of the most visible economic issues in this presidential primary
election cycle is the apparent failure of the economy to create
jobs. Even though the U.S. economy has been growing strongly for
over two years, many analysts have focused on an illusion of 2.2
million "lost jobs" since President George W. Bush took office. The
illusion stems from a survey of employment conducted each month by
the U.S. Bureau of Labor Statistics (BLS), officially referred to
as the Current Employment Statistics (CES) survey and commonly
known as the payroll survey.
all surveys, the CES suffers from a number of problems that are
well known to data analysts. However, the payroll survey contains a
unique methodological problem: It systematically overcounts the
jobs held by one person when that person changes employers. The
existence of a potential turnover effect is not new. But worker
turnover is far below its pre-war norm, with potentially large
consequences for estimates of total employment.
paper takes a critical view of the payroll survey and finds
- The payroll
survey double-counts many workers who change jobs and is now
artificially deflated because job turnover is down.
Decelerating turnover in 2002-2003 explains up to 1 million jobs
artificially "lost" in the payroll survey since 2001.
- The BLS
household survey indicates record high employment. The
disparity of 3 million jobs (in employment growth) between the
household and payroll surveys since the recovery began is
- The disparity
between the two BLS surveys of total employment is
cyclical. The disparity widens during recessions and
narrows during periods of rapid growth in gross domestic product
(GDP). Such variation strongly suggests a statistical bias in one
of the surveys.
- Payroll survey
data are always preliminary. Past revisions have regularly
shown the initial estimates to be off by millions of jobs. For
example, initial estimates of job losses in 1992 were revised in
1993, 1994, and 1995 and now show net job creation.
- The payroll
survey does not count the surge in self-employment. The
household survey has recorded a surge of 650,000 self-employed
workers. This number may be even higher if modern workers in
limited liability companies and in consulting positions with
traditional firms are not identifying themselves as
economic indicators suggest an improving economy since November
2001, except for the loss of payroll jobs according to the CES.
Aside from the payroll survey, most labor indicators suggest an
improving labor market: Real wages are rising, unemployment is low
and declining, and jobless claims are down. The sharpest contrast
is the record high level of total employment: 138.6 million
according to the Labor Department's household survey, formally
known as the Current Population Survey (CPS).
Since the recession ended in November
2001, payroll jobs are down by 716,000 as opposed to a CPS increase
of 2.2 million employed Americans. This 3 million-job mystery can
be resolved through a critical examination of what the two surveys
measure and how those measures should be recalibrated for an
economy that has evolved dramatically. Congress should not be
moving to protect jobs or meddle in labor markets if, as the facts
show, those markets are functioning well. This report reviews the
problems with the payroll survey and highlights two new innovative
data series recently introduced by the Department of Labor.
level of total employment according to the household survey, shown
in Chart 1, is different from the payroll level by definition. For
example, nonfarm payrolls do not count agricultural and
self-employed workers. More important, payrolls will count an
individual twice if he or she works two jobs or changes jobs during
the pay period. Although the two survey employment levels track
closely over time, the gap between them is somewhat irregular.
Chart 2 shows the accumulated increase in
employment in the months after a recession ends and compares the
current recovery period to the two survey levels averaged over the
last five recessions. Trends of job recovery in the different
surveys after the last five recessions appear almost identical,
whereas this recovery has seen unprecedented declines in payroll
employment. With the other economic indicators signaling a normal
recovery during 2003, Chart 2 makes a compelling case that the
payroll survey--not the household survey--is behaving oddly.
Is The Bls To Blame?
statistical and economic staff at the BLS has built a well-deserved
reputation for professionalism and public service, yet the recent
divergence among surveys during a sensitive political season has
led some to cast doubt on the government workers who publish the
data or to question their methodology. But many doubts are
politically driven and are a poor substitute for objective inquiry.
It is unfair to criticize the BLS for the job growth mystery,
especially when the first possible explanation is that both surveys
are behaving normally.
results are puzzling because the surveys are measuring a changing
economy, not because the surveys are any different or less correct
in their methodology. Analysts know intuitively that today's
economy is structurally different from the economy of five or 10
years ago, but the consequences of the new economy are difficult to
predict. Perhaps payroll jobs are weak simply because the modern
company relies less on payrolls for engaging the labor force.
that is the case, the current pattern of declining payroll jobs
alongside rising individual employment makes perfect sense.
However, additional measurements are needed to prove the
fact, without any additional funding or guidance, the BLS quietly
unveiled an innovative data series known as Business Employment
Dynamics (BED) on September 30, 2003. The BED series aspires to
reveal "creative destruction" in labor markets. The BED reports
gross job flows on all new jobs gained and all jobs lost, in
contrast to the net result available in the CES and CPS surveys.
