Category: Economic Stability

The value of search-and-matching models for the labor market

Posted on by Ed Paisley

University of Queensland economics professor John Quiggin of Crooked Timber recently published an excellent blog post questioning the usefulness and empirical success of the dominant macroeconomic model of the labor market: the search-and-matching framework.  Peter Diamond of the Massachusetts Institute of Technology, Dale Mortensen of Northwestern University, and Christopher Pissarides of the London School of Economics won the Nobel Prize in Economics in 2010 for their foundational work on this model. Most recent theoretical and empirical work on macro labor markets, including my own dissertation, is based on it because it was the best thing economists had on hand when the world came calling to ask about unemployment in the Great Recession.

Moreover, several high-quality datasets that track the model’s observables have also become available in recent years and have enabled important empirical work based on investigations of the model’s predictions and the implications of their success and failure. But Quiggin’s critiques are well taken, and have sparked an interesting conversation, with contributions from Stony Brook University economist Noah Smith, the Roosevelt Institute’s Mike Konczal, and others. Why is it worth having this discussion? Is this just an ivory tower academic debate about oversimplified mathematical formalizations with no empirical basis?

On the contrary, a correct understanding of the labor market is of central importance to assessing its ailments and ordering the right prescription. And the labor market is the way that the majority of people earn the majority of their living, although that living has gotten more meager for all but the top few over the past several decades. The middle fifth of the household income distribution earned labor income of $45,315 in 2011 dollars, or 77.1 percent of their total income, in 1979, and only $45,997 (amounting to 65.8 percent of their income) in 2007—a mere 1.5 percent increase despite a 129 percent increase in inflation-adjusted gross domestic product. The overall share of national income going to labor has declined from 79 percent in 1979 to 71 percent in 2010.

The search-and-matching model works like this: one class of agents, “workers,” is either searching for a job or employed while another class of agents, “firms,” is either vacant, meaning it has a vacancy posted, or filled, in which case it employs a worker and together they hum along productively. In the earliest formulation of the model, the only economic decision made by either agent was whether a firm would post a vacancy in an attempt to match with a worker or would choose not to, thus remaining inactive. Otherwise, both searching workers and vacant firms mindlessly wait until they match up, then commence a productive relationship that lasts until their match spontaneously dissolves. Then the worker goes back to searching and the firm makes its decision about whether to post a vacancy or not once again.

The reason why search-and-matching labor market models have something to say about the recent history of the labor market is because they are a good deal richer than the simple search-based story, which is the reason why Federal Reserve Bank of Richmond economist Karthik Athreya, whose book sparked this discussion, said that “search is not really about searching.” Specifically, they allow for alternative theories of wage-setting, a factual timeline for unemployment spells and what determines their duration, a rich set of labor market outcomes beyond employment and unemployment, and an implementable notion of power that is often a critical missing piece of economic modeling.

Like all economic models, the search-and-matching model is a simplification, even a ludicrous one. Quiggin argues that it fails even as a simplification of reality because the main reason why unemployment exists is not because workers and firms are groping in the dark for one another, a process which just by its nature takes time. And he’s right about that. So do we search theorists have a big problem?

Notice that my summary of the model left out one big thing: how the fruits of the productive employment relationship are split between the worker and the firm. This is by far the biggest controversy in the field of search theory. The assumption made by the earliest search-and-matching models is that the “surplus” the two agents generate is split between the parties in the optimal way, where the optimality concept is defined within the model but with some relationship to a more general intuition about what each party would want. (That optimal way is known as the “Nash Bargain” after the Nobel-Prize-winning mathematical theorist John Nash, the protagonist of the film A Beautiful Mind.)

The problem is that this theory of wage setting is an empirical disaster. Not only is it inconsistent with investigations into how actual wages are actually set, but it generates false predictions about unemployment spells that crucially fail to line up with what happens to unemployment during recessions (it goes up, and it stays high for a long time, when the optimal theory of wages says that wages should do the adjusting). Refinements that make the theory with Nash Bargaining consistent with the data on unemployment in recessions yield their own big empirical problem: those refinements imply that being unemployed isn’t really that bad for workers, which everyone who is sentient knows to be untrue.

So the search-and-matching model has a crazy theory about how wages are set, and that makes it a crazy model of how labor markets work, right? No. What the search-and-matching theory has, and what its alternatives lack for the most part, is indeterminacy about how wages are set. The “Nash Bargain” theory is optimal, but it’s not necessary—other wage-setting assumptions can be used to resolve the indeterminacy. And if economists can get their minds around the idea that the “market solution” is not always optimal then they can make real headway with the search-and-matching approach precisely because it’s consistent with those alternatives.

That’s where the most promising research into the macro labor market is happening. If wage-setting in the search-and-matching model is made more factual by including what seems to be the well-established norm of not actually cutting pay in nominal terms, then it generates long unemployment spells and high unemployment rates—not because something about the matching process has become more inefficient, which Quiggin is correct to call absurd, or because workers don’t care whether they’re employed or unemployed— but because the labor market is a great deal stickier than the canonical competitive equilibrium model assumes.

The search-and-matching model boasts several other strengths. In the popular imagination (mostly of those who have never been unemployed), unemployment follows a large-scale layoff. Basically, it’s the destruction of employment that leads to high unemployment. But in reality, high unemployment occurs mostly when the hiring rate declines. The overall job separation rate is, in general, not related to the business cycle, and it has been in long-run decline, which is itself evidence of ill health in the labor market. There was a very transient uptick in mass layoffs during the 2008 recession, but the market reverted to its long-run level of around 1.2 percent laid-off per month as the official recession ended in late 2009.

Hiring, on the other hand, went down at the beginning of the recession and has remained lousy for a long time. The factual way to interpret this is that there’s inherently churn, or movement in the labor market as workers quit jobs or get laid off and are hired for a new job. The labor market is unhealthy when the workers who leave their jobs can’t find new ones. That is a story that can’t be told without a search-and-matching model.

Furthermore, modifications to the search-and-matching model allow it to explain numerous other phenomena. Instead of workers being only either employed or unemployed, non-employed workers can be allowed to exit the labor force entirely, to go on disability, or to remain in traditional unemployment (that is, receiving unemployment insurance while searching for a job), or enter some other unattached state. Employed workers can be allowed to remain happily with their existing firm or look for a new job while staying employed at the old one. These elaborations obviously allow for a richer set of predictions, and they also let trends such as a prolonged slack labor market to manifest themselves in more ways than high unemployment and/or low wages, including the reduced size of the labor force and more job-lock as those lucky enough to have a job cling to it tenaciously.

Another strength of the search-and-matching approach, and one that is essentially an implication of the indeterminacy of wages, is that it has room for the concept of power, which alternative approaches, especially the competitive equilibrium, do not. In the Nash Bargain, there’s an explicit mathematical parameter that captures the relative power that workers and firms have in the wage-negotiation process. That alone is not terribly meaningful because if anything is an endogenous concept requiring an explanation rather than simply a mathematical assumption, it’s power.

