Category: In Conversation

Equitable Growth in Conversation: An interview with Claudia Goldin

Posted on by Nick Bunker

“Equitable Growth in Conversation” is a recurring series where we talk with economists and other social scientists to help us better understand whether and how economic inequality affects economic growth and stability.

In this installment, Equitable Growth’s Executive Director and Chief Economist Heather Boushey talks with economist Claudia Goldin about the gender wage gap and some of its implications. Read their conversation below.

Heather Boushey: I want to focus on your work on the gender wage gap. Lots of us have been thinking about this for a long time and noticed that you have gotten a lot of attention in the press for your recent research on this, so I wanted to ask you some questions teasing out both what it is and what some of the implications are.

In your paper, “A Grand Gender Convergence: Its Last Chapter“—and I love the title of that—you argue that the gender wage gap cannot be explained by differences in productivity between men and women. Instead, when we look at occupations, we see that there is a price paid for flexibility in the workplace. And given what people are thinking about in terms of policy, that seemed like a really good place to start our conversation today. Can you tell me a little bit more about this result?

Claudia Goldin: So the key finding is that there is a gender wage gap. But the question is why? We know from lots of people’s work that we used to be able to squeeze a lot of the gap away due to differences in education—differences in your college major, whether you went to college or not, whether you have a Ph.D., an M.D., whatever. We were also able to squeeze a lot away on the basis of whether you had continuous work experience or not.

Today, we are not able to squeeze much away. In fact, women on average have more education than men. The quantities [of women with college degrees] are higher, and even the qualities [of degrees] aren’t that much different anymore. And the extent of past labor force participation is pretty high. Lifecycle labor force participation for women is very, very high. So we can’t squeeze that much away anymore.

What’s also really striking is that, given lots of factors such as an individual’s education level, many occupations have very large gender gaps and some occupations have very small gender gaps. Looking at occupations at the higher part of the income spectrum, which is also the higher part of the education spectrum — so occupations where about 50 or 60 percent of all college graduates are—we see that the biggest gaps are in occupations in the corporate and finance field, in law, and in health occupations that have high amounts of self-employment. And the smallest gaps are found in occupations in technology, in science, and in lots of the health occupations where there is a very low level of self-employment.

That’s sort of a striking finding.

Then when we dig deeper and look at particular occupations—in law, for example, and in the corporate and finance field—we see a couple of things. We see that differences in hours have very high penalties even on a per hour basis. Differences in short amounts of time off have very high penalties, unlike in other fields. And many of the differences occur at the event of or just after the event of first birth. So there is something that looks like women disproportionately, relative to men, are doing something different after they have kids.

When we look at men and women in the finance and corporate fields who haven’t taken any time off and among the women who don’t have kids, we find that the differences are really tiny. So those are the differences that are coming about, not surprisingly, from the fact that women are valuing predictability, and flexibility, and many other aspects of the job that many men are not valuing.

So, looking at data for the United States, we find that this change from being an employee, a worker, and a professional, to being an employee, a worker, a professional, and a parent has a disproportionate impact on women.

Now one might say, isn’t that because the United States has really lousy coverage in terms of parental leave policy, and in terms of subsidized daycare? Well, there are two very interesting papers, one for Sweden and one for Denmark. Both countries have policies that are just about the best in the world, and these studies, using these extraordinary cradle-to-grave data that they have, look at the widening in the — what men are getting versus women is occurring at — they can do an event study at that [having a child].

And women are moving into occupations that have more flexibility, but they are working fewer hours and getting less per hour. And the same sorts of things are going on even in countries that have incredibly good parental leave policies, subsidized daycare, schools that appear to us to be better, and what we think of as social norms that are better.

Boushey: One of the things that you found in your research that you haven’t mentioned yet is this idea that some workers are more substitutable—this idea that the industries with a high level of self-employment play some role in the gender pay gap. Could you explain that a little bit?

Goldin: Well, it would be very nice for us to go to each one of these occupations and take part in each one of these occupations and learn something about them. We can’t do that so instead we use the O*NET database, which gives us a lot of information about what goes on in these occupations.

And in O*NET, there are certain characteristics of the occupations that seem to map very nicely into aspects that would appear to be important, such as how predictable the job is, what the time demands are, whether you have to deal with clients, or whether work relationships are important.

And much of that is related to the issue about whether if an individual wants to leave work at 11 o’clock in the morning but do the same task at 11 o’clock at night, whether that’s severely penalized. That would be penalized if the individual can’t easily hand off work to someone else if it is needed at 11 a.m. That would be important if the fidelity of the information would be altered, if the client would feel that the individual wasn’t a very good substitute, and so on.

So using this information from O*NET, I find that the occupations that have the largest gender gaps are those that have the least predictability and the greatest time demands. And the occupations that have the smallest gender gaps are on the other side. It’s not necessarily causal, but it’s pretty good evidence that there is something going on.

And then I drill down deeper into particular occupations, such as the work that I have done on MBAs in the corporate and finance sector, and the longitudinal information that exists on lawyers. And finally, there’s a very interesting occupation that went through tremendous change during the 20th century and into the 21st century, and that’s pharmacy.

Pharmacists used to own their own businesses by and large, and they hired other pharmacists to work with them, often part-time. Many of these part-time workers were women, but there were few women who were owners. Well, ownership involves lots of responsibility, and as the owner, you are the residual claimant [the person with the last claim to the firm’s assets]. So in 1970 or so, women got about 66 cents on the male dollar in terms of pharmacy. Today, women working full-time full-year get 92 cents on the male dollar, uncorrected for any other differences and a lot more adding other relevant factors.

There are three things going on here. One is that there is no longer a lot of self-employment. Pharmacists by and large are not working for independent pharmacies anymore. They are working for big chains, national chains, regional chains, world chains. So the residual claimant now is the owner of the stock. There is professional management, and then there are just people who work there who are pharmacists.

The second thing is that there is very good use of IT. Every pharmacist now knows all the prescriptions that you have under your health plan, not just the ones that were filled in that pharmacy. And the third thing is that the drugs themselves are highly standardized by and large, so it isn’t that you are very attached to a particular pharmacist because they fill your prescriptions better or because they know you better. Pharmacists are highly paid professionals, but they are very good substitutes for each other.

Boushey: I’m glad you brought that study up, because I was going to ask you about it. My great uncle was a pharmacist, so I also just find it personally a fascinating example.

If you look at O*NET and the kinds of things that you are measuring, it seems like there are some cases where it seems very logical—especially in the case of pharmacists—that the substitutability is related to the profitability of the firm. It seems like a real strong business case.

Have you found in your research examples where perhaps not the substitutability but the job requirements around predictability or schedules may be more about keeping some workers out than they are about what’s good for the firm?

Goldin: Well, I’m all ears. (Laughter.)

Boushey: Yeah, I don’t know that I have answers there. I just think it begs the question. And I don’t know if you have thought about how to discern that difference in terms of —

Goldin: It’s that firms are leaving very large amounts of money on the ground. And so, if they are able to do that, they are able to pay for their taste for discrimination, then they can [discriminate]. And so that’s what one would look for, whether there are invaders standing at the gates. And if there aren’t, then they can do that and get away with it.

But the question is, where are the invaders that should be standing at the gates?

Boushey: And if part of what you have found is that a lot of this happens right after a child, that’s an invader of a different kind, perhaps.

Goldin: What’s interesting in the case of the MBAs is that it’s not right after the kid. It’s like two years later.

Babies are easier to take care of than 2-year-olds, and so it’s not that the firm then says, “Aha, we have one of those that has kids. We’ll just make certain that she doesn’t get the clients.” And one hears a lot of those stories, and those are the ones that the HR people are always talking about and making certain that people in their firm don’t do that—don’t have sexist paternalism, as it’s called.

But that doesn’t seem to be what is going on. I’m not doubting that there isn’t some of that, but what seems to be going on is that the individual tries and tries—in our data at least, in the Chicago Booth [School of Business] data—and eventually it’s just too much. There are too many demands, so they decide to scale back somewhat.

Boushey: Then I guess there are two questions. It sounds like it is that scaling back that causes the gender pay gap, right?. And what can we do about it?

