estimates revised and when are they final?
On what basis
are the industries in the Current Employment Statistics survey
How are the
data in the CES survey collected?
How are CES estimates developed?
What is a
seasonally adjusted estimate?
Do hours and
earnings statistics include overtime?
How are the
How can I get
employment data for all private and public hospitals or schools?
What is a
What is the UI
Why are the
payroll survey estimates benchmarked to UI universe counts?
How does the
benchmark revision affect the employment data for months prior to the
How does the
benchmark revision affect the employment data for months subsequent to the
What are the
causes of benchmark revisions?
What is the
birth/death adjustment? Why is it used?
How are the
birth/death adjustment amounts calculated?
How do strikes
affect CES estimates?
(1) Why are estimates revised and when are
Estimates are presented as soon as sufficient data have been collected to
meet standards of accuracy and reliability so that they can be used to guide
policy decisions. Aggregate level estimates (all 3-digit NAICS industry groups
and above) are published with the first release of preliminary data, usually three
Fridays after the survey reference week. At this point, about 72 percent of the
sample have been collected and used in the estimates. One month later, when over
92 percent of the sample has been collected, estimates are published for the
first time for all of the detailed industries, and the second set of preliminary
estimates are published for the aggregate levels. The "first final" estimates
are published the following month, when over 94 percent of the sample reports
have been collected. These estimates, published the third month after the month
of reference, are the official estimates until the next benchmark revision which
is published each February.
All estimates, including annual averages, are subject to two revisions in
connection with benchmarking, and seasonally adjusted series may be revised
slightly three additional times, in conjunction with reseasonal adjustment. See
the question on benchmarking in this section for further discussion.
(2) On what basis are the industries in the Current
Employment Statistics survey classified?
A sample establishment in the CES survey is an economic unit, such as a
factory, which produces goods or services. It is generally at a single location
and engaged predominantly in one type of economic activity. Establishments
reporting on the schedule (form BLS 790) are classified into industries based on
their principal product or activity. Ideally, the principal good or service
should be determined by its relative share of current production costs and
capital investment at the establishment. In practice, however, it is often
necessary to use other variables such as revenue, shipments, or employment as
proxies for measuring significance. Industry classification, based on the
North American Industry Classification System (NAICS) 2012, is determined from a supplement
to the quarterly unemployment insurance tax reports filed by each employer.
NAICS was developed through a cooperative effort between the United States,
Mexico, and Canada. NAICS is based on a production-oriented concept in which
industries with similar production processes are classified together.
(3) How are the data in the CES survey collected?
BLS as well as BLS Data Collection
Centers collect data on employment, hours, and earnings from a sample of
about 145,000 businesses and government agencies, which cover approximately
557,000 individual worksites drawn from a sampling frame of approximately
9 million Unemployment Insurance tax accounts. The active CES sample includes
approximately one-third of all nonfarm payroll employees. Sample respondents
extract the requested data from their payroll records, which must be maintained
for a variety of tax and accounting purposes. Data are collected by telephone,
touch-tone self response, computer-assisted interviews, fax technology, internet,
and mail. The use of electronic media results in more rapid
response times and higher response rates.
(4) How are CES estimates developed?
Data submitted on the 790 schedule are used in
developing National, Statewide, and major metropolitan area estimates. All States'
samples are combined to form a collective sample for developing
National industry estimates. Statewide samples range from nearly 30,000 sample
units in California to about 1,000 units in smaller States. It should be noted
that State estimation procedures are designed to produce accurate data for each
individual State. BLS independently develops National and State and area employment, hours, and earnings series and
does not force State estimates to sum to National totals nor vice versa. Because
each State series is subject to larger sampling and nonsampling errors than the
National series, summing them cumulates individual State level errors and can
cause significant distortions at an aggregate level. Due to these
statistical limitations, BLS does not compile a "sum of States" employment
series and cautions users that such a series is subject to a relatively large
and volatile error structure.
(5) What is a seasonally adjusted estimate?