But power also works its way into the model through what are known as the parties’ threat points, meaning the alternatives each agent has available when they are negotiating. When the labor market is weak and unemployment is high, the threat point for workers deteriorates, which means they can be squeezed by firms, a phenomenon that captures a great deal of truth about the functioning of the labor market and needs to be in any model of it. That phenomenon is right there in search-and-matching.

Quiggin makes much of the observation that the rise of Internet-based job searches has not led to a decline in the unemployment rate by making the search process more fluid, as the search-and-matching model supposedly predicts. But the issue is this: has the Internet actually changed how the labor market works? In some ways, it has. My organization, the Washington Center for Equitable Growth, currently has a job vacancy posted (one that would not be captured by the standard data on job vacancies) for which we’ve received a great many applications, whereas in the past a classified advertisement might have yielded a dozen phone calls and half that many mailed resumes.

But we will still take many weeks to interview candidates and fill the position. Thus, a decline in what might be considered search costs just leads to more searching, but not necessarily more matching. A similar dynamic is at play in the rise of the average number of colleges most applicants apply to: instead of streamlining the search process, more information just intensifies it.

There are other examples where one might have expected advances in information technology to have had a significant macroeconomic impact but which in fact have not. Financial integration is one: in the 1990s and early 2000s, then Federal Reserve Board chair Alan Greenspan assured us that in a world of instantaneous financial transactions and global credit markets, systemic risk could not rise because everyone is connected to everyone. We all saw how that turned out. Similarly, ATMs were supposed to have decreased the economy’s structural demand for money, which means that unless the money supply also shrank dramatically there would be high inflation. Nope. Exactly why supposedly world-changing technologies don’t actually change the world is a difficult question, but that critique is not one that pertains to search-and-matching labor market models specifically.

Quiggin also argues that the big question in labor market macroeconomics—essentially, why is labor demand low and why does it stay low—can only be answered by macroeconomic models. He asserts that search-and-matching models don’t add any insight. Let me offer an alternative schematization. There are two big questions in business cycle macroeconomics. Why do recessions happen? And why do they look the way they look, with high, persistent unemployment and a cascade of other symptoms of illness in the labor market?

Search-and-matching models don’t do anything on the first question; one has to assume the recession into the story. But the model goes a long way toward answering the second one if you allow for factual wage-bargaining and other modifications. In short, the model is a great tool to have in the economist’s toolbox, provided it’s used skillfully and with attention to the data, first and foremost.

 

Is Piketty’s treatment of housing an excuse to ignore him?

Posted on by Marshall Steinbaum

French economist Thomas Piketty’s treatment of housing as capital in his blockbuster “Capital in the 21st Century” is not an excuse to ignore his predictions about rising economic inequality. “Capital in the 21st Century” is clear from the beginning that housing—and real estate generally—ought to be included in the definition of “capital” for the book’s purpose, which is to examine the aggregate effect of accumulated wealth that produces an annual return through no effort on the part of its owner.

A whole set of Piketty “rebuttals” attacks that treatment of housing as capital. The critics focus on that aspect of his analysis because a large proportion of the increase in the capital-to-income ratio that he emphasizes is thanks to the accumulation of housing and real estate at market prices. In some countries, the rise in the value of housing accounts for all of the increase in the capital-to-income ratio since 1970. And even beyond housing, Piketty’s approach is not consistent with standard neo-classical economic theory in several important ways—and so the critics have looked to housing as a reason to cling to their theory in the face of his countervailing facts.

But if housing were not counted as part of capital in Piketty’s analysis then the wealth distribution patterns he explores would be even more skewed. He identifies one key historical phenomenon that is unique to the 20th century—the rise of what he calls a  “patrimonial middle class,” that is, non-trivial, inheritable wealth holdings by those between the 50th and 90th percentiles of the wealth distribution in advanced economies, rather than the top decile holding nearly all the wealth as was true in the 19th century and previously.

So, even though total capital accumulated (as a percentage of national income) has already reached the level where it was in the late 19th century, inequality has not yet attained its prior height, at least not in Europe, because that capital is partly held by the middle class. And their wealth is largely in housing.

This means that removing housing from consideration would by fiat skew the wealth distribution as much as Piketty predicts it will be skewed in the future if that patrimonial middle class dwindles, which is the dire outcome his whole book warns against. In other words, the arguments put forward as part of an attempt to discount Piketty’s prediction about the rise in capital’s share of income would, if accepted, put his prediction about the evolution of wealth inequality into effect mechanically. So how should economists interpret housing wealth?

Is housing capital?

Claim:  Housing is not “productive” capital, like machines or factories or even farmland.

Response: In fact, housing is productive in the sense that it produces a good—shelter, broadly conceived—that economic agents value. Someone who owns his or her home doesn’t have to pay rent, and the owner of an investment property will earn rent exactly as does the owner of some piece of “productive” capital equipment. Second, capital functions as a store of value, and not simply as an input to production—a function that Piketty’s historical data show has been vital over the long run.

To take the argument a bit further, the value in real estate is often a matter of proximity—of “location, location, location”—and proximity to productive economic activity or to agents whom it is valuable to know is a very real economic resource. That proximity is capitalized as real estate. An identicallysized and equipped dwelling in Manhattan, Kansas costs much less than one in the more famous Manhattan because of the productivity and amenity benefits that come from living and working near many other people in New York City.

Arguably, in a world of increasing population density, location has been getting more important, and incumbent owners of real estate have been the main beneficiaries. Klaus Desmet at the University of Charles III and Esteban Rossi-Hansberg at Princeton University have a 2014 paper called “Spatial Development” that emphasizes population densification as the cause of productivity gains, location rent dynamics, and inter-sectoral employment flows in the United States. Piketty doesn’t discuss spatial trends as such, but the dynamics of housing wealth are entirely consistent with the argument in “Capital in the 21st Century.”

Excluding housing and real estate from the capital stock is convenient if the goal is to dismiss Piketty’s data and predictions, but that interpretation is not warranted by economic theory or empirical analysis.

How should the value of housing be calculated?

 Claim: Piketty’s use the market price of housing distorts his analysis because housing should be priced according to its discounted rental stream, which is a measure of its “fundamental value.” The market price is subject to bubble dynamics, which according to the standard economic theory of bubbles would occur when the price deviates from some notion of its fundamental value, such as if a fruit tree were to cost more than the appropriately discounted sum of all the fruit it will ever produce.

