Here are some of my current research projects.

For more: See my CV.

Targeting the Poor and Vulnerable: A Re-analysis of a Field Experiment in Indonesia

Community wealth ranking methods, in which communities identify the poorest households to receive a targeted transfer, are of interest in the targeting literature, as they leverage community information about households’ welfare that may be difficult or costly for researchers to observe. In an experiment in Indonesia, Alatas et al. (2012) compare the rankings from a traditional proxy means test (PMT), in which easily observable assets are used to predict consumption levels, and community rankings in identifying households with the lowest per capita total consumption. They find PMT rankings better predict consumption, and conclude that the community appears to target transfers based on an alternate conception of poverty. However, it is not obvious that total consumption is the appropriate measure of welfare for comparing these methods, as utility changes will only correspond directly with changes in total consumption if utility is both homothetic and additively separable, which the data seems to reject. We claim that an index of the marginal utility of expenditure (IMUE) may better capture changes in households’ welfare from receiving transfers. Using methods from Ligon (2019) and data from Alatas et al. (2012), we test if there is evidence that communities target transfers based on an IMUE rather than only total consumption, and consider other factors which affect community rankings. Preliminary results show evidence that IMUE rankings help to explain community rankings even after controlling for total consumption rankings and PMT rankings.

Community-based targeting (CBT) methods are commonly used throughout the developing world to identify the poorest households, for the purpose of targeting anti-poverty programs. These methods rely on community members providing information about the relative rankings of other households in their community. Notably, welfare rankings of households produced by CBT methods often differ greatly from rankings based on other standard welfare metrics. While this may be because community members have a more contextually appropriate or utility-based notion of welfare, it also could be because community members have limited information on their neighbors, or because they have other preferences that enter into their CBT ranking decisions. Through a set of lab-in-the-field exercises with respondents in Central Java, Indonesia, I attempt to understand what welfare information households have about their neighbors, what households' preferences are regarding which neighbords receive program transfers, and how such information and preferences are reflected in CBT rankings. The results of this experiment could help policymakers to better understand CBT processes and if/when they should be used for targeting.

We estimate California residents' preferences and willingness to pay (WTP) for current beverage container recycling methods, including curbside pick-up services, drop-off at government-subsidized recycling centers, and drop-off at non-subsidized centers. Using a representative online and telephone survey of California households, we estimate a discrete choice model that identifies: the California Redemption Value (CRV) refund amount (paid to consumers only if they recycle at drop-off centers), the volume of recyclable material generated by the household, and the effort associated with bringing recyclable materials to recycling centers, as key attributes explaining consumers' beverage container disposal decisions. Additionally, we use counterfactual policy analysis to show that increasing the CRV amount increases overall recycling rates, with the largest changes in consumer surplus accruing to inframarginal consumers, who are on the boundary between taking containers to recycling centers and recycling using curbside pick-up, namely white and higher income consumers. Conversely, we show that eliminating government-subsidized drop-off centers does not significantly alter consumer surplus for any major demographic group, and has little impact on recycling rates.

Introducing quality certification in staple food markets in Sub-Saharan Africa: A review of evidence (with Gashaw Abate, Tanguy Bernard, Alain de Janvry, and Elisabeth Sadoulet)

Third party quality certification can be used reduce transaction frictions caused by asymmetric information in value chains. Such certification may help to secure the competitiveness of smallholder farmers in domestic markets for staple crops in Sub-Saharan Africa (SSA), in the face of rising competition with high quality imports. Yet, while frequent in high value export crops, quality certification is still rare for staple crops. To understand why this discrepancy persists, we develop a model with four sufficient conditions for the functionality of certification in a value chain—-willingness to pay for quality by downstream agents, upstream competition among traders with pass-through of quality price premiums to farmers, existence of cost-effective certification, and farmers' capacity to respond to certification by enhancing quality. We show that if these conditions hold, certification should theoretically lead to farmers: receiving higher prices for higher quality goods, increasing investment in quality-enhancing inputs, and experiencing welfare gains in response to this quality enhancement. To see if these conditions and results hold in practice, we consult the literature and a novel diagnostic survey of experts in 20 SSA countries. We find that while certification systems exist in most countries surveyed, evidence of downstream willingness to pay for quality and of price premiums paid to farmers for quality is mixed. However, in cases where quality price premiums do exist, we observe producers responding by enhancing quality. We conclude that policymakers can promote quality certification in staple chains by first ensuring the four conditions we identify hold.

Understanding Gender-Specific Constraints to Agricultural Technology: Evidence from Cassava Farming in Kenya (with Ethan Ligon and Muthoni Ng'ang'a)

Female subsistence farmers in developing countries often have lower levels of agricultural productivity than men, partially due to lower adoption rates of agricultural technologies. These lower adoption rates may be due to lack of physical access to new technologies or lack of access to information about new technologies, among other explanations. In this study, we consider these two classes of explanations of low technology use among females, and consider the relative impacts of interventions designed to combat each. Specifically, we consider the technology of improved cassava in Murang’a County, Kenya, a more climate-resistant maize substitute, which has been underutilized especially by female farmers. Using a randomized control trial with a 2x2 matrix treatment design, we test the effects on cassava adoption by female farmers of two interventions: delivering cassava seeds directly to female farmers at their homes (improved access), and hiring female “lead farmers,” to diffuse information about cassava seeds (improved information access), as well as explore complementarities between these interventions. The results of this study will be of critical use to policymakers with the goal of improving agricultural productivity of female farmers in this setting, but who may face resource constraints in implementing policies to do so.