Monthly Labor Review February 2006 23

Employment Measures

The monthly BLS “Employment Situation” news release

includes two distinct employment measures

from two different surveys; although these measures

track well over the long term, occasional differences

in trend have confounded labor market analysts

Understanding the employment

measures from the CPS and CES survey

Mary Bowler

and

Teresa L. Morisi

Mary Bowler and

Teresa L. Morisi are

economists in the

Office of Employment

and Unemployment

Statistics, Bureau of

Labor Statistics. E-mail:

bowler.mary@bls.gov

or morisi.teri@bls.gov

Each month, the Bureau of Labor Statistics

(BLS, the Bureau) releases data on current

employment in the “Employment Situation”

news release. The data come from two different

surveys: the Current Population Survey (CPS), also

known as the household survey, and the Current

Employment Statistics (CES) survey, also known

as the establishment or payroll survey. These data

are important indicators of the strength of the labor

market and provide an early snapshot of the state

of the Nation’s economy.

Although both surveys measure employment

in the United States, they have different definitions

of employment, along with different samples, estimation procedures, and concepts. Despite these

differences, the two series track well together over

long periods; at times, however, their rates of

growth or decline differ significantly. These diverging movements in employment between the two

surveys have been researched in the past. Most

recently, they gained prominence in the mid- to late

1990s and during the recession and recovery from

2001 to 2004.1 In the mid- to late 1990s, employment

from the establishment survey grew faster than

employment as measured by the household survey.

During the recent recession and postrecession

period, establishment survey employment declined for a number of months after the end of

the recession, while household survey employment expanded.

Why do these two employment surveys sometimes give different pictures of the labor market?

There are a number of differences between the

two surveys that can be quantified. Other areas

of difference, however, are more difficult to measure.

This article discusses the various differences and

suggests reasons those differences may or may

not affect the divergences between the two employment series. The first portion of the article offers a

general background on the two surveys and a

summary of past research into earlier divergences

in the 1960s, 1970s, and 1980s. The second portion

examines the latest BLS research into the divergences in the mid- to late 1990s through 2004.2

The two surveys

The CPS and the CES survey are monthly sample

surveys; the CPS is a household survey, while the

CES survey is a survey of businesses as well as

government establishments. (Exhibit 1 summarizes

the key features of the two surveys.) With a sample

of about 60,000 eligible households, the CPS covers

the U.S. civilian noninstitutional population aged

16 years and older. The survey results are collected

for the Bureau of Labor Statistics by the U.S.

Census Bureau. Interviewers from the Census

Bureau contact households and ask questions

regarding the labor force status of members of the

household during the calendar week that includes

the 12th day of the month. The broad coverage of

the CPS encompasses not only wage and salary

workers, but also the self-employed, farmworkers,

unpaid family workers, persons employed by private

households, and workers temporarily absent from

work without pay. The CPS provides information
24 Monthly Labor Review February 2006

Employment Measures

on labor force status by detailed demographic characteristics,

such as sex, age, race, and ethnicity. Data are collected not only

on the employed, but also on the unemployed and on those

persons who are not in the labor force.3

The CES survey is a Federal-State cooperative program in

which the Bureau of Labor Statistics works with State employment security agencies to collect data each month on employment, hours, and earnings from a sample of nonfarm

establishments, including government. The CES survey sample,

which includes about 160,000 U.S. firms of all sizes, covers about

400,000 worksites. The survey counts nonfarm payroll jobs

only—with no age restriction on the employed—and does not

include the self-employed. Businesses report the number of

persons on their payrolls who received pay during the pay period

that includes the 12th day of the month. Workers who did not

receive pay during the pay period are not counted. CES data are

available by detailed industry and geographic area. In addition

to collecting data on employment, the CES program provides

data on average hours paid and average hourly and weekly

earnings for private-sector production or nonsupervisory

workers.

Data strengths and limitations

The CPS has a broad definition of employment and provides

detailed demographic characteristics on individuals by their labor

force status. The CPS includes groups of workers that are not

included in CES estimates: the self-employed, agricultural

workers, unpaid family workers, workers on unpaid leave, and

employees of private households. In addition, the CPS provides

information on the Nation’s workers by sex, race, Hispanic

ethnicity, educational attainment, marital status, and other

characteristics. Finally, the CPS categorizes data by occupation

and industry. While, of course, useful, occupation and industry

information provided by household respondents are more

subject to nonsampling error than are establishment-based

 Comparison of Current Employment Statistics (CES) survey and Current Population Survey (CPS)

 CES survey CPS

• Monthly sample survey of approximately 60,000

 households

• Designed to measure employment and unemployment

 with significant demographic detail

• Reference period is the week that includes the 12th of the

 month

• Only workers aged 16 and older are included

• Employment measure reflects the number of employed

 persons

• Multiple jobholders are counted once

• Self-employed persons are included

• Agriculture sector is included

• Private household workers are included

• Unpaid family workers are included

• Workers on leave without pay throughout the reference

 period are included

• Monthly sample survey of 160,000 businesses and

 government agencies. Firms of all sizes are included

• Designed to measure employment, hours, and earnings with

 significant industrial and geographic detail

• Reference period is the pay period (could be weekly, biweekly,

 monthly, and so forth) that includes the 12th of the month

• Employees of all ages are included

• Employment measure reflects the number of nonfarm payroll

 jobs

• Multiple jobholders are counted for each payroll job

• Self-employed persons are excluded

• Agriculture sector is excluded

• Private household workers (nannies, housekeepers, and the

 like) are excluded

• Unpaid family workers (persons working without formal pay

 in their family’s business) are excluded

• Workers on leave without pay throughout the reference period

 are excluded

Exhibit 1.
Monthly Labor Review February 2006 25

surveys. Moreover, the relatively small sample that the CPS uses

limits the ability of the survey to produce statistically reliable

geographic information below the national level.

The CES survey provides detailed industrial and geographic

information on the Nation’s workers. Approximately 1,200

national series, some down to the most detailed level available

under the 2002 North American Industry Classification System

(NAICS), are generated from the survey. The CES State and area

program provides data by industry for States and more than 270

metropolitan areas.

By design, the CES survey is a highly reliable gauge of monthly

employment change. The CPS is designed to provide highly

accurate rates, including estimates of unemployment rates and

labor force participation rates. At about 60,000, the household

survey sample is much smaller than the CES survey sample.4 As

a result, and because of the design of the CPS, its employment

estimates are subject to a larger sampling error than those of the

CES survey—indeed, about 4 times as large on a monthly basis—

and so are more volatile than estimates derived from the latter

survey. In order for a change to be statistically significant, larger

over-the-month changes are required in the CPS series than in

the CES series.

The CES employment estimates are benchmarked annually to

universe counts. Benchmarking is a regular “anchoring” of the

estimates to universe counts of employment. The universe

counts are derived from administrative data from the State

Unemployment Insurance (UI) system and are collected by the

Bureau of Labor Statistics for the Quarterly Census of Employment and Wages (QCEW) program (also referred to as the ES-202

program). The QCEW data cover about 97 percent of nonfarm

employment. The Bureau uses various sources to benchmark

the remaining nonfarm employment that is exempt or partially

exempt from UI coverage. CPS employment estimates, by contrast,

are not directly benchmarked to a universe count, but are controlled to estimates of the civilian noninstitutional population.

The Census Bureau develops the population controls for the

household survey from the decennial census and, between

census years, projects population estimates based on administrative information on births and deaths and Census Bureau

estimates of net international migration. The Census Bureau

conducts an annual review and adjustment of the intercensal

population controls.

Both the CPS and the CES survey publish data on a seasonally

adjusted basis; that is, the data are adjusted for the normal

seasonal variations that regularly occur in certain months during

the year. For example, one kind of seasonal movement that occurs

every year is the hiring of retail workers in December to staff

stores for the holiday season. Seasonally adjusting the data for

normal seasonal movements such as holiday hiring allows nonseasonal movements in the series, such as cyclical, trend, or

irregular movements, to be analyzed.

The CPS conducts supplemental inquiries that are added to

the regular CPS questions asked of households. Often, the supplements are repeated annually or biennially. Topics include

computer use, contingent workers, displaced workers, employment of veterans, volunteerism, and job tenure. The data gathered

from these supplemental surveys provide further insight into the

social, economic, and demographic characteristics of the labor

force.