Response: This critique fails for the same reason the argument that housing isn’t capital fails—because capital, broadly conceived to include wealth, is a store of value, and thus the stream of annual rent from its users isn’t the only relevant aspect of the return to its owner. The price of housing in central metropolitan areas has been on an upward march for the past several decades, in part because economic agents foresee dynamics of the kind described by economists Desmet and Rossi-Hansberg and in part because investing in real estate abroad is an effective way for the wealthy global elite to stash their cash overseas. At times, this has given rise to the property bubbles observed in Japan before 1990 and in the United States before 2006, but the resulting firesales do not erase the long-run trend. The fluctuation in housing market prices probably occurs in part because of misperceptions or misevaluations of the timing of long-run trends, but that does not imply the trend doesn’t exist.

Is housing really as substitutable with labor as Piketty assumes?

Claim:  Including housing in the stock of capital should reduce Piketty’s assumed value for the marginal rate of substitution between capital and labor, and hence his prediction of an increasing capital share of income. Piketty’s assumption that the marginal rate of substitution between capital and labor is greater than one is important since it implies that the aggregate rental rate of capital will not decline by as much as the stock of capital increases.  In other words, workers face no threat of losing their jobs just because more houses exist since there’s “no way to substitute a house for a worker.”

Response: Piketty’s main argument that the marginal rate of substitution is greater than one—that workers are indeed threatened by capital accumulation, including housing—is based on the dual U-shaped historical evolutions of the capital-to-income ratio and capital’s share of income in the very long run. That implies that when capital is accumulated, the resulting decline in the price of capital is not large enough to offset the increase in its quantity. Hence, the total share of income going to capital is higher when there’s more capital. If the marginal rate of substitution were less than one, the capital share would move inversely with the capital-to-income ratio, and if it were equal to one, as neo-classical theorists generally assume, the capital share would not change at all with the capital-to-income ratio.

All the evidence that the marginal rate of substitution between capital and labor is less than one cited by the critics is drawn from relatively short-run studies of the tradeoff between capital and labor at the firm- or industry-level, and there are very good reasons to believe that long-run elasticities are higher. Piketty’s long-run, aggregate evidence already includes the historical value of housing in capital, so this critique doesn’t bring anything more to the table—Piketty already has an excellent empirical case for assuming the marginal rate of substitution is high: the dual U shapes cited above.

Moreover, the aggregate marginal rate of substitution incorporates a much larger range of empirical economic phenomena than simply how easy it is to substitute between two factors in the production of a single good. So interpretations that adhere narrowly to that premise—such as econometric estimates at the firm or industry level—are bound to fail. The neo-classical argument holds that the price of capital is determined by its marginal productivity, and that marginal productivity declines mechanically as the quantity of capital increases. That is the so-called Ricardian scarcity principle, named for the 19th century thinker David Ricardo.

The rate at which it declines depends on how substitutable capital and labor are. The argument that they are not very substitutable implies that additional capital is relatively useless—and hence that its price will get much lower as its quantity increases. Notably, if what is relevant about housing and its value dynamics is that it acts as a store of value, then there’s no reason to believe that diminishing marginal productivity is operative. That concept relates to the additional output produced by increasing the use of one input in production while holding all others constant, but there’s no production going on if what’s being amassed is a store of value.

In this sense, housing wealth accumulation is like hording a precious metal: how useful the metal is in the production of other goods is irrelevant to the value of the horde. Finally, there are strong empirical reasons to believe that the price of housing, and of capital in general, is not only determined by marginal productivity as in the traditional, neo-classical macroeconomic model. That is the subject of my next response.

Are housing price increases due to supply restrictions?

 Claim: There’s been a great deal of research into the dynamics of the housing market since the housing bubble burst, starting in 2006, and especially the unsurprising conclusion that local housing supply elasticity is related to price dynamics, and further, that political pressure by homeowners and the mortgage lending industry, especially on the west coast of the United States, has constrained housing supply and led to the enormous price swings. Those supply restrictions have nothing to do with the rise in the capital-to-income ratio and the reasons for it proposed by Piketty.

Response: This explanation for housing price dynamics isn’t actually distinct from Piketty’s narrative. The Economist commentator Ryan Avent wrote about this eloquently: “Over the last few decades technological changes have greatly increased the return to locating in large cities filled with skilled people. Being in such places makes workers more productive and raises the income they are able to earn. But skilled cities have not allowed housing supply to expand to meet rising demand. Housing has therefore been rationed by price, pushing less productive workers toward cities where housing supply growth is higher and housing cost growth is lower.

As a result, fewer people live in the most productive places, and quite a lot of the gain from employment in productive places is captured by landowners earning rents thanks to artificial housing scarcity. This may mean lower overall productivity, more income inequality, and more income flowing to capital rather than labour.” In other words, what we have here is collective political action to make sure the price of housing remains high just as increases in the bargaining power of capital relative to labor have contributed to the decline of the labor share. There is no room in the neoclassical model for these effects—only for the Ricardian scarcity principle and diminishing marginal productivity—but that doesn’t mean they aren’t there.

The answers are clear

Piketty’s framework, including his decision to count housing as capital, does not map directly onto the standard neoclassical economic growth model—but his approach is more consistent with empirical reality in several key ways. The critics who want to cling to their outdated theories have latched onto his interpretation of housing as a way to do so, but given their theory’s many empirical shortcomings, they are seriously misguided.

Job quality matters: How our future economic competitiveness hinges on the quality of parents’ jobs

Posted on by Alexandra Mitukiewicz

Being the parent of young children in the United States today is no easy task. Many have to juggle multiple jobs with unpredictable hours—single-parent and two-income families alike—and whether wealthy or poor, the question of childcare is ever present. Only adding to this stress is the growing evidence of the importance of the years between conception and kindergarten for a child’s development. No wonder parents, and particularly mothers given their traditional role as the primary caregiver and increasingly as breadwinner, are so concerned about how to balance work and raise their young children.

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The findings of many new studies on the importance of children’s early years for future outcomes should give pause to parents and policymakers. As this paper documents, the research shows that children’s kindergarten skill levels are correlated with their subsequent success (or failure) in the job market as adults, even accounting for the quality and quantity of elementary, secondary, and post- secondary schooling.1 An even more worrisome finding is that experiencing stress during childhood or adolescence (such as experiencing a parent working a low- quality job—or worse—losing a job) can negatively affect mental and physical health, and educational attainment and have lasting effects into adulthood.2

No wonder harried working mothers and fathers, up and down the income ladder, report conflicts between their job and meeting their children’s needs. Our work- place policies largely fail to help the majority of working parents—a substantial majority of whom lack the income to compensate for the lack of family-friendly workplace policies in our nation. In 2013, only 61 percent of private-sector workers had employer-provided paid sick days and only 12 percent had access to employer-provided paid family leave.1 Access to workplace flexibility policies is also extremely limited: in 2011, only half of workers had access to flexible hours policies and about one quarter of workers had access to flexible location policies.4

Low-income workers have even more limited access to policies to help them address conflicts between earning a living and caring for the next generation. Too many families rely on a fragile patchwork of familial and non-relative care to try to balance the demands of work and home.5  In a 2000 study of low-income working parents, the majority of parents reported that they did not expect to be able adjust their work schedules or create arrangements to better balance work and family, other than through finding another job.6

 In short, the structures of our workplaces today do not at all match the needs of working parents or their children. This crisis in the home is not just a private problem—it is one of national importance. In not meeting the needs of today’s children, we risk a lower-productivity future, which will have serious implications for our nation’s economic growth.