Goldin: If a firm somehow believes, or it’s the case that right now, its production function is such that working 80 hours a week is worth a lot more than having two workers work 40 hours a week, then that produces non-linearities in pay and it leads to exactly what we are seeing. End of story.

Boushey: And on the policy side, it sounds like there isn’t a lot of incentive from the firm’s side to fix that –

Goldin: No, there’s a lot of incentive on the firm’s side. If I’m paying someone more than twice as much to work 80 hours a week than I’m paying two people to work 80 hours a week, then I should think about ways of reducing my costs.

And if I am working people 80 hours a week and that leads people with skills, very expensive skills, to leave, then I should want to do something to keep them there and to figure out how to make certain that they aren’t working 80 hours a week.

I often hear how the CEO of a company has said, “We really want to keep our talent—women as well as men who don’t want to work 80 hours a week, who don’t want the pressure of being called up when they are at a soccer game with their kids, on a Sunday or a Saturday or an evening, or whatever.” The CEO will set down a policy to ensure that doesn’t happen, but then there are a lot of managers who don’t hear that or who claim they don’t hear that. So lots of firms hire HR people to go around and make certain that this is policed.

And these issues are present even in the military. Some time ago at a conference on workplace flexibility, Adm. Mike Mullen, former Chairman of the Joint Chiefs of Staff, essentially said “I’m having trouble doing it, and I’m the head of the entire military.”

So there are principal-agent problems that firms would like to rein in. So they are losing money.

Boushey: Yeah. Well, the federal government implemented a “right to request” policy in one of the agencies—I believe it was OPM, the Office of Personnel Management. I talked to them when they were starting to implement that and the folks we were talking to were super excited, and then they told me, “Oh, yeah, we had some problems with middle management actually implementing it.” And then they stopped the experimenting and I never heard about it again.

Goldin: Yeah.

Boushey: And I think it’s a real challenge how firms are making that connection between that profit motive that the big guys are thinking about and what’s actually happening.

Goldin: Right. But there are lots of firms that have what they call work-life balance, or work-family balance; where, if you work at 11 at night versus 11 in the morning, that’s perfectly fine with them.

I was talking with a very senior partner at a well-known consulting firm once and I asked, “Well, what do you do when clients [call people up at 11 p.m.]?” And she said, “I call up the clients and I say, I have staff and they are not your slaves.” Well. (Laughter.)

Boushey: Good for her.

Goldin: Good for her, and right. But let’s just say that there are cases in which we don’t want someone to have a perfect substitute. I do not want my president, for example, to turn around and say, “oh, by the way, I really don’t like this unpredictability business. You know? That little red button on the phone—every now and again, I say, you know, I’m really not here right now.” (Laughter.)

Because there are cases in which that person better be on 24/7 and that’s it. And we know that in the world of work, those people get higher pay—or, in the case of our president, just get better ratings.

So there are going to be cases in which individuals who are willing to work long hours, work unpredictable hours, be on call, whatever we want to call it, are going to get more. And they are not going to be substitutable. And information is not going to flow perfectly, with total high fidelity.

The question is, what fraction of the occupations in the economy are like that? And I think you and I would agree that the fraction is probably a lot lower than appears to be the case right now.

Boushey: So what should folks who are thinking about policy do about this? Is there a role for us, or is this just a business case? Do they all have to learn this lesson on their own, or is there something policymakers can do?

Goldin: Yeah, we have a policy. It’s called public schools. We’ve had it for a very, very long time. We have public schools that get out nationwide at about 2:30 or 3:00, that end sometime in June, that begin school at 5 years old or 6 years old. None of that was ever discussed as being the optimal way to run schools.

It is suboptimal with respect to individuals who have kids, because kids are not one- or two-year capital goods. Family leave policy is not the only thing that’s going to help families with kids, because the kids live, I hope, for many, many years after they are 2 years old. That’s the policy.

Boushey: I love it. That’s a fantastic way to end this interview, and something I will take with me in my travels here in Washington. Thank you so much, Claudia.

Goldin: Thank you.

This interview has been edited for length and clarity.

Equitable Growth in Conversation: An interview with David Card and Alan Krueger

Posted on by David Hudson

“Equitable Growth in Conversation” is a recurring series where we talk with economists and other social scientists to help us better understand whether and how economic inequality affects economic growth and stability.

In this installment, Equitable Growth Research Economist Ben Zipperer talks with economists David Card and Alan Krueger. Their discussion touches on the origins of empirical techniques they advanced, how the United States is falling behind when it comes to data, and two conflicting threads of contemporary economic theory.

Read their conversation below.

Ben Zipperer: A common theme in both of your work involves isolating specific interventions or plausibly exogenous changes in the phenomena you’re studying, say in the case of your famous study comparing restaurants in New Jersey and Pennsylvania after a minimum wage increase. What kind of challenges did you face early on in that research—in the days before words or phrases like “research design” and “natural experiment” were kind of ubiquitous terms in the field of economics?

And then also, can you talk a little bit about the influence of the quasi-experimental approach on labor economics today and maybe the field of economics as a whole?

David Card: There are several origin stories that meet sometime in the late ’80s, I would say, in Princeton. One part of the origin story would be Bob LaLonde’s paper on evaluating the evaluation methodologies. So, in the 1970s, if you were taking a class in labor economics, you would spend a huge amount of time going through the modeling section and the econometric method. And ordinarily, you wouldn’t even talk about the tables. No one would even really think of that as the important part of the paper. The important part of the paper was laying out exactly what the method was.

But there was an underlying current of how believable are these estimates, what exactly are we missing. And some of that came to the fore in LaLonde’s paper.

He was a grad student at Princeton in the very first cohort that I advised: He was actually a grad student when I was a grad student, but he was a couple years behind me.  Then I was his co-adviser with Orley Ashenfelter. And in the course of doing that work, it became pretty obvious that these methods were very, very sensitive: If you played around with them, you got different answers.

The impetus of that paper was some work that Orley and I were asked to do evaluating the old CETA programs. There were a bunch of different methods that were around and they would give very different answers. So Orley had the idea of setting Bob on that direction and that really evolved that way.

So that was one part of the origin story. Another part was the move from macro-type evidence to micro evidence. There was growing appreciation of that. And the first person that I saw really use the phrase “natural experiment” was Richard Freeman.

Alan Krueger: That’s who I learned it from, too. Richard always had an interest in evidence-based natural experiments. He was an enormous fan of the work by LaLonde; also, the paper Orley did in JASA [the Journal of the American Statistical Association] on the negative income tax experiment. Richard always had a soft spot for natural experiments. But I think he used the term differently than we would.

He applied it to big shocks. So to him, the passage of the Civil Rights Act was a natural experiment. The tight labor market in the 1960s was another natural experiment. I think the way he viewed it was a bit different from the way it started to get applied, which was that the world opened up and made a change for some group that could be viewed as random. When Josh Angrist and I looked at compulsory schooling, we looked at a small change.  The natural experiment was just being born on one side or the other of the threshold for starting school, which then affected how many years of education you ultimately got because of different compulsory schooling laws and students would reach the minimum schooling age in different grades.

But that’s where I first heard the term.

Card: Right. And you mentioned research design. I remember Alan was an assistant professor and I was a professor at Princeton and Alan sat next to me. And he, for some reason, got a subscription to the New England Journal of Medicine. (Laughter.) And —

Zipperer: Intentionally?

Krueger: Yeah. I loved reading the New England Journal of Medicine.

Card: Yeah. And the New England Journal would come in every week, so there was a lot of stuff to read. And the beginning of each article would have “research design.”

Krueger: And “methods.”

Card: Yes, and if you’ve never seen that before and you were educated as an economist in the 1970s  or 1980s, that just didn’t make any sense. What is research design? And I remember one time I said, “I don’t think my papers have a research design.”

And so that whole set of terms entered economics as a result of those kinds of changes in orientation. But I would say that another thing that happened was that Bob LaLonde got a pretty good job and his paper got a lot of attention. And then Josh Angrist, again following up a suggestion from Orley to look at the Vietnam draft—that paper got a lot of attention. And it looked like there was a market, in a way, for this new style of work. It’s not like we were trying to sell something that no one wanted. There was actually a market out there generally, in the labor economics field, at least.

