Morning Must-Read: Tony Yates: John Taylor the Republican Contradicts John Taylor the Economist

The question as to whether one actually believes the models one teaches, and tries to apply the principal conclusions that follow from them, or regards them as ritualistic incantations to be dropped as soon as they contradict one’s ideological instincts or the preferences of one’s political masters… this is more and more coming to seem to me to be a key issue:

Tony Yates (2013): John Taylor the Republican Contradicts John Taylor the Economist: “John Taylor… [says] we would be better off…

…with tighter monetary policy, and greatly tighter fiscal policy. And the other smoking guns causing the crisis (lax regulation, global imbalances, irrational exuberance, politically motivated lending to subprime borrowers, etc) were a sideshow…. Taylor’s remarks sounded like a classic Republican critique of monetary and fiscal policy… objected to QE, fearful that it would stoke up inflation… objected to the stimulus package because it went against their preference for small government. But this Republican critique flies in the face of Taylor’s… work took on the causes of the business cycle, what monetary policy can do about it, and, by very close analogy, what fiscal policy can do too…

Morning Must-Read: Kevin J. Lansing and Benjamin Pyle: Persistent Overoptimism about Economic Growth

Kevin J. Lansing and Benjamin Pyle: Persistent Overoptimism about Economic Growth: “Since 2007, Federal Open Market Committee participants…

…have been persistently too optimistic about future U.S. economic growth. Real GDP growth forecasts have typically started high, but then are revised down over time as the incoming data continue to disappoint. Possible explanations for this pattern include missed warning signals about the buildup of imbalances before the crisis, overestimation of the efficacy of monetary policy following a balance-sheet recession, and the natural tendency of forecasters to extrapolate from recent data.

The early origins of the gender pay gap

One of the more remarkable and discouraging facts about the U.S. economy is that even while women have increasingly entered the workforce, they still make less than comparable men on a variety of metrics. Even though women now outnumber men in college, there is still a difference in earnings. Part of this gap is because men are more likely to study in high-paying fields such as math, science, and various technology fields. But why does this gap exist?

A new study argues that gender biases early in a child’s education may be a root cause.

Economists and sociologists already know a lot about gender bias in the workforce, of course. A variety of earlier economic studies showed how gender biases, even unconscious ones, can result in unequal work outcomes. Consider a paper published in 2000 by Harvard University economist Claudia Goldin and Princeton University economist Cecilia Rouse. They looked at how gender biases might affect auditions for seats in a symphony orchestra. Goldin and Rouse found that making the audition blind by having the musician play behind a screen resulted in the hiring of many more female musicians. The orchestra staff appeared to have an unconscious bias against female applicants.

The new paper, by economists Victor Lavy and Edith Sand of the University of Warwick and Tel Aviv University, respectively, looks at how this kind of bias from teachers might affect the future educational path of students. Specifically, they look at the implicit gender biases of primary school teachers. Lavy and Sand have access to a data set from Tel Aviv, Israel that tracks the progress of students from primary, or elementary school, all the way through high school. This way they can see how events from primary school affect a student’s educational trajectory.

The authors measure gender bias by looking at the difference between two tests that students take on math and language skills. One test is external and graded by an outside evaluator. This person has no information about the student’s identity, including his or her gender. The other test is internal and graded by the student’s teacher who knows quite a bit about the student. Lavy and Sand take the difference between the two test scores, which cover very similar areas, as a measure of gender bias.

Lavy and Sand find that these gender biases do exist and they have long-term effects. Male students that had more biased teachers do better on standardized tests later in their schools years. And the opposite happens for female students: they will do less well. And the effects aren’t just limited to test scores. Boys with biased primary school teachers are more likely to take math classes in high school and girls are less likely. Considering that these courses serve as a base for further course in math and science, this could explain future gaps. The authors show a strong correlation between test scores and future earnings.

And the effect is larger for certain kinds of students. In particular, girls that come from a family with a large difference in education levels are more affected by the early gender bias. In other words, if a girl’s father is more educated than her mother, she’ll be more affected by the gender bias of an early teacher.

The direct applicability of this study in terms of its exact findings to other countries or even other cities in Israel is debatable. But given the other research on the extent of implicit gender biases in the United States, the broader point of the paper could very likely hold up. And this would mean that actions early in a student’s life can affect not only their adult experiences but the overall economy if gender biases distort the allocation of potential scientists and engineers. In other words, the economy might miss out on a great scientist.

Research shows again and again that the quality of education and other factors early in a child’s life can affect their outcomes later in life. Lavy and Sand’s findings are another indication that early life circumstances need rapt attention.

The Rise in Inequality: The Honest Broker

Event – Income and Wealth Inequality in the United States: Evidence, Causes and Solutions | Rice University’s Baker Institute:

The policy debate on the sources, causes and potential solutions to rising income and wealth inequality has intensified in the past few years. Recently, French economist Thomas Piketty’s popular book ‘Capital in the Twenty-First Century’ garnered much attention and ignited further debate about these issues. Piketty argues that wealth will inevitably become more concentrated under capitalism because the returns to wealth are larger than economic growth rates. The solution he proposes is a coordinated global tax on wealth. The Baker Institute’s Tax and Expenditure Policy Program will host two renowned economists to discuss the underlying causes and consequences of inequality, evaluate the empirical evidence of rising inequality, and examine potential solutions for dealing with these problems in the United States.

  • WELCOME AND INTRODUCTION: John W. Diamond, Ph.D., Edward A. and Hermena Hancock Kelly Fellow in Public Finance, Baker Institute
  • PANELISTS
    • R. Glenn Hubbard, Ph.D.: Dean and Russell L. Carson Professor of Finance and Economics, Columbia Business School
    • J. Bradford DeLong, Ph.D.: Professor of Economics, University of California, Berkeley
  • MODERATOR: George R. Zodrow, Ph.D., Allyn R. and Gladys M. Cline Chair of Economics; and Baker Institute Rice Faculty Scholar.

As prepared for delivery:

The Rise in Income and Wealth Inequality: Evidence, Causes, and Solutions

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J. Bradford DeLong :: U.C. Berkeley, NBER, WCEG, INET :: February 3, 2015 :: http://tinyurl.com/dl20150202a

I am very happy to be here, especially as Texas is a state I get to relatively rarely. I have unusually few relatives in it, you see. When the DeLongs got to Wichita they decided to turn north rather than south and wound up in DeKalb County, Illinois. And those who did end up here decamped to North Carolina, leaving me with none until last year when my cousin Annie and her husband moved to Dallas. The last time my wife and I spent any extended time in Texas was on our honeymoon, when we were washed out of our campsite in a swamp near the Louisiana border by a midnight mid-June thunderstorm, so we bypassed Galveston and Houston and then spent a week and a half going Austin-San Antonio-Permian Basin-El Paso.

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We are here today because of a problem in the American economy, a problem that emerged back at the end of the 1970s. Since 1980 our rate of productivity growth in the American economy has been little more than half what it was before. Americans used to expect living standards in the country to double every generation. Not since 1980. in fact, standards of living at the median–with half the workers above and half the workers below–pretty much stopped growing around 1980 and are still stuck.

Now you can and probably should paint a more optimistic picture of how the American economy has done since 1980 then the standard rapidly growing wealth at the very top and stagnation everywhere else. Women are much better off economically with the decline in discrimination–if, that is, work burdens both outside and inside the household are fairly shared.

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African Americans are better off economically with the decline and discrimination–although the overwhelming proportion of the African-American population has been caught up in the negative parts of broader trends. Our standard indices of what prices really are are biased upwards by about an extra half a percentage point per year which means that our standard indices of real incomes are biased downward by about the same amount. And the value each of us receives from what the buy is greater than its price–if it were not, we would not buy it. For information-type virtual goods the ratio of true user value to market price is bigger, and as more of our economy shifts the information goods this factor pays an extra dividend. Plus how people live is different from what they receive an income because of progressive taxes and the safety net.

