Big Push Pro-poor Policies and Economic Preferences: Evidence from a Partial Population Experiment
joint with Adnan.Q.Khan (LSE), Nicolas Cerkez (UCL) and Anam Schoaib (CERP)
Abstract Big push pro-poor policies have been shown to cause lasting improvements in the economic outcomes of beneficiaries. In this paper we move beyond economic impacts to study whether such interventions impact three interlinked economic preferences: redistributive preferences, pro-market beliefs, and trust in neighbors. We do so using an experiment tracking 15,600 rural households in Punjab, Pakistan. Villages are randomly assigned to receive an intervention where the poor are either offered a one-time asset transfer of value $620 or an equivalent valued one-off unconditional cash transfer. Within villages, we randomize which of the poor receive the transfer. Our partial population experiment tracks treated poor, not treated poor and not poor households for four years. The treated poor have immediate gains in economic outcomes following the transfers, with gains persisting, but not accumulating further. The interventions also cause persistent reductions in village consumption inequality. Given this backdrop, we examine impacts on economic preferences. Two-years post intervention, the treated poor are less likely to favor redistribution, hold stronger pro-market beliefs, and increase trust in neighbors. This pattern of impacts also holds for the not treated poor (despite them being overtaken by the treated poor in economic standing) and the not poor. Hence shifts in economic preferences do not depend on whether households are direct beneficiaries, but are rather shaped by village-wide exposure to pro-poor policies. Four-years post intervention, the preferences of all groups no longer differ from controls. Hence there is no virtuous cycle feeding back from shifting preferences to driving forward economic outcomes. We provide suggestive evidence that shifts in economic preferences do not persist because they are driven by changes in economic outcomes, not their levels.
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)
Abstract Exposure to armed conflict in early life is a traumatic experience, affecting 400 million children worldwide. We combine theory, measurement and evidence to study 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 Leonean 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 that 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. Finally, we show how our model and evidence can help reconcile heterogeneous findings across conflict scenarios, 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.
Families as Drivers of Inequality: Experimental Evidence from an Early Childhood Intervention
joint with Pedro Carneiro (UCL) and Francesca Salvati (Essex)
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.
Identifying Network Ties from Panel Data: Theory and an Application to Tax Competition
joint with Aureo de Paula (UCL) and Pedro CL Souza (Warwick)
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.
Revisions requested (second round), Review of Economic Studies.