David Card seems like a pretty mild-mannered guy. True, he speaks with conviction, but it is confidence backed by meticulous research and tempered with open acknowledgment of the limits of that research. Card, an economist
at the University of California, Berkeley, is the antithesis of a zealot.
Nonetheless, by virtue of the topics he investigates, he has frequently found himself in the center of the nation's most incendiary controversies. And in many cases, Card's findings have been at odds with the conventional wisdom. Raising the minimum wage modestly is likely to have a negligible impact on employment levels, he has found. Immigration has only a minor impact on wages of native-born workers.
But it would be wholly inaccurate to say he's been drawn into these debates.
In fact, he has scrupulously avoided taking advocacy positions. A public stance,
he believes, might raise doubt as to the rigor of his methods and the impartiality
of his findings—two qualities he does defend zealously.
In 1995, Card was awarded the John Bates Clark Medal, given every two years to an outstanding American economist under 40 years of age. In granting the award, the American Economic Association highlighted Card's ingenious use of "natural experiments"—naturally occurring instances of the phenomena under study.
To study the impact of minimum wage legislation, for instance, Card looked
at fast-food jobs in New Jersey and Pennsylvania. To understand immigration, he examined the 1980 Mariel boat lift, when Miami's labor force increased by 7 percent. In a just-released paper on unemployment benefits and job search behavior, he scrutinized data from Austria, where workers on the job for 36 months or longer
get generous severance.
"If one unifying principle runs through David Card's work," observes Harvard economist Richard Freeman, "it is a belief in the power of empirical economic
science—in the ability to use statistics creatively to make inferences about how the economy operates."
TAX RATES AND LABOR SUPPLY
Region: As you may know, Ed Prescott has argued that different tax rates on labor in the United States and Europe explain why Europeans work fewer hours than Americans. Do you accept that explanation?
Card: I think that taxes could be part of the story. I would be surprised—given what I think is the credible range of estimates for the elasticity of labor supply—that tax differences are big enough to really explain the whole story.
It is conventional in one school of macroeconomics to assume that the elasticity of labor supply is quite high. And for some purposes that assumption may be correct. In thinking about responses to intertemporal or short-run shocks, for example, it is possible that the relevant elasticity is higher than labor economists have been able to estimate with conventional data and methods. A lot of work in the last 20 years has shown that the actual responsiveness of individuals to short-run fluctuations in wages may be bigger than the conventional estimates from the literature in the 1980s. Nevertheless, for the issue of taxes, we're really concerned about the long-run labor supply elasticity, which includes both the so-called substitution effect, representing the pure price effect of the higher wage, and the income effect. Those two go in opposite directions.
I believe that many labor economists in the United States—starting with H. Gregg Lewis, who was the intellectual father of modern labor economics—would agree with the view that in the long run the income effect dominates the substitution effect, so that over time, as societies become richer, people work a little bit less.
Region: They want more leisure.
Card: Yes, on average. That conclusion would be consistent with the long-run pattern of labor supply in the United States between 1890 and 1990. And in that case, one would normally assume that higher taxes [mean] lower wages and lead to a bit more work. That would have been my starting presumption, to tell you the truth: that the long-run labor supply elasticity is pretty small, and probably negative.
Twenty years ago, I think everyone was pretty comfortable with that notion that the reason hours fell from 60 or more per week at the beginning of the 20th century to well under 40 today is that we have become richer. More recently, hours trends have flattened out, and maybe today some people believe that the traditional interpretation of historical hours trends is incorrect, or inapplicable to the situation today. My own view would be that the plausible elasticity is not very big and that therefore the tax explanation won't go too far.
But I don't want to get in a fight with Ed Prescott. After all, he's got a Nobel Prize and I don't [laughs].
Region: Your research on the effects of raising the minimum wage, much of which was compiled in your book with Alan Krueger, generated considerable controversy for its conclusion that raising the minimum wage would have a minor impact on employment.
Have you continued to conduct research on the impact of raising the minimum wage? And do you have an opinion about "living wage" legislation and the petition that's been circulated recently with 650 or so economists calling for an increase in the minimum wage?
