Category: Economic Stability

How the student debt crisis affects African Americans and Latinos

Posted on by David Hudson
A student hugs family during the procession at commencement ceremonies at Hampton University in Hampton, Virginia. (AP Photo/Steve Helber)

Our first Mapping Student Debt interactive released this past December revealed a striking negative relationship between income and delinquency across zip codes. Not surprisingly, we found that higher levels of income are associated with fewer problems with student loan delinquency. In this second installment of the Mapping Student Debt project, we document that the geography of delinquency is highly racialized.

Zip codes with higher shares of African Americans or Latinos show much higher delinquency. What’s more, our analysis finds that among minority student borrowers, those most adversely affected are the middle class—those who have taken out debt to go to college but who haven’t been able to find jobs or don’t have sufficient family wealth to pay it back.

Delinquency disproportionately affects minority communities

Our findings are stark. They show the strong relationship between a zip code’s minority population and its delinquency rate at both the city and national levels. In the Washington, D.C. metro region, for example, zip codes in the northeastern part of the District of Columbia and east of the Anacostia River and adjacent suburbs—all of which have the largest shares of African Americans and Latinos—also have delinquency rates that range from somewhat high to extremely high. The same pattern holds in Los Angeles, where areas with large African American or Latino populations, such as Compton, Linwood, and Huntington Park, are also where delinquency is highest. (See Figure 1.)

Figure 1

At the national level, too, we find that zip codes with higher shares of African Americans or Latinos have much higher delinquency rates. This relationship suggests that minority communities disproportionately suffer from student loan delinquency. (See Figures 2 and 3.)

Figure 2

Figure 3

Controlling for income

The geography of race and of income are similar, so a natural question that arises is whether race has an independent effect on delinquency, and, if so, what is it? The answer turns out to depend on income, but not in an obvious way.

In order to investigate the effect of race independent of income, we first ranked zip codes by median income and divided them into 100 groups of equal size. Within each of these income groups, median income levels are nearly identical, which means we can look at how delinquency varies across zip codes with different shares of African Americans or Latinos but otherwise very similar income levels. In Figures 4 and 5, we plot how an increase in the minority share of the zip code population changes the rate of delinquency. Points above zero mean that as a zip code’s minority population increases (relative to zip codes with a similar income), so does the share of delinquent loans in that zip code. Conversely, a negative number implies that zip codes with larger minority populations have lower loan delinquency rates.

Figure 4

Figure 5

In both Figures 4 and 5, the positive correlation between the share of minorities in a zip code and loan delinquency rates is highest for the middle of the income distribution. Among zip codes with a median income of about $20,000, for example, zip codes with a large share of Latinos and those without have approximately the same rates of delinquency. But among zip codes with a median income of around $60,000, those with large Latino share have much higher rates of loan delinquency than those without.

We see a similar pattern for the share of African American in zip codes, and there the effect is even more pronounced. For zip codes with median incomes above $60,000, the effect of race on delinquency either stays roughly constant or declines slightly.

Another interesting feature of the data is that among the zip codes with the poorest populations, an increase in the share of African Americans is associated with a decline in delinquency rate, whereas the share of the Latino population has no impact on delinquency. We do not think our data are rich enough to meaningfully address this particular fact, which merits further research.

The role of race in student loan delinquency

Minority populations disproportionately suffer from high delinquency, and, within minority populations, the middle class seems most adversely affected. What can we make of these findings? We believe that these two facts reflect the impact of structural racism in the U.S. higher education system, credit and labor markets, and distribution of wealth.

African Americans and Latinos are, on average, less likely than white students to complete college once they start. According to the National Center for Education Statistics, in 2013 roughly 57 percent of recent African American high school graduates and 60 percent of recent Latino high school graduates were enrolled in college compared to 69 percent of white students. Yet the National Center for Education Statistics reports that for the 2005 starting cohort of college students, about 21 percent of African Americans and 29 percent of Hispanics complete a four-year institution within four years compared to a four-year completion rate of 42 percent for white students.

The college enrollment gap between whites and minorities is narrowing, but the college completion gap is not. One likely explanation for higher student loan delinquency among African Americans and Latinos is that the borrowing is concentrated among those who either attended for-profit or other non-traditional institutions or who dropped out—exactly the population at the margin of attending college in the first place. Furthermore, we know that higher education is racially segregated, with minorities less likely to attend—or even consider applying to—selective institutions.

Even after controlling for key risk factors, African Americans and Latinos are disproportionately served by high-cost credit providers who provide less generous terms and more onerous repayment requirements, implying that discrimination occurs through market segmentation and sorting.

Another explanation for high delinquency rates among minorities is that after college, graduates still confront significant discrimination in labor markets, with minority applicants less likely to get job offers, even after factors such as education are taken into account. Even minority students who successfully complete college suffer from higher unemployment rates and lower earnings than their white counterparts. These disadvantages extend across college majors, occupations, and the type of higher education institution that these recent graduates attended. In combination, these factors leave minority students and their families substantially more vulnerable to delinquency than comparably situated white students and their families.

A closely related issue is that, holding income constant, African American and Latino households have substantially lower levels of wealth than do white households, including financial assets that can act as a buffer against student loan delinquency in the event of job loss or some other misfortune.

Middle-class minorities are hurt the most by student loan delinquency

Why are middle-class African American and Latino students and their families the most adversely affected by student debt delinquency? The poorest minority populations generally lack access to any kind of formal credit, instead relying on payday lending and other types of informal credit access. This means that they cannot be delinquent by our measure that is based on credit reports. What’s more, they rarely go to college, so in many cases, they do not acquire student debt.

The housing crisis revealed a similar dynamic in the late 2000s. The poorest minority households lost relatively little wealth because they didn’t have any to begin with, whereas somewhat richer minority households were among the biggest losers from the Great Recession. That was because they earned enough to have bought a house under the relatively generous terms available before the housing market crash, but then they were more likely to lose their jobs and less likely to have any cushion of family wealth. It is out of these very dynamics that persistent, multi-generational racial wealth gaps are born. And it seems likely that student debt is on the same path now—a signpost of relative economic success among minorities, but also a threat. Many young people of color have gone into debt to ascend to the middle class, and been supported by their families to do so, yet it’s not having the intended effect.

These data tell us that at least with respect to longstanding group and individual income and wealth gaps between minorities and the overall population, debt-financed higher education is not the solution, and may even be contributing to the problem. The fact that, among minorities, the middle class is most strongly affected implies the problem is structural racism, not poverty. Any solution to the student debt crisis has to recognize that.

Methodology

This geographic analysis uses two primary datasets: credit reporting data on student debt from Experian and income data from the American Community Survey.

The Experian data includes eight key student debt variables (see Figure 6) aggregated from household-level microdata to the zip code level. The underlying household data are a snapshot of the entire U.S. population at a single point in time—in this case, the autumn of 2015.

Figure 6

There are a number of caveats regarding the Experian data file that have guided our methodology for constructing variables and analyzing results:

  • The universe of households contains only those with “any type of credit” and which, therefore, have a credit report. Relative to the population as a whole, this likely excludes the poorest households without any official credit access whatsoever.
  • It is unclear how Experian constructs “households” since credit reports pertain to an individual’s credit history.
  • If the same student loan has more than one signatory, then the loan may be assigned to multiple households and hence to multiple zip codes or even counted more than once within the same household.
  • Experian claims that the universe of their geographically-aggregated data is all households with credit, but the levels of the data on loan balance and delinquency are more consistent with the idea that the universe is only households that have student loans. In other words, Experian claims their data include households that have credit but no outstanding student loans, but if that is the case the reported levels for average delinquency are much higher than other sources would suggest. Average delinquency rates, however, are comparable to reliable outside estimates if interpreted as delinquency among only those households with student debt.