Krueger: There was, but there was also resistance. (Laughter.)

I agree with everything David said. The other thing—which I think helped to support this, although maybe it gets overrated—is that data became more available, and big datasets like the Census were easier to use.

Historically, when the 1960 Census microdata first became available, Jacob Mincer used it and had an enormous impact. And I think the fact that we were inventorying more data meant that if you wanted to look at a natural experiment – for example, a change in social security benefits which affected one cohort and not another —  the data were out there to do it.

I think another thing — which was a bit new when we did it for our American Economic Review article on the minimum wage — was to go out and collect our own data when we saw the opportunity to study a natural experiment. But in other situations the fact that there were just data out there to begin with, I think, helped this movement.

Card: Yeah. That was the case with my Mariel Boatlift paper. It was written a little bit before we started working on minimum wages. And in that case, it just so happened that the Outgoing Rotation Group files were available starting in 1979. And so, with those files, it was fairly straightforward to do an analysis of what affected even the Miami labor market.

And in retrospect there’s a new paper by George Borjas flailing around trying to overturn the results in my paper. But in truth, if somebody had been on the ground in Miami in 1980 and gotten their butts in gear, there would have been so much more interesting stuff to do.

For instance, when Hurricane Andrew happened, people actually convinced the CPS to do a survey or supplement, right?

Krueger: Yes.

Card: So, I think the whole, not just the profession, but even maybe the government, has become a little bit more aware of the importance of really strategically moving resources around and collecting data.

And now the administrative data is available for some things as well.

Zipperer: Speaking of data access, how important do you think it is now for work on the research frontier of labor economics, say, to have administrative data access, or access to often-restricted-access datasets? Is the United States positioned as a leader in this? Or are we paling in comparison to other countries?

Card: Well, we’ve got a lot of disadvantages. One problem is that we don’t have a centralized statistical agency. And so you’ll forever run into someone who wants to do a project and they’re not able to do it because there’s a bureaucratic obstacle to using this particular dataset or that particular dataset.

So for example, matching the LEHD [Longitudinal Employer-Household Dynamics] data to the Census of manufactures or the Census of firms. That would be a natural thing to do, but not that easy to do. If it was one statistical agency, we would have a lot more ease.

And then the laws of the United States—not just the federal but then the state laws—governing access to, say, the UI [unemployment insurance] files. Partially, those are available to the Feds when they’re constructing the LEHD data or other types of datasets, but they’re not available to individual researchers.

Although Alan and I have both used, for example, data from New Jersey. So individual researchers can, in some cases, contact the state and get some help. But that often requires some combination of a person on the other side who actually wants to answer the phone and talk to you, and maybe some resources.

Krueger: Yes, so I would say we’re behind other countries in terms of administrative datasets. We’ve long been behind Scandinavia, which has provided linked data for decades. And we’re now behind Germany, where a lot of interesting work is being done.

And it’s unfortunate because we did lead the world, I would say, in labor force surveys. The rest of the developed world copied our labor force survey and copied our practice of making the data available for researchers to use.

It’s much more cumbersome, bureaucratic, and idiosyncratic here to get access to the administrative data. And I don’t think that’s good for American economists or for studies of the economy.

And it’s going to make it much harder to replicate work going forward. And that’s unfortunate because I think a strength in economics has been the desire to replicate results.

Card: But I think it is absolutely critical for front-line research in the field to have access to some kind of data. Either you get access to administrative data through personal connections like a lot of people do. Or there are certain countries that make it available, like Germany, for instance—I’ve done a lot of work there—or Portugal. Or like Alan has done where he’s used some of the resources available at Princeton to do some specialized surveys and connect the responses with the administrative data. That’s probably the frontier at this point. But that’s not going to be a thing that a typical person can do very easily.

Krueger: And we haven’t caught up in terms of training students to collect original survey data. I’ve long thought we should have a course in economic methods—going back to the New England Journal of Medicine—and cover the topics that applied researchers really rely upon, but typically are forced to learn on their own. Index numbers, for example. Or ways of evaluating whether a questionnaire is measuring what you want it to measure. And survey design, sampling design and the effect of non-response bias on estimates.

These are topics that other social science fields often teach and we just take for granted that students know it. And there’s a lot of work that’s being done, especially in development economics, on implementing randomized experiments, which I think is a net positive. But there’s also a lot of noise being produced. And I think having more training in terms of data collection, survey design, experimental design, would be helpful for our field.

Zipperer: You mentioned randomized experiments. What are your views on the pluses and minuses of what seem to be a variety of different empirical approaches now common in economic research, such as randomized experiments, actually conducting an experiment? Or a quasi-experimental approach, compared to say, a more model-centric approach? Or even more recent kinds of data mining techniques that let the data tell us the research design?

Card: I would say, and I think Alan would probably agree with me, that at the end of the day, you probably want to have all those things if possible. And each of them has some strengths and some weaknesses.

The strength of a randomized controlled trial is the ability to say you’ve got this treatment and this control group and it’s random. So that means that you’re internally consistent. The weakness is that the set of questions you can ask and the context in which you can ask those questions is often very contrived.

So the one extreme is the lab experiment, where you’re getting a bunch of students and you’re asking them to pretend that they’re two sides of a bargaining table or something similar. And by changing the way you set the protocols for those experiments, as people that work in that field are aware, you can get somewhat different answers. To some extent, the criticisms of psychology that you would see played out in the newspapers recently has a lot to do with those difficulties. It’s not just how you read the script but how you set up the lab and everything else that kind of matters.

So the great advantage of a quasi-experiment or natural experimental like minimum wage is that it’s a real intervention. It’s real firms that are all affected. You get part of the general equilibrium effect. That’s pretty important for understanding the overall story. The disadvantage is that someone can always say, well, it isn’t truly random. And the number of units might be small. So you might only have two states. At some abstract level, there’s only two degrees of freedom there. And so that’s a problem.

And then there’s a third set of problems, which I’ve alluded to before, which is the types of questions that you can ask. And this is where my former colleague, Angus Deaton, is well-known for his vitriolic criticism of RCTs in development economics.

And I think one interpretation of his concern is the set of questions that can be asked are really so small, relative to the bigger questions in the field. Now that isn’t always the case but that is a concern.

Krueger: Yes, I would just add that no research design is going to be perfect. And you can poke holes in anything. And I think if you believe that existing research is great and we have answered so many questions and we were on the right track before, then one might be hostile towards the growth of randomized controlled trials. But that’s not how I view the earlier state of research.

In my mind, there are two great strengths of randomized experiments. One is that the treatment is exogenous by design. And the other is that it makes specification searching more constrained. It’s pretty clear what you’re going to do. You’re going to compare the treatment group and the control group.

I’ve seen cases where people muck around to generate a result from an experiment. For example, look at Paul Peterson’s work on school vouchers, where he finds no impact overall and kind of buries that, but looks at a restricted sample of African Americans in some cities and argues that we’ve got these great effects from school vouchers, which turn out not to hold up if you actually expand the sample. So I’m not saying that randomized experiments totally ties people’s hands. But I think they do so more than is the case with non-experimental methods applied to observational data.

I’ve become more eclectic over time regarding research method, as I mentioned at the event earlier today. I mean, I was struck when I worked in the White House at the range of questions I would get from the President. And you’d want to do the best job answering them. That was your job.

And there were some cases where there was very little evidence available and there was some modeling which, if you buy the assumptions of the modeling, could answer a lot of questions.

And I think that was probably better than the alternative, which is having a department come in and plead its case based on no evidence or model whatsoever.

So I encourage economists to use a variety of different research styles. What I think on the margin is more informative for economics is the type of quasi-experimental design that David and I emphasize in the book.

But the other thing I would say, which I think is underappreciated, is the great value of just simple measurement. Pure measurement. And many of the great advances in science, as well as in the social sciences, have come about because we got better telescopes or better microscopes, simply better measurement techniques.

In economics, the national income and product accounts is a good example. Collecting data on time use is another good example. And I think we underinvest in learning methods for collecting data—both survey data, administrative data, data that you can collect naturally through sensors and other means.

