One of the most eagerly anticipated Nobel Prizes is awarded in the category of Economic Sciences and this year three Americans were honoured. The three recipients are David Card, Guido Imbens and Joshua Angrist. Card was recognised for his work on the labour market and the other two for their contribution to econometrics, a branch of Economics.

This year's honourees truly have an international background. David Card, born 1956 in Guelph, Canada, got his Ph.D. in 1983 from Princeton University, USA. He is Professor of Economics, University of California, Berkeley, USA. Joshua D Angrist, born 1960 in Columbus, Ohio, USA received his Ph.D. in 1989 from Princeton University, USA and is currently Ford Professor of Economics, Massachusetts Institute of Technology (MIT), Cambridge, USA. Guido W Imbens, born 1963 in the Netherlands came to the USA and finished his Ph.D. in 1991 from Brown University, Providence, USA. He is the Applied Econometrics Professor and Professor of Economics, Stanford University, USA. Angrist holds a dual US-Israeli citizenship while Imbens has both Dutch and American nationality.

Until now, more than 90 percent of the recipients of the Nobel Prize in Economics have been working in advancing the theoretical principles of the discipline. The trio recognised this year could be considered "applied" economists, and all three worked with data to address issues that strengthen our understanding of real-life problems. MIT president L Rafael Reif, in a note to students, faculty, and staff said of Angrist, "His rigorous empirical approach to using the tools of economics, especially 'natural experiments,' to understand and help address important real-world problems exemplifies the finest tradition of the department." Obviously, this tribute applies equally to all three. 

Since the days when I was in graduate school many decades ago, researchers have struggled to figure out whether an observed relationship between two variables is causal or coincidental. For example, if data shows that workers with higher education levels also earn more, can we conclude that these workers make more money because of greater education? As we know, correlation does not imply causality! In the same vein one could ask, does a correlation between age (X) and Covid-19 infection (Y) mean that X is causing Y?

Card, Imbens, and Angrist address the above questions with data from the labour market with tools in econometrics. The Nobel Committee recognised Card for his empirical contributions to labour economics and the other two laureates for their methodological contributions to the analysis of causal relationships.

As the announcement of the Nobel Committee mentions, the trio's work "provided us with new insights about the labour market and showed what conclusions about cause and effect can be drawn from natural experiments. Their approach has spread to other fields and revolutionised empirical research."

The research framework utilised by these economists can be broadly categorised as "natural experiments". Natural experiments are somewhat different from the other experimental technique adopted in economics known as randomised control trials (RCT) which was popularised by Nobel Laureate Abhijit Banerjee.

Why are these experiments important? If an economist hypothesises that providing free inputs to farmers should increase their per capita yield, there is a need to test the hypothesis under controlled conditions. In RCT, to test if fertiliser increases the yield of crops, you select two different sets of farmers, provide fertiliser to one group but the other, known as the control group, does not get any fertiliser.   

 Similarly, if free mosquito nets are offered to rural households to combat malaria, there has to be compelling evidence that providing free mosquito nets is the most cost-effective way to eradicate malaria. If not, the policy might result in failure and worse, be thrown out and tarred for the wrong reasons. That's also important because there are competing uses of money allocated for administering the "free net" programme.

Let's consider the case for raising the minimum wages of workers, a debate going on in every country. Using the traditional theory of supply and demand, economists were taught that raising wages will decrease the demand for labour. As noted by the Economist magazine, in 1992 a survey of the American Economic Associations members found that 79 percent agreed that a minimum-wage law increased unemployment among younger and lower-skilled workers. The current year's Nobel winners' research altered economists' views of such policies.

Card's work challenged two misconceptions: a) raising minimum wage decreases demand for labour; and b) immigrants take away jobs and lower wages. He and the late Princeton economist Alan Krueger found that in the early 1990s, the experience of New Jersey and Pennsylvania provided a "natural experiment" to test the hypothesis that raising minimum wages lowers labour demand. Card and Krueger looked at the effects of New Jersey's decision to raise the minimum wage from USD 4.25 to USD 5.05 an hour. The two surveyed more than 400 fast-food restaurants in New Jersey and eastern Pennsylvania, where the minimum wage was unchanged. They found "no indication that the rise in the minimum wage reduced employment." 

Incidentally, in an op-ed in 2014 on the issue of raising the minimum wage in Bangladesh's RMG industry, I had argued that higher wages for the garments workers would not cause any job loss—I had immensely benefitted from the work of Card and Krueger ("Will rising minimum wage affect the RMG sector?" The Daily Star, October 1, 2014).

Coming back to the importance of natural experiments, these models provide economists, psychologists, and other social scientists with an opportunity to collect data when experimentation with human lives is impossible. It is difficult for economists to conduct empirical research akin to those done by medical scientists in a clinical setting. RCTs can be applied to answer only certain types of epidemiologic questions, but they are not suitable for all situations. They are also not useful in the investigation of questions for which random assignment is either impracticable or unethical. 

Take the case of an experiment where Angrist and Krueger compared people who had different levels of education. US states allowed students to drop out of school at different ages, and they compared their lifetime financial earnings. Using statistical tools, they isolated certain societal variables that could also have an impact on income and concluded that a year's difference in education resulted in a roughly nine percent gap in income. This natural experiment on the labour market was feasible because the variables of interest, educational level and earnings, happened without the researchers' intervention, and the labour market provided data as events progressed.

A glowing tribute for this year's laureates came from Eva Mörk, a member of the Prize Committee for the Alfred Nobel Memorial Prize in Economic Sciences. He told the press on Monday that Card, Angrist, and Imbens "have revolutionised empirical work in economics. They have shown that it's indeed possible to answer important questions even when it's not possible to conduct randomised experiments."

Dr Abdullah Shibli is an economist and IT consultant. He is also Senior Research Fellow of International Sustainable Development Institute (ISDI), a think tank based in Boston.