Technical Notes to Establishment Survey Data
Introduction
BLS collects data each
month on employment, hours, and earnings from a sample of nonfarm
establishments. The sample includes about 141,000 businesses and government
agencies, which cover approximately 486,000 individual worksites drawn from a
sampling frame of Unemployment Insurance (UI) tax accounts covering roughly 9 million establishments.
The active
CES sample includes approximately one-third of all nonfarm payroll employees. From
these data, a large number of employment, hours, and earnings series in
considerable industry and geographic detail are prepared and published each
month. Historical statistics are available at http://www.bls.gov/ces/home.htm,
the BLS Internet site.
Data collection
Each month, BLS collects data on employment,
payroll, and paid hours from a sample of establishments. BLS has a comprehensive
program of new sample unit solicitation in four BLS Regional Data
Collection Centers (DCCs). The DCCs perform initial enrollment of each firm via
telephone, collect the data for several months via Computer Assisted Telephone
Interviewing (CATI), and where possible transfer respondents to a self-reporting
mode such as Touchtone Data Entry (TDE), FAX, or Internet collection. In addition,
the DCC's conduct an ongoing program
of refusal conversion. Very large firms are often enrolled via personal visit
and ongoing reporting is established via Electronic Data Interchange (EDI). Offering survey
respondents a choice of reporting methods helps sustain response rates to this voluntary survey.
The largest portion of the CES sample is collected via EDI (44 percent), while Internet
collection and CATI are used to collect approximately 27 percent and 17 percent of all reports,
respectively. Under EDI, the firm provides an electronic file to BLS each month
in a prescribed file format. This file includes data for all of the firm's
worksites. The file is received, processed, and edited by the BLS operated EDI
Center. Internet collection is one of the fastest growing collection methods. Under Internet
collection, the respondent links to a secure website that contains an image of the questionnaire
and enters their data into the on-line form. The data are subject to a series of edit checks
before being transmitted to BLS.
TDE, another self-reporting mode, is used to collect about 4 percent of the monthly reports.
Under the TDE system, the respondent uses a touchtone telephone to call
a toll-free number and activate an interview session. The questionnaire resides
on the computer in the form of prerecorded questions that are read to the
respondent. The respondent enters numeric responses by pressing the touchtone
phone buttons. Each answer is read back for respondent verification.
FAX collection through the combined Regional BLS DCCs account for
most of the remainder of the reports (5 percent). For the few establishments that do not use the
above methods, data are collected using mail, transcript, magnetic tape, or computer diskette (3 percent).
Chart 1 shows the percentage of the establishments using different data
collection methods.
Concepts
Industrial classification
All data on employment, hours, and earnings for the Nation and for
States and areas are classified in accordance with the 2012 North American Industry Classification System (NAICS), specified by the U.S. Office of Management and Budget. The United States, Canada, and Mexico share this classification system, which allows a direct comparison of economic data across the three countries. For information about
the conversion from NAICS 2007 to NAICS 2012, please see
http://www.bls.gov/ces/cesnaics12.htm.
Establishments are classified into industries on the basis of
their primary activity. Those that use comparable capital equipment, labor, and
raw material inputs are classified together. This information is collected on a
supplement to the quarterly UI tax reports filed by
employers. For an establishment engaging in more than one activity, the entire
employment of the establishment is included under the industry indicated by the
principal activity.
Industry grouping
CES aggregates estimates for detailed industries into one of 17 major industry sector. Major industry sectors are defined in Table 1 below. All major industry sectors include only privately-owned establishments, except for 90-910000 Federal government, 90-920000 State government, and 90-930000 Local government.
Table 1. Major Industry Sectors
| CES Industry Code |
Major Sector Name |
NAICS Codes Included / Ownership |
10-000000 |
Mining and logging |
1133, 21 / Private |
20-000000 |
Construction |
23 / Private |
31-000000 |
Durable goods |
33, 32* / Private |
32-000000 |
Nondurable goods |
31, 32* / Private |
41-420000 |
Wholesale trade |
42 / Private |
42-000000 |
Retail trade |
44-45 / Private |
43-000000 |
Transportation and warehousing |
48-49 / Private |
44-220000 |
Utilities |
22 / Private |
50-000000 |
Information |
51 / Private |
55-000000 |
Financial activities |
52,53 / Private |
60-000000 |
Professional and business services |
54,55,56 / Private |
65-000000 |
Education and health services |
61,62 / Private |
70-000000 |
Leisure and hospitality |
71,72 / Private |
80-000000 |
Other services |
81 / Private |
90-910000 |
Federal government |
All in-scope NAICS / Federal government |
90-920000 |
State government |
All in-scope NAICS / State government |
90-930000 |
Local government |
All in-scope NAICS / Local government |
* CES allocates 3-digit NAICS industries to this major industry sector based on industry description.