Card: I haven't really done much since the mid-'90s on this topic. There are a number of reasons for that that we can go into. I think my research is mischaracterized both by people who propose raising the minimum wage and by people who are opposed to it. What we were trying to do in our research was use the minimum wage as a lever to gain more understanding of how labor markets actually work and, in particular, to address a question that we thought was quite important: To what extent does the simplest model of supply and demand actually describe how employers operate in the labor market? That model says that if an employer wants to hire another worker, he or she can hire as many people as needed at the going wage. Also, workers move freely between firms and, as a result, individual employers have no discretion in the wages that they offer.
In contrast to that highly simplified theoretical model, there is a huge literature that has evolved in labor economics over the last 25 years, arguing that individuals have to spend time looking for job opportunities and employers have to spend time finding employees. In this alternative paradigm a range of wage offers co-exist in the market at any one time. That broader theory is, I think, pretty widely accepted in most branches of economics. The same idea is used to think about product markets where two firms that sell
very similar products may not charge exactly the same price. The theory explains a lot of things that don't seem to make sense, at least to me, in a simple demand and supply model.
For example, what does it mean for a firm to have a vacancy? If a firm can readily go to the market and buy a worker, there's no such thing as a vacancy, or at least not a persistent vacancy. During the early 1990s, when Alan and I were working on minimum wages, it was our perception that many low-wage employers had had vacancies for months on end. Actually many fast-food restaurants had policies that said, "Bring in a friend, get him to work for us for a week or two and we'll pay you a $100 bonus." These policies raised the question to us: Why not just increase the wage?
From the perspective of a search paradigm, these policies make sense, but they also mean that each employer has a tiny bit of monopoly power over his or her workforce. As a result, if you raise the minimum wage a little—not a huge amount, but a little—you won't necessarily cause a big employment reduction. In some cases you could get an employment increase.
I believe that that model of the labor market is correct. There are frictions in the market and some imperfect information. It doesn't mean that if we raised the minimum wage to $20 an hour we wouldn't have massive problems, if we enforced it. Realistically, of course, the U.S. is never going to enforce a draconian minimum wage, nor is one ever going to be passed. However, our results don't mean that minimum wages in other economies couldn't have some effect.
I think economists who objected to our work were upset by the thought that we were giving free rein to people who wanted to set wages everywhere at any possible level. And that wasn't at all the spirit of what we actually said. In fact, nowhere in the book or in other writing did I ever propose raising the minimum wage. I try to stay out of political arguments.
I think many people are concerned that much of the research they see is biased and has a specific agenda in mind. Some of that concern arises because of the open-ended nature of economic research. To get results, people often have to make assumptions or tweak the data a little bit here or there, and if somebody has an agenda, they can inevitably push the results in one direction or another. Given that, I think that people have a legitimate concern about researchers who are essentially conducting advocacy work. I try to stay away from advocacy of any kind, but that doesn't prevent people from being suspicious that I have an agenda of some kind.
I've subsequently stayed away from the minimum wage literature for a number of reasons. First, it cost me a lot of friends. People that I had known for many years, for instance, some of the ones I met at my first job at the University of Chicago, became very angry or disappointed. They thought that in publishing our work we were being traitors to the cause of economics as a whole.
I also thought it was a good idea to move on and let others pursue the work in this area. You don't want to get stuck in a position where you're essentially defending your old research. I certainly think it's possible that someone will come up with credible research documenting a situation where raising the minimum wage has a significant employment effect. I rather doubt we will see that right now because minimum wages are fairly low, at least in northern California where I live. My guess is that small raises in the minimum wage won't have much of an effect.
Region: As you know, some economic models rely on the assumption of sticky prices and sticky wages to help explain trade-offs between unemployment and inflation. What does your research suggest, if anything, about the importance of wage stickiness?
Card: About 10 years ago I did some work with one of my Ph.D. students at the time—Dean Hyslop, now at the New Zealand Treasury—trying to address the issue of downward nominal wage rigidity. Our work was motivated by the observation that in the presence of downward rigidity, we will see a lot of people who have fixed nominal wages. Instead of a smooth distribution of wage changes—some up and some down—we'll see a mass of people stuck at a zero increase. And the fraction of people with a zero increase will be higher when the inflation rate is lower.