The results are startling and may serendipitously solve the current
mystery of the diverging surveys. More than 7 percent of jobs are
destroyed each quarter, and another 7 percent are created. The
implications of total job turnover and its effect on net payroll
counts are profound.
Conventional Wisdom Prefers the Payroll
is our judgment that the payroll survey provides more reliable
information on the current trend in wage and salary
employment.--Kathleen P. Utgoff, Commissioner, Bureau of Labor
Analysts of U.S. labor markets have
usually preferred the payroll survey data over the household survey
data. Since the two total employment series have generally moved in
tandem, there was little need even to question the payroll data. In
fact, the large swings from one month to the next in CPS employment
estimates made them less useful for forecasting. However, the
widening divergence in the two series has shaken the conventional
numerous occasions, the BLS has reaffirmed the reliability of the
payroll survey, especially for comparisons of employment levels
over time. Other respected observers, including economists at the
Federal Reserve and Congressional Budget Office (CBO), have also
expressed a preference for the payroll survey. A recent paper by
Elise Gould of the Economic Policy Institute makes one of the
strongest cases for the orthodox view and serves as a good baseline
for conventional errors in the conventional wisdom. The rationale for
favoring the CES payroll series is often repeated in the media and
boils down to three seemingly clear and compelling arguments:
Rationale #1: The household survey is
rationale is fundamentally a critique that the CPS is not designed
as a time series. Gould says, "The household survey is extremely
volatile, indicating its inadequacy for analyses of month-to-month
employment trends," which she attributes to its "smaller sample
size." But the experts at the Labor Department assert that the CPS
is designed as a time series, notably ratios like the unemployment
rate and the employment-population ratio.
However, level estimates like total
employment and the size of the labor force reported in the CPS are
extrapolated based on population estimates and are consequently
subject to large annual adjustments to the Census Bureau's
population estimate. Footnotes in the Joint Economic Committee's
Economic Indicators warn that civilian employment levels from the
household survey are "not strictly comparable with earlier data." Comparability is
problematic because the annual fix gets lumped into the month of
January for every year. Those adjustments could be smoothed over
each month of the year if the goal was to make the series
comparable over time. Until now, the BLS had no incentive to do so,
especially because the payroll survey was already serving as the
time series to watch.
high variability on a month-to-month basis is a concern, but
critics should take care to understand its real cause. High
variability in the CPS, beyond the January population spikes, is
not a result of a small sample size. Instead, the rotating nature
of the CPS sample drives its variability. One-quarter of
respondents are rotated out of the survey each month, which keeps
the survey respondents fresh. The overriding advantage of the
household survey is its direct interface with American workers,
which makes it a higher quality measure in many ways.
While high variability might rule out
relying on the household survey for short-term movements, it by no
means disqualifies it for longer periods. Considering that the
divergence controversy spans the three years since the recession
began in March 2001, holding the short-term variability rationale
against the household survey seems to be a stretch.
Rationale #2: The sample size is much
larger for the payroll survey.
Payroll numbers are based on a much wider
sample than the CPS, covering one-third of all U.S. workers every
month. Moreover, CES survey results are confirmed and updated
annually by benchmarking the data to records for all U.S.
businesses that file unemployment insurance papers. The result is
nearly complete coverage of the U.S. workforce, or 98 percent of
all jobs. The household survey has a smaller sample of 60,000
brief introduction to statistics would confirm that a survey sample
of 60,000 is more than adequate. Much smaller samples are used
every day in media polls assessing everything from voter attitudes
to consumer product ratings, and they are perfectly valid.
danger in the "payroll survey is bigger" rationale is mistaking
quantity for quality. True, the CES has a bigger sample--but of
payroll survey is largely automated. Companies in the sample file
their payroll figures based on computer software that simply counts
up the number of unique payroll recipients each pay period, whether
an employee works for one day or 30. A waiter who works at five
establishments in one pay period will be counted as five jobs.
Meanwhile, self-employed and agricultural workers are not on a
payroll and are left uncounted by the CES. If modern companies are
employing fewer workers on traditional payrolls, the CES is not
currently designed to take such a trend into account.
Rationale #3: The payroll survey has a
stronger relationship with GDP.
forecasting GDP growth is the goal, then 50 years of research
suggest that the payroll survey is preferable because of its proven
high correlation with GDP. This rationale is not one used in public
debates, but it may be more important than anything else for
academic economists and Wall Street analysts. Billions of dollars
ride on the accuracy of economic forecasts.
what if the payroll-GDP correlation is an illusion of revised data?