Aggregate industry sectors group the major industry sectors into higher levels of detail, as defined in Table 2 below.
Table 2. Aggregate Industry Sectors
| CES Industry Code |
Aggregate Sector Name |
Sectors Included |
00-000000 |
Total nonfarm |
05-000000 Total private, 90-000000 Government |
05-000000 |
Total private |
06-000000 Goods-producing, 08-000000 Private service-providing |
06-000000 |
Goods-producing |
10-000000 Mining and logging, 20-000000 Construction, 30-000000 Manufacturing |
07-000000 |
Service-providing |
40-000000 Trade, transportation, and utilities, 50-000000 Information, 55-000000 Financial activities, 60-000000 Professional and business services, 65-000000 Education and health services, 70-000000 Leisure and hospitality, 80-000000 Other services, 90-000000 Government |
08-000000 |
Private service-providing |
40-000000 Trade, transportation, and utilities, 50-000000 Information, 55-000000 Financial activities, 60-000000 Professional and business services, 65-000000 Education and health services, 70-000000 Leisure and hospitality, 80-000000 Other services |
30-000000 |
Manufacturing |
31-000000 Durable goods, 32-000000 Nondurable goods |
40-000000 |
Trade, transportation, and utilities |
41-420000 Wholesale trade, 42-000000 Retail trade, 43-000000 Transportation and warehousing, 44-220000 Utilities |
90-000000 |
Government |
90-910000 Federal government, 90-920000 State government, 90-930000 Local government |
Industry employment
Employment data refer to persons on establishment payrolls who
received pay for any part of the pay period that includes the 12th day of the
month.
The data exclude proprietors, the unincorporated self-employed, unpaid volunteer
or family employees, farm employees, and domestic employees. Salaried officers of
corporations are included. Government employment covers only civilian employees;
military personnel are excluded. Employees of the Central Intelligence Agency,
the National Security Agency, the National Imagery and Mapping Agency, and the
Defense Intelligence Agency also are excluded.
Persons on establishment payrolls who are on paid sick leave (for
cases in which pay is received directly from the firm), on paid holiday, or on
paid vacation, or who work during a part of the pay period even though they are
unemployed or on strike during the rest of the period are counted as employed.
Not counted as employed are persons who are on layoff, on leave without pay, or
on strike for the entire period, or who were hired but have not yet reported
during the period.
Production and related employees. This category
includes working supervisors and all nonsupervisory employees (including group
leaders and trainees) engaged in fabricating, processing, assembling,
inspecting, receiving, storing, handling, packing, warehousing, shipping,
trucking, hauling, maintenance, repair, janitorial, guard services, product
development, auxiliary production for plant's own use (for example, power
plant), recordkeeping, and other services closely associated with the above
production operations.
Construction employees. This group includes the following
employees in the construction sector: Working supervisors, qualified craft
employees, mechanics, apprentices, helpers, laborers, and so forth, engaged in new
work, alterations, demolition, repair, maintenance, and the like, whether
working at the site of construction or in shops or yards at jobs (such as
precutting and preassembling) ordinarily performed by members of the
construction trades.
Nonsupervisory employees. These are employees (not above
the working-supervisor level) such as office and clerical employees, repairers,
salespersons, operators, drivers, physicians, lawyers, accountants, nurses,
social employees, research aides, teachers, drafters, photographers, beauticians,
musicians, restaurant employees, custodial employees, attendants, line installers
and repairers, laborers, janitors, guards, and other employees at similar
occupational levels whose services are closely associated with those of the
employees listed.
Industry hours and earnings
Concurrent with the release of January 2010 data, the CES program began publishing
all employee hours and earnings as official BLS series. These series were developed to
measure the average hourly earnings and average weekly hours of all nonfarm private sector
employees and the average overtime hours of all manufacturing employees. All employee hours
and earnings were first released as experimental series in April 2007, and included National
level estimates at a Total private sector level and limited industry detail.
Historically, the CES program has published average hours and earnings series for production
employees in the Goods-producing industries and for non-supervisory employees in the Service-providing
industries. These employees account for about 80 percent of Total private nonfarm employment. The
all employee hours and earnings series are more comprehensive in coverage, covering 100 percent of
all paid employees in the private sector, thereby providing improved information for analyzing
economic trends and for constructing other major economic indicators, including nonfarm
productivity and personal income.
All employee average hours and earnings data are derived from reports of payrolls and hours
for all employees. Production/nonsupervisory employee average hours and earnings data are derived from
reports of production and related employees in Manufacturing and Mining and logging, construction
employees in Construction, and nonsupervisory employees in Private-service-providing industries.