This was an idea that was raised in an American Economic Association presidential address by James Tobin. He argued that pay administrators find it much easier to reduce real wages in a higher-inflation environment. And I think there's something to that. That is certainly what we found: The spike in the distribution of nominal wage changes at zero is higher when inflation is lower. On the other hand, we then tried to relate the size of the spike to the unemployment trade-off, and we didn't find much evidence of a connection.
I think there are some rigidities in wage adjustment. We've now had 15 years or so of low inflation, so presumably some of the fears or concerns that people had about nominal wage cuts might be different. But in any case, I would say the evidence that nominal wage rigidity has a strong impact on something like the overall level of unemployment is pretty tenuous and has remained quite tenuous. It was an interesting idea, I think, but the evidence is mixed at best. Certainly we couldn't find anything.
In the early 1980s, a lot of labor economists, including me, studied wage setting in the union sector. The staggered nature of union contracts motivated a whole line of research by John Taylor and others focused on the persistence of shocks in the economy, and I was interested in this general issue. In that particular context I found evidence of an effect of wage rigidity. Specifically, unionized firms with multiyear labor contracts have their nominal wages set two or three years in advance. If there is an unexpected bout of inflation, these employers end up with lower real wages than they initially intended. In the late 1970s, there were periods of rapid inflation, and real wages ended up 3 or 4 percent lower than expected. There was also a rapid slowdown in inflation in the early 1980s, so some employers ended up with unexpectedly high wages.
I used this idea to look for evidence of movements along the demand curve and found employment responses to unexpectedly high or low real wages. So in this case I found real responses to nominal rigidities, although these rigidities were actually built into formal contracts. This kind of rigidity is less interesting now with the declines in unionization in the U.S., though it is still important in many European countries, I think.
Region: Your work on labor strikes argued that economic models prevalent at that time, which suggested asymmetries—that management knew more about their companies' financial situation than did workers—weren't sufficient to explain strike patterns. And you proposed that other information asymmetries might be important.
Card: Right. I continue to believe that.
Region: Could you elaborate a bit on that? Have adequate models now been developed to explain strike patterns?
Card: I think people who were interested in union wage setting and negotiations were very excited about the emergence of asymmetric-information bargaining models in the 1980s. It had been clear since the work of the British economist John Hicks that strikes had something to do with information problems. The most straightforward explanation is that firms have an unobserved element of profitability, and the union is trying to learn if the firm is really profitable or not. If the firm is profitable, it won't be willing to undergo a long strike and will settle fast. Through the strike the firm signals its profit situation to employees. This story gives rise to a set of predictions that don't work out so well—like many other predictions in labor economics.
I think there's actually a lot of uncertainty on the other side of the bargaining table about the cohesiveness of the union. At a union meeting the leaders can say: "We're going to go out on strike, and no one's going to cross the picket line. Moreover, we think there will be strong support from the community." Community support is very important in strikes. For example, in a service sector strike, it's very important whether the Teamsters honor the picket line. If they do, UPS won't deliver, and it can become a very costly strike!
No one really knows the level of support that individual workers and their families, or the local newspapers and community leaders, will provide. I think that workers are often optimistic about their ability to stick to the picket line. And prior to the strike, they may not have much incentive to reveal their true situation. No one's going to stand up at a union meeting and say, "You know, I'd like to support this strike, but I'm behind on my mortgage and my wife's going to kill me if I go on strike."
So, the problems of information aggregation are much worse for the union than for the firm. The union is just an organization of people, whereas the firm has simple financial objectives. So I think that in some cases a strike is used by the firm to test the union's resolve. And in that case, when a strike is called, if the workers capitulate right away, they might well get a smaller wage increase than if they can hold out.
Of course, there is probably imperfect information on both sides of the bargaining table. However, if I were to work on this problem again, I would try to focus on information problems on the union side. I did some work using historical data from the 1880s on strikes, and the evidence was more consistent with the story I just gave.
Region: I'm impressed that you could find good data from that far back.
Card: It turned out that the Commissioner of Labor Statistics issued a detailed report on strikes in 1886. That's when the Knights of Labor were at their peak, and there was widespread concern about the spread of industrial unionism and the threats to American industry.
UNIONS AND INEQUALITY
Region: As you mentioned earlier, union membership has declined dramatically, at least in the private sector, in the United States. You've done a lot of research on the impact of that decline in terms of inequality among both men and women. Can you tell us briefly what you've found? And do you think the decline is a significant factor in growing income inequality in the United States?
