The Liscio Report

Public Service Announcement on the Non-farm Payroll

2012-10-05T10:07:42-07:00

The large upward revisions to August payrolls released by the Bureau of Labor Statistics this morning (with jobs data for September) set the conspiracy theorists' world on fire. And they were strong, about three times the usual revision. But, as we pointed out in a report we sent to our clients earlier this week, this is a long-standing pattern. It almost always happens, whether there's an election coming up or not. Here's the relevant text from this morning's note:

August's gain was revised upward by 46,000, and July's by 40,000. Almost all the revisions, however, came from an upward revision of 101,000 to local government education in August before seasonal adjustment - a recurrent anomaly at this time of year that we wrote about in Wednesday's report. The concurrent seasonal adjustment technique distributes large changes like that backwards, so the gain was split between July and August in the adjusted numbers. Some excitable types are attributing the upward revision to political machinations, but this pattern has been around a long time. It's likely something is amiss in the BLS's collection process, and they are working on it. There shouldn't be a recurrent pattern of error like this. (Excitable types should also note that the birth/death model subtracted 9,000 jobs in September.)

Student Debt: Onerous, and a Drag

2012-05-20T16:05:23-07:00

We have heard from a number of sources that researchers at the New York Federal Reserve Bank are worried that without some form of mortgage debt relief we may face a crisis in a couple of years that eclipses the one that took place in 2008. In line with such worries, the New York Fed has started collecting previously unavailable data on student debt, a form of indebtedness that’s a major burden on the young, and also more of a macroeconomic drag than many analysts realize. Here are some details on all that.

Runaway Inflation

The rise in college tuition has been relentless, far outpacing the famous rise in the cost of health care (see graph, below). Since 1980, the overall CPI is up 194%. Its medical care component is up 436%, more than twice as much. But its college tuition component is up 829%, more than four times as much.

It’s hard to put a finger on just what drives educational inflation. No particular category of spending is rising out of line with the averages, though contacts at a number of institutions point to a great fondness for building fancy new buildings, many of them financed with bonds secured by supposedly ever-rising student tuition and fees. This is how NYU, with its relatively small endowment, is financing its grand expansion plans in lower Manhattan. Faculties of both the business school and economics department have filed objections, citing a fearsome growth in leverage. Similar things are going on in public systems, like the University of California’s, despite continued reduction in state financing.

Instructional budgets have remained at a stable 33% of spending for the last decade, even as student/teacher ratios have fallen. The reason that those ratios could fall while the instructional share of budgets has been stable is that universities have squeezed on labor costs. To start with, the composition of faculties has changed markedly—from nearly 80% full-time in 1970 to about 50% today. Over the last decade, student enrollment is up 38%; full-time faculty is up 23%, and part-time is up 63%. But the full-time faculty haven’t been raking it in. Tuition and fees have risen 82% faster than the salaries of full-time faculty since the early 1990s at private institutions, and 149% faster at public ones.

Burdens Shifting to Individuals

At the same time costs have been rising, state governments have cut back their support of public universities and colleges. Some major state universities now get less than 10% of their income from state budgets. As the graph below shows, the personal share of higher ed spending surpassed the state and local share about ten years ago, and the two lines continue to get farther apart. (This data, drawn from the national income accounts, stops in 2010. Given budget cutbacks since then, the gap has undoubtedly gotten wider.) The feds have kicked up their share, but nowhere near enough to offset the decline in the state and local share.

Of course, because of aid, not everyone pays the full published prices. According to the College Board, net costs of public institutions in 2008 were around 44% of household income for the poorest quartile of the population, 26% for the next-poorest, 19% for the second-richest, and 10% for the best off. That’s a lot of money. And more of the aid, at least until very recently, has been coming in the form of loans rather than grants. In the 1970s, loans were 21% of aid; lately, the share has been 47%. Pell Grants, the major federal program, covered 45% of the average public university tuition bill in 1990; in 2011, it covered 32%.

