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Queen’s alumnus David Card (ArtSci ’78, LLD ’99) was recently named one of the winners of the 2021 The Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel for his influential use of natural experiments as well as his significant contributions to understandings of labour markets.

Reflecting on his career, Dr. Card has said his passion for his field began as an undergraduate, when he originally intended to study physics before encountering economics. While Dr. Card has not been a student at Queen’s for some time, his presence is still felt here through his research, which has influenced the work of many economists. To better understand Dr. Card’s work, the Queen’s Gazette connected with two experts from the university’s highly-ranked and internationally-recognized . and help explain Dr. Card’s research, his impact on the field, and his influence on their own work.

The Nobel committee highlights Dr. Card’s influential use of natural experiments. What are natural experiments and why have they been so important?

Lehrer:  With natural experiments, the researcher is generally trying to conduct analysis similar to a randomized experiment, except without randomization. Now a true experiment may not have been conducted but in its place something called a natural experiment occurred and we explore differences before and after, rather than just after as in a randomized experiment.

One of Dr. Card’s most influential natural experiments was on the topic of minimum wage. In a paper from 1994, Dr. Card and Alan Krueger studied the increase in the minimum wage in New Jersey from $4.25 to $5.05. This change took effect on April 1, 1992. Card and Krueger collected data on employment at fast food restaurants in New Jersey in February and in November 1992. They also collected similar data on restaurants in eastern Pennsylvania, the neighboring state, for the same period. The minimum wage in Pennsylvania remained at $4.25 throughout this period. So the idea is that we could exploit these situations in a manner similar to a randomized experiment.

Dr. Card was not the first to use natural experiments, but his minimum wage study received incredible attention since it challenged conventional wisdom on how labour markets function.

Can you say more about how Dr. Card changed the way economists think about labour markets?

Liu: Some of Dr. Card’s research has produced findings that are different from what economists would expect from economics models. For instance, a supply-and-demand model predicts that an increase in the minimum wage should reduce employment. However, in the New Jersey study, Card and Krueger find that the minimum wage increase had a small but positive effect on employment for workers of the fast-food industry in New Jersey (relative to similar nearby counties in Pennsylvania). Dr. Card’s research provides some counter-intuitive findings and has invoked debates in many important issues. This has greatly pushed forward the research in these fields.

Lehrer: He helped shift the attention paid towards data. The analogy I often give to students is that if you are a chef, it does not matter how fancy your kitchen equipment is (how complicated your model is or how fancy your econometric tools are): if the ingredients are low quality, the meal will be poor. Data is the primary ingredient to empirical economic research. I believe his work reoriented attention to data and away from focusing on building unnecessarily complicated models and econometric methods.  By using better data with more transparent research designs, the attention paid to economics research has increased in policy circles since it is more accessible.

Dr. Card’s research has touched on pressing topics such as minimum wage, immigration, and education. Has his work had any impact on how policymakers approach these areas?

Liu: A central question related to the immigration debate is the causal effect of immigration on the employment opportunities of the local workers. The raw data often suggest a positive correlation between local wages/employment and immigration. However, the positive correlation should not be viewed as evidence for the impact of immigration on the local labour market or used for policy making, because immigrants often choose to go to cities with high wages and more job opportunities. Dr. Card tackles the selection issue by using the Mariel Boatlift as a natural experiment. In April of 1980, Fidel Castro, the former leader of Cuba, declared that Cubans who wanted to leave Cuba could do so from the port of Mariel. Suddenly, Miami’s labour force increased dramatically and unexpectedly because it is the closest U.S. city to Mariel. Dr. Card’s research suggests that the immigration shock had negligible effect on the employment rate in Miami. Dr. Card’s research suggests a path to overcoming selection issues and understanding causal effects from raw data, taking the advantage of natural experiments. These results provide more reliable empirical evidence for policy making.

How has Dr. Card influenced your own work?

Liu: Dr. Card’s work has greatly influenced my own research. For instance, some of my research investigates the impact of mass incarceration in the U.S. on black women’s marriage and labour market outcomes, and its impact on black children’s educational attainment. These questions seem to be very different from those of Dr. Card’s research. However, in terms of methodology, I have greatly benefited from Dr. Card’s work. I use sentencing policy reforms in the U.S. as a natural experiment. Different states may punish offenders who committed similar crimes differently, due to different harshness of their sentencing policies. This creates some variation in the incarceration rate across states and over years, which is uncorrelated with the characteristics of the offenders or the economic conditions of the states. The natural experiment allows me to overcome the potential issue that different economic outcomes of black women and children across states could be correlated with different characteristics of men “missing” from their families or communities, or different economic conditions. These differences can be also correlated with the differential incarceration rates.

Lehrer: I spent part of my sabbatical at Berkeley and David was my host. Three things I learned from him immediately jump out to me.

The first is related to data. Since I attended many department seminars where he was an active participant, I saw how he would interact with slides on tables or data visualization relative to slides filled with text/notation. This stressed how I should present my findings to increase their impact and accessibility.

Second, the amount of coffee that I would consume during the day increased sharply during and after this visit because, following David’s example, I started to regularly use trips to coffeeshops to discuss research ideas or work through challenges with colleagues who would join me on a coffee run.

Third, he also changed the way that I supervise graduate students as well as stay in contact following their graduation. David has coauthored papers with many of his former PhD students and has a sterling reputation for his work with students.