Card: First of all, the presumption that unions might have an effect on men is based on the observation that within the union sector, wages are more compressed than outside the union sector. There are several institutional reasons for this. For one thing, unions try to equalize wages for people doing similar jobs. They also try to lower the differences between higher-wage and lower-wage people, largely for political reasons. Both features tend to lower inequality in the union sector.
The same thing is not as true for women, largely because unionized women work in sectors where there is already a lot of institutional wage setting, like teaching. In these settings, whether or not there is a union involved makes less difference. In any case, you don't see much difference in the variability of wages among women who are unionized, or not once you control for education.
What I had done was look at the decline of unionization and how that has affected overall inequality for men. One thing that countervails the equalizing effect of trade unions for men is that unions raise wages. If they raise pay for one group and leave it the same for another, that in itself increases dispersion. The starting point for any analysis is to measure how the equalizing tendency within the union sector plays off against the fact that wages are now higher for an arbitrary group of workers.
The answer for men has always been that the equalizing effect is bigger. Actually, this wasn't really understood in the literature until the early 1970s when Richard Freeman conducted the first detailed empirical studies of unions and inequality. Prior to his work people didn't realize the equalizing effect was so much bigger.
My results suggest that the decline in unionization is a small but noticeable part of the overall increase in inequality for men over the past 30 years—maybe 10 to 20 percent of the total. It was most important for workers at the middle of the wage distribution. Typically, a unionized worker is not somebody at the bottom of the distribution, but somebody at the middle. In the 1970s, unionization was pushing this group a little closer to the top and narrowing the degree of wage variability across jobs. As unionization has gone away, there has been some downward drift in the level of wages (relative to the top skill groups) and an opening up of wage inequality in sectors like trucking and manufacturing. Both effects are important, but they're only a small part of the overall trend.
And within the female labor force, there's really no effect because unions don't really equalize wages much for women.
SKILL-BIASED TECHNICAL CHANGE
Region: I think it's fair to say that most economists embrace the hypothesis of skill-biased technical change as the driving force behind recent inequality trends in the United States. Do you?
Card: Like a lot of other ideas in economics, I think that "skill-biased technical change" can be pulled off the shelf and used to explain inequality in a very superficial way. John DiNardo (of the University of Michigan) and I were troubled by the fact that there are a lot of patterns and trends in the labor market that don't fit in very well with a skill-biased technical change explanation. We were motivated to embark on a Don Quixote mission, a noble cause that wasn't going to go anywhere [laughs].
One thing we pointed out, for example, is that women are lower skilled than men, if you take the fact that they have lower wages as evidence of their skill. The SBTC theory says that people with lower skills should have slower wage growth than people with higher skills. But over the 1980s, women did much better than men. It's also the case that over the 1990s, women's relative wages were fairly stable again. So there was a long period of stability of women's relative wages, then a period of convergence of women relative to men that ended in 1991-92, and then stability again. That's an important set of trends that SBTC doesn't address. SBTC might be consistent with it; it might not be, but the theory needs a lot of auxiliary hypotheses to work.
The same thing is true with respect to the black/white wage gaps. Blacks earn less than whites, and many people believe that the reason they do so is because they're less skilled. Nevertheless, during the 1980s, the black/white wage differential was stable. It didn't widen as people had predicted it might.
Another trend that didn't fit with the SBTC hypothesis concerns the relative wages of people with different bachelor's degrees. There are a couple of different data sets that collect starting salaries for newly minted B.A.s. What these data show is quite remarkable. Everyone knows that the average wage of young college graduates went up over the 1980s. It wasn't the case, however, that the gains were most pronounced in engineering or science. They were actually greater for graduates in the humanities, which doesn't seem consistent with the idea that there is increasing demand for technically proficient, computer-savvy people.
Another thing we looked at were wage differences across industries. Historically, economists have argued that differences in average wages across industries are related to skill differences. Wages in many manufacturing industries, like airplane construction, are well above average; wages in other sectors, like retail trade, are much lower. Those pay differences remain even after you control for the characteristics of the workers.