Card: Yeah. For instance, take the American administrative data that’s collected by the Social Security Administration. If you wanted to do something very simple to that dataset that would make it possible to do a lot more, you could ask each employer, who reports their employees’ Social Security earnings data to also report the spells that they worked — the starting and ending of the job.

That simple kind of information—which could be collected, maybe with some burden, but in many cases, almost trivially—would expand the use of that dataset amazingly, for just an amazing set of purposes.

It turns out, that’s what they do in other countries. So you can then take an administrative dataset like Social Security Administration and that suddenly becomes a spell-based dataset, because you’ve got every employment spell that somebody had during the year, automatically, for free.

It’s not perfect, but it’s just a quantum improvement. Unfortunately, though, we don’t have anybody saying, well, what could we do to make administrative datasets better and more useful for research?

There are people at the Census Bureau who are kind of working on matching administrative and non-administrative survey type datasets. But often times that’s way down in the subterranean levels, partially because of the concern that if people knew that you can actually take the Numident [Numerical Identification System] file and attach a Social Security number to every piece of paper going through, that they would be shocked somehow. So we have quite a problem here.

Zipperer: So, to take another concrete case where measurement seems to be particularly important and related to work that you’ve done on minimum wages, what kind of wage spillover effects do minimum wages generate for people who are, say, earning above a new minimum wage after a minimum wage increase?

There’s a lot of work showing that there are spillover effects and there are questions about how big they are, perhaps due to a measurement error in wages and survey data. What are your views about why these spillover effects seem to exist?

Krueger: Let me make some initial comments. In our book, we discovered spillover effects. When I say we discovered it, we asked in a very direct way when the minimum wage went from $3.35 to $4.25, and you had a worker who was making $4.50, did that worker get a raise as a result?

And what we found was that a large share of fast food restaurants responded “yes.” We had these knock-on effects or spillover effects.

Interestingly, they tended to occur within firms that were paying below the new minimum wage. You had some restaurants that were already above the new minimum wage. And the increase in the minimum wage had very little effect on their wage scales, which suggests that internal hierarchies matter for worker morale and productivity.

Only to economists is that surprising. The rest of the world knows that the way that they’re treated compared to other people influences their behavior, and the way that they view their job and how likely they are to continue on their job, and so on.

The standard textbook model, by contrast, views workers as atomistic. They just look at their own situation, their own self-interest, so whether someone else gets paid more or less than them doesn’t matter. The real world actually has to take into account these social comparisons and social considerations. And the field of behavioral economics recognizes this feature of human behavior and tries to model it. That thrust was going on, kind of parallel to our work, I’d say.

Now, I also found it interesting that when the minimum wage was at a higher level compared to a lower level, the spillover effects were less common.

So to some extent, the spillover effects are voluntary and the companies are willing to put up with somewhat lower morale when the minimum wage is at a relatively higher level. And I always found it curious that companies would complain, “It’s not the minimum wage itself, it’s that I’m going to have to pay more than everybody else.” Well, that shows that you’re actually not behaving the way the model that you just cited to argue that you are going to hire fewer workers says you should behave. Because you’re voluntarily choosing to pay people, who were working before at a lower wage, a higher wage.

And it also gets you to think, well, maybe the wage from a societal perspective was too low to start with. And the fact that employers are taking into account these spillover effects when they set the starting wage means that from a societal perspective, we could get stuck in an equilibrium where the wage is too low.

Now, I always suspected that the spillover effects kind of petered out when you got 50 cents or a dollar an hour above the new minimum wage. But interestingly, work by David Lee, who was a student of David’s and mine at Princeton, suggests that the spillover effects are pretty pervasive throughout the distribution. And he used a different method, one that I think is quite compelling to look at: What happened around minimum wage increases in states where they really had more of a binding effect?

And he found quite significant spillover effects. So one area where I think the literature has deviated from what we concluded in our book was we thought the spillover effects were there but they were modest. And I would say, if anything, it points to a larger impact of the minimum wage because of the spillovers.

Card: Thinking about why these occur—Laura Giuliano, who attended the conference today, has a very interesting new paper studying a large retailer that has establishments all across the country, where wages were set at the company level.

And the paper shows that employees who were above the minimum wage, but in stores where different fractions of the employees below them got bigger and smaller raises, have differential quit behavior. So it’s really strong direct evidence of this channel that everyone has always thought is probably true.

I think that our understanding of exactly all the forces that determine the equilibrium wage distribution is pretty limited, to tell you the truth.

In the United States, for example, it’s very, very difficult to get an administrative dataset that would say: Here’s everybody that works together at the firm. And let’s treat that, as Alan was saying, as part of the social group. What things do they share? What features of their outcomes seem to be mediated through the fact that they all work for the same employer?

And in the Scandinavian countries, there’s quite a bit of work that’s going in that direction. One really simple example is if a male boss at a firm takes leave when his wife has a baby, then the other employees do too. So that’s just a really simple example of the kind of work that you could do if you had the ability to match these datasets together and show they were all the firm.

I think outside of economics, in sociology for instance, they’ve always thought that a very important part of everyone’s identity is the firm they work for and who they work with.

And it has to be really influential in how you think about your life and how you organize your time and people you hang out with and so on. But in a standard economics model, that’s all thrown out the window. And for some questions, it might be second-order at best. But for other questions, it seems like it’s first-order.

Zipperer: Do you see that changing somewhat with, for example, your and others’ work on the nature of the firm influencing inequality?

Card: Well, I’m always hopeful. (Laughter.)

Krueger: Yes, I would say the success of behavioral economics is a major development in economics.

Card: And in labor economics especially, I’d say.

There is an interesting thing going on in economics. So, we see job market candidates that come through every year. And there’s sort of two sides of economics in their work simultaneously.

One side is uber-technical. More and more technical stuff every year. You cannot believe the complicated ideas that people are trying to pretend that individuals are working with and choosing whether to do this or that.

And on the other side, behavioral economics is almost a reaction to that. It says, “Actually, those effects are all third-order. The first-order thing is the concern is about how you rank relative to your peers.”

So the great advantage of behavioral economics is that it is saying, “OK. I’m going to try and simplify away from this incredibly complicated thing where your choice about whether to participate in a welfare program is influencing how you’re going to divide up the surplus between you and your husband and whether you’re going to be divorced next year.”

I saw a paper like this last week and I honestly thought, “If I could think this through myself, it would be a miracle.” (Laughter.) I spent my life thinking about that.

Krueger: And you oversimplified it: You’re considering each step in the way, assuming you will make optimal choices each year in the future, and then integrating back to figure out what to do today.

Card: So there are these two strands of economics that are really fighting it out right now in the theory side. And in a way, behavioral economics is much more closely linked to what I think someone earlier today was calling institutional economics. So it’s the idea that people are doing a set of things, maybe rules of thumb and so on, that are influencing how they choose what they do. That maybe we would gain a lot from understanding those things a little bit better.

Zipperer: At the beginning of this discussion, a lot of arrows seemed to point back to Orley Ashenfelter. Could you talk about his influence on your work and maybe the field generally?

Card: Well, for me it’s very strong because he was my thesis adviser and really the reason why I went to Princeton as a grad student. And even as an undergraduate, the two professors who I took courses from that had the most influence on me were students of Orley’s.

So my connection to him goes back a long time. And we wrote a bunch of papers together over the years and advised many students. But also many of the people of my generation of labor economists, like Joe Altonji, John Abowd, or other people like that, were strongly influenced by Orley.

Right from the get-go, he was a very, very strong proponent of “experiments if you can do them” and “collect your own data if you can do it” and “spend the money if you can.” One time, he and Alan went to Twinsburg Twins Festival and collected data on twins.

Krueger: One time? Four summers in a row we went to Twinsburg, Ohio, with a group of students. We brought a dozen students. (Laughter.)

And it was actually classic Orley because he spent a lot of time choosing the restaurant for dinner, a lot of time chatting with some people, and not too much time collecting data, as I recall.

I read Orley’s work when I was an undergraduate. And a big part of the attraction for me to come to Princeton was Orley, and then David was just really a bonus who I ended up working with so closely for a decade.