For these reasons, we do not report any student loan data in rate amounts. Instead, we have used the Experian variable to construct an analog to relative delinquency.

To create the delinquency variable, we calculate a “delinquency rate” for each zip code by dividing the average number of student loans that are delinquent by 90 or more days per household by the average number of outstanding loans per household. Then, after winsorizing the top 1 percent of observations to the 99th percentile value, we project the “delinquency rate” onto a scale that ranges from 0 to 10.

For user-friendliness, we assign the student debt scale variable a qualitative category. If the delinquency reads “very low,” for example, it corresponds to a scale level between 0.067 and 0.091. Figure 7 summarizes the relationship between the delinquency scale variable’s levels and its qualitative descriptions.

Figure 7

Next, we merge zip code-level household median income with data from the 2013 American Community Survey on the share of African Americans and Latinos in those zip codes along with our imputed scaled delinquency variable in order to construct choropleth maps.

The actual map uses two different techniques to display the variables on a choropleth scale. For delinquency, we created 10 quantiles (or equal counts) to account for the right-skewed data. And for the two minority share variables, we used 10 jenks (or natural breaks in the data) to assign the color scale. Higher numbers and darker shading correspond to higher shares of outstanding loans that are delinquent by 90 or more days in the previous 24 months and higher shares of African Americans and Latinos in a zip code.

Additional reading

Adam Looney and Constantine Yannelis, “A crisis in student loans? How changes in the characteristics of borrowers and in the institutions they attended contributed to rising loan defaults.”

Benjamin Backes, Harry J. Holzer, and Erin Dunlop Velez, “Is It Worth It? Postsecondary Education and Labor Market Outcomes for the Disadvantaged.”

Caroline M. Hoxby and Sarah Turner, “What High-Achieving Low-Income Students Know about College,” American Economic Review.

Devah Pager, Bruce Western, and Bart Bonikowski, “Discrimination in a Low-Wage Labor Market: A Field Experiment.”

Fenaba R. Addo, Jason N. Houle, and Daniel Simon, “Young, Black, and (Still) in the Red: Parental Wealth, Race, and Student Loan Debt,” Race and Social Problems.

Janelle Jones and John Schmitt, “A College Degree is No Guarantee.”

Jeffrey P. Thompson and Gustavo A. Suarez, “Exploring the Racial Wealth Gap Using the Survey of Consumer Finances.”

Jess Bricker and others, “Changes in U.S. Family Finances from 2010 to 2013: Evidence from the Survey of Consumer Finances.”

John Schmitt and Heather Boushey, “The College Conundrum: Why the Benefits of a College Education May Not Be So Clear, Especially to Men.”

Joshua Angrist, David Autor, Sally Hudson, and Amanda Pallais, “Leveling Up: Early Results from a Randomized Evaluation of Post-Secondary Aid.”

Martha J. Bailey and Susan M. Dynarski, “Gains and Gaps: Changing Inequality in U.S. College Entry and Completion.”

Marianne Bertrand and Sendhil Mullainathan, “Are Emily and Greg More Employable Than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination.”

Neil Bhutta, Paige Marta Skiba, and Jeremy Tobacman, “Payday Loan Choices and Consequences.”

Patrick Bayer, Fernando Ferreira, and Stephen L. Ross, “Race, Ethnicity and High-Cost Mortgage Lending.”

Rakesh Kochhar and Richard Fry, “Wealth inequality has widened along racial, ethnic lines since end of Great Recession.”

Stephanie Chapman, “Student Loans and the Labor Market: Evidence from Merit Aid Programs.”

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.

Paid leave is good for our families and our economy

Posted on by David Hudson

Heather Boushey, Executive Director and Chief Economist at the Washington Center for Equitable Growth, testifies before the Committee of the Whole, Council of the District of Columbia on the Universal Paid Leave Act of 2015 (Bill 21-415).

Thank you, Chairman Mendelson, for calling this hearing. And thank you to the D.C. Council for extending an invitation to speak to you today. I am honored to be here.

My name is Heather Boushey and I am Executive Director and Chief Economist at the Washington Center for Equitable Growth. We seek to accelerate cutting-edge analysis into whether and how structural changes in the U.S. economy, particularly related to economic inequality, affect economic growth.

I am also the author of a forthcoming book from Harvard University Press, Finding Time: The Economics of Work-Life Conflict, where I go into great detail on the need for policies such as the Universal Paid Leave Act of 2015. What I’ve learned through my research is that the economic evidence points in one direction: Smoothing and securing people’s participation in the economy is good for families, good for firms, and good for the economy. Family and medical leave insurance would help all D.C. workers be less economically vulnerable when balancing work, illness, and family care.

I recognize that there are some added costs for businesses when implementing paid family leave—most importantly, the expenses incurred when coping with an employee’s absence. However, the cost of coping with an employee’s absence is not new to businesses in the District of Columbia since the District of Columbia Family and Medical Leave Act of 1990 already grants employees 16 weeks of family leave and 16 weeks of medical leave within any 24-month period. The additional step of universal paid leave will enable workers to meet the needs of their families and of the firms they work for in better and more productive ways. This will help make the District of Columbia more—not less—economically competitive and broadly benefit families.

I will make four points in my testimony today:

  1. Paid family leave is a necessary policy for modern families.
  2. Family economic security is important for our overall economic strength and stability.
  3. Localities—like the District of Columbia—should consider action because neither private employers nor federal policymakers have thus far addressed this urgent economic issue.
  4. There are models from three states that have led the way that show paid family leave is good for the economy.

Download the full pdf for a complete list of sources

Paid family leave is a necessary policy for modern families

The majority of families do not have a stay-at-home parent to provide care for children or for ailing family members. At the top of the income ladder, families are more often comprised of two earners, while at the bottom, they typically have one earner, often someone playing the dual role of sole earner and sole caretaker/parent. Among children, 71 percent live in a family with either two working parents or a single working parent, and the percentage of adult children providing care for a parent has tripled over the past 15 years. Among workers who were employed at some time while caregiving, one in five reported that they took a leave of absence from work in order to address caregiving responsibilities.

Because of the changes in how families interact with the economy, when a new child comes into the family, when a family member is seriously ill, or when a worker himself is ill, an employee needs a few weeks or more to be at home. Most families no longer can rely on a stay-at-home caregiver to provide this care, and firms cannot assume that families have someone at home. Instead, employees must negotiate time off with their employer. The District of Columbia was at the forefront of addressing the need to better balance family care and work responsibilities when it established the right to 16 weeks of unpaid leave in 1990.

However, for many low-, moderate-, and even high-income families, unpaid leave is nice, but unaffordable. The loss of income—even for just a few months—can cause a serious economic pinch for most families. Most families’ savings will cover barely a few months’ expenses.  Families must have the money to pay the rent or mortgage and put food on the table (and pay the utility bill, the health insurance copayments, and everything else), which is possible only with a regular paycheck, or at least a portion of it. This leads many to refuse unpaid leave, even when it would help them and their families address their care needs. According to a recent survey by the U.S. Department of Labor and Abt Associates, 46 percent of those who need leave but don’t take it cited an inability to afford the time off.

Paid family leave addresses a key conflict caused by the lack of a full-time, stay-at-home caregiver and keeps caregivers in the workforce. Over the past 40 years, this added employment of women has been responsible for much of the gains in family income across the income distribution. From 1979 to 2007, low-income women were responsible for all of the growth in their family income. Their earnings as a source of total family income increased by 156 percent, which more than made up for the 33 percent decrease in men’s contribution during the time. Families cannot afford to go back to having a stay-at-home caregiver.

Family economic security is important for our overall economic strength and stability

The economy is a system in which both firms and families matter. Each is a key player in our economy. Families buy goods and services from firms and, in turn, supply firms with workers by selling time. Firms buy people’s labor, or time, to produce goods and services, which they then sell to families, completing the cycle.

