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.

We propose a technique for assessing robustness to demand effects of findings from experiments and surveys. The core idea is that by deliberately inducing demand in a structured way we can bound its influence. We present a model in which participants respond to their beliefs about the researcher’s objectives. Bounds are obtained by manipulating those beliefs with “demand treatments.” We apply the method to 11 classic tasks, and estimate bounds averaging 0.13 standard deviations, suggesting that typical demand effects are probably modest. We also show how to compute demand-robust treatment effects and how to structurally estimate the model.

Skepticism about the quality of health systems and their consequent underuse are thought to contribute to high rates of mortality in the developing world. The perceived quality of health services may be especially critical during epidemics, when people choose whether to cooperate with response efforts and frontline health workers. Can improving the perceived quality of health care promote community health and ultimately help to contain epidemics? We leverage a field experiment in Sierra Leone to answer this question in the context of the 2014 West African Ebola crisis. Two years before the outbreak, we randomly assigned two interventions to government-run health clinics—one focused on community monitoring, and the other conferred nonfinancial awards to clinic staff. Prior to the Ebola crisis, both interventions increased clinic utilization and patient satisfaction. Community monitoring additionally improved child health, leading to 38% fewer deaths of children under age five. Later, during the crisis, the interventions also increased reporting of Ebola cases by 62%, and community monitoring significantly reduced Ebola-related deaths. Evidence on mechanisms suggests that both interventions improved the perceived quality of health care, encouraging patients to report Ebola symptoms and receive medical care. Improvements in health outcomes under community monitoring suggest that these changes partly reflect a rise in the underlying quality of administered care. Overall, our results indicate that promoting accountability not only has the power to improve health systems during normal times, but can also make them more resilient to emergent crises.

A large literature has examined how best to target antipoverty programs to those most deprived in some sense (e.g., consumption). We examine the potential trade-off between this objective and targeting those most impacted by such programs. We work in the context of an NGO cash transfer program in Kenya, employing recent advances in machine learning methods and dynamic outcome data to learn proxy means tests that jointly target both objectives. Targeting solely on the basis of deprivation is not attractive in this setting under standard social welfare criteria unless the planner’s preferences are extremely redistributive.

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.