And I think Orley kind of set the tone for the Industrial Relations Section. He had done work on the minimum wage with Bob Smith at Cornell, on non-compliance and how much non-compliance there was—which made us think that, if you really want to look for the effects on minimum wage, you need to look in places where it’s binding and companies are complying.

He had a healthy dose of skepticism about the research that had come from the National Minimum Wage Study Commission. Which sometimes he called, as I recall, the National Minimum Study Commission.

Card: Minimum Study Wage Commission.

Krueger: The Minimum Study Wage Commission. (Laughter.)

Card: You can quote me on that.

Krueger: We’re just quoting him. (Laughter.) And he used to like to tell a story, which I remember vividly, where he met with some restaurant group when he worked, I think, at the Labor Department. And they said, we’ve got a problem in our industry: The minimum wage is too low and we can’t get enough workers.

And that’s inconsistent with the kind of view that the market determines the wage, and you get all the workers you want at the going wage, and you can raise the wage if you can’t get enough workers. And I think he was always sympathetic to the famous quote, in “A Wealth of Nations,” where Adam Smith said that employers rarely get together when the subject doesn’t turn to how to keep wages low; that there’s a tacit and constant collusion by employers. So I think he kind of set a tone where it was acceptable if you found results that went against the conventional wisdom.

And I came from an environment where even Richard Freeman at the time, who was a somewhat heterodox economist, had written that there’s a downward sloping demand curve for low-wage workers and a higher minimum wage reduces employment, but not all that much, but you get the conventional effects. So that was my background coming in.

Zipperer: Well, thanks very much. This was a great discussion.

Krueger: Sure.

Card: Sure.

Zipperer: Thank you.

Equitable Growth in conversation: An interview with Byron Auguste

Posted on by Nick Bunker

“Equitable Growth in Conversation” is a recurring series where we talk with economists and other social scientists to help us better understand whether and how economic inequality affects economic growth and stability.

In this latest installment, Heather Boushey, Executive Director and Chief Economist here at Equitable Growth, talks with Byron Auguste, Managing Director of Opportunity@Work. The two discuss the current problems with the labor market, how these problems may be mostly on the demand side, and how we might “rewire” the labor market.

Read their conversation below.

Heather Boushey: Byron, thank you so much for talking with us. The big topic that I want to focus on with you is about the demand-side problems when it comes to opportunity in the labor market. When we’re thinking about policy, we think a lot about the supply-side problems. And I know that you’ve spent some time thinking about the demand side and I’m eager to learn more from you.

Since the end of the Great Recession, the number of job openings in the United States has increased much quicker than the number of hires. And many economists have been interpreting that as a sign of supply-side problems—that workers don’t have the skills that employers are looking for. But you actually see this as a demand-side, or employer-side, problem. Can you tell us why?

Byron Auguste: The first step to really understanding what’s going on in the labor market is to think about it as a market, take it seriously as a market, understand its market characteristics, the information that’s available to the different actors, the incentives that they face, and then to look at their actual behavior and how it’s changed over time.

Over the past 30 years, there’s been an increasing sense that somehow there are these mismatches in the labor market. We have a situation where in 2015, open jobs that employers were trying to fill in the United States were at a record high, while at the same time, labor force participation among working-age adults was at a 40-year low.

A number of commentators and particularly businesspeople talk about this as a skills gap, which gives the impression that if only people were getting the right skills or more skills there would be no problem. But if you look at the labor market, both the changes in the demand side and the supply side, it’s really striking how much the supply side—that is to say, education and training—has been relatively stable, whereas the behavior of the demand side—how employers hire and fire, who and how they train, and just everything about their HR behavior—has changed dramatically in the last 30 years.

If you’re looking for the main reason to change the labor market, all the data and the stylized facts should lead you to look at the demand side first. And if you look at the demand side first, you see some really striking things.

First of all, you see that employers have significantly changed their model with respect to hiring and training. Thirty years ago, maybe half of hiring was in some sense entry-level hiring—hiring people out of high school, out of college, out of Ph.D. programs, whatever it was. The expectation was that the companies would train the new hires and they would learn generalized work skills, as well as the specific skills that companies need on the job.

But if you look at 2014, although we don’t have great data on this, Wharton professor Peter Cappelli has noted that entry-level hiring accounted for just 6 percent of all new hires in 2012—much lower—and that much more of hiring now is for experienced workers with very specific education and experience profiles.

When you’re looking at entry level hiring, it’s much easier to find poaching from other companies. Then on top of that, when employers look for these sorts of specific profiles, they tend to characterize them, like in a job description, in terms of their specific education and employment history.

The requirements for a four-year college degree, in particular, are rising dramatically. Burning Glass, a data analytics company in the labor market, showed that only about 20 percent of administrative assistants in this country have college degrees, but that two-thirds of the new job postings for administrative assistants require a bachelor’s degree. In other words, about 80 percent of existing administrative assistants can’t apply for two-thirds of the new jobs in their own field.

If you think about it, the way this “credential creep”  moved through many parts of the labor market, it might connect the dots to the fact that we have low voluntary quits. Voluntary job mobility is down by 23 percent since 2001. And of course that’s partly cyclical, but it’s much lower now than at a similar point in past cycles. And it’s because a lot of people are stuck. They can’t move, based on the way that employers have increasingly depended on these kind of backward-looking heuristics. That’s an example of the demand-side behavior that really stops people from making progress.

In addition, when you look at the demand behavior over the business cycle by employers, it’s a really big difference. In the first five recessions after World War II, U.S. employers only laid off about one-third of the workers they would have needed to lay off to fully offset the drop in demand for their products or services. In other words, two-thirds of their workforce, in the aggregate, was absorbed by what economists would call labor hoarding, but what a CEO would now call “missing quarterly earnings targets,” right? This happens so consistently in the post-World War II period that economists called it Okun’s Law [after macro economist Arthur Okun].

But employers don’t do [much of] that anymore; their behavior started to change in the early ’80s. It went to 50/50 in that recession in the early ’80s, then to 25/75—the other way—in the early ’90s. And in the last two recessions, U.S. employers laid off 100 percent of the workforce that was needed to offset the demand drop. In other words, there was no more labor hoarding, profits were maintained, and layoffs for workers absorbed the entire demand drop.

Okun’s “Law” has been repealed, but only in the United States. In the United Kingdom, employers are still laying off one-third, two-thirds; Okun’s Law is alive and well there. In Germany, employers have moved in the other direction and they had almost no layoffs in the last recession.

So, ten million people can get laid off all at once and employers still maintain the hiring heuristic that, well, if you’ve been laid off for a while, then you’re a riskier hire. We have lots of evidence that if you are unemployed—well, if you’re unemployed, period, but particularly if you’re unemployed for over six months—you’re somewhere between half as likely and a quarter as likely to get an interview, even when you have identical education and work experience as someone who currently has a job.

When you add up all of those factors—how employers hire, how much they fire, how they train, who they train—the data on internal employer training is not so great, so we don’t know exactly what’s going on. But we do know that training matters a lot. We know that employers, for example, spend probably something like 20 times as much as the federal government does on training.

We can estimate that on a per-worker basis, training expenditures have dropped by about 30 percent in the last 20 years or so. Although it’s harder to quantify, there’s a lot of evidence that the pattern of expenditure on training has shifted towards the middle and the top of the occupation and wage stack in companies, and most of the cutbacks in training expenditures are at the lower end, or frontline workers.

Typically, if you’re a frontline worker (e.g. working in a retail store, a factory, a warehouse, or a call center, for example) and no one’s reporting to you, then you’re probably just being trained for safety, compliance, and efficiency. You’re not being trained like higher-income workers who are being trained for job progression and cross-training, developing their human capital in ways that would allow them to contribute more and to earn more over time.

There’s tremendous bifurcation now in the labor market. It’s driven more from the demand side and it really flows back into the supply side of the market.

We need to look at the demand side harder, however it’s not at all to say that there isn’t a lot of improvement that’s needed in higher education and job training and K-12 education and the like; there really is. But when you look at job training and at the parts of higher education where the implicit or explicit promise to the student is that they’ll be able to earn a higher wage, get a better job, the fact that the demand side is so misaligned makes it very difficult to change the supply side.