The Great Recession had a major effect on college choice and financing. According to a Sallie Mae/Ipsos survey, college costs—actually paid, not sticker prices—came down in the 2010–2011 school year, especially for higher-income families. (It rose for the poorest quartile, though.) Students traded down, looking for cheaper options (many—at all income levels—shifted from four-year public to two-year public institutions), and grants and scholarships increased (led by increases in Pell Grants from the federal government). More middle-income families applied for financial aid—the product, no doubt, of the recession’s lingering hit to income and balance sheets. Middle- and high-income families increased their use of grants and scholarships, with both dollar levels and shares of costs paid rising over the last couple of years. More middle-income families are applying for aid, and they’re still plenty worried about rising costs.

But a lot of college funds have to be borrowed. According to Sallie Mae/Ipsos, poor families paid 25% of expenses with borrowed funds in the 2010–2011 year. The share declines as you go up the ladder, but not as much as you might think: 22% for the middle ranks, and 17% for the best off. And the trend is towards increasing reliance on loans. In 1992, 32% of undergrads borrowed; in 2007, 53% did.

Heavy Debt Loads

The result has been a relentless increase in education debt. (See graph, below, for a yearly flow picture.) We don’t know exactly how much it’s risen, since there are no official sources of the stock of loans outstanding. A private researcher, Mark Kantrowitz, proprietor of a website called finaid.org, estimates that total student debt has risen from about $200 billion in 2000 to $1 trillion today, but he’s stingy about disclosing his sources and techniques. While the trajectory is probably more or less right, we don’t know for sure.

More recently, the New York Fed, using data gathered from the credit rating agency Equifax, has been publishing estimates of student debt, which are the closest to definitive we now have. The numbers are staggering. They estimate that as of the third quarter of 2011, total student debt was about $870 billion—more than credit card balances ($693 billion) and auto loans ($730 billion).

Just over 15% of adults have student debt balances. The mean balance is $23,300—but that is pulled up, as most debt aggregates are, but a minority who are deep in debt. The median is only about half the mean: $12,800. A quarter owe more than $28,000, and 10% owe more than 54%.

Although almost all age groups owe student debt, the profile skews young: 40% of people in their 20s are on the hook, compared with just 7% of those over 40. But the numbers don’t go to 0 with age: 5% of over-60s owe student debt.

And since the young have relatively low incomes—on which more in a moment—there’s a lot of distress among the indebted. On the surface, about 10% of those with student debts are in arrears, roughly in line with credit card debt. But since many borrowers are still in school or just out, they’re not yet expected to begin servicing their debts. Adjusting for that, the New York Fed estimates that more than a quarter—27%—of borrowers have past-due balances.

That level of distress, combined with a still-lousy job market, means that today’s young are having a hard time getting on their feet. A just-released survey of recent grads by the Heldrich Center for Workforce Development at Rutgers shows unrelated to their fields of study, and having a hard time making ends meet. Median student debt of recent grads is $20,000—higher than the New York Fed’s figure, no doubt because of the increasing prominence of debt finance. And it’s pinching their spending sharply: 40% have delayed the purchase of a house or car, 28% have put off additional education, 27% have moved back in with their parents, and 14% have delayed marriage. And they have generally gloomy views of their future—personally and especially for their generation as a whole.

A Nonflattering Profile

One of the more established facts in economics is that people’s incomes tend to rise with age to a peak around their early 50s, then decline into retirement and beyond. As with many established facts, recent economic history is challenging this pattern.

Graphed below is average household income in constant dollars by age of household head. In 2010, households headed by someone aged 15–24 had an income of $28,322, 15% less than their counterparts in 1970. All other age groups were better off than their predecessors 40 years earlier, though in general, the younger the cohort, the lesser the advantage. The 65+ set, though, was almost 80% better off than their 1970s counterparts. Today’s young are about 20% worse off than those of 2000. Most other groups are 10–15% worse off than their counterparts at the century’s turn.

That’s not to say that older households are doing swimmingly. In fact, the 35–44s and 45–54s are also worse off than their 1990s ancestors. And economic progress over time is looking to have stalled for the middle ranks. While the 25–34 set in 2010 had incomes 42% above the 15–24 group ten years earlier (presumably, that is, mostly the same people), the 45–54 group was 8% worse off than that cohort was when they were 35–44, and the 55–64 group was worse off.

Only the elderly have been exempt from this stagnation/downward mobility. They’re the only group whose incomes have risen consistently. But before one concludes that they’re rolling in it, the average income of this cohort was $31,408 in 2010, 36% below the national average.

