Dr. Susanna Berkouwer is an Assistant Professor of Business Economics and Public Policy at Wharton, specializing in energy, environment, and development economics. Current research projects include energy efficiency adoption, the economic impacts of power outages, the political economy of infrastructure construction, climate change and electricity consumption, and carbon taxes under credit market failures.
Susanna holds a PhD from UC Berkeley, an MA from Yale University, and a BSc from the University College London. They worked as a Research Fellow at Harvard University’s Evidence for Policy Design prior to graduate school.
Many low-income country governments hire contractors to carry out large infrastructure projects, as they often lack the capacity to implement these themselves. At 14.5% of GDP, low-income countries have the highest share of public procurement in their economies (World Bank 2017). At the same time, low-income countries often have limited capacity to oversee public projects, which can result in low-quality infrastructure and leakage of public funds.
In 2015, Kenya’s President Kenyatta launched the Last Mile Connectivity Project (LMCP), whose goal was “to connect one million new customers to electricity each year” and achieve universal household electricity access by 2020. The USD 500 million program — one of Kenya’s largest public programs, financed largely by international aid agencies — would extend Kenya’s low voltage network to every household located within 600 meters of more than 13,000 sites nationwide. The program also sought to reduce red tape. The old process of applying for electricity — often requiring months of paperwork — would be replaced by a system where Kenya Power contractors initiate connections, with minimal effort from households.
Concerns around corruption are widely thought to threaten the quality, cost, timeliness, and equity of the construction process, and contribute to significant leakage The LMCP is just one example of many infrastructure projects financed by international agencies. To prevent corruption and improve construction quality, such projects are often accompanied by stringent conditions over how local implementing agencies are to use these funds. But do donor conditions actually improve infrastructure quality on the ground? And, could additional independent monitoring improve accountability?
(June 2020). Credit and attention in the adoption of profitable energy efficient technologies in Kenya, forthcoming.
What roles do credit constraints and inattention play 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. 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. Private benefits and avoided environmental damages generate average benefits of $600 for each stove adopted and used for two years.
(February 2019). Electric Heating and the Effects of Temperature on Household Electricity Consumption in South Africa. The Energy Journal, 41(4).
How does temperature affect 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 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.