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Nevertheless:

2/5 of the measured productivity growth we reasonably expected back in the late 1970s that we would have seen by now in the American economy is simply not there.

Effectively all of the growth and measured living standards at the median of the population that we reasonably expected we would have seen by now is simply not there.

And that is a big problem–at least, that is a big problem if you believe in American exceptionalism an American progress.

Why has productivity growth done so much worse than previous generations? That is not a topic for tonight: and if he were to start there, we could never get anywhere else.

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Why has the median done so much worse than the average since the late 1970s? Arithmetically, it is not because the bottom has caught up via some leveling process but because the top has leaped ahead. America’s best educated, best positioned, and most fortunate tenth looks no better educated or entrepreneurial relatively speaking now then its predecessor did in 1980. Yet it receives half of all income now while it only received one-third of all income then. That is what is given us a lower 85% little better than stagnant since 1980 in their real incomes, and 85th percentile to 95th percentile upper-middle-class with incomes growing roughly with economy wide productivity, and with an upper-class of households–a fortunate twentieth–with their incomes outstripping everyone else’s. The incomes of the top 1% slots in the distribution are the only ones to have grown faster since 1980 then before–economy why productivity +3% growth and income as per year for the top 1%.

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And by the time you get up to the top 0.01%–The richest earning 260 households in Houston, in the rarefied air that only 1300 households now in Houston will ever breathe at any point in their lives–well, the incomes of those 260 start at $7 million a year and average $50 million a year. Back in the late 1970s would have started at, in today’s prices, $900K and averaged $6M. Fur people in that slice, The past generation has been a wonderful era of the American dream coming true.

What has happened has not been a tilting of the income distribution as globalization or the race between education and technology shifts the skill and education premium. What has happened, instead, has been a great hollowing out.

Below the 80%-ile–below roughly $90,000/year in household income–the slots in the distribution have had a hard time holding their own in real terms. Above that we have an upper middle class–from the 80% to the 95%-ile, with household income in the $90-$160,000/year level-—where the slots are more or less holding its own in relative terms and with income levels rising at the rate of growth of productivity.

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And above that we have:

  • At the 99%-ile, income from 1978-2013 up from $200 to $375,000/year.
  • At the 99.9%-ile, up from $500,000 to $1,400,000/year.
  • At the 99.99%-ile, up from $900,000 to $7,000,000/year

Why has this happened?

Why the enormous surge in wealth at the top and relative disappointment and stagnation everywhere below the upper-middle-class? 15 years ago when we talked about rising inequality we talked about the decision in the 1970s to stop increasing relative spending on public higher education. We talked about how thereafter technology kept creating more high-skill jobs and removing low-skill jobs and so college graduates and the well-trained found themselves in a sellers’ market and others in a buyers’.

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Add onto that globalization, plus something title weird going on at the very top, and we thought we had a handle on it. We did not. The lion’s share of the gains are not being distributed in proportion to education or skill, but simply to those at the top.

There are a bunch of hypotheses. Larry Summers likes to muse on how George Eastman and Steve Jobs were both master technologist entrepreneurs, but one’s inventions supported middle-class prosperity in Rochester for decades, while the other’s created a few Silicon Valley millionaires. Some point to the decline of the union movement: it used to be overpaying your executives handed the UAW a powerful organizing tool, hence George Romney lived in a “normal” house, albeit in Grosse Point.

I tend to focus on the rise of finance–from 3% to 8% of total incomes, a very steeply-peaked sector indeed, and yet does the increase in the share of income it receives reflect anything more than modern high finance is much better at convincing individual middle-class investors and trustees of pension funds to take risks that they shouldn’t?

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I tend to focus on the extra 5% of total income we spend on health care that other countries with health-care systems that outperform ours do not–and how much of that money flows to those who have gotten legislatures to bar nurse-practitioners from offering to treat their patients and who have figured out that the way to really make money in health is to collect insurance premiums and then figure out a way not to pay for the treatment of sick people, for sick people are expensive. I tend to focus on how with falling marginal tax rates and much higher pay levels for financiers who top executives regard as their peers, it is much much harder for directors and bosses who are part of the same social networks as bosses and immediate reports to hold the line, especially in the interest of shareholders given our well-known and longstanding flaws in corporate governance.

And then there are the hypotheses that suggest that rising inequality is relatively benign. There is the focus on winner-take-all information-goods industries. Fifty years ago it would have really raised the quality of life of three women to have been able to spend their afternoons hanging out laundry and gossiping with Oprah Winfrey over the back fence. In today’s world she manages to talk to not three people over the fence but to millions via the TV, and to turn her skill into a job, and to make $3 billion. That’s a big plus.

Back at the end of the 1970s it was promised that we would get better corporate governance and more time and energy devoted to invention and production management and less to tax avoidance if we lowered tax rates. We lowered them. But the productivity-growth benefits that were expected–well, I cannot see them in the data, and the only people who can are those with much more faith than St. Thomas ever had. And the argument that entrepreurship can only be spurred by the hope of a few very big prizes–well, Glenn Hubbard’s successor Greg Mankiw in the George W. Bush administration points to Steven Spielberg, Steven Jobs, and J.K. Rowling–all of whom would have been extremely happy to work like the dogs they worked like for 1/100 of the compensation.

Thinking about policies to remedy the situation is very difficult if we do not have a secure diagnosis of the causes of the problem, and we do not have a secure diagnosis of the causes of the problem. But I can say that making our income tax and our safety-net transfer system less progressive is not a rational policy reaction to the market economy’s having become a more unequal place.

And then there is the possibility that it is the old America, the America from 1933-1979, that was the anomaly. America before 1880 is the free-land America of the frontier, but as the frontier closed and the Gilded Age began income and wealth inequality rapidly became like it was today. Perhaps it is not what is going on now that is unusual, but what went on in the shadow of the Great Depression and the New Deal.

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That is certainly what Thomas Piketty thinks. He points out that, historically:

  1. Wealth is nearly always highly concentrated.
  2. The era of wars, revolutions, progressive taxes, depressions, and social democracy that began in the 1910s quickly saw economy-wide wealth-to-annual-income ratios in the North Atlantic fall from about 7 to about 3.
  3. And now it simply looks like we are going back to the old pre-World War I Belle-Époque Gilded-Age pattern.

Now this might be a benefit for the rest of us. After all, if the rich are rich because their ability to compound wealth is undisturbed, then they have to invest their wealth in something. And if they invest their wealth in useful buildings and productive machines, well then the rest of us who want to rent those buildings and work in businesses equipped with those machines find that we are in a buyers’ market: our wages go up, interest rates and dividend yields go down, and we have what John Maynard Keynes called the euthanization of the rentier, as the super-rich have immense wealth but because of low rates of profit derive only modest incomes from it.

It’s possible. But, as Thomas Piketty points out, when we look in history for the negative relationship between wealth-to-annual-income ratios and rates of return, we do not find it. Societies in which the rich are richer in relative terms appear to be societies in which the political-economic system is tuned to protect the profits of the rich as well.

So perhaps our grandchildren’s destiny will be to live in a world once again like that of Jane Austen or Honoré de Balzac–one in which marrying well after choosing the right parents are the roads to success as the world measures it…


The Rise in Income and Wealth Inequality: Evidence, Causes, and Solutions

The Problem

  • Americans used to expect living standards to double every generation…
  • That stopped at the end of the 1970s—productivity growth halved…
  • And stagnant real hourly median compensation tells us standards of living at the median stopped growing much, if at all…

Things Wrong with This Graph

  • Misses decline in discrimination against women…
  • Misses decline in discrimination against African-Americans…
  • Denominator in real compensation still mostly a price index rather than a cost-of-living index (bias of 0.5%/year?)…
  • Misses consumer surplus…
    • A lot more consumer surplus from “information goods” than from physical commodities…
  • Misses progressive taxes
    • Misses safety net

Nevertheless…

  • 2/5 of the total productivity growth we reasonably expected back in the late 1970s to see by now is not there…
  • Effectively all of the growth in measured living standards at the median we expected to see is not there…

Why Has the Median Done so Much Worse than the Average?