Amid shifting trends and uncertainty, one thing doesn’t change: our young adults are our country’s future. It’s a good thing the NY Fed is paying attention to the burdens are best hopes are carrying.

Mismatch Redux

2012-03-28T16:01:51-07:00

It’s encouraging to see Chairman Bernanke continue his pushback against Minneapolis Fed President Narayana Kocherlakota’s theory of structural unemployment in his speech this week:

“Research has found that during and immediately after the serious recessions of 1973 to 1975 and 1981 to 1982, the Beveridge curve also shifted outward, but in both cases it shifted back inward during the recovery. This temporary outward shift during a deep recession may be the result of a particularly sharp increase in layoffs, which raises unemployment quickly, even as vacancies adjust more slowly.”

That’s a point we’ve been making since Kocherlakota first advanced his jobs mismatch theory back in August 2010. ( For more information, see: Mismatching the Facts http://tlrii.typepad.com/theliscioreport/2010/09/mismatching-the-facts.html )

Recent work on income disparity

2012-03-28T15:54:17-07:00

Setting the stage

UC Berkeley Economics Professor Emmanuel Saez recently updated his income-share spreadsheets through 2010, using data from the IRS’s Statistics of Income Division. This series includes capital gains, which results in more dramatic swings than one sees in series that exclude them.

Including capital gains real incomes fell 17.4% between 2007 and 2009, the largest decline since the Great Depression. Within that the incomes of the top 1% were down 36.3%, largely the result of the 74% decline in realized capital gains between 2007 and 2009, while those of the lower 99% were down 11.6%.

Painful for all, indeed, but skewed to the upper income groups, a trend that had more than retraced itself by the end of 2010, the most recent year of IRS data. Between 2009 and 2010 the incomes of the lower 99% rose only 0.2% while the incomes of the top percentile rose 11.6%, meaning that close to all the over-the-year improvement in income, when adjusted for population, was captured by that top percentile, 93% of it to be exact. (See links below for more data.)

That puts some numbers on why the recovery is experienced so differently by ordinary wage earners and by elite income groups, which in turn has surely heightened public awareness of our growing income disparity.

But there’s another big question out there. Whether you’re rooting for the upper or lower percentiles, if you spend a lot of time looking at income distribution tables, you can’t help but wonder why there is so little popular support for redistribution toward the middle classes, especially as the share of income going to the wealthiest citizens has risen toward levels last seen in the Roaring Twenties:

Piecing together what people think

In “The American Public Looks at the Rich,” sociologists David Weakliem and Robert Biggert round up a number of opinion polls on the subject taken over the last five decades and suggest some answers.

We’re re-quoting their opening quote because it’s a bit hard to remember that concerns about “tyranny of the majority” related to taxation have a long history. Back in late 19^th Century England, as property restrictions on voting weakened, John Stuart Mill fretted, “…is it not a considerable danger lest [the majority] should throw…upon the larger incomes, an unfair share, or even the whole, of the burden of taxation; and having done so, add to the amount without scruple, expending the proceeds of modes supposed to conduce to the profit and advantage of the labouring class?”

Although American workers have fought for wages, unions, and benefits, why a push for inequitable tax burdens (some would say even equitable tax burdens) on the rich feared by Mill and his colleagues has never gained traction remains an open question. After reviewing polling evidence, Weakliem and Biggert note, “There is little support for direct redirection from the rich,” and, “Even the general principle of progressive taxation does not draw clear majority support.”

The paper is thoughtful, even-handed, and a refreshing break from dreary speculation that the lower-income groups are dominated by a disproportionate share of misguided lottery enthusiasts. The comments of the authors suggest a far more complex picture.

For one thing, the authors note that Americans are not opposed to higher taxes on the rich-- 59% of respondents to a 2011 poll favored higher rates for families making at least $250K—but they don’t have much faith in the government’s ability to accomplish this. In one poll that inquired about the government’s ability to provide health care, college education, day care, and a few other services, “reducing the difference between the rich and poor” was the only item for which a larger percentage had had “no confidence at all,” rather than “a great deal of confidence.”

One pollster notes that since the 1980s “people have told pollsters that the rich, not themselves, will benefit from budget agreements. It does not seem to matter what the contents of the agreement are or whether they are negotiated by Republicans or Democrats.” Widespread belief that the rich get out of paying taxes leads respondents to believe that additional revenues intended to come from the wealthy would fall instead on the middle and lower incomes.

