In 2019, more than 700 million people still live with extremely low incomes. Half of the world’s children still leave school without basic literacy and numeracy skills. Every year, around 5 million children under the age of five still die of diseases that could often have been prevented or cured with inexpensive treatments.

Several studies focus on understanding the causes that drive poverty and developing theories and policies to tackle them. Take, for instance, child mortality and health, the problems of which could, in theory, be tackled by empowering women. However, theory doesn’t tell us which policy would be most effective and efficient to boost women’s empowerment thereby decreasing child mortality: it could be a policy focused on educating mothers, new marital age legislation, or better access to healthcare.

All great ideas, in theory, but what about practice? Which policy would bring the best outcome? Which could save the lives of the largest number of children?

This is where Behavioural Economics and the 2019 Nobel Prize come into the picture.

The 2019 Nobel Prize for Economics has been awarded to Abhijit Banerjee, Esther Duflo and Michael Kremer “for their experimental approach to alleviating global poverty”.

In a nutshell, the Laureates divided the global poverty issue into smaller, more manageable questions at individual or group levels. They then looked for the most accurate answer to those questions by using specially designed field experiments. As a result, they noted that a lot of people in low-income countries were not taking advantage of the benefits offered and they asked themselves: ‘why?’. That is, they attempted to pinpoint the causal pathways, through which changes in incentives, constraints and information influence the outcomes of interest via human behavior.

Accordingly, to find an answer, they incorporated economic theories of incentives and development economics – the branch which deals with studying the causes of global poverty and how to combat it – by using direct experiments to design adequate policies based on the behavioral responses of all the experiment participants.

Let’s get a closer look at what they did.

They asked themselves: How can we improve pupils’ learning outcomes?

To answer this question, the Laureates took (let’s say) 250 schools and randomly divided them into different groups of 50. These groups received extra resources in different forms: 50 schools got free school meals, 50 received more textbooks, 50 got extra teachers, 50 schools got a different length of contract for the same number of teachers, and finally the last group received no extra resources, in order to control and credibly link later differences in learning outcomes to the various forms of support provided.

The experiment showed that neither more textbooks, nor free school meals, nor extra teachers per pupil made any difference to educational outcomes. The only change that significantly improved the learning outcomes was employing teachers on short-term contracts, which could be extended through good performance. This intervention increased teachers’ motivation and presence at school and, as a consequence, improved learning outcomes…and yes, among others, it is also the only cost-free solution!

At a first glance, most people would assume that the problem of poor educational outcomes in low-income countries are related to the facility (schools), the tolls (textbooks), parents not enrolling their children in schools, or the poor quality and lack of teachers. The Laureates, however, understood that much of what we want to achieve (such as better educational outcomes) reflects multiple individual decisions – including teachers, parents and pupils. Effective improvements, thus, require an understanding of why people make the decisions they do and what drives those decisions. Among others, Behavioral Economics studies the incentives, restrictions, information and distortions that motivates people’s decisions.

The experiment on education in low-income countries revealed that adding resources (meals, textbooks, teachers) is, in general, of limited value and expensive. Instead, adjusting the existing resources – by understanding why they are creating limited value – can help to efficiently address investments rather than crowd them out.

Let’s look at another finding. Why, in spite of the available subsidies on vaccinations, the percentage of immunized children remains so low?

Healthcare in poor countries is a well-known problem, despite the heavily subsidized vaccines provided by the governments (<1$). Millions of children in low-income countries die from preventable diseases each year. Today’s discussion about reducing child mortality in low-income countries, therefore, largely revolves around human behavior and around what stops people from taking advantage of subsidized vaccinations.

Low-income people are extremely price-sensitive regarding investments of any kind, even healthcare. The experiment implemented by the Laureates was once again to randomly divide the sample into 3 groups of villages:

The first group of villages is the control group offering only the subsidized vaccination;

The second group of villages was provided with a mobile clinic with specialized staff always on site;

The last group had the mobile clinic and families were receiving a bag of lentils as a bonus to vaccinate their children.

As shown in the picture, compared to the first control group, vaccination rates grew by 300% in the villages selected to have access to mobile clinics and by 650% in villages with mobile clinic and the bag of lentils as a bonus. As a specialized facility, the mobile clinics carry high fixed costs, independent of the number of vaccinations. Therefore, the more vaccinations performed by the clinic, the lower the cost per vaccination will be. Accordingly, adding the bag of lentils (a cost) increases the number of vaccinations in such a way, that the final cost per vaccination will be halved compared to the case in which the bag of lentils is not offered (28$ per vaccination and 56$ per vaccination, respectively).

However, mobile clinics and extra incentives did not solve the immunization problem, as 61% of children did not vaccinate. The causes must stem from people’s irrationality. One explanation is the so-called present bias, which is based on the assumption that the present takes up a great deal of people’s awareness, so they tend to delay investment decisions. When tomorrow comes, they once again face the same decision, and again choose to postpone investments, which would be beneficial in the long-term. If individuals are present-biased, then temporary subsidies are better than permanent ones: space-and-time limited offer reduce incentives to delay investments. Besides, it is more cost-effective.

The work of Banerjee, Duflo and Kremer has dramatically increased the practical, quantitative knowledge necessary to isolate key mechanisms behind poverty, which was investigated through the prism of the behavioural responses to various policy interventions. Their work has significantly deepened our understanding of poverty in the developing world. It has already helped in alleviating global poverty and has great potential to further improve the lives of many around the world.

Watch and read more about 2019 Nobel Prize in Economics:

https://www.nobelprize.org/uploads/2019/10/advanced-economicsciencesprize2019.pdf

Esther Duflo in a TED talk about her research: Social Experiments to Fight Poverty www.ted.com/talks/esther_duflo_social_experiments_to_fight_poverty/transcript

Michael Kremer in a YouTube lecture: The Origin and Evolution of Randomized Experiments in Development www.youtube.com/watch?v=YGL6hPgpmDE