This reminds me of something that would be fun to mention. A famous data set from the 1970s—the National Longitudinal Study—asked a series of questions called "Knowledge of the World of Work." Teenagers were asked questions like: "Who earns more: a worker in a shoe factory or a worker in a steel factory?" Every labor economist knows that the steel worker earns more. (Of course, there are no shoe factories in the U.S. anymore, and not so many steel factories, so the question is obsolete.) But the wage patterns across industries were so persistent that teenagers were supposed to know about them.
What DiNardo and I found, though, was that in the 1980s and '90s, there was no systematic tendency for wages in the lower-wage industries (like shoe manufacturing) to fall relative to wages in higher-wage industries (like steel). The wage structure was very stable. So if you believe that the industry differentials are due to skill differences, the patterns are not what you would expect from SBTC.
A final puzzle concerned the age structure of the increases in the relative wages of college versus high school graduates. Wages of young college-educated workers rose relative to young high school workers, but for people over age 40 or so, there really wasn't any change in the high school/college premium.
DiNardo and I pulled together all these facts and said: "Here are a bunch of facts about the labor market that people should be aware of and that we think should attract more research attention." To some extent, we were lamenting the fact that research on wage determination had lost direction in the 1990s. It seemed like analysts were saying: "It's all just SBTC. There's nothing more to say." We wanted to point out that there are many, many puzzles that SBTC can't explain and that people should be working on.
Region: So SBTC wasn't the silver bullet that it seemed to be.
Card: It's definitely not a grand unifying hypothesis. I don't know that experts in the area ever felt that it was, but to outsiders and students, it was sometimes portrayed as a unifying theory. In fact, it leads to some pretty bad predictions.
RETURNS TO EDUCATION
Region: I'd like to ask you about the education premium. Many parents and others today are concerned about rising tuition and high levels of debt assumed by college students.
Does your research into the returns to education suggest that such concerns can be mitigated by the likelihood of high earnings post-college?
Card: I've done research on two related questions. Probably the more important is the question of whether people who go to college earn more because of the extra schooling, or because they are talented and would earn more no matter what their education. My main contribution has been to analyze the implications of alternative schooling models a bit more carefully and to explain how some of the new studies that were conducted in the 1990s could be integrated into a model of the education choice decision.
I was motivated by the observation that in quasi-experimental studies that focus on very narrowly defined education interventions, you often find quite high returns to college attendance. For example, I did a study looking at the effect of college proximity on educational choices of children. The presence of a local college or university actually leads to some gain in education for the people who grow up in the surrounding county. The gains don't appear for the children of well-educated families (who were probably going to go to college anyway), but rather for the children from the middle and lower groups. I've always believed there was some effect of local education institutions. I grew up on a farm near a university town, and as a high school student, I certainly used the facilities of the university and felt that the university had a strong impact on the overall intellectual environment in that small town. So I found it plausible that college proximity matters, especially for children whose own parents are not as well educated.
There are many other examples of institutional reforms that end up having effects on children. What seems to be true in general is that the children whose behavior is affected by these reforms get very good returns to their educational investments, maybe better than average, and certainly at least as good as average. That is inconsistent with the notion that
people who weren't going to college before didn't go because they expected only small returns. It's more consistent with the idea that they were not going to college because they didn't really understand what college was about, or their parents hadn't pushed them in that direction, or because they couldn't afford it.
There's now been a lot of research around the world, and in most cases researchers find that when college is made more accessible, more people go to college, and they get good returns to their educational investment. It's not the case that they weren't going before because it wasn't worth it.
Now we come to the effect of tuition. I suspect that behavioral effects of tuition are a little overstated. It's easy to say: "I'm going to have to pay a lot more for tuition, and so I'm not going to go to college." In reality there are still quite a few generous programs, especially for lower-income families. And the economic value of going to college is higher than it's ever been, so the ability to pay off those loans is high. There are studies that have tried to isolate the effects of tuition policies, and they show some effect. Most recently there's a paper in the American Economic Review by an economist named Nicole Fortin that looks at the effect of tuition increases on college enrollments and finds a small but important effect.
Some economists believe that tuition costs can't really matter because everyone can easily borrow to pay for it. More broadly, however, I don't think it's really the case that lower-income families can't borrow the money. It's that they feel uncomfortable doing so, or don't quite understand the grant and loan programs available to them, or don't appreciate that although college seems like a risky investment, in most cases it's a very good deal.
