We exploit random assignment of gender quotas for leadership positions on Indian village councils to show that prior exposure to a female leader is associated with electoral gains for women. After ten years of quotas, women are more likely to stand for, and win, elected positions in councils required to have a female chief councilor in the previous two elections. We provide experimental and survey evidence on one channel of influence—changes in voter attitudes. Prior exposure to a female chief councilor improves perceptions of female leader effectiveness and weakens stereotypes about gender roles in the public and domestic spheres.

A seven-year randomized evaluation suggests education subsidies reduce adolescent girls' dropout, pregnancy, and marriage but not sexually transmitted infection (STI). The government's HIV curriculum, which stresses abstinence until marriage, does not reduce pregnancy or STI. Both programs combined reduce STI more, but cut dropout and pregnancy less, than education subsidies alone. These results are inconsistent with a model of schooling and sexual behavior in which both pregnancy and STI are determined by one factor (unprotected sex), but consistent with a two-factor model in which choices between committed and casual relationships also affect these outcomes.

To the extent that students benefit from high-achieving peers, tracking will help strong students and hurt weak ones. However, all students may benefit if tracking allows teachers to better tailor their instruction level. Lower-achieving pupils are particularly likely to benefit from tracking when teachers have incentives to teach to the top of the distribution. We propose a simple model nesting these effects and test its implications in a randomized tracking experiment conducted with 121 primary schools in Kenya. While the direct effect of high-achieving peers is positive, tracking benefited lower-achieving pupils indirectly by allowing teachers to teach to their level.

We model farmers as facing small fixed costs of purchasing fertilizer and assume some are stochastically present biased and not fully sophisticated about this bias. Such farmers may procrastinate, postponing fertilizer purchases until later periods, when they may be too impatient to purchase fertilizer. Consistent with the model, many farmers in Western Kenya fail to take advantage of apparently profitable fertilizer investments, but they do invest in response to small, time-limited discounts on the cost of acquiring fertilizer (free delivery) just after harvest. Calibration suggests that this policy can yield higher welfare than either laissez-faire policies or heavy subsidies.

How High Are Rates of Return to Fertilizer? Evidence from Field Experiments in Kenya by Esther Duflo, Michael Kremer and Jonathan Robinson. Published in volume 98, issue 2, pages 482-88 of American Economic Review, May 2008

What are the determinants of health and of well-being? Income and wealth are clearly part of the story, but does access to health care have a large independent effect, as the advocates of more investment in health care, such as the World Health Organization’s Commission on Macroeconomics and Health (Commission on Macroeconomics and Health, 2001), have argued? This paper reports on a recent survey in a poor rural area of the state of Rajasthan in India intended to shed some light on this issue, where there was an attempt to use a set of interlocking surveys to collect data on health and economic status, as well as the public and private provision of health care.

In many regulated markets, private, third-party auditors are chosen and paid by the firms that they audit, potentially creating a conflict of interest. This article reports on a two-year field experiment in the Indian state of Gujarat that sought to curb such a conflict by altering the market structure for environmental audits of industrial plants to incentivize accurate reporting. There are three main results. First, the status quo system was largely corrupted, with auditors systematically reporting plant emissions just below the standard, although true emissions were typically higher. Second, the treatment caused auditors to report more truthfully and very significantly lowered the fraction of plants that were falsely reported as compliant with pollution standards. Third, treatment plants, in turn, reduced their pollution emissions. The results suggest reformed incentives for third-party auditors can improve their reporting and make regulation more effective.

High pollution persists in many developing countries despite strict environmental rules. We use a field experiment and a structural model to study how plant emission standards are enforced. In collaboration with an Indian environmental regulator, we experimentally doubled the rate of inspection for treatment plants and required that the extra inspections be assigned randomly. We find that treatment plants only slightly increased compliance. We hypothesize that this weak effect is due to poor targeting, since the random inspections in the treatment found fewer extreme violators than the regulator's own discretionary inspections. To unbundle the roles of extra inspections and the removal of discretion over what plants to target, we set out a model of environmental regulation where the regulator targets inspections, based on a signal of pollution, to maximize plant abatement. Using the experiment to identify key parameters of the model, we find that the regulator aggressively targets its discretionary inspections, to the degree that half of the plants receive fewer than one inspection per year, while plants expected to be the dirtiest may receive ten. Counterfactual simulations show that discretion in targeting helps enforcement: inspections that the regulator assigns cause three times more abatement than would the same number of randomly assigned inspections. Nonetheless, we find that the regulator's information on plant pollution is poor, and improvements in monitoring would reduce emissions.

Can we identify highly central individuals in a network without collecting network data, simply by asking community members? Can seeding information via such nominated individuals lead to significantly wider diffusion than via randomly chosen people, or even respected ones? In two separate large field experiments in India, we answer both questions in the affirmative. In particular, in 521 villages in Haryana, we provided information on monthly immunization camps to either randomly selected individuals (in some villages) or to individuals nominated by villagers as people who would be good at transmitting information (in other villages). We find that the number of children vaccinated every month is 22% higher in villages in which nominees received the information. We show that people’s knowledge of who are highly central individuals and good seeds can be explained by a model in which community members simply track how often they hear gossip about others. Indeed, we find in a third data set that nominated seeds are central in a network sense, and are not just those with many friends or in powerful positions.