For another, poll respondents did not have an accurate idea of how big the current income gap is, and were in the dark concerning America’s international ranking in terms of economic equality. The authors found that although respondents were quite accurate in estimating compensation in a number of professions, they “dramatically underestimated” top executive incomes. For example, estimates of what CEOs and owners of large factories make were less than half the official estimates of actual salaries, as pieced together from a number of sources. Additionally, the margin between what respondents think executives make and what seems fair to them is considerably smaller than the margin between what respondents think executives make and what they actually make. (The authors note that respondents might have made more accurate estimates had they been asked about entertainers and athletes, rather than business-people, and that doctors’ and lawyers’ salaries are often over-estimated.)

In a 2006 poll, the respondents optimistically gave the US a mean ranking of 15^th out of 32 industrialized nations in terms of economic equality as measured by income ratios. Our actual ranking was 28th, with only Mexico, Turkey, Hong Kong and Singapore more unequal.

And for yet another, across a number of polls, respondents showed strong agreement that the possibility of earning high salaries was important to the economy as a whole, and to bringing people into professions demanding a lot of preparation. One poll found 63% agreeing that the spending of millionaires gives "employment to a lot of people," with 23% not agreeing, and 68% agreeing that investments help "create jobs and provide prosperity," with 19% disagreeing. A majority agree that no one would go through law or medical school unless they could earn substantially higher incomes than ordinary workers. So concerns about the negative economic effects of curtailing income inequality look to be part of the explanation for the lack of support for redistribution.

On the other hand, the authors found little support for the idea that Americans over-estimate their own standing on the income ladder, and none at all for David Brooks's claims that 19% of Americans believe they are in the top percentile. In one older poll, 20% ranked their families as above or far above average, and 29% as below or far below average; in a newer poll 8% ranked themselves as poor, 19% as lower income, 11% as upper income, and 2% as rich. The halves don't add up, and are skewed to the lower side. The authors note the people tend to be generous in evaluating their abilities, so perhaps there is some over-estimation, but polling evidence suggests otherwise.

The common assumption that people over-estimate upward mobility is complicated by disparate estimations of what it means to be wealthy. One study found that those making $10K a year would require only $50K, while it would take $250K for those making around $75K, so definitions of “rich” probably include moving beyond a hand-to-mouth existence. But the authors suggest that respondents are generally quite reasonable in their expectations about becoming wealthy. Noting that 8% of households make more than $150K a year, and that one analysis of tax returns found a 50% turnover within the top 5% over ten years, the number of people who will be rich at some point is several times larger than the number who are rich at any given time. According to various polls, about 10% of respondents think it is very likely they will be rich, and about 24% that it’s somewhat likely, so they aren’t so far off.

In 2009, one set of pollsters concluded that, "Americans doggedly believe in the rags-to-riches story," but there's a problem with the question on which this conclusion is based: "Do you believe it is still possible to start out poor in this country, work hard, and become rich?" The authors point out that it's certainly possible, so the correct answer in fact is yes; people answering yes may well be acknowledging that possibility, not saying it's highly likely, just as the up to 40% who responded no were more likely commenting on the rareness of the event than the literal impossibility.

Some have suggested that the American public tends to idolize the rich, but this was not supported in polls. First, the majority of respondents indicated they don’t find the rich that interesting, although they like to read about celebrities. A majority of respondents to an AARP poll thought being wealthy was the result of hard work rather than luck, but other polls found that percentages of people who agreed and disagreed that people worked hard for their wealth, and agreed and disagreed that the wealthy had exploited people to get where they were, were about even. Weakleim and Biggert suggest that the number of people who dismiss luck’s importance in becoming wealthy might be unrealistically high because some people may understand “luck” to “mean completely haphazard events, rather than systematic factors such as being born in a wealthy family.”

Although a majority of respondents in one poll believe millionaires give generously to charities, 49% do not believe they feel a responsibility to society because of their wealth, 78% believe them more likely to be snobs, 66% less likely to be honest, and 54% think them more likely to be racists. So, although 61% think the very rich are more likely to be physically attractive, that hasn’t translated to general merit, so admiration for the rich does not rank high as a reason that Mill’s prediction has not come to pass.