Recent changes to the surveys

Both surveys underwent major redesigns in the past decade. In

1994, the CPS survey questionnaire was completely redesigned

to utilize computer-assisted interviewing methods, rather than

a paper survey form.5 The new electronic format includes

dependent interviewing techniques, whereby some questions

are based on respondents’ earlier answers, and it also allows

complex skip patterns in the series of questions asked. In

addition, the CPS redesign was intended to modernize the

questions themselves in order to gather better information

about respondents’ employment status. The CES survey underwent a multiyear redesign beginning in 2000 and ending in

2003 that included replacing its quota sample design with a

probability-based survey design and introducing modelbased estimation for business births and deaths. Quota samples are known to be at risk for biases. Probability samples are

designed to ensure a more representative sample and more

accurate estimates. Both the CPS and CES redesigns included

changes suggested by outside experts to address their various

limitations.

The CES survey also introduced a number of changes in

June 2003, in addition to completing the sample redesign and

switching to the birth/death model.6 Another major change

was the conversion to an entirely new industry classification

scheme: the 2002 North American Industry Classification

System (NAICS). In addition, the survey converted from a

seasonal adjustment process in which seasonal factors were

forecasted 6 months in advance to concurrent seasonal adjustment, in which seasonal factors are developed each

month. Concurrent seasonal adjustment is preferable to

forecasted factors because the most current information is

used in the calculations. Furthermore, research showed that

revisions between CES estimates and benchmarked data are

smaller with concurrent seasonal adjustment.7

The CPS also introduced a number of changes in 2003. In

January, it moved to new population controls that reflected the

results of the 2000 census; the new controls raised the estimates

of the civilian noninstitutional population level and, therefore,

increased the estimated numbers of the employed and unemployed.8

 The CPS data from January 2000 through December 2002

were revised to reflect these controls. Another change in January

2003 was the adoption of the 2002 Census Bureau occupational

and industry classification systems, which are based on the 2000

Standard Occupational Classification (SOC) system and the 2002
26 Monthly Labor Review February 2006

Employment Measures

NAICS. The CPS also moved to concurrent seasonal adjustment

in January 2003.9

Methodological and conceptual

differences

There are a number of differences in how employment is counted

in the two surveys. One major difference has to do with counting

jobs as opposed to counting employed persons. Another is how

paid and unpaid workers are counted. There are also special

cases that occur periodically, such as academic faculty in summer

and decennial census workers, for which employment is counted

differently.10

Count of jobs as opposed to count of employed persons. In

the CES survey, the employment estimate provides a count of

all nonfarm jobs. This means that persons working at more

than one job would appear on more than one payroll and thus

would be counted for each job. In contrast, the household

survey provides an estimate of employed persons, and each

worker is counted once regardless of how many jobs he or

she holds.

Reference periods and paid and unpaid workers. The

reference period for the household survey is the calendar

week that includes the 12th day of the month. The CPS counts

a person as employed if the person performed at least 1 hour

of work during the reference week, whether as a wage and

salary worker, as a self-employed individual in his or her own

business or farm, or as an employee of a private household.

Unpaid family workers are counted if they worked at least 15

hours in a family-owned business. Workers away on temporary unpaid absences also are included as employed, falling

into a category known as “with a job, not at work.” This

category includes workers who have a job at which they did

not work during the survey week because they were on

vacation, were ill, needed to take care of family or personal

obligations, were on maternity or paternity leave, were involved in a labor dispute such as a strike, or could not work

due to bad weather.

For the establishment survey, the reference period is the pay

period that includes the 12th day of the month. The pay period

can be weekly, biweekly, semimonthly, monthly, or some other

period. Workers must have received pay for the pay period in

order to be counted, regardless of whether they were present or

on paid leave. Those on paid leave for the entire pay period are

included in the survey, whereas those on unpaid leave are not.

Workers on strike or on other unpaid work stoppages for the

entire pay period are not included in the CES employment

estimates.

Scope of coverage. As previously noted, the CPS has a much

broader scope than the CES survey. The CPS includes the selfemployed, unpaid family workers, agricultural workers, those on

unpaid absences, and employees of private households. The

CES survey is a survey of nonagricultural business establishments, excludes the unincorporated self-employed, and requires

that workers be paid in order to be counted.

Age limit. CPS data on employment are restricted to persons

aged 16 years and older, while there is no age limit on who is

reported to the CES survey. The CPS provides employment data

categorized by age, whereas the CES survey does not have any

details on age for its employment data.

Institutionalized workers. By definition, workers in any type

of institution, such as a prison or a mental health facility, are not

counted in the CPS, because the CPS sample represents the civilian

noninstitutional population. The establishment survey also

excludes workers in prison-sponsored work programs that take

place inside the prison or other institution. However, Federal law

did not specifically exclude prison workers from UI coverage

(and hence from the CES benchmark data) until 1997. It is not

known to what extent prison workers were reported in the

benchmark data, if they were at all, before 1997. Inmates working

outside the walls of a correctional institution are counted by the

CES survey if they are covered by the State’s UI laws.

Persons on active duty in the U.S. military. In the CPS, activeduty members of the resident Armed Forces are considered to

be out of the scope of the survey. Nor are active-duty service

members counted in the CES survey, on the basis of their

employment in the Armed Forces; however, if the service

member also holds a secondary civilian (private-sector) job,

the civilian job is counted in the CES.

Periodic trend differences

Although short-term movements in the two surveys’ employment

measures sometimes differ (see box on next page), their longterm trends track rather well. An effective way to identify the

notable divergences in trend in the two series’ histories is to

chart the ratio of establishment survey employment to nonagricultural wage and salary employment from the household

survey. (See chart 1; as the next section makes clear, the nonagricultural wage and salary series also is a convenient starting

point for reconciling the two surveys.) When the surveys’ trends

are viewed in this manner, some cyclical behavior can be observed: in many, but not all, instances, establishment survey

employment increases relative to household survey employment

during business cycle expansions (that is, the ratio increases),

and household survey employment increases relative to the

establishment survey measure during recessions (that is, the

ratio declines).
Monthly Labor Review February 2006 27

Historically, the ratio has tended to remain within the range

from 1.00 to 1.03, regardless of the business cycle. Brief exceptions occurred in the 1950s and 1960s. A more significant

divergence in the 1990s, however, clearly stands out: beginning

in 1992, establishment survey employment began growing more

rapidly than household survey nonagricultural wage and salary

employment. The ratio moved up fairly steadily and was nearly

1.06 by 2000; the discrepancy was unprecedented in size and

duration.

Comparing and reconciling

employment trends

Despite the numerous differences in the employment measures

of the establishment and household surveys, it is possible to

adjust them to a relatively similar concept for comparison. This

“reconciliation” of the employment measures adjusts household

survey employment to make it look more like establishment

survey employment. As currently carried out by the Bureau of

Labor Statistics, reconciliation involves subtracting the following

categories from total household survey employment: all agricultural and related employment, the nonagricultural selfemployed, nonagricultural unpaid family workers, private household workers, and workers on unpaid absences from their jobs.

This series of subtractions roughly eliminates all major categories

of employment that are not in the scope of the establishment

survey. (Note that the self-employed are specifically taken to be

the unincorporated self-employed; the incorporated selfemployed are considered employees of their own businesses

and therefore are classified as wage and salary workers in the

household survey.)

Next, the number of multiple jobholders whose primary job is

nonagricultural in nature and who are wage and salary workers is

added to the reduced household employment number. This step

is needed because multiple jobholders are counted for each

nonagricultural wage and salary job they hold in the establishment survey. These adjustments result in a household employment estimate with a definitional scope more like that of the

establishment survey measure and one that reflects a “jobs”

concept rather than an “employed persons” concept. This adjusted household survey employment measure can then be better

compared with establishment survey employment to examine

differences in trends between the two. (See table 1.)

It is important to remember that the adjustment of household

survey employment is an imprecise exercise. For example, the

adjustment for multiple jobholders is based only on the classification of those workers’ primary jobs; the classification of

their secondary jobs is not taken into account.11 Because

some of them are self-employed in their secondary jobs (and

hence not counted twice in the establishment survey), this

adjustment somewhat overestimates the multiple-jobholder

effect. In addition, one must bear in mind that a number of

other survey differences—in reference periods, age limits, and

more—between the surveys are not accounted for in this reconciliation process.

The household survey employment adjustment process

just described can be carried out effectively only from 1994

forward. This is because the data on multiple jobholders became available on a monthly basis only following the 1994

major redesign of the household survey. After the nonagricultural self-employed, multiple jobholders represent the

largest adjustment to household survey employment in the

reconciliation process.

