Comments & Context

All This, and Indentured Servitude Too

It’s no secret that many of our more vulnerable workers have it tough these days.

In July, the Treasury Department decided to take a look at the widespread use of non-competition agreements among low-wage workers as a factor in ongoing low job churn and wage growth.

Additionally, Case Western law professor Ayesha B. Hardaway is looking into the proliferation of these “non-competes” among low-wage low-skill workers as a condition of their at-will employment as a violation of the 13th Amendment. She argues that Reconstruction Era debates, legislation passed after the amendment itself, and judicial opinions of the time make it clear that the prohibitions against indentured servitude and peonage in the broader amendment were intended to prevent wage slavery.

Which is what you get if you put at-will employees on this particular one- way street. They are not protected by contracts and, since they cannot seek like similar employment elsewhere, have no bargaining power.

And therefore no economic mobility. Hardaway argues that such use is outside the original scope of post-employment restrictive covenants, which were designed to protect trade secrets, thereby encouraging employers to invest in new ideas and in the training of their employees.

Restrictive employment covenants have been addressed by the courts for centuries, and US legal thought on such matters came, originally, from British courts in the 16th century. These courts generally put attempts to restrict work opportunities of former apprentices under the rubric “improper and unethical motives of masters.” Specifically, applying the rule of reason, the court stamped the idea that an apprentice could not seek employment in the “very trade he honed during his apprenticeship to be morally improper and outside ordinary norms.” Such thinking on employment restrictions held in England, although specific confidentiality clauses, and non-solicitation and non-poaching agreements, Hardaway’s “original scope,” generally got the green light.

And so it was in America until the late nineteenth century, when judicial decisions began to wear away the precedent set by the test of reason. Even so, through the twentieth century such agreements were limited by the courts to high-level employees with access to proprietary information, employees whose names and reputations themselves often added value to the company. These sophisticated workers are on a two-way street: at the same time they sign such agreements, they also sign employment contracts.

Hardaway believes that subjecting low-wage un-skilled workers to similar arrangements “fails to comport with the established rule of reason.” Indeed, and worth thinking about with the Politics of Rage getting so much ink these days.


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Oil and the Economy

In our reports, we have often made the point that the belief that shoppers spend their fuel savings on other sending is largely a myth—overall spending and spending on gas generally move together, and we tend to drive more when gas is cheaper. But just what is the relationship between oil prices and economic growth? Are high prices signs of economic strength or do they portend decline? Conversely, are low prices stimulative, or are they a sign of weakness? How do we separate cause and effect?

New York Fed economists Jan Groen and Patrick Russo have been on the case. The answer is basically—and unsurprisingly—“it’s complicated.” Groen and Russo develop a model, using what they describe as “a large number of financial variables,” to isolate supply and demand influences on the price of Brent crude since 1986. In a June 2015 post, they report that the price declines of the late 1980s and late 1990s were driven by supply-side shocks, namely aggressive expansion of production by OPEC members, notably Saudi Arabia. More recently, they find that the 2001–2001 and 2007–2009 declines were driven by demand shocks resulting from U.S. recessions. But outside these recessions, tighter supplies put upward pressure on prices through 2010. Between 2010 and 2012, prices were driven higher by a combination of rising demand and supply constraints. But since then, expanding supply has driven prices lower—a tendency that was partly counterbalanced at first by rising demand through mid-2014. Since then, demand has weakened while supply has remained plentiful.

And what are the effects of changes in oil prices? They find that price declines resulting from supply shocks have only modestly stimulative effects on GDP and consumption—roughly a +0.10–0.15% kick to both from a one-standard-deviation supply shock in the first quarter or two afterwards that decays in about four quarters. Real nonresidential fixed investment responds more strongly but more slowly, maxing out at about 0.30% three quarters after the shock. Investment takes a little longer to decay, but the effect is all gone in seven or eight quarters. Their model projected that the decline in oil prices of late 2014 and early 2015 would have only a modest stimulative effect during the second half of 2015, and would be mostly dissipated by early 2016. Given recent growth rates, that looks like not a bad forecast.

In a recent post, Groen and Russo updated their work. Their model suggests that the price declines in late 2015 and early 2016 have had and will have little effect this year. Perhaps, then, we all pay too much attention to oil prices.

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Don’t make promises you can’t keep

Taking a page from Charles Kindleberger’s research on the increase in credit’s effect on asset prices, David O. Lucca, Taylor Nadauld, and Karen Shen, researchers at the New York Federal Reserve Bank, have posted a paper putting a price on what increased student loan availability has done to college tuition levels. (Link at foot of article.)