Payroll. This refers to the payroll for full- and
part-time all employees, production, construction, and nonsupervisory employees who received pay
for any part of the pay period that includes the 12th day of the month. The
payroll is reported before deductions of any kind, such as those for old-age and
unemployment insurance, group insurance, withholding tax, bonds, or union dues;
also included is pay for overtime, holidays, and vacation, and for sick leave
paid directly by the firm. Excluded from the payroll are bonuses (unless earned and paid regularly each pay period); other pay not earned in the pay period reported (such as retroactive pay); and the value of free rent, fuel, meals, or other payment in kind.
Hours. These are the hours paid for during the pay period
that includes the 12th of the month for all employees, production, construction, and
nonsupervisory employees. Included are hours paid for holidays and vacations, and
for sick leave when pay is received directly from the firm.
Overtime hours. These are hours worked by all employees, production and
related employees, and nonsupervisory employees in Manufacturing for which overtime premiums were paid because the hours were in
excess of the number of hours of either the straight-time workday or the
workweek during the pay period that included the 12th of the month. Weekend and
holiday hours are included only if overtime premiums were paid. Hours for which
only shift differential, hazard, incentive, or other similar types of premiums
were paid are excluded.
Average weekly hours. The workweek information relates to
the average hours for which pay was received and is different from standard or
scheduled hours. Such factors as unpaid absenteeism, labor turnover, part-time
work, and stoppages cause average weekly hours to be lower than scheduled hours
of work for an establishment. Group averages further reflect changes in the
workweek of component industries.
Indexes of aggregate weekly hours and payrolls. The
indexes for all employee aggregate weekly hours are calculated by dividing the current month's
aggregate by the average of the 12 monthly figures for 2007. The
indexes of aggregate weekly hours for production employees are calculated by dividing the current month's
aggregate by the average of the 12 monthly figures for 2002. For basic
industries, the hours aggregates are the product of average weekly hours and
employment (either all employee or production/nonsupervisory employees). At all higher levels of
industry aggregation, hours aggregates are the sum of the component aggregates.
The indexes of aggregate weekly payrolls are calculated by
dividing the current month's aggregate by the average of the 12 monthly figures
for 2007 for all employees and 2002 for production employees. For basic industries, the payroll aggregates are the product of
average hourly earnings and aggregate weekly hours. At all higher levels of
industry aggregation, payroll aggregates are the sum of the component
aggregates.
Average overtime hours. Overtime hours represent that portion of
average weekly hours that exceeded regular hours and for which overtime premiums
were paid in the Manufacturing sector. If an employee were to work on a paid holiday at regular rates,
receiving as total compensation his holiday pay plus straight-time pay for hours
worked that day, no overtime hours would be reported. This applies to both all employee and production and
nonsupervisory employee average overtime hours.
Because overtime hours are premium hours by definition, weekly hours and
overtime hours do not necessarily move in the same direction from month to
month. Such factors as work stoppages, absenteeism, and labor turnover may not
have the same influence on overtime hours as on average hours. Diverse trends at
the industry group level also may be caused by a marked change in hours for a
component industry in which little or no overtime was worked in both the
previous and current months.
Average hourly earnings. Average hourly earnings are on a "gross"
basis. They reflect not only changes in basic hourly and incentive wage rates,
but also such variable factors as premium pay for overtime and late-shift work
and changes in output of employees paid on an incentive plan. They also reflect
shifts in the number of employees between relatively high-paid and low-paid work
and changes in employees' earnings in individual establishments. Averages for
groups and divisions further reflect changes in average hourly earnings for
individual industries.
Averages of hourly earnings differ from wage rates. Earnings are the actual
return to the employee for a stated period; rates are the amount stipulated for a
given unit of work or time. The earnings series do not measure the level of
total labor costs on the part of the employer because the following are
excluded: Benefits, irregular bonuses, retroactive items, payroll taxes paid by
employers, and earnings for those employees not covered under production employee,
construction employee, or nonsupervisory employee definitions.
Average hourly earnings, excluding overtime. Average hourly earnings,
excluding overtime-premium pay, are computed by dividing the total all
employee or production
employee payroll for the industry group by the sum of total all employee or production employee hours
and one-half of total all employee or production employee overtime hours. No adjustments are made for other
premium payment provisions, such as holiday pay, late-shift premiums, and
overtime rates other than time and one-half.
Average weekly earnings. These estimates are
derived by multiplying average weekly hours estimates by average hourly earnings
estimates. Therefore, weekly earnings are affected not only by changes in
average hourly earnings but also by changes in the length of the workweek.
Monthly variations in such factors as the proportion of part-time employees,
stoppages for varying reasons, labor turnover during the survey period, and
absenteeism for which employees are not paid may cause the average workweek to
fluctuate.
Long-term trends of average weekly earnings can be affected by structural
changes in the makeup of the workforce. For example, persistent long-term
increases in the proportion of part-time employees in Retail trade and many of the
services industries have reduced average workweeks in these industries and have
affected the average weekly earnings series.