In comparing the earlier history of the two employment

measures, the Bureau of Labor Statistics typically uses the

nonagricultural wage and salary employment series from the

household survey, as illustrated previously in the use of the ratio

of establishment survey employment to household survey nonagricultural wage and salary employment. This comparison has

some limitations, but is still very useful.

Previous work on reconciling the surveys

The issue of examining and attempting to reconcile differences

between the household and establishment surveys has existed

for decades. On September 27, 1962, a report from the President’s

Committee to Appraise Employment and Unemployment StaShort-term differences in the

Over-the-month and short-term differences in the two

surveys’ employment measures are not uncommon. These

divergences often result from large monthly swings in

household survey employment, because the household

survey is statistically much more volatile or “noisy” than

the establishment survey. This volatility is due to the fact

that the household survey has a smaller sample and is

designed to optimize the measurement of the unemployment

rate, not the employment level. The establishment survey,

besides having a larger sample, is designed to optimize the

measurement of the over-the-month change in employment

and so provides a much more stable estimate of employment.

To illustrate, from 1994 through 2004, there were 23

months when household survey employment changed by

about 500,000 over the month (using originally published

data and not including months when survey changes

caused breaks in the series). The establishment survey, by

contrast, showed a change of that magnitude only once in

those 10 years (also using originally published data), and

that was due to an unusual weather event: a major blizzard

that affected much of the Northeast.

employment measures
28 Monthly Labor Review February 2006

Employment Measures

tistics was released. Entitled “Measuring Employment and Unemployment,” it has come to be known as the Gordon report,

after Robert A. Gordon, the chairman of the committee. A chapter

in the report compared the employment series from the household

and establishment surveys and noted that, in 1960 and 1961, the

two series moved in opposite directions, with the household

series showing an over-the-year increase of 203,000 while the

establishment survey declined by 270,000. The authors noted

the differences between the two series and created a reconciled

household series for December 1960 by adjusting for (1) dual

jobholders, (2) the 1950 census undercount, (3) postal workers

who were not employed during the CPS survey week (at the time,

CES Federal Government employment figures for the Postal

Service reflected all temporary workers employed during December), and (4) unpaid absences. Before adjustment, the levels were 3.4

million apart; afterwards a difference of 1 million remained.12

The authors concluded that there were a number of explanations for the remaining difference, but few firm facts. They

mentioned the effect of pay periods longer than 1 week, which

should have increased the estimate of the number of multiple

jobholders and job changers on payrolls. The authors also

mentioned that the counts of multiple jobholders from the CPS

may have been incomplete. In addition, some workers who

reported that they were self-employed in the household survey

may have appeared on payroll records as employees. (At the

time of the Gordon report, the incorporated self-employed were

not separated from the unincorporated self-employed in the

household survey. It was not until 1967 that a question on incorporation was added to the CPS questionnaire.) It also was

theorized that the establishment data included some military

personnel, institutionalized persons, persons under 14 years

of age (at the time the household data encompassed those

aged 14 and older), and Mexican and Canadian residents. Finally,

the authors noted that there was a small, but persistent, undercount of part-time and occasional workers in the CPS and that it

was possible (although no evidence existed for the claim) that

the benchmark source used for the CES was overstated.

A number of studies followed the 1962 Gordon report. A

December 1969 article by BLS economist Gloria Green examined

over-the-year differences during the 1962–68 period and attempted to reconcile the annual levels.13 Green reconciled the two series

for 1968 and discussed factors affecting the comparability of the

data. She noted that unpaid absences, multiple jobholding, age

limitations, the Census undercount of 1960, differences in survey

coverage and periods, dissimilar ways of treating academic

faculty, and different sampling and estimating procedures were

all factors in the divergence between the employment series from

the two surveys.14

1948 1952 1956 1960 1964 1968 1972 1976 1980 1984 1988 1992 1996 2000 2004

0.98

0.99

1.00

1.01

1.02

1.03

1.04

1.05

1.06

0.98

0.99

1.00

1.01

1.02

1.03

1.04

1.05

1.06

Chart 1. Ratio of establishment survey employment to household survey nonagricultural wage 

and salary employment, 1948—2004

Ratio Ratio

NOTE: Shaded areas indicate recessions. Data were current as of December 2, 2005.
Monthly Labor Review February 2006 29

In 1979, the National Commission on Employment and

Unemployment Statistics’ report Counting the Labor Force (also

known as the Levitan report) compared employment figures from

the CPS and CES from 1958 to 1978 and reconciled the two series

for the year 1978.15 The authors noted that the two employment

series tracked well between 1958 and 1978, although, during that

period, the CES declined by larger amounts in recessions than

the CPS did and expanded more in recoveries. One explanation

given was that, because of the decennial census undercount

and the resulting undercoverage every month, the CPS gave insufficient weight to the poor, minorities, and other disadvantaged

groups. The authors noted that these types of workers experience the largest employment gains when labor markets tighten,

yet suffer the largest declines in employment when labor demand

is slack.

Later articles by BLS economists John Stinson and Paul Flaim

looked at employment growth over various periods in the 1970s

and 1980s in the household and establishment surveys. A 1983

study by Stinson examined the period from 1981 to 1983, in which

the household survey showed more employment growth than

the establishment survey.16 Data on multiple jobholding were

not available during that time; therefore, Stinson was not able to

include multiple jobholders in the reconciliation. Another study

by Stinson in 1987 covered the 1982–86 period, in which CES

employment grew more than CPS employment, and concentrated

on the treatment of multiple jobholders.17 Data on multiple

jobholding were collected from supplemental questions to the

CPS asked in May of 1980 and 1985. Stinson noted that there was

indirect evidence that the growth in multiple jobholding between

1980 and 1985 likely occurred during the recovery period after

the 1981–82 recession and would have contributed to the gap

between the two surveys. Flaim examined the period from

1982 to 1989, when the CES showed more employment growth

than the CPS.

18 He reviewed the dual-jobholding issue and found

that all of the excess employment growth in the CES relative to

the CPS occurred in services industries, particularly retail trade

and services. He noted that many of the jobs in these two

industries are of a part-time nature, and rapid growth in the

industries would have provided ample opportunities for workers

to moonlight. Flaim also noted the difficulties in estimating the

number of undocumented immigrants and their effect on

population growth. During a period in which undocumented

immigrants increased their numbers, problems with estimating

the undocumented might have led to understated CPS population levels and employment. Flaim looked at individual States

and noted that CES series tended to grow at a faster rate than CPS

series in areas with strong labor demand and that this geographic

pattern supported the hypothesis that the gap between the two

series was related to an increase in multiple jobholding and a rise

in undocumented workers.

All of these studies examined the divergence between the

two surveys and offered reconciliation procedures, but none

came to a definitive conclusion regarding the cause of the

discrepancy.

The discrepancy during the 1990s

The most recent BLS study on the divergence issue was presented to the Federal Economic Statistics Advisory Committee

in 2003.19 The report reviewed the most substantial employment

Adjusting household survey employment to a payroll-type concept, annual averages

Payroll jobs ................................................. 114,291 131,785 17,494 131,826 131,480 –346

Household employment .............................. 123,060 136,891 13,831 136,933 139,252 2,319

Less: Agriculture ....................................... 3,409 3,382 –27 2,299 2,232 –67

Nonagricultural self-employed ........ 9,003 8,765 –238 9,121 9,467 346

Nonagricultural unpaid family

workers ........................................ 131 104 –27 107 90 –17

Private household workers ............. 966 900 –66 694 779 85

Unpaid absences ............................ 1,991 2,017 26 2,021 1,926 –95

Total .............................................. 15,500 15,168 –332 14,242 14,493 251

Plus: Multiple jobholders3 ........................ 6,776 7,124 348 6,934 7,067 133

Adjusted household employment ............... 114,336 128,847 14,511 129,625 131,825 2,200

20001 1994 Change,

1994—2000 Employment 2001

Table 1.

Change,

2001—042

[In thousands]

2004

1 Household survey data for 2000 reflect revised population

controls based on the 2000 census, not as originally published.

Prior to the introduction of the population controls following the 2000

census, the adjusted discrepancy was approximately 1.5 million larger.

2 Changes are based on unrounded data.

3 Multiple jobholders who are nonagricultural wage and salary workers on

their primary job.

