Chapter 2.
Employment, Hours, and Earnings from the Establishment
Survey
Estimating
Procedures
Employment
Employment estimates are made at what is termed the basic
estimating cell level, and are aggregated upward to broader
levels of industry detail by simple addition. Basic cells
are defined by industry (usually at the five- or six-digit
NAICS level). Within the construction industry,
stratification by geographic region also is used.
To obtain all-employee estimates for a basic
estimating cell, the following five steps are
necessary:
- A total employment figure (benchmark) is obtained
for the basic estimating cell as of a specified
month (March).
- For each report, employment is multiplied by the
sample selection weight to obtain weighted employment
for the months for which estimates are being made and
for the previous month.
- For each cell, the ratio of the weighted all
employees sample total in 1 month to that in the
preceding month (termed the weighted link-relative) is
computed for sample establishments that reported for
both months.
- Beginning with the benchmark month, the
all-employee estimate for each month is obtained by
multiplying the all-employee estimate for the previous
month by the weighted link-relative for the current
month.
- Add a net birth/death estimate from the model
described below.
The following example illustrates how the estimating
procedure is applied in preparing a series. Assume that
the estimate for all employees for a given cell was 50,000
in July. The sample, comprising 60 establishments that
reported for both months, had weighted employment of 25,000
in July and 26,000 in August, a 4-percent increase.
The net birth/death estimate for August equals 100.
To derive the August estimate, the ratio of weighted
sample employment for August to that for July is applied
to the July estimate:
![](https://webarchive.library.unt.edu/web/20090507023305im_/http://stats.bls.gov/opub/hom/images/homch2_f3.gif)
This procedure, known as the weighted link-relative
technique, is efficient in that it takes advantage of a
reliable, complete count of employment and of the high
correlation between levels of employment in successive
months in identical establishments.
Business birth and death modeling. A net birth/death
factor is added to national employment estimates to produce
the monthly published estimates. Regular updating of the
CES sample frame with information from the UI universe
files helps to keep the CES survey current with respect to
employment change due to business births and deaths. The
timeliest UI universe files available however, always will
be a minimum of 9 months out of date. Thus, the CES survey
cannot rely on regular frame maintenance alone to provide
estimates of the employment effects of business births and
deaths. BLS utilizes a model-based approach for this
component.
While both the business birth and business death portions
of total employment are generally significant, the net
contribution is relatively small and stable. To account for
this net birth/death portion of total employment, BLS has
an estimation procedure with two components. The first
component uses business deaths to impute employment for
business births. 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 imputation component is incorporated in the weighted
link-relative estimation procedure by simply not reflecting
sample units going out of business, but imputing to them the
same trend as the other firms in the sample. The ARIMA
time-series model estimates the residual net business
birth/death employment that is not accounted for by
imputation. The historical time series used to create
and test the ARIMA model was derived from the UI universe
micro-level database and reflects the actual residual net
of births and deaths over the past 5 years.
The net birth/death model component figures are unique to
each month and exhibit a seasonal pattern that can result
in negative adjustments in some months.
Production and nonsupervisory workers. To obtain
estimates of production (or construction or nonsupervisory)
worker employment, the ratio of weighted production workers
to the weighted all employees in the sample is assumed to
equal the same ratio in the universe. The current months
production worker ratio is thus estimated and then
multiplied by the all-employee estimate. The weighted
difference- link and taper formula, described in the
section on hours and earnings, is used to estimate the
current months production worker ratio. This formula adds
the change in the matched samples production worker ratio
(the weighted difference link) to the prior months estimate,
which has been slightly modified to reflect changes in the
sample composition (the taper). An analogous method is used
to estimate the number of women workers.
The estimates for each type of series (all employees,
production workers, and women workers) for individual basic
estimating cells are summed to obtain corresponding totals
for broader industry sectors.
Hours and earnings Independent benchmarks are not available for the
hours and earnings series; consequently, the levels derive
directly from the CES weighted-sample averages.
Average weekly hours and average hourly earnings.
Before hours and earnings sample averages or estimates
are calculated, production workers and aggregate hours
and payrolls must be multiplied by sample weights both
for the month for which estimates are being made and for
the prior month. To obtain average weekly hours for a
basic estimating cell, the sum of reported worker hours
for the establishments classified in the cell is divided
by the total number of production workers reported for the
same establishments. In computing average hourly earnings,
the reported payroll is divided by the reported worker hours
for the same establishments.
Sample averages of average weekly hours and average
hourly earnings are first modified at the basic
estimating-cell level through the use of a wedging technique
designed to compensate for month-to-month changes in the
sample of reporting establishments (weighted difference-link
and taper).
For example, unmodified sample averages for the current
month, ,are obtained from aggregates from a matched sample
of establishments reporting for both the current month and
the previous month. Similarly, unmodified sample averages
for the previous month, xp, are calculated from the same
matched sample. The expression xc-xp denotes the change
between the 2 months.
