Grady Killeen
- Incoming Assistant Professor, Kenneth C. Griffin Department of Economics, University of Chicago (2027)
- Postdoc, Development Innovation Lab, University of Chicago
I am a development economist. I primarily study topics related to industrial organization and firms. A second strand of my research studies the long-run effects of cash transfers.
I received my Ph.D. in economics from UC Berkeley in 2026.
Recent papers
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Risk Aversion and Barriers to Firm Growth: Experimental Evidence from Small Retailers
Job Market PaperCoverage: World Bank Development Impact, The Economic Misfit
Does risk aversion prevent firms in developing economies from making profitable but uncertain investments? Using a model and two field experiments with over 1,200 Kenyan firms, I study retailers' decisions to stock a new consumer product. First, an insurance contract that is strictly dominated under risk neutrality increases adoption from 20% to 30%. Second, a temporary supplier returns policy increases post-intervention stocking by 70%, through reduced belief uncertainty rather than higher expected profits. Third, increasing the continuation value of learning expands adoption by 88%. Results indicate that risk aversion constrains firm experimentation, limiting the retail diffusion of new products.
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A New Experimental Method for Estimating Demand for Non-market Goods: With an Application to the Value of a Statistical Life
This paper introduces a new method for estimating demand for non-market goods and applies it to the value of a statistical life (VSL) in Kenya. The approach updates beliefs about the life-saving efficacy of a product (helmets) and elicits product choice. This allows demand to be estimated from subjective beliefs rather than assuming rational expectations. The resulting VSL estimate is $523, near the lower end of Kenyan estimates. Standard methods produce skewed results, driven by violations of rational expectations. The findings rationalize weak demand for preventive health and highlight limited evidence and theoretical support for VSLs used in benefit-cost analysis.
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Can Cash Transfers Save Lives? Evidence from a Large-Scale Experiment in Kenya
Revise and Resubmit, Journal of Political EconomyCoverage: New York Times, NPR, The Guardian
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 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. These improvements appear to arise from better maternal health and nutrition, a 53% reduction in labor supply around the time of childbirth, and a 45% increase in hospital delivery. There is a transient 10% increase in fertility, but mortality reductions are largest in households receiving transfers after pregnancies began, ruling out selection bias. Mortality effects dissipate rapidly when cash is distributed more than three months from the birth. Mortality reductions are concentrated among households with limited (monetary) consumption gains, suggesting a trade-off between financial and health investments.
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Using satellites and phones to evaluate and promote agricultural technology adoption: Evidence from smallholder farms in India
Journal of Development Economics
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.