To put it another way, we say there’s a skills gap and that we want to train a bunch of people for skills. But the first five steps of the six-step hiring process are not about skills, rather they are actually about pedigree and history. Even if you train someone to have those skills, you don’t have a time machine, so you can’t go back in time and change their history or pedigree. All you can change is their skills. Until we have a labor market where people can get hired based exclusively on their skills, abilities, readiness, independent of how they got there, then the labor market is going to continue to keep a lot of people stuck, shut a lot of people out, and ultimately a lot of people will drift off.

As a result, you get lower labor force participation, lower voluntary mobility, and less wage growth. When people are able to go find a better job (to work at something, and then to earn more as a result) that’s where half of wage growth comes from, not just sticking in your role and getting an occasional cost-of-living increase.

HB: So there are two things that I want to hit on specifically. First, I just want you to connect the dots for me about what you said—how employers look for resumes, which is about what workers have done, and not competencies, which is what workers can do. I believe that’s exactly what you were just speaking to, so I just want to make sure I’m getting the lingo and how you’re thinking about it correct.

But second, one thing that I think is very interesting is how this looks different up and down the skills ladder. You talked about how there are fewer openings for entry-level positions and that there’s less training at the bottom and still more training at the top. Could you say more about how the demand side is driving that across the ladder? Is it that employers don’t think that folks at the bottom are trainable? Or is it that they don’t feel that those jobs need much training? Could some of this be that jobs are shifting so much that the ones at the bottom are being so deskilled that that’s a shift employers are making? Or is it tied up with other kinds of demand-side issues? 

So a two-part question. Take them in whichever order you would like.

BA: I’ll take the first question first—this observation that employers look for resumes instead of competencies.

Any competent employer will tell you, “No, we’re looking for competencies. We want people who can really do the job.” But if you break down their hiring process, you’ll find that competencies and sort of demonstrating what you can do often make up the last step or perhaps the last two steps in the hiring process.

The smart businesses will look for competencies. But again, they’ll do that with a handful of people that are finalists for the position, right? That might have started with several hundred or several thousand people sending in their resumes for that position and others coming through references and the like.

Companies need a way to screen, in the sense that it would not be cost effective for them to evaluate the competencies of 3,000 different people, on their own, through their existing processes. They narrow it down by keyword algorithms on resumes, so most of those resumes are never seen or evaluated by a human being.

They’re screened on job-applicant tracking software that’s looking for certain keywords associated with that job. And they are screened based on educational qualifications. Jobs get defined as, “this job requires a four-year degree,” or “this job requires specific years of work experience in specific roles,” and the like.

Unfortunately, this process often leaves out somebody who has not walked this sort of straight path where they had a good high school education, then went to college, graduated from college, or perhaps from a community college in a very in-demand, well-structured program with good employer ties.

There are a few ways to getting a job that work, but the ways that work more straightforwardly represent about half of our labor market, give or take. And for the other half, they’re going a more circuitous route.

There are 35-40 million Americans who went to college but never graduated. They don’t have that degree. On average, they make a little bit more than high school graduates, but their earnings are much closer to high school graduates than to bachelor’s degree graduates.

Then there are workers who have developed skills on the job but don’t have any credentials associated with it. They managed to stay at their company and their company is doing well. The people around them know that they can do that job. But if they ever want to apply for even the same job at another company, they’re very likely to be screened out by the educational requirements, which is another reason you see people not being able to move jobs and this huge decline in job mobility that’s been largely unexplained. If we start looking at some of those institutional factors and demand-side behaviors, we’re going to get a lot more of an explanation for why that is happening.

So consider the alternative. What if an employer, defined it in terms of “This is what we need you to be able to do to meet this standard in this context, and here’s how you can demonstrate it” instead of making a job description and the associated processes of hiring based on someone’s history and pedigree?

And what if there are a variety of ways you can demonstrate that you can do this now. In other words, if you can do the job, you can get the job. What if that were the norm and we built systems around that?

I’ve been working with this organization Opportunity@Work on the information technology occupations and trying to apply it there. Take coding or computer programming, for example. Today, if you want to know whether someone can code, you can look at their resume or you can look at their code. And there are standard repositories like GitHub that you can use.

So instead of using a software algorithm on someone’s resume, why not use a software algorithm to look at the quality of someone’s code?   That changes the nature of the demand signal.

And this is a very important point, because there are two big implications of changing that structure of the demand side of employment. The first is that there are millions of people today who can do more than they are allowed to do. In other words, you might be a bus driver and you’re running your church website, but you can’t get a job running a website for a company because you’re a bus driver. You might get a good reference from someone, but you wouldn’t get through the typical hiring process. And there are millions of people who could do more, earn more. They could fill those jobs already for which employers say they have trouble hiring.

So that’s one phenomenon. But that’s not enough. There are not enough of those people [who can do the job] to fill all the jobs that employers would characterize as a skills gap. But if you change that demand signal to be truly based on competency and ability and skill, then you change the business model for training which benefits those who don’t yet have the skills, but are capable of learning. Because today, if you train someone for a job and that person lacks the pedigree for the job, lacks the past history, the professional history, the educational history, that person is unlikely to get the job, even if you trained them.

Even if they have the ability, the underlying potential, and you train them well, they probably still can’t get the job. And as a result, it doesn’t make sense to train them. It’ll be a failed government program if the government pays for that training. It’ll be an unsustainable nonprofit if a nonprofit does that training. And it’ll be a failed business if a business does that training. And the individual will have wasted their time because they won’t actually get the job under today’s standard hiring heuristic.

But if, instead, a business had a robust hiring channel where you could get the job if you acquired the skills, then to train someone with the aptitude and the motivation for that job would be an excellent business investment, an excellent public investment, and an excellent investment of that person’s time.

So if you create that, then, that’s the second-order effect and it’s much larger, because there are many more people with the underlying potential to learn and to master a set of skills than there are people who already have those skills and can’t get the job.

That’s the second big wave. But then the third thing is, if that’s true, then everyone from entrepreneurs to social entrepreneurs to a creative kind of government can enable entirely new sorts of business models or policy approaches, but underpin the scaling of human capital acquisition, which I think is sort of the breakthrough.

But again, once you start understanding that this is a market, you understand that you actually have to change that initial demand signal first. For example, until there’s a sufficiently large market for a certain manufactured product, there’s no demand for enough factories to build it. And if there’s not enough demand for factories, then there’s not enough demand for machine tools for those factories. You see, it sort of goes back in the chain.

The labor market is an $8.5 trillion market in the United States and essentially the market in which investments in human capital realize their return, then you see that it flows back to all of our human capital kind of systems, which is a large part of our economy.

HB: So you say that the first step is to figure out the policy solutions. What do you think the first key policy steps are on the demand side to make that happen? What would you say the most urgent ones are—or are you guys there yet at Opportunity@Work?

BA: I think it’s a matter of both policy and practices, in the sense that not all of this can be solved by public policy. It has to be solved by employer practices, which public policy can enable, can incentivize, but can’t mandate at the level of specificity that would be necessary to still keep up with changes in the labor market.

The approach we’ve taken at Opportunity@Work is to really think about where the capabilities and mandates of government, business, the nonprofit sector, and these sort of technology platforms can be rewired, combined in different ways.

If you think about the problem we’re trying to solve, it is a market-based collective action problem. Hiring people, it’s not consumption for a company. It is an input to a complex and rapidly changing set of production processes meant to try to target a moving market, or set of moving markets. So it moves very quickly and government really can’t do market-based activities at that level.

On the other hand, the phenomenon we’re talking about on the demand side is really a collective action problem, because companies transactionally, individually, have a very strong incentive to poach an already experienced and trained worker instead of hiring a promising worker that they would have to train and give experience. But if they’re all poaching out the front door, then everybody’s being poached out the backdoor, and they’re not creating a new supply of people.

HB: Did you just make an argument for why the non-compete clauses that many workers are being forced to sign might actually be a good thing?

BA: No, I don’t believe these non-competes are a good thing. I don’t believe excessive requirements for licensure and so forth are a good thing. I think they’re all bad things.