  • Arithmetically, top 10% up from 34% to 50%…
    • Reduction in 90% share by 1/4—from 2/3 to 1/2—accounts for the median…
    • Lower 85% little better than stagnant…
    • 85-95% growing with productivity…
    • 95-99% at productivity +0.8%/year…
  • Top 1% at productivity + 3.0%/year—better than pre-1980…
  • These are incomes of slots, not of people

And Look at the Top 0.01%

  • From 1% to 5%…
  • From 100 to 500 times average…
  • 13,000 households at any point in time…
    • 260 households in Houston…
    • 1300 households now in Houston will make it there at some point in their lives…
    • Average income $50 million/year…
      • Back in the late 1970s their then-counterparts averaged $6 million/year…

What Has Happened?

  • A “hollowing out”:
    • Below 80%—below $90K in household income—roughly holding its own in real terms…
    • An upper middle class—80%-95%, household income, $90K-$160K/year—holding its own in relative terms…
    • At the 99%-ile, income from 78-13 up from $200-375K/year…
    • At the 99.9%-ile, up from $500K-1.4M…
    • At the 99.99%-ile, up from $900K-$7M…

Why Has This Happened?

  • Used to think:
    • Race between education and technology…
    • Plus “globalization”…
    • With something weird but less important going on at the top and the very top…
  • That’s much harder a belief to hold on to now,
    • The lion’s share of the gains aren’t going to the educated, but to the top…

Hypotheses…

  • Negative:
    • Something to do with the character of “technology”?
      • Kodak vs. Facebook
    • Decline of “union threat”:
      *It used to be that overpaying your boss gave your unions an excellent organizing tool…

      • George Romney lived in a “normal” house in Grosse Point…
    • Rise of finance: from 3% to 8% of total income…
    • Rise of health-care excess: another 5% of total income…
    • NIMBYism/congestion…
    • “Because they can”—lowered marginal tax rates, could afford to…
  • Positive:
    • The rise of winner-take-all information-goods industries:
      • Oprah Winfrey, estimated net worth $3B, as America’s best friend…
    • Beneficial spur for innovation:
      • Greg Mankiw’s faux pas: “Steve Jobs as he develops the iPod, J.K. Rowling as she writes…Harry Potter… or Steven Spielberg as he directs…”
    • It didn’t work: we haven’t gotten faster productivity growth or better corporate control as a benefit of the 1980s reduction in marginal tax rates…
  • Worrisome:
    • Great Depression and after as an unusual and anomalous era—it’s not what is going on now that is unusual, it is 1933-1979…

Thomas Piketty’s Take

  • Wealth nearly always concentrated…
  • Wealth-to-income falls from 7x to 3x annual income…
  • Now it is simply going back…
  • Will this be a bonanza for the rest of us? Keynes’s euthanasization of the rentier?…
    • No: wealth is very good at protecting itself and its returns…
  • Your grandchildren will live, once again, in a world in which marrying well and choosing the right parents are the roads to success as the world measures it…

2920 words

The economic and fiscal consequences of improving U.S. educational outcomes

This new study addresses a key challenge confronting the United States—how to promote both widely shared and faster economic growth. It does so by analyzing and describing the effects of raising educational achievement, especially for those not at the top of the economic ladder. The results of the analysis demonstrate that improving the education of future workers accelerates economic growth and can promote more equal opportunity over the long run. This interactive below enables readers to explore the ramifications of the study swiftly and tellingly.

Download a pdf of the overview.
Download a pdf of the “Fast Facts”.
Download a pdf of the methodology.
Download a pdf of the full report.

Methodology

The results of the literature on the effects of cognitive skills on economic growth are used to estimate the increase in the U.S. gross domestic product and tax revenues that would result from narrowing or closing the educational achievement gap between children from advantaged and disadvantaged family backgrounds.

A growing body of research uses cognitive skills, as reflected in international test scores, as a measure of human capital. This research suggests that human capital accounts for a significant portion of the economic growth of economically advanced nations. The results of regression analyses conducted by Eric A. Hanushek and Ludger Woessmann found statistically significant and strong effects of cognitive skills—as measured by the internationally administered PISA test scores—on the economic growth of 24 nations in the Organization for Economic Co-Operation and Development from 1960 to 2000. Specifically, Hanushek and Woessmann (2010) found that “an increase of one standard deviation in education achievement (i.e., 100 test-score points on the PISA scale) yields an average annual growth rate over 40 years that is 1.86 percentage points higher.”

Three simulations using the Hanushek and Woessmann regression estimate, one for each of three scenarios, are done to project the economic impact of closing or narrowing the educational achievement gaps between children from socioeconomically advantaged and disadvantaged families. The projection models follow closely the model developed by Hanushek and Woessmann in 2010, though several adjustments are made to account for factors specific to this study, such as the incorporation of estimates of future impacts on federal, state, and local government revenues. For all three scenarios, the 2012 U.S. PISA test scores in math and science are used as the baseline in the analysis.

We assume that the estimated impact of the PISA test scores on economic growth is causal, meaning that any policy that increases the test scores of students will result in faster economic growth. For the interested reader, Hanushek and Woesmann (2009) provide evidence that the association between cognitive skills—as measured by the PISA test scores—and economic growth is indeed casual and reflects the effects of cognitive skills on growth. They use a variety of instrumental variables to test causality, use a difference-in-differences approach to compare country of origin-educated to U.S.-educated immigrants, and test whether countries that have improved their test scores have experienced commensurate growth rate improvements.

All three of our simulation scenarios use the PISA index of economic, social, and cultural status, or ESCS, to differentiate advantaged from disadvantaged families. The PISA index of economic, social and cultural status is based on the highest level of parental education, parental occupation, an index of home possessions related to family wealth, educational resources available in the home such as the number of books, and possessions related to culture such as works of art in the home. We follow the OECD practice of defining students as socioeconomically advantaged if they are among the 25 percent of students from families with the highest PISA index of social, economic, and cultural status in their country. The parents of socioeconomically advantaged students have higher educational attainment and work in higher skilled jobs than do the parents of other children. More advantaged students have more books and educational resources, such as desks, dictionaries, computers, and Internet connections at home. Their homes also have more material possessions such as cars or rooms with a bath or shower.

Children from the most advantaged quartile of families scored an average of 532 on the math test, while children from the most disadvantaged three quartiles of families scored (in descending order by quartile) 494, 462, and 442, respectively. On the science test, children from the most advantaged top quartile of families scored 548 while children from the most disadvantaged bottom three quartiles scored 511, 480, and 456.

The first scenario assumes that the scores of children from the most disadvantaged bottom 3 quartiles of families are increased only enough to raise the average U.S. math and science scores to match the OECD average scores. Specifically, the difference between the average OECD math and science scores and the U.S. average math and science scores is calculated. For both math and science, the OECD-U.S. average score difference is divided by three quarters and the result is then added to the average score of students in each of the bottom three quartiles of the ESCS index. The math and science scores of the top quartile are assumed to remain constant.

The national average PISA math and science test scores are then recalculated for the nation as a whole. Aside from raising the combined math and science average U.S. score from 978 to 995 so that it matches the OECD average score, this scenario also narrows the achievement gaps between children from the most advantaged and most disadvantaged quartiles by approximately 13 percent. The average test score for the nation rises by 13 points in math and 4 points in science. The 13-point improvement in math and the 4-point improvement in science represent an increase of 0.09 standard deviations on the combined average score.

The second scenario raises the math and science scores of each quartile (by socioeconomic status) of U.S. students to match the math and science scores of Canadian students. This raises the combined average U.S. math and science scores from 978 to 1,044. It also improves the scores of the bottom three quartiles of students more so than for the top quartile of U.S. students, thereby narrowing gaps. The 66-point improvement in the combined math and science average test score is roughly an increase of 0.37 standard deviations on the combined score.

