large positive spillovers on non-recipient households and firms, and minimal price inflation. We estimate a local transfer multiplier of 2.5. We interpret welfare implications through the lens of a simple household optimization framework.

Conditional cash transfer (CCT) programs innovate by conditioning transfers to poor families on investments in the human capital of children and other family members. The Mexican CCT program Progresa/Oportunidades began in 1997 and has served as a model for many of the now over sixty countries with CCTs around the world, in large part due to its initial evaluation with an experimental design and numerous follow-up studies. This article reviews the literature on the development, evaluation, and findings of Progresa/Oportunidades, summarizing what is known about program effects, taking into account corrections for multiple-hypothesis testing.

This article presents the findings of a review of the impact of non-contributory cash transfers on individuals and households in low- and middle-income countries, covering the literature of 15 years, from 2000 to 2015. Based on evidence extracted from 165 studies, retrieved through a systematic search and screening process, this article discusses the impact of cash transfers on 35 indicators covering six outcome areas: monetary poverty; education; health and nutrition; savings, investment and production; work; and empowerment. For most of the studies, cash transfers contributed to progress in the selected indicators in the direction intended by policymakers. Despite variations in the size and strength of the underlying evidence base by outcome and indicator, this finding is consistent across all outcome areas. The article also investigates unintended effects of cash transfer receipt, such as potential reductions in adult work effort and increased fertility, finding limited evidence for such unintended effects. Finally, the article highlights gaps in the evidence base and areas which would benefit from additional future research.

We study an at-scale natural experiment in which debit cards were given to cash transfer recipients who already had a bank account. Using administrative account data and household surveys, we find that beneficiaries accumulated a savings stock equal to 2% of annual income after two years with the card. The increase in formal savings represents an increase in overall savings, financed by a reduction in current consumption. There are two mechanisms. First, debit cards reduce transaction costs of accessing money. Second, they reduce monitoring costs, which led beneficiaries to check their account balances frequently and build trust in the bank.

Although many countries recruit bureaucrats using affirmative action, the effect of affirmative action recruits on bureaucratic performance has rarely been examined. Some worry that affirmative action worsens bureaucratic performance by diminishing the quality of recruits, whereas others posit that it improves performance by making recruits more representative of and responsive to the population. We test for these possibilities using unusually detailed data on the recruitment, background, and careers of India's elite bureaucracy. We examine the effect of affirmative action hires on district-level implementation of MGNREGA, the world's largest anti-poverty program. The data suggest that disadvantaged group members recruited via affirmative action perform no worse than others.

Background Population aging poses a demographic burden on a country such as India with inadequate social security systems and very low public investment in health sector. This challenge of accelerated demographic transition is coupled by the rural-urban disparity in access to healthcare services among the elderly people in India. An important objective of India’s National Health Policy (2017) is to “progressively achieve universal health coverage” which is posited upon mitigating the sub-national disparity that necessitates identifying the drivers of the disparity for targeted policy intervention. This study, therefore, makes an attempt towards the exploration of the prominent contributory factors behind the rural-urban gap in utilisation of healthcare among the older population in India. Methods The analysis has been done by using the unit level data of Social Consumption: Health (Schedule number 25.0) of the 75th round of the National sample Survey conducted during July 2017–June 2018. Two binary logistic models have been proposed to capture the crude and the adjusted association between health seeking behaviour and place of residence (rural/ urban). To compute the group differences (between rural and urban) in the rate of healthcare utilization among the elderly population in India and to decompose these differences into the major contributing factors, Fairlie’s decomposition method has been employed. Results The logistic regression models established a strong association between place of residence and likelihood of healthcare utilisation among the Indian elderly people. The results of the Fairlie’s decomposition analysis revealed considerable rural-urban inequality disfavouring the rural residents and health care utilisation was found to be 7 percentage points higher among the older population residing in urban India than their rural counterparts. Level of education and economic status, both of which are indicators of a person’s Socio-Economic Status, were the two major determinants of the existing rural-urban differential in healthcare utilisation, together explaining 41% of the existing rural-urban differential. Conclusion Public health care provisions need to be strengthened both in terms of quality and outreach by way of greater public investments in the health sector and by building advanced health infrastructure in the rural areas. Implementation of poverty alleviation programmes and ensuring social-security of the elderly are also indispensable in bringing about equity in healthcare utilisation.