Technical Note
This news release presents statistics from two major surveys, the
Current Population Survey (CPS; household survey) and the Current Employment
Statistics survey (CES; establishment survey). The household survey provides
information on the labor force, employment, and unemployment that appears
in the "A" tables, marked HOUSEHOLD DATA. It is a sample survey of about
60,000 eligible households conducted by the U.S. Census Bureau for the U.S.
Bureau of Labor Statistics (BLS).
The establishment survey provides information on employment, hours,
and earnings of employees on nonfarm payrolls; the data appear in the
"B" tables, marked ESTABLISHMENT DATA. BLS collects these data each
month from the payroll records of a sample of nonagricultural business
establishments. Each month the CES program surveys about 141,000 businesses
and government agencies, representing approximately 486,000 individual worksites,
in order to provide detailed industry data on employment, hours, and earnings of
workers on nonfarm payrolls. The active sample includes approximately one-third
of all nonfarm payroll employees.
For both surveys, the data for a given month relate to a particular week
or pay period. In the household survey, the reference period is generally
the calendar week that contains the 12th day of the month. In the establishment
survey, the reference period is the pay period including the 12th, which
may or may not correspond directly to the calendar week.
Coverage, definitions, and differences between surveys
Household survey. The sample is selected to reflect the entire
civilian noninstitutional population. Based on responses to a series
of questions on work and job search activities, each person 16 years
and over in a sample household is classified as employed, unemployed,
or not in the labor force.
People are classified as employed if they did any work at all as paid
employees during the reference week; worked in their own business,
profession, or on their own farm; or worked without pay at least 15
hours in a family business or farm. People are also counted as employed
if they were temporarily absent from their jobs because of illness, bad
weather, vacation, labor-management disputes, or personal reasons.
People are classified as unemployed if they meet all of the following
criteria: they had no employment during the reference week; they were
available for work at that time; and they made specific efforts to find
employment sometime during the 4-week period ending with the reference
week. Persons laid off from a job and expecting recall need not be
looking for work to be counted as unemployed. The unemployment data
derived from the household survey in no way depend upon the eligibility
for or receipt of unemployment insurance benefits.
The civilian labor force is the sum of employed and unemployed persons.
Those not classified as employed or unemployed are not in the labor
force. The unemployment rate is the number unemployed as a percent of
the labor force. The labor force participation rate is the labor force
as a percent of the population, and the employment-population ratio is
the employed as a percent of the population. Additional information about
the household survey can be found at www.bls.gov/cps/documentation.htm.
Establishment survey. The sample establishments are drawn from private
nonfarm businesses such as factories, offices, and stores, as well as
from federal, state, and local government entities. Employees on nonfarm
payrolls are those who received pay for any part of the reference pay
period, including persons on paid leave. Persons are counted in each job
they hold. Hours and earnings data are produced for the private sector
for all employees and for production and nonsupervisory employees.
Production and nonsupervisory employees are defined as production and
related employees in manufacturing and mining and logging, construction
workers in construction, and nonsupervisory employees in private service-
providing industries.
Industries are classified on the basis of an establishment’s principal
activity in accordance with the 2012 version of the North American Industry
Classification System. Additional information about the establishment survey
can be found at www.bls.gov/ces/#technical.
Differences in employment estimates. The numerous conceptual and
methodological differences between the household and establishment
surveys result in important distinctions in the employment estimates
derived from the surveys. Among these are:
--The household survey includes agricultural workers, the self-
employed, unpaid family workers, and private household workers
among the employed. These groups are excluded from the
establishment survey.
--The household survey includes people on unpaid leave among the
employed. The establishment survey does not.
--The household survey is limited to workers 16 years of age and
older. The establishment survey is not limited by age.
--The household survey has no duplication of individuals, because
individuals are counted only once, even if they hold more than one
job. In the establishment survey, employees working at more than
one job and thus appearing on more than one payroll are counted
separately for each appearance.
Seasonal adjustment
Over the course of a year, the size of the nation's labor force and
the levels of employment and unemployment undergo regularly occurring
fluctuations. These events may result from seasonal changes in weather,
major holidays, and the opening and closing of schools. The effect of
such seasonal variation can be very large.
Because these seasonal events follow a more or less regular pattern
each year, their influence on the level of a series can be tempered by
adjusting for regular seasonal variation. These adjustments make
nonseasonal developments, such as declines in employment or increases
in the participation of women in the labor force, easier to spot. For
example, in the household survey, the large number of youth entering
the labor force each June is likely to obscure any other changes that
have taken place relative to May, making it difficult to determine if
the level of economic activity has risen or declined. Similarly, in
the establishment survey, payroll employment in education declines by
about 20 percent at the end of the spring term and later rises with
the start of the fall term, obscuring the underlying employment trends
in the industry. Because seasonal employment changes at the end and
beginning of the school year can be estimated, the statistics can be
adjusted to make underlying employment patterns more discernable. The
seasonally adjusted figures provide a more useful tool with which to
analyze changes in month-to-month economic activity.