Seasonal adjustment removes the change in employment that is due to normal
seasonal hiring or layoffs, thus leaving an over-the-month change that reflects
only employment changes due to trend and irregular movements. Seasonally
adjusted estimates of employment and other series are generated using the X-12
ARIMA program developed by the United States Census Bureau. This program adjusts
estimates for fluctuations that occur on a regular basis within a year. For
example, employment in Retail trade rises prior to the Christmas holiday season
and then falls following the holiday. Annual averages, however, are computed
using data that are not seasonally adjusted.
(6) Do hours and earnings statistics include overtime?
Yes, employers report payroll and hours including overtime. Overtime hours
are published for Manufacturing industries only.
(7) How are the estimates organized?
The data are first separated by ownership — private and public. The public
ownership is further divided into Federal, State, and Local. Each of these is
then organized by industry (NAICS codes). Thus, for example, employment
in all hospitals would be the sum of the estimates for Private, Federal, State,
and Local hospitals. Federal government estimates also are published
for the Department of Defense, the U.S. Postal Service, Ship building,
Hospitals, and Other federal government.
(8) How can I get employment data for all private and
public hospitals or schools?
See above answer.
(9) What is a benchmark?
The benchmark adjustment, a standard part of the payroll survey estimation
process, is a once-a-year re-anchoring of the sample-based employment estimates
to full population counts available principally through Unemployment Insurance
(UI) tax records filed by employers with State Employment Security Agencies. By
late September of each year, BLS completes preliminary tabulations of these
universe counts for the first quarter of the year and routinely shares that
information with the public.
(10) What is the UI universe count?
The Bureau's UI universe count is a quarterly tabulation from administrative
records of the number of employees covered by UI laws.
UI universe counts, available on a lagged basis, contain individual employer
records for approximately 9 million establishments and cover nearly 97 percent of Total
nonfarm employment; they thus provide a benchmark for the sample-based
estimates. For the small segment of the population not covered by UI, BLS
develops employment benchmarks from several alternative sources.
(11) Why are the payroll survey estimates benchmarked to
UI universe counts?
The CES survey, like many other surveys, establishes benchmarks on a periodic
basis in order to adjust its sample-based estimates to complete population
counts available from administrative records.
Because of their much smaller size, sample surveys offer an ability to
produce very timely estimates along with a greater ability to control the data
quality of individual reports. There is a need, however, to recalibrate sample
estimates periodically against full population counts. The use of a population
count, or benchmark, allows a sample survey to adjust the results of estimation
processes for new birth units in the population frame and to adjust for
sampling and other nonsampling errors.
(12) How does the benchmark revision affect the employment
data for months prior to the benchmark month?
Following standard BLS methodology, the March UI-based benchmark employment
level replaces the March sample-based employment estimate, and then the
difference between the benchmark level and the sample-based estimate is wedged
back to the previous benchmark level. For example, the benchmark revision that
was released in February 2013 replaced the March 2012 estimate with the
benchmark level, increasing the employment level for that month by 424,000. To
wedge this adjustment over the prior year, one-twelfth of the difference was added to
April 2011, two-twelfths to May, and so forth, through February 2012 which received
eleven-twelfths of the difference.
(13) How does the benchmark revision affect the employment
data for months subsequent to the benchmark month?
Estimates for the period after the benchmark month (the post-benchmark
period) are calculated for each month based on the new benchmark level, new net
birth/death figures, and the annual sample update, which is implemented in
November following the benchmark month.
(14) What are the causes of benchmark
In general, differences between universe counts and sample-based estimates
result from both sampling and nonsampling error. Although sampling error is
present in the payroll survey, as it is in all surveys, the CES sample is so
large that sampling error is not usually an important factor in explaining the
Nonsampling error arises in the survey estimates and in the universe counts
from both the UI and the alternative sources used to establish the noncovered
population benchmarks. Nonsampling error is a more significant cause of
benchmark revisions. Sources of nonsampling error include coverage, response,
and processing errors in both data series. Additionally, the survey is
potentially subject to sample design and estimator biases.
