March 6, 2014

Lately we’ve been seeing the argument made that the labor market is tighter than it looks. The argument goes like this: while the decline in the unemployment rate may have been boosted by labor force withdrawal, many of the dropouts will never work again, so it’s wrong to adjust the official jobless rate, either statistically or mentally, to compensate for depressed participation rates. So January’s 6.6% unemployment rate, 0.1 point above the Fed’s long-standing trigger, is getting close to “full employment,” and it would be prudent to start thinking about raising the fed funds rate sooner than most market participants expect. Is there anything to this?

We think not. For one, a 6.6% rate is about two-thirds of a standard deviation above the 1948–2007 average of 5.6%, which is not trivial. It’s even further above, in absolute terms, its 2002–2007 average of 5.3%, an expansion that was far from robust. It may be close to the Congressional Budget Office’s estimate of the “natural” rate of 6.0%, but as we showed last month, there’s nothing very scientific about these estimates; just six years ago, the CBO projected that the natural rate would be 4.8% right now.

A more subtle version of the argument looks at sectoral unemployment rates and finds some getting awfully close to full employment. We have a hard time seeing that. Graphed at right are unemployment rates by major sector compared to their 2000–2007 averages. In only one sector—manufacturing—is the January 2014 unemployment rate close to its average, though it’s 0.1 point above. Next closest is finance, 0.8 point above. The others are 1–2 percentage points above their average. A nice theory, but it just doesn't hold water.

Relatedly, some analysts are detecting wage pressures under a placid overall average—a 1.9% gain for the year ending in January. One argued that weakness in financial sector pay is dragging down the average. But if you do a weighted average of hourly wage growth excluding that sector, you still get 1.9%. Most major sectors, accounting for 72% of total private employment, exhibit wage growth below their 2007 average. In fact, wage growth is slower than it was a year ago—and that’s true of sectors accounting for 68% of private employment. It’s hard to see any tightness here either.

quit rates

Another place to look for signs of labor market tightness is in the quit rate. If workers perceive jobs as easy to get, they’re more likely to quit on their own. And, short of that, they’re more likely to demand raises from employers eager to keep them. But currently the quit rate is low by historical standards.

The BLS started publishing the quit rate in 2000. Since the quit rate tracks the number of those unemployed 5 weeks or less very closely, we used that series to estimate the quit rate going back to 1967. (Where the two series overlap, the fit is very tight—an r² of 0.93.) December’s 1.7% rate is well below the full series’ 2.1% average. It’s also well below levels seen close to previous business cycle peaks, like 1979, 1989, 1999, and 2007.

The quit rate moves generally in line with the unemployment rate. You can “predict” the unemployment rate with decent accuracy with the quit rate, in fact. But as the graph on the bottom of this page shows, the unemployment rate associated with the December 2013 quit rate is a full point above its actual level. Or, putting it more bluntly, workers are acting as if December’s unemployment rate were 7.7%, not the 6.7% it actually was. If the job market were tighter than it looks, we’d expect a much higher quit rate.

The BLS released Quarterly Census of Employment and Wages (QCEW) data for the second quarter of 2013 this morning. Since it's based on the unemployment insurance system's records, it offers near-universal coverage of the job market (as opposed to the monthly payroll survey, which is just a sample, though a very large one). It shows that total employment grew 1.6% in the year ending in June, compared with 1.7% reported by the monthly payroll numbers. This is a reversal of the last release, which had the QCEW growing 0.1 point more than the payroll survey. But an 0.1 point difference in either direction is trivial, and confirms that the payroll survey is doing a good job at tracking this weird recovery/expansion.

Earnings figures in the QCEW are difficult to compare with the monthly payroll numbers, since the definitions and coverage are different, and the series is not seasonally adjusted. They showed a 6.9% decline in wages from the first quarter to the second, following a 1.1% decline from 2012Q4 to 2013Q1. Quarterly declines are normal in the first and second quarters in the QCEW earnings series, but the second quarter decline is larger than normal (the first quarter was quite close to average).

Finally, the number of employing establishments rose 0.7% for the year ending in the second quarter, a decline from the 2.0% gain in the first. The trend, however, is working its way slowly higher after the sharp (and unprecedented since the series began in 1976) decline in establishments during the Great Recession. The pace of startups is well below the 2-3% average of the 1980s and 1990s, and even the 1.7-1.8% average of the mid-2000s. Establishment formation is extremely important to employment growth, since young firms are the primary creators of new jobs. So this is good news for continued employment gains, but offers little hope for an acceleration in the pace of job growth over the next year or two.