Real earnings. These earnings are in constant dollars and are
calculated from the earnings averages for the current month using a deflator. The Consumer Price
Index for All Urban Consumers (CPI-U) is used to deflate the new earnings series for all employees,
while the Consumer Price Index for Urban Wage Earners and Clerical employees (CPI-W) is used to
deflate the earnings series for production and nonsupervisory employees. The scope for the CPI-W is
similar to that of the production employee earnings, both in the type of worker which is covered and
the amount of the population that is covered by these series. The CPI-U used to deflate the all
employee earnings is more inclusive than the CPI-W. Since the all employee earnings include all
private sector employees the more inclusive deflator is used in the calculation. The reference base
for the CPI series is the 36-month period covering the years 1982, 1983 and 1984.
Indexes of diffusion of employment change. These indexes
measure the dispersion of employment change in industries over the specified
time span. The overall indexes are calculated from 266 seasonally adjusted
employment series (primarily 4-digit NAICS industries) covering all nonfarm payroll
employment in the private sector. The Manufacturing diffusion indexes are based
on 81 4-digit NAICS industries.
To derive the indexes, each component industry is assigned a value of 0, 50,
or 100 percent, depending on whether its employment showed a decrease, no
change, or an increase, respectively, over the time span. The average value
(mean) is then calculated, and this percent is the diffusion index number.
The reference point for diffusion analysis is 50 percent, the value
indicating that the same number of component industries had increased as had
decreased. Index numbers above 50 show that more industries had increasing
employment and values below 50 indicate that more had decreasing employment. The
margin between the percent that increased and the percent that decreased is
equal to the difference between the index and its complement - that is, 100 minus
the index. For example, an index of 65 percent means that 30 percent more
industries had increasing employment than had decreasing employment (65-(100-65)
= 30). However, for dispersion analysis, the distance of the index number from
the 50-percent reference point is the most significant observation.
Although diffusion indexes commonly are interpreted as showing the percent of
components that increased over the time span, the index reflects half of the
unchanged components as well. (This is the effect of assigning a value of 50
percent to the unchanged components when computing the index.)
Estimating methods
The Current Employment Statistics (CES) or establishment survey estimates of
employment are generated through an annual benchmark and monthly sample link
procedure. Annual universe counts or benchmark levels are generated primarily
from administrative records on employees covered by UI
tax laws. These annual benchmarks, established for March of each year, are
projected forward for each subsequent month based on the trend of the sample
employment and an adjustment for the net of business births and deaths. Benchmarks
and monthly estimates are computed for each basic estimating cell and summed
to create aggregate-level employment estimates.
Benchmarks
For the establishment survey, annual benchmarks are constructed in order to
realign the sample-based employment totals for March of each year with the
UI-based population counts for March. These population counts are much less
timely than sample-based estimates and are used to provide an annual
point-in-time census for employment. For National series, only the March
sample-based estimates are replaced with UI counts. For State and metropolitan
area series, all available months of UI data are used to replace sample-based
estimates. State and area series are based on smaller samples and are therefore
more vulnerable to both sampling and non-sampling errors than National
estimates.
Population counts are derived from the administrative file of employees
covered by UI. All employers covered by UI laws are required to report
employment and wage information to the appropriate State Workforce
Agency four times a year. Approximately 97 percent of Private and Total nonfarm employment within
the scope of the establishment survey is covered by UI. A benchmark for the
remaining 3 percent is constructed from alternate sources, primarily records
from the Railroad Retirement Board (RRB) and County Business Patterns (CBP). The full
benchmark developed for March replaces the March sample-based estimate for each
basic cell. The monthly sample-based estimates for the year preceding and the
year following the benchmark are also then subject to revision.
Monthly estimates for the year preceding the March benchmark are readjusted
using a "wedge back"; procedure. The difference between the final benchmark level
and the previously published March sample estimate is calculated and spread back
across the previous 11 months. The wedge is linear; eleven-twelfths of the March
difference is added to the February estimate, ten-twelfths to the January
estimate, and so on, back to the previous April estimate, which receives
one-twelfth of the March difference. This assumes that the total estimation
error since the last benchmark accumulated at a steady rate throughout the
current benchmark year.
Estimates for the seven months following the March benchmark also are
recalculated each year. These post-benchmark estimates reflect the application
of sample-based monthly changes to new benchmark levels for March and the
recomputation of business birth/death factors for each month.
Following the revision of basic employment estimates, all other derivative
series (such as number of production employees and average hourly earnings) also
are recalculated. New seasonal adjustment factors are calculated and all data
series for the previous five years are re-seasonally adjusted before full
publication of all revised data in February of each year.