This is a careful paper: the authors lay out concerns about their methodology, stress areas where they see weakness, and balance the whole thing against the benefits to our workers and to our nation of an increase in the share of workers with college degrees. Nonetheless, it is a sobering piece of work that should force a number of deep questions, and, one hopes, policy changes.

In opening the discussion the authors note that much study has been devoted in recent years to the relationship between cheap credit and the 2002-6 housing bubble, and point out that although student loans fund a capital investment, whether delineated broadly as an educated work force, or on an individual level, while mortgages fund an asset, credit is crucial to both, and both enjoy the support of government-sponsored programs.

Federal student aid programs are governed by the 1965 Higher Education Act (HEA), which outlined 6 mandates, the fourth, Title IV, authorizing financial aid to support access to post-secondary education through the Federal Pell Grants program and the Federal Direct Loan Program. The researchers looked at three amendments to HEA: the increase in subsidized loan caps in 2007-8 school year; in unsubsidized caps in the 2008-9 school year, and the gradual increase in Pell Grants between 2207-8 and 2010-11 to link changes in tuition following increases access to loan and grant funding.

Although changes in caps theoretically apply to all institutions, the percentage of students who meet the requirement to gain access to those funds is not evenly distributed, and the students at program caps, say those with funding needs larger than the maximum loans available before cap increases, are the ones most likely to take the loans. As of 2012, about 60% of post-secondary students attended four-year public universities, 29% not-for-private private liberal art colleges and research universities, and 11%, Title IV “less-than-two-year” for-profit outfits, largely vocation and specializing in technology, business, photography, and fashion, including cosmetology and hair styling. That last 11% receives more than 77% of their funding through Title IV, with the largest share of near-the-cap students.

Between 2001 and 2012 yearly student-loan initiations increased from $53 billion to $120 billion, and in recent years 90% of those initiations came through federal student aid programs. Over the same stretch, the average tuition “sticker” price in constant 2012 dollars rose from $6,950 to $10,200, or 46%. (The authors focus on sticker rather than net tuition because it is more readily available, and because of the effects of institutional grants and the like.)

The authors found, not surprisingly, that the institutions with most aid exposure before the cap increases underwent “disproportionate” increases in tuition around those changes. For subsidized loans the authors found that 70 cents of each newly available dollar was captured as a tuition increase, and that approximately 55 cents of each Pell Grant dollar was so captured. Highest pass-throughs took place in the more expensive four-year private institutions with “relatively high-income students but average selectivity.”

Regarding this they conclude:

From a welfare perspective, these estimates suggest that, while one would expect a student aid expansion to benefit its recipients, the subsidized loan expansion could have been to their detriment, on net, because of the sizable and offsetting tuition effect.

But it was good for the stock market. On the for-profit front Lucca et al. found evidence of “large abnormal stock market responses for a portfolio of all publicly traded for-profit institutions,” following the passage of the aid increases that summed up to 10% across the segments. They also found that the average increase in the sticker price in these outfits averaged $180, but averaged $56 in the not-for-profit colleges and universities.

Here’s some food for thought via a severe example of tax dollars gone astray. Surely some of the for-profit outfits meet their stated goals, but Corinthian Colleges Inc. (CCI), the largest such for-profit network, was not among them. In April 2015, under Federal criminal investigation, Corinthian closed down its operations, and filed for bankruptcy in May. Charges include misleading students on their career options and Corinthian’s ability to place them following graduation, the graduation rates themselves, and loan issues. California Attorney General alleges CCI targeted single parents close to the poverty level via aggressive marketing. So that’s one place our tax dollars earmarked to increase access to post-secondary education have been. Note to for-profit educators: Don’t make promises you can’t keep.

But we can end on an encouraging note. As is often the case, the action is at the margin. In working to ascertain whether student debt expansion increased access to post-secondary education over the short-haul, the NY Fed researchers found that only the availability of Pell grants increases access. These grants go directly to low-income students, who are most likely to be on the enrollment margin. And although they also push up tuition, they do so at a lower rate than the loan-based increases.

If we’re serious about increasing access to college for those who want to attend, we’d be wise to funnel funds into grant programs that advance that goal, and to do so at the expense of outfits like CCI.

Credit Supply and the Rise in College Tuition: Evidence from the Expansion in Federal Student Aid Programs

by Philippa Dunne· · 0 comments · Comments & Context

What gas dividend?

Oil (and gasoline) prices have crept off their lows; they’re up about 25% this year, though they’re still well below year-ago prices. But many analysts have been scratching their heads wondering why the decline in energy prices hasn’t done more to goose up retail spending. It may be that's not really much of a conundrum. 


