Powering development, stabilisation and conservation?
The impact of electricity roll-out by Virunga Alliance in Eastern Congo
This research project measures the impact of electricity provision on economic development, security and conservation. Our case study focuses on rural and urban communities nearby Virunga National Park, in North-Kivu, DR Congo. Impoverished by two decades of armed conflict, the communities complement their livelihoods with the park’s resources to make ends meet. These resources are also illicitly exploited by at least eight armed groups that have their hideouts within the park’s boundaries. The electricity rollout is implemented by Virunga Alliance, a public-private partnership that seeks to bring about security and conservation through development. According to Virunga’s theory of change, electrification will spur development, which will in turn reduce people’s reliance on the park’s resources as well as their support for, and participation in, rebel groups. The theory of change finds support in the literature, but needs further testing.
Virunga Alliance is rolling out 100 megawatts (MW) electricityover a multi-year period. Early 2019, about 10% of the targeted 100 MW was being generated by two hydropower plants: Mutwanga I and Matebe, located in the territories of Beni and Rutshuru (see the map below). Two plants with a combined capacity of 14.3MW become operational in the course of 2019-2021. In the longer term, five additional hydropower plants with a combined capacity of about 70MW are scheduled to be constructed, bringing the total estimated number of inhabitants in the rural and urban catchment area to 500,000 and 1 million, respectively.
The impact evaluation
To learn about the causal effect of electrification, we designed an impact evaluation that exploits the gradual rollout of electricity, in combination with a difference-in-differences estimation. Concretely, the impact will be measured by comparing time trends in socio-economic development, conservation and security across treatment and control localities. The treatment localities have been connected in the period between January 2019 and December 2021. The time trends will be measured by means of a pre-treatment and post-treatment census and survey.
We completed baseline data collection in Beni territory, Goma, and Lubero territory. To this end we trained a team of locally recruited enumerators.
In total, the baseline data contains census information on approximately 50,000 households and 2,500 firms, and a detailed structured survey among a stratified random sample of almost 2,000 households and 700 firms.
The map below presents the baseline census data for one locality in Beni territory. The blue dots indicate the location of households, green dots indicate firms and red dots indicate institutions.
We registered a pre-analysis plan which is available here.
While the collection of follow-up data is still ongoing, the core research project led to several spin-offs.
1. Ebola vs Covid-19
In April 2020, Eastern Democratic Republic of Congo was facing two major infectious disease outbreaks: Covid-19 and Ebola Virus Disease (EVD). To study the socioeconomic impact of both diseases, we conducted a phone survey with subsamples of our respondents in Goma and Beni, and a new sample of respondents from Rutshuru territory. While 3,470 EVD cases and 2,287 EVD deaths were confirmed since August 2018, self-reported impacts of EVD on revenues, access to food and behavior were limited. In contrast, only 251 Covid-19 cases were reported as of July 22nd but respondents reported sizable effects on livelihoods, especially in the large urban hub, in part driven by substantial job losses. Our results show that different infectious disease outbreaks can have very different effects, largely unrelated to case numbers of the disease. Moderately lethal but highly transmissible viruses such as Covid-19 can trigger a steep economic downturn, especially in areas with high economic interconnectedness, reflecting both national and international policies to contain the pandemic.
2. Nyiragongo Eruption
On May, 22, 2012 the Nyiragongo volcano, located at the outskirts of Goma erupted. Following a series of earthquakes, there were concerns that the city could be further affected. Hence, on May, 27, 2021 an evacuation order was given for 10 city areas in Goma. The evacuation order was lifted on June, 7, 2021. Both the eruption and the risk for subsequent eruption triggered a refugee flow of people seeking safety. We study how Goma residents coped with the eruption and evacuation order. Who decided to leave, or stay behind? How did the evacuation order and the relative risk of exposure to the lava stream affect the decision to flee? Did this decision vary across individuals part of the same household? If so, why? How did people who fled fulfil their basic needs in terms of shelter, food, and water? To answer these questions, we conducted interviews with 642 respondents who were present in Goma at the time of the eruption.
Elias Maombi analysed these data in his Master Dissertation “Flee or stay? Exploring the intra-household decision to flee in the face of the 2021 volcano eruption in Goma, Eastern DRC”. His dissertation won The Prize for Global Research awarded by the province of Antwerp. We are now transforming this dissertation into an academic article. Check out Elias’ short video on his prize-winning research.
3. Atlas AI
We have started collaborating with Atlas AI – a University of Stanford spin-off specialized in applying Artificial Intelligence techniques to develop better quality and more localized socioeconomic measures in data sparse environments. Our collaboration is benefiting from a Wellspring Philanthropic Fund grant to explore the extent to which satellite- and machine learning-based estimates can complement survey-based outcome measurements. For instance, we will conduct a complementary impact assessment of electrification relying on Atlas AI’s localized measures of asset wealth. In addition, we are exploring the possibility of using high-resolution imagery to develop new machine learning pipelines to identify building construction and quality characteristics, as well as locate exact places and times where deforestation and charcoal production take place.
This spinoff has become so large that it merits a separate research project page.
N. Stoop, S. Desbureaux, A. Kaota, E. Lunanga, M. Verpoorten. 2020 “Covid-19 vs. Ebola: impact on households and SMEs in Nord Kivu, DR Congo” World Development PDF replication