However, where the very purpose of a firm is to engage in the economy, the purpose of families is both economic and non-economic. Families are where we raise children and care for one another. These roles may be subjectively more important to family members than their role in the economy, which raises the importance policies such as paid family leave play in our economy.

In order to see how paid family leave will affect the D.C. economy, we need to look at all kinds of costs and benefits. Costs include all the hidden costs that may be hard to see. Costs aren’t only what firms pay out of pocket, and benefits aren’t only about more money. We also need to look at the long-term effects. Upfront costs might be obvious, but benefits may take a while to show up, especially those that affect productivity.

Policies that keep good people in their jobs save firms money. Sociologist Sarah Jane Glynn and I conducted a review of the literature on the cost of job turnover and found that up and down the pay ladder, businesses spend about one-fifth of a worker’s salary to replace that worker. Among jobs that pay $30,000 or less, the typical cost of turnover was about 16 percent of the employee’s annual pay, only slightly below the 19 percent across all jobs paying less than $75,000 a year.

Paid family leave improves wages and earnings for caregivers. In my research, I found that women who had access to paid leave when they had their first child had wages years later that were 9 percent higher than similar women who had not had access to paid leave. Other researchers have found that women who had access to job-protected maternity leave were more likely to return to their original employer. This reduced the gap in pay that mothers experience relative to nonmothers. The Rutgers University Center for Women and Work found that working mothers who took paid family leave for 30 days or more for the birth of their child are 54 percent more likely to report wage increases in the year following their child’s birth, relative to mothers who did not take leave.

Economists find that the lack of paid family leave is one reason that the United States ranks 17th out of 22 OECD countries in female labor force participation. In one recent study, Cornell University economists Francine D. Blau and Lawrence M. Kahn found that the failure to keep up with other nations and adopt family-friendly policies such as parental leave is a reason for this lack of employment.

A lower employment rate for caregivers has dramatic economic consequences. In my work with Eileen Appelbaum and John Schmitt, we estimated that, between 1979 and 2012, the greater hours of work by women accounted for 11 percent of the growth in gross domestic product. In today’s dollars, had women not worked more, families would have spent at least $1.7 trillion less on goods and services—roughly equivalent to the combined U.S. spending on Social Security, Medicare, and Medicaid in 2012.

The economic effects of paid leave are also important for families caring for an elder. According to the Bureau of Labor Statistics, about one in six Americans (16 percent) cares for an elder for an average of 3.2 hours a day. Most unpaid family caregivers—63 percent—also hold down a job; most of those with a job are employed full time. The National Alliance for Caregiving’s 2015 survey found that among those caring for an aging or ailing loved one, 61 percent reported that this negatively affected their paying job, because they needed leaves of absence, had to reduce their work hours, or received performance warnings. The survey also found that 38 percent of caregivers reported feeling high stress. This means that the “family” part of family and medical leave is important for large swaths of the U.S. workforce. This is especially true since, unlike in other countries, few elders receive support from government—about 6.4 percent of seniors are in long-term care in the United States compared with 12.7 percent across other developed economies.

Because paid family leave protects families from suffering financial setbacks when working, parents are not forced to take unpaid leave or exit the labor force entirely in order to provide care for their children. This can reduce long-term costs for state and local governments. Researchers from Rutgers University’s Center for Women and Work found that paid family and medical leave reduced the number of women who relied on public assistance. In the year after they had their child, women who took paid leave were 39 percent less likely to receive public assistance, like TANF, compared with mothers who did not take leave but returned to work. They were also 40 percent less likely to receive food stamp income in the year following a child’s birth.

Paid family leave improves a family’s ability to care for the next generation. The economists Raquel Bernal and Anna Fruttero explain that paid parental leave can increase a child’s average human capital as parents use their leave to spend time with their new baby, which, as research indicates, increases a child’s future skill level. Parental leave also enhances children’s health and development and is associated with increases in the duration of breastfeeding and reductions in infant deaths and later behavioral issues. Similarly, returning to work later is associated with reductions in depressive symptoms among mothers.

Localities—like the District of Columbia—should consider action because neither private employers nor federal policymakers have thus far addressed this urgent economic issue 

Private employers do not typically provide paid family leave. A paid family leave program covers only about 13 percent of employees. There are a number of high-profile exceptions, such as Google, which now provides 18 weeks of paid maternity leave and 12 weeks of paid paternity leave for its employees, but they are rare.

When firms do provide leave, they often only give it to their higher-paid employees. Only 5 percent of workers in the bottom quarter of earners have paid family and medical leave through their employer, compared with 21 percent in the top quarter. The trends look similar across educational categories. Unlike pensions and health insurance, uniform leave policies are not mandatory. Low-income families are least likely to be able to afford paid help to care for loved ones, so this lack of leave can quickly lead to an exit from employment or a sharp reduction in family spending.

There is no federal guarantee of paid family leave. In the absence of federal action, there is an opportunity for states and localities to develop programs and policies that provide this increasingly critical piece of help to working families. The United States is the only advanced industrialized nation without a federal law providing workers access to paid maternity leave, and one of only a handful of nations that does not offer broader family and medical leave insurance. In fact, among OECD countries, mothers are, on average, entitled to 17 weeks of paid maternity leave around childbirth alone, so the D.C. proposal is modest.

Three states—California in 2002, New Jersey in 2008, and Rhode Island in 2013—provide a model for this kind of program. In these states, paid caregiver leave for new parents and workers who need to care for a seriously ill family member was an expansion to their longstanding statewide temporary disability insurance programs. Benefits are for six weeks in California and New Jersey, four weeks in Rhode Island, and typically cover about half or more of an employee’s pay, capped at around what the typical, or median, worker earns in a week. Benefits in those states are paid for through an employee payroll deduction for family leave, though the New Jersey temporary disability insurance plan, the most expensive portion of their paid leave program, is two-thirds employer funded.

In the current bill, D.C. employers pay the insurance premium for paid leave, which makes it different than in these three states. This is due to the unique nature of our city’s ability to tax. However, like in the three states, the program spreads the costs of leave through an insurance pool. While the tax is on employers, economic research tells us that they will pass on this additional cost to either consumers, through minimal price increases, or to employees through nominal salary adjustments over time.

Paid family leave is good for the economy

Research on the effects of paid leave policies finds that leave periods up to a reasonable length of time is positive for employment outcomes, and those positive employment outcomes are consequently beneficial to the entire economy. In an extensive survey of employers and employees, the sociologist Ruth Milkman and the economist Eileen Appelbaum found that in California, the overwhelming majority of employers—9 out of 10—reported that the paid family leave program has had either no effect or positive effects on profitability or performance. Further, the researchers found that 9 out of 10 employers (87 percent) reported no increase in their costs.

Some might also argue that paid leave is bad for business because it hurts their bottom line. The truth of the matter is that this argument fails to consider the opportunity costs of not providing paid leave, the costs that businesses here in the District and around the United States face currently. Further, a standard that provides workers with paid leave that is funded in a fair, administratively effective way levels the playing field and gives all businesses the ability to compete for talent, not just those that are large and can treat paid leave as a perk rather than a right.

Paid family and medical leave fosters economic security—boosting local demand—by making it possible to sell time in a way that works for families. After California implemented paid family leave, researchers found workers, especially low-wage workers, who took paid family leave through the state program were more likely than those who did not to transition back into their job and remain in the labor force. Among workers in low-paying jobs, 88.7 percent of those who used the leave returned to their jobs, compared with 81.2 percent of those who did not use the leave. The economist Tanya Byker found that the paid family and medical leave programs in California and New Jersey increased the number of mothers in the labor force around the time when they had a child. This was particularly the case for women without a college degree. Similarly, access to family leave to care for an elder can keep people in the workforce.