While the historical CES employment series has an indisputably
strong relationship with growth rates, those historical data have
undergone multiple revisions. An even bigger concern is whether the
strong relationship is due to an internal statistical bias.
Economists should be very careful to check for an endogenous
influence of growth rates on payroll counts.
Analysts Confounded by the Divergence
analysts have reviewed the survey divergence, and it remains one of
the most fascinating economic mysteries of the modern recovery.
However, policymakers, who rely on simplicity and certainty, have
an intuitive need to select a favorite of the two surveys. The CBO
weighed in with its August 2003 Economic Outlook, stating:
The establishment survey better reflects
the state of labor markets, the CBO believes, not only because
other indicators also imply rather weak labor-market conditions but
because large revisions or misreporting appears less likely for the
establishment than the household data.
Bernanke, a prominent academic economist and recently appointed
Governor of the Federal Reserve, commented on the survey disparity
on November 6, 2003. His views are a fair reflection of the
academic economists, and he confesses, "[W]e do not fully
understand the differences in employment reported by the payroll
and household surveys, and the truth probably lies in between the
two series." Nevertheless, Bernanke was quick to emphasize the
conventional wisdom that "greater reliance should probably be
placed on the payroll survey."
many serious investigations into the details have been unable to
solve the mystery. The BLS reviewed the disparity in a major study
for its October 2003 Advisory Committee, concluding, "To date, BLS
has not been able to pinpoint a source or sources of these
differing trends in employment growth." More recently, the February 2004
Economic Report of the President noted that "the explanation for
why these two surveys' results have diverged so markedly over the
last few years, and what this might indicate about the economic
recovery, remains a puzzle."
Clearly, the tide is turning, and many
analysts are reconsidering the conventional wisdom. As the months
go by, the payroll data are growing seriously out of step with
other indicators, such as higher real earnings, booming hiring
indices, and declining jobless claims. (See Table 1.)
Leading the turnaround, the CBO's January
2004 Economic Outlook modified its earlier support for the payroll
survey, suggesting that "it is less clear which survey provides a
more accurate picture of labor market conditions in the second half
of 2003." The CBO notes that tax withholding also seems to be
consistent with stronger employment growth.
Smoothing the Household Series
the divergence between the surveys has grown, analysts have become
increasingly frustrated that the household data are not comparable
over time because of the population adjustments that are lumped
into the January data for every year. The Joint Economic Committee
recommended a process for smoothing the adjusted population level
over the entire time period and produced a comparable household
employment time series in late 2003.
response, the BLS recently published two briefs that describe a
process for making incremental population adjustments to the
The first brief, "Creating Comparability in CPS Employment Series"
by Marisa Di Natale, was published in December 2003 and is the
BLS's first effort to make its household series on total employment
comparable across different months. The second paper was published
on the BLS Web site on February 6, 2004, and offers, for the very
first time, a smoothed total employment CPS series dating back to
innovation allows analysts to use CPS measures of employment growth
in the same manner that the payroll numbers are used each month. It
also eliminates the key rationale against household survey
The Divergence in Surveys Is
the new, comparable household employment data, this report presents
a side-by-side comparison of employment growth unclouded by
population spikes. This new view confirms previous suspicions that
the present divergence in job growth between surveys is
unprecedented. The last five recessions experienced survey
discrepancies, but nothing like the 3 million-job divergence of
recent years. In fact, the household survey outpaced the payroll
survey by around 500,000 jobs in three of the last five recoveries,
while payrolls surged faster in the other two recoveries. But the
divergence has never before reached this magnitude.
Interestingly, a historical view of the
two series reveals that the total employment gap has widened and
narrowed with regularity over the years, suggesting a relationship
between the disparity and the business cycle.
Chart 3 shows the total level of civilian
employment (from the household survey) minus the total nonfarm
employment (from the payroll survey). The household survey count is always
higher because it includes some categories of workers that the
payroll survey does not. Obviously, payroll counts only nonfarm
jobs on business payrolls (with corporate benefits like health
care), while the household measure includes every American who says
he or she has a job. The disparity makes some sense then, but a
change in the survey disparity, especially a divergence that
follows the business cycle, raises questions. Which survey is
mis-measuring the economy?
can see that the disparity has been trending downward since 1948,
which is probably a reflection of the net decline in farmers. The
curious cyclical movements are three sudden declines in the early
1950s, mid-1960s, and mid-1990s. The only sharp increase in the
disparity has occurred during the past three years. Economic
expansions mark the three periods when the gap declined.