The third scenario assumes that the PISA test scores for children from the most disadvantaged bottom 3 quartiles of families are raised to equal the scores of children from the most advantaged quartile of families. In other words, the achievement gap between advantaged and relatively disadvantaged children is completely eliminated. The average PISA math and science test scores are then recalculated for the nation as a whole. This raises the combined average math and science score to 1080, which represents an increase of 0.54 standard deviations on the combined average score.

To assess the “reasonableness” of PISA test score increases of the sizes assumed in the three scenarios, the history of PISA test score increases was reviewed. Unfortunately, the PISA tests have only been administered at three-year intervals for a dozen years starting in 2000, and tests results have only been standardized and made comparable for the nine-year period between 2003 and 2012. This makes it difficult to compare actual increases in PISA scores to those in the three scenarios which take place over a longer time period: 20 years.

Nonetheless, several nations have experienced PISA test score increases that exceeded those of scenario one and roughly equaled those of scenario two. Germany and Italy, for example, experienced 33 and 27 point increases, respectively, in their combined average math and science score between 2003 and 2012, far exceeding the 17-point increase assumed in scenario one and roughly matching the annual 3.3 point-increase assumed in scenario two, although short of the 66-point total increase. Poland’s 6.3-point annual increase in its combined average math and science score between 2003 and 2012 is greater than the 5.1-point annual increase assumed in scenario three, although Poland’s total increase over the nine years of 56 points is less than the 66 and 102 total point increases over twenty years of scenario’s two and three. Thus, the cognitive ability increase assumed in scenario one is clearly achievable, while those of scenarios two and three may require an unprecedented sustained national effort.

All three simulations calculate the annual GDP growth-rate increases as the educational improvements are phased in fully. The cause of the educational improvement is not specified. In general, however, improvements in cognitive skills are not necessarily a function of educational reforms but, instead, could be the function of a variety of non-education and education policies. For instance, as explained in the paper, enhancements in educational achievement could result from the adoption of high-quality, universal pre-Kindergarten, class size reductions, improvement in the education of teachers, higher wages for teachers, child health and nutrition policies, better prenatal and post-natal care, criminal justice reforms that help lessen the detrimental effects of incarceration on the children of prisoners, reductions in racial and housing segregation, changes in work place policies such as those related to family leave or schedules or vacation time, or combinations of these and many other policies.

Whatever the source of the improvement in cognitive skills, the achievement gains are not assumed to be immediate but, instead, they are phased in linearly over a 20-year period. Thus, the cognitive skills improvements are assumed to be very small after one year, but they grow steadily year after year so that after 20 years, the achievement improvements are fully phased in.

Similarly, it is assumed that the economic impacts of enhanced cognitive skills are not felt until students with better skills enter the labor force. As these new, higher-skilled workers replace older, retiring workers, the average skill of the workforce progressively improves, productivity increases, and economic growth accelerates.

It is assumed that the average laborer works for 40 years. This means that it will take 60 years to feel the full economic effects of policies to improve cognitive skills—20 years to phase in the achievement improvements and 40 years until the full workforce reaches the higher skill level.

The simulations indicate the average annual increase in economic growth that results from the narrowing (scenarios 1 and 2) or gradual closing (scenario 3) of the educational achievement gap between children from more and less advantaged families and the subsequent upgrade in the skill level of the workforce. The annual estimated growth increase is then multiplied by Congressional Budget Office’s long-term projections of real U.S. GDP to derive the annual increases in GDP over the years from 2015 to 2075 that result from closing or narrowing achievement gaps.

The Congressional Budget Office’s long-term projections of real U.S. GDP do not already assume the cognitive achievement improvements built into scenarios one, two, and three. Nor should they. The results of the National Assessment of Educational Progress (NAEP), the largest nationally representative and continuing assessment of the educational achievement of children in U.S. schools, indicate little or no progress in the educational achievement of 17-year olds over the past forty years. For example, the NAEP math score for 17-year olds was essentially unchanged over the past forty years, varying slightly from 304 in 1973 to 306 in 2010.

To estimate the federal tax revenue impacts of GDP increases that are induced by closing education achievement gaps, the Congressional Budget Office’s long-term projections of federal tax revenues as a percentage of GDP between 2015 and 2075 are used. For other revenue projections, the historical record on state and local, Social Security, and Medicare revenues as a percentage of GDP over the past 30 years is reviewed and used as a guide. Except for during the recession-affected years of 2002 and 2009, state and local revenues typically varied between 14 percent and 18 percent of GDP. It is assumed that state and local revenues derived from future increases in GDP would sum to the middle of the historical range, or 16 percent of GDP. It is further assumed that additional Social Security taxes and Medicare revenues—among the most significant subcomponents of federal revenues—would equal 4.3 percent and 1.3 percent, respectively, of annual increases in GDP, which is consistent with their current levels. These rates are applied to the calculated increases in GDP to determine increases in revenues.

To compare the worth of these future increases in GDP and tax revenues to the current value of GDP and revenues, the common practice of discounting the future increases in GDP is followed to recognize that each dollar of GDP acquired in the future is less valuable than each dollar of GDP secured today. In general, a dollar earned sometime in the future is less valuable than a dollar earned today because of the interest-earning capacity of money. For instance, if the current interest rate is 3 percent, then 97 cents earned today and put aside in an interest-bearing account would be worth approximately $1 a year from now. This is equivalent to saying that a dollar earned a year from now would be worth only 97 cents today. The discounted future value, known as the present value, allows us to state the value of future benefits in present dollars so that they can be more easily compared to current values. Thus, we calculate the present value of these future GDP and tax revenue increases by assuming a standard 3 percent discount rate. All calculations are in real (inflation-adjusted) numbers, with 2015 as the base year.

To calculate the increases in lifetime earnings for children who complete their schooling 20 years from the start of the policy reforms, we used the OECD’s estimate that 41 score points on the PISA math test is equivalent to about one year of schooling in the typical OECD country. Consistent with the literature on the relationship between schooling attainment and lifetime earnings, we then assumed that for each year of additional schooling, students would experience a 10 percent increase in lifetime earnings. Thus, for example, under scenario three a student in the bottom quartile of socioeconomic status experiences a 90 point increase in their PISA math score, which is the equivalent to 2.2 years of additional schooling or a 22 percent increase in lifetime earnings.

The Economic and Fiscal Consequences of Improving U.S. Educational Outcomes

This new study addresses a key challenge confronting the United States—how to promote both widely shared and faster economic growth. It does so by analyzing and describing the effects of raising educational achievement, especially for those not at the top of the economic ladder. The results of the analysis demonstrate that improving the education of future workers accelerates economic growth and can promote more equal opportunity over the long run. This interactive below enables readers to explore the ramifications of the study swiftly and tellingly.

Download a pdf of the overview.
Download a pdf of the “Fast Facts”.
Download a pdf of the methodology.
Download a pdf of the full report.

Methodology

The results of the literature on the effects of cognitive skills on economic growth are used to estimate the increase in the U.S. gross domestic product and tax revenues that would result from narrowing or closing the educational achievement gap between children from advantaged and disadvantaged family backgrounds.

A growing body of research uses cognitive skills, as reflected in international test scores, as a measure of human capital. This research suggests that human capital accounts for a significant portion of the economic growth of economically advanced nations. The results of regression analyses conducted by Eric A. Hanushek and Ludger Woessmann found statistically significant and strong effects of cognitive skills—as measured by the internationally administered PISA test scores—on the economic growth of 24 nations in the Organization for Economic Co-Operation and Development from 1960 to 2000. Specifically, Hanushek and Woessmann (2010) found that “an increase of one standard deviation in education achievement (i.e., 100 test-score points on the PISA scale) yields an average annual growth rate over 40 years that is 1.86 percentage points higher.”