And finally the authors take on happiness. Although polls have found that large majorities believe they would be happier if they made more money, and 60% would like to be rich, only about 40% believe they would be happier if they were rich. Fifty-two percent believe the rich are no happier than they are, with only 11% thinking the rich are happier, and 35%, less happy. The authors don’t really see a contradiction here. They note that people might prefer to be rich because it would provide better benefits for their children, or that they would like to be relatively better off than they are, but not necessarily rich. In any case, the authors suggest that people are “resisting the logical consequence of the principle that money makes life better.”

Who knew?

Notes:

Income distribution data available at Emmanuel Saez’s website: http://elsa.berkeley.edu/~saez/

If you would like to see a copy of, “America Looks at the Rich,” please get in touch with us.

JOLTs update

2011-03-14T19:10:00-07:00

The Bureau of Labor Statistic's March 11 release of the Job Openings and Labor Turnover Survey (JOLTS) data for January showed a distinct lack of dynamism in the labor market: the level of hires and separations, expressed as a share of employment matched record lows for the series (which goes back to December 2000).

Net hiring - hires less separations - was just 0.1% of employment. Turnover - hires plus separations - was just 5.5% of employment, a record low for the series. Openings fell to 2.1% of employment (from 2.2%). That's better than the 2009 average of 1.8%, but matches the 2010 average. The numbers for the private sector were similarly tepid. January was not a sizzling month for employment.

Also, the relationship between job openings and unemployment, which had gotten out of whack, has gotten somewhat back into whack. Based on the historical relationship, unemployment in December "should" have been 7.7%, not its actual 9.4%. That gap narrowed substantially in January; the expected unemployment rate was 8.0%, vs. the actual of 9.0%. There were 5.02 unemployed persons per job opening in January, compared with 4.96 in December - and a 2002-2007 average of 2.03.

Flows out of unemployment—and out of the labor force

2011-03-05T18:23:00-08:00

Many analysts have been scratching their heads over the combination of a sharp drop in unemployment over the last few months alongside rather tepid job growth. The discrepancy is partially caused by the two different surveys from which the numbers are derived, surveys that often march to their own drummer in the short term. The BLS’s data on job flows offers additional clues.

Graphed below are some histories based on the flows numbers. The top graph shows where the formerly employed go from one month to the next. Between December 2010 and January 2011, 1.5% of the employed became unemployed, and 2.6% of the employed dropped out of the labor force. (There was a break in all the household survey numbers, because of the annual adjustments to the population controls, but the effect on these flows numbers looks to be very small.) The three-month moving averages of those two series are 1.7% and 2.7% respectively. The share becoming unemployed has been drifting lower since early 2009, but still remains rather high; the share leaving the labor force is up over the last few months, but isn’t out of line with historical averages.

The bottom graph is striking, however. The share of the unemployed finding work is very close to the recently set all-time low, and has barely improved over the last year. The share of the unemployed dropping out of the labor force, however, has been rising for more than a year, and now has exceeded those finding work for two years.

When you make a point like this, some skeptics are quick to blame excessively generous unemployment benefits and a labor force unfit for today’s demanding employers rather than a still-sick macroeconomy, suggesting that there’s less slack in the labor market than might appear at first glance.

There’s not much evidence for that. As newly minted San Francisco Fed president John Williams pointed out in a recent speech, the “natural” rate of unemployment—the one below which inflationary pressures rise—has probably risen from 5.0% before the financial crisis to 6.7% now. About half the increase is the result of extended unemployment insurance benefits (which will wane soon enough). The balance is the result of severe shocks that have hit the labor market, notably in the construction sector. Williams and his staff estimate that these increases in the natural rate are temporary, and likely to dissipate over the next few years. In any case, the unemployment rate is still considerably above 6.7%, and likely to stay there for quite a while. (Full text here: http://www.frbsf.org/economics/speeches/2011/john_williams0222.php)

SF Fed paper argues against mismatch

2010-12-05T19:02:00-08:00

In the November 8 issue of the San Francisco Fed’s Economic Letter, Rob Valletta and Katherine Kuang look at the regional and sectoral behavior of employment and find little evidence for the mismatch employment thesis currently making the rounds. If there were a serious mismatch problem, you’d expect to find major disparities in employment across geography and industry: healthy regions or sectors would show shortages of workers, and sickly ones would show surpluses. But in fact you don’t see that: regional and sectoral variation is little different now from past cycles. Valletta and Kuang conclude that the major reason for persistently high unemployment is cyclical and not structural.