2000-2003 spike in the survey disparity clearly coincides with the
current recession and recovery. The question, then, is whether this
recovery is somehow unique. First, the late-1990s stock and dot-com
bubbles coincided with high worker confidence and high job
turnover, and this inflated payroll counts. Second, the recovery in
late 2001 began immediately in the wake of terrorist attacks on
America followed by two wars. Turnover has not recovered because
employees are expressing a preference for job stability over job
movement, and this deflates payroll statistics.
little noticed study published in 1999 supports this line of
Economists Chinhui Juhn and Simon Potter at the Federal Reserve
Bank of New York were concerned about the growing divergence
between the two employment surveys. It may come as a surprise from
today's perspective, but the concern then was that payroll jobs
were growing much faster than the number of workers in the CPS.
Faced with the inverse of today's puzzle but lacking any clear
solution to the divergence, they pointed to a potential error in
population estimates underlying the household survey. Analysts now
know that population adjustments still leave much of the survey
divergence unexplained and that the jobs gap "bubble" of 1999
mirrored the stock market bubble. The question remains: How much was a
bubble of real jobs and how much was a statistical illusion?
Problems with the Payroll Survey:
conventional wisdom that the CES is superior for month-to-month
trends has one major drawback: Monthly payroll data are
preliminary. For example, the initial payroll number for December
2003 was a meager 1,000-job increase; yet it was revised up to
16,000 after one month and will be revised again. Since January
1990, 15 percent of preliminary CES reports that showed job growth
were later revised to show job losses (or vice versa).
following disclaimer accompanies every month's Employment Situation
[I]n the establishment survey, estimates
for the most recent 2 months are based on substantially incomplete
returns; for this reason, these estimates are labeled pre-liminary
in the tables. It is only after two successive revisions to a
monthly estimate, when nearly all sample reports have been
received, that the estimate is considered final.
Thus, while the payroll survey may
eventually be better for month-to-month analysis of the economy in
retrospect, it is by no means appropriate for real-time
Preliminary revisions are not, in fact,
the end of the story. Even after all the establishment responses
are submitted for the CES, the final estimate is still based on a
sample, not on the entire universe of establishments. Those
estimates are significantly revised once per year when the
comprehensive universe of payroll employers is incorporated into
result of benchmarking is another lesson in caution, as
post-benchmark CES data are usually--not rarely--quite different
from the pre-benchmark series. Chart 4 shows the dramatic
difference between preliminary estimates of total U.S. jobs and
current estimates. During the early 1990s and 2000s, payroll jobs
were overestimated, and during the mid-1990s, they were
underestimated, often by 1 million jobs.
The Myth of a
Jobless Recovery in 1992
The critical months of the 1992 presidential campaign
coincided with a string of erroneous payroll survey reports.
Although the recession was officially over as of March 1991, jobs
continued to erode according to the payroll survey. In April 1991,
total nonfarm employment was a preliminary 109.3 million. Today,
that number is listed as 108.5 million. In October 1992, the
payroll count was announced as 108.4 million, and voters went to
the polls with that number in mind. It was called a jobless
recovery and blamed on President George H. W. Bush. But today, the
October 1992 payroll survey measure of total nonfarm employment is
listed as 109.0 million.
CES was overestimating total employment in the early months of the
1991-1992 recovery by 700,000-860,000 jobs, but underestimating in
the last five months of 1992 by 235,000-522,000. Interestingly,
corrections were made not just during the initial benchmarks, but
also in 1993 and 1994 and even in later years.
Fair-minded observers should recognize
that the payroll survey methodology is not to blame for the snafu.
Rather, the problem was traced back to errors in unemployment
insurance records, which have since been fixed.
one hand, the peculiar situation is a reminder that
statistics--especially survey data--are not ultimate truth and are
prone to bugs. On the other hand, one would then expect 1992's
situation to be unique. It is not.
A History of
Large Revisions in Payrolls. The variance of 1992 payroll
reports was not unique. Table 3 summarizes the differences between
originally reported data and current revised data. The first column
reports the average difference for the 12 months of each calendar
year, where error equals the preliminary estimate of payroll jobs
minus the current estimate of payroll jobs. In 1990, for example,
initial payroll counts were overestimated by an average of 883,800
Oddly, the average error for 1992 was much
lower, typically an underestimation of 79,000. However, an average
may be misleading: Half the months could have positive errors of
200,000, and the other half could have negative errors of
second column in Table 3 reports standard deviation, which is a
measure of monthly error variability over a given year--not
variability from one month to the next, but from the typical
month's preliminary estimate to the revised current estimate. The
year 1992 saw the highest standard deviation in payrolls (512,600),
while 1991 data were relatively stable. However, high variability
is the rule, not the exception, and is thus a concern for anyone
relying on real-time payroll data.
lessons are that preliminary data are not final, final data are
subject to annual benchmark revisions, and a single year's
benchmark is not the end of seasonal adjustments. And there is
always the odd case like 1992, in which a statistical error
corrupts the data. In its defense, the BLS has made great strides
in 2003 in updating its methodology--primarily by changing to what
is called a probability sample--to avoid large future revisions.
