Several decades ago, the most common ways of thinking about problems of poor people in low-income countries involved ideas like the \”poverty trap\” and the \”dual economy.\” The \”poverty trap\” was the idea low-income countries were close to subsistence, so it was hard for them to save and make the investments that would lead to long-term growth. The \”dual economy\” idea was that low-income countries had both traditional and a modern parts of their economy, but the traditional part had large numbers of subsistence-level workers. Thus, if or when the modern part of the economy expanded, it could draw on this large pool of subsistence level workers and so there was no economic pressure for subsistence wages to rise. In either case, a common policy prescription was that low-income countries needed a big infusion of capital, probably from a source like the World Bank, to jump-start their economies into growth.

These older theories of economic development captured some elements of global poverty, but in many of their details and implications have proved unsatisfactory for the modern world. (Here\’s an essay on \”poverty trap\” thinking, and another on \”dual economy\” thinking.) For example, it turns out that low-income countries often do have sufficient saving to make investments in the future. Also, in a globalizing economy, flows of private investment capital along with remittances sent back home from emigrants far outstrip official development assistance. Moreover, there have clearly been success stories in which some low-income countries have escaped the poverty trap and the dual economy and moved to rapid growth, including China, India, other nations of east Asia, Botswana, and so on. 
Of course, it remains important that low-income countries avoid strangling their own economies with macroeconomic mismanagement, overregulation, or corruption. But a main focus of thinking about economic development shifted from how to funnel more resources to these countries to what kind of assistance would be most effective for the lives of the poor. The 2019 Nobel prize in economics was awarded “for their experimental approach to alleviating global poverty” to Abhijit Banerjee, Esther Duflo, and Michael Kremer.  To understand the work, the Nobel committee publishes two useful starting points: a \”Popular Science\” easy-to-read overview called \”Research to help the world’s poor,\” and a longer and more detailed\”Scientific Background\” essay on \”Understanding Development and Poverty Alleviation.\”

In thinking about the power of their research, it\’s perhaps useful to hearken back to long-ago discussions of basic science experiments. For example, back in 1881 Louis Pasteur wanted to test his vaccine for sheep anthrax. He exposed 50 sheep to anthrax. Of those 50, half chosen at random had been vaccinated. The vaccinated sheep lived and others died. 
Social scientists have in some cases been able to use randomized trials in the past. As one recent example, the state of Oregon wanted to expand Medicaid coverage back in 2008, but it only had funding to cover an additional 10,000 people. It chose those people through a lottery, and thus set up an experiment about how having health insurance affected the health and finances of the working poor (for discussions of some results, see here and here). In other cases, when certain charter high schools are oversubscribed and use a lottery to choose students, it sets up a random experiment for comparing students who gained admission to those schools with those who did not. 
The 2019 laureates took this ideas of social science experiments and brought it to issues of poverty and economic development. They went to India and Kenya and low-income countries around the world. They arranged with state and local governments to carry out experiments where, say, 200 villages would be selected, and then 100 of those villages at random would receive a certain policy intervention. Just dealing with the logistics of making this happen–for different interventions, in different places–would deserve a Nobel prize by itself. 
Many of the individual experiments focus on quite specific policies. However, as a number of these experimental results accumulate, broader lessons become clear. For example, consider the question of how to improve educational outcomes in low-income countries. Is the problem a lack of textbooks? A lack of lunches? Absent teachers? Low-quality teachers? Irregular student attendance? An overly rigid curriculum? A lack of lights at home that make it hard for students to study? Once you start thinking along these lines, you can think about randomized experiments that address each of these factors and others, separately and in various combinations. From the Nobel committee\’s \”Popular Science Background\”:

Kremer and his colleagues took a large number of schools that needed considerable support and randomly divided them into different groups. The schools in these groups all received extra resources, but in different forms and at different times. In one study, one group was given more textbooks, while another study examined free school meals. Because chance determined which school got what, there were no average differences between the different groups at the start of the experiment. The researchers could thus credibly link later differences in learning outcomes to the various forms of support. The experiments showed that neither more textbooks nor free school meals made any difference to learning outcomes. If the textbooks had any positive effect, it only applied to the very best pupils. 

