John Goodenough, at 97 the oldest person to be awarded a Nobel prize — Britain’s Stanley Whittingham, and Japan’s Akira Yoshino won the Nobel Chemistry Prize for the development of lithium-ion batteries, paving the way for smartphones and a fossil fuel-free society.
Lithium-ion batteries which are lightweight, rechargeable and powerful are used in mobile phones to laptops and electric vehicles and can also store significant amounts of energy from solar and wind power, making possible a fossil fuel-free society. Lithium batteries have revolutionised our lives since they first entered the market in 1991, and were of the greatest benefit to humankind.
Over two-thirds of the world’s population own a mobile device, nearly all of which are powered by rechargeable lithium-ion batteries.
Seeking an alternative source of power during the oil crisis of the 1970s, Whittingham discovered a way to harness the potential energy in lithium, a metal so light it floats on water. He constructed a battery partly made of lithium that utilised the element’s natural tendency to shed electrons, thereby transferring energy.
The 2019 Nobel Peace Prize has been awarded to Ethiopian Prime Minister Abiy Ahmed who made peace in 2018 with Eritrea. He was awarded the prize for his efforts to "achieve peace and international cooperation”. Mr Abiy's peace deal with Eritrea ended a 20-year military stalemate following their 1998-2000 border war.
In 2018, a deal between Eritrean President Isaias Afwerki and Ethiopian Prime Minister Abiy Ahmed ended the border conflict between both countries, restoring full diplomatic relations, and agreeing to open their borders to each other for persons, goods and services. It ended the Eritrean–Ethiopian War (1998–2000) and of the following Eritrean–Ethiopian border conflict (2000–2018) with sporadic clashes
Three scientists have been awarded the 2019 Nobel Prize in Physics for "ground-breaking" discoveries about the Universe. James Peebles, Michel Mayor and Didier Queloz were announced as this year's winners at a ceremony in Stockholm. Peebles was honoured for work on the evolution of the Universe, while Mayor and Queloz won for their discovery of a planet around a Sun-like star- exoplanet.
With others, Peebles predicted the existence of cosmic microwave background (CMB) radiation, the so-called afterglow of the Big Bang. By studying the CMB, scientists have been able to determine the age, shape and contents of the Universe. Peebles also made major contributions to the theory of dark matter and dark energy, the mysterious components which together make up some 95% of the Universe.
Michel Mayor and Didier Queloz were awarded the prize for finding 51 Pegasi b, a gas giant orbiting a star 50 light-years away. It was the first exoplanet to be discovered orbiting a star like our own. They used the pioneering radial velocity technique. This detects distant worlds indirectly.
Physiology or Medicine
The 2019 Nobel Prize in Physiology or Medicine is awarded jointly to William G. Kaelin Jr, Sir Peter J. Ratcliffe and Gregg L. Semenza “for their discoveries of how cells sense and adapt to oxygen availability.”
They established the basis for our understanding of how oxygen levels affect cellular metabolism and physiological function. Their discoveries have also paved the way for promising new strategies to fight anemia, cancer and many other diseases.
Oxygen (O2), makes up about one fifth of Earth’s atmosphere. Oxygen is essential for animal life: it is used by the mitochondria present in virtually all animal cells in order to convert food into useful energy. During evolution, mechanisms developed to ensure a sufficient supply of oxygen to tissues and cells. The carotid body, adjacent to large blood vessels on both sides of the neck, contains specialized cells that sense the blood’s oxygen levels. In addition to the carotid body-controlled rapid adaptation to low oxygen levels (hypoxia), there are other fundamental physiological adaptations. A key physiological response to hypoxia is the rise in levels of the hormone erythropoietin (EPO), which leads to increased production of red blood cells (erythropoiesis). Gregg Semenza studied the EPO gene and how it is regulated by varying oxygen levels.
Polish author Olga Tokarczuk and Austria's Peter Handke have been awarded the Nobel Prize for Literature. Two winners were named - one for 2019 and one for 2018 - because the prize was not awarded last year. The Swedish Academy, which oversees the prestigious award, suspended it in 2018 after a sexual assault scandal. Tokarczuk, who also won the Man Booker International Prize last year, was awarded the 2018 Nobel Prize, with this year's Nobel going to Handke.
2019 Nobel Prize for Economics: Poverty Eradication & Randomized Controlled Trials (RCTs)
What does Development Economics study?
Economics as a discipline initially dealt with efficient allocation of resources for maximum growth. Later, it balanced growth with redistribution and thus welfare focus emerged. But when decolonisation started and developing countries with mass poverty needed to develop, a distinct school of economics came up- development economics- dedicated to the causes and cure of mass poverty. It undertook studies to understand poverty to effectively alleviate it. It retained the earlier focus on efficient allocation of resources but from a perspective that stressed on eradication of poverty. In fact, development economics(DE) brings the best of all schools of economics and consolidates them. DE marries efficiency to effectiveness: efficiency being output for input and effectiveness is the achievement of overall results. DE is predominantly centered around the question of why poverty persists in spite of so much economic growth, and ways to eradicate it.