Paid family leave helps close the gender pay gap because it gives both men and women time to care for their families, boosting family incomes. The percentage of leave taken by men in California has increased since the institution of the state’s paid leave program. Men’s share of parent-bonding family leave—as a percentage of all parent-bonding family leave claims—increased from 17 percent in the period from 2004 to 2005 to 30.2 percent in the period from 2011 to 2012. In addition, men in California are taking longer leaves than they did before family and medical leave insurance was available.

Conclusion

As a District resident, I am proud that the D.C. Council is considering legislation that would help not only families across the income spectrum, but our entire economy. Families living in the District and considering moving here are different from those decades ago. They don’t often have the luxury of having a parent who doesn’t have to work, but they still have to deal with the challenges of welcoming a new baby or caring for an aging spouse or parent. And helping these families stay connected to the workforce helps businesses retain quality employees and keep people who otherwise might drop out connected to the workforce. That means these families can still spend time shopping at D.C. stores and paying income taxes, rather than cutting their budgets or relying on public assistance. We know from experience in states that have implemented paid leave that these changes are benefiting both workers and businesses. I, again, am honored to be here testifying about the Universal Paid Leave Act of 2015, and I thank you for the opportunity.

Allow me to restate two key points from my testimony. First, with an added cost per employee, it is less important whether the employer or the employee pays the bill. In the end, the cost will in all likelihood be passed onto employees through either changes in nominal pay over time or a marginal addition to consumer prices.

Second, the key economic point is that having families with working caregivers isn’t just nice, it’s an economic imperative for families and for our economy more generally. This is the kind of policy that keeps people in the workforce and sustains family income. This will, in turn, sustain consumer buying power, boost local tax revenues, and lower government expenditures on programs to support the unemployed and caregivers who have trouble addressing conflicts between work and life.

The State of the Union: a Rorschach test

Posted on by David Hudson
President Barack Obama delivers his State of the Union address before a joint session of Congress on Capitol Hill in Washington, Tuesday, January 12, 2016. (AP Photo/Evan Vucci, Pool)

Sometimes the truth seems like a Rorschach test. Two people can both look at the same inkblot but where I see a bunny, you see a bulldozer. We’re both right, of course, but we’re also both wrong.

Last night, as President Obama gave his final State of the Union speech, I was struck by how today’s economy seems like that famous inkblot. A large percentage of Americans believe the U.S. economy is performing poorly and that their jobs are seriously in jeopardy. The president looks at the same evidence and sees a strengthening economy.

“We’re in the middle of the longest streak of private-sector job creation in history,” he told Congress and the nation. “More than 14 million new jobs; the strongest two years of job growth since the ‘90s. An unemployment rate cut in half. Our auto industry just had its best year ever. Manufacturing has created nearly 900,000 new jobs in the past six years. And we’ve done all this while cutting our deficits by almost three-quarters.”

This is all true and it is good news. It’s especially so relative to the condition of the U.S. economy eight years ago. In January 2009 when President Obama entered the White House, the economy was shedding jobs at a rate of more than 20,000 per day. About 2.65 million homeowners were estimated to be in default in 2008, up dramatically from around 800,000 in 2005. And the stock market had shrunk by 44 percent from the beginning of 2008 to President Obama’s first inauguration. The economy appeared to be in free-fall.

Decisive action on the part of the President and Congress averted a full-scale economic collapse. But it didn’t prevent a multiplicity of smaller economic crises from happening inside families all across the United States. While there were immediate fixes made to avert a second Great Depression, serious long-term economic problems remain—ones that many Americans are fully aware of.

As President Obama acknowledged, not everyone is benefiting from the strong economic gains. For the past 40 years, our economy has been on an upward march of increasing inequality. The Great Recession and our policy responses to it didn’t change this course. According to the latest data from University of California-Berkeley economist Emmanuel Saez, between 2009 (when the economic recovery began) and 2014 (the latest year for which we have data), the top 1 percent of Americans have taken 58 percent of all economic gains. As of 2014, the bottom 99 percent had recovered just under 40 percent of the losses they suffered between 2007 and 2009.

Economic progress is important, but it must be shared. This is not just about values—although that’s important. Shared prosperity promotes economic stability. A key strength of our economy has always been our middle class. Yet the Pew Research Center reports that the share of Americans that are in middle-income households is at its lowest point since 1971.

As the president pointed out during his speech, the kind of economic security that families crave is more likely seen inside the halls of Congress than on Main Street. What’s more, many families have a nagging sense that the jobs being created aren’t as good as the ones we’ve lost. There’s fear that solid, middle-class jobs aren’t coming back. Some blame globalization or immigrants, but last night President Obama pushed the American people to focus on how “working families won’t get more opportunity or bigger paychecks by letting big banks or big oil or hedge funds make their own rules at the expense of everyone else; or by allowing attacks on collective bargaining to go unanswered.”

How do we give everyone a fair shot at opportunity and security in this new economy? Looking at what’s happening at the top of the income and wealth ladders is a good place to start. Economists are looking into the question of whether those at the top are getting more than their fair share—and they’re finding evidence that this may be the case. Armed with this data-driven research, policymakers can investigate the kind of pro-growth economic policies that may create the kind of economy that looks good to those at the top, the middle, and the bottom of the U.S. wealth and income spectrum.

Heather Boushey is Executive Director and Chief Economist at the Washington Center for Equitable Growth.

An introduction to the geography of student debt

Posted on by David Hudson

Today, the Washington Center for Equitable Growth, with Generation Progress and Higher Ed, Not Debt, released its interactive, Mapping Student Debt, which compares the geographic distribution of average household student loan balances and average loan delinquency to median income across the United States and within metropolitan areas. The stark patterns of student debt across zip codes enable us to begin to analyze the role that debt plays in people’s lives and the larger economy.

Delinquency and income

One element of the student debt story that has already been explored is that borrowers with the lowest student loan balances are the most likely to default because they are also the ones likely face the worst prospects in the labor market. Our analysis using the data displayed in the interactive map is consistent with these findings.

The geography of student debt is very different than the geography of delinquency. Take the Washington, D.C. metro region. In zip codes with high average loan balances (western and central Washington, D.C.), delinquency rates are lower. Within the District of Columbia, median income is highest in these parts of the city. Similar results–low delinquency rates in high-debt areas–can be seen for Chicago, as well. (See Figure 1.)

Figure 1

For the country as a whole, there’s an inverse relationship between zip code income and delinquency rates. As the median income in a zip code increases, the delinquency rate decreases, corroborating findings that low-income borrowers are the most likely to default on their loan repayments. (See Figure 2.)

Figure 2

What explains this relationship? There appear to be two possible, and mutually consistent, theories. First, although graduate students take out the largest student loans, they are able to carry large debt burdens thanks to their higher salaries post-graduation. One study of student loans by institution type reports a three-year cohort default rate for graduate-only institutions of 2 percent to 3 percent.* Second, the rise in the number of students borrowing relatively small amounts for for-profit colleges has augmented the cumulative debt load, but because these borrowers face poor labor market outcomes and lower earnings upon graduation (if they do in fact graduate), their delinquency rates are much higher. This is further complicated by the fact that these for-profit college attendees generally come from lower-income families who may not be able to help with loan repayments.

The inverse relationship between delinquency and income is not surprising, especially when considering that problems of credit access have disproportionately affected poor and minority populations in the past. In the 1930s, for example, the government-sanctioned Home Owner’s Loan Corporation labeled maps of American cities by each neighborhood’s worthiness for mortgage lending. Neighborhoods outlined in red were considered the least worthy, purposefully coinciding with their black and poor white populations. Banks and insurance agencies also adopted these discriminatory “redlining” practices, further cutting off communities from the essential capital that is needed to develop neighborhoods and invest in sustainable infrastructure. Though redlining was outlawed in the 1960s, its pernicious effects still persist, as seen in Figure 2 as well as in maps of the subprime mortgage crisis that began in 2006.