I think they’re all part and parcel of a reality that much of our public policy—a lot of it at the state and local level—and many of our business practices really make it more difficult for people to find their path to the work that would give them the most satisfaction, that would produce the most value, and in which they could be most highly compensated in whatever mix of passion, freedom, and joy that reflects what they want.

So, no, I think they’re pretty much all bad, because there’s been a reduction in voluntary job mobility as a result of a lot of these things, including the licensure, the non-competes, and the like.

HB: But if we have a labor market where people are changing jobs a lot, isn’t there an upside to policies that might make it harder for people to switch, because it would create more incentives for businesses to invest in the talent that they have?

BA: It’s a logical argument on the face of it, but when you look at the data, you see it’s a myth that there’s some Millennial wanderlust and people just want to switch jobs more. They’re job-hopping more.

The reality is that businesses are treating workers more as a kind of sort of contingent workforce, whereas before, a much larger portion of businesses had a model where they thought of their employee base a little bit more like a long-term asset.

It’s not that people wouldn’t change jobs, but on average, businesses were investing as if they were going to keep people for a long time, to the point of accepting significantly lower profits during recessions so that they could hold on to two-thirds of the people they would otherwise have to lay off.

It’s businesses that stop doing that, right? Employers stop doing that.  The volatility in the labor market is driven much more by employers hiring up when demand goes up and then firing and laying off people quickly when demand drops.

That’s where the volatility is coming from, much more from the employer side than on the employee side. On the employee side, actually, the voluntary quits are lower at any given point in the business cycle than it used to be. And geographic mobility is much less; it’s half of what it was 30 years ago.

So in theory, what you’re asking is plausible. But when you look at the data, that’s not what’s going on. The volatility in people’s working lives is being driven much more by changes in employer behavior than by changes in individual worker preferences. And that has a lot of implications.

HB: Well, I think that’s all the time we have, but this has been very insightful and enormously helpful. Thank you so much, Byron.

BA: Thank you. I enjoyed it. Take care.

Equitable Growth in Conversation: An interview with Lawrence H. Summers

Posted on by Nick Bunker

Today, Equitable Growth kicks off “Equitable Growth in Conversation”—a recurring series where we’ll talk with economists and other social scientists to help us better understand whether and how economic inequality affects economic growth and stability in particular ways.

In this first installment, Heather Boushey, Executive Director and Chief Economist here at Equitable Growth, interviews renowned economist and former U.S. Treasury Secretary Lawrence H. Summers. The two dig into secular stagnation—what it is, what problems it creates, and the issues for policymaking—as well as how inequality plays a role in the phenomenon.

Read their conversation below.

Heather Boushey: You’ve been talking a lot about secular stagnation. That’s what we want to dig into, and in particular we want to talk about what it is, what problems it creates, and what the issues are for policymaking. But then we want to talk about how you see inequality playing a role in secular stagnation. I know in a couple of pieces, you’ve referenced inequality playing a role, so that’s what we want to take a close look at today.

To open up this interview, can you briefly sketch out what secular stagnation is?

Larry Summers: Secular stagnation, as I use the term, refers—and I think this was the essence of Alvin Hansen’s argument in the 1930s—to a situation in which there’s a chronic excess of savings, desired savings, relative to investment in an economy—in an individual economy or in the global economy.

The consequence is downwards pressure on real interest rates, a weakness in demand leading to slow growth, and leading to sub-target inflation. In a situation of secular stagnation, there will be normal fluctuations, centered around a relatively low level of performance. And there will be a tendency for those moments of rapid growth to be financially unsustainable because they’re based on unsustainable levels of borrowing and, perhaps, of asset prices.

HB: So what do you think are the key problems that this creates for policymakers?

LS: Look at the global economy. Look at the industrialized world today. If you look across the United States, Europe, and Japan, inflation is expected to be less than 1 percent over the next 10 years, and real interest rates are expected to be below zero. And that’s over a 10-year period.

That’s a market judgment—and it’s a judgment that markets have had for quite some time now—that economic performance is going to disappoint substantially in the industrial world. And the key to it is that there’s a lack of demand. That leads ultimately to reduction in supply potential, as lack of demand inhibits investments and leads to more unemployment and labor force withdrawal through hysteresis effects.

But if you see a tendency toward “low-flation” and deflation, and you see sluggish economic growth, and you see that in progress for a long period of time, you have to think that something’s going wrong on the demand side of the economy.

HB: So let’s set aside the politics if we can, which I know is not a rational thing to do. But let’s start with what you think we need to be thinking about. For policymakers—both on the fiscal and monetary side, but let’s start on the fiscal—what do you think needs to get done that would address these kinds of issues? Is it all demand management?

LS: The least rational political cliche in economics is the idea that, because in downturns people and businesses are tightening their belts, government should as well.

HB: I believe President Obama said that when you were working for him.

LS: I think it was after I was working for him, but he did say it. He did say it and I regretted it when he said it. Virtually every American president has said some version of that at some time or another. The reality is that it’s government’s responsibility to be countercyclical—that when private saving is substantially exceeding private investment, that is precisely when government should be borrowing and investing.

This is a moment when the United States can borrow money at less than 3 percent for 30 years, in a currency we print ourselves. It is a moment when materials costs are extraordinarily low. It is a moment when construction unemployment rates remain high.

Has there ever been a better moment to fix LaGuardia or Kennedy Airport? It is crazy that at a moment like this, the United States has the lowest rate of federal infrastructure investment, relative to the economy, than we’ve had since 1947. And on a net basis—that is, taking into account depreciation—we’re essentially not investing at all.

So there is a compelling case, in my view, for expanded public investment. Even the International Monetary Fund, hardly a group of radical socialists, has recognized that in situations like the present one, where the economy is close to being in a liquidity trap, the likelihood is that increased public investments will, over time, reduce rather than increase debt-to-GDP ratios, as they call forth increased economic growth.

I yield to no one, not Pete Peterson, not the Concord Coalition, in my concern for the well-being of my children’s generation and future generations. It’s just that I think a deferred maintenance liability of trillions of dollars compounds at a far higher rate than the interest rate at which the United States is now able to borrow. So addressing that deferred maintenance liability is actually reducing the financial burden that we will place on future generations.

HB: So for the deficit hawk that’s in Congress, what do you think is the best illustration of the effectiveness of the policy agenda that you just outlined? If you were to show one chart, one figure, one country example, what would you point to that you think really hammers that home for the non-economist—somebody who’s a politician?

LS: You know, I’m not sure. Judging by the decisions Congress has made on infrastructure, I’m not sure those of us on this side of the argument have been successful. I suppose I would show what’s happened, show the growing deferred maintenance burden that we are incurring as a country, and I would show the available evidence, which suggests that when you defer maintenance, you can raise its total costs by a factor of two or more.

I do think that some part of the skepticism about public investment comes from a sense that the government doesn’t always do it as well as it could. There’s a bridge across the Charles River right near Harvard Square, right near my office. The bridge was constructed around 1915, in 10 months. It’s now in its 50th month of being repaired.

So I think there are legitimate concerns about how public investment projects are executed. And I think there is a tendency for some macroeconomists and some progressives, in their enthusiasm for public investment, to lose sight of valid concerns about the competence and efficiency with which public investment projects are executed.

HB: Yes, which poses a lot of political problems.

LS: Yes.

HB: That might be an interesting segue into the next set of questions. I want to come back to monetary policy, but I want to move now to thinking about the role of inequality.

What role do you think inequality plays in the problem of secular stagnation? And my follow-up question to that: There are a variety of dimensions in inequality that we could think about. I don’t want to limit you to a particular dimension, but I am going to ask you if you think there are other dimensions than whatever you mentioned in the first part of the answer.

LS: You know, I think there’s a broad issue. When I went to graduate school in the 1970s, the prevailing view among economists, captured by Art Okun’s book “Equality Versus Efficiency: The Big Tradeoff,” was that equality and efficiency were both desirable, but they were likely to trade off—that more progressive taxation would achieve more equality but would inevitably in some way distort economic choices and, so, reduce efficiency, for example.

