UC Berkeley

Low-income countries are expected to contribute almost all of the growth in global energy demand over the coming decades. A large body of research spanning several decades has generated a deep understanding of energy economics in the U.S.—but policy makers have little rigorous evidence about what optimal energy policy may look like in a setting where policy makers face pressures to simultaneously reduce poverty, stem growing inequality, and stimulate economic growth, while also protecting the environment. Second-best policy for correcting environmental externalities may look different in settings with frictions that are common in developing settings, such as credit constraints, the cognitive stress of poverty, and weak institutions.

Energy generation in low-income countries often generates large negative health consequences. But reliable energy has also facilitated higher levels of economic welfare than ever before: energy powers hospitals, schools, homes, transport for billions, and other industries that have enabled higher qualities of life and longer life expectancies. How can the billions of people who currently have no or low-quality access to electricity reach higher, safer, and healthier standards of living, while also minimizing the potential damages of environmental changes? And how can this be done given the political pressures, credit constraints, corruption, and other market failures that are common in low-income contexts? Motivated by the broader goal of reducing poverty and increasing welfare among the poor, my research attempts to inform policies that reduce poverty while protecting individuals against the environmental damages that have often accompanied economic growth through industrialization in the past two centuries.

In the first chapter, coauthored with Joshua Dean, we explore the roles of credit constraints and inattention in the under-adoption of high-return technologies. We study this question in the case of energy efficient cookstoves in Nairobi. Using a randomized field experiment with 1,000 households, we estimate a 300% average annual rate of return to investing in this technology, or $120 per year in fuel savings—around one month of income. Despite this, adoption rates are low: eliciting preferences using an incentive-compatible Becker-DeGroot-Marschak mechanism, we find that average willingness-to-pay (WTP) is only $12. Households would need to have a discount factor of 0.88 per week to rationalize this. To investigate what drives this puzzling pattern, we cross-randomize access to credit with two interventions designed to increase attention to the costs and benefits of adoption. Our first main finding is that credit doubles WTP and closes the energy efficiency gap over the period of the loan. Second, credit works in part through psychological mechanisms: around one-third of the total impact of credit is caused by inattention to loan payments. We find no evidence of inattention to energy savings. These findings have implications for second-best regulation of pollution externalities using subsidies versus taxes. These results contribute to the debate on the efficacy of taxation versus technology subsidies in correcting environmental externalities: in low-income contexts, where credit constraints are common, Pigovian taxation alone may not be the optimal policy. Private benefits and avoided environmental damages generate average welfare gains of $600 for each stove adopted and used for two years. A subsidy would have a marginal value of public funds of $19 per $1 spent. Low- and middle-income countries will propel global energy demand in coming decades, increasing costs for the poor and straining energy systems, and credit constraints will exacerbate deadweight loss by limiting the adoption of energy efficient technologies. We show that technology subsidies correct environmental externalities more efficiently than Pigovian taxation alone in these settings.

In the second chapter I study how temperature affects household energy demand in low-income countries. I use 132,375,282 hourly electricity consumption observations from 5,975 households in South Africa to estimate the causal effects of short-term temperature changes on household electricity consumption. The estimates flexibly identify a constant log-linear temperature response—for every 1C increase in temperature, electricity consumption decreases by 4.1% among temperatures below the heating threshold but increases by 8.1% among temperatures above the cooling threshold. This relationship is driven more strongly by seasonal than hourly temperature changes. Holding all else constant, a 3.25C increase in temperatures would reduce electricity consumption by 1,093.4 kWh (6.2%) per year per household. Widespread use of electric heating due to limited residential gas heating infrastructure likely drives this. These results point to important regional heterogeneity in how temperature increases may affect household energy demand in the coming decades.

In the third chapter, coauthored with Eric Hsu, Oliver Kim, Edward Miguel, Felipe Vial, and Catherine Wolfram, we study how political favoritism shapes the provision of public goods. We study the implementation of Kenya’s Last Mile Connectivity Project, a large-scale program to connect all households in Kenya to electricity. Using administrative construction data and voting data from the 2013 and 2017 presidential elections, we find evidence that sites in wards that voted for the current president in 2013 are more likely to be included in the program, and that construction at these sites proceeds on average more quickly than those that voted for the opposition---a pattern consistent with clientelistic behavior around the election cycle. To account for unobservables that may threaten identification, we repeat our analysis using only adjacent electoral wards, where unobservable characteristics are less likely to differ, and find similar results.