Susanna B. Berkouwer

Susanna Berkouwer (2023), Money or Power? Choosing Covid-19 Aid in Kenya, Energy Economics, 127 (). https://doi.org/10.1016/j.eneco.2023.107036

Susanna Berkouwer and Joshua Dean (2022), Credit and Attention in the Adoption of Profitable Energy Efficient Technologies in Kenya, American Economic Review, 112 (), pp. 3291-3330. 10.1257/aer.20210766

Abstract: We study an energy efficient charcoal cookstove in an experiment with 1,000 households in Nairobi. We estimate a 39 percent reduction in charcoal spending, which matches engineering estimates, generating a 295 percent annual return. Despite fuel savings of $237 over the stove's two-year lifespan—and $295 in emissions reductions—households are only willing to pay $12. Drawing attention to energy savings does not increase demand. However, a loan more than doubles willingness to pay: credit constraints prevent adoption of privately optimal technologies. Energy efficient technologies could drive sustainable development by slowing greenhouse emissions while saving households money.

Susanna Berkouwer, Catherine Wolfram, Pierre Biscaye, Steve Puller (2022), Disbursing emergency relief through utilities: Evidence from Ghana, Journal of Development Economics.

Abstract: We provide descriptive evidence on the challenges in efficiently, effectively, and fairly dis- tributing in-kind electricity transfers to households. We collect panel data from 1,200 households eligible for Ghana’s COVID-19 electricity relief program. Distributing relief through electric- ity transfers enabled an immediate response to the crisis. Theoretical efficiency concerns are mitigated because transfers were inframarginal and storable for most households. Transfer re- ceipt may have increased support for the governing party, possibly due to obfuscation of the program’s financial burden. However, the program was regressive in design, and implemen- tation challenges—delays, technological hurdles, information constraints, and the targeting of meters rather than households—add to inefficiency and regressivity. Households receiving the least average relief are those who use less electricity, pay a landlord or other intermediary for electricity, or share an electricity meter—characteristics of low-income households. Program implementation challenges were just as important as design features in determining program costs and benefits.

Susanna Berkouwer (2020), Electric Heating and the Effects of Temperature on Household Electricity Consumption in South Africa, The Energy Journal, 41 (4), pp. 209-230. 10.5547/01956574.41.4.sber

Abstract: How does temperature affect household energy demand in low-income countries? This paper uses 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 1°C 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 3.25°C 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.

Susanna Berkouwer, Noah Klugman, Joshua Adkins, Catherine Wolfram, Jay Taneja, Prabal Dutta (2019), Hardware, apps, and surveys at scale: Insights from measuring grid reliability in Accra, Ghana, ACM Conference on Computing and Sustainable Societies (COMPASS). https://doi.org/10.1145/3314344.3332482

Abstract: The vision of sensor systems that collect critical and previously ungathered information about the world is often only realized when sensors, students, and subjects move outside the academic laboratory. However, deployments at even the smallest scales introduce complexities and risks that can be difficult for a research team to anticipate. Over the past year, our interdisciplinary team of engineers and economists has been designing, deploying, and operating a large sensor network in Accra, Ghana that measures power outages and quality at households and firms. This network consists of 457 custom sensors, over 3,000 mobile app instances, thousands of participant surveys, and custom user incentive and deployment management systems. In part, this deployment supports an evaluation of the impacts of investments in the grid on reliability and the subsequent effects of improvements in reliability on socioeconomic well-being. We report our experiences as we move from performing small pilot deployments to our current scale, attempting to identify the pain points at each stage of the deployment. Finally, we extract high-level observations and lessons learned from our deployment activities, which we wish we had originally known when forecasting budgets, human resources, and project timelines. These insights will be critical as we look toward scaling our deployment to the entire city of Accra and beyond, and we hope that they will encourage and support other researchers looking to measure highly granular information about our world’s critical systems.