It might seem counterintuitive that lack of access to credit results in delinquency—seemingly a problem of “too much debt.” But in fact, lack of access to credit and delinquency are two sides of the same coin. Nearly everyone needs access to credit markets to meet basic economic needs, and if they can’t get loans through competitive, transparent financial networks, poor people are more likely to be subjected to exploitative credit arrangements in the form of very high rates and other onerous terms and penalties, including on student loans. That disadvantage interacts with and is magnified by their lack of labor market opportunities. The result is exactly what we see across time and space: high delinquency rates for those with the least access to credit markets.

Student loan balances and debt burdens

When we look at average loan balance and median income, we find a stark positive relationship, at least below a certain income threshold. As median income increases in a zip code, so does the average loan balance, until income reaches approximately $140,000. After that, the relationship becomes flat. (See Figure 3.)

Figure 3

Figure 4 shows the relationship between the “burden” of student loan payments and zip code median income. Using the “average monthly payments on student loans” variable, we calculate that student debt absorbs around 7 percent of gross income in zip codes where median income is $20,000, declining to 2 percent in the highest-income zip code

Figure 4

These graphs show us that the burden of student debt isn’t just shouldered by the young. As borrowers age, servicing their student debt hinders their ability to accumulate wealth. In fact, the Pew Research Center found that college-educated householders with student debt have one-seventh the wealth of people without debt, in part because the wealthiest students don’t need to go into debt to pay for college. Student debt repayment may also delay expenditures that are associated with the traditional economic lifecycle, such as owning a home or a car or even getting married. Altogether, this new expense associated with attaining a middle-class income contributes to the erosion of middle-class wealth across generations.

As cumulative student debt continues to grow and we learn more about its role in the nation’s many economic problems, it is clear that a reconsideration of the policies that treat student debt as “good debt” because it finances valuable human capital is in order, especially in light of the problems that even young college graduates have in the labor market.

Methodology

This geographic analysis uses two primary datasets: credit reporting data on student debt from Experian and income data from the American Community Survey.

The Experian data includes eight key student debt variables (see Figure 5) aggregated from household-level microdata to the zip code level. The underlying household data are a snapshot of the entire U.S. population at a single point in time—in this case, the autumn of 2015.

Figure 5

There are a number of caveats regarding the Experian data file that have guided our methodology for constructing variables and analyzing results:

• The universe of households contains only those with “any type of credit” and which, therefore, have a credit report. Relative to the population as a whole, this likely excludes the poorest households without any official credit access whatsoever.

• It is unclear how Experian constructs “households” since credit reports pertain to an individual’s credit history.

• If the same student loan has more than one signatory, then the loan may be assigned to multiple households and hence to multiple zip codes or even counted more than once within the same household.

• Experian claims that the universe of their geographically-aggregated data is all households with credit, but the levels of the data on loan balance and delinquency are more consistent with the idea that the universe is only households that have student loans. In other words, Experian claims their data include households that have credit but no outstanding student loans, but if that is the case the reported levels for both average loan balance and average delinquency are much higher than other sources would suggest. Average loan balance and average delinquency rates, however, are comparable to reliable outside estimates if interpreted as loan balance and delinquency among only those households with student debt.

For these reasons, we do not report any student loan data in dollar amounts. Instead, we have used two of the Experian variables to construct analogs to relative average household loan balance and relative delinquency.

To create the average household loan balance variable in the interactive map, we calculate an “average of the average” zip code-level student loan balance for the entire country, then code zip codes by percentage above or below that average-of-averages. For delinquency, we calculate a “delinquency rate” for each zip code by dividing the average number of 90-or-more-days-delinquent loans per household by the average number of outstanding loans per household. Then, after winsorizing the top one percent of observations to the 99th percentile value, we project the “delinquency rate” onto a scale that ranges from 0 to 10.

For user-friendliness, we assign each of these student debt scale variables a qualitative category. If average loan balance on the map is “somewhat high,” for example, then it means that a zip code’s average loan balance is between 25 and 35 percent higher than the national average of $24,271. Similarly, if the delinquency reads “very low,” it corresponds to a scale level between 0.067 and 0.091. Figure 6 summarizes the relationship between each of the scale variables’ levels and their qualitative description.

Figure 6

Next, we merge zip code-level median income data from the 2013 American Community Survey with our imputed scaled student debt variables in order to construct choropleth maps.

The actual map uses three different techniques to display the variables on a choropleth scale. For the average loan balance, we artificially set ten cutpoints to enhance the geographic variation in metropolitan areas; to do this, we maximized the breadth of the color categories for values higher than the average-of-averages loan balance. For delinquency, we created ten quantiles (or equal counts) to account for the right-skewed data. Finally, for median income, we used ten jenks (or natural breaks in the data) to assign the color scale. Higher numbers and darker shading correspond to higher household average student loan balances, higher shares of outstanding loans that are 90 or more days delinquent in the previous 24 months, and higher median incomes. We think that the geographic variation in the Experian data (and as seen in the maps) is believable, but not the levels reported by Experian.

Download the “Mapping Student Debt” presentation from the December 1, 2015 release (pdf)

*Correction, December 8, 2015: A previous version of this column cited a Department of Education projected graduate student default rate of 7 percent, but the Department has removed that projection from its website and we now think the 2 percent to 3 percent realized default rate is a better estimate.

Is the lack of paid leave partly to blame for declining U.S. labor force participation?

Posted on by Bridget Ansel
Couple with their newborn son, by Andy Dean, veer.com<br />

While once seen as an obscure “women’s issue,” policymakers and celebrities alike are increasingly arguing that paid family leave in the United States is a necessity in the 21st century.

Many businesses agree, with everyone from Netflix to Spotify jumping on the bandwagon and providing some of their employees with paid leave. Yet these are partial, private-sector solutions that, while a good first step, do not necessarily address the national problem. A new working paper released by the Organisation for Economic Co-operation and Development suggests that the United States’ failure to implement such policies on a federal level—as opposed to the other OECD countries—is generating consequences for our economy that go far beyond a single family.

While various types of paid leave have become standard practice in almost all OECD countries, the United States is the only developed nation that does not have any legal right to take paid leave to care for a new child. Some U.S. businesses do offer paid leave as a benefit, but only 12 percent of private-sector workers are employed at such places. U.S. federal law does mandate 12 weeks of unpaid leave through the Family and Medical Leave Act, but only 60 percent of workers are eligible for this benefit because of various restrictions. And, among those who are eligible, many cannot afford to go without pay for that period of time.

For individual families, this is clearly problematic. Without the kinds of income support and subsidized child care that workers in other OECD countries rely on, many American parents are forced to go back to work too soon after the birth of their child. This has consequences for parent and child alike. Parents, especially women, are  more likely to experience poor health and depression when they return to work too soon. And poor care early in life can hurt children’s health and development, which can affect their well-being far into the future. On the other hand, as the cost of childcare continues to increase, many parents—and women in particular—find that continuing to work is not necessarily the most economically beneficial choice.

But these consequences create ripple effects that go far beyond an individual child or family. The working paper points out that as other OECD countries began implementing a suite of policies designed to help working parents over the past three decades, the United States did very little. At the same time, the United States has seen its labor force participation rank screech to a halt since 2000, with the nation dropping from 7th among 24 OECD nations to 17th today. While the aging Baby Boomer population is a major driver of the declining participation rate, the paper also points to our inability to help workers balance their home and work lives as a contributing factor.