Region: So it's an information friction?
Card: An information friction and perhaps a lack of sophistication. One of the interesting things that I've witnessed in my 25 years as a professional economist is the changing character of the students that I see in graduate school. Every year I do a poll of students and ask how many of their parents have Ph.D.s. That ratio is now close to 60 percent, even at Berkeley. We are getting a very select group of people going into Ph.D. programs, who have very different backgrounds from the average person in the country. I think that is a little troubling. It means our students don't really understand what a big leap it is for some families to send a child to college.
They don't think about college as a difficult choice, because everybody in their family has high education, and all their friends went to college and will probably go further. We live in a stratified society. There are many families with very high levels of education who are doing extremely well, others with much lower levels of education who earn a modest living. I think it is important for labor economists to have some insights into the lower group as well as the higher group. In my experience, no one ever becomes a labor economist whose family was too well off. They go into other fields.
Region: And you were born on a farm.
Region: Since the controversial 2000 presidential election, many have called for the implementation of electronic voting to increase reliability of results. The Help America Vote Act was passed into law in 2002 to facilitate such efforts.
You've found some intriguing correlations between the use of touch-screen voting and a number of other variables. What does this research suggest about the likely impact of increased use of electronic voting technology? And please bear in mind this interview will appear in December.
Card: After the 2000 and 2004 elections, there was a lot of discussion about vote fraud. If you Google "electronic voting," you will find a large community that is concerned about vote fraud and the spread of electronic voting machines. Some of them are quite serious.
My co-author (Enrico Moretti) and I were also motivated by the observation that voting is a form of social behavior. You don't get anything out of it. From a rational point of view, it's very difficult to explain why people vote. But voting is critical to the political system, and I think a real concern about any voting technology is whether people believe it's fair. You need to believe that you're not throwing your vote away. People won't vote if they believe the system is corrupt.
We were interested in what the data show about electronic voting, because a number of small-scale studies seem to suggest that there is something irregular about voting outcomes when electronic voting machines are used. We tried to put together all the data and see whether there is any systematic evidence that the share of votes going to one party or the other is affected by the use of direct recording electronic technology—so-called touch-screen voting machines.
What we found is that although there is a statistical correlation between DRE technology and vote shares, it's very difficult to make the claim that there was a systematic effort to skew the vote. DRE technology is no more likely to be adopted in places where, say, a Republican is the secretary of state, or where the vote is quite close and a Republican is the secretary of state. If you really thought there was manipulation going on, you would expect to see a pattern of vote outcomes that is associated with who is in charge of selecting and programming the DRE machines, and that's not apparent in the data at all.
We also found that the correlation between the use of DRE and voting outcomes is quite sensitive to how one handles trends in the underlying electorate. For example, DRE technology has spread much more quickly in the South, and the South has gradually changed from being more Democrat to being more Republican, so it may look like DRE technology is associated with a shift toward Republican vote share, but that's probably not the right explanation. Rather, DRE happened to be adopted in certain places, so there's a spurious correlation.
As often happens in labor economics, our conclusion is that in the absence of random assignment of DRE technology—a real experimental test, in other words—trying to make a statement about whether DRE technology affects voter outcomes is extremely difficult. We don't think that the data point to evidence of systematic corruption, but the nonexperimental research design at hand is not strong enough to really make a good statement.
Region: You've found that the economic impact of recent immigration on native-born workers is slight and that second-generation immigrants have done well educationally. Not all economists appear to accept those conclusions.
What do you feel is the heart of the disagreement, and does it seem likely to you that economists will be able to arrive at a consensus sometime soon?
Card: I don't have a prediction for that. Again, my interest in the question of immigration is driven by a slightly different objective than asking whether immigration is good or bad. Looking across different cities, we see remarkable variation in the local skill distribution. A city like Los Angeles is nearly half immigrants and has a very high fraction of less-educated immigrants. Other cities like Pittsburgh and Cleveland have very few immigrants and actually have a relative shortage of low-educated workers. That leads me to ask, How is the labor market adapting? That is one of the most important questions in my field: How do markets adjust to differences in supply?