I believe there are still many areas in which one does have to trade off equality versus efficiency. But I also believe there are many areas in which it’s possible to reform policy to promote both economic efficiency and equality. One such area is policy to mitigate secular stagnation by promoting demand at times when there is slack in the use of resources.

Recall that I defined secular stagnation as having at its essence an excess of savings over investment, desired saving over desired investment. There are many reasons for that. Some of them have to do, for example, with reduced investment demand because so much more capital can be purchased with fewer dollars. I think of the fact that my iPad has more computing power than a Cray supercomputer did when Bill Clinton came into office in 1993.

One aspect of that excess in saving over investments is that rising inequality has operated to reduce spending. We are fairly confident that what economists call the “marginal propensity to consume” of those with high incomes is less than the marginal propensity to consume of those with middle incomes.

And so the combination of rising inequality in the distribution of income across income levels and a shift in inequality toward the higher profit share slows economic growth. In normal times, such a change might be offset by easier monetary policy. But in the current environment, where interest rates are very close to the zero lower bound, the capacity for that kind of offset is greatly attenuated.

There’s another aspect of the connection between secular stagnation and inequality that bears emphasis. Experience suggests that in an economy where there are more workers seeking jobs than there are jobs seeking workers, the power is on the employer side, and workers do much less well. A tight economy, where employers are seeking workers, shifts the balance of power toward workers and leads to higher pay and better benefits. That, in turn, leads to more spending being injected into the economy, which supports further economic growth.

And so, as Keynes recognized when he wrote to FDR in the late 1930s urging the importance of wage increases, measures that strengthen workers’ capacity to earn income by increasing spending power can promote both equality and strengthen the economic performance of the country.

HB: A number of economists are now talking about the rise of inter-firm inequality—that it’s not necessarily just a gap between the typical worker and all bosses, but that some firms are pulling further and further away. Do you have any sense that that might be playing any role in the dynamics that you just mentioned?

LS: I’m familiar with that argument, but I don’t yet have a view. I have a concern that we may be seeing some increases in monopoly power. That, because of overly rigorous protection of intellectual property, for example, because of the rise of industries where there are very important network or first mover advantages, we may be seeing more monopoly power. And monopoly power exacerbates secular stagnation in two respects.

On the one hand, it means more income going to groups that are likely to have a high marginal propensity to save. On the other hand, it means less investment demand because monopolists have a desire to constrict supply.

HB: So I just have two questions left. We talked a lot about problems. We talked a lot about the role of inequality. We talked about secular stagnation. Just to remind us all of what we covered.

The big questions that I have are: What solutions should policymakers pursue, above and beyond the things you already mentioned, around infrastructure investment? And what, importantly, do they need to know to help them make those decisions? What I’m looking for is what solutions we should pursue, and what questions we, as an organization, should be encouraging researchers to ask in order to help inform those decisions.

LS: Let me answer them in the opposite order.

HB: OK.

LS: I think we need more research on the links between inequality and spending. It’s an area where there’s a lot of talk and relatively little hard data. In particular, there was a previous generation of research on the impact of a profit share of corporate-retained earnings on aggregate levels of savings. But that work has not been extended in recent years.

There’s a great concern on the part of progressives about mechanisms through which corporations distribute cash, like excessive stock buybacks and dividends. If the alternative is investment, that concern is very understandable. If the concern is cash that is held on corporate balance sheets, then reducing payouts may have the effect of reducing spending and hurting the economy. And I don’t think we understand those aspects of corporate behavior as well as we might think.

In the wake of the financial crisis and the Great Recession, there’s been an entirely appropriate concern with curbing excessive lending and with maintaining prudential standards. But, of course, an inadequate capacity to support lending operates to discourage investments and in turn to exacerbate secular stagnation.

I don’t think we know as much as we should about the determinants of a flow of credit to small business. And I have a particular concern that if we had an excessive flow of credit to housing for many years, we may have an insufficient flow of credit to some who want to buy homes at the present time. And this seems to me to be a valuable area for future inquiry.

An additional area that I have tried to do some work in recently, with Gauti Eggertsson, but where much more needs to be done is the open economy aspect of considering secular stagnation.

Increasingly, the United States is the single engine that is driving large parts of the world economy, and policy measures that lead to a much stronger dollar may have the effect of shifting demand from the United States to the rest of the world in ways that are not fully in our interest. And so, what the appropriate attitude is, for example, toward capital outflows from China, is an issue that I think deserves careful consideration and research.

At the broadest level, the concern with excessively low interest rates in the United States—and the danger that the United States will hit the zero lower bound on interest rates repeatedly in the years ahead—raises the question of what the appropriate public policy posture is toward promoting savings versus promoting investments. For many years, we have seen the promotion of savings as a central objective. Perhaps in an environment of such low returns to savings, and an environment with the shortage of demand, we should be more concerned with promoting demand.

It’s ironic to remember that when Keynes visited the United States during the Second World War, he saw one important virtue of the Social Security system as being that, by making retirement secure, it would support spending—spending that would help to drive the economy forward and avert what might otherwise be a stagnant outcome.

For a whole variety of reasons, those arguments haven’t looked very relevant for most of the last 60 years, but we may be coming into an era when they are increasingly relevant. And so, the question of the right attitude toward savings is one on which I think there is valuable future work to be done.

One critical area is with respect to the relationship between macroeconomic policies and financial stability. The secular stagnation hypothesis raises a possibility that I think needs to be considered much more thoroughly in future research. That possibility is that financial instability is obviously in part a reflection of inadequate regulation. But in a deeper sense, it may be that the structure of the economy has become such that the kinds of flows of credit that are necessary to maintain full employment are inconsistent with financial sustainability.

From that point of view, efforts to contain dangerous credit flows or avoid monetary policies that risk bubbles and asset price inflation may have the very adverse side effect of holding down demand and thereby inhibiting economic growth. If so, there needs to be much more emphasis on structural measures and fiscal measures as tools for maintaining consistently adequate levels of aggregate demand.

There may also be a scope for further research on unconventional aspects of monetary policy. A central concern coming out of the secular stagnation thesis is this: If you look at the experience of economies that are in the mature stage of recovery, and where the unemployment rate has fallen to reasonably low levels, historical experience suggests that the odds of a recession within three years are very high, and the odds of a recession within the next year are certainly not small. Traditionally, the Federal Reserve has lowered interest rates by between 300 and 500 basis points to combat a recession. We are unlikely to have that much room when the next recession comes.

What are the alternative tools? Part of the answer lies in choosing fiscal policy, and I think we need to do more than we normally do to have contingency plans for the use of fiscal policy. But an additional part of the answer, I would submit, will lie in creativity with respect to possible unconventional monetary policy. How much easing can be achieved in a world where quantitative easing has already brought loan rates down to very low levels? What is the full extent to which negative interest rates are or are not a viable economic possibility? What are the toxic side effects in terms of financial stability of easy monetary policies? These are all crucial questions raised by secular stagnation.

HB: Thank you. Those are all great. My last question is, on this policy question around inequality, are there things that policymakers should be thinking about—specifically in the area of non-macro policy—about addressing inequalities that would ultimately be important for macroeconomic stability in ways that perhaps policymakers aren’t thinking about now?

And then, if inequality plays any role in this instability, should we be thinking more about addressing inequality at the top or the bottom and putting it into that larger economic framework for people?

LS: No, as Keynes recognized in the late 1930s, traditional economics of measures to support wages—like stronger collective bargaining or increases in the minimum wage—are quite different in the context of an economy that is demand-constrained compared to one that is not demand-constrained.

And so I think it is an appropriate moment for more active consideration of structural measures that influence inequality. The minimum wage is one such measure. Collective bargaining is another. The appropriate application of regulatory and antitrust policy is yet another that deserves consideration.

I think the agenda of seeking to identify areas within the economy where large rents are being earned and to contain those rents is very worthy of consideration. One needs to also be mindful that one person’s rent can be another person’s incentive. And so I think one needs to consider policy quite carefully in these areas, but I don’t think that issues surrounding rents have received the appropriate amount of attention in recent years.

HB: Well, that’s a great place to end it. This has been wonderful, and I really appreciate your time. Thank you.

LS: Thank you.

This interview has been edited for length and clarity.