NOTE: CPS data for 1994 and 2000 are based on the 1990 census industry

classification; data for 2001 and 2004 are based on the 2002 census industry

classification. Data were current as of December 2, 2005.
30 Monthly Labor Review February 2006

Employment Measures

discrepancy in the surveys’ history, which occurred in the 1990s,

when establishment survey employment growth outpaced the

employment growth measured by the household survey. The

cumulative discrepancy in employment from 1994 to 2000 was

approximately 4.5 million, after a definitional and conceptual

reconciliation like that described earlier was carried out and before

population control revisions to the household survey were

introduced. (Table 1 shows that, after revision of the population

controls following the 2000 census, the cumulative employment

discrepancy between the payroll survey and the adjusted household survey from 1994 to 2000 was 2,983,000—that is, 17,494,000

payroll jobs minus 14,511,000 adjusted household employment.)

The study came to no definite conclusions as to the causes of

the divergence. No complete explanation has been found to date,

either by the Bureau of Labor Statistics or by outside researchers

who have wrestled with the issue. Notwithstanding this frustration, at least one major factor in the discrepancy did come

to light: understatement in the household survey population

controls. In the years between decennial censuses, the population controls for the household survey are based on population estimates that the Census Bureau projects from the

previous decennial census level. These intercensal estimates

are derived from administrative data, namely, birth and death

statistics, along with the Census Bureau’s best estimate of

net international migration. Gauging net international

migration is the difficult part of the intercensal estimation

process, because no data source exists that captures the full

gamut of immigration—most obviously, the number of

undocumented entrants to the United States. When new

population controls based on the 2000 census became available in 2003, they showed that, by January 2000, the intercensal population estimates projected from the 1990 census

base were approximately 2.6 million too low, and as a result,

the household survey employment estimate was understated

by about 1.6 million.20 This understatement in the household

survey population controls explained one-third of the 4.5

million cumulative gap in employment growth between the

surveys in the late 1990s.

Many other possible factors in the 1990s discrepancy were

investigated. In some instances, there was at least limited

information on which to estimate their effect. For other factors,

the Bureau could only speculate. The obvious starting point

was to look at known definitional and conceptual differences

that are not part of the standard reconciliation process. These

factors include an age minimum in the household survey, persons

with more than two jobs, secondary civilian jobs of members of

the Armed Forces, employment among the institutional population, foreign commuters, and differences in the reference

periods of the surveys. For three of these issues—the age minimum, persons with more than two jobs, and the reference period

differences—some information was available from the household

survey to help assess the potential effect.

With regard to the age minimum, the household survey employment estimates include only those aged 16 years and older;

the establishment survey has no such restriction. Therefore, if

an increasing number of teens younger than 16 began working in

the 1990s, that factor might be a cause of the discrepancy. To test

this hypothesis, the Bureau generated estimates of the number

of employed 15-year-olds from the household survey.21 The

estimates indicated an increase in employment among this age

group from 1994 to 2000 (+79,000 over the 6-year period), but not

nearly enough to provide an adequate explanation of the

employment gap between the surveys.

A similar exercise was carried out to estimate the number of

persons with more than two jobs. As discussed earlier, the

standard reconciliation of the surveys adjusts roughly for

multiple jobholders with two jobs; however, it does not account

for those who have more than two jobs. A growing number of

persons with more than two jobs (of a nonfarm payroll nature)

could contribute to the discrepancy. Tabulations of these

persons (not restricted by type of job) from the household survey

indicated very little change (+21,000) from 1994 to 2000,

effectively ruling this factor out as a major contributor to the gap.

BLS research also looked at reference period differences

between the surveys. Because the establishment survey uses a

“jobs” concept, it is possible that a worker who changes jobs in

a short period of time will be counted twice in the survey (once

by the old employer and again by the new employer), in particular

because the establishment survey reference period may be longer

than 1 week for some employers. The Bureau theorized that if

job-to-job movement was picking up during the 1990s expansion,

it could create some upward bias in establishment survey employment. Certainly, anecdotal information about rapid job

changing abounded in the media during the expansion, particularly around 1999–2000, when the job market seemed especially

tight, but data to support this impression were harder to come

by.22 At the time the research was underway—from the late 1990s

into 2000, for example—data from the BLS Job Openings and

Labor Turnover Survey were not yet available. BNA, Inc., a

private news and publishing firm, had (and still has) a turnover

survey, the results of which indicated growing turnover with

a peak in 1999. Regardless, both of these sources have a key

limitation pertaining to this particular research: they measure

job separations and are not necessarily indicative of rapid jobto-job movement.

The best measure of job changing was found in the household

survey: respondents who have been identified as employed in

consecutive months are asked if they still work for the same

employer. This question is used to flag a potential occupation or

industry classification change and is not normally tabulated. It

has been part of the survey since 1994. The Bureau generated

special tabulations of those who answered “yes” to the question

and evaluated the trend since 1994 by looking at these job

changers as a percentage of the total employed. Somewhat
Monthly Labor Review February 2006 31

surprisingly, this job-changing rate did not show any increase

from 1994 to 2000.23 As a result, what had seemed to be a promising explanation for the discrepancy did not pan out. The Bureau

revisited this issue when it evaluated the discrepancy from the

2001 recession forward, and it was estimated that job changing

played a small part. (The next section discusses the discrepancy

after the 2001 recession.)

Three other conceptual differences between the surveys were

examined as well. The first concerned secondary civilian jobs of

members of the resident Armed Forces, which would be counted

in the CES survey, whereas active-duty members of the Armed

Forces are out of the scope of the CPS. On the basis of the

relative levels and steady decline of active-duty military ranks

during the 1990s, the Bureau essentially dismissed this factor as

a possible contributory one. Second, the Bureau looked at

employment among the institutional population—that is, the

prison population. Prisoners working outside a correctional

institution are counted by the CES survey if they are covered by

the State’s UI laws; prisoners are out of the scope of the CPS.

24

Employment among the institutional population, too, was

dismissed as a factor in the discrepancy, given the relative small

number of employed prisoners nationwide.25

The third conceptual difference examined was foreign

commuters. In the CPS, only people who live in the 50 U.S. States

and the District of Columbia are surveyed about their employment status. In the CES survey, only business establishments

located in the United States are surveyed, regardless of where

their employees actually reside. The BLS hypothesis was that if

foreign commuters into the United States were a significant factor

in employment growth, they would be reflected in the

establishment survey, but not the household survey, because

only U.S. households are in the latter’s scope. The Bureau tested

this possibility by comparing employment from the two surveys

at the State level. There was no consistent pattern of discrepancy

among border States, although Texas, Arizona, and Minnesota

had sizeable differences in employment growth between the two

measures. In addition, the Bureau looked at the relative size and

strength of establishment survey employment growth in selected

metropolitan areas near border crossings. Even under the

unlikely assumption that most of the growth in those areas

resulted from foreign commuters, they would have accounted

for about one-fifth of the discrepancy. So although the effect of

foreign commuters cannot be ruled out altogether, it probably

played only a small role at most.26

Other areas of BLS research into the 1990s discrepancy had

less direct information to utilize. Instead, the Bureau attempted

to test various theories with what information was available.

One such exercise tried to shed light on whether undocumented

immigrant workers were a factor. The Bureau cannot determine

the extent to which undocumented workers are reflected in either

survey. However, reports from the Social Security Administration

indicated that the 1990s saw sharp growth in the use of invalid

Social Security numbers on employer payroll records reported to

tax authorities and that these records often were from industries

that commonly employ undocumented workers.27 Given this

finding, the Bureau hypothesized that the establishment survey

might be counting more undocumented workers in its employment measure than the household survey does. The assumption

was that if employers were unknowingly or uncaringly submitting invalid worker Social Security numbers to the Internal

Revenue Service and the Social Security Administration, it stood

to reason that they also would include these workers in their

establishment survey responses or their UI tax reports (which

provide the benchmark data for the establishment survey).

On the household survey side, one could imagine that

undocumented workers might be reluctant to disclose their labor

market activities to the survey interviewer, despite the pledge of

confidentiality that is given to all respondents. In addition,

households with undocumented workers may be more likely to

be missed by the survey sample, or, if these households are not

missed altogether, then not all occupants in the household may

get included.28 What is called “undercoverage” bias may enter

the household survey estimates when households or household

members are missed in the sample. The missed portion of the

sample is reflected in the final estimates when the survey results

are weighted to the population controls; the persons missed will

be assigned the labor force characteristics of their counterparts

who were in the sample. To the extent that the labor force

characteristics of those in the sample differ from the labor force

characteristics of those missed, bias may be present in the final

estimates. Put another way, it is often assumed that those in the

sample have a higher employment rate than those who are likely

to be missed and, furthermore, that the employment patterns of

those who are missed are more cyclically sensitive. Therefore, if,

during an expansion, employment growth was relatively greater

among those missed by the survey, that growth might not have

been fully reflected in the final estimates. Hence, household

employment growth would have been understated.29

Working under these assumptions, the Bureau looked for

evidence of a discrepancy in counting undocumented workers

by comparing household and payroll employment at the State

level. This State employment comparison was examined in

conjunction with the Immigration and Naturalization Service’s

(INS’s) State estimates of the population growth of unauthorized

immigrants. On the one hand, on the basis of INS estimates, a

number of States with large discrepancies—Texas, Florida,

Massachusetts, North Carolina, and Virginia—were believed to

have experienced significant growth in undocumented immigrants in the 1990s. On the other hand, States such as California

and New York did not have particularly large discrepancies

relative to their size, yet were estimated by the INS to be the firstand third-ranked States for undocumented immigration growth.