Three simulations using the Hanushek and Woessmann regression estimate, one for each of three scenarios, are done to project the economic impact of closing or narrowing the educational achievement gaps between children from socioeconomically advantaged and disadvantaged families. The projection models follow closely the model developed by Hanushek and Woessmann in 2010, though several adjustments are made to account for factors specific to this study, such as the incorporation of estimates of future impacts on federal, state, and local government revenues. For all three scenarios, the 2012 U.S. PISA test scores in math and science are used as the baseline in the analysis.

We assume that the estimated impact of the PISA test scores on economic growth is causal, meaning that any policy that increases the test scores of students will result in faster economic growth. For the interested reader, Hanushek and Woesmann (2009) provide evidence that the association between cognitive skills—as measured by the PISA test scores—and economic growth is indeed casual and reflects the effects of cognitive skills on growth. They use a variety of instrumental variables to test causality, use a difference-in-differences approach to compare country of origin-educated to U.S.-educated immigrants, and test whether countries that have improved their test scores have experienced commensurate growth rate improvements.

All three of our simulation scenarios use the PISA index of economic, social, and cultural status, or ESCS, to differentiate advantaged from disadvantaged families. The PISA index of economic, social and cultural status is based on the highest level of parental education, parental occupation, an index of home possessions related to family wealth, educational resources available in the home such as the number of books, and possessions related to culture such as works of art in the home. We follow the OECD practice of defining students as socioeconomically advantaged if they are among the 25 percent of students from families with the highest PISA index of social, economic, and cultural status in their country. The parents of socioeconomically advantaged students have higher educational attainment and work in higher skilled jobs than do the parents of other children. More advantaged students have more books and educational resources, such as desks, dictionaries, computers, and Internet connections at home. Their homes also have more material possessions such as cars or rooms with a bath or shower.

Children from the most advantaged quartile of families scored an average of 532 on the math test, while children from the most disadvantaged three quartiles of families scored (in descending order by quartile) 494, 462, and 442, respectively. On the science test, children from the most advantaged top quartile of families scored 548 while children from the most disadvantaged bottom three quartiles scored 511, 480, and 456.

The first scenario assumes that the scores of children from the most disadvantaged bottom 3 quartiles of families are increased only enough to raise the average U.S. math and science scores to match the OECD average scores. Specifically, the difference between the average OECD math and science scores and the U.S. average math and science scores is calculated. For both math and science, the OECD-U.S. average score difference is divided by three quarters and the result is then added to the average score of students in each of the bottom three quartiles of the ESCS index. The math and science scores of the top quartile are assumed to remain constant.

The national average PISA math and science test scores are then recalculated for the nation as a whole. Aside from raising the combined math and science average U.S. score from 978 to 995 so that it matches the OECD average score, this scenario also narrows the achievement gaps between children from the most advantaged and most disadvantaged quartiles by approximately 13 percent. The average test score for the nation rises by 13 points in math and 4 points in science. The 13-point improvement in math and the 4-point improvement in science represent an increase of 0.09 standard deviations on the combined average score.

The second scenario raises the math and science scores of each quartile (by socioeconomic status) of U.S. students to match the math and science scores of Canadian students. This raises the combined average U.S. math and science scores from 978 to 1,044. It also improves the scores of the bottom three quartiles of students more so than for the top quartile of U.S. students, thereby narrowing gaps. The 66-point improvement in the combined math and science average test score is roughly an increase of 0.37 standard deviations on the combined score.

The third scenario assumes that the PISA test scores for children from the most disadvantaged bottom 3 quartiles of families are raised to equal the scores of children from the most advantaged quartile of families. In other words, the achievement gap between advantaged and relatively disadvantaged children is completely eliminated. The average PISA math and science test scores are then recalculated for the nation as a whole. This raises the combined average math and science score to 1080, which represents an increase of 0.54 standard deviations on the combined average score.

To assess the “reasonableness” of PISA test score increases of the sizes assumed in the three scenarios, the history of PISA test score increases was reviewed. Unfortunately, the PISA tests have only been administered at three-year intervals for a dozen years starting in 2000, and tests results have only been standardized and made comparable for the nine-year period between 2003 and 2012. This makes it difficult to compare actual increases in PISA scores to those in the three scenarios which take place over a longer time period: 20 years.

Nonetheless, several nations have experienced PISA test score increases that exceeded those of scenario one and roughly equaled those of scenario two. Germany and Italy, for example, experienced 33 and 27 point increases, respectively, in their combined average math and science score between 2003 and 2012, far exceeding the 17-point increase assumed in scenario one and roughly matching the annual 3.3 point-increase assumed in scenario two, although short of the 66-point total increase. Poland’s 6.3-point annual increase in its combined average math and science score between 2003 and 2012 is greater than the 5.1-point annual increase assumed in scenario three, although Poland’s total increase over the nine years of 56 points is less than the 66 and 102 total point increases over twenty years of scenario’s two and three. Thus, the cognitive ability increase assumed in scenario one is clearly achievable, while those of scenarios two and three may require an unprecedented sustained national effort.

All three simulations calculate the annual GDP growth-rate increases as the educational improvements are phased in fully. The cause of the educational improvement is not specified. In general, however, improvements in cognitive skills are not necessarily a function of educational reforms but, instead, could be the function of a variety of non-education and education policies. For instance, as explained in the paper, enhancements in educational achievement could result from the adoption of high-quality, universal pre-Kindergarten, class size reductions, improvement in the education of teachers, higher wages for teachers, child health and nutrition policies, better prenatal and post-natal care, criminal justice reforms that help lessen the detrimental effects of incarceration on the children of prisoners, reductions in racial and housing segregation, changes in work place policies such as those related to family leave or schedules or vacation time, or combinations of these and many other policies.

Whatever the source of the improvement in cognitive skills, the achievement gains are not assumed to be immediate but, instead, they are phased in linearly over a 20-year period. Thus, the cognitive skills improvements are assumed to be very small after one year, but they grow steadily year after year so that after 20 years, the achievement improvements are fully phased in.

Similarly, it is assumed that the economic impacts of enhanced cognitive skills are not felt until students with better skills enter the labor force. As these new, higher-skilled workers replace older, retiring workers, the average skill of the workforce progressively improves, productivity increases, and economic growth accelerates.

It is assumed that the average laborer works for 40 years. This means that it will take 60 years to feel the full economic effects of policies to improve cognitive skills—20 years to phase in the achievement improvements and 40 years until the full workforce reaches the higher skill level.

The simulations indicate the average annual increase in economic growth that results from the narrowing (scenarios 1 and 2) or gradual closing (scenario 3) of the educational achievement gap between children from more and less advantaged families and the subsequent upgrade in the skill level of the workforce. The annual estimated growth increase is then multiplied by Congressional Budget Office’s long-term projections of real U.S. GDP to derive the annual increases in GDP over the years from 2015 to 2075 that result from closing or narrowing achievement gaps.

The Congressional Budget Office’s long-term projections of real U.S. GDP do not already assume the cognitive achievement improvements built into scenarios one, two, and three. Nor should they. The results of the National Assessment of Educational Progress (NAEP), the largest nationally representative and continuing assessment of the educational achievement of children in U.S. schools, indicate little or no progress in the educational achievement of 17-year olds over the past forty years. For example, the NAEP math score for 17-year olds was essentially unchanged over the past forty years, varying slightly from 304 in 1973 to 306 in 2010.

To estimate the federal tax revenue impacts of GDP increases that are induced by closing education achievement gaps, the Congressional Budget Office’s long-term projections of federal tax revenues as a percentage of GDP between 2015 and 2075 are used. For other revenue projections, the historical record on state and local, Social Security, and Medicare revenues as a percentage of GDP over the past 30 years is reviewed and used as a guide. Except for during the recession-affected years of 2002 and 2009, state and local revenues typically varied between 14 percent and 18 percent of GDP. It is assumed that state and local revenues derived from future increases in GDP would sum to the middle of the historical range, or 16 percent of GDP. It is further assumed that additional Social Security taxes and Medicare revenues—among the most significant subcomponents of federal revenues—would equal 4.3 percent and 1.3 percent, respectively, of annual increases in GDP, which is consistent with their current levels. These rates are applied to the calculated increases in GDP to determine increases in revenues.