Here are several ways of making that point. First, there’s the graph above, showing the annual growth rate in nominal expenditures on energy and all other forms of consumption from the national income accounts. If energy prices could add to or subtract from other forms of consumption, you’d expect the two lines to look more like mirror images. In fact, they move more together than apart. The correlation coefficient between the two series is 0.43. Lag the non-energy spending a year, on the supposition that there might be a delayed reaction time, and the correlation coefficient actually falls to 0.28.

Moves in energy consumption are overwhelmingly dominated by price. The correlation coefficient between the annual change in the gasoline price and energy expenditures is 0.97. (That’s made even more remarkable by the fact that more than a third of energy spending is on services like electricity, which are not priced like gas.) While people may drive more or less, or raise or lower the thermostat, based on price movements, it appears they don’t change their behavior all that much. They just take the price—and it doesn’t seem to have much effect on other spending.

One gets similar results looking at the BLS’s Consumer Expenditure Survey (often abbreviated CEX, so as not to confuse it with Current Employment Statistics, the official name of the payroll survey). The CEX can be volatile, and dependent on the unreliable memories of the surveyed in describing their spending habits, but it’s still the best household-based measure of expenditures we have—and it allows for fairly detailed demographic analysis.


As the first graph above shows, we don’t find the mirror image between energy and non-energy spending growth that you might expect in the aggregate. The correlation between energy and non-energy spending growth is 0.28—positive, not negative. And the story is similar when you look at poor (bottom quintile), middle-income (third quintile), and affluent (top quintile) households. The correlation weakens the higher you go up the income ladder (0.52 for the first, 0.42 for the third, and 0.14 for the fifth), but they remain positive for all five. 

Not surprisingly, there’s a tight relation between income growth and spending. A regression of the annual change in non-energy spending in the CEX on the annual change in household income yields an impressively high r2 of 0.53. So the “mystery” of why lower energy prices are not translating into higher retail spending may not be a mystery at all. The best explanation of tepid retail growth is tepid income growth.

Advanced industries

February 11, 2015

 The Brookings Institution just published a paper outlining the importance of our advanced industries (AI), and a call to do more to support its growth. To be classified as advanced  industries must spend more than $450 per worker on R&D, putting them in the 80th percentile, and the share of workers whose jobs demand a high degree of STEM (Science, Technology, Engineering and Math) knowledge must exceed the national average of 21%. Overall, industries so classed constitute our tech sector at its broadest: most manufacturing operations including aerospace, automotive, navigational instruments, medical equipment and supplies; energy including electric power, mining and extraction; and services, including architecture and engineering, data processing, satellite communication and scientific research. 

Between 1980 and 2013 such industries grew 30% faster than the rest of the economy, or 5.4% annually, but employment levels held basically steady, largely because of productivity advances. Since the Great Recession both activity and employment have been on the rise, the sector adding one million direct jobs between 2010 and 2013, with employment and output rates 1.9 and 2.3 times faster than the nation as a whole. And AI employment has a high multiplier: those 1 million direct jobs likely generated another 2.2 million outside the industry itself, which compares to about 6 million total jobs created nationally over the same stretch. Advanced services were responsible for 65% of the total AI jobs, with computer design by itself up 250,000. Industries building transportation equipment have been adding jobs, finally, after decades of losses. A lot of attention has been focused on contributions to national payroll gains made by AI subsector gas and oil extraction since the recession. 

A boost? Certainly, but dwarfed by the mothership.

 Each worker in the sector generates about $210,000 in value added, in comparison to the $101,000 average overall, which helps offset the sharp increase in wages. In 2013 the average AI worker earned $90,000 annually, close to twice the overall average. Between 1975 and 2013 inflation-adjusted AI wages were up 63%, compared with 17% outside the sector. Total AI employment was about 12.3 million in 2013, about 9% of total overall employment, with another 27 million jobs riding AI's coattails. Together with the directly employed, that’s about one-fourth of US employment. Surprisingly, about half of the workers in the sector hold less than a bachelor’s degree, and Brookings ranks it as an accessible field. And one where more workers are needed.

Computer systems design owns the largest share of total AI employment, 13.8%, followed by architecture and engineering, 11.0% and management and technological consulting, 9.6%. Between 2010 and 2013 fastest rates of employment growth took place in information services, 10%; railroad rolling stock, 8.4%; automotive, 8.1%, and gas and oil extraction 7.6%.

Advanced industries tend to thrive in urban areas: San Jose is our most advanced hub, with 30% of the workforce laboring in the sector, followed by Seattle, 16%, Wichita, 15.5%, Detroit, 14.8%, and San Francisco, 14%. San Jose, Detroit and Seattle have the broadest array of advanced industry. (We’ll be presenting more data on this in coming months.)

 We are losing international share, and there are a host of serious problems we like to nag about, but even in its somewhat weakened state our AI sector a powerful thing. And if we’re worried about productivity, as we should be, it’s a great place to start.