Thus, the role of undocumented workers in the discrepancy

between the surveys remains unclear.
32 Monthly Labor Review February 2006

Employment Measures

In another issue related to the household survey sample, the

Bureau tested whether the geographic distribution of the sample

might have missed employment growth during the 1990s

expansion. The issue is that, although the household survey

sample is designed to be nationally representative, it does not

include all U.S. counties. The Bureau reviewed county-level data

from the QCEW program (the establishment survey benchmark

source) to see if employment growth in the counties that were

excluded from the sample was greater than those which were in

the sample. The growth rates of the counties in and the counties

out of the sample compared favorably, and in fact, the rates were

somewhat higher in the counties that were in the sample.

Consequently, the Bureau dismissed the geographic distribution

of the household survey sample from having played a role in the

1990s discrepancy.

The Bureau also looked at various types of response error

that might occur in the two surveys and how they might play a

role in the discrepancy. In the household survey, none of the

known types of response error have a systematic bias that would

fit the discrepancy pattern exhibited. In the establishment survey,

a response error that caused an upward bias in the benchmark

data (but not in the survey itself) was discovered in 1991 and

later corrected. Since then, the Bureau has found no evidence

that it has recurred.30 Also, with regard to the establishment

survey benchmark, the Bureau reviewed the secondary benchmark data sources (the so-called presumed noncovered) for

errors and possible bias, but there were no indications of

problems.

The discrepancy after the 2001 recession

During the 2001 recession, employment from the establishment

and household surveys showed similar declines. Following the

official trough of the recession in November 2001, however,

establishment survey employment continued to decline while

household survey employment began to show signs of growth.

Because establishment survey employment was at a higher point

entering the 2001 recession, this divergence in trend actually

brought the two measures closer together. (See chart 2.) In early

2003, employment from the two surveys converged, and a few

months later, establishment survey employment turned upwards. Employment from the two surveys tracked fairly closely

from that point through the end of 2004.

Nevertheless, the conflicting directions of the two employment

measures in late 2001 through early 2003—a period that was a

critical juncture in the business cycle—drew much scrutiny from

labor market analysts, perhaps more than the large discrepancy

in the late 1990s. Even though the employment estimates from

both surveys later trended upwards, the difference in employment growth measured by the two surveys was notable; from

November 2001 through December 2004, for example, the CES

survey showed an increase of 1.6 million while the CPS exhibited

a rise of 4 million. This absolute difference added to the consternation of some observers, especially because it occurred

during the period leading up to the 2004 election, when many

were focusing on the state of the job market.31 (Table 1 shows the

cumulative employment discrepancy between the payroll survey

and the adjusted household survey, using annual average data

for 2001 and for 2004. The discrepancy was –2,546,000—that

is, –346,000 payroll jobs minus 2,200,000 adjusted household

employment.)

The causes of the discrepancy following the post-2001

recession are not known, but it is possible that this discrepancy

shared common factors with that of the 1990s. That is, the greater

growth in establishment survey employment during the expansion of the 1990s may be correlated with the sharper decline it

showed during and after the 2001 recession. It also is interesting

to note that, when employment from the two surveys is evaluated

in ratio form, as illustrated in chart 1, one sees that the ratio has

been moving back to its “normal” range since the 2001 recession.

Some of the factors examined in the late 1990s have continued

to be evaluated as contributors to the more recent discrepancy.

Chief among these factors is the potential effect of rapid job

changing on establishment survey employment. Although jobchanging rates derived from household survey data did not help

explain the discrepancy during the 1990s expansion, they did

indicate that the rate of job changing slowed after the economy

peaked in 2001. Since the last recession, the Bureau has undertaken a somewhat more sophisticated analysis in an attempt to

gauge the potential effect of job changing on payroll employment. The approach takes into account the fact that the longer

the employer’s pay period, the more likely a job changer is to be

captured twice in the establishment survey. Because pay-period

length is highly correlated with industry, BLS researchers established industry weights and looked at job-changing rates by

industry and then at the aggregate level. As reported in August

2004, the results of the examination indicated that, from March

2001 through June 2004, the job-changing effect may have

accounted for about 250,000, or 10 percent, of the discrepancy

over that period.32 The Bureau is continuing to examine this issue and also is looking at other ways to test the impact of job

changing.

Among many outside analysts, the household survey population controls also continued to be eyed as a source of discrepancy between establishment and household survey employment.

With household survey employment showing so much more

growth after the 2001 recession, some speculated that the CPS

population controls were now overstating U.S. population

growth and therefore employment growth. Specifically, some

argued that the Census Bureau’s estimates of population growth

after the 2000 census were too high, particularly because

undocumented immigration might have slowed due to heightened security measures after September 11, 2001. No one, of

course, can effectively prove or disprove this argument, given
Monthly Labor Review February 2006 33

that full enumerations of the population are carried out only

every 10 years to gauge the relative accuracy of the intercensal

estimates. Between decennial censuses, no one knows how

accurately the population estimates reflect the true population at

any point. For example, the population control revision to the

household survey following a decennial census could be relatively small, but in reality, the intercensal estimates at times may

have strayed significantly high and low during the previous

decade. The Census Bureau continues to look for ways to

improve the relative accuracy of the intercensal population

estimates and controls, but the task of quantifying undocumented immigration remains a daunting one.

Various other potential factors in the post-2001-recession

discrepancy remain under review. Following are some additional

areas that the Bureau of Labor Statistics has researched or

continues to examine.

CES births. The CES survey is not able to include new firms

(births) immediately. There is a lag between a firm’s opening for

business and appearing in the sampling frame. Likewise, there is

a lag in capturing business deaths: if a sampled firm goes out of

business, it usually stops reporting instead of reporting zero

employees. The CES survey cannot immediately determine the

status of a reporter that is not responding; it takes time to learn

whether a firm indeed has closed down. In order to reduce the

sampling error due to not having timely information on entries

and exits of firms, the CES survey uses a model-based approach,

known as a “birth/death model,” to adjust the sample-based

estimates for the existence of new firms and for firms that go out

of business. With the release of data in June 2003 and the full

implementation of the new probability-based sample design, the

survey began to use model-based birth/death factors across all

industry series.

The birth/death model uses an estimation procedure with two

components, the first of which utilizes business deaths to impute

employment for a portion of business births and the second of

which is an ARIMA time-series model designed to estimate the

residual net birth/death employment not accounted for by the

first component’s imputation.33 The net birth/death model component factors are unique to each month and include negative adjustments in some months.

Since the implementation of the birth/death model, there have

been some criticisms from outside sources.34 Analysts have

suggested that, in some months, the number of jobs added due

to the birth/death model was close to the total number of CES

jobs created in a given month. However, one must note that

1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

110,000

115,000

120,000

125,000

130,000

135,000

140,000

110,000

115,000

120,000

125,000

130,000

135,000

140,000

Chart 2. Establishment survey employment and household survey employment adjusted to a 

 payroll-type concept, 1994—2004

Thousands

Establishment survey

Adjusted 

household survey

Thousands

NOTE: Shaded area indicates recession.
34 Monthly Labor Review February 2006

Employment Measures

birth/death figures are not seasonally adjusted and therefore

should not be compared with seasonally adjusted over-themonth changes in employment. In addition, the birth/death

model contributes negative adjustments in some months.

Comparisons of CES monthly estimates with the universe data,

along with the relatively small benchmark revisions for March

2003 and 2004, indicate that the model has been performing

well in recent times.

