vol IV chap 15 sect 3
Previous: 15.2. Role of statistical analysis in the formulation of models.
15.3. Interpretation of natural experiments in Economic sciences.¶
This Section refers to the 2021 Prize; it does not consider the Prize awarded to David Card “for his empirical contributions to labour economics”; it concentrates on the Prize awarded the same year to Joshua D. Angrist and Guido W. Imbens “for their methodological contributions to the analysis of causal relationships”. In what follows we include excerpts from two documents Press release and Popular information.
Press release: Natural experiments help answer important questions for society.
MLA style: Press release. NobelPrize.org. Nobel Prize Outreach AB 2023. Tue. 14 Nov 2023. https://www.nobelprize.org/prizes/economic-sciences/2021/press-release/
“This year’s Laureates – David Card, Joshua Angrist and Guido Imbens – have provided us with new insights about the labour market and shown what conclusions about cause and effect can be drawn from natural experiments. Their approach has spread to other fields and revolutionised empirical research.”
“Many of the big questions in the social sciences deal with cause and effect. How does immigration affect pay and employment levels? How does a longer education affect someone’s future income? These questions are difficult to answer because we have nothing to use as a comparison. We do not know what would have happened if there had been less immigration or if that person had not continued studying.”
“However, this year’s Laureates have shown that it is possible to answer these and similar questions using natural experiments. The key is to use situations in which chance events or policy changes result in groups of people being treated differently, in a way that resembles clinical trials in medicine.”
“Using natural experiments, David Card has analysed the labour market effects of minimum wages, immigration and education. His studies from the early 1990s challenged conventional wisdom, leading to new analyses and additional insights. The results showed, among other things, that increasing the minimum wage does not necessarily lead to fewer jobs. We now know that the incomes of people who were born in a country can benefit from new immigration, while people who immigrated at an earlier time risk being negatively affected. We have also realised that resources in schools are far more important for students’ future labour market success than was previously thought.”
“Data from a natural experiment are difficult to interpret, however. For example, extending compulsory education by a year for one group of students (but not another) will not affect everyone in that group in the same way. Some students would have kept studying anyway and, for them, the value of education is often not representative of the entire group. So, is it even possible to draw any conclusions about the effect of an extra year in school? In the mid-1990s, Joshua Angrist and Guido Imbens solved this methodological problem, demonstrating how precise conclusions about cause and effect can be drawn from natural experiments.”
“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.
Popular information: Natural experiments help answer important questions.
MLA style: Popular information. NobelPrize.org. Nobel Prize Outreach AB 2023. Tue. 14 Nov 2023. https://www.nobelprize.org/prizes/economic-sciences/2021/popular-information/
“If we are to make good decisions, we must understand the consequences of our choices. ….. However, answering broad questions about cause and effect is not easy, because we will never know what would have happened if we had made a different choice.”
“One way of establishing causality is to use randomised experiments, where researchers allocate individuals to treatment groups by a random draw. This method is used to investigate the efficacy of new medicines, among other things, but is not suitable for investigating many societal issues – for example, we cannot have a randomised experiment determining who gets to attend upper-secondary school and who does not.”
“Despite these challenges, the Laureates have demonstrated that many of society’s big questions can be answered. Their solution is to use natural experiments – situations arising in real life that resemble randomised experiments. These natural experiments may be due to natural random variations, institutional rules or policy changes. In pioneering work from the early 1990s, David Card analysed some central questions in labour economics – such as the effects of a minimum wage, immigration and education – using this approach.” ….
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“Natural experiments differ from clinical trials in one important way – in a clinical trial, the researcher has complete control over who is offered a treatment and eventually receives it (the treatment group) and who is not offered the treatment and therefore does not receive it (the control group). In a natural experiment, the researcher also has access to data from treatment and control groups but, unlike a clinical trial, the individuals may themselves have chosen whether they want to participate in the intervention being offered. This makes it much more difficult to interpret the results of a natural experiment. In an innovative study from 1994, Joshua Angrist and Guido Imbens showed what conclusions about causation can be drawn from natural experiments in which people cannot be forced to participate in the programme being studied (nor forbidden from doing so). The framework they created has radically changed how researchers approach empirical questions using data from natural experiments or randomised field experiments.”
One example of a natural experiment
“Let us use a concrete example to illustrate how a natural experiment works. One question that is relevant to both society and to young people considering their future, is how much more you would earn if you chose to study longer.” …..
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“It would be easy to believe that situations which enable natural experiments are very unusual, especially those that can be used to answer important questions. …. There is thus unintended randomness that divides people into control and treatment groups, providing researchers with opportunities for uncovering causal relationships.”
Understanding labour markets
The effects of a minimum wage
“In the early 1990s, the conventional wisdom among economists was that higher minimum wages lead to lower employment because they increase wage costs for businesses. …. Reverse causation could even be the issue: when unemployment rises, employers can set lower wages which, in turn, may lead to demands to increase the minimum wage.”