The San Francisco Fed study looks at Beveridge curves. Beveridge curves plot unemployment against job vacancies. In general, the more vacancies there are, the lower the rate of unemployment. Minneapolis Fed President Narayana Kochlerlakota’s argument, outlined in a speech he made over the summer, depended heavily on the idea that the Beveridge curve suggests that the unemployment rate should be about 1.5–2.0 points below where it is, which is what leads him to the mismatch conclusion. His curve, though, was based entirely on only the most recent decade’s data.

But there’s nothing at all stable about this relationship over time. The Valletta–Kuang paper includes a graph showing how much the Beveridge curve has wiggled around over the decades. For example, Valetta and Kuang point out that the curve shifted about 4 points to the right between 1960 and the early 1980s before shifting back about 2.5 points by 1989, and that the variation in the NAIRU during that period was considerably smaller than the movement in the curve would suggest. We thought this worth a closer look.

Unfortunately, the JOLTS data only begins in 2000. Most earlier work on the unemployment–vacancy relationship used the Conference Board’s old Help Wanted (HW) index as a proxy for openings. In an earlier paper, Valletta used the period of overlap between the HW series and the JOLTS data to estimate a consistent vacancy rate series going back to 1960. He graciously shared that with us.

In the graph below you will see a set of Beveridge curves by decade—they show that a major cause of the noisiness in the long-term relation is that the vacancy–unemployment connection shifts over time. The r2’s for the decade regressions are a lot better than for the whole series, with most in the high 0.80s/low 0.90s. But there are also some noisy decades: the r2 for the 1970s is just 0.39. The 1980s aren’t so great either, with an r2 of 0.77.

The labor market is usually thought to be functioning better the further down and to the left (i.e., closer to the origin) the Beveridge curve is on the graph. The further out the curve is, the more friction, like regional or sectoral mismatches. The graph for the 2000s (which is based on data through June 2009, when the relationship prevailing earlier in the decade started breaking down) shows a much better-functioning labor market than in earlier decades, especially the 1980s.

Until, that is, we get to recent history, as shown by the dot marking the data for November 2010. It’s about two unemployment points to the right of where the curve suggests it “should” be. But it’s actually lower than the 1980s curve would predict, and not that much higher than the 1970s curve. And those were decades of major structural change in the U.S. economy—periods of major financial and real sector shocks, far more severe than those of the following two decades.

So the recent breakdown in the Beveridge curve looks to us more like a reflection of a major financial and psychological shock (one that has left employers extremely shy about hiring) than some fresh mismatch in the U.S. labor market. The fresh mismatch theory seems especially odd in light of the fact that things seemed to be functioning so well (meaning the Beveridge curve was close to the origin) for so much of the decade until the economy fell apart. The novelty is the having fallen apart, not some recent change in the labor force.

Mismatching the facts

2010-09-02T18:54:00-07:00

In a speech delivered on August 17, Minneapolis Fed president Narayana Kocherlakota claimed that there’s been a major breakdown between the relationship between the unemployment rate and the number of job vacancies reported in the BLS’s Job Openings and Labor Turnover Survey (JOLTS). According to Kocherlakota, the breakdown began in mid-2008 as the unemployment rate rose more rapidly than the JOLTS openings data suggest—a breakdown that intensified in mid-2009, as the unemployment rate continued to rise and then failed to decline significantly as the number of openings rose by nearly 20%. Kocherlakota explains this by asserting that there’s a mismatch between the skills, geography, and demography of available workers and unfilled openings. And that’s not anything that monetary policy can change: “the Fed does not have a means to transform construction workers into manufacturing workers.”

There are many things wrong with Kocherlakota’s argument. While he’s right that a regression that forecasts unemployment based on the JOLTS openings rate says that the jobless rate should have been 7.7% in June, not 9.5%, the number of unemployed fell by over a quarter-million more than the number of openings rose during the first half of 2010.

