On October 11, David Card, Joshua Angrist and Guido Imbrens were awarded the Nobel Prize for bringing laurels in the field of Economic Sciences. Their contributions mainly appertained the Labour Market, Employment and Immigration, and the role of elongated education duration’s contribution in determining a person’s future income. All of these topics have been a matter of consequential discussion, and Economists have sought answers for them.

Does immigration really provide market opportunities for less skilled labour? The results to scientific hypotheses usually depend on experimentation and observations. However, when one has to deal with the real-world problems, such as the aforesaid question or the effect of immigration over minimum wage, it becomes imperative to look at the data of subsequent years. This is easier said than done, because the data isn’t solely affected by the upheaval; several other factors contribute and this leads to difficulties. The Nobel Prize Laureates have shown brilliance in determining answers to topics as crucial as immigration and labour market through the unmitigated power of observational data. To put it in simpler terms, an individual can study how the implementation of a certain policy or sanctioning of a certain event causes different kinds of people to be treated differently, pretty similar to a medicine’s clinical trials.

Before we delve deeper, let us look into some of the quintessential terms for our subsequent discussions.

Natural Experiment is a form of observational study where data is assimilated from events which do not involve the investigator, for instance the effect of natural calamities, weather reports. Usually, a group of individuals are subjected to conditions and factors that occur ‘naturally’, which elucidates the science behind its name.

David Card: For his empirical contributions to Labour Economics

“Card’s studies of core questions for society and Angrist and Imbens’ methodological contributions have shown that natural experiments are a rich source of knowledge. Their research has substantially improved our ability to answer key causal questions, which has been of great benefit to society,” says Peter Fredriksson, chair of the Economic Sciences Prize Committee.

Before Card and his co-author Alan Krueger had presented a credible causation linking immigration and minimum wages, it was an established belief that an increase or imposition of minimum wage will most likely come at the cost of multiple jobs, since employers will not have enough money to keep the staff. However, that is not the case. Card and Krueger did a thorough survey to prove the same.

David Card (Image Credit: University of California, Berkeley)

In 1992, New Jersey increased its minimum wage to be the highest in the US, while its neighbouring state Pennsylvania did not. Card and Krueger examined this natural experiment by analysing and surveying the fast-food workers on either side of the border. The results were riveting.

After looking at around 400 joints on either side of the border (in order to determine the immediate effect) they found no indication of minimum wage associated with loss of jobs. This result is incumbent especially to low wage workers, and poses a potential for growth in wages without costing their jobs. Hence, Card and Krueger did a commendable job of towing the boat of minimum wages to respectable shores.

One more immensely important inference of Card’s observations was how influx of new immigrants from a poor country can affirmatively affect wages of the native citizens. This consequence particularly aims at the strong anti-immigration sentiments prevalent in the US and Canada.

The Mariel Boatlift was a mass immigration of 125,000 Cubans and 25,000 Haitians who traveled from Cuba’s Mariel Harbour and entered the United States between 15th April and 31st October 1980. This exodus was triggered by a tremendous recession in the Cuban Economy and increased the Miami’s local labour force by a substantial seven percent.

Cuban Refugees during the Mariel Boatlift (Image Credit: Wall Street Journal)

Analysis of data obtained by such natural experiment is a rather cumbersome task because change in labour wage due to such a large-scale immigration would be impossible in a laboratory setting, but Card could infer that this immigration has done little to no tampering with the wages of the native community. Card used the ‘difference of differences’ to conclude this, meaning he surveyed the juxtaposition of the data before and after the migration in the US. This proved to be a credible medium to estimate the causal effects of the arrival of so many low-skilled labour force.

At first glance this might seem erroneous, like how could an influx fail to derail the growth trajectory of a nation? There have been several surmises to Card’s hypotheses and one of the most becoming ones say that due to the increase in the labour force, the native people can indulge tasks that include a greater practical advantage and can assign the refugees to different tasks that they specialize in. This in turn, uni-directionally points to one now proven theory- that immigration does not reduce the wages of native-born workers.

Card’s profound ‘nullification’ conclusion to some of the very debatable topics has earned him the title of one of the engineers of ‘Credibility Revolution’, which provides incentive to many students to pursue the field of Empirical Economics.

Joshua Angrist and Guido Imbrens: For their methodological contributions to the analysis of Casual Relationships

While Card analysed the outcomes of natural experiments, Angrist and Imbrens were awarded for contributing to the method of interpretation of the data from the said experiments. They solved methodological problems and paved the way for precise conclusions and causations to be extracted from them.

(Left to Right) Joshua Angrist and Guido Imbrens (Image Credit: Pagina100)

We have already discussed about the method of Difference of Differences. There is one more method to examine data from natural experiments; the Method of Instrumental Variables. Instrumental Variables (or IVs) are used to control measurement error in observational studies. This method advocated for drawing out casual inferences from observational data. Angrist and Krueger found out that this method provided a higher payoff than compared to standard analysis methods. We are measuring the returns of Education here (specifically about some students who decide to drop out).

For a more thorough detail, kindly visit the following link: Natural experimenters: Nobel laureates David Card, Joshua Angrist, and Guido Imbens | VOX, CEPR Policy Portal (voxeu.org)


The field of Natural Experimentation has not constricted itself to Labour Economics; this study is based on random assignment and has promising applications in various other fields of Economics as well. This article dealt with David Card’s study on immigration and minimum wage, both of which are pejorative discussions. Natural Experiments can be difficult to record because they can’t be controlled by the investigators and only rely on observational data. Card and his fellow co-author worked on the aforementioned concepts using various methods of analysing Natural Experiments and came up with credible results.

Joshua Angrist and Guido Imbrens thoroughly examined methodological problems and indicated that they are worthy of drawing conclusions and causal effects.