DE draws from behavioural economics as far as drawing up incentives and disincentives to promote a certain type of behaviour.
DE conducts micro experiments and uses the microeconomic data generated to suggest macroeconomic policies for empowerment.
DE as well suggests fiscal, monetary and welfare policies for poverty alleviation and eradication.
How do Randomized Controlled Trials (RCTs) connect with Development Economics?
Within Development Economics, Randomized Controlled Trials (RCTs) have gained enormous ground in dealing with various aspects of human development. RCTs represent experimental economics where empirical field studies are the basis of social and economic interventions for betterment. Thus, evidence-based public policy interventions are encouraged with myriad advantages.
Can we have the history of RCTs?
Randomized controlled trials have a long history in science. A century ago, agricultural researchers pioneered the approach in crop studies. In the postwar era, randomized controlled trials became closely associated with clinical trials and later field trials in medicine. In economics, some important randomized controlled trials predate the explosion of experimental work in development economics, including welfare reform programme experiments in the 1980s and 1990s and educational research. Thus, the main method used to estimate cause-effect relation is not new. But the application of randomized controlled trials in development economics has significantly expanded in the last 2-3 decades.
How is an RCT structured?
In an RCT, two or more groups of people are compared:
It is important that in an RCT, the two (or more) groups of people in a trial are as similar as possible, except for the treatment they receive.
It is important because it ensures that any differences in outcomes between the groups are only due to the treatment received.
The treatment can be a drug being clinically tried or a welfare measure being tested or an incentive being offered or a constraint being imposed and so on.
Information from the control group allows the researchers to see whether the new treatment is more/less effective than the current standard treatment.
Randomization is the process of assigning trial subjects to treatment or control groups using an element of chance in order to reduce the bias.
Randomised controlled trials are the most reliable way to compare treatments and come to relatively unbiased conclusions.
What is a blind RCT?
The trial may be blinded, in which information which may influence the participants is withheld until after the experiment is complete. Blind can be imposed on any participant of an experiment, including subjects, researchers, technicians, data analysts and evaluators to eliminate some sources of experimental bias like selection bias.
For example, without randomization, scientists may consciously or otherwise assign patients to the group receiving the active treatment if they look more likely to benefit from the experimental treatment. This could make a treatment appear more beneficial than it actually is. This is the selection bias and removes objectivity from the experiment.
Because the outcomes are measured, RCTs are quantitative studies.
Thus, RCTs are quantitative, comparative, controlled experiments in which investigators study two or more interventions in a series of individuals who receive them in random order.
What are the advantages of RCTs?
RCTs have limited application as the micro findings are difficult to generalise as the studied population is very different from the population treated in normal life.
Thus, RCTs at best produce insights.
Why are the RCTs in headlines?
2019 Nobel Prize for Economics
The experimental poverty research driven by RCTs of Abhijit Banerjee, Esther Duflo and Michael Kremer won the Nobel economics prize (Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel) in 2019. Esther Duflo was only the second woman to win the prize (the other was Elinor Ostrom).
They have shown how the problem of global poverty can be tackled by breaking it down into a number of smaller – but more precise – questions at individual or group levels. They then answer each of these using a specially designed field experiment-RCT.
Abhijit Banerjee, Esther Duflo and Michael Kremer are honoured for a long series of field experiments, or studies carried out in real but carefully controlled conditions to measure credibly what sort of policies can make a difference to poverty and related outcomes.
In order to understand the contribution of the trio to experimental poverty research, the following examples help from the fields of: education, health, behavioral biases, gender and politics, and credit.
How did RCTs contribute to Education?
RCTs score in finding out about which interventions increase educational outcomes at the lowest cost. In low-income countries, textbooks are scarce and children often go to school hungry. It can be thought that students` results will improve by increasing access to more textbooks or giving them free school meals. In the mid-1990s, Michael Kremer and his colleagues performed a number of field experiments in partnership with a local non-governmental organisation (NGO). It is important to conduct RCTs to come to right conclusions as simply comparing schools with different access to textbooks is not a viable approach. The schools could differ in many ways: wealthier families usually buy more books for their children, grades are probably better in schools where fewer children are really poor, and so on. One way of avoiding these difficulties is to ensure that the schools being compared have the same average characteristics.
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 and others 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 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. This study was the start of an interactive process, in which new research results went hand in hand with increasingly large-scale programmes to support pupils. These programmes have now reached more than 100,000 Indian schools.
Other field experiments investigated the lack of clear incentives and accountability for teachers, which was reflected in a high level of absenteeism. One way of boosting the teachers’ motivation was to employ them on short-term contracts that could be extended if they had good results. Duflo, Kremer and others compared the effects of employing teachers on these terms with lowering the pupil-teacher ratio by having fewer pupils per permanently employed teacher. They found that pupils who had teachers on short-term contracts had significantly better test results, but that having fewer pupils per permanently employed teacher had no significant effects.