Calculating noncovered employment. Noncovered employment results from a difference in scope between the CES program and the Quarterly Census of Employment and Wages (QCEW) program. QCEW employment counts are derived from UI tax reports that individual firms file with their State Employment Security Agency (SESA). Most firms are required to pay UI tax for their employees; however, there are some types of employees that are exempt from UI tax law, but are still within scope for the CES estimates. Examples of the types of employees that are exempt are students paid by their school as part of a work study program; interns of hospitals paid by the hospital for which they work; employees paid by State and local government and elected officials; independent or contract insurance agents; employees of non-profits and religious organizations (this is the largest group of employees not covered); and railroad employees covered under a different system of UI administered by the Railroad Retirement Board. This employment needs to be accounted for in order to set the benchmark level for CES employment.
No single source of noncovered data exists; therefore, BLS uses a number of sources to generate the employment counts, including County Business Patterns and the Annual Survey of Public Employment and Payroll (ASPEP) both from the US Census Bureau, the Railroad Retirement Board, and the State Workforce Agencies.
The majority of noncovered employment is calculated using CBP data. Industries for which noncovered employment is derived from the CBP are provided in Table A. The CBP — which draws from Social Security filings and other records which do include those employees not covered by UI tax laws — is lagged in its publication by approximately two years (e.g. in 2011 the 2009 CBP data was published). To adjust for this lag, CES assumes that the noncovered portion of employment grows or declines at the same rate as the covered portion and trends the CPB data forward using the QCEW trend. The current QCEW employment level is subtracted from the trended CBP figure, and the residual is the noncovered employment level.
Noncovered employment for all CBP based industries, with the exception of Religious organizations, is calculated as follows:
where:
= Noncovered employment estimate
= CBP employment data for NAICS
= QCEW employment for NAICS
= Benchmark year
Noncovered employment for Religious organizations is calculated by:
where:
= Noncovered employment estimate
= CBP employment data for NAICS 813110
= QCEW employment for NAICS 813110
= Benchmark year
Table A. Noncovered Industries Calculated Using County Business Patterns Data
| NAICS Code |
Industry Title |
524113 |
Direct life insurance carriers |
524114 |
Direct health and medical insurance carriers |
524126 |
Direct property and casualty insurance carriers |
524127 |
Direct title insurance carriers |
524128 |
Other direct insurance carriers, except life, health & medical |
524130 |
Reinsurance carriers |
524210 |
Insurance agencies and brokerages |
611110 |
Elementary and secondary schools |
611210 |
Junior colleges |
611310 |
Colleges and universities |
611410 |
Business and secretarial schools |
611420 |
Computer training |
611430 |
Management training |
611511 |
Cosmetology and barber schools |
611512 |
Flight training |
611513 |
Apprenticeship training |
611519 |
Other technical and trade schools |
611610 |
Fine arts schools |
622110 |
General medical and surgical hospitals† |
622210 |
Psychiatric and substance abuse hospitals† |
622310 |
Other hospitals† |
624310 |
Vocational rehabilitation services |
624410 |
Child day care services |
813110 |
Religious organizations |
813211 |
Grantmaking foundations |
813312 |
Environment and conservation organizations |
813410 |
Civic and social organizations |
813910 |
Business associations |
813940 |
Political organizations |
813990 |
Other similar organizations |
†Indicates that noncovered employment is calculated for firms owned both privately and by State and local government.
The estimated employment for industries listed in Table B is calculated from the Annual Survey of Public Employment and Payroll data using the following calculation. .
where:
= Noncovered employment estimate
= Public employment data for higher education*
= Benchmark year
*Public employment data for higher education is the sum of institutional full time and part time employment, and non-institutional full time and part time employment.
Table B. Noncovered Industries Calculated Using Annual Survey of Public Employment and Payroll Data
| NAICS Code |
Industry Title |
611210 |
Junior colleges‡ |
611310 |
Colleges and universities‡ |
‡Indicates that noncovered employment is calculated only for firms owned by State and local government.
Railroad employment estimates are developed based on data provided by the Railroad Retirement Board. RRB data is broken out by railroad class rather than industry so BLS prorates the class data out to NAICS industry classifications (Table C). These data are lagged by one year and are trended forward using a ratio based on the benchmark year and the previous year for the CES series Rail transportation (NAICS 482). This ratio is applied to the RRB data and then mapped to the corresponding NAICS codes.