I've also been motivated by trying to understand the mechanisms that lead to the apparent flexibility of the U.S. labor market. Economists believe that U.S. labor markets are relatively successful. Certainly around the world we're held up as a paragon of adaptation to immigrants in particular, but also to other economywide shocks. I've always thought it was important to understand why.
I'm not sure that there is really so much difference of opinion on the impacts of low-skilled immigration. Let's consider two extreme views: The most extreme negative view amongst professional economists would be that between 1980 and 2005, continued immigration reduced the wages of the least-skilled natives by 4 or 5 percent, once we take into account capital adjustments. On the other side, I don't think anyone thinks immigration has helped low-skilled natives very much. So the most positive view would be a zero effect.
So relatively speaking, that leaves a very narrow range. Rhetorically, however, the debate is mired in the same problem that arises in the minimum wage literature and the school quality literature. The debate is polarized between people who say "no effect" and people who say "big effect." And that is not really helpful at the end of the day. It's quite possible that unskilled immigration is having some negative effect on unskilled natives. The question is, How big is the effect? Has it reduced native wages by 20 percent, or has it reduced their wages a couple of percent?
Given my reading of the literature, the best available evidence is the effect is on the order of a couple of percents nationwide over 25 years, and possibly a little bigger in certain local labor markets, although as I said in the presentation today, I think the effects are hard to isolate. [See Supply, Demand & Deadlines '06.] Given that, it seems like we should move on to focus on the other effects of immigration. And research from a theoretical perspective as well as from an empirical perspective suggests that there are positive benefits for other workers, for consumers and for the economy as a whole.
So my perspective on the question is that U.S. labor markets are remarkably able to adapt to changing composition of local labor forces. Immigrants are absorbed incredibly quickly and easily, at least in most cities. In the future my work, I think, will be focused on the adaptation question. What are the main mechanisms for absorbing immigrants? What does that tell us about the way that the labor market as a whole functions? What lessons does it give for other countries, where immigrants don't do so well?
I think some economists are concerned that immigration has gone "too far." Just as in the minimum wage case, where it's important for opponents to show that the minimum wage has reduced employment, people who want to lower the rate of immigration think it's extremely important to emphasize the negative effects of immigration, at the expense of other dimensions of the story.
My guess is that at the end of the day, most voters' and legislators' views about immigration, and even most economists' views, are driven by concerns outside of the narrow realm of economics. They're driven by concerns over protecting the English language or the political culture of the country. Some people believe that cultural and linguistic diversity poses serious challenges for a country. Others believe that diversity is good, and we'll be a better country if we have more diversity. At heart, these views have little to do with the labor market effects of immigration.
WHY LABOR ECONOMICS?
Region: What motivated you to become a labor economist? Obviously you had the econometric bent, but you could have applied that in any number of fields. Other fields might have been "sexier," more remunerative; you could have gone into finance. Why labor economics?
Card: I think that I've always been interested more in human behavior than in the behavior of derivative assets [laughs]. Actually, as a graduate student at Princeton in the late 1970s, two of my fields were labor and finance. So, having followed the finance literature a little, I think there have been a lot of interesting developments. Certainly the techniques that have been developed for dealing with uncertainty in a continuous-time environment, for example, are quite interesting. And I think the basic ideas about markets really work in finance. In the labor market, there are information issues, rigidities and a huge amount of heterogeneity, none of which you have when you're dealing with shares of IBM or options in Dell.
Much of my work has focused on how the labor market works for lower-skilled or less-able people. I think somebody should pay attention to that. It seems important enough to me. Trying to understand why some people succeed and others fail, and how their success or failure is related to the environment, institutions and the people themselves—those seem like important issues to me.
There is an even simpler explanation though. I actually started out as a physics major in college and switched into economics relatively late. So I needed to get into classes that would take me. One of the few I could get into was labor economics. And I had a very good instructor—Michael Abbott—who was a student of Orley Ashenfelter. Orley then recruited me to go to Princeton as a Ph.D. student. So my history was set.
In the 1980s, labor economics was also a very exciting field. It wasn't well understood by people outside the field, but labor economics was at the forefront in combining economic theory, high-tech econometrics and exciting new data sources. We felt we were on a very serious mission.