Young firms, not small firms, make an outsized contribution to job growth here in the U.S., and the ongoing decline in start-up activity has taken a lot of the fizz out of the U.S. job market. We've gathered some research that considers why creative destruction in the business world has lost its creative half, a serious and ongoing issue for our workforce

In a presentation at a November 2012 IMF research conference, Teresa Fort, John Haltiwanger, Ron Jarmin and Javier Miranda note that between 2006 and 2009 employment growth in firms less than 5 years old with fewer than 20 employees fell from 26.6% to 8%, while employment in businesses more than 5 years old with more than 500 employees fell from 2.8% to -3.9%, narrowing the differential from 23.7% to 12.5%. They note that many of the hypotheses concerning why small firms are more sensitive to credit conditions apply more accurately to young firms and start-ups because they don’t have access to commercial paper and corporate bonds, and instead rely on their own finances to get started including, you guessed it, home mortgages. Specifically, they found that the housing price shock in California explains 2/3s of narrowing of the growth rate differential noted above, found like patterns in other states with severe housing price declines, and did not find them in states that did not experience such declines.

In a related paper, the same team, sans Ms. Fort, found that the largest declines in the share of employment accounted for by young firms (declines ranging from 11.8 to 14.3%) occurred to California, Nevada, Utah, Arizona and Idaho, while the second tier (declines of 7.1 to 11.8%) were wider spread, but included Florida, Oregon, Wyoming, and Michigan. So, all front-line housing bust states are all in the top tiers.

 …and housing bust

 The authors note the work of Atif Mian and Amir Sufi on aggregate demand at the state level, and note that the decline in housing prices cuts both into self-financing, and into local demand. A San Francisco Fed paper released yesterday authored by Mian and Sufi using state-level National Federation of Independent Businesses data finds a strong correlation between the decline in the employment-population ratio between 2007 and 2009 and the 20pp increase in businesses citing poor sales as their biggest problem. (The percentage citing credit conditions barely moved, which struck the authors, and us, as odd.) 

They looked at household-leverage and found that the percentage of businesses citing weak sales rose more in states with higher household leverage, where largest declines in spending and employment catering to local customers took place as well. And although the percentage of small business owners reporting regulation and red tape as their biggest problem rose between 2008 and 2011, the increase was inconsistent across states—Rhode Island reported a rise of over 30pp while that measure fell by 10pp in New Jersey—and the states where the complaints about regulation and taxes rose the most also experienced the strongest employment growth, although the correlation was not statistically significant.

The weakness in start-up activity since the Great Recession is no mystery. 

longer-term issues

 But what about the long if less dramatic decline since the 1980s? Of course there are many factors, including concentration of power in major corporations, barriers to entry, and outsourcing, especially of manufacturing activity, and we have identified a few other trends that have gotten less attention.

 First there is a well-documented relationship between education and entrepreneurship: as of 2007, 28% of the overall US population had attained a bachelor’s degree or higher, but 48% of business owners with paid employees had bachelor’s degrees or higher. Between 1980 and 2010 both overall job growth and educational attainment have slowed from their 1950–1980 rates. Metro areas with smaller education gaps (the difference between the years of education required by the average posted job openings and the ears of education attained by the average worker in that area) have significantly lower unemployment rates for well and poorly educated workers alike. The decline in job growth/ed attainment coincides with the decline in start-up activity. 

 Second, in a paper in the January 2011 issue of The Journal of Health Economics, Robert W. Fairlie, Kanika Kapur, and Susan Gates used CPS panel data to expand on limited research on “entrepreneurship lock,” and found that self-employed business owners are “much less likely” than wage & salary workers, part-time workers and even unemployed workers to have health insurance, and that new business owners have lower rates than those in older businesses. Business creation rates are lower for workers with employer-based heath insurance, and higher for those who have no health insurance, or have insurance through their spouses. They estimate that, for men, this lowers the probability of starting one’s own business by 1% “relative to an annual base business creation rate of 3%.” They conclude that eligibility for Medicare has a lot to do with it: business ownership rates for men increase from 24.6% for those just under 65 to 28% just over 65, but there is no change between the ages of 55 and 75, meaning it’s not just because they reach retirement age. In closing they note that the relatively low rates of business ownership in the US may be related to differences in our health insurance coverage with coverage in other wealthy countries. 

 Third, a disproportionate number of start-ups are founded by skilled immigrants. A Kauffman Foundation study found that a quarter of the science and technology firms founded in the US between 1995 and 2005 were headed up by a foreign-born CEO or lead technician, and that in Silicon Valley the percentage rose to 52%, with Indian immigrants founding one fourth of the start-ups, and immigrants from Britain, China, Taiwan and Japan founding the other fourth. Weakness in our economy has caused a decline in immigration, and although there have been some legislative proposals to award VISAs to those who might want to start a new company here, it doesn’t really work that way. Generally firms are started by entrepreneurs who come here to go to school, work, or for family reasons, about not until they have been in the US for about  10 years. So this is likely to be a persistent problem as well. 