U.S. women’s ability to continue working has suffered in particular. A study by Cornell University’s Francine D. Blau and Lawrence Kahn found that work-life policies explain about 28% of America’s declining female labor force participation rate relative to other OECD countries. This trend is not likely to reverse. In fact, the OECD predicts that, if all stays as it is, substantial labor force declines will continue for the next few decades, which could come at a considerable cost to U.S. economic performance. In contrast, the OECD found that eliminating the gender gap in workforce participation by 2025 could boost U.S. GDP per capita by 0.5 percentage points.

California, Rhode Island, and New Jersey have all implemented paid leave programs. While Rhode Island and New Jersey’s programs are fairly recent, California’s paid family leave policy has been in place for more than a decade, giving researchers a sufficient timeline to evaluate the policy’s effectiveness.

Different studies all find that California’s paid family leave program has increased the percentage of women who stay in the labor market post-birth. California’s paid leave program also seems to be good for business—or at least it does not harm it. Because the program does not directly cost employers—it is funded completely by employee contribution—it does not inflict a disproportionate burden on businesses. In fact, the great majority of California businesses reported that the policy had positive or neutral effects on employee turnover, absenteeism, and morale according to a survey done by the Center for Economic and Policy Research’s Eileen Appelbaum and the CUNY Graduate Center’s Ruth Milkman. Initial evaluations of the program in New Jersey report similar findings.

As the OECD paper points out, implementing a national paid family leave program in the United States—along with other family-friendly policies such as subsidized child care and paid sick days—could go a long way in helping more women stay in the labor force. Doing so could help offset the slowdown in the nation’s labor force participation rate, and contribute to stronger U.S. economic growth.

 

What happened to the job ladder in the 21st century?

Posted on by Bridget Ansel
The job ladder, Veer.com

A few weeks ago, we published an analysis showing that the lowest-paying industries saw the largest increases in workers with a college degree between 2000 and 2014. Today, we follow that up by showing that the pattern is similar among young workers ages 19 to 34 (as opposed to workers with a college degree), but with one big difference—the oil, gas, and mining resource extraction and refining industries, which pay relatively well, saw a substantial increase in the share of young workers hired.

Considered alongside our previous results, this new analysis implies that resource extraction and refining industries provided an outlet for young workers without college degrees to attain well-paying employment. These industries profited from the development of hydraulic fracturing and other new technologies, as well as a worldwide boom in demand for natural resources that seems to have reversed since late 2014.

Figure 1

But these young adults working in the high-paid extraction and refining sectors obscures the larger picture of the U.S. job ladder: Outside those industries, young workers are increasingly being hired into low-paying ones. That is important to document because, as we discussed in our previous column, the education level for most workers in the U.S. Census Bureau’s Quarterly Workforce Indicators database is imputed rather than observed directly—and that imputation is potentially faulty since it is based on the 2000 Census. In contrast, the age of workers is observed directly for the vast majority of workers.

Figure 2

Looking at the share of young workers hired in each quarter between 2000 and 2014 yields further insight, which our colleague Kavya Vaghul discussed in part in her column last week on the impact of student debt on economic security. It divides industries into thirds based on their average earnings in 2000, then traces the share of hires in each industry that went to young workers. The share of young workers hired in high-paying industries shrank right at the onset of the Great Recession, while in its aftermath that share grew in low-paying ones. (See Figure 3.)

Figure 3

These findings are consistent with previous findings on the evolution of the job ladder during and after the Great Recession of 2007-2009, though our analysis indicates that the job ladder had already started deteriorating even before that, following the recession of the early 2000s.

The labor market has always been characterized by what economists call a “last in/first out” or “last hired/first fired” structure, meaning that workers who are laid off during recessions are generally those with the shortest job tenure, many of whom tend to be young. We also know that high-paying firms exhibited the greatest decline in hiring during the Great Recession. In combination, these two patterns imply that young adult workers disproportionately lost out at high-paying firms and industries, which is what the darkest green line in Figure 3 shows.

Following the Great Recession, employment grew most in low-wage jobs, so that is where young adults entering the workforce could find work—even if they had a college education. And because the high-wage firms and industries aren’t hiring, many of these workers are stuck in low-wage jobs. That failure of the job ladder portends dire consequences for young workers’ lifetime earnings since the peak years for job-switching and wage growth are the early ones. If these workers do not find opportunities to climb, then they will potentially be stuck on the lower income rungs for the rest of their lives.

Appendix

The construction of the U.S. Census Bureau’s Quarterly Workforce Indicators, the data from which these charts are constructed, is discussed in the appendix to our previous column. To make these charts on young adult workers’ share of hires, we define “young adult workers” as QWI age groups 2, 3, and 4 (comprised of workers ages 19 to 34), and we exclude groups 1 (ages 14 to 18) and 8 (ages 65 to 99) from the analysis entirely. Industry average earnings of full-quarter hires in 2000, or EarnHiraS, are deflated to 2014 dollars using the U.S. Consumer Price Index for all Urban Consumer, or CPI-U. When industries are divided into thirds according to earnings levels in Figure 3, the three groups are weighted by employment so that each group corresponds to approximately one third of the total U.S. workforce.

The observations excluded between Figures 1 and 2 are the North American Industrial Classification System (three-digit) industries 211 (Oil and Gas Extraction), 212 (Mining except Oil and Gas), 213 (Support Activities for Mining), and 324 (Petroleum and Coal Products Manufacturing, including Oil Refineries).

The pernicious effects of growing student debt on the economic security of young workers

Posted on by Bridget Ansel
Student debt illustration by David Evans, Equitable Growth

Student loans in the United States are now the second-largest source of debt, totaling $1.1 trillion shared among 42 million people with no sign of slowing down. Unfortunately, many questions about student debt, the characteristics of borrowers, and the nature of delinquency remain unanswered, primarily because agencies and researchers alike lacked access to the rich data in the U.S. Department of Education’s loan portfolio.

That changed last week when Adam Looney of the U.S. Department of the Treasury and Constantine Yannelis of Stanford University released an impressive new report that makes use of administrative data on student borrowing and earnings from linked, de-identified tax records to explore the student debt terrain.

Student debt nearly quadrupled over the past 15 years, and Looney and Yannelis find that the accelerated growth is largely due to a new type of borrower: students attending for-profit colleges. During the Great Recession, the number of students attending for-profit universities grew significantly in response to poor employment opportunities and a weak labor market. As a consequence, the number of borrowers grew too. Looney and Yannelis find that most of these “non-traditional” borrowers are vulnerable individuals who mostly come from lower-income backgrounds. Although average loan balances for borrowers who graduate from for-profit schools are smaller than those of nonprofit undergraduates or graduate students, these for-profit students face worse labor market opportunities, lower earnings, and, ultimately, much higher delinquency rates than their traditional college counterparts.

But just because the student loan crisis is concentrated among non-traditional borrowers does not mean that students attending a selective, non-profit, four-year university have it easy: The current labor market is not kind to young workers, even with traditional college degrees.

Young workers rely on job-to-job flows—transitioning between jobs to find better offers—in order to build their careers, move up the job ladder, and grow their earnings. Low unemployment allows workers to quit their jobs to search for more fruitful employment. When the labor market contracted during the Great Recession of 2007-2009, however, these job-to-job flows fell. Economists Giuseppe Moscarini of Yale University and Fabien Postel-Vinay of University College London find that during the recession, the jobs ladder shut down, trapping young workers in low-wage jobs. (See Figure 1.)

Figure 1

The danger for recent college graduates is that carrying a large load of student debt requires young people to remain employed, even at jobs that don’t pay well, and hence restricts their ability to search out better opportunities for long-term earnings growth.

