Employment & Productivity

How is the non-farm payroll tracking the most complete data?

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.

The start-up bust: it’s credit and the housing collapse in the short term; education, health insurance and immigration in the long

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.




When will it ever end, aka, potential subscribers take note.

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.

Months to Trough in Employment Employment Growth, year-to-year
  peak in claims, yty cycle level growth claims peak year later swing
Dec 69-Nov 70     Apr 70 7 7 7 1.8% -0.4% -2.3%
Nov 73-Mar 75 Nov 74 4 5 7 0.4% -0.7% -1.2%
Jan 80-Jul 80 May 80 2 2 2 0.7% 1.0% +0.3%
Jul 81-Nov 82 May 82 6 7 5 -1.3% -0.5% +0.8%
Jul 90-Mar 91 Feb 91 1 3 3 -0.6% -0.4% +0.2%
Mar 01-Nov 01 Oct 01 1 22 4 -0.7% -0.7% +0.0%
average 4 8 5 0.1% -0.3% -0.4%

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.

The Envelope Please: NBER Study finds ratio between Establishment and Household Surveys to the Cyclical

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

Calculating the Unemployment Rate

Recently several news pieces have made the claim that if the unemployment rate were calculated as it was during the Great Depression, the current rate would be close to double what it is, and creeping toward the formidable rates back in the 1930s.


The first problem with this statement is that there was no official unemployment rate until the 1940s. The ones we use today were reconstructed after the fact. As unemployment ballooned during the Great Depression a number of ad hoc attempts were made to calculate the rate, and the widely divergent results led private researchers and some state and local governments to experiment with various sampling methods. In 1940 the WPA began publishing statistics on those working (the employed), those looking for work (the unemployed), and those doing something else (hiding under the bed perhaps?) and so not in the equation.*

The second problem with the statement is that it's just not true. Although the BLS has refined their surveys and made questions more specific, conceptually the unemployment formulas have not changed, and the BLS's own analysis of test data shows that the impacts of several sets of changes on the overall numbers are minor.

In 1962 high unemployment and two recessions in three years led to the formation of The Presidential Committee to Appraise Employment and Unemployment Statistics, led by Robert Gordon, and tasked with reassessing the concepts used in gathering labor-market data. The Committee gave high marks to the BLS's integrity and suggested some improvements. For several years the BLS tested new survey techniques before instituting a number of changes in 1967.

Among the most important of these were the requirement that workers must have actively sought employment in the last four weeks in order to be classified as unemployed.  A contact at BLS agrees that some discouraged workers were probably counted as unemployed before this change was made, but the effect of this migration is small. As they generally do, the BLS ran the new definitions alongside the old, in this case for 2.5 years, before adopting the new.  Although the test series is not entirely comparable with the new series, the overall unemployment rate in the new series dropped by just one-tenth of a percent and, within that, the rate for adult men was down 3/10th, up 4/10th for adult women, and off a full point for teenagers.  (Maybe they were just being teenagers: the requirement that they give a concrete example of their job search may well have reminded them of their parents and got the blank stare.) The Committee also recognized the need for more detailed data on persons outside the labor force, who are highly sensitive to changes in labor demand, and the BLS began collecting information on those who wanted a job although they were not looking for work in 1967.

In 1976, in order to provide more information on the hidden unemployed (who would presumably be part of the labor force in a full-employment scenario), the BLS first published the original U1 to U7 tables, which break out marginally attached workers.  These tables were revised in the 1994 redesign (becoming U1 to U6) and the controversial requirement that discouraged workers must have sought work in the prior year was added. This change halved the number of discouraged workers, resulting in a complete break in the time series.

But those workers can still be found in the U-6 series, which is the broadest measure of labor underutilization, and it ain't a pretty sight. Up 4.8% over the year, U-6 currently includes an ugly 13.5% of the labor force. Update: In February U-6 unemployment rose to 14.8%. There's no need to fool around with the official unemployment rate (U3) to get an accurate picture of how quickly our labor market has deteriorated: the U1 to U6 tables tell the story.

Update 03/14/2009
In response to a reader's comment:

There are three unemployment series available for the early 1930s: Stanley Lebergott’s, Michael Darby’s reworking of the Lebergott series, and the G.H. Moore series, available through NBER. (Michael Darby is the economist who pointed out that the Lebergott series included those on work-relief as unemployed. His series moves them to employed.) We used Moore’s series, which pretty much splits the difference between the other two. When you combine different series, usually necessary for long-term views, the series breaks themselves produce spikes or dips. Splicing the Darby series to the official BLS data makes it look like the unemployment rate jumped in 1940, which we did not want, and Lebergott’s inclusion of those on work relief as unemployed was in line with 1940 census practice.

Here are the yearly averages for the three series:

  Moore Lebergott Darby
1929   3.2% 3.2%
1930   8.7% 8.7%
1931   15.9% 15.3%
1932   23.6% 22.9%
1933 23.4% 24.9% 20.6%
1934 19.1% 21.7% 16.0%
1935 17.6% 20.1% 14.2%
1936 14.2% 16.9% 9.9%
1937 12.2% 14.3% 9.1%
1938 18.4% 19.0% 12.5%
1939 16.3% 17.2% 11.3%
1940   14.6% 9.5%

Basically, if you want to evaluate the effect of government work programs, compare the Lebergott series to the Darby series. If you want a more readable trend line (while avoiding accusations of playing politics) use the Moore series.

For more information and some notes on definitions, please see “Employment and Unemployment in the 1930s,” by Vanderbilt economist Robert A. Margo, available here: http://fraser.stlouisfed.org/docs/MeltzerPDFs/maremp93.pdf

Philippa Dunne and Doug Henwood

*There is currently a bit of a fracas over the reconstructed unemployment rates for the period prior to official series. Stylish Stanley Lebergott, the BLS economist who put together the most widely used series, categorized workers on emergency relief as unemployed. In the 1980s data reclassifying these workers as employed were released, a definition in line with current practice and more widely accepted. In the past month or so, those wishing to show the WPA programs did little to alleviate unemployment have been relying on the unrevised Lebergott series, and those taking the opposite view the revised data. Of course, if you compare the two series it appears that between 1934 and 1941 WPA projects took 2 to 3.5 million workers off the unemployment roles, and shaved the rate by 4 to 7 percentage points.