Economists have long argued that human capital, that is, the level of skills, education, and talents of the potential workforce, is one of the most important factors in deter- mining economic growth.7  Human capital has long been the engine powering our nation’s global competitiveness. Yet, growing evidence suggests that the United States is falling behind other countries in terms of skill acquisition. New data from the Organisation for Economic Co-Operation and Development found that across 34 developed countries, U.S. teenagers rank 17th in reading, 21st in science, and 26th in math.8

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In the national debate over how to improve skills of the U.S. workforce, economists and policymakers are looking to early childhood and finding compelling evidence that the early years matter far more than we previously understood. Economists traditionally measure human capital in terms of educational attainment or levels of training, but this may overstate the importance of post-secondary education.9  This is not to say that later investments are not important, but that recent research in economics points to the conclusion that, in order to improve our nation’s economic growth and competitiveness, policymakers must also focus on early childhood.10

 Early childhood is so important because this is when we acquire what economist and Nobel laureate James Heckman terms “non-cognitive” skills, also known as “soft skills,” which are both important on their own as well as provide the foundation for later skill acquisition.11 Non-cognitive skills are skills that are not specifically intellectual or analytical in nature, such as a child’s perseverance or ability  to get along with others. By and large, these soft skills are learned from primary caregivers very early in life—be they mom and dad, grandparents, childcare professionals, some combination of these role models, or sadly sometimes hardly anyone at all. This is why it is so important for our society and our policymakers tounderstand the largely under-explored issue of children’s widely differing early childhood experiences due to changes in inequality and the kinds of jobs in which their parents are engaged.

Two interrelated trends define the economic experience of families over the past 50 years. First, families have altered the way they work and care for children. Most children no longer have a full-time, stay-at-home parent, which means that where and how children spend their days are markedly different compared to a generation or two ago.12  The typical American middle-income family put in an average of 11 more hours a week at work in 2007, just before the start of the Great Recession, than it did in 1979 and, in 2010, fewer than one third of children lived in a family with a full-time stay-at-home parent.13 Abundant economics research has explored the effects of greater maternal employment and the quality of childcare on children’s outcomes, but we know much less about how the quality—and flexibility—of parents’ jobs interacts with these processes. What we do know from the research points to the conclusion that parental job quality, including the ability to have some control over when work happens, is a very important issue.

Second, the United States has seen a sustained rise in economic inequality, widening the gap between low-and high-incomes to unprecedented levels.14 As has been well documented, inequality in the United States has taken the form of the top pulling apart from the rest of the income distribution, with little income gains for the bottom 90 percent of families.15  This means that while some children have access to immense resources, others lack access to the resources they need to be fully productive members of our society and economy. Just as importantly, high inequality is associated with greater divergence in access to high-quality jobs— those that pay good wages, offer stable and predictable schedules, and provide benefits that allow workers to address conflicts between work and family.16 This means that low-income children are experiencing the double-whammy of less income just as their parents cope with less control over their time to provide care.

This report examines what is known about the importance of early childhood for the development of human capital, then turns to what we know about the effects of family income, employment patterns, and job quality on children’s development. We find that job quality, especially control over schedules and access to benefits that allow workers to address conflict between work and family, is an under-examined issue in the economics literature. However the research that does exist shows that this is an important issue to include in our policy agenda to improve children’s outcomes.

Briefly, here is what we discovered:

 

  • The time parents spend with their child affects the child’s cognitive and non-cognitive development, with strong effects during a child’s earliest years.

 

 

  • Mothers’ movement into the workplace and the rise in income inequality means there is a growing divergence across families in terms of resources that parents can devote to their children.

 

 

  • Money matters. Parents’, and particularly single mothers’, access to well-paying work has real impacts on child outcomes through a variety of mechanisms. Perhaps most significantly, access to quality childcare is highly dependent on income.

 

 

  • The level of stress among parents due to juggling work and family responsibilities has a direct effect their child’s development.

 

 

  • Most working parents have limited or no access to work-family policies such as workplace flexibility, paid leave, and paid sick days and those who do are more likely to be from higher income families. These policies help parents address conflicts between work and home, with real implications for parenting and children’s outcomes.

 

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All of these factors have a direct impact not only on the future human capital available in our country, but also, by extension, the productivity of our economy in the decades ahead.A key conclusion of this paper is that we need to better understand the links between developing our children’s human capital and the quality of their parents’ jobs, including wages, the ability to have some control or flexibility on hours or scheduling, and the stress that they experience and bring home from work. One thing is very clear: our future economic competitiveness depends on getting this right.

 

1      Almond, Douglas, and Janet Currie. Human Capital Devel- opment Before Age Five. NBER Working Paper. Cambridge, MA: National Bureau of Economic Research, 2010. http:// www.nber.org/papers/w15827.pdf.

2      National Scientific Council on the Developing Child. Excessive Stress Disrupts the Architecture of the Developing Brain. Working Paper. Cambridge, MA: Harvard University, Center on the Developing Child, June 2009; Strazdins, Lyndall, Megan Shipley, Mark Clements, Léan V. Obrien, and Dorothy H. Broom. “Job Quality and Inequality: Parents’ Jobs and Children’s Emotional and Behavioural Difficulties.” Social Science & Medicine 70, no. 12 (2010): 2052–60. doi:10.1016/j.socscimed.2010.02.041; Kalil, Ariel,and Ziol-Guest, Kathleen M. “Single Mothers’ Employment Dynamics and Adolescent Well-Being.” Child Development 76, no. 1 (2005): 196–211.

3      U.S. Bureau of Labor Statistics. “Table 32. Leave Benefits: Access, Private Industry Workers, National Compensation Survey, March 2013.” U.S. Department of Labor, 2013. http://www.bls.gov/ncs/ebs/benefits/2013/ownership/ private/table21a.pdf.

4      Glynn, Sarah Jane. Working Parents’ Lack of Access to Paid Leave and Workplace Flexibility. Washington, DC: Center for American Progress, November 2012. http://cdn. americanprogress.org/wp-content/uploads/2012/11/ GlynnWorkingParents-1.pdf.

5      Williams, Joan C., and Heather Boushey. The Three Faces of Work-Family Conflict: The Poor, the Privileged, and the Miss- ing Middle. Washington, DC: Center for American Progress and the Center for WorkLife Law, University of California, Hastings College of the Law, 2010.