To compare the worth of these future increases in GDP and tax revenues to the current value of GDP and revenues, the common practice of discounting the future increases in GDP is followed to recognize that each dollar of GDP acquired in the future is less valuable than each dollar of GDP secured today. In general, a dollar earned sometime in the future is less valuable than a dollar earned today because of the interest-earning capacity of money. For instance, if the current interest rate is 3 percent, then 97 cents earned today and put aside in an interest-bearing account would be worth approximately $1 a year from now. This is equivalent to saying that a dollar earned a year from now would be worth only 97 cents today. The discounted future value, known as the present value, allows us to state the value of future benefits in present dollars so that they can be more easily compared to current values. Thus, we calculate the present value of these future GDP and tax revenue increases by assuming a standard 3 percent discount rate. All calculations are in real (inflation-adjusted) numbers, with 2015 as the base year.

To calculate the increases in lifetime earnings for children who complete their schooling 20 years from the start of the policy reforms, we used the OECD’s estimate that 41 score points on the PISA math test is equivalent to about one year of schooling in the typical OECD country. Consistent with the literature on the relationship between schooling attainment and lifetime earnings, we then assumed that for each year of additional schooling, students would experience a 10 percent increase in lifetime earnings. Thus, for example, under scenario three a student in the bottom quartile of socioeconomic status experiences a 90 point increase in their PISA math score, which is the equivalent to 2.2 years of additional schooling or a 22 percent increase in lifetime earnings.

The Economic and Fiscal Consequences of Improving U.S. Educational Outcomes

This study addresses a key challenge confronting the United States—how to promote both widely shared and faster economic growth. It does so by analyzing and describing the effects of raising educational achievement, especially for those not at the top of the economic ladder. The results of this analysis, which are consistent with a large body of research across a variety of academic disciplines, demonstrate that improving the education of future workers accelerates economic growth and can promote more equal opportunity over the long run. The result: stronger, more broadly shared economic growth, which in turn raises national income and increases government revenue, providing the means by which to invest in improving our economic future.

Click for our interactive graphic.
Download a full pdf of the report.
Download the “Fast Facts” pdf.

Since the early 1970s, economic growth in the United States has been relatively slow and income inequality has risen rapidly. Over this same period, income growth has been so sluggish and unevenly distributed that families on the bottom and middle rungs of the income ladder experienced stagnating or declining incomes even as earnings among those at the top increased sharply. In contrast, the years immediately following World War II and continuing into the early 1970s were characterized by relatively rapid and broadly shared growth. Those at the top earned substantially more than those across the middle and bottom of the income spectrum, but high, middle, and low-income earners all saw their incomes grow at about the same rate.

A restoration, then, of the economic growth pattern that characterized the first three post-war decades would result in both greater and more widely shared economic growth—equitable growth. In order to address this key challenge confronting the United States, this study empirically quantifies the economic and tax benefits of raising the educational achievement of children from less advantaged socioeconomic backgrounds. In general, there are large gaps in the educational outcomes among children from families with lower and higher socioeconomic status. These gaps contribute to subsequent economic inequality, with the relatively poor performance of children from lower socioeconomic backgrounds reducing U.S. economic growth. Thus, closing income or class-based educational gaps would promote faster and more widely shared economic growth.

The study shows the consequences of raising the educational achievement of children from the bottom three quarters of families who are most socioeconomically disadvantaged to more closely match those of children born into the top quarter of families. Observing the impact of three different scenarios that all have 2015 as their starting date, the analysis quantifies various outcomes over the next 35 years—to 2050, when the pressure of supporting the retired baby boomers will have largely abated—and over the next 60 years—to 2075, when the benefits of narrowing achievement gaps under the three scenarios will have been fully phased in.

Specifically, the study quantifies how much greater U.S. economic growth (measured by gross domestic product, or GDP, the total value of goods and services produced in our economy) and tax revenues would be. The analysis also assesses the reductions in economic inequality that result from the narrowing of education gaps.

In all three scenarios we use the 2012 scores on the Programme for International Student Assessment, or PISA, math and science achievement tests as our indicator of academic achievement. For each scenario, a simulation model is used to estimate the economic effects of potential policy reforms that raise U.S. PISA scores—effects that improve the educational achievement of U.S. children and reduce disparities in educational outcomes among them. The results of this modeling suggest the extent to which appropriate policies could enhance economic growth, raise tax revenue, and reduce economic inequality. (See the Methodology section on page 45 of the full report for details on the simulation model and data used in this report.)

The three scenarios and the consequences for U.S. economic growth and fiscal stability

In the first and most modest scenario, we examine the consequences of simply raising the educational achievement of U.S. children so that it matches, instead of lags behind, the average of the 34 economically advanced nations who are members of the Organisation for Economic Co-operation and Development. Specifically, we raise the achievement scores of U.S. children from the bottom three quartiles of disadvantaged families just enough so that the national average educational achievement of all U.S. children on the PISA tests matches the average educational achievement of children from the OECD nations. This raises the combined U.S. math and science PISA score from 978 to 995 (the OECD average) and improves the nation’s relative ranking from 24th to 19th best out of the 34 OECD nations, or roughly to the middle of the pack on par with France. (See Table 1, and for a complete breakdown by OECD member country see table 6 on page 29 of the full report.)

In the second, middle-range scenario, we explore the effects of raising the achievement of U.S. children to match that of the children of our neighbors to the immediate north in Canada. This adjustment lifts the combined U.S. math and science PISA score from 978 to 1044 (the Canadian average) and improves the nation’s relative ranking from 24th to 7th, tied with Canada.

In the third and most ambitious scenario, the economic consequences of completely closing educational achievement gaps between U.S. children from lower and higher socioeconomic backgrounds are estimated. In particular, the PISA test scores of the bottom three quartiles of socioeconomically disadvantaged U.S. children are raised so that they match the PISA test scores of the most advantaged quartile of U.S. children. This increases the combined U.S. math and science score to 1,080 and raises the U.S. academic standing to third best among the OECD countries, behind only South Korea and Japan.

TABLE 1
0115-gap-table01

The paper then summarizes the reductions in disparities in educational outcomes under each of the three scenarios. It reports the gap in outcomes on the PISA tests scores between children in the top and bottom quartile of family socioeconomic status as a percentage of the average PISA score. (See Table 2.)

TABLE 2
0115-gap-table02

Under scenario one, the education gap is reduced from 18.6 percent to 16 percent, and the U.S. ranking on equity improves from 21st to 11th out of the 34 OECD nations. Under the second scenario, the gap falls to 13.2 percent and the U.S. ranking rises to 6th. The third scenario completely closes the educational achievement gap between students from different socioeconomic background, and the United States ranks first among the OECD countries in the equality of educational outcomes.

The paper then demonstrates how the reduction in educational achievement gaps in the United States translates into stronger economic growth over the next 35 years and 60 years. Tables 3 and 4 summarize the economic consequences of raising academic achievement and narrowing educational achievement gaps.

TABLE 3
0115-gap-table03

Under scenario one, the inflation-adjusted size of the U.S. economy in 2050 would be 1.7 percent, or $678 billion, larger. The cumulative increase in real GDP (after factoring in inflation) between 2015 and 2050 would amount to $2.5 trillion in present value, or PV, the current dollar value that is equivalent to the future GDP increases calculated by the model, which allows for a comparison of future values of GDP to current values of GDP. This amounts to an average of over $72 billion per year. The economic effects of raising and narrowing achievement gaps build upon themselves so that over time the growth consequences are increasingly magnified. By 2075, when the effects of policy reforms required to reach this first scenario are fully phased in, the U.S. economy would be 5.8 percent, or $4.1 trillion, larger than it would otherwise be, and the cumulative increase in GDP over the 60-year period from 2015 to 2075 would amount to $14 trillion in present value, an average of $234 billion per year.