CES benchmark data. Along with some recurrent criticism of

the establishment survey’s effectiveness in estimating employment from business births, questions have been raised about the

quality of the establishment survey benchmark data from the

QCEW. QCEW statistics come from mandatory quarterly tax

reports that employers file with State UI programs. Additional

characteristics help make the QCEW a reasonably complete and

accurate data source; for example, there are financial penalties

for noncompliance. The UI system also has something of a builtin check mechanism: if a noncompliant firm lays off a worker and

that worker files a UI claim, the employer will be identified and

penalized. In addition, many States have integrated tax and

licensing systems that check for compliance among sales, UI,

and other tax rolls, as well as among applicants for licenses such

as those required for selling alcoholic beverages.

Other questions and criticisms have concerned the timely

capture of business births in the QCEW, because that, too, would

have repercussions for the quality of the establishment survey

data, specifically causing it to miss growth associated with the

formation of new businesses. In 2004, the Bureau of Labor

Statistics undertook a study to address just that issue, reviewing

detailed administrative reports on State UI operations. The study

found that, since 1995, about 80 percent of new businesses were

in the database within 90 days and about 90 percent were

captured within 180 days (including the years 1999 and 2000,

when new-business formations were at peak levels). By third

quarter 2003 (the latest quarter available at the time of the study),

the percentage of new businesses captured in the database within

90 days had risen to 84.9 percent and the percentage captured

within 180 days was 92.8 percent. Therefore, no change has

emerged in the normal lag of capturing new-business formation

in the benchmark data that would detrimentally affect the

establishment survey employment estimates.35

“Off-the-books” employment. Separately, some have theorized

that “off-the-books” employment has caused or at least contributed to the postrecession discrepancy in the surveys’ employment measures. The idea is that, although this type of economic

activity obviously is not counted by the establishment survey,

because the workers would not be shown on employer payrolls,

the household survey will capture some or all of such activity.

Some also theorize that “off-the-books” employment increases

in a poor or weak labor market. Unfortunately, the Bureau cannot

test this theory, because there is no way to determine the extent

to which such employment is reported in the household survey.

“Off-the-books” employment undoubtedly will remain one of

the issues associated with the employment discrepancy. It

does not seem likely to hold any possible answers for the

discrepancy that occurred in the 1990s, however, and for that

reason, it may be questionable how much of an effect it has

had since the recession.

Self-employment. Much has been written about the role of

self-employment in the post-2001-recession job market. As

previously discussed, the Bureau adjusts for this definitional

difference in the surveys in its routine reconciliation; however,

we know that the adjustment is imprecise. Any number of the

self-employed work as independent contractors. In past years,

periodic special supplements to the household survey have

provided estimates of the number of independent contractors.

When these estimates have been compared with information in

the “basic,” or standard, part of the household survey, the Bureau

has found that about 12 percent to 15 percent of independent

contractors are mistakenly reported as wage and salary workers,

rather than self-employed, in the monthly employment estimates.

In February 2001, this figure was about 1.2 million workers, or

approximately 13 percent of all independent contractors. In

February 2005, it was 1.4 million workers, still about 13 percent.

Thus, despite the Bureau’s best efforts to reconcile the employment measures from the two surveys, the household survey may

be overstating the number of wage and salary workers to some

extent through misclassification of some independent contractors. To the degree that this has occurred, the discrepancy since

the 2001 recession would have been exaggerated.

Following the 2001 recession, there were many anecdotal

reports about the growing use of independent contractors,

because employers were thought to be reluctant to hire permanent workers on their payrolls. These contractors were dubbed

“1099 workers” by some, after the Internal Revenue Service (IRS)

form on which employers report payments made to independent

contractors. The Bureau attempted to confirm the hypothesis of

greater use of independent contractors with IRS tax data. Examining the trend in the issuance of IRS Form 1099-MISC,

“Miscellaneous Income,” in the pre- and postrecession years

was not especially useful, because the form is used to report

numerous types of income, not just that paid to independent

contractors. The Bureau then obtained a special IRS summary of

a subset of data from Form 1099-MISC. Specifically, the IRS

provided a count of the number of taxpayers with nonemployee

income reported on Form 1099-MISC, excluding instances in which

a corporation issued the form to another corporation. The data

showed an increase of about 565,000, or 4 percent, between 2001

and 2002. Viewed as a proportion of household survey employment, the number increased from 9.3 percent of total employment in 2001 to 9.7 percent in 2002. This special tabulation
Monthly Labor Review February 2006 35

probably came closer to identifying independent contractors,

but still had its limitations,36 a key one of which is that it is unknown whether the nonemployee income represents the worker’s

sole or primary work income. Undoubtedly, it represents secondary work income for any number of individuals, in which

case they would already be included in household survey

employment on the basis of their primary job. If that job is a

nonfarm wage and salary job, those individuals also would

be reflected in establishment survey employment. Although

these data may provide some support to the notion that the

use of contractors grew following the 2001 recession, any

possible effect on the employment discrepancy in the surveys is

unclear.

On a related note, some analysts have suggested that comparisons be made between self-employment data from the CPS

and “nonemployer” statistics from the Census Bureau. The

concepts and definitions used to create each of these data series

are so different, however, that it is difficult to make comparisons

between the two. The Census Bureau nonemployer data include

businesses with no paid employees and that (1) have annual

business receipts of more than $1,000 ($1 or more for construction

establishments) and (2) are subject to Federal income taxes. The

business may or may not be the primary job of the owner and can

be either an unincorporated business (individual proprietorship),

a partnership, or a corporation. The CPS is a household survey

that categorizes persons into classes of worker—wage and

salary, self-employed, or unpaid family worker—according to

their primary job. There are no rules regarding receipts or

taxability of the self-employed person’s business. As previously

mentioned, to be classified as self-employed in the CPS, the

person must be performing his or her work as an unincorporated

business; the incorporated self-employed are classified as wage

and salary workers.

One specific group of self-employed workers the Bureau

examined was real-estate agents, most of whom work solely for

commission and are not covered under State UI laws. These

employees tend to set their own work schedules and receive no

benefits or leave. They are not considered employed in the

establishment survey. In the household survey, real-estate

agents who work only for commission are counted as employed.

It is likely that many of these commissioned agents report

themselves as self-employed in the CPS. CPS data show little

increase in the number or proportion of self-employed real-estate

agents between 2000 and 2004. However, these data do show an

increase in the number of real-estate agents classified as wage

and salary workers (about 100,000) over the period. What is not

known is the extent to which any of these agents are misclassified

as wage and salary workers. The increase in real-estate agents

classified as wage and salary workers from 2000 to 2004 is

small enough, though, that even if they were all misclassified,

there would be little effect on the gap between the CPS and the

CES survey.

Limited-liability companies. The limited-liability company

(LLC) is a fairly new type of business organization. An LLC is

a type of business entity used by small-business owners; its

liability is similar to that of a corporation, in that none of the

members of an LLC are personally liable for its debts. An LLC

may be classified for Federal income tax purposes as a sole proprietorship (referred to as an entity to be regarded as separate

from its owner), a partnership, or a corporation. According to

statistics from the Internal Revenue Service, the number of LLC’s

rose from about 119,000 in 1995 to 946,000 in 2002.37 There is

some question as to how these persons are reported in the CPS.

Owners of LLC’s should be reported as self-employed, and their

being misclassified as wage and salary workers would influence

the discrepancy between the two surveys. The Bureau of Labor

Statistics cannot be certain how much, if any, misclassification of

LLC owners is occurring in the CPS. Nor is it known to what

extent LLC owners are included in the CES survey. An informal

survey of State government Web sites showed that UI coverage

mandated by States varied. In some States, LLC owners were not

covered at all, and in others they could elect coverage. In

determining eligibility for UI coverage, some States also take into

account the LLC’s IRS filing status or the owners’ proportions of

ownership interest. The Bureau is continuing to review the LLC

issue.

Welfare-to-work programs. Beginning in 1996, the welfare

program known as Aid to Families with Dependent Children was

replaced by Temporary Assistance for Needy Families (TANF) as

part of the Personal Responsibility and Work Opportunity

Reconciliation Act of 1996. TANF requires participation in work

opportunities as a condition for receiving benefits, and there is a

5-year limit to each family’s participation in the program. Work

activities under TANF include unpaid and paid work, both

subsidized and unsubsidized, along with activities such as

training and education that are directly related to employment.

Theoretically, the CES survey and the CPS treat these workers

differently, depending on whether the jobs are subsidized or

unsubsidized; however, the actual reporting practices of survey

participants and their employers are not known. Paid, unsubsidized employment should be covered by both surveys. Subsidized employment would be treated differently. Workers in

subsidized jobs would be covered in the CPS, because such

workers would be considered to be employed, regardless of who

pays them. Under the CES survey, if the employer is paying any

portion of the wages of a worker in a subsidized job, then the

worker should be reported as employed. If the subsidy is paid

directly to the welfare recipient and the employer does not pay

his or her wages, then the worker would not be counted as employed. It is not known to what extent welfare-to-work participants in subsidized jobs are included in CES employment.