Joseph Altonji, Lisa Kahn, and Jamin Speer of Yale University report that all recessions have a damaging long-term effect on recent college graduates no matter what they majored in. For the average major, a recession means a 10 percent reduction in earnings in their first year out of college. In past recessions, high-paying majors such as engineering were less adversely affected, but in the Great Recession, even an engineering degree wasn’t sufficient protection. The three researchers find that between 2007 and 2009, the effect of unemployment on earnings halved the relative advantage that a high-paying major previously guaranteed.

So if young, traditional college graduates are being challenged by the post-recession labor market, what happens when high levels of student debt are thrown into the mix? In a recent paper, Emmanuel Saez and Gabriel Zucman of the University of California-Berkeley find that between 1986 and 2012, the wealth of the bottom 90 percent of the wealth distribution in the United States didn’t grow at all. With the little wealth that is, it’s unlikely that recent graduates with large student debt are able to accumulate any savings after servicing their student debts. In fact, the Pew Research Center’s tabulations of the Survey of Consumer Finances show that college-educated householders under 40 who have student debt have one-seventh of the wealth of people who don’t.

Student debt is a long-term burden in other ways too. Paying off college loans displaces other costs associated with our traditional perception of U.S. adulthood and the economic life-cycle. Economists David Cooper and J. Christina Wang of the Federal Reserve Bank of Boston find that homeownership rates among college graduates ages 30 to 40 are lower for households with student debt. Similarly, other studies show that car ownership and marriage rates are also lower for young student borrowers.

As the student debt load grows for young borrowers, it is clear there may be long-term effects on young workers’ economic security. Just a generation ago, higher education was considerably more affordable or at least heavily subsidized by state governments, enabling young workers to begin saving and eventually realize the American Dream. But now, higher education is a transformative economic burden for the young workforce. And for the amount of student debt that graduates face upon entering the workforce, higher education certainly has not yielded commensurate benefits.

Putting the new U.S. Census data on income and poverty in context

Posted on by Nick Bunker

Earlier this morning, the U.S. Census Bureau released new data on the state of incomes in 2014. According to the new data, the share of income going to the top 5 percent of American households is at 21.9 percent, a 0.3 percentage point decrease from 2013. Similarly, the Gini coefficient (a broad measure of income inequality) was essentially unchanged at 0.480. The official poverty rate stood still at 14.8 percent.

The important new data released today, however, are far from the only source of data on income and poverty trends in the United States. Other datasets paint a different story of family economic wellbeing. For instance, the flat levels of income inequality over the course of 2014 in the Census data diverge from evidence of rising inequality in other data on family incomes. Using tax data, University of California-Berkeley economist Emmanuel Saez finds that the share of income going to the top one percent increased by 1.1 percentage points in 2014. Understanding the state of income inequality and poverty in the United States means we have to be aware of what the Census data can and cannot tell us about the broader trends.

Case in point: it’s important to keep in mind what the Census Bureau considers as “income,” which can be defined in a number of ways. It could focus on income that’s earned strictly from work or investments (“market income”), or it could focus on income after accounting for the effects of government spending programs and taxes (“after-tax-and-transfer income”). The Census takes a third route with its preferred measure, called “money income.”

Money income includes some government programs (such as Social Security or unemployment compensation) but not all of them (such as in-kind transfers including the Supplemental Nutrition Assistance Program, also known as food stamps). It doesn’t include the value of some market income (such as employer-provided health insurance). And it doesn’t include the effects of taxation.

The difference between the Census’s definition of money income and data sources that use a different definition can paint different pictures of what’s happening to the U.S. economy.

Consider trends in income for the median household (the household that’s directly in the middle of the distribution of income in the United States). According to the Census Bureau data using money income, median household income dropped by 8.7 percent from 2000 to 2011. But Congressional Budget Office data on after-tax-and-transfer income shows a much different picture. Over the same time period, that data set shows median household income increasing by 13 percent. The CBO data on market income show a decline of only 4.3 percent. (See Figure 1.)

Figure 1

Something similar happens when we look at the poverty rate in the United States. The Census Bureau’s official poverty rate shows an essentially flat trend over the past few decades, rising only from 14 percent in 1967 to 15 percent in 2012. But the official rate doesn’t include the effects of many anti-poverty programs that aren’t straight cash transfers.

Researchers at Columbia University created a series that accounts for these additional programs among other factors, and the trend is quite different from the official series—poverty starts much higher at 26 percent in 1967 and then declines to 16 percent in 2012. So while this trend shows a decline in the poverty rate over the years (due mainly to an expanded social safety net), it also illustrates the significant share of the population still in poverty. In 2014, the supplemental poverty measure was slightly above the official poverty rate.

The Census has its own preliminary alternative measure of poverty (the “Supplemental Poverty Measure”) that takes into account the research communities’ findings on how best to measure poverty. Like the Columbia University team’s measure, the Supplemental Poverty Measure also includes many anti-poverty programs that offer “in-kind” support rather than cash benefits. Today’s Census data using the Supplemental Poverty Measure pegs poverty at 15.3 in 2014.

The data released today are an important update on the state of income and poverty in the United States. The Census data fill out a picture of a U.S. economy where too many families are struggling, and where the typical family’s income remains 6.5 percent lower than it was prior to the Great Recession. While the Census figures certainly aren’t the final word on the issue, this release is a key addition to our ability to understand some of the most important trends—inequality and poverty—in the U.S. economy today.

The intellectual history of the minimum wage and overtime

Posted on by Casey Schoeneberger

The rapid growth of the “Fight for $15” minimum wage movement and President Barack Obama’s changes to overtime regulations have sparked new rounds of debate over the economic consequences of an increased overtime pay threshold and a higher minimum wage. Advocates of overtime and wage hikes argue these policies protect workers from exploitation and improve job quality. Opponents insist these regulations will hurt workers in the long run, as they will inflict a burden on companies that will be forced to cut jobs. These concerns are nothing new—this debate dates back to the early 20th century, before the minimum wage even existed in the United States and when overtime pay was unheard of.

At the end of the 19th century, economists such as John Bates Clark preached that markets, if left to their own devices, would function at equilibrium levels with the best possible distribution of resources. Rapid industrialization created the Gilded Age of American wealth, and people credited the free market with their increased prosperity. But along with increasing growth, industrialization also sharpened economic inequalities and made certain groups particularly vulnerable to exploitation. Debates over hour and wage limits focused on which groups required labor protections and the best mechanisms for protecting these groups.

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History of the Minimum Wage

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Labor regulations began in the 1890s as state-level maximum hour and minimum wage protections, which the U.S. Supreme Court repeatedly struck down. Federal standards were not created until four decades later, when president Franklin Delano Roosevelt and his Secretary of Labor, Frances Perkins, guided the Federal Labor Standards Act into law. (See Figure 1). This issue brief details the arguments that shaped hour and wage limits in the early 20th century.

Figure 1

Women’s maximum hours

U.S. legal historians usually describe the beginning of the 20th century as the “Lochner Era,” a 32-year period characterized by the Supreme Court’s attempt to protect the free market through its constant repeal of labor laws. The Supreme Court actually was discriminatory in its protection of the free market—although it consistently blocked labor laws that applied to men, the high court allowed restrictions on women’s employment. The Supreme Court passed distinct rulings for men and women by emphasizing different doctrines for the two sexes. For men, the court consistently upheld freedom of contract; for women, the court privileged police powers.

The Supreme Court’s gender discrimination began with cases concerning maximum hour limits. In Lochner v New York (1905), the namesake of the Lochner Era, the court justified its decision to strike down the 1895 Bakeshop Act—which placed hour limits on New York bakers—with the freedom of contract doctrine. Freedom of contract comes from the due process clause of the Constitution, which says that no person shall be “deprived of life, liberty, or property without due process of law.” At the time, justices interpreted due process to mean that individuals should be free from restraint except to guarantee the same freedoms to others, and that government could not restrict people’s ability to acquire future property. Limiting the hours that New York bakers worked, proponents argued, took away their liberty to choose the terms of their employment and limited the money they could earn, so maximum hour laws violated freedom of contract.

