Essays on developing human capital among disadvantaged populations [electronic resource]

This dissertation consists of three research papers that examine how to promote human capital, especially for more disadvantaged populations. The first chapter uses data from a field experiment conducted in Malawi to assess whether parents have inaccurate perceptions about their children's academic abilities, and whether parents' inaccurate perceptions distort their investments in their children's education. I find that the divergence between parents' beliefs about their children's achievement and their children's true achievement is large, and that this creates a wedge between parents' intended and actual educational investments. Providing parents with information significantly impacts their investments, causing them to become more closely aligned with their children's achievement. Poorer, less-educated parents have less accurate perceptions about their children's academic abilities than richer, more-educated parents, and update their beliefs more in response to improved information. Inaccurate perceptions may thus exacerbate inequalities in educational outcomes between richer and poorer families. The second chapter examines the effect of school accountability systems on teachers. A commonly-cited concern with holding schools accountable for student performance is that it could cause good teachers to leave low-performing schools. This chapter presents regression discontinuity estimates from New York City, which assigns schools grades based on student achievement, suggesting the opposite. At the bottom end of the grade distribution, lower accountability grades decrease teacher turnover, especially for high-quality teachers, and increase joiner teacher quality. One potential explanation is that accountability induces performance improvements at lower-graded schools. In contrast, at the top of the grade distribution, where accountability pressures are lower, lower grades have no turnover effects, but decrease joiner quality. The third chapter, co-authored with Pascaline Dupas and Jonathan Robinson, examines the efficacy of delivering targeted public health subsidies through existing government infrastructure by measuring the performance of free bed net distribution programs targeted towards pregnant women in Ghana, Kenya and Uganda. If implemented correctly, such subsidies have the potential to substantially decrease child mortality in developing countries. However, with weak governance, government workers may perform poorly, thereby undermining the programs' efficacy. While the Kenya and Uganda distribution schemes were government-led, the program in Ghana was part of a randomized controlled trial we put in place to evaluate three commonly proposed schemes to improve performance: vouchers (so that health workers do not have control over the subsidized products themselves); flat bonus pay for health workers charged with delivering the subsidies; and threats of top-down audits. We evaluate performance through a rich set of data, including (1) home surveys of eligible women, (2) informal interviews with community members, and (3) decoy "mystery client" visits. Overall, we find that local delivery is surprisingly effective: around 80% of eligible women received the subsidy, less than 2% of eligible women were asked for a bribe, and only 4.5% of ineligible clients were able to obtain a subsidized net. In the Ghana experiments, we find no effect of either bonus pay or audit threats, and the voucher scheme appears dominated: it does not reduce leakage but it reduces coverage among eligibles. Survey evidence suggests that antenatal nurses and midwives in all three countries are positively selected in terms of other-regarding preferences and intrinsic motivation, and that they perceive their job continuation as contingent on performance.

Keywords: Economics.
Advisor: Dupas Pascaline primary advisor. Thesis advisor
Abramitzky Ran advisor. Thesis advisor
Bernheim B. Douglas advisor. Thesis advisor
Hoxby Caroline Minter advisor. Thesis advisor