According to data from the Administration for Children and

Families, of the Department of Health and Human Services, the
36 Monthly Labor Review February 2006

Employment Measures

number of adult participants in TANF has been declining, as has

the proportion of participating adults engaging in work for which

they received pay.38 By contrast, the proportion of participating

adults engaging in unpaid work activities has been increasing. In

fiscal year 1999, the average monthly number of adults who

participated in work activities was about 885,000. Of these

participating adults, about 590,000, or 67 percent, participated in

at least some paid activities. By fiscal year 2004, the number of

adults who participated in at least some work activities was down

to about half a million, with 49 percent of adults, or about 245,000,

on average, participating in paid work activities.

Because, theoretically, the CPS would count all welfare-to-work

participants, whether in subsidized or unsubsidized work

activities, that survey would include more of these workers than

the CES would. However, the number of adults in TANF who

participate in paid work activities is fairly small and has been

declining. It is not likely that the different coverage between the

two surveys would have contributed much to the discrepancy in

growth as estimated by the CPS and by the CES.

Other factors. Although several other factors were previously

found to be rather small and to have little or no impact on the

discrepancy, the Bureau continues to look at them. Among these

factors are multiple jobholders with more than two jobs and

employed 15-year-olds. More recent observations for 2001–04

are similar to what was observed before the recession: 15-yearold employment accounts for a small portion of the discrepancy

(–110,000), and multiple jobholders with more than two jobs had

a small increase (+44,000). The net effect still explains very little of

the discrepancy.

THE EMPLOYMENT MEASURES FROM THE BLS HOUSEHOLD

and establishment surveys have different definitional scopes

and concepts, are produced by means of distinct survey

methodologies, and have their own relative strengths and

weaknesses as statistics. It is possible to adjust the employment

measures to a more similar concept for comparison. This adjustment process addresses some of the primary differences in

concept and scope: number of jobs compared with number of

employed persons (resulting in the multiple-jobholder effect) and

coverage of the agricultural sector, the self-employed, unpaid

family workers, private household workers, and workers on

unpaid absences.

Adjusted for major differences, the employment measures

track rather well over time, but they have exhibited periodic trend

discrepancies throughout their histories. Although many theories

about the discrepancies have been put forth, complete explanations have never been found for any of the divergences, despite a significant amount of research by the Bureau of Labor

Statistics and by outside analysts. Population controls in the

household survey have been shown to be a factor in the past,

and the Bureau also has some evidence that the misclassification

of some self-employed and rapid job changing may contribute to

the discrepancy. Other potential factors are extremely difficult to

test or measure. Questions remain, for example, about the

possible effect of “off-the-books” employment and the inclusion

of undocumented workers in the two surveys. The Bureau

continues to investigate many of the factors described in this

article and also to look for new avenues of research. Divergences

in the two surveys’ employment measures may occur again. At

such times, data users and analysts would be well served not to

think of one survey as “right” and the other “wrong,” but to

consider their statistical strengths and the distinct information

that each provides and then weigh them accordingly.

Notes

ACKNOWLEDGMENTS: The authors gratefully acknowledge the earlier

work of Thomas Nardone, Jurgen Kropf, Katie Kirkland, and Signe

Wetrogan, as well as research on job changing by Anne Polivka and John

Stewart. All of their work made an important contribution to this article.

The authors also thank Peter Sailer of the Internal Revenue Service for

4

 The household survey sample of approximately 60,000 addresses

is selected from all counties and independent cities in the United States.

The 3,141 counties and cities are formed into 2,007 sample areas

(Primary Sampling Units, or PSU’s), which are then grouped into strata

within each State. Then one sample area is chosen from within each

stratum, with the probability of selection proportional to the population within the PSU; this totals 754 PSU’s. Sampling groups within

these PSU’s are in the sample for 4 consecutive months, leave the

sample for the next 8 months, and then return for the next 4 months.

In each month, 1 of the 8 rotation groups is in its first month, while

another rotation group is in its second month, and the group in its

fifth month is returning after a break of 8 months. This rotation procedure allows the sampled households not to be overburdened.

 The CES sample includes about 160,000 businesses and government

agencies in the United States, covering about 400,000 worksites. In

June 2003, the CES program completed a redesign and moved from a

quota-based sample to a probability-based sample. The program began

to introduce the new sample in 2000 with one industry, and by June

2003, it was used for all industries under NAICS. The new sample design

is a stratified, simple random sample of worksites clustered by Unemployment Insurance (UI) account number. The sampling frame for the

his assistance in creating the special tabulations of IRS form 1099–MISC.

1

 The National Bureau of Economic Research is generally recognized

as the arbiter of business-cycle turning points. The organization determined that the latest recession began in March 2001 and ended in

November of that year.

2

 Since this article was prepared, data for recent years have been subject

to routine revisions for seasonal adjustment, household survey population

controls, and establishment survey benchmarking. These revisions do not

significantly change the discrepancy between the surveys as it is described

herein.

3

 Detailed information on both the CES survey and the CPS is found in

the BLS Handbook of Methods, on the Internet at http://

www.bls.gov/opub/hom/homtoc.htm. (See chapter 1 for the CPS and

chapter 2 for the CES survey.)
Monthly Labor Review February 2006 37

CES survey is the list of employers in the Longitudinal Database (LDB),

a universe file of business establishments that is derived from the UI tax

system and collected by the BLS Quarterly Census of Employment and

Wages (QCEW) program. The frame and the sample are updated twice a

year. The sample is stratified by State, employment size, and industry.

Each year, approximately 40,000 new units are added to the sample in

order to rotate part of it, get representation from new firms, and

realign the sample distribution with the universe distribution.

5

 For more information on the 1994 CPS redesign, see “Revisions in

the Current Population Survey Effective January 1994,” Employment

and Earnings (Bureau of Labor Statistics, February 1994), pp. 13–37.

6

 For further details on changes in the CES survey in 2003, see

Teresa L. Morisi, “Recent changes in the national Current Employment Statistics survey,” Monthly Labor Review, June 2003, pp. 3–

13; on the Internet at http://www.bls.gov/opub/mlr/2003/06/

art1full.pdf.

7

 Concurrent seasonal adjustment for the CES uses updated seasonal

factors not only for the latest month, but also for the previous 2

months. With the release of each new estimate, these factors are

routinely revised to incorporate additional sample responses for those

months. Once a year, 5 years of historical monthly estimates are

revised with the latest seasonal factors. For further information on

concurrent seasonal adjustment for the CES, see Chris Manning,

“Concurrent seasonal adjustment for national CES survey,” Monthly

Labor Review, October 2003, pp. 39–43; on the Internet at http://

www.bls.gov/opub/mlr/2003/10/ressum2.pdf.

8

 Some changes to the composite weighting also were implemented

in the CPS in January 2003, and the survey questions on race and

Hispanic ethnicity were modified to comply with new standards set by

the Office of Management and Budget. Further details on the CPS

changes in January 2003 are found in “Revisions to the Current

Population Survey Effective in January 2003,” on the Internet at

http://www.bls.gov/cps/rvcps03.pdf, and in Employment and

Earnings (Bureau of Labor Statistics, February 2003), pp. 4–23.

9

 In the CPS, only the latest month is seasonally adjusted with the

latest seasonal factors. Once a year, 5 years of historical monthly

estimates are revised with the latest seasonal factors.

10 Two such situations are as follows:

Faculty in schools. The CES survey has a special treatment for “regular” faculty members of elementary and secondary schools and colleges

and universities. Regular faculty are those persons who are professional

or certified and who have a contractual arrangement (written or otherwise) for 1 or more years. Regular faculty are counted as employed the

entire year, regardless of whether they get paid year round or have 9-

or 10-month payment plans. This means that regular faculty members who do not work during the summer break or other breaks are still

counted as employed. The treatment of regular faculty members differs

from that of workers in all other industries in the CES program, who

must have been paid during the reference week in order to be counted.

In the CES survey, if regular faculty take another job during the summer

months, they are counted twice for those months. The household

survey has no such special treatment for faculty. One of the categories

for those “with a job, not at work” includes vacation; therefore, faculty

with a written or verbal contract to return to teaching in the fall would

still be counted as employed during the summer break. Because CPS

employment is a count of those employed, faculty who take a second

job during the summer are not counted twice.