If American children matched the academic achievement of Canadian kids, then economic growth would be significantly larger. In 2050 the U.S. economy would be 6.7 percent, or $2.7 trillion, larger. The cumulative increase in GDP between 2015 and 2050 would amount to nearly $10 trillion in present value, $285 billion on average per year. In 2075, the real U.S. GDP would be 24.5 percent, or $17.3 trillion, larger, and the cumulative increase between 2015 and 2075 would sum to over $57 trillion in present value GPD, an average of $956 billion per year.

Finally, if achievement gaps between children from different socioeconomic backgrounds were completely closed, then the U.S. economy would be 10 percent, or $4 trillion, larger in 2050. The cumulative increase in GDP by 2050 would amount to $14.7 trillion in present value, or $420 billion per annum. In 2075, once policy reforms have fully taken effect, the real U.S. GDP would be 37.7 percent, or $26.7 trillion, larger, and the cumulative increase in present value GDP over 60 years would sum to $86.5 trillion, an average of over $1.4 trillion per year.

These results demonstrate that investments targeted at raising academic achievement and narrowing achievement gaps generate large returns in the form of economic growth. The increases in present value economic growth described above suggest the size of potential policy investments that would pay for themselves in the form of growth over the next 60 years and beyond.

Narrowing or closing achievement gaps also would also have significant positive consequences for future federal, state, and local revenues. Over the first 35 years, these would sum to $902 billion in PV federal, state, and local revenues under scenario one, $3.6 trillion under scenario two, and $5.3 trillion under scenario three. Over 60 years, the consequences would be significantly larger. Federal, state, and local revenues would sum to $5.2 trillion (scenario one), $21.5 trillion (scenario two), and $32.4 trillion (scenario three), all expressed in present value. (See Table 4.)

TABLE 4
0115-gap-table04

Thus, public policy investments that raised academic achievement as described under the three scenarios and that cost less than an average of $87 billion, $358 billion, and $540 billion over each of the next 60 years would more than pay for themselves in budgetary terms. To put these revenue figures in perspective, consider that the entire budget for the federal Department of Education in 2013 was $72 billion. Keep in mind, as well, that these revenue increases are not a function of tax rate increases. Instead they are the additional revenues that would accrue to governments because U.S. GDP would be larger and Americans would be earning more income and paying taxes on their additional income.

The increased growth and subsequent revenue increases will enable us to more easily sustain public retirement benefit programs such as Medicare and Social Security. Improving educational outcomes, for example, would lift Social Security tax contributions by $256 billion, $1 trillion, and nearly $1.5 trillion under the three scenarios by 2050. Similarly, Medicare tax revenues for the Hospital Insurance Fund would increase by $77 billion, $306 billion, and $452 billion under the three scenarios from 2015 to 2050, providing a substantial boost to Medicare solvency. Revenues for Social Security and Medicare would be substantially larger by 2075.

The benefits of closing educational achievement gaps also would reduce income inequality. These effects are calculated under the three scenarios for children who complete their schooling 20 years from the start of the necessary policy reforms (in 2035) because it is assumed that it takes 20 years for the academic reforms to be fully phased in. Children who complete their schooling prior to 2035 would experience only a part of the increase in lifetime earnings. (See Table 5.)

TABLE 5
0115-gap-table05

Under scenario one, the lifetime earnings of children from the bottom three quartiles of socioeconomic status would increase by an additional 4.3 percent. Under scenario two, all children would earn more, although the increases are smallest for children with the highest socioeconomic status and thus income inequality would be reduced. Finally, under the third scenario, the increase in lifetime earnings for children in the bottom three quartiles of socioeconomic status would be very large: 22 percent, 17 percent, and 9.3 percent respectively.

As explained in greater detail later in the report, these economic and tax benefit projections understate the impact of raising achievement gaps for at least four reasons. First, under scenarios one and three, they assume that educational achievement improvements are limited to children in the lower three quartiles of socioeconomic status, but in the real world policies that increase these children’s educational achievement are likely to improve all children’s achievement and further enhance growth.

Second, the model does not take into account any of the social benefits—such as better health outcomes—that are likely to occur as a result of educational improvement. Third, the model may be understating growth effects because it assumes that improvements in the educational achievement of children in the bottom three quartiles of socioeconomic status have the same impact on growth as do equal sized improvements in the educational achievement of the average child. Yet there is evidence that raising skills at the bottom improves growth more than raising skills at the top. Finally, the model does not calculate the potential positive effects on children born to future parents who, because of improved academic achievement, will have higher incomes and thus be able to provide them better educational opportunities.

If the model properly accounted for all of these factors, the benefits of improving educational achievement would be larger than those estimated in this study. Yet by a similar logic, the projections overstate the reductions in economic inequality. Helping the most disadvantaged students improve their educational outcomes will likely improve the educational outcomes of all children and thus raise the incomes of the most advantaged children as well as temper reductions in income inequality.

Closing the socioeconomic gaps in education

The potential economic gains described above illustrate in stark terms the waste of human talent and opportunity that we risk if achievement is not raised and gaps are not narrowed. They also suggest the magnitude of the public investments we should be willing to make now and in the decades to come to achieve these goals. Even from a narrow budgetary perspective, the tax revenue gains this study forecasts suggest that many investments to raise achievement and close educational achievement gaps could amply pay for themselves in the long run.

The report provides numerous examples of effective public policy strategies that promote equitable growth to illustrate that there are many ways of doing so, though their details are left to future research. Broadly, these public policy strategies fall into three categories:

  • Early childhood care and education
  • Criminal justice reform
  • Family friendly workplaces

Completely closing socioeconomic-based educational achievement gaps will not happen instantly, but we can begin to narrow them immediately. As the report details, we already know many of the reasons these gaps exist and policies that can help close them. Thus, we can begin to experience some of the economic gains described in this report as policies that successfully narrow achievement gaps are implemented. Raising achievement and closing socioeconomic-based educational gaps is about not only reducing the degree of inequality in our society and promoting more widely shared economic growth but also inducing faster economic growth. In short, it is about promoting equitable growth.

Waiting for wage and income acceleration

Later today President Obama will officially release his administration’s proposed budget for the next fiscal year beginning in October 2015. Just as with his State of the Union address, many of the proposals in the budget have already been announced or previewed in some manner. But unlike previous budget proposals from the Obama Administration, where the focus was on how large the budget deficit will be, the focus will be on purported solutions to what David Leonhardt of The New York Times calls the “great wage slowdown.” Even though the economic recovery is taking hold, there are still many areas for improvement.

On Friday the U.S. Bureau of Economic Analysis released their first estimate for GDP growth in the last quarter of 2014. GDP grew 2.6 percent on an annual basis, resulting in a GDP growth rate of 2.4 percent for the whole of 2014. In 2013, GDP grew 2.2 percent and 2.3 percent in 2012. So the overall economy has been growing at a steady and unspectacular level for the last several years.

And the labor market recovery is continuing apace as well. The unemployment rate has dropped significantly over the past year and total job growth has been strong enough to make a dent in the jobs lost in the recession, averaging about 250,000 new jobs a month. But broader measures of the labor market show there’s a ways to go. The employment-to-population ratio hasn’t moved up nearly as much as the unemployment rate has gone down. Wage growth has yet to accelerate while incomes are still stagnant for many households.

With these trends in mind, there are two data sets to look at in the coming week. Later today, the Bureau of Economic Analysis will release data on Personal Income and Outlays, which will show how much income is coming in and then going back out in the form of consumption. The Wall Street Journal highlighted the large inequality in consumption during this recovery, so that’s something to keep in mind when looking at the average data that the BEA releases today.