Despite that, there are still almost 5 unemployed for every opening—down from over 6 at the end of 2009, but still enormously high. Also, as the graphs below show, the major problem with the labor market is that the recession was harsh and the recovery so far has been weak. The gap between GDP growth and employment growth, though wider than it was in the recessions of the early 1990s and early 2000s, isn’t out of line with earlier downturns, like those of the early 1980s, mid-1970s, and the 1950s. Since the JOLTS data that Kocherlakota bases his mismatch thesis on only begins in December 2000, he’s missing a lot of important history.

And, the share of permanent job losers, as opposed to those on temporary layoff, hit a record high in over 40 years of data at the end of 2009, and has come down only slightly since. By contrast, the share on temporary layoff is at a record low. Clearly, that composition makes re-employment a lot harder.

In a paper prepared for a Brookings Institution panel in March, Michael Elsby, Bart Hobijn, and Aysegul Sahin review the grim pathologies of the labor market in the Great Recession. In almost every aspect, the downturn was the worst since the 1930s. Among their specific points:

While inflows into unemployment in the early part of the recession were dominated by the weaker demographics—the young, the less educated, the nonwhite—the rate of exit has been broadly similar for all subgroups.
Since the workforce is now older than it was in earlier recessions, the rise in the unemployment rate is actually sharper than it appears, since older workers are less likely to be disemployed than younger ones. Adjusting historical unemployment figures for the labor force’s changing age composition shows that this recession’s unemployment rate is a record by a significant margin.
Specifically addressing the mismatch argument, Elsby et al. find that instead of finding a divergence in outflows from unemployment between industries in structural decline and those not in decline, the rates of sectoral outflow have converged. (Outflow rates in the financial, durable goods and information sectors were all lagging the total when Elsby et al. published.) As with demographics, then, the problem is largely an aggregate one.
The dominance of long-term unemployment among the jobless in this cycle is disturbing, since the longer people are unemployed, the less likely they are to find new employment. Based on historical relations, Elsby & Co. project that the decline in unemployment could be half as rapid as it was in the mid-1980s. (Of course, if GDP growth remains weak, then that recovery would be even slower.)
Another factor likely to contribute to a slow decline in the unemployment rate: the high share of the employed working part-time for economic reasons. In July, they were 6.0% of the total employed, well over two standard deviations above the series’ 55-year average, and not far below last December’s record of 6.6%. And it’s likely that they’ll find full-time work before the currently unemployed do.
Some analysts have pointed to the extension of unemployment benefits over the last couple of years as keeping the jobless rate higher than it would otherwise be. Based on other studies, Elsby et al. estimate that emergency benefits have contributed between 0.7 and 1.8 points of the 5.5 point rise in unemployment in the recession, with the lower end far more likely than the upper. (One reason: the statistical estimates are largely based on periods when temporary layoffs rather than permanent losses were more common.)
Finally, the JOLTS data show that the quit rate was remarkably low during the recent recession. It’s picked up a bit since but remains lower than at any time before late 2008. This suggests that employed workers, who presumably have the qualifications that employers desire, remain remarkably skeptical about the possibility of finding fresh work. If it were easier than it looks for the qualified to find a job—as the mismatch theory suggests—then the quit rate would be higher.

Where we are?

2010-08-18T03:11:02-07:00

Here’s an updated guide to “where we are”—how the U.S. economy is faring relative to the average of previous financial crises around the world. Though individual details vary, we’re following the script pretty well.

In the graphs of four major indicators that below, the lines marked “average” are the averages of fifteen financial crises in thirteen rich countries since the early 1970s, as identified by the IMF. GDP isn’t shown because the experiences were so varied that the averages were meaningless. But for the indicators shown, the averages do illustrate some tendencies worth taking seriously.

Employment
Though the U.S. peaked later and bottomed earlier than the average, and also rose higher and fell harder, the trajectories of the two lines are still remarkably similar. Note that after hitting bottom, employment in the average experience grew very slowly. If we’re in for anything like that average, then we’re likely to see employment growth of only about 35,000 a month over the next year—less than a third what’s necessary just to accommodate population growth. That suggests that we could see an unemployment north of 10% in about a year.

CPI
Given the gyrations in energy prices over the last couple of years, reading the headline CPI has been very difficult. But the gyration does seem to be around the average line. And core CPI—for which we don’t have international data—is tracking the average pretty tightly. If inflation follows the script, it should continue to decline into next year. With core inflation at around 1%, it’s reasonable to expect that we could go into mild deflation sometime over the next few quarters.

