Families as Drivers of Inequality: Experimental Evidence from an Early Childhood Intervention
joint with Pedro Carneiro (UCL) and Francesca Salvati (Essex)
March 2023
Abstract Families shape inequality across individuals, by determining whether initial endowment differences across children are magnified or equalized through the intrahousehold allocation of resources over time. We study the link between early life circumstances, parental investments and child outcomes, over time and across multiple siblings in families in rural Northern Nigeria, where households reside in extreme poverty and sibling rivalry effects can be first order. We do so by evaluating a pre-natal intervention providing information and cash transfers to families triggered by the verified pregnancy of a target child. We track outcomes and child-specific parental inputs across older and younger siblings of the target child in 3600 families over four years. We find that unlike for the target child, stunting outcomes for older siblings do not improve, because they are too old when the intervention begins to gain from it in terms of height. We also document muted gains on height for younger siblings, and show this is because of endogenous responses to the intervention through shorter birth spacing between the target child and younger siblings, labor supply responses of mothers, and fade out of knowledge on specific peri-natal practices. However, on a raft of other outcomes such as health, nutrition and parental inputs more relevant outside the first 1000-days of life window, outcomes significantly shift forward for all siblings. Our results show parents behave as if to equalize inputs across siblings, despite differences in their physical endowments. Calculating the annualized IRR to the intervention based on this fuller set of family impacts, leads them to rise ten-fold over those based on target child outcomes alone.
Legacies of Conflict: Self-efficacy and the Formation of Conditional Trust
joint with Niklas Buehren (World Bank), Markus Goldstein (World Bank) and Andrea Smurra (UCL)
March 2023
Abstract Exposure to armed conflict in early life is a traumatic experience, affecting 400 million children worldwide. We combine theory, measurement and evidence to offer a new angle on the study of how psychological legacies of conflict mediate the relationship between exposure to conflict and the long-run formation of trust preferences. Our analysis is based on a sample of 4,200 women born during the Sierra Leonian civil war and surveyed 14 years later. We first introduce the notion of conditional trust in one-off anonymized exchange. We then develop a framework formalizing the link between exposure to conflict and trust. This makes precise what individuals have in mind when expressing conditional trust in others, and establishes the roles of post-traumatic growth and self-efficacy in linking conflict and trust. Taking the predictions to data, we show exposure to conflict significantly increases self-efficacy, and through this channel, conflict leads conditional trust to rise, and for outright trust of others to fall, relative to those never exposed to conflict. To further microfound how exposure to conflict translates into psychological legacies, we construct a granular typology of experiences of conflict, combining information on exposure to conflict, recall of victimization, and ages of exposure to conflict. We use this to show how direct exposure, memories and trauma, and narratives of conflict from others each distinctively shape self-efficacy. In discussing the external validity of our findings to other conflict scenarios, we show how our model and evidence can help reconcile heterogeneous findings across conflicts, and suggests avenues for future work on the more general role of psychological legacies from traumatic shocks early in life on the long-run formation of economic preferences.
Identifying Network Ties from Panel Data: Theory and an Application to Tax Competition
joint with Aureo de Paula (UCL) and Pedro CL Souza (Warwick)
January 2023
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 Generalized Method of Moments. We employ the method to study tax competition across US states. We find that 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 that the analysis of social interactions can be extended to economic realms where no network data exists.
Revised and resubmitted, Review of Economic Studies.
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)
July 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.
Revisions requested, Journal of Labor Economics.