Just three years later, the Supreme Court set a different standard for women. In Muller v Oregon (1908), it upheld a 1903 Oregon law that prohibited women from working more than 10 hours a day. The court argued that women’s freedom to contract was superseded by the police powers doctrine, which allows government regulation for the purpose of promoting health, safety, morality, and the general welfare of the public. The court found that “as healthy mothers are essential to vigorous offspring, the physical wellbeing of woman is an object of public interest.” In other words, protecting women’s reproductive health was more important than respecting their freedom to contract. Women were also seen as fragile, vulnerable, and lacking the skills necessary to effectively bargain for wages and working conditions, and therefore unable to exercise their freedom of contract. These sex-specific discussions about government-imposed hour limits set the stage for a new conversation: the passage of state minimum wages.

Women’s minimum wages

In 1912, Massachusetts became the first state to pass a minimum wage law that applied only to women and children. Thirteen more states (along with DC and Puerto Rico) followed in the next 11 years. These legislatures passed a patchwork of legislation with a range of wage limits and enforcement mechanisms. States such as Massachusetts created wage commissions to determine industry-specific minimum wages and enforced standards through public shaming, publishing the names of companies that did not comply with the regulations. In contrast, states such as Arkansas set two cross-industry minimum wages for women: experienced women were paid $1.25 a day while inexperienced women only got $1.

The police powers doctrine justified minimum wages for women, but said nothing about how they affected industries. To justify minimum wages on the industry side, academics used the parasitic industries argument. Originally developed by the British economists Beatrice and Sidney Webbs in the late 19th and early 20th centuries, the parasitic industries argument says that businesses who focused on short-term profit maximization instead of long-term efficiency tend to pay workers unlivable wages. Workers receiving these sweatshop wages become a burden to society, since they have to rely on charity or other family members for subsistence. To fix the problem, companies have to either amend their practices to consider the long-term welfare of the company and the workers, or exit the market.

Women’s minimum wage laws grew out of gender norms supporting women’s protection, but at the same time, racial biases led to laws that neglected women of color. Because minimum wage legislation was usually industry-specific, industries such as domestic work, agriculture, retail, and laundry—all dominated by African American workers—were often excluded from regulation. One case in point: The Wage Board in the District of Columbia set a weekly rate for laundry workers that was $1 lower than the across-the-board minimum adequate weekly wage of $16 it has previously chosen. The board explained that since 90 percent of laundry workers were African American, “the lower rate was due to a crystallization by the conference of the popular belief that it cost colored people less to live than white.” By not extending equal minimum wage protections to African American women, minimum wage laws reinforced their lower economic status.

In the next decade, legal changes in women’s status, paired with the economic optimism of the Roaring Twenties, brought a big shift in minimum wage legislation. Ratified in 1920, the 19th Amendment granted Women’s Suffrage. Shortly after, in a victory for more equal gender standards but a loss for labor protections, the Supreme Court issued a ruling that struck down women’s minimum wage laws across the country. In Adkins v Children’s Hospital (1923), the court overturned the 1918 law that created D.C.’s Wage Board, which had set minimum wages for women employed in laundries and food-serving establishments. Reasoning that women were now politically empowered to advocate for themselves in the free market, the Court privileged freedom of contract over police powers and nullified minimum wage laws in the United States.

This optimism about the competitiveness of the free market did not last long. Once the Great Depression hit, people lost faith in the fairness of the U.S. economy. The failure of the banks cultivated distrust of large corporations. People were afraid that business concentration hurt competition and created unfair trusts. The new popular economic narrative of economists such as Joan Robinson and Edward Chamberlain said that imperfect and monopolistic competition dominated the market. This unfair competition gave businesses a huge advantage, which they used to exploit labor. Public opinion shifted toward seeing government intervention not as redistribution but rather as reestablishing a competitive market.

The Fair Labor Standards Act

In this rapidly shifting political and economic climate Franklin D. Roosevelt won the 1932 elections and appointed Frances Perkins as his Secretary of Labor. With decades of experience advocating for labor rights as a social worker and later as Roosevelt’s Secretary of Labor when the future president was governor of New York, Perkins accepted the federal cabinet office on the condition that Roosevelt would commit to supporting her reform platform, which included hour limits and minimum wages for both women and men. Perkins’ platform originally appeared in the National Industrial Recovery Act, which tried to improve working conditions through voluntary industrial participation. Under the proposed law, industries would be able to form alliances, which previously violated anti-trust laws, if they complied with maximum hour and minimum wage standards. In return, participating companies could display a Blue Eagle emblem in their stores, brandishing their patriotism and commitment to post-Great Depression recovery. In Schechter Poultry Corp. v United States (1935), however, the Supreme Court struck down the law, drawing the ire of Roosevelt and forcing Perkins to find a new way to pass labor reform.

Out of growing frustration with the Supreme Court’s challenges to his policies, Roosevelt came up with a plan to pack the court. He set off a campaign to reform the Supreme Court so he could appoint additional members to the court who would vote in line with his New Deal reforms. Faced with this existential threat and greater public support for labor laws, in 1937 the Supreme Court ruled in favor of Washington state’s minimum wage law for women in West Coast Hotel Co. v Parrish. The court’s ruling de-emphasized the freedom of contract, reversing its 1923 decision and opening the door for future minimum wage legislation.

Following the Supreme Court decision, Perkins and Roosevelt sent a maximum hour and minimum wage bill to Congress. The original draft of the bill had called for industry-specific, regionally variant minimum wages to account for regional differences in prices and cost of living. As the bill made its way through Congress, two more opposition groups emerged: unions and northern industries. Unions feared that government-imposed wage and hour restrictions would undermine their influence in collective bargaining. Northern industries opposed regionally specific wages for fear that industries would follow the cheap labor south. To appease these two groups, Roosevelt and his Democratic allies in Congress tweaked the bill to make it more popular. Roosevelt appeased the unionists’ fears in his State of the Union address by emphasizing that more desirable wages should continue to be the responsibility of collective bargaining. Lawmakers suggested a national minimum wage to satisfy northerners, but set the wage low enough to appease southerners.

In its final form, the Fair Labor Standards Act of 1938 mandated a 44-hour workweek, scheduled to decrease to 40 hours in three years, with time-and-a-half overtime wages. The new law also created a minimum wage of 25 cents an hour, set to increase by 5 cents a year to reach 40 cents an hour by 1945. The original law was not universal. It included exemptions for agricultural, domestic, and some union-covered industries—once again, mostly industries dominated by African Americans. Since the law lacked a mechanism for automatically increasing wages beyond 1945, it has been updated over the decades to increase wages and broaden industry (and racial) coverage. In the most recent revision to the Fair Labor Standards Act in 2009, the federal minimum wage was increased to $7.25 an hour.

Conclusion

The intellectual history of maximum hours and minimum wages is a story of debates over which groups should be protected from exploitation and what form this protection should take. Concerns over women’s health, ambivalence toward African American rights, and advocating for unorganized workers dominated the debate at different points. As social views changed, so did economic policies. Today, women account for two-thirds of minimum wage earners and people of color account for two-fifths. Studying the history of the minimum wage should compel policymakers to question how social priorities influence different groups, who is considered worthy of protection, and to what extent their welfare is considered. By implementing effective maximum hour and minimum wage regulations, policymakers can protect vulnerable workers’ standard of living to encourage productivity, push companies to increase their efficiency, and consequently cultivate long-term equitable growth.

-Oya Aktas is a Summer 2015 intern for the Washington Center for Equitable Growth