Accelerating Birth Timing to Access Cash Transfers? Evidence from Households in Extreme Poverty

joint with Pedro Carneiro (UCL), Lucy Kraftman (IFS) and Molly Scott (OPM)

April 2022

Abstract There has been a dramatic rise in cash transfer programs to the poor, and burgeoning interest in interventions promoting early childhood development. We draw together these trends to study whether open enrolment interventions targeting cash transfers to pregnant mothers unintentionally induce those not pregnant to accelerate birth timing in order to start receiving cash transfers. Our study context is rural Northern Nigeria, where households have high demand for short term liquidity because the majority reside in extreme poverty, are reliant on volatile earnings streams from agriculture, and face a lean season during which they resort to extreme coping strategies to overcome food scarcity. Our evidence comes from a four-year evaluation of an intervention targeting high-valued and long-lasting unconditional cash transfers to pregnant mothers, with open enrolment into the program. We use survival analysis to examine how this impacts birth timing for 1700 women not pregnant at baseline. We document relatively weak distortionary impacts on birth timing. The reasons are women retain full control over the use of cash transfers, they have available productive investment opportunities in their own businesses, and they choose to invest in those rather than transfer resources to husbands. As women and children bear the costs of shortened birth spacing, this constellation of factors allows women to place a brake on the economic incentives households otherwise have to accelerate birth timing. We provide evidence on the internal validity of these mechanisms. On external validity, we draw together 45 DHS surveys to classify countries into those more or less likely to see distortionary effects on birth timing from open enrolment interventions targeting cash transfers to pregnant mothers.

The Search for Good Jobs: Evidence from a Six-year Field Experiment in Uganda
joint with Oriana Bandiera (LSE), Vittorio Bassi (USC), Robin Burgess (LSE),
Munshi Sulaiman (BRAC) and Anna Vitali (UCL)
March 2022

Abstract One third of the 420 million young people in Africa are unemployed. Understanding how youth search for jobs and what affects their ability to find good jobs is of paramount importance. We do so using a field experiment tracking young job seekers for six years in Uganda's main cities. We examine how two standard labor market interventions impact their search for good jobs: vocational training, vocational training combined with matching youth to firms, and matching only. Training is offered in sectors with high quality firms. The matching intervention assigns workers for interviews with such firms. At baseline, unskilled youth are optimistic about their job prospects, especially over the job offer arrival rate from high quality firms. Relative to controls, those offered vocational training become even more optimistic, search more intensively and direct search towards high quality firms. However, youth additionally offered matching become discouraged because call back rates from firm owners are far lower than their prior. As a result, they search less intensively and direct their search towards lower quality firms. These divergent expectations and search behaviors have persistent impacts: vocational trainees without match offers achieve greater labor market success, largely because they end up employed at higher quality firms than youth additionally offered matching. Our analysis highlights the foundational but separate roles of skills and expectations in job search, how interventions cause youth to become optimistic or discouraged, and how this matters for long run sorting in the labor market.

The Anatomy of a Public Health Crisis: Household Responses Over the Course of the Zika Epidemic in Brazil
joint with Ildo Lautharte (World Bank)
January 2022

Abstract The global frequency and complexity of viral outbreaks is increasing. In 2015, Brazil experienced an epidemic caused by the Zika virus. This represents the first known association between a flavivirus -- carried by the Aedes Aegypti mosquito -- and congenital disease, marking a `new chapter in the history of medicine' [Brito 2015]. We use hundreds of millions of administrative records to document household responses to the first public health alert linking the Zika virus to the risk of congenital disease for those in utero. We study the two margins of household behavior emphasized by economic epidemiological models of disease diffusion: risk avoidance behaviors (avoiding pregnancy), and risk mitigation behaviors during pregnancy (ultrasounds and abortions). On risk avoidance, we find a 7% reduction in pregnancies post-alert, a response triggered immediately after the alert, and driven by higher SES women. On risk mitigation during pregnancy, we find a 9% increase in the use of ultrasounds in the first trimester of pregnancy, and abortions rise by 5%, being concentrated among late term abortions. We document that post-alert all groups -- irrespective of race, marital status, education, age, and socioeconomic status -- were able to reduce risks during pregnancy, in line with preventative measures not being costly. Combining the evidence on avoidance and mitigation behaviors rules out that higher educated mothers responded more in terms of delayed pregnancies because they were better informed of the risks from Zika. Rather, the combined evidence suggests more educated households might be able to delay conception because they face lower costs of altering their fertility timing from their plan. We conclude by discussing consequent impacts on birth outcomes, and the extent to which our findings extend to household responses to public health alerts on other emerging viral threats.

Social Incentives, Delivery Agents and the Effectiveness of Development Interventions

joint with Oriana Bandiera (LSE), Robin Burgess (LSE), Erika Deserranno (Northwestern),

Ricardo Morel (IPA) and Munshi Sulaiman (BRAC)

December 2021

Abstract There has been a dramatic rise in the use of the local delivery model for development interventions, where local agents are hired as intermediaries to target benefits to potential beneficiaries. We study this model in the context of a standard agricultural extension intervention in Uganda using a novel two-stage experimental design. In the first stage, we randomize the delivery of the intervention across communities. In the second, in each community we identify two potential delivery agents and then randomly select one of them. This stage yields exogenous variation in social ties to the actual delivery agent as well as to their counterfactual. We use this to identify how social incentives shape the behavior of delivery agents through them having social ties to farmers in communities from which they are recruited and serve. We document a trade-off between coverage and targeting: delivery agents treat more farmers when they have a greater number of social ties, but they are significantly more likely to target their non-poor ties -- counter to the pro-poor intent of the intervention. We explore reasons why delivery agents target their non-poor ties, and conclude by discussing the implications of our findings for the design of the local delivery model.

Identifying Network Ties from Panel Data: Theory and an Application to Tax Competition
joint with Aureo de Paula (UCL) and Pedro CL Souza (Warwick)

August 2020

Abstract Social interactions determine many economic behaviors, but information on social ties does not exist in most publicly available and widely used datasets. We present results on the identification of social networks from observational panel data that contains no information on social ties between agents. In the context of a canonical social interactions model, we provide sufficient conditions under which the social interactions matrix, endogenous and exogenous social effect parameters are all globally identified. While this result is relevant across different estimation strategies, we then describe how high-dimensional estimation techniques can be used to estimate the interactions model based on the Adaptive Elastic Net GMM method. We employ the method to study tax competition across US states. We find the identified social interactions matrix implies tax competition differs markedly from the common assumption of competition between geographically neighboring states, providing further insights for the long-standing debate on the relative roles of factor mobility and yardstick competition in driving tax setting behavior across states. Most broadly, our identification and application show the analysis of social interactions can be extended to economic realms where no network data exists.

Revisions requested, Review of Economic Studies.