The other component of the weighted difference-link and
taper formula is the estimate of average hourly earnings for
the previous month, Xp. Because the panel of establishments
reporting in the sample is not completely fixed from month
to month, Xp and xp may differ. An estimate for the current
month, Xc, is obtained by using both pieces of
information:
![](https://webarchive.library.unt.edu/web/20090507023305im_/http://stats.bls.gov/opub/hom/images/homch2_f4.gif)
The procedure reflected in this formula has the
following advantages: (1) It uses matched sample data;
(2) it tapers the estimate toward the sample average for
the previous month of the current matched sample (xp)
before applying the current months change; and (3) it
promotes continuity by heavily favoring the estimate
for the previous month (Xp) when applying the numerical
factors.
Average weekly hours and average hourly earnings for
industries and groups above the basic estimating cell level
are weighted averages of the figures for component cells.
The average weekly hours for each basic estimating cell
are multiplied by the corresponding estimate of the number
of production workers to derive aggregate worker hours.
Payroll aggregates are the product of the aggregate worker
hours and average hourly earnings. The payroll and
worker-hour aggregates for industry groups and divisions
are the sums of the aggregates for the
component industries.
Average weekly hours for industry groups are obtained
by dividing the worker-hour aggregates by the corresponding
production worker estimates. Average hourly earnings for
industry groups are computed by dividing the payroll
aggregates by the worker-hour aggregates. This method is
equivalent to weighting average weekly hours by the
estimated number of production workers in the universe
and weighting average hourly earnings by the estimated
worker hours for the universe.
For all levels, from basic estimating cells to
supersectors and higher aggregates, average weekly
earnings are computed by multiplying average hourly
earnings by average weekly hours.
Overtime hours. Average weekly overtime hours are
estimated in basically the same way as average weekly
hours. Overtime worker-hour sample averages are used in
the computations in place of the sample averages for
total worker hours. The sample totals for production
workers used in the computations are those for the reports
containing overtime worker hours (including those reporting
zero overtime hours) as well as production workers, total
payroll, and total worker hours. The wedging technique and
the summary level estimating technique for the overtime
hours estimation also are comparable to those used to
estimate average weekly hours.
Average hourly and weekly earnings in 1982 dollars.
Average hourly and weekly earnings are computed and
published in terms of 1982 dollars to give an approximate
measure of changes in real average earnings (earnings
in constant dollars). These series are computed by
dividing the average hourly and weekly earnings (in
current dollars) for a given month by the BLS Consumer
Price Index for Urban Wage Earners and Clerical Workers
(CPI-W) (1982 = 100) for the same month.
Average hourly earnings, excluding overtime, for
the manufacturing supersector. These estimates are
computed by dividing the total production worker payroll
for an industry group by the sum of the total production
worker hours and one-half of the total overtime worker
hours, which is equivalent to the payroll divided by
straight-time hours. This method excludes overtime
earnings at an assumed rate of 1 1/2 times the straight-time
rates; no further adjustment is made for other premium
payment provisions.
Indexes of aggregate weekly hours and payrolls.
These indexes are prepared by dividing the current months
aggregates by the annual average aggregate for 2002. The
hours aggregates are the product of average weekly hours and
production, construction, or nonsupervisory worker
employment; the payroll aggregates are the product of the
hours aggregates and average hourly earnings.
Indexes of diffusion of employment changes. These
indexes measure the dispersion among industries of the
change in employment over the specified timespan. The
overall indexes are calculated from seasonally adjusted
employment series for four-digit NAICS-coded industries.
The diffusion indexes for private nonfarm payroll
employment are based on estimates for 278 industries,
while the manufacturing indexes are based on
estimates for 84 industries. Each component series
is assigned a value of 0, 50, or 100 percent,
depending on whether its employment showed a decrease,
no change, or an increase over a given period. The
average (mean) value is then calculated, and this
percent is the diffusion index number. The reference
point for interpreting the diffusion indexes is 50
percent, the value that indicates that the same
number of component industries have increased in
employment as have decreased. The direction and
distance of the index number from the 50 percent
reference point indicate whether growing (above 50)
or declining (below 50) industries predominate and by
what magnitude. The margin between the percentage of
industries that increased and the percentage that
decreased employment equals twice the difference
between the index number and 50 percent.
Seasonally adjusted series
Many economic statistics reflect a regularly
recurring seasonal movement that can be measured
from past experience. By eliminating that part of
the change attributable to the normal seasonal variation,
it is possible to observe the cyclical and other
nonseasonal movements in these series. Seasonally
adjusted series are published regularly for selected
employment, hours, and earnings series. CES published
146 seasonally adjusted employment series in 2003.
X-12 ARIMA software, developed by the U.S. Census
Bureau, is used to seasonally adjust CES data on a
concurrent basis. Using special features of X-12 ARIMA,
adjustments are made to remove the effect of the
variable number of weeks between surveys from month to
month (about 1 month in 3 has a 5-week instead of a 4-week
interval) and to remove the effect of the variable number
of work days in the reference month, to adjust for moving
holidays, and to adjust for the variations in the number
of election poll workers in November from year to year.
CES processes concurrent seasonal adjustment on a
monthly basis using the latest estimates of employment,
hours, and earnings. Seasonally adjusted employment
series for broader industry groups are obtained by
summing the seasonally adjusted data for the component
industries. Seasonally adjusted hours and earnings
averages for broader level industry groups are weighted
averages of the seasonally adjusted component series.
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