 There is much speculation about tax rates but, although increased tax rates on capital gains may discourage angel investors, David Friend, who has founded six companies in three decades, notes that the marginal tax rate “doesn’t make any difference” to entrepreneurs: they are unlikely to make much in their first few years, and are focused on “hitting it big” in the future, as were Bill Gates and Steve Jobs who braved top income tax rates of 70% when founding their companies.

The market is currently abuzz with news that Robert J. Gordon, longtime member of NBER's Business Cycle Dating Committee, has provided solid evidence supporting a tight link between the peak in initial claims and, dare we say it, the end of recessions.

Back on April 2, we sent this to our subscribers:

Here's a rare note of possible cheer: could the behavior of initial claims be signaling that an end to the labor market contraction is in the offing?

Graphed below is the yearly change in initial claims for unemployment insurance. Note that this measure typically peaks a little before the end of a recession. No surprise, perhaps. But what is a little surprising is how similar current behavior  looks to earlier end-of-recession patterns.

And as the table below shows, the peak in claims growth occurs, on average, four months before the official NBER trough month, though the range is one to seven months. Note too that employment doesn't necessarily turn positive until a few months later, with the trough in yearly job growth typically coming five months after the peak in claims growth, and the trough in the employment level coming eight months after. In 1970s, yearly job growth hadn't picked up even a year after the peak in claims. But even then, the bottom was getting close.

Since there's a good chance that the job market in this cycle will resemble the slow recovery after the 2001 recession, it could be 2011 before employment starts growing again. But if we think of this as a sort of leading indicator of a leading indicator, we could start seeing signs of the recession's end by mid-summer. We hope.

NBER has just released a working paper, "Exploring Differences in Employment between Household and Establishment Data," that presents research and analysis carried out by the Census Bureau and the BLS concerning the unusually large gap between the two major employment surveys that developed in the late 1990s. By matching individual Unemployment Insurance records with individual respondents in the Household Survey, the authors unearthed characteristics of the workers most likely to show up in one survey yet be missed in the other, and conclude that most of these workers are on the margins of the income and education spectra. For example, poor recent immigrants working under the table and highly educated consultants might both be missed by the Establishment Survey but included in the Household Survey.

But that example should not give Household Survey enthusiasts false hope. The study demonstrates that divergences between the Current Employment Survey (aka the Establishment Survey or Nonfarm Payroll) and the Current Population Survey (aka the Household Survey) are "cyclical phenomenon," with the CES outpacing the CPS during business-cycle expansions, and then falling back during recessions and the early stages of recoveries. The 60-year history of the ratio between the two surveys graphed below shows this clearly. (Take that, Kudlow & Co.) Also note that the ratio failed to rise during the most recent recovery, which seems to underscore the ongoing weakness in terms of employment growth.

Based on characteristics of respondents discovered in their study, the authors contend that tight labor markets create a growing number of marginal jobs that often go unreported in the Household Survey, e.g., establishments hiring short-term workers to cover busy periods, which begins to lift the Establishment Survey. As economic conditions continue to improve, workers tend to drop informal jobs (which would be reported in the CPS but not the CES) for formal jobs (that would be reported in the CES), thus widening the gap between the two surveys. These trends then reverse as economic activity falls off, with establishments laying off workers who then turn to informal employment, moving from the CES to the CPS. The graph of the two series since 1994 directly below illustrates this process.

The unusually large and long-lived gap between the two surveys began in 1998 as the Establishment Survey rose well above the Household Survey, and reversed in 2001, when the Household Survey remained stable as the Establishment Survey fell.  The relative pick-up in the Household Survey that got so much attention in the press was the unwinding of the prior trend and not the beginning of a new one. To put some numbers on it, in comparing UI and CPS data the authors found that jobs counted in the UI but not in the CPS grew by 2.3 million between 1996 and 2001, while jobs counted by the CPS and not by the UI grew by just 600K. Between 2001 and 2003, jobs counted by the CPS but not the UI grew by 800K, while jobs counted in the UI but not the CPS fell by 500K.

 So next time any of us, understandably, seeks solace in the Household Survey’s strength when the Payroll Survey disappoints, we need to remember that NBER researchers, who are responsible for officially calling recessions, have determined that such relative strength is indicative of a weakening economy.

NBER Working Paper No. 14805, issued in March 2009, "Exploring Differences in Employment between Household and Establishment Data," by Katharine G. Abraham, John C. Haltiwanger, Kristin Sandusky and James Spletzer, available here (subscription required): http://www.nber.org/papers/w14805.pdf