This should remind any observer that current methodologies are not
written in stone.
bottom line is that either the current payroll data will be revised
significantly or they will not. If they are revised, the CPS is
essentially vindicated. The more intriguing possibility is that
there are structural problems within the payroll survey that have
only just now surfaced in the wake of the odd recovery of the "new"
economy. If this is the case, then the payroll numbers will not be
revised in the traditional sense. The loss of payroll jobs may be
permanent as the workforce shifts to new forms.
Problems with the Payroll Survey:
the debate over the survey disparity has unfolded, most observers
have focused on the definitional case against the payroll survey.
However, most attempts to refine the apples-to-oranges comparison
into an apples-to-apples comparison miss the heart of the matter.
This is not a case of a household survey that counts all workers
(traditionally employed plus self-employed) versus a survey that
counts only payroll jobs (traditionally employed). Instead, it is a
case of a new class of workers who have consulting contracts, are
not counted on payrolls, and still see themselves as traditional
can think of the payroll survey as counting all the "brown-eyed"
workers at traditional firms, plus an extrapolation of the
"blue-eyed" workers at start-ups who do not yet have payroll
records. It does not count "green-eyed" individuals who are
for start-up firms, nobody knows exactly how many exist in the
economy, but the BLS uses a careful process of estimating that
number based on the observable fact that some portion of start-ups
eventually grow into larger, traditional firms. In fact, BLS
Commissioner Kathleen Utgoff addressed the issue when the major
revisions were announced on February 6:
An issue often raised with regard to the
establishment survey is that it might lag in recording a
substantial portion of the job growth generated by new business
for-mation. We do not believe that is the case.
seems that their effort to extrapolate the "blue-eyed" population
of workers performed well during this recovery, though future
benchmarks may revise the totals.
Start-ups should not be confused with
self-employed workers. Economists Brian Wesbury, Allan Meltzer, and Robert Barro have independently suggested a rise in
self-employment as the answer to the divergence mystery.
Fortunately, the CPS specifically asks individuals whether they are
self-employed, and indeed the ranks have swelled in the past two
years. Seasonally adjusted self-employment levels are 647,000
higher than in November 2001. At a minimum, the "green-eyes"
explain 20 percent of the divergence since the recession ended.
Consultant? The problem with CPS counts of self-employment
is that the workforce is evolving. It is by no means clear that
Americans understand self-employment in the same sense that the
government does. For example, a worker who leaves the IBM payroll
and switches to a full-time consulting role with IBM is likely
still to consider himself or herself an IBM employee. Certainly,
the worker's family is likely to misidentify the worker's role as
employed rather than self-employed. Likewise, partners at a limited
liability company (LLC, a new company form) often consider
themselves traditional employees when the government classifies
them as self-employed partners.
Internal Revenue Service first approved the limited liability
company as a form of business organization in 1988. The most
current data from Congress report an astounding 719,000 LLCs in
2000, with a growth rate of 34 percent per year. Clearly, the emergence of a
"hazel-eyed" workforce is at hand--self-employees who consider
themselves payroll "brown-eyes."
is a seismic institutional shift in the structure of the economy.
These kinds of changes imply that the CES levels will seem
artificially low because workers will misidentify themselves as
traditionally employed in the CPS, creating a wider divergence. A
contract worker may no longer have benefits such as health
insurance but may enjoy a higher paycheck. This "hazel-eyed"
misidentification hypothesis gathered a boost from Utgoff's recent
There are other differences between the
two surveys that are more difficult to quantify. We know, for
example, that some independent contractors are not reported as
self-employed in the household survey but rather as wage and salary
consequence of the emergence of a consultant-driven workforce is
that U.S. labor markets are even more flexible--which, ironically,
will improve the economy even as it makes payrolls look anemic.
Sclerotic labor markets lead to higher unemployment rates, and this
new economy is based on labor flexibility.
Another consequence is that statistics
based on payroll counts will experience a level shift. The most
obvious impact has been on productivity growth rates, which
recently accelerated. Since productivity is simply a firm's output
divided by the number of its payroll workers, the logical result of
a reclassification of payroll workers is a boom in the productivity
measure. Consultants are accounted as an expense, not a factor
Quantifying the consultant population is
difficult given existing survey methods. The fundamental problem is
psychological: If Americans have preconceived notions of what
"self-employee" and "independent contractor" mean, there will be
large degrees of misreporting in the CPS.