Table C. Noncovered Industries Calculated Using Railroad Retirement Board Data
| Rail Class |
NAICS Code |
Industry Title |
Class 1 |
482111 |
Line-haul railroads |
Class 2 |
482112 |
Short line railroads |
Class 3 |
482112 |
Short line railroads |
Class 8 |
488210 |
Support activities for rail transportation |
|
532411 |
Commercial air, rail, and water transportation equipment rental and leasing |
Class 9 |
485111 |
Mixed mode transit systems |
|
485113 |
Bus and other motor vehicle transit systems |
|
485999 |
All other transit and ground passenger transportation |
Over time some sources from which BLS draws input data have become unreliable. Where possible BLS has tried to find new sources of input data, but for series that no longer have reliable input data, BLS trends forward the previous year’s noncovered employment levels using a ratio derived from QCEW employment data. These industries are contained in Table D and are calculated using the following method
where:
= noncovered employment estimate
= QCEW employment
= Benchmark year
Table D. Noncovered Industries Calculated Using QCEW Trend
| NAICS Code |
Industry Title |
511110 |
Newspaper publishers |
511120 |
Periodical publishers |
511130 |
Book publishers |
921140 |
Executive and legislative offices‡ |
922190 |
Other justice, public order, and safety activities‡ |
923110 |
Administration of education programs‡ |
924110 |
Administration of air and water resource and solid waste management programs‡ |
925110 |
Administration of housing programs‡ |
926110 |
Administration of general economic programs‡ |
927110 |
Space research and technology‡ |
928110 |
National security‡ |
‡Indicates that noncovered employment is calculated only for firms owned by State and local government.
Corporate officers are one of the largest exemptions outside of the industries listed. In several States, corporate officers are exempt from UI coverage and as a result noncovered employment exists in most NAICS industries in those States. Corporate officers and other State specific employment exemptions outside of those listed above are collected from State offices annually by BLS.
Noncovered employment industries are reviewed and refined periodically. This review is done to identify any changes in state UI coverage, as well as to ensure that BLS captures all exempted employment within the scope of the CES Survey and that our methodology and external data sources are as accurate as possible. When additions and changes are identified during review, they are incorporated with the following March benchmark.
Changing data ratios for Education and Religious organizations.
Due to the small sample in Religious organizations (NAICS 8131)
and definitional exclusions in the collection of data for Educational services
(NAICS 611), certain ratios for these series are recalculated with each benchmark
to allow for the creation of aggregate totals. Production or nonsupervisory employee and women employee
ratios, all employee average hourly earnings and average weekly hours, and production
employee average hourly earnings and average weekly hours for these series are calculated based
on the weighted average of the previous year’s Professional and technical
services, Education and health services, Leisure and hospitality, and Other
services supersectors' annual averages. This year the March 2011 values were set
based on the 2010 annual averages.
The Education services series uses the nonsupervisory employee
ratio, average hourly earnings, and average weekly hours calculated from the
weighted average. The Religious
organizations series uses the production employee ratio, women employee ratio,
average hourly earnings, and average weekly hours calculated from the weighted
average. In both cases, the ratios,
average hourly earnings, and average weekly hours for all employees and production
employees are held constant through the
next benchmark.
Monthly estimation
CES uses a matched sample concept and weighted link relative estimator to
produce employment, hours, and earnings estimates. These methods are described
in Table 2-A. A matched sample
is defined to be all sample members that have reported data for the reference
month and the month prior. Excluded from the matched sample is any sample unit
that reports that it is out-of-business. This aspect of the estimation
methodology is more fully described in the section on estimation of business
births and deaths below.
Stratification. The sample is stratified into 587 basic
estimation cells for purposes of computing National employment estimates. Estimating cell
structures may differ for hours and earnings due to the expansion of hours and earnings
series for all employees and production employees. Cells are defined primarily by detailed industry. In the
Construction supersector, geographic stratification is also used. The estimation
cells can be defined at the 3-, 4-, 5-, and 6-digit NAICS level.
In addition to the estimation cells mentioned above, there are 37 independently
estimated cells which do not aggregate to the summary cell
levels.
Weighted link-relative technique. The estimator for the all
employee (AE) series uses the sample trend in the cell to move the previous level to
the current-month estimated level. A model-based component is applied to account
for the net employment resulting from business births and deaths not captured by
the sample.
The basic formula for estimating all employees is:
,
where:
i = matched
sample unit;
=
weight associated with the CES report;
= current-month
reported all employees;
= previous-month reported all
employees;
= current-month estimated all
employees; and
= previous-month estimated all
employees.
Weighted link and taper technique. The estimator used for
all datatypes other than all employees accounts for the over-the-month change in the sampled
units, but also includes a tapering feature used to keep the estimates close to
the overall sample average over time. The taper is considered to be a level
correction. This estimator uses matched sample data; it tapers the estimate
toward the sample average for the previous month of the current matched sample
before applying the current month's change; and it promotes continuity by
heavily favoring the estimate for the previous month when applying the numerical
factors.
Current month estimate of production and non-supervisory employees (PE) is
defined as
, where
for all i
I and j J
Current month estimate of women employees (WE)
Estimation of the series for women employees is identical to that
described for production employees with the appropriate substitution of women
employees values for the production or nonsupervisory employee values in the previous formulas.