6      Dodson, Lisa, Tiffany Manuel, and Ellen Bravo. Keeping Jobs and Raising Families in Low-Income America: It Just Doesn’t Work. Radcliffe Institute for Advanced Study, 2002.

7      DeLong, J. Bradford, Claudia Goldin, and Lawrence Katz. “Sustaining U.S. Economic Growth.” In Agenda for the Nation, edited by Henry J. Aaron, James M. Lindsay, and Pietro S. Nivola. Washington, DC: The Brookings Institution, 2003; Mankiw, N. Gregory, David Romer, and David N. Weil. “A Contribution to the Empirics of Economic Growth.”The Quarterly Journal of Economics 107, no. 2 (1992): 407–37; Barro, Robert, and Jong-Wha Lee. “Educational Attainment in the World, 1950-2010.” Vox, 2010. http://www.voxeu.org/index.php?q=node/5058.

8      Organization for Economic Co-Operation and Development. PISA 2012 Results: What Students Know and Can Do: Student Performance in Mathematics, Reading and Science (Volume I). Revised edition. OECD Publishing, 2014. http://www.oecd.org/pisa/keyfindings/pisa-2012-results- volume-i.htm.

9      Heckman, James J., and Lakshmi K. Raut. Intergenerational Long Term Effects of Preschool – Structural Estimates from a Discrete Dynamic Programming Model. NBER Working Paper. National Bureau of Economic Research, May 2013. http://www.nber.org/papers/w19077.

10   On the importance of later interventions, see, for example: Heller, Sara, Harold A. Pollack, Roseanna Ander, and Jens Ludwig. Preventing Youth Violence and Dropout: A Randomized Field Experiment. Working Paper. National Bureau of Economic Research, May 2013. http://www.nber.org/papers/w19014.

11   Heckman, James J. Schools, Skills, and Synapses. Working Paper. National Bureau of Economic Research, June 2008. http://www.nber.org/papers/w14064.

12   Boushey, Heather. “The New Breadwinners.” In The Shriver Report: A Woman’s Nation Changes Everything, edited by Heather Boushey and Ann O’Leary. Washington, DC: Center for American Progress, 2009.

13   Mishel, Lawrence, Josh Bivens, Elise Gould, and Heidi Shierholz. “Table 2.18 – Annual Hours Worked by Married Men and Women Age 25-54 with Children, by Income Group, Select Years, 1979-2010.” In The State of Working America, 12th ed. Ithaca, NY: Cornell University Press, 2012; Glynn, Sarah Jane. The New Breadwinners: 2010 Update. Washington, DC: Center for American Progress, 2012.

14   Piketty, Thomas, and Emmanuel Saez. “Income Inequality in the United States, 1913–1998.” The Quarterly Journal of Economics 118, no. 1 (February 2003): 1–39.

15   See: Saez, Emmanuel. Striking It Richer: The Evolution of Top Incomes in the United States (Updated with 2012 Preliminary Estimates). Berkeley, CA: University of California – Berkeley, September 2013. http://elsa.berkeley. edu/~saez/saez-UStopincomes-2012.pdf; Mishel, Lawrence, Josh Bivens, Elise Gould, and Heidi Shierholz. “Figure 4H – Cumulative Change in Real Annual Wages, by Wage Group, 1979-2010.” In State of Working Amer- ica, 12th Edition. Ithaca, NY: Cornell University Press, 2012. http://www.stateofworkingamerica.org/chart/ swa-wages-figure-4h-change-real-annual-wages/.

16  Schmitt, John, and Janelle Jones. Bad Jobs on the Rise. Washington, DC: Center for Economic and Policy Research, September 2012. http://www.cepr.net/docu-ments/publications/bad-jobs-2012-09.pdf; Schmitt, John, and Janelle Jones. Making Jobs Good. Washington, DC: Center for Economic and Policy Research, April2013.  http://www.cepr.net/documents/publications/good-jobs-policy-2013-04.pdf; Williams, Joan C., and Heather Boushey. The Three Faces of Work-Family Conflict: The Poor, the Privileged, and the Missing Middle.

How important is the college wage premium to reducing inequality?

Posted on by Marshall Steinbaum

The college wage premium—the difference between average earnings among those with a college (but no graduate) degree and those who do not attend college—has increased substantially in recent years while the premium for those who attend “some college” without actually earning a degree has not changed at all. This fact leads many observers to conclude that a college degree is the best way for young adults to attain the skills they need to earn more and thus reverse growing inequality. (See Figure 1.)

Figure 1

college-wage-col

This view, however, has serious problems. The idea that not enough people are graduating from college implies that the much-reported rise in income inequality is thanks to a “shortage” of highly skilled college grads able to meet the labor market’s need. That idea has been conclusively debunked. The fact that the wage premium only kicks in when a college student receives a diploma, rather than gradually appearing in the cross section of people who go to college for one, two, or three years but don’t earn a degree, casts serious doubt on the idea that it’s the skills content of college that matters. Furthermore, the fact that buying an expensive degree correlates with high income certainly doesn’t imply that causation runs from buying the expensive degree to the high income.

So where in the academic literature did this notion of the four-year college degree as the solution to labor market inequality arise? The idea that the college wage premium reflects a rise in the labor market’s demand for skills stems in large part from a 1992 paper by Harvard University economist Lawrence Katz and University of Chicago economist Kevin Murphy, who argued that since there’s been both a rise in the college wage premium and a rise in the proportion of the population with college degrees, demand in the market for skilled labor has increased against a somewhat elastic but essentially unchanged supply curve.

Along similar lines, Katz and another Harvard professor Claudia Goldin, published a paper in 2007 that tracks the college premium over the long run and posits that its dynamics are explained by the race between education and technology. They argue that “skill-biased technological change” creates a demand for college degrees that takes time to be reflected in the skill composition of the workforce.

The story about the race between education and technology leaves questions unanswered. First, it cannot explain the significant differences between the income distributions across countries, especially at the very high end. Technological change and the distribution of individuals’ skills seem to be uniform across countries, at least in the developed economies, and yet their income distributions are very different. For instance, the distributions of harmonized standardized test results for high school math students in the United States and France are basically the same, yet the top ten percent of income earners accrue 25 percent of total labor market income in France and 35 percent in the United States- and the shares are even more skewed higher up the distribution.

Second, the argument that increasing inequality is caused by a shift in the demand for scarce skilled labor is only theoretical: it’s not at all clear where that technological change comes from. Every attempt to operationalize the theory of skill-biased technological change has run up against problematic data. Since the late 1990s, most of the increase in the college wage premium (which has not grown much during the last fifteen years) is due declining absolute wages for those with less education. That is the exact time period in which the “IT revolution” is supposed to have had a wide impact on experience of the middle class in the labor market. And it has had an impact—on the industrial mix of workers, but not on their wages. If there is a race between education and technology, currently the runners are tied: both supply and demand for skills have shifted such that wages are unaffected.