According to BLS economists, the best
assessment of the new workforce comes from the biennial survey of
Contingent and Alternative Employment Arrangements, most recently
conducted in February 2001, which is regrettably right before the
recession began. The relative size of the alternative workforce did
not change from the 1999 survey, and no comparison to today's
economy can be made because BLS did not have enough funding to
conduct the survey in 2003. Even so, it is no clearer that survey
respondents would identify themselves as independent contractors
instead of self-employees when they maintain a self-image as
rough estimate of "hazel-eyed" workers who misidentify themselves
as "brown-eyed" may be useful. If new self-employed workers
misidentify themselves in the household survey in 50 percent of
cases, then the measured number of self-employed workers should
actually be doubled. That would imply 1.3 million new self-employed
workers, not 650,000. Congress and the BLS should consider
rephrasing some questions on the household survey to begin tracking
this emerging class of workers. In the meantime, awareness of the
modern company structure and modern workforce will help
policymakers to keep "anemic" payroll growth in perspective.
Problems with The Payroll Survey:
final problem with the payroll survey stems from the methodology
that automatically counts payroll jobs, not workers. Consequently,
the payroll survey indicates net job losses when the rate of worker
turnover slows. This will occur even if the total level of
employment is stable or slightly rising.
experts Tom Nardone and co-authors proposed this intriguing theory
in their October 2003 paper:
If a person leaves one job and starts
another during a relatively short time span, they could appear on
both employers' payrolls for the CES reference period. They would
be counted twice.
payroll survey double-counts any individual who changes jobs during
the pay period in which the worker is on two payrolls. Such
turnover overcounting would normally be irrelevant if (1) the
turnover rate was stable over time and (2) pay periods were stable.
But if turnover rates increase or pay periods expand from weekly to
monthly, overcounting will inflate the payroll count of total
is especially interesting because job turnover skyrocketed during
the fast-paced labor markets of the 1990s, when labor demand was
very high. In fact, Nardone and his team cite statistics from the
Bureau of National Affairs showing that "in 1999 employee turnover
reached its highest level in nearly two decades." Economic theory
suggests that both hiring and quits, and maybe even layoffs, are
pro-cyclical. Nevertheless, the BLS researchers did not attempt to
quantify the inflationary effect of turnover on the CES.
critical challenge facing any attempt to quantify the effect of
turnover on payroll jobs is a dearth of data. Labor statistics for
decades focused on whether a person was employed, in what sector,
at what pay, and so on. It is much harder to keep track of a worker
between jobs and over any length of time. Workers who have
plentiful job opportunities were less interesting than the dilemma
of those without. A 2001 paper by Federal Reserve economists Bruce
Fallick and Charles Fleischman noted, "One important flow that has
been poorly measured is the movement of workers from one employer
to another without any significant intervening period of
The payroll survey systematically overestimates the level
of jobs due to turnover, and it likely does so in a manner that
varies with the business cycle. The following equation is a rough
sketch of the process:
where Payrollrecorded is the level of
total nonfarm employment published by the BLS, Payrolltrue is the
actual number of payroll jobs held by individuals, and T is the
amount of job turnover during the month. If turnover has a baseline
minimum level as well as a variable component, the equation
Taking the process one step further, the
variable amount of turnover could be influenced by employer
confidence, worker confidence, GDP growth, and the increased use of
monthly pay periods (as opposed to weekly or biweekly). The result
can be described with:
where the coefficients (á1,
á2, and á3) represent the size of each variable's
effect on inflating the recorded payroll level over the true
payroll level at a moment in time. When workers are hesitant to
change jobs in the early part of a recovery, that effect can be
partially captured by measures of GDP growth rates and lower levels
of consumer-business confidence.
New Data on
Gross Job Gains and Losses
Innovative new data from the BLS on gross job flows can
illuminate the amount of turnover. Interestingly, the BLS has
introduced not one, but two new data series on the gross numbers of
jobs created and lost. These broader views of gross job flows, as
opposed to the more limited data on net job changes in the CES and
CPS, offer a potential confirmation of the turnover hypothesis.
Labor Department recently started reporting a monthly data series
on Job Openings and Labor Turnover (JOLTS) with data starting in
December 2000. JOLTS measures ES-202 establishment data on "hires,
quits, layoffs, discharges, and other separations for the entire
month." In late
2003, the BLS unveiled another new series--Business Employment
Dynamics (BED)--with quarterly data starting in the third quarter
of 1992. Both series confirm that the rate of gross job flows has
decreased during the past five years.
creation actually peaked in mid-1999 at 9 million jobs in one
quarter, declining to 7.5 million in the second quarter of 2003, as
shown in Chart 5. Gross job losses peaked in 2001 and have dropped
back to normal levels. It seems that the problem with labor market
payrolls is not high rates of job loss, but slower rates of job
report accepts the traditional assumption that job turnover equals
the sum of gross job losses and gross job gains. The JOLTS turnover rate presented in
this report equals the sum of the hires rate and separations rate.