Current month estimate of Hours and Earnings series
The same estimation formulas currently used for the published series on production
and nonsupervisory employee hours and earnings are used for the all employee hours and earnings
series. Within the formulas, simply substitute all employee references for production employee references.
Current month estimate of AWH is defined as
for all i 
I and j J
Current month estimate of AHE is defined as
for all i 
I and j J
where:
i = a matched CES report
I = the set of all matched CES reports
j = a matched CES report where the current month is atypical
J = the set of all matched CES reports where the current month is atypical
(Note: J is a subset of I)
=
weight associated with the CES report;
=
current month reported Production Employees
=
previous month reported Production Employees
= current month
reported Production Employees, atypical record
= previous
month reported Production Employees, atypical record
= current month reported Production
Employees, atypical WH record
= previous month reported Production
Employees, atypical WH record
=
current month estimated Production Employees
=
previous month estimated Production Employees
=
current month reported Weekly Hours
=
previous month reported Weekly Hours
= current month
reported Weekly Hours, atypical record
= previous month
reported Weekly Hours, atypical record
= current month reported Weekly Hours,
atypical PR record
= previous month reported Weekly
Hours, atypical PR record
= current
month estimated Aggregate Employee Hours
= previous
month estimated Aggregate Employee Hours
= current month estimated
Average Weekly Hours
= previous month estimated Average
Weekly Hours
= current
month reported Weekly Payroll
= previous
month reported Weekly Payroll
= current month reported
Weekly Payroll, atypical record
= previous month reported
Weekly Payroll, atypical record
= current month estimated Average
Hourly Earnings
= previous month estimated Average
Hourly Earnings
Current month estimate of overtime hours (OT)
Estimation of overtime hours is identical to that described for weekly hours
with the appropriate substitution of overtime hours values for the weekly hours
values in the previous formula.
Small domain model. National employment estimates for six industries
are produced using the CES Small Domain Model (SDM). Relatively small sample sizes in these industries
limit the reliability of the weighted-link-relative estimator for estimates of all employees
(see Table 3). Estimation of nonsupervisory employees, average weekly hours,
and average weekly and hourly earnings is completed using the standard weighted link relative
methodology used for other series. BLS has been using the CES SDM for some State and metropolitan
area employment series which have small samples since 2003.
Table 3. Small domain model industries
| Industry Title |
CES Industry Code |
Direct health and medical insurance carriers |
55524114 |
Lessors of nonfinancial intangible assets |
55533000 |
Tax preparation services |
60541213 |
Other technical consulting services |
60541690 |
Remediation services |
60562910 |
Recreational and vacation camps |
70721214 |
The CES Small Domain Model (SDM) is a Weighted Least Squares model with two
employment inputs: (1) an estimate based on available CES sample for that series, and
(2) an ARIMA projection based on trend from ten years of historical QCEW data.
Business birth and death estimation. In a dynamic economy,
firms are continually opening and closing. These two occurrences offset each
other to some extent. CES
uses this fact to account for a large proportion of the employment associated
with business births. This is accomplished by excluding 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 births.
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
required.
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.
With any model-based approach, it is desirable to have five or more
years of history to use in developing the models. Due to the absence of reliable
counts of monthly business births and deaths, development of an appropriate
birth/death residual series assumed the following form:
Birth-death residual = Population - Sample-based estimate +
Error
During the net birth/death modeling process, simulated monthly probability
estimates over a 5-year period are created and compared with population
employment levels. Moving from a simulated benchmark, the differences between
the series across time represent a cumulative birth/death component. Those
residuals are converted to month-to-month differences and used as input series
to the modeling process.
Models are fit using X-12 ARIMA (Auto-Regressive Integrated Moving Average).
Outliers, level shifts, and temporary ramps are automatically identified. Five models
were tested, and the model exhibiting the lowest average forecast error was
selected. Table
2-B shows the net birth/death model figures for the post-benchmark period of
April 2011 to October 2011.
Prior to the release of preliminary January 2011 employment estimates in February 2011, birth/death residuals were calculated on an annual basis and then applied each month during development of monthly estimates. With the release of the January 2011 preliminary estimates, BLS began updating the CES net birth/death model component of the estimation process on a quarterly basis instead of annually. This change allows for the incorporation of QCEW data into the birth/death model as soon as it becomes available and reduces the post-benchmark revision in the CES series. This change does not impact the timing or frequency of CES monthly and annual releases or when benchmarking is done. For more information on the CES switch to quarterly net birth/death forecasting, please visit http://www.bls.gov/ces/ces_quarterly_birthdeath.htm.
Residential and Nonresidential specialty trade contractors estimates.