The potential harm in misattributing rising income inequality to a race between education and technology — a race that technology is winning — is that it could lead to perverse policy prescriptions. Trying to get more enrolled college students to undertake the cost of finishing their degrees might lead to yet further tuition hikes, especially if that route receives government subsidies, without significantly improving their outcomes in the labor market or reducing inequality overall.

 

Patterns of economic mobility in the United States

Posted on by Carter Price

“That dream of a land in which life should be better and richer and fuller for everyone, with opportunity for each according to ability or achievement regardless of the fortuitous circumstances of birth or position.”

—James Truslow Adams, “The Epic of America” (1931)[1]

The idea of the American Dream as defined by historian James Truslow Adams reflects a powerful cultural narrative with deep historical roots.[2] It also reflects the understanding that broad-based opportunity propels the economy forward. Adams wrote at a time when Horatio Alger’s nineteenth-century rags-to-riches tales were confronting the harsh realities of the Great Depression. This American Dream of upward economic mobility, though deferred for many women and people of color, became reality for many among the generation of Americans who came of age during the Depression and World War II and entered the workforce in the 1950s and 1960s, and for many of their Baby Boomer children, too. This drove productivity gains and strong economic growth, as people with talent and initiative were able to match their skills to jobs and economic opportunities.

Read a pdf of the full document

mobility-report-fig

Yet over the past decades, living the dream has seemed less likely for Americans following in their footsteps—those born into Generation X (1965-1980), the Millennials (1981-2000), and the so called Boomlet generation of the 21st century. Research suggests economic mobility in the United States as a whole has been essentially flat since the 1970s.[3] Although economic mobility may not have declined, income inequality has risen over that period, making the consequences of the ‘birth lottery’—the household a child happens to be born in—more stark.[4] Larger differences in income between people at the top and bottom of the income distribution are visible across the country, as are differences in perceived economic mobility. Understanding trends in levels of economic mobility is important to understanding what influences economic mobility, which in turn is important to understanding economic growth and stability.

The narrative that America was the best place for people to achieve a better life than their forebears, though once uncontroversial, was built at a time when reliable statistics were difficult to come by. Recent advances in data collection and more precise methodology allow us to examine how the United States measures up as a land of opportunity today.[5] Now we can ask ourselves whether the entire United States is a land of opportunity or a country where different lands of opportunity exist, depending on one’s geographic location or one’s place on the income spectrum.

In the pages that follow, we present the most recent research and data available on economic mobility, which we define as movement up and down the income ladder from one generation to the next. This report aims to explain recent scholarship on intergenerational economic mobility across the nation. Briefly, this research and data show that:

  • There are regional differences in economic mobility across the country.
  • Economic mobility nationwide has been roughly flat in recent decades, but it has not remained flat everywhere.
  • Economic mobility in the United States is lower than in many other developed economies.

We identify three sets of factors that are correlated with—though not necessarily causal determinants of—economic mobility: economic factors, social factors, and family factors. Economic factors are measures of economic well-being in an area. Social factors are a variety of measures of social cohesion and community activity. Family factors are various measures of family cohesion and structure. While there is more research to be done, this gives us ideas about what to pursue and where to look for answers. Researchers will need to explore these relationships further in order to identify the causal mechanisms driving levels and trends of economic mobility.

In this report, we first present terms related to economic mobility, before looking at how economic mobility varies across communities in the United States. We then examine how mobility has changed over time. Next, we look at factors that may influence mobility. Finally, we highlight a few questions for future research in this area.

Read a pdf of the full document

[1] James Truslow Adams, The Epic of America (Simon Publications, 2001).

[2] Ibid.

[3] Raj Chetty et al., Is the United States Still a Land of Opportunity? Recent Trends in Intergenerational Mobility, Working Paper (Cambridge, MA: National Bureau of Economic Research, January 2014), http://www.nber.org/papers/w19844.

[4] Ibid.

[5] Orsetta Causa and Asa Johansson, Intergenerational Social Mobility in OECD Countries (OECD, 2010), http://www.oecd.org/eco/growth/49849281.pdf.

Heritage Weighs into the Inequality Discussion with Some Problematic Data Analysis

Posted on by Ed Paisley

It is great that Heritage Foundation pundit Stephen Moore and The University of Ohio economic historian Richard Vedder are talking about economic inequality in the opinion pages of The Wall Street Journal, but they seem to have missed the mark. They correctly note that the states (and the District of Columbia) with the highest economic inequality, at least as measured by the Gini coefficient of income inequality, tend to also be “blue” states (those that tend to elect Democrats). They go on to argue Democratic policies are failing to reduce inequality.

This piece and its underlying data analysis have three fundamental flaws:

  • The Gini coefficient they are referencing is of income and does not factor in the effect of taxes or transfers. Thus, the measure they are using explicitly misses the impact of the policies that they claim are ineffective.
  • They are suffering from one of the cardinal sins of data analysis: omitted variable bias. More populous areas also tend to have higher inequality, at least in part because higher density allows for higher incomes. Furthermore, cities and urban areas also tend to elect more progressive leaders for a variety of reasons. Thus population density is the omitted variable. They fundamentally misunderstand (or at the very least ignore) the relationship between inequality and population density.
  • Finally, they are factually incorrect to say the 1980s and 1990s are emblematic of the very laudable notion that  “a rising tide lifts all boats.” As can be seen in the figure below, median hourly compensation has been essentially flat since 1970 despite the fact that per capita economic growth more than doubled over the same period.

 

productivity-compensation

It is certainly possible that they made these errors because they are neophytes to the inequality discussion, but it is important to correct them now so that these spurious claims do not propagate. Now that pundits from the Heritage Foundation are dipping their toes into the inequality discussion, I hope that they can bring some new and interesting policy ideas instead of misinformation and boilerplate rhetoric to the discussion.

Inequality: Making the Point

Posted on by Ed Paisley

Equitable Growth senior director Ed Paisley publishes a link to a response from The Brookings Institution’s Gary Burtless regarding a recent post by Equitable Growth research economist Marshall Steinbaum:

“In the essay that Marshall Steinbaum criticizes, I discuss findings by Professors Thomas Piketty and Emmanuel Saez showing that market income inequality has returned to the peak last seen in the 1920s. In my essay I do not criticize those findings. In fact, in previous writings I have strongly defended Piketty and Saez’s landmark research against criticisms by conservative commentators. Instead, my recent article makes two simple points.

“First, inspired by the recent publication of Piketty’s best-selling book, a number of people have described in a misleading way the implications of that book for the long-term trend in U.S. inequality. Many writers appear to misunderstand the limited concept of “inequality” that Piketty and Saez have estimated. Under a comprehensive income definition, inequality today is certainly below, and probably far below, its level in the 1920s.