The BED turnover rate presented here is likewise a sum of the rate
of job gains and rate of job losses.
Table 4 presents a summary of data on
gross turnover from two different surveys. There are many caveats
to using either JOLTS or BED as measures of turnover, and readers
should realize that these are proxy measures. Gross job flows are
not equivalent to turnover, because flows include departures (due
to retirement, pregnancy, and injury) and new entrants (e.g.,
college graduates and immigrants). But the focus is on changes in
gross flows, which logically are driven by changing turnover
JOLTS and BED data concur that turnover
rates have declined over the past two years, and the BED data show
a peak in 1998 and 1999. JOLTS data show 0.8 percent fewer gross
payroll jobs turned over per month in 2003 than in 2001. The BED
series is quarterly but shows the same decline on a quarterly basis
over the past two years. The BED data go even further back and show
a large decline (1.7 percent) from 1999 turnover rates.
more complex concern with this paper's model of overcounting is
that most pay periods are weekly, implying that the impact of these
turnover rates is overstated by a factor of four or 12 because they
are monthly and quarterly measures, respectively. If this were the
case, one might think that the monthly JOLTS turnover would be
one-third of BED turnover and that the change in rates would also
be one-third as large. Instead, the decline in turnover rates is
identical in both series in 2002 and in 2003. This implies a
similar decline in turnover rates over any period. Nevertheless,
the impact on payroll counts is muddled because the CES asks
establishments to consider only the payroll period that includes
the 12th day of the month. Hence, the decline in turnover would
only potentially overcount a quarter of turnover cases per month,
assuming (1) no response error by establishments and (2) no
overlaps beyond the day of job change.
Common sense suggests that workers prefer
no break in employment, especially if employment carries health
insurance. One can even argue that the predominance of weekly pay
periods mixed with payroll overlaps would heighten the degree of
overcounting in the CES. This is mostly a speculative debate until
researchers can help clarify the re-employment behavior of workers.
The model presented below uses simple and clear assumptions in
order to introduce the payroll survey's problem with
What is the impact of lower turnover on job counts? The answer
depends on the rate at which departing workers are replaced (or,
alternatively, the rate at which departing workers find new jobs)
within the typical pay period. Calculating payroll deflation is a
re-employment rate is difficult to specify. By definition,
re-employed workers in the context of this model are never
categorized as unemployed during their job transition, so figures
on unemployment and unemployment durations are partially
informative at best.
Research from the Labor Department offers
some clues. One study of 1997-1998 labor turnover showed that the
median duration between jobs for long-tenured displaced workers was
5.3 weeks, and only three weeks for younger workers. We can infer that
most workers are re-employed quickly, especially if they are
younger and are shorter-tenure. Another relevant study found that
baby boomers held an average of 9.8 permanent jobs between the ages
of 18 and 36. Common sense dictates that a majority of separations
are described by workers who take up new opportunities without any
gap of unemployment. The study also found that "more than
two-thirds of these jobs were held in the first half of the period,
from ages 18 to 27."
These two findings imply that
re-employment rates within a pay period are high for a great many
workers and that an 80 percent rate is reasonable. Returning to
Equation 4 and substituting in actual values for the payroll
deflation since 1999 yields:
Thus, the payroll survey may have been
deflated by nearly 1.77 million jobs since 1999 due to turnover
alone. Considering the period since the recession ended, roughly 1
percent fewer jobs are counted per month in 2003 than during 2001,
deflating the payroll survey by 1 million jobs.
Observers should keep in mind that these
calculations are based on only a sketch of the turnover problem,
using the best available data on gross job flows. Critics will
remark that re-employment rates are inexact, but the fact that these rates are also
pro-cyclical suggests a stronger, not weaker, deflation in
payrolls. (See the Appendix.) Nevertheless, the existence of
sizeable payroll deflation is the important point, because this
problem in the payroll survey is simply not in the public
conversation on jobs, and it should be.
implications of decelerating turnover are that:
- A constant-turnover payroll correction
would increase January's total nonfarm employment from 130.1
million to about 131.1 million, using a 2001 baseline for turnover
rates. The illusion of 716,000 payroll jobs lost during the
recovery becomes instead a gain of 300,000 jobs.