Residential and nonresidential employment estimates in Specialty trade contractors (NAICS 238)
are produced as breakouts under the standard NAICS
coding structure. Benchmarks for these series are developed from the QCEW data
and independent estimates for these series are made on a monthly basis and raked
to the estimates produced under the standard structure to ensure that the sum of
the Residential specialty trade contractors and Non-residential specialty trade
contractors series is consistent with the published total for Specialty trade
contractors at the 3-digit NAICS level.
The raking adjustment uses the following methodology:
Estimates are derived independently for the residential and nonresidential
groups at the 4-digit NAICS level for each region. The regional estimates are
rounded and summed to the 4-digit NAICS level for both the residential and
non-residential groups. Within each 4-digit NAICS series, ratios of
residential-to-total employment and nonresidential-to-total employment are
calculated.
At the 4-digit NAICS level, the sum of the Residential/Nonresidential series
is subtracted from the official industry-region cell structure total to
determine the amount that must be raked. The total amount that must be raked is
multiplied by the ratios to determine what percentage of the raked amount should
be applied to the residential group and what percentage should be applied to the
nonresidential group.
Once the residential and nonresidential groups receive their proportional
amount of raked employment, the two groups are aggregated again to the 4-digit
NAICS level. At this point they are equal to the 4-digit NAICS total derived
from the official industry-region cell structure. This raking process also
forces additivity at the 3-digit NAICS level.
Only estimates of all employees are made for the Residential and Nonresidential
specialty trade contractor series. Estimates of construction employees, women employees, and
hours and earnings are not produced.
Aggregation procedures
CES estimates at the basic estimating level and then aggregates these estimates to higher industry levels. Aggregation procedures are specific to the data type and published level of precision (i.e. the degree of rounding).
Publication Precision. For employment data types, CES publishes estimates for major industry and aggregate industry sectors in thousands, rounded to the thousands, except for major industry sectors 41-420000 Wholesale trade, 42-000000 Retail trade, 43-000000 Transportation and warehousing, and 44-220000 Utilities, which are published in thousands, rounded to the hundreds. More detailed employment estimates are published in thousands, rounded to the hundreds.
For hours and earnings data types, estimates are published using the same procedures for all levels of detail. Hours data types are published in hours, rounded to the tenths. Earnings data types are published in dollars, rounded to the cent.
Employment (AE, PE, and WE). All employment data types use the same method for aggregation. Basic level estimates, rounded to the hundreds, are aggregated to summary level estimates up to and including major industry sectors and then rounded to the published precision. Aggregate industry sector estimates are then calculated by summing the rounded major industry and aggregate industry sector estimates that make up the aggregate industry sector and then rounded according to the published precision.
Average weekly hours (AE and PE). The aggregation method for average weekly hours of all employees and production employees is identical, with the appropriate substitution of all employee values or production employee values in the following formulas. Average weekly hours are estimated at the basic level and combined with employment estimates for the same basic level to calculate aggregate employee hours. Aggregate Employee Hours (AH) are rounded to the tenths at the basic estimating level and calculated as shown:
AH = AWH * Emp
where:
AH = current month aggregate employee hours calculation for the basic level , rounded to the tenths;
AWH = current month AWH estimate for the basic level, rounded as published; and
Emp = current month employment estimate for the basic level, rounded as published.
Next, aggregate employee hours are added up to the summary levels. Average weekly hours, rounded to the tenths, are calculated for the summary level by:
AWH = 
where:
AWH = current month average weekly hours estimate for the summary level, rounded to the tenths;
AH = current month aggregate employee hours calculation for the summary level, rounded to the tenths; and
Emp = current month employment estimate for the summary level, rounded according to published precision.
Average hourly earnings (AE and PE). The aggregation method for average hourly earnings of all employees and production employees is identical, with the appropriate substitution of all employee values or production employee values in the following formulas. Average hourly earnings are estimated at the basic level and combined with employment estimates for the same basic level to calculate aggregate employee hours. Calculation of aggregate employee hours (AH) is identical to that described for average weekly hours.
Aggregate payroll (PR) is calculated using basic level average weekly hours, average hourly earnings, and employment. Basic level aggregate payroll calculations are rounded to the cent and are defined as:
PR = AHE * AWH * Emp
where:
PR = current month aggregate payroll calculation for the basic level, rounded to the cent;
AHE = current month average hourly earnings estimate for the basic level, rounded as published;
AWH = current month average weekly hours estimate for the basic level, rounded as published; and
Emp = current month employment estimate for the basic level, rounded according to published precision.
To calculate the summary level estimates, summarize the aggregate employee hours and aggregate payroll to the summary level. Average hourly earnings, rounded to the cent, are calculated for the summary level by:
AHE = 
where:
AHE = current month average hourly earnings estimate for the summary level, rounded to the cent;
AH = current month aggregate employee hours calculation for the summary level, rounded to the tenths; and
PR = current month aggregate payroll calculation for the summary level, rounded to the cent.
Last Modified Date: May 8, 2012