Interest Rates
Rates on 10-year Treasury bonds have fallen harder in the U.S. than in other crisis-afflicted countries, but the trend is typically down for almost four years after the onset of crisis. Further declines in U.S. rates seem like a stretch, but the likelihood of an upward spike looks remote.

Stocks
Stocks fell much harder in the U.S. than they did in the wake of the average financial crisis, though they did enjoy five quarters of nice recovery. As with interest rates, further declines seem unlikely; in fact, the average increase from here would be around 7% over the next year.

So, all in all, we’re getting pretty much what we might expect out of our major economic and financial variables: a weak, choppy recovery with a deflationary undertow.

The Richmond Fed’s Take on Unemployment and Participation Rates

2010-04-08T18:07:13-07:00

In their economic brief, "Comparing Labor Markets across Recessions: A Focus on the Age Composition of the Population," Richmond Fed researchers Marianna Kudlyak, Devin Reilly, and Steven Slivinski find that controlling for the recent decline in teenagers' participation rate produces an unemployment rate of 11.3%, a new post-war high, and that much of the decline in the overall participation rate has been driven by the increasing percentage of workers 55 and older. Things are what they are, and you have to be careful about making this kind of adjustment, but this is Fed research and we are taking it seriously.

Setting the stage, they find that although the 2008 contraction in output was comparable to those of the 1957 and 1973 recessions (the prior record-setters), the 7% decline in employment was more severe than any other post-WWII recession. The 2% decline in weekly hours in the 2008 recession was not as severe as 1969's 3%, or 1973's 2.1%, but aggregating hours worked with employment produces a 9% decline, far worse than 1948's 5.7%, the previous record.

For their next comparison, they assume that the recovery began when Nonfarm Business Sector output turned positive, Q309 for the current recovery, and find that employment growth is lagging prior recoveries. Of the ten prior recoveries considered in the paper, employment continued to decline during the first two quarters of the recoveries following the 1957, 1960, 1991 and 2001 recessions, but percent declines were larger than the current decline (1.35%) only following the 2001 recession (1.8%) Positive note: Unlike the 2001 recession/recovery, weekly hours showed modest growth during the second quarter of the current recovery.

Noting that looking at labor indicators without adjusting for demographics, "may not be the best way to compare recessions," they adjust for teenagers' diminishing and the over-55 set's growing share of the work-force. In 1982, when unemployment hit 10.7%, its post-war high, teenagers constituted 7.6% of the workforce; in 2009, their share had dropped to 4%. This may be a good thing in the long-run as there is anecdotal evidence suggesting that teens are staying in school longer, and it is definitely a good thing for the unemployment rate. Teens have a volatile and high rate of unemployment, so Kudlyak et al. adjust the current rate by holding the teenagers' participation rate constant since 1982, resulting in the postwar high of 11.3% mentioned above. They go on to say that the larger share of older participants in the labor force "means the 'natural' unemployment rate is lower than it as in 1982," and that Q309's 10% is "likely further" from the natural rate than was 1982's 10.7%.

They apply the same technique to the labor force participation rate to determine how much of the current decline is cyclical and how much structural. Total participation was 58.6% in 1948, rose to 67.3% in 2000, and has declined since, hitting 64.7% in January 2010, with half of the decline occurring since December 2007. In March 2000, workers 55 and older constituted 26.8% of the working-age population, compared to 30.3% currently. Reconstructing the series using the current age composition replaces the long downward trend shown in the official series with a more modest decline that does not begin until mid-2009 and so far has only reached the level of mid-2005. Reconstructing another series that keeps 1999 participation rates constant across age groups, they show that in 2005 the official rate actually rose above what would have been predicted by demographic changes, and has only recently fallen below, suggesting that much of decline since 2000 is structural.

Their conclusions are a bit contradictory: the high unemployment rate of this cycle is "much higher in relative terms," than those of prior recessions, meaning there is a great deal of slack in the labor force but, since there has been less of a cyclical decline in the participation rate, there may not be as many workers outside the labor force ready to step in as the recovery continues as in prior cycles.

Economic Brief with a number of graphs here: http://www.richmondfed.org/publications/research/economic_brief/2010/pdf/eb_10-04.pdf

Philippa Dunne & Doug Henwood