Census workers. Every 10 years, the Census Bureau hires a number

of temporary workers to staff the decennial census. Although some

hiring is done prior to the census year, the bulk of the increase in

workers and of the subsequent decline occurs in approximately February

through May of the census year. The influx of these workers causes

spikes in Federal Government employment and in total nonagricultural

employment in the CES survey as additional jobs are added to payrolls.

In order to count the new workers accurately, the Census Bureau transmits to the CES program actual counts of temporary workers hired to

staff the census, and the CES program incorporates the counts into the

CES survey estimates. The household survey does not add in outside

counts for temporary census workers. Because the CPS counts each

person who is employed once and does not count jobs, persons who

have second jobs as temporary census workers will not be counted

twice, as they would be in the CES survey. Household survey employment

does not show any discernible effects due to the hiring of temporary

census workers.

11 These data on secondary jobs are available from outgoing rotation

groups in the CPS sample.

12 “Measuring Employment and Unemployment,” President’s Committee to Appraise Employment and Unemployment Statistics, 1962,

pp. 113–21.

13 Gloria P. Green, “Comparing employment estimates from house-hold

and payroll surveys,” Monthly Labor Review, December 1969, pp. 9–20.

14 See note 10, earlier, for a description of the treatment of faculty.

15 Counting the Labor Force (National Commission on Employment

and Unemployment Statistics, Labor Day 1979), pp. 193–99.

16 John F. Stinson, Jr., “Comparison of Nonagricultural Estimates from

Two Surveys,” Employment and Earnings, March 1994, pp. 6–9.

17 John F. Stinson, Jr., “Moonlighting: a key to differences in

measuring employment growth,” Monthly Labor Review, February

1987, pp. 30–31.

18 Paul O. Flaim, “How many new jobs since 1982? Data from two

surveys differ,” Monthly Labor Review, August 1989, pp. 10–15.

19 Thomas Nardone, Mary Bowler, Jurgen Kropf, Katie Kirkland,

and Signe Wetrogan, Examining the Discrepancy in Employment

Growth between the CPS and the CES, report to the Federal Economic

Statistics Advisory Committee on October 17, 2003; on the Internet

at http://www.bls.gov/bls/fesacp2101703.pdf. Note that the reconciliation methodology used at the time was somewhat different from

the current procedure. As a result, the report to the committee shows

the unexplained portion of the employment discrepancy for 1994–

2000 to be 4.2 million, somewhat less than the 4.5 million derived

with current methods for this article.

20 See Mary Bowler, Randy E. Ilg, Stephen Miller, Ed Robison, and

Anne Polivka, “Revisions to the Current Population Survey Effective

in January 2003,” Employment and Earnings, February 2003, pp. 4–

23; on the Internet at http://www.bls.gov/cps/rvcps03.pdf.

21 In the household survey, the questions designed to elicit household

members’ employment status are asked about all household members

aged 15 years and older. The published estimates, however, reflect

only those aged 16 years and older.

22 The idea that both job changing and the different survey reference

periods contribute to the discrepancy between the surveys has been

around for some time. Earlier research in this area—by Antos, Barkume,

Mixon, and Triplett in 1976, for example (cited in Nardone, Bowler,

Kropf, Kirkland, and Wetrogan, Examining the Discrepancy)—was

hindered by even less information than is available now.

23 Research by Bruce C. Fallick and Charles A. Fleischman, economists at the Federal Reserve Board, came to a similar conclusion. (See

The Importance of Employer-to-Employer Flows in the U.S. Labor

Market, Finance and Economics Discussion Series working paper

2001–18 (Federal Reserve Board, Division of Research and Statistics

and Monetary Affairs, April 2001).)

24 The establishment survey benchmark data are based primarily on

administrative tax reports filed with State UI programs and provided to

the Bureau of Labor Statistics for the agency’s QCEW program. Prison

workers were not formally excluded from coverage under Federal UI

law until 1997. Although the Bureau never identified any instances in
38 Monthly Labor Review February 2006

Employment Measures

which prison workers were reported in the QCEW employment figures,

the possibility that they were did exist before 1997.

25 See 2000 CIA Directory (Baltimore, Correctional Industries

Association, 2000).

26 On a related note, the CES employment measure includes a relatively

small number of American workers employed by U.S. companies overseas.

These workers are not in the scope of the CPS. In the mid- to late

1990s, there were fewer than 10,000 such workers, representing only

a tiny portion of the discrepancy between the surveys.

27 See Patterns of Reporting Errors and Irregularities by 100

Employers with the Most Suspended Wage Items, Audit Report A-03-

98-31009 (Office of the Inspector General, Social Security

Administration, September 1999); and The Social Security

Administration’s Earnings Suspense File Tactical Plan and Efforts to

Reduce the File’s Growth and Size, Evaluation Report A–03–97–31003

(Office of the Inspector General, Social Security Administration, February

2000).

28 See, for example, Manuel de la Puente, Using Ethnography to

Explain Why People Are Missed or Erroneously Included by the Census:

Evidence from Small Area Ethnographic Studies (U.S. Census Bureau,

Center for Survey Methods Research, 1995); on the Internet at http://

www.census.gov/srd/papers/pdf/mdp9501.pdf.

29 Simon Potter and Chinhui Juhn of the Federal Reserve Bank of

New York present an excellent discussion of undercoverage in their

article “Explaining the Recent Divergence in Payroll and Household

Employment Growth,” Current Issues in Economics and Finance

(Federal Reserve Bank of New York, December 1999); on the Internet

at http://www.ny.frb.org/research/current_issues/ci5-16.html.

30 The response error that occurred in the CES benchmark data—

monthly employment figures reported by employers in their State UI

tax reports and provided to the Bureau of Labor Statistics for the QCEW

program—was discovered when CES employment estimates and the

benchmark data diverged significantly in 1991.

31 Although many focused on the absolute difference in employment

growth between the surveys, others conducted a more thoughtful analysis

that compared the trend in the employment-population ratio from the

CPS—a statistically stronger measure than the CPS employment level—

with CES employment and found that they both indicated a similar, lessthan-robust labor market. (See Mark Schweitzer and Guhan Venkatu,

“Employment Surveys are Telling the Same (Sad) Story,” Economic

Commentary (Federal Reserve Bank of Cleveland, Research Department,

May 15, 2004)); on the Internet at http://www.clevelandfed.org/Research/

Com2004/05-15.pdf.

32 More detailed information is available on the BLS Internet site at http://

www.bls.gov/ces/cesjobch.pdf.

33 In its seasonal adjustment process, the Bureau of Labor Statistics uses X12 ARIMA software developed by the Bureau of the Census. For further

information on both the net birth/death model and benchmark revisions, see

Kirk Mueller, “BLS Establishment Estimates Revised to Incorporate March

2005 Benchmarks,” Employment and Earnings, February 2006; on the

Internet at http://www.bls.gov/web/cesbmart.htm.

34 On a related note, some who criticized the establishment survey for

failing to capture new firms have used the terms “new firms” and “startups”

interchangeably with “self-employed.” These are distinct employment

concepts and such usage is misleading. As previously mentioned, the CES survey

does not include the unincorporated self-employed; the household survey

provides this information. The CES birth/death model is used to estimate

employment associated with new firms that have payroll employees.

35 For additional information, see “Assessing the Timeliness of Business

Births in BLS Establishment Statistics” (Bureau of Labor Statistics, Apr. 7,

2004); on the Internet at http://www.bls.gov/cew/eta581study.pdf.

36 The IRS Statistics of Income Division tabulated for the Bureau the number

of taxpayers with nonemployee income reported on Form 1099-MISC from

Individual Statistics of Income samples matched to Forms 1099-MISC from the

Information Returns Master File. These samples excluded instances in which

a corporation issued a 1099-MISC to another corporation. Even this refined

tabulation, however, would include a number of types of payments that were

not necessarily for independent contractor services, so it should not be

construed as an estimate of the number of independent contractors.

37 Statistics of Income Division, Internal Revenue Service, Table 11,

Partnership Returns: Selected Balance Sheet and Income Statement Items for

Specific Income Years. These types of companies are under-stated because

some businesses failed to answer the question about type of partnership on

their tax returns.

38 The BLS analysis categorized paid and unpaid work as follows: paid work

includes unsubsidized employment, subsidized private employment, and

subsidized public employment; unpaid work includes work experience programs,

on-the-job training, job searches, community service, vocational education,

job skills training, education, providing childcare, and other TANF-approved

activities.