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I am an applied microeconomist whose primary fields are development and public. My Job Market Paper, `Insurance Networks and Endogenous Poverty Traps', investigates why households in developing countries invest so little. This is a puzzle, as high return investments are available, and households belong to risk sharing networks which have the resources needed to invest. This paper provides a novel explanation for this puzzle: informal risk sharing can crowd out investment. I extend the canonical model of limited commitment in risk sharing networks to allow for lumpy investment, and show that together these features generate a poverty trap. I verify key empirical predictions of the model using data from a large scale asset transfer program in 1400 Bangladeshi villages. My results highlight how capital transfer programs can be made more cost-effective by targeting communities at the threshold of the aggregate poverty trap.
Other work in my thesis explores (i) how one can use data on networks to understand social spillover effects, including in the presence of endogenous network formation and measurement error; (ii) how the trade-off between economic and cultural incentives determines whether heterogeneous communities, such as migrants to the US, choose to integrate or segregate; and (iii) the impact of migrants’ initial networks on later labour market outcomes.
Whilst studying for my PhD at University College London, I have also been working part-time at the Institute for Fiscal Studies. As part of that work I coauthored a number of policy reports and comments on environmental taxation in the UK, and more recently I have been involved in issues of Tax Compliance. Using data from HMRC (the UK tax office), I am investigating how tax audits affect long term tax reporting, and in future work how the effects of audits spillover onto coworkers, business partners, and family members.
- Development Economics
- Networks and Interactions
- Public Economics
Insurance Networks and Endogenous Poverty Traps
Abstract
Poor households often do not undertake profitable investments. This is so even when their informal risk sharing networks have the resources to allow one of their members to make such investments. This paper provides a novel explanation for this puzzle: informal risk sharing can crowd out investment. I extend the canonical model of limited commitment in risk sharing networks to allow for lumpy investment. The key insight is that the cost of losing insurance is lower for a household that has invested, since it has an additional stream of income, limiting its ability to credibly promise future transfers, so network partners demand transfers today and investment does not take place. The model generates two key predictions: there exists a non-linear relationship between total income and investment at the network level – namely there is a network level poverty trap – and there is an inverse U-shaped relationship between network income inequality and investment. I test these predictions using a randomised control trial in Bangladesh, that provided capital transfers to the poorest households. The data covers 27,000 households from 1400 villages, and contains information on risk sharing networks, income and investment. I exploit variation in the number of program recipients in a network to identify the threshold level of capital provision needed for the program to move the network out of a poverty trap and generate further investment. I also verify additional predictions of the model and rule out alternative explanations. My results highlight how capital transfer programs can be made more cost-effective by targeting communities at the threshold of the aggregate poverty trap.
- Prof Sir Richard Blundell
- Prof Imran Rasul
- Prof Orazio Attanasio
- Prof Aureo de Paula