(15) What is the birth/death adjustment? Why is it
To derive a complete count of Total nonfarm employment, a two-part estimator
is required. First, a sample-based estimate of the over-the-month employment
change is made using the CES sample, which represents about 557,000 business
establishments. The sample is drawn from the population of all employers who
have filed Unemployment Insurance tax returns. The sample does not include
employers who have recently formed new businesses but who have not yet been
added to the Unemployment Insurance tax files. Business births occur every
month, and failure to include an estimate for these units would result in a
consistent underestimation of employment totals, that is, a downward bias.
Therefore, BLS utilizes a model-based technique to estimate for this part of the
In a dynamic economy, firms are continually opening and closing. These two
occurrences offset each other to some extent. That is, firms that are born
replace firms that die. CES uses this fact to account for a large proportion of
the employment associated with business births. This is accomplished by
excluding such business death units from the matched sample definition.
Effectively, business deaths are not included in the sample-based link portion
of the estimate, and the implicit imputation of their previous month's
employment is assumed to offset a portion of the employment associated with
There is an operational advantage associated with this approach as well. Most
firms will not report that they have gone out of business; rather, they simply
cease reporting and are excluded from the link, as are all other nonrespondents.
As a result, extensive follow-up with monthly nonrespondents to determine
whether a company is out of business or simply did not respond is not
Employment associated with business births will not exactly equal that
associated with business deaths. The amount by which it differs varies by month
and by industry. As a result, the residual component of the birth/death offset
must be accounted for by using a model-based approach.
(16) How are the birth/death adjustment amounts
During the net birth/death modeling process, simulated monthly probability
estimates containing continuous and imputed employment over a 5-year period are
created and compared with population employment levels that contain actual
business births and deaths along with the continuous units. Moving from a
simulated benchmark, the differences between the series across time represent a
cumulative error component. Those residuals are converted to month-to-month
differences and are used as input series to the modeling process.
Models are fit using X-12 ARIMA. Outliers, level shifts, and temporary ramps
are automatically identified. Five models are tested, and the model exhibiting
the lowest average forecast error is selected for each series.
(17) How do strikes affect CES estimates?
Anyone paid for working any portion of the
reference pay period (pay period that includes the 12th of the month)
is counted as employed. Therefore, to be counted as not
employed for purposes of the CES survey, a person on strike or
strike-related layoff must not receive pay for the entire
reference pay period.
Average Weekly Hours (AWH) and Average Hourly Earnings (AHE)
These are hours for which employees are paid for work or on paid
leave for the reference pay period (including paid vacation, holidays, sick
leave, or other paid leave).
When strikers or laid off employees work part but not all of the reference
pay period, then they are counted as employed according to the CES survey but
with reduced hours. The magnitude of the reduction on average weekly hours
depends on the proportion of employees in the industry's sample with reduced hours
and the number of hours they worked.
Employees who are on strike or layoff for the entire reference pay period
do not have any effect on the average weekly hours estimate
unless their normal hours differ significantly from the average for the
industry. Similarly, average hourly earnings estimates will be little affected
unless the normal hourly earnings of those on strike or layoff differ
significantly from the average for the industry.
January with reference week Sunday 1/6 to Saturday 1/12
February with reference week Sunday 2/10 to Saturday 2/16
Company A strike: Strike/layoff activity. (This company has a weekly pay
||on strike the whole reference pay period
||on strike part of the reference pay period
||laid off after the reference pay period
The strike is settled February 19. All employees are called back to work
Effect on January employment:
over-the-month change lowered by 2,000
Effect on February employment:
over-the-month change lowered by 4,500
Effect on January AWH:
reduced slightly by the 1,500 on strike part of the reference pay
Effect on February AWH:
the January effect is reversed because the employees with shorter hours
in that month are off payrolls*
* Both the January and February AWH and AHE also could be affected if
strikers' normal hours and/or hourly earnings differ significantly from industry
Note: For confidentiality reasons, CES staff cannot provide
company-specific information, including dates or employees involved in
strike/layoffs, other than what is already publicly available at the time of
the strike. Contact the company or news sources for more specific
Last Modified Date: February 1, 2013