And on Friday, the Bureau of Labor Statistics will release its monthly Employment Situation Report, better known as the jobs report. Given the steady pace of the recovery so far, the headline figures—nonfarm employment growth and the unemployment growth—should only create news if there is some large swing.

Here are two numbers to keep an eye on.

First, be sure to look at the share of prime-age workers (25-to-54 years old) with a job. The movements in the overall U.S. unemployment rate can be complicated by long-term trends in the labor force participation rate due to demographics and the fact the many workers leave the labor force during times of economic weakness. But if you’d like to know how many workers in their best working years have jobs, then the prime-age EPOP is your friend.

Second, look at the year-on-year growth rate in average wages. Wage growth is important not only because it’s indicative of how well the average American is gaining from the recovery, but also as a measure of labor market slack. Once wage growth has picked up, then we can say that labor market recovery has really accelerated.

The recovery’s steady pace and wage growth that hasn’t increased in the last 4 years needs to change. The current rate isn’t enough to make a dent in the many economic issues of the day. Slow and steady won’t win the race this time.

Things to Read on the Evening of February 1, 2015

Must- and Shall-Reads:

 

  1. Ezra Klein: Baker’s Dozen Sample of Weblogs: “There’s: * Daring Fireball, * Slate Star Codex, * Ta-Nehisi Coates, * Freddie DeBoer, * Noahpinion, * Marginal Revolution, * Elizabeth Stoker Breunig, * Paul KrugmanDigby’s Hullabaloo, * Jared Bernstein, * Brad DeLong, * The Incidental Economist, * Kevin Drum, to name a few. There are plenty of great voices out there.”

  2. Nouriel Robin: On Secular Stagnation: “Who would have thought that six years after… advanced economies would still be swimming in an alphabet soup… of unconventional monetary policies?… Just in the last year and a half, the European Central Bank adopted its own version of FG, then moved to ZIRP, and then embraced CE, before deciding to try NDR…. One result of this global monetary-policy activism has been a rebellion among pseudo-economists and market hacks… ‘Austrian’ economists, radical monetarists, gold bugs, and Bitcoin fanatics… repeatedly warned that such a massive increase in global liquidity would lead to hyperinflation, the US dollar’s collapse, sky-high gold prices, and the eventual demise of fiat currencies at the hands of digital krypto-currency counterparts. None of these dire predictions has been borne out…. Most of the doomsayers have barely any knowledge of basic economics. But that has not stopped their views from informing the public debate…. Unemployed workers… chasing too few available jobs… trade and globalization… labor-saving technological innovations… squeezing workers’ jobs and incomes…. Slack in real-estate markets where booms went bust…. North America’s shale-energy revolution has weakened oil and gas prices…. China’s slowdown has undermined demand for a broad range of commodities… a global glut of manufactured and industrial goods…. Rising income inequality, by redistributing income from those who spend more to those who save more, has exacerbated the demand shortfall. So has the asymmetric adjustment between over-saving creditor[s]… and over-spending debtor[s]…. Perhaps more important has been a profound mismatch with fiscal policy. To be effective, monetary stimulus needs to be accompanied by temporary fiscal stimulus, which is now lacking in all major economies…. With long-term interest rates close to zero in most advanced economies (and in some cases even negative), the case for infrastructure spending is indeed compelling…. All of this adds up to a recipe for continued slow growth, secular stagnation, disinflation, and even deflation…. In the absence of appropriate fiscal policies… unconventional monetary policies will remain a central feature of the macroeconomic landscape.”

  3. Ezra Klein: What Andrew Sullivan’s Exit Says: “The incentives of the social web make it a threat to the conversational web. The need to create content that ‘travels’ is at war with the fact that great work often needs to be rooted in a particular place and context… that the reader and the author already share…. We’re getting better at serving a huge audience even as we’re getting worse at serving a loyal one. At Vox, we have some cool ideas that we’re going to roll out in the coming months to try to chip away at this problem, but I don’t think we’re anywhere near a solution…”

  4. Mile Kimball: John Stuart Mill on the Rich and the Elite: “I hate bashing of the honest rich. Of course, the dishonest or unworthy rich are a very different matter…. Whatever arguments one may have for taxing the rich, it is not OK to verbally attack the honest rich. If we fail to give honor to those who became rich by helping to provide goods and services that we value, then we will have to let them keep more money in order to provide appropriate incentives. On the other hand, the more we honor and tend to the souls of the rich, the more we can tax them and still have adequate incentives…. Envy raises complex philosophical issues for utilitarian social welfare maximization, related to issues about respect for the boundaries between people…. Interfering with conspicuous consumption out of one’s envy… has the potential to interfere with the efficient provision of incentives… [and] also often leads to attempts to limit conspicuous excellence…”

  5. Robert Waldmann: A Question for Those Skeptical about Fiscal Stimulus: “There are many opponents of fiscal stimulus… e.g. Robert Lucas and Eugene Fama. Some argue that nominal aggregate demand affects only the price level… others argue that fiscal stimulus doesn’t affect aggregate demand. My question is: What about Argentina?… Do fiscal policy skeptics… think that a temporary reduction in Argentine public spending would cause reduced aggregate demand?… If someone who considers himself a fiscal stimulus skeptic realizes that he thinks that austerity is a good anti-inflation tool, then he has a puzzle to solve. I also ask those who believe in expansionary austerity if they think that Argentina should cut aggregate demand and inflationary pressure by raising public spending. If the problem is the over-exuberant confidence fairy, then policy should be designed to damage confidence…”

Should Be Aware of:

 

  1. MathBabe: Leaving Academia for Finance and then Leaving Finance…: “People who are successful for a while think they know everything.  People who are rich think they are always right. People who are both successful and rich are absolutely incredible douchebags. It seems like a law of nature. (i.e. I can only assume that if I ever become rich and successful I will also become a douchebag….) when I think about that last project I was working on, I still get kind of sick to my stomach. It was essentially, and I need to be vague here, a way of collecting dumb money from pension funds. There’s no real way to make that moral, or even morally neutral. There’s no way to see that as scavenging on the marketplace. Nope, that’s just plain chasing after dumb money, and I needed to quit…”

  2. Ogged: Unfogged: “I enjoyed Belle ‘The Blender’ Waring’s follow-up on Chait, and it reminded me of a thought I had after his anti-PC piece: this is going to be interesting just as a psychological study of one guy. He might end up backgrounding his redistributive, government-loving self and becoming by degrees indistinguishable from a lefty-attacking righty so that in twenty years one of today’s kindergartners will say to her friend: ‘Dude, did you know that Jonathan Chait used to be a liberal?’ Or he might do the harder thing, and keep plugging away as one liberal writer among others, with the occasional defensive joke about those disagreements. It’s of no consequence, but I’ll be watching anyway.”

  3. : Comment on Following Up: “Tim ‘Ripper’ Owens: Actually, reading [TNR] in the 90s when I lived in DC, the vibe was very specific. It was ‘I am a smarmy recent Ivy Leavue grad, likely Jewish, who is completely terrified of being mugged on my way home after work. Also Clinton is surrounded by too many goobers.’ I swear that basically is sufficient to define the magazine’s politics in the early-mid 90s. peep: What’s a goober? Tim ‘Ripper’ Owens: Dumb Arkansas redneck, but in the mind of my ideal-type TNR reporter it basically included anyone who wasn’t exactly like them. Thorn: I hear you, fa, and I’d love to read a more expansive history, but this wasn’t it, I thought. And to dalriata’s second point, the 1991 rap article struck me as almost entirely of a piece with what I was reading in my parents’ National Reviews in ’91. The hard part of all of this is the people who had an emotional attachment to TNR trying to make sense of what they loved and how to justify and/or recreate it, right?…”

Morning Must-Read: Ezra Klein: Baker’s Dozen Sample of Weblogs

Ezra Klein: Baker’s Dozen Sample of Weblogs: “There’s:

to name a few. There are plenty of great voices out there.