I am also a very practical person, and labor economics is an extremely practical field. I think it's a great accomplishment of American academia that you can find 10 labor economists who know everything there is to know about something like unemployment insurance or the welfare system—not just conceptual things, but all the details. If you want to evaluate a change in a program, or understand how the welfare system or unemployment insurance works, you need labor economists. Their focus will be on the data, first and foremost, and on the institutional features that matter. Labor economists also use models that are close to the data and aren't wildly inconsistent with long-run trends or well-known facts.
Economics as a whole is really a combination of two kinds of people: those who are very practically oriented and those who are more like mathematical philosophers. The mathematical philosophers get most of the attention. They deal with the big unanswerable questions. Labor economists try to be more scientific: looking for very specific predictions and trying to test these as carefully as possible. The mathematical philosophers get very frustrated by labor economists. They come up with a broad general theory, and we tell them it doesn't fit the evidence.
Region: Skill-biased technical change, for example?
Card: Or tax differences explaining labor supply differences.
Region: I was trying to get a little farther from Minnesota [laughs].
Card: Right. An interesting new example is behavioral economics. Behavioral economics is largely driven by a philosophical approach. People in the field believe that humans have a lot of trouble making decisions and make systematic mistakes. A lot of students come to Berkeley to study behavioral economics ...
Region: ... because of Matthew Rabin and George Akerloff?
Card: Yes, and others. They're great colleagues and wonderful teachers, and inspiring to the students—much more so than labor economists. But I like to remind students that they need to know the practical side of economics too. I explain that if they get a job in Washington and someone asks them how many more people will enter welfare if we raise the benefit level, they are going to come back and do the same calculations that Orley Ashenfelter did in 1983. Labor economists need to know the basic nuts and bolts of our field. That's why we get paid reasonably well. On average, philosophers don't get paid much [laughs].
Region: Thank you so much.
October 17, 2006
More About David Card
Class of 1950 Professor of Economics at the University of California, Berkeley
Director of the Center for Labor Economics at the University of California, Berkeley
Faculty Research Associate of the National Bureau of Economic Research
Visiting Professor of Economics at Princeton University, 2000–01;
Professor of Economics, 1987–97; Assistant Professor of Economics, 1983–87
Fellow at the Center for Advanced Study in Behavioral Sciences,
Visiting Professor of Economics at Columbia University, 1990–91
Assistant Professor of Business Economics in the Graduate School of Business at the University of Chicago, 1982–83
Professional Activities and Memberships
Editorial Board, Journal of Population Economics since 2001 and Canadian Public Policy since 2000
Florida Opportunity Scholarship Research Project Advisory Board since 1999
Co-editor, American Economic Review, 2002–05; Econometrica,
Russell Sage Foundation Immigration Advisory Committee, 1999–2001
National Institute of Health Social Sciences, Nursing, Epidemiology and Methods Review Panel, 1998–2003
National Research Council Institute of Medicine Board on Children,
Youth and Families, 1998–2001
Joint Center for Poverty Research, 1997–99
Inter-University Consortium for Political and Social Research Advisory Council, 1994–96
Statistics Canada Advisory Committee on Labour Statistics, 1990–2002
American Economic Association Representative to the U.S. Census Advisory Committee, 1991–96
Associate Editor, Journal of Labor Economics, 1988–92
Honors and Awards
Alfred Marshall Memorial Lecture, Cambridge University, 2000
Honorary LL.D., Queen’s University at Kingston, Ontario, 1999
Fellow, American Academy of Arts and Sciences, 1998
John Bates Clark Medal, American Economic Association, 1995
Douglas Purvis Prize (for an article or book on economics and public policy
in Canada), 1994
Fellow, Econometric Society, 1992
Manufacturers Hanover Preceptorship in Economics, 1983–88
Prince of Wales Prize, Queen’s University, 1978
Author of more than 80 published research articles, reviews and comments focusing on immigration, labor, welfare reform and education, among other topics. Co-author (with Alan B. Krueger) of Myth and Measurement: The New Economics of the Minimum Wage in 1995.
Co-editor of five books, including Poverty, the Distribution of Income, and Public Policy (with Alan Auerbach and John Quigley) in 2006.
Princeton University, Ph.D., 1983
Queen’s University (Kingston, Ontario), B.A., 1978