Many seasonally adjusted series are independently adjusted in both
the household and establishment surveys. However, the adjusted series
for many major estimates, such as total payroll employment, employment
in most major sectors, total employment, and unemployment are computed
by aggregating independently adjusted component series. For example,
total unemployment is derived by summing the adjusted series for four
major age-sex components; this differs from the unemployment estimate
that would be obtained by directly adjusting the total or by combining
the duration, reasons, or more detailed age categories.
For both the household and establishment surveys, a concurrent
seasonal adjustment methodology is used in which new seasonal factors
are calculated each month using all relevant data, up to and including
the data for the current month. In the household survey, new seasonal
factors are used to adjust only the current month's data. In the
establishment survey, however, new seasonal factors are used each month
to adjust the three most recent monthly estimates. The prior 2 months
are routinely revised to incorporate additional sample reports and
recalculated seasonal adjustment factors. In both surveys, 5-year revisions
to historical data are made once a year.
Reliability of the estimates
Statistics based on the household and establishment surveys are
subject to both sampling and nonsampling error. When a sample rather
than the entire population is surveyed, there is a chance that the
sample estimates may differ from the "true" population values they
represent. The exact difference, or sampling error, varies depending
on the particular sample selected, and this variability is measured by
the standard error of the estimate. There is about a 90-percent chance,
or level of confidence, that an estimate based on a sample will differ
by no more than 1.6 standard errors from the "true" population value
because of sampling error. BLS analyses are generally conducted at the
90-percent level of confidence.
For example, the confidence interval for the monthly change in
total nonfarm employment from the establishment survey is on the order
of plus or minus 100,000. Suppose the estimate of nonfarm employment
increases by 50,000 from one month to the next. The 90-percent confidence
interval on the monthly change would range from -50,000 to +150,000
(50,000 +/- 100,000). These figures do not mean that the sample results
are off by these magnitudes, but rather that there is about a 90-percent
chance that the "true" over-the-month change lies within this interval.
Since this range includes values of less than zero, we could not say with
confidence that nonfarm employment had, in fact, increased that month.
If, however, the reported nonfarm employment rise was 250,000, then all
of the values within the 90-percent confidence interval would be greater
than zero. In this case, it is likely (at least a 90-percent chance) that
nonfarm employment had, in fact, risen that month. At an unemployment rate
of around 5.5 percent, the 90-percent confidence interval for the monthly
change in unemployment as measured by the household survey is about
+/- 280,000, and for the monthly change in the unemployment rate it is
about +/-0.19 percentage point.
In general, estimates involving many individuals or establishments
have lower standard errors (relative to the size of the estimate) than
estimates which are based on a small number of observations. The precision
of estimates also is improved when the data are cumulated over time, such
as for quarterly and annual averages.
The household and establishment surveys are also affected by
nonsampling error, which can occur for many reasons, including the failure
to sample a segment of the population, inability to obtain information
for all respondents in the sample, inability or unwillingness of
respondents to provide correct information on a timely basis, mistakes
made by respondents, and errors made in the collection or processing of
the data.
For example, in the establishment survey, estimates for the most
recent 2 months are based on incomplete returns; for this reason, these
estimates are labeled preliminary 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.
Another major source of nonsampling error in the establishment survey
is the inability to capture, on a timely basis, employment generated by
new firms. To correct for this systematic underestimation of employment
growth, an estimation procedure with two components is used to account
for business births. The first component excludes employment losses from
business deaths from sample-based estimation in order to offset the
missing employment gains from business births. This is incorporated into
the sample-based estimation procedure by simply not reflecting sample
units going out of business, but imputing to them the same employment
trend as the other firms in the sample. This procedure accounts for most
of the net birth/death employment.
The second component is an ARIMA time series model designed to estimate
the residual net birth/death employment not accounted for by the
imputation. The historical time series used to create and test the ARIMA
model was derived from the unemployment insurance universe micro-level
database, and reflects the actual residual net of births and deaths over
the past 5 years.
The sample-based estimates from the establishment survey are adjusted
once a year (on a lagged basis) to universe counts of payroll employment
obtained from administrative records of the unemployment insurance program.
The difference between the March sample-based employment estimates and
the March universe counts is known as a benchmark revision, and serves as
a rough proxy for total survey error. The new benchmarks also incorporate
changes in the classification of industries. Over the past decade, absolute
benchmark revisions for total nonfarm employment have averaged 0.3 percent,
with a range from -0.7 to 0.6 percent.
Other information
Information in this release will be made available to sensory impaired
individuals upon request. Voice phone: (202) 691-5200; Federal Relay
Service: (800) 877-8339.