Later field experiments have shown that the primary problem in many low-income countries is not a lack of resources. Instead, the biggest problem is that teaching is not sufficiently adapted to the pupils’ needs. In the first of these experiments, Banerjee, Duflo et al. studied remedial tutoring programmes for pupils in two Indian cities. Schools in Mumbai and Vadodara were given access to new teaching assistants who would support children with special needs. These schools were ingeniously and randomly placed in different groups, allowing the researchers to credibly measure the effects of teaching assistants. The experiment clearly showed that help targeting the weakest pupils was an effective measure in the short and medium term.

Such experiments have been done in a wide range of contexts. For example, what about issues of improving health? 

One important issue is whether medicine and healthcare should be charged for and, if so, what they should cost. A field experiment by Kremer and co-author investigated how the demand for deworming pills for parasitic infections was affected by price. They found that 75 per cent of parents gave their children these pills when the medicine was free, compared to 18 per cent when they cost less than a US dollar, which is still heavily subsidised. Subsequently, many similar experiments have found the same thing: poor people are extremely price-sensitive regarding investments in preventive healthcare. …

Low service quality is another explanation why poor families invest so little in preventive measures. One example is that staff at the health centres that are responsible for vaccinations are often absent from work. Banerjee, Duflo et al. investigated whether mobile vaccination clinics – where the care staff were always on site – could fix this problem. Vaccination rates tripled in the villages that were randomly selected to have access to these clinics, at 18 per cent compared to 6 per cent. This increased further, to 39 per cent, if families received a bag of lentils as a bonus when they vaccinated their children. Because the mobile clinic had a high level of fixed costs, the total cost per vaccination actually halved, despite the additional expense of the lentils.

How much do the lives of low-income people change from receiving access to credit? For example, does it change their consumption, or encourage them to start a business? If farmers had access to credit, would they be more likely to invest in fertilizer and expand their output?

As the body of experimental evidence accumulates, it begins to open windows on the lives of people in low-income countries, on issues of how they are actually making decisions and what constraints matter most to them. The old-style approach to development economics of sending money to low-income countries is replaced by policies aimed at specific outcomes: education, health, credit, use of technology. When it\’s fairly clear what really matters or what really helps, and the policies are expanded broadly, they can still be rolled out over a few yeas in a randomized way, which allows researchers to compare effects of those who experience the policies sooner to those who experienced them later. This approach to economic development has a deeply evidence-based practicality. 

For more on these topics, here are some starting points from articles in the Journal of Economic Perspectives, where I labor in the fields as Managing Editor: 
On the specific research on experimental approaches to poverty, Banerjee and Duflo coauthored Addressing Absence (Winter 2006 issue), about an experiment to provide incentives for teachers in rural schools to improve their attendance, and Giving Credit Where It Is Due (Summer 2010 issue), about experiments related to providing credit and how it affects the lives of poor people. 
I\’d also recommend a pair of articles that Banerjee and Duflo wrote for JEP where they focus on the economic lives of those in low-income countries: \”the choices they face, the constraints they grapple with, and the challenges they meet.\” The first paper focuses in the extremely poor. \”The Economic Lives of the Poor (Winter 2007), while the other looks at those who are classified as \”middle class\” by global standards, \”What Is Middle Class about the Middle Classes around the World? (Spring 2008). 

From Kremer, here are a couple of JEP papers focused on development topics not directly related to the experimental agenda: \”Pharmaceuticals and the Developing World\” (Fall 2002) and \”The New Role for the World Bank\” (written with Michael A. Clemens, Winter 2016).

Finally, the Fall 2017 issue of JEP had a three paper symposium on the issues involved in moving from a smaller-scale experiment to a scalable policy. The papers are: 

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