“Second, contrary to a common claim advanced in many discussions of the Piketty-Saez estimates, real incomes of Americans in the middle and at the bottom of the income distribution have increased over the past 35 years. Although the growth in their incomes has fallen far short of the income gains enjoyed by the top 1%, it is simply wrong to say that all or nearly all U.S. income gains have been obtained by the top 1%.”

Read the entire post on The Brookings Institution’s blog Up Front.

 

Marriage promotion isn’t the only solution to America’s mobility problem

Posted on by Ed Paisley

We at the Washington Center for Equitable Growth and much of the economics blogosphere have given substantial attention to the recent work on mobility in the United States by Harvard economists Raj Chetty and Nathanial Hendren and University of California—Berkeley economists Emmanuel Saez and Patrick Kline. One of the study’s key findings is that there is strong, statistically significant relationship between the share of single mothers in an area and the gap in mobility between children from high- and low-income families (Chetty and his co-authors refer to this as a measure of relative mobility).

Brad Wilcox, University of Virginia sociologist and Director of the National Marriage Project, employs this finding to promote pro-marriage policies. His research on the issue is intriguing (though he bases his recommendations on regressions that suffer from multicollinearity, because all of the independent variables are highly correlated with each other, and thus his analysis is statistically questionable). His analysis may leave policymakers with the wrong message. When policymakers focus on marriage as the most important path to higher economic mobility, it allows them to ignore the pro-family policies that can help improve mobility. After looking at the data more deeply, I think they are drawing the wrong conclusions and should look at ways to support families of all types instead of pushing a specific family model.

My issue brief, “A Regional Look at Single Moms and Mobility,” indicates that the Pacific states of California, Hawaii, Oregon, and Washington stand out for having relatively high rates of single mothers while also having relatively high mobility. (See map) These states tend to have more family-friendly laws like paid sick days so that parents can take care of sick children and they have relatively generous parental leave so that new parents can spend more time with their newborn children. This analysis is far from definitive, but it does imply that these kinds of pro-family policies can improve mobility in the absence of a high rate of two-parent households.

States with Family Friendly Policies have Better Economic Mobility

A regional look at single moms and upward mobility

Posted on by Carter Price

One of the big takeaways from the recent work by Harvard economists Raj Chetty and Nathanial Hendren and University of California—Berkeley economists Emmanuel Saez and Patrick Kline is that differences in family structure are strongly associated with differences in economic mobility.[1] Some scholars and policymakers have used these findings as an opportunity to encourage marriage promotion policies, but a deeper look at the data raises some important questions.[2]

For example, why is it that the West Coast states of California, Oregon, and Washington stand out for having relatively high rates of single mothers while also having relatively high rates of economic mobility? Conversely, why are other parts of America characterized by low rates of single mothers but very low rates of economic mobility?

Understanding economic mobility can yield insights into whether and how economic inequality and economic growth are linked. And scholars and policymakers across academic disciplines and political divides agree that understanding how single mothers fare in our economy is critical to future economic growth, powered by their contributions today and the future contributions of their children.

Read a PDF of the full document
Read a PDF of the appendix

This issue brief explores where single mothers are more likely to be moving up the economic ladder, relying upon the latest research on mobility in the United States by Chetty and his colleagues.[3] One of their study’s key findings is that there is a strong, statistically significant relationship between a higher gap in mobility between children from high- and low-income families, which Chetty and his co-authors refer to as relative mobility, and a higher share of families headed by single mothers.

This insight enables us to look at this “mobility gap” in an area, compare the share of single-mother households, and then look at the difference between the share of single mothers and the mobility gap.[4] This difference tells us whether the mobility gap is higher, lower, or about what would be expected given the share of single mothers in an area. In the pages that follow, this issue brief will present these data analyses in more detail. But the upshot of this analysis is that states with more family friendly laws, [5] such as paid sick days so that parents can take care of sick children and relatively generous parental leave policies so that new parents can spend more time with their newborn children, are more likely to have a relatively high rates of economic mobility despite high rates of single mothers—among them California, Oregon, and Washington.

Conversely, parts of America, particularly parts of the Rust Belt, are significantly less mobile than one would expect given the relatively low share of households headed by single mothers. This analysis is far from definitive, but it does suggest that pro-family policies can improve mobility in the absence of a high rate of two-parent households.

Our first map in this issue brief tells the tale, at least for those born in the United States when the tail end of Generation X—1965-1980—gave way to the Millennials born between 1981 and 2000. (See Figure 1.)

Figure 1

States with Family Friendly Policies have Better Economic Mobility

Parsing the data on mobility and single mothers

These differences in the mobility of single moms that we mapped on Figure 1 can be further refined down to metropolitan regions of the country. Figure 2 below shows the relationship between the share of households led by single mothers and the gap in mobility between the children of high- and low-income families. Each dot represents a commuting zone (areas within which people are more likely to live and work). The arrow represents the “best-fit-line” on these points and indicates that places with a higher share of single mothers also tend to have a higher gap in mobility—indicating lower relative mobility. Because of the strength of this relationship, many commentators have identified marriage promotion as the silver bullet policy to improve economic mobility.

Figure 2

Single Mothers Struggle with Upward Mobility

While Figure 2 provides a pretty convincing picture that a higher rate of single motherhood is associated with a higher gap in mobility between children from high- and low-income families, there may be something missing. High- and low-income children born in large West Coast cities such as Seattle and San Diego have a much smaller gap in mobility than high- and low-income children born in cities such as Cincinnati or Indianapolis, despite having a similar share of single mothers. So before making sweeping policy proclamations, we should dig a little deeper to understand this relationship.

Figure 3 is a map of the mobility gap between the children of high- and low-income families. The mobility gap is the difference in incomes as adults between people born into the lowest-earning and highest-earning households. A lower ‘mobility gap’ implies greater mobility, and vice versa.[6] The lightly colored areas in the map are those that have a low mobility gap, while the dark green areas have a much higher mobility gap. The South and much of the Rust Belt have particularly low economic mobility, while the West Coast and many parts of the Great Plains states are particularly economically mobile.

Figure 3

How Hard is it to Climb the Ladder?

The mobility gap is an obviously useful measure of the chances of the children of families achieving the American Dream, but to complete our analysis presented in Figure 1, we need to calculate the share of single mothers in our nation. Figure 4 does that, with lightly colored places indicating an area in which a higher share of households are headed by single mothers than average for the country, while dark green indicates a lower share. The South and much of the West have higher shares of single mothers that the rest of the country, while the Great Plains states in particular have the lowest share of households led by single mothers.

Figure 4

Concentrations of Single Mothers

This brings us back to the first map in this issue brief. It looks at the difference between the actual mobility gap and what one would expect the mobility gap to be based only on knowing the share of single mothers. The brown indicates those places where you would expect mobility to be better given the relatively low share of households led by single mothers, while the green indicates those places where the mobility is better than you would expect given the high share of single mothers. The geographic distribution of the colors is telling. Table 1 details the states with the more long-standing family friendly policies.