Overall, this new, experiment-based research on education in low-income countries shows that additional resources are, in general, of limited value. However, educational reforms that adapt teaching to pupils’ needs are of great value. Improving school governance and demanding responsibility from teachers who are not doing their job are also cost-effective measures.
How did RCTs contribute to 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 and others 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 did RCTs contribute to Microcredit?
Development economists have also used field experiments to evaluate programmes that have already been implemented on a large scale. One example is the massive introduction of microloans in various countries, which has been the source of great optimism. Banerjee, Duflo and others performed an initial study on a microcredit programme that focused on poor households in the Indian metropolis of Hyderabad. Their field experiments showed rather small positive effects on investments in existing small businesses, but they found no effects on consumption or other development indicators, neither at 18 nor at 36 months. Similar field experiments, in countries such as Bosnia-Herzegovina, Ethiopia, Morocco, Mexico and Mongolia, have found similar results.
How did RCTs contribute to Gender and Politics?
An important issue in the political economics of development is how the identity of political leaders affects observed policy choices. Duflo tackled this question in one of her very first published studies (2004). The research related to a political reform that aimed to strengthen women’s political standing in India in 1993 when federal government introduced a new constitutional rule that each state had to reserve a third of all positions for women in Panchayats. These councils had also been given an increasing role in local decisions on infrastructure, with rules that differed by state.
To investigate the effect of female reservations, Duflo and Chattopadhyay surveyed a sample of villages in the two states of West Bengal and Rajasthan, where the former had a longer history of village elections and also more extensive decentralized powers allocated to village councils. In both states, a specific set of rules ensured that the chairs were reserved for a woman in a random selection of village councils. Based on these rules and the data from their own surveys, Duflo and Chattopadhyay could thus estimate the effects of having a randomly selected female leader.
They found that female leaders seemed to make decisions that accorded better with the preferences of women. In West Bengal, village women were more concerned with drinking water and roads, while village men were more concerned with education. Female leaders in West Bengal indeed invested more than male leaders in drinking water and roads, at the expense of education. In Rajasthan, where women were more concerned than men with water but less concerned with roads, Gram Panchayats reserved for women leaders made similar priorities in their investments, spending more money for water than for roads.
Moreover, they demonstrated that an important mechanism behind this result was decreased stereotypes among voters: specifically, less prejudice against women as effective policymakers.
What is Bounded Rationality and how did RCTs come across Bounded Rationality?
There are many factors that impact on the rationality of human behaviour. Bounded rationality is a concept that shows that for a variety of reasons, rationality is limited in human behaviour.
In the vaccination study, incentives and better availability of care did not completely solve the problem, as 61 per cent of children remained partially immunised. The low vaccination rate in many poor countries probably has other causes, of which one is that people are not always completely rational. This explanation may also be key to other observations which, at least initially, appear difficult to understand. One such observation is that many people are reluctant to adopt modern technology.
Duflo, Kremer and others investigated why smallholders – particularly in subSaharan Africa – do not adopt relatively simple innovations, such as artificial fertiliser, although they would provide great benefits. One explanation is `present bias’ – 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 delay the investment. The result can be a vicious circle in which individuals do not invest in the future even though it is in their long-term interest to do so. Bounded rationality has important implications for policy design. If individuals are present-biased, then temporary subsidies are better than permanent ones: an offer that only applies here and now reduces incentives to delay investment. This is exactly what Duflo, Kremer et al. discovered in their experiment: temporary subsidies had a considerably greater effect on the use of fertiliser than permanent subsidies.
What Policy Influence can the RCTs have?
All the examples of RCTs conducted by the Nobel laureates show that the findings have great value for public policy and NGO interventions with many benefits. Fiscal benefits; better targeting; more robust and quicker outcomes are some policy advantages.
What is Abdul Latif Jameel Poverty Action Lab (J-PAL)?
The Abdul Latif Jameel Poverty Action Lab (J-PAL) is a global research center working to reduce poverty by ensuring that policy is informed by scientific evidence. Anchored by a network of 181 affiliated professors at universities around the world, J-PAL conducts randomized impact evaluations to answer critical questions in the fight against poverty. J-PAL affiliates have led more than 800 randomized evaluations across a diverse range of topics, from clean water to microfinance to crime prevention. J-PAL translates research into action, promoting a culture of evidence-informed policymaking around the world.
J-PAL builds partnerships with governments, NGOs, donors, and others to generate new research, share knowledge, and scale up effective programs.
J-PAL was founded in 2003 as the "Poverty Action Lab" by professors Abhijit Banerjee, Esther Duflo and Sendhil Mullainathan. J-PAL was established to support randomized evaluations measuring interventions against poverty on topics ranging from agriculture and health to governance and education.