Economists typically view firms as risk neutral. Yet many enterprises, especially in low and middle-income economies, are small and owner-operated, making household consumption sensitive to business risk. As a result, owners' risk preferences may influence firm decisions. This paper demonstrates that small retailers in Kenya are risk averse, leading them to under-adopt a new product when they face uncertain demand. I model risk averse firms who learn about demand through stocking decisions, then test the model's predictions using two field experiments. The first establishes that risk aversion affects the stocking decisions of enterprises. I test for risk aversion by offering treated firms an insurance contract that lowers expected profits from a new product while reducing the risk of losses. This leads to a 50% increase in adoption, rejecting risk neutrality. The second experiment shows that temporarily reducing inventory risk leads firms to permanently stock a profitable new product because they overcome demand uncertainty through learning. These results show that risk aversion in firms can impede product diffusion, potentially limiting growth.

Economists often study non-market goods such as health and air quality. This paper introduces a new method to estimate demand for such amenities and applies it to measure the value of a statistical life (VSL) in Kenya. My approach is to update beliefs about the life-saving efficacy of a product (a motorcycle helmet) and elicit product choice. This generates instruments allowing one to use subjective beliefs to estimate demand, rather than assuming rational expectations. This method does not require beliefs to be reported error-free but does require classical mismeasurement. I validate this assumption using features of the experimental design. The estimated VSL is $224, near the left tail of Kenyan estimates. Standard methods for estimating VSL produce skewed results, driven by severe violations of rational expectations. These findings help explain low observed demand for many health products and suggest that directing more development aid towards consumption may increase welfare.

We estimate the impacts of large-scale unconditional cash transfers on child survival. One-time transfers of USD 1000 were provided to over 10,500 poor households across 653 randomized villages in Kenya. We collected census data on over 100,000 births, including on mortality and cause of death, and detailed data on household health behaviors. Unconditional cash transfers (accounting for spillovers) lead to 48% fewer infant deaths before age one and 45% fewer child deaths before age five. Detailed data on cause of death, transfer timing relative to birth, and the location of health facilities indicate that unconditional cash transfers and access to delivery care are complements in generating mortality reductions: the largest gains are estimated in neonatal and maternal causes of death largely preventable by appropriate obstetric care and among households living close to physician-staffed facilities and those who receive the transfer around the time of birth, and treatment leads to a large increase in hospital deliveries (by 45%). The infant and child mortality declines are concentrated among poorer households with below median assets or predicted consumption. The transfers also result in a substantial decline of 51% in female labor supply in the three months before and the three months after a birth, and improved child nutrition. Infant and child mortality largely revert to pre-program levels after cash transfers end. Despite not being the main aim of the original program, we show that unconditional cash transfers in this setting may be a cost-effective way to reduce infant and child deaths.

This paper evaluates a low-cost, customized soil nutrient management advisory service in India. As a methodological contribution, we examine whether and in which settings satellite measurements may be effective at estimating both agricultural yields and treatment effects. The intervention improves self-reported fertilizer management practices, though not enough to measurably affect yields. Satellite measurements calibrated using OLS produce more precise point estimates than farmer-reported data, suggesting power gains. However, linear models, common in the literature, likely produce biased estimates. We propose an alternative procedure, using two-stage least squares. In settings without attrition, this approach obtains lower statistical power than self-reported yields; in settings with differential attrition, it may substantially increase power. We include a “cookbook” and code that should allow other researchers to use remote sensing for yield estimation and program evaluation.

In low and middle-income (LMIC) countries, businesses often use technologies inside the frontier, innovate less, and slowly adopt new products and technologies (Cirera et al. 2022). The reasons for these facts are not well understood, particularly for small and microenterprises (e.g. Atkin et al. 2017). We investigate whether a lack of institutions to protect the value of intellectual property contributes to these facts. High-income economies tend to have strong patent systems to promote discoveries, and regulators permit exclusive dealing in retail environments due to similar forces. But LMIC firms are often informal and undifferentiated, meaning neighbours are likely to adopt discoveries of their competitors without compensation. This project focuses on this problem in the case of retail firms’ decision to adopt a new product-- a setting where firms face risk ex-ante because they do not know if demand will exist, but, ex-post, competitors can learn if demand is high by observing the first mover. We examine whether offering retailers exclusive access to supply of a new product promotes adoption. Our study also tests whether firms are colluding so that if there is a null result we can understand if it is due to collusion, a possible upside to the finding that some markets in LMICs are uncompetitive (Bergquist and Dinerstein 2020).

Recent studies document positive short-run effects of unconditional cash transfers (UCTs) on cash recipients and spillover effects on non-recipients. But modest sample sizes and challenges with tracking households over time have limited research on the long-run effects of UCTs. We study the long-run effects of the Kenya General Equilibrium Study (KGES) on recipient households and the local economy using census and survey data collected up to ten years post-transfers. An “endline 2” completed 4-7 years after the transfers collected census data from each household and enterprise in the study area, and a representative survey of more than 10,000 households and firms obtained more detailed consumption and production measures for a subset, including from those that migrated out of the study area. We collected this same information in an “endline 3” completed 7-10 years after the experimental start. Preliminary results from endline 2 show persistent consumption gains among recipients and expansion of non-farm enterprise revenue. Ongoing analysis examines whether these effects persisted to endline 3 and aims to estimate long-run transfer multipliers.