“To investigate how increased minimum wages affect employment, Card and Krueger used a natural experiment. …. As with randomised experiments, a control group was needed, i.e., a group where wages didn’t change but all the other factors were the same.”
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“Card and Krueger focused on employment in fast-food restaurants, an industry where pay is low and minimum wages matter. ….. The overall conclusion is that the negative effects of increasing the minimum wage are small, and significantly smaller than was believed 30 years ago.”
“The work conducted by Card at the beginning of the 1990s also led to new research, which attempted to explain the absence of negative effects on employment. ….. The many studies inspired by Card and Krueger’s work have considerably improved our understanding of the labour market.”
Research on immigration and education
“Another important issue is how the labour market is affected by immigration. To answer this question, we need to know what would have happened if there had not been any immigration.” ….. “To examine how this huge influx of workers affected the labour market in Miami, David Card compared the wage and employment trends in Miami with the evolution of wages and employment in four comparison cities.”
“Despite the enormous increase in labour supply, Card found no negative effects for Miami residents with low levels of education. Wages did not fall and unemployment did not increase relative to the other cities. This study generated large amounts of new empirical work, and we now have a better understanding of the effects of immigration.”…..
….. “Card and Krueger found that resources are important: returns on education increased with teacher density in the state in which the individuals had grown up.”
“This research also inspired many new studies. There is now relatively strong empirical support to show that investments in education influence students’ later success on the labour market. This effect is particularly strong for students from disadvantaged backgrounds”.
A new framework for studies of causal relationships
“In all realistic scenarios, the effect of an intervention – for example, the effect of additional schooling on earnings – varies between people. Moreover, individuals are affected differently by a natural experiment. …. How can a causal relationship between education and income be established?”
“Joshua Angrist and Guido Imbens tackled this problem in an influential study from the mid-1990s. More specifically, they asked the following question: Under which conditions can we use a natural experiment to estimate the effects of a particular intervention, such as a computing course, when the effects vary between individuals and we do not have complete control of who participates? How can we estimate this effect and how should it be interpreted?”
“Somewhat simplified, we can imagine a natural experiment as if it randomly divides individuals into a treatment group and a control group. The treatment group is entitled to participate in a programme while the control group is not. Angrist and Imbens showed that it is possible to estimate the effect of the programme by applying a two-step process (known as the instrumental variables method). The first step investigates how the natural experiment affects the probability of programme participation. The second step then considers this probability when evaluating the effect of the actual programme. …. Joshua Angrist and Guido Imbens thus showed exactly what conclusions about cause and effect can be drawn from natural experiments. Their analysis is also relevant for randomised experiments where we do not have complete control over who participates in the intervention, which is the case in almost all field experiments. The framework developed by Angrist and Imbens has been widely adopted by researchers who work with observational data. By clarifying the assumptions necessary to establish a causal relationship, their framework has also increased the transparency – and thus credibility – of empirical research.”
A revolution in empirical research
“The Laureates’ contributions from the early 1990s demonstrate that it is possible to answer important questions about cause and effect using natural experiments. Their contributions complement and strengthen one another: Angrist and Imbens’ methodological insights about natural experiments and Card’s applications of this approach to important questions led the way for other researchers. We now have a coherent framework which, among other things, means that we know how the results of such studies should be interpreted. The work of the Laureates has revolutionised empirical research in the social sciences and significantly improved the ability of the research community to answer questions of great importance to us all.”
REFERENCES¶
MLA style: Advanced information. NobelPrize.org. Nobel Prize Outreach AB 2023. Tue. 14 Nov 2023. https://www.nobelprize.org/prizes/economic-sciences/2021/advanced-information/
MLA style: David Card – Prize presentation. NobelPrize.org. Nobel Prize Outreach AB 2023. Tue. 14 Nov 2023. https://www.nobelprize.org/prizes/economic-sciences/2021/card/prize-presentation/
MLA style: Joshua D. Angrist – Facts – 2021. NobelPrize.org. Nobel Prize Outreach AB 2023. Tue. 14 Nov 2023. https://www.nobelprize.org/prizes/economic-sciences/2021/angrist/facts/
MLA style: Joshua D. Angrist – Prize lecture. NobelPrize.org. Nobel Prize Outreach AB 2023. Tue. 14 Nov 2023. https://www.nobelprize.org/prizes/economic-sciences/2021/angrist/lecture/
MLA style: Guido W. Imbens – Facts – 2021. NobelPrize.org. Nobel Prize Outreach AB 2023. Tue. 14 Nov 2023. https://www.nobelprize.org/prizes/economic-sciences/2021/imbens/facts/
MLA style: Guido W. Imbens – Prize presentation. NobelPrize.org. Nobel Prize Outreach AB 2023. Tue. 14 Nov 2023. https://www.nobelprize.org/prizes/economic-sciences/2021/imbens/prize-presentation/