- If worker confidence returns to its normal
levels of the 1990s, more workers will be willing to change jobs
and the payroll count will re-inflate.
are workers not changing jobs as frequently two years into the
recovery? The likelihood is that many factors are reinforcing one
another. First, economic studies show that turnover declines during
a recession. Worker anxiety is probably heightened now more than
usual by pessimism prevalent in the media. Certainly, the
perception of losing jobs to workers in Mexico, India, and China is
more profound than in previous eras.
is non-economic factors, however, that make this era unique. The
attacks of September 11, two wars in the Middle East, and constant
terrorism alerts all generate psychological insecurity, which
logically affects employment decisions. Americans are likely to
place more emphasis on stability and other priorities as opposed to
career opportunities during these times.
payroll survey may be systematically undercounting job growth,
creating an unprecedented job growth gap between its total
employment measure and the household survey's. In the past six
months, the BLS has approved new techniques to smooth the household
survey's measure of total employment in order to make
month-to-month comparisons. Analysts can now point with confidence
to the employment of a record number of Americans as of January
2004 and the employment of an additional 2.2 million workers since
the recession ended.
has the payroll survey missed so much recent job creation? The BLS
is skeptical of the start-up explanation, and recent benchmarks
confirm the BLS's position. Self-employment is a different matter,
and the latest statement by the BLS commissioner confirms the
appearance of a new class of contractors. The evolution of the
workforce--specifically, the demographic emergence of consultants
and contractors who do not consider themselves self-employed--is a
likely wedge between the surveys. Self-employment has grown by over
600,000 in two years, and misidentification by the LLC and
consulting workforce implies a much higher number.
Finally, a new hypothesis quantified in
this report is that decelerating turnover is artificially deflating
company payrolls, creating an illusion of 1 million jobs lost since
2001. The heightened insecurity since September 11, the Iraq war,
and the specter of outsourcing are logical explanations for reduced
turnover. Here again, innovative new data series on employment
dynamics from the BLS allow economists to confirm this
Policymakers and analysts should treat
payroll data with caution when making comparisons to employment
levels in 2001 and earlier years. Contrary to the conventional
wisdom, the best measure of job growth now comes from smoothed
total employment reported in the household survey. Consequently,
policies aimed at protecting illusory lost jobs are ill-advised.
Employment in America is rebounding strongly, and the increasing
dynamism of U.S. job markets should not be clogged by misguided and
Ph.D., is Research Fellow in Macroeconomics in the Center
for Data Analysis at The Heritage Foundation.
Appendix: Technical Note on
Payroll Overcounts Due to Turnover
more complex approach to payroll overcounts due to turnover would
incorporate re-employment rates that vary over time. Because the
aggregate re-employment rate within a pay period is pro-cyclical,
it will amplify the cyclical overcount in the payroll survey.
better model of overcounts would also divide the turnover rate in
half in order to correct the double-count of job-changers rather
than ignoring them altogether. This approach would use the
following equation to calculate payroll inflation every year and
where T is the monthly turnover rate and R
is the average re-employment rate within the pay period.
As utilized here, the re-employment rate is defined as
the ratio of workers who are employed at a new job within the same
pay period of their old job. This assumes that most
employer-to-employer transfers are not interrupted by unemployment
spells or departures out of the labor force, but are voluntary
movements to an immediately better opportunity. In those cases, the
worker will appear on two payrolls in a single pay period. There
are also many cases where a transitioning worker will appear on
both payrolls for multiple periods, but these considerations are
excluded here. The basic re-employment rate can be described
where EE is the number of workers who move
from employment to employment during the pay period, EU is the
number moving to unemployment, and EN is the number moving to "not
in the labor force" status. Thus, the denominator represents total
separations. Here the simplifying assumptions are that all EE job
transitions have a single payroll overcount (realistically, some
will have no overcounts and some will have multiple overlapping
payrolls) and that all EU and EN transitions are defined completely
by a spell that outlasts the pay period.
paper assumes a re-employment rate of 80 percent within a monthly
pay period. Using CPS data from 1994-2000, Fallick and Fleischman
estimate R to be around 40 percent. Their paper does not offer a time
series for re-employment rates. While the 80 percent rate used here
may seem high, it is based on assumptions derived from Labor
Department research. Furthermore, this does not calibrate for
multiple payroll overlaps.
model that incorporates half turnover and changing re-employment
rates yields results similar to the simple model presented in
Equation 4. Calculation of the "complicated" model indicates that
payroll jobs were inflated as shown in Table 5. The net effect is a
1.3 million-job deflation since the recovery began (a deflation of
2.0 million since 1999), higher than the simple model.