Table 1

States with Longstanding Family-Friendly Policies

The West Coast states of California, Oregon, and Washington stand out for having relatively high rates of single mothers while also having relatively high mobility. Several New England states, among them Rhode Island, Maine, and Vermont, also have higher levels of mobility than would be expected given the share of households headed by single mothers. As seen in Table 1, these states tend to historically have had more family-friendly laws,[7] such as parental leave so that new parents can spend more time with their newborn children. This analysis is far from definitive, but it does imply that these kinds of pro-family policies can improve mobility in the absence of a high rate of two-parent households.

To look a little deeper into the relationship between mobility and marriage, we also did an international comparison akin to the famous Great Gatsby Curve.[8] Figure 5 has the intergenerational earnings elasticity (a measure of the variability in earnings for one generation that is associated with the variability in earnings from the previous generation.) from University of Ottawa economist Miles Corak[9] plotted against the share of children that live primarily with one parent using data from the OECD.[10]

At the international level, we find the opposite relationship between single parenthood and mobility that we see from data in the United States, as seen in Figure 2. While it appears that higher shares of children primarily living in single-parent households is weakly associated with lower intergenerational earnings elasticity, the United States is an outlier, and by excluding it from the calculations, the cross-country association is quite strong. This is almost certainly not an indication that single-parent households are better for mobility, but instead an indication that what matter are other differences between countries, such as public policy. Those countries that have a larger share of single mothers, other than the United States, also tend to do a much better job providing support services to families of all types.[11] (See Figure 5.)

Figure 5

The United States Compares Poorly in Economic Mobility

By comparing the maps of mobility with family structure and also seeing the international relationship, we see that those places with stronger support for families of all types appear to be less impacted by any adverse effect on mobility from having a high share of single mothers. This suggests that low mobility stemming from a high proportion of single-parent households may be largely a function of policy choices rather than an inherent characteristic associated with the prevalence of different family structures.

Conclusion

While none of this analysis constitutes definitive economic analysis, it does highlight areas for researchers to focus their efforts and also for policymakers to consider. Marriage promotion may be one possible policy solution to the low mobility in the United States, though evidence would be needed to show what it is about marriage that leads to higher economic mobility. But we may want to try what already appears to be working in some states and in other developed nations too.

The notion that low mobility is driven by family structure alone allows policymakers to ignore their role in the problem and implies solutions that ignore more fundamental economic and work-related problems. Thus, it is important for researchers to do more than just a cursory analysis of these data and to understand the mechanisms of mobility before making strong policy recommendations.

Endnotes

[1] Raj Chetty et al., Where Is the Land of Opportunity? The Geography of Intergenerational Mobility in the United States, Working Paper (Cambridge, MA: National Bureau of Economic Research, January 2014), http://www.nber.org/papers/w19843.

[2] W. Bradford Wilcox, If You Really Care About Ending Poverty, Stop Talking About Inequality, The Atlantic, January 8th, 2014,  http://www.theatlantic.com/business/archive/2014/01/if-you-really-care-about-ending-poverty-stop-talking-about-inequality/282906/

[3] Chetty et al, 2014.

[4] We used the residual from a regression of single mothers on the relative mobility as the difference.

[5] Waldfogel, Jane. 1999. “Family Leave Coverage in the 1990s.” Monthly Labor Review 10 (October): 13–21.

[6] Raj Chetty et al., Where Is the Land of Opportunity? The Geography of Intergenerational Mobility in the United States, Working Paper (Cambridge, MA: National Bureau of Economic Research, January 2014), pp.2-3, http://www.nber.org/papers/w19843.

[7] National Conference of State Legislatures, State family and Medical Leave Laws, December, 31st, 2013, http://www.ncsl.org/research/labor-and-employment/state-family-and-medical-leave-laws.aspx

[8] Alan Krueger, “The Rise and Consequences of Inequality” (Center for American Progress, January 12, 2012). http://www.whitehouse.gov/sites/default/files/krueger_cap_speech_final_remarks.pdf.

[9] Miles Corak, Inequality from Generation to Generation: The United States in Comparison, 2012, http://milescorak.files.wordpress.com/2012/01/inequality-from-generation-to-generation-the-united-states-in-comparison-v3.pdf.

[10] OECD, Living arrangements of children, OECD Family Database, January 7, 2010, http://www.oecd.org/social/family/41919559.pdf.

[11] Wikiprogress, Hours Worked, http://www.wikiprogress.org/index.php/Hours_Worked

Missing the Point on Income Inequality in the 1920s and Today

Posted on by Ed Paisley

Gary Burtless of the Brookings Institution takes issue with widely publicized findings that income inequality in the United States has reached the level that prevailed in the 1920s, when the top one percent of earners received 20 percent of total income. According to Burtless, that conclusion ignores the creation of the welfare state, consisting of Social Security, Medicare, Medicaid, and other government programs that aim to redistribute disposable income and goods and services to Americans in retirement and those at or near the poverty line. These programs did not exist in the 1920s, argues Burtless, so to ignore them is to misrepresent the degree of income inequality today. Columnist Robert J. Samuelson made the same argument in a column yesterday.

In support of that argument, Burtless turns to the Congressional Budget Office, which calculates measures of pre-tax-and-transfer “market” income, post-transfer income, and post-tax-and-transfer income. Specifically, Burtless turns to a report CBO published breaking down income in 2010. That report does show that taxes and transfers redistribute income relative to “the market,” meaning gross household income from labor, capital, rent, royalties, and miscellaneous non-government sources.

But this CBO analysis doesn’t provide crucial context—the extent to which the redistribution of income through tax policies and government spending has declined since 1979. I discussed this last week, largely in reference to an earlier CBO report that explicitly tracks the trends in pre- and post-tax-and-transfer income distributions. The data needed for that analysis doesn’t extend back to the 1920s, but Burtless is likely correct that since there was far less in the way of redistributive government policy back then, the post-tax-and-transfer distribution then was more stratified than it is now.

But this line of argument neglects that between the 1920s and today income became much less stratified, thanks to higher effective taxes on the very wealthy that helped pay for the New Deal and Great Society progressive programs enacted in the interim—policies that resulted in sustained and stable economic growth, unlike what prevailed before or after. Since the advent of supply side economics in the 1980s, of course, tax policies have become less redistributive in percentage terms exactly as market income has become more unequal, and transfer programs have shifted their focus toward the elderly of all income levels and away from the poor.

The upshot: the potential for policies to rectify income inequality and boost economic growth is very high, which by itself invalidates long-term conservative arguments that government is powerless or ineffective in the face of “the market’s” inexorable force. Burtless’ claim is correct, but some conservative critics of the latest research on income inequality are using the welfare state they previously devoted themselves to dismantling to support their argument that inequality either doesn’t really exist or is at least not as bad as in the 1920s.