Publications

Working Papers

Work in Progress

Poverty alleviation and micro-enterprise saturation at high frequency

Draft coming soon

Abstract: In a large randomized control trial in Malawi, I explore the mechanisms behind the widely documented success of the graduation model (cash transfers + training + coaching + capital asset / grant + financial inclusion), how such a program scales, and how it interacts with strong agricultural seasonality. At the core of the project lie rich, high-frequency panel data on a plethora of shocks to households' health and livelihood, their coping behavior and preventive actions, income generating activities, expenditure, and time use.

Research Assistance

Public and Private Transit: Evidence from Lagos

Included and excluded instruments in structural estimation

Abstract: We consider the choice of instrumental variables when a researcher’s structural model may be misspecified. We contrast included instruments, which have a direct causal effect on the outcome holding constant the endogenous variable of interest, with excluded instruments, which do not. We show conditions under which the researcher’s estimand maintains an interpretation in terms of causal effects of the endogenous variable under excluded instruments but not under included instruments. We apply our framework to estimation of a linear instrumental variables model, and of differentiated goods demand models under price endogeneity. We show that the distinction between included and excluded instruments is quantitatively important in simulations based on an application. We extend our results to a dynamic setting by studying estimation of production function parameters under input endogeneity.

Building Resilient Health Systems: Experimental Evidence from Sierra Leone and the 2014 Ebola Outbreak (2021, QJE)

Developing countries are characterized by high rates of mortality and morbidity. A potential contributing factor is the low utilization of health systems, stemming from the low perceived quality of care delivered by health personnel. This factor may be especially critical during crises, when individuals choose whether to cooperate with response efforts and frontline health personnel. We experimentally examine efforts aimed at improving health worker performance in the context of the 2014–15 West African Ebola crisis. Roughly two years before the outbreak in Sierra Leone, we randomly assigned two accountability interventions to government-run health clinics – one focused on community monitoring and the other gave status awards to clinic staff. We find that over the medium run, prior to the Ebola crisis, both interventions led to improvements in utilization of clinics and patient satisfaction with the health system. In addition, child health outcomes improved substantially in the catchment areas of community monitoring clinics. During the crisis, the interventions also led to higher reported Ebola cases, as well as lower mortality from Ebola – particularly in areas with community monitoring clinics.  We explore three potential mechanisms: the interventions (1) increased the likelihood that patients reported Ebola symptoms and sought care; (2) unintentionally increased Ebola incidence; or (3) improved surveillance efforts.  We find evidence consistent with the first: by building trust and confidence in health workers, and improving the perceived quality of care provided by clinics prior to the outbreak, the interventions encouraged patients to report and receive treatment. Our results suggest that accountability interventions not only have the power to improve health systems during normal times, but can additionally make health systems resilient to crises that may emerge over the longer run.

Main paper, Companion Paper (AEA P&P), Non-technical summary

Media Coverage: New York Times, IPA, CBS

Put to rest

Robust results in the presence of treatment interactions: The case of unconditional cash transfers

Abstract: Recent contributions to the analysis of randomized experiments have shown that cross-randomizing several treatments can lead to small cell sizes, which can result in distorted treatment effect estimates. In addition, it has been suggested that failure to include interaction terms in regressions may also bias results. In light of these concerns, we re-evaluate a large study of unconditional cash transfers in Kenya with three cross-randomizations (recipient gender, transfer magnitude and timing). To circumvent the failure of asymptotic results in small cells, we first re-estimate the treatment effects of the study using randomization inference,bootstrapping, and a jackknife method. The results are very similar to those obtained with conventional asymptotic methods. Second, we show that in the class of experiments which assign multiple versions of the same treatment, rather than several independent treatments, inclusion of interaction terms does not yield “pure” treatment effects, but rather treatment effects for particular subgroups,which are not generally estimands of interest. Finally, we quantify the possible bias introduced by slight imbalances in cell sizes generated by randomization, and suggest a simple re-weighting to correct for it.