Most discussions about energy in the developing world quickly turn to the 1.3 billion people who don’t have access to electricity. Many initiatives are focused on serving these people, such as Kenya’s Last Mile Connectivity Project or the US’s ambitions of supporting 60 million new electricity connections through the Power Africa program.
I hear a lot less about the people who have an electricity connection but for whom reliability is bad. And, as anyone who has spent time in the developing world knows, poor reliability doesn’t just mean that the lights occasionally flicker. Whole neighborhoods can be left in darkness for hours and even days on end.
The importance of reliability – and not new connections – is particularly meaningful in cities, where nearly everyone has a connection, but reliability is poor. For example, the figure below, from a forthcoming working paper by my colleagues Ken Lee, Paul Gertler and Mushfiq Mobarak, summarizes data from 21 Sub-Saharan African cities. The share of city dwellers who have access is represented in the graph on the left – many are close to 100 percent, and almost all are above 75 percent (except the capital of Malawi). The graph on the right represents the share of those city dwellers who report that their electricity connections works “all the time” or “most of the time.” It’s less than 20 percent in Lagos, Nigeria, home to nearly 20 million people.
Cities are important because one of the starkest demographic trends in the developing world is urbanization. And, in my experience, a lot of rural families are tied to the urban economy – relying on remittances from the husband, older son, or uncle who has moved to the city.
The Reliability Measurement Gap
So, why is reliability the poor stepsister to energy connections? Why aren’t there more programs to promote reliability?
I believe a major reason is that reliability is really hard to measure. As my colleague Jay Taneja says in a recent working paper, “Before electricity reliability can be improved, it needs to be accurately measured.” You can’t fix what you can’t see.
Jay’s paper has some super interesting figures highlighting the difficulty measuring reliability in the developing world. For example, the graph below compares a common metric of outages (called SAIDI, for System Average Interruption Duration Index) measured two ways – as reported by utilities on the vertical axis and by their customers on the horizontal axis. Each point represents a country. If the utilities and their customers were reporting the same thing, the points would all lay on the dashed line. In fact, almost all of the points are below the line, indicating that the utilities are reporting one-seventh as many outages as their customers on average!
Luckily, Jay and a team of engineers at Berkeley are working on some really innovative, inexpensive ways to measure reliability using smartphones and low-cost sensors.
The Cost of Poor Reliability
Why might reliability be a big issue?
For one, poor reliability doesn’t just impact households, but also hospitals, factories, telecom systems, government buildings, etc., all of which are important to economic development. Around the world, non-residential customers use well over 50 percent of electricity, and over 70 percent in some of the major developing countries, including India, China and Brazil.
I spoke to an entrepreneur from Lagos last year who was trying to make a go of a company selling beauty products designed for the local market. It’s a business that has very little to do with energy. And yet, the conversation quickly turned to Lagos’ electricity problems. Not only did he have a backup generator, but his internet service provider had a backup generator, his accountant had a backup generator – you get the picture. To start a business in Lagos, you have to invest in a generator. This is a tax on doing business, which makes it hard for new businesses to start and for existing ones to grow.
We need more research to document just how much of a drag this is on the local economy, but I suspect it could be a big hindrance to growth.
Within the residential sector, this isn’t necessarily a story about allowing rich city dwellers to watch TV and keep their apartments air-conditioned. In fact, reliability may impact the poor more than the rich. The chart below was made by an enterprising Accra resident, who hired people to stand on street corners in different neighborhoods and record whether the nearby lights were on. (Another indication of just how starved people are for data on reliability.) The neighborhoods at the bottom of his chart, with 3 or fewer outages over the two-week period, are where the rich people live. I believe that the human observers were able to distinguish grid outages from local backup generators, although I’m not positive.
Finally, the pollution created by all of the backup generators is a major contributor to poor air quality. For example, my former graduate student Fiona Burlig pointed me to estimates from India suggesting that diesel generators contribute 10 to 20 percent of cities’ pollution, depending on the pollutant (here’s another source).
Considering the Trade-Offs Between Reliability and New Connections
Don’t get me wrong. I care about the 1.3 billion people who do not have electricity connections. They are no doubt some of the world’s poorest people. But, that’s only part of the energy access problem. And, I believe that we need to be open to the possibility that connecting fewer people and increasing reliability for existing customers is better for economic development than putting all our eggs in the connection basket. Remember, the already-connected customers include hospitals, schools, etc.
Kenya, for example, has made great strides connecting households to the grid in recent years. According to the latest reports, 15 million more people are connected to the grid now than 7 years ago. But, these newly connected consumers aren’t using much electricity – only one fifth of what the average household was using in 2009. This means that Kenya Power’s revenues per customer are dropping, just as it has added a bunch of new infrastructure to its system, infrastructure that it will need to maintain for years to come. It’s possible that building out the system will take resources away from improving the reliability.
There’s a lot of work to do. We need to figure out cost-effective ways to improve measurement technologies, identify the many varied causes of poor reliability, work with utilities to improve their systems for both preventative maintenance and triaging when they face reliability incidents. Those seem like jobs for engineers. Economists can provide estimates of the development benefits to investments in reliability as well as energy access, and they can identify ways to provide utilities with better incentives and more capital to invest in reliability. There are big payoffs to getting these answers right.
Catherine Wolfram is the Cora Jane Flood Professor of Business Administration at the Haas School of Business, University of California, Berkeley. During Academic year 2018-19, she will serve as the Acting Associate Dean for Academic Affairs at Berkeley Haas. She is the Program Director of the National Bureau of Economic Research's Environment and Energy Economics Program, Faculty Director of The E2e Project, a research organization focused on energy efficiency and a research affiliate at the Energy Institute at Haas. She is also an affiliated faculty member of in the Agriculture and Resource Economics department and the Energy and Resources Group at Berkeley.
Wolfram has published extensively on the economics of energy markets. Her work has analyzed rural electrification programs in the developing world, energy efficiency programs in the US, the effects of environmental regulation on energy markets and the impact of privatization and restructuring in the US and UK. She is currently implementing several randomized controlled trials to evaluate energy programs in the U.S., Ghana, and Kenya.
She received a PhD in Economics from MIT in 1996 and an AB from Harvard in 1989. Before joining the faculty at UC Berkeley, she was an Assistant Professor of Economics at Harvard.