Benchmark Article 

BLS Establishment Estimates Revised to Incorporate March 2008 Benchmarks 

• Introduction• Summary of the benchmark revisions• Revisions in the post-benchmark period• Why benchmarks differ from estimates• Benchmark revisions for other data types• Methods• Availability of revised data• Changes to the CES published series • Small domain model• Seasonal adjustment procedure• Special model adjustments

Introduction Steven Kroll Steven Kroll is an economist in the Division of Current Employment Statistics, Office of Employment and Unem

Bureau of Labor Statistics. Telephone: (202) 691-6555; e-mail: CESInfo@bls.gov

With the release of data for January 2009, the Bureau of Labor Statistics (BLS) introduced its annual revision of employment, hours, and earnings from the Current Employment Statistics (CES) monthly survey of nonfarm estayear, the CES survey realigns its sample-based estimates to incorporate universe counts of employment—a procebenchmarking. Comprehensive counts of employment, or benchmarks, are derived primarily from unemploymenreports that nearly all employers are required to file with State Workforce Agencies. Summary of the benchmark revisions The March 2008 benchmark level for total nonfarm employment is 136,944,000; this figure is 89,000 below the estimate for March 2008, an adjustment of -0.1 percent. Table 1 shows the total nonfarm percentage benchmark ten years. 
Table 2 shows the nonfarm employment benchmarks for March 2008, not seasonally adjusted, by industry. As is 

benchmark revisions at many industry levels were larger in percentage terms than at total nonfarm, but were offs

supersectors had downward revisions. The largest downward revision occurred in leisure and hospitality with a ror -1.1 percent. The revision is concentrated in limited-service restaurants, revised by -94,100 or -2.7 percent, ful

revised by -48,100 or -1.1 percent, and drinking places, alcoholic beverages, revised by -16,100 or -4.6 percent. Professional and business services was revised -63,000, or -0.4 percent, while financial activities was revised -23Within professional and business services, temporary help services was revised downwards by 24,800, or 1.0 peractivities, mortgage and nonmortgage loan brokers revised downwards by 23,200, or 26.3 percent. Manufacturing and education and health services each had a revision of -17,000, or -0.1 percent. Most of the revi

manufacturing was driven by heavy duty trucks, which was revised down by 10,400, or 34.6 percent. Within eduservices, offices of dentists was the largest downward revision of 15,400, or 1.9 percent. Six supersectors had upward revisions. Trade, transportation, and utilities was revised upward by 65,000, or 0.2 p

supersector, retail trade dominated with a revision of 92,800, or 0.6 percent. Also contributing was an upward revtransportation and warehousing of 15,000, or 0.3 percent, while wholesale trade was revised downwards by 43,1Other significant upward revisions occurred in construction (49,000 or 0.7 percent) and government (48,000 or 0supersectors with upward revisions were other services (revised up 9,000 or 0.2 percent), information (8,000 or 0mining and logging (3,000 or 0.4 percent). 

Revisions in the post-benchmark period Post-benchmark period estimates from April 2008 to December 2008 were calculated for each month based on nAlso, beginning in April, model-based estimates for the net of birth/death employment were revised to incorporathe most recent year of universe employment counts. Text table A shows the net birth/death model figures for the 

the post-benchmark period. From April 2008 to December 2008, the cumulative net birth/death model added 821,005,000 in the previously published April to December estimates. 
Text table A. Net Birth/Death Estimates, Post-Benchmark 2008

Mining

& 

Logging 

Construction Manufacturing

Trade, 

Transportation,

& Utilities 

InformationFinancial ActivitiesProfessional & Business Services Education & Health Services 

H

April 1 45 -16 17 3 -8 36 31 May 1 40 4 24 3 3 12 7 June 2 27 5 17 1 5 18 -8 July 0 0 -13 -6 -3 -5 -1 4 August 1 11 3 14 4 2 20 10 September 1 9 1 17 1 2 2 14 October 1 8 -7 25 2 13 50 27 November 0 -7 2 12 2 3 10 8 

2008 

December 0 -10 1 18 3 14 7 7 

Cumulative Total 7 123 -20 138 16 29 154 100 

Revisions to November and December also reflect incorporation of the annual CES sample update and the routinadditional sample units not available for the respective months' preliminary estimates. Why benchmarks differ from estimates A benchmark revision is the difference between the benchmark employment level for a given March and its correbased estimate. The overall accuracy of the establishment survey is usually gauged by the size of this differencerevision often is regarded as a proxy for total survey error, but this does not take into account error in the univers

employment counts obtained from quarterly unemployment insurance tax forms are administrative data that reflekeeping practices and differing State laws and procedures. The benchmark revision can be more precisely interpbetween two independently derived employment counts, each subject to its own error sources. Like all sample surveys, the establishment survey is susceptible to two sources of error: sampling error and nons

Sampling error is present any time a sample is used to make inferences about a population. The magnitude of th
variance, relates directly to sample size and the percentage of the universe covered by that sample. The CES mo

slightly under one-third of the universe, exceptionally high by usual sampling standards. This coverage insures a at the total nonfarm employment level. Both the universe counts and the establishment survey estimates are subject to nonsampling errors common to al

response, and processing errors. The error structures for both the CES monthly survey and the UI universe are coprograms generally produce consistent total employment figures, each validating the other. Over the last decaderevisions at the total nonfarm level have averaged 0.2 percent, with an absolute range of 0.1 percent to 0.6 percen

Benchmark revision effects for other data types The routine benchmarking process results in revisions to the series for production and nonsupervisory workers. Tbenchmark employment levels for these series; they are revised by preserving ratios of employment for the particemployees employment prior to benchmarking, and then applying these ratios to the revised all-employee figurescalculated at the basic cell level and then aggregated to produce the summary estimates. Average weekly hours and average hourly earnings are not benchmarked; they are estimated solely from reports respondents at the basic estimating cell level. The aggregate industry level of the hours and earnings series are derived as a weighted average. The production worker employment estimates for the basic cells are used as weights for the hours and earnings estimates for bro

groupings. Adjustments of the all employee estimates to new benchmarks may alter the weights, which, in turn, estimates for hours and earnings of production or nonsupervisory workers at higher levels of aggregation. Generally, new employment benchmarks have little effect on hours and earnings estimates for major groupings. hours and earnings estimates of a broader group, employment revisions have to be relatively large and must affechours or earnings averages that are substantially different from those of other industries in their group. Table 4 g

the levels of specific hours and earnings series resulting from the March 2008 benchmark. At the total private lechange in average weekly hours from the previously published level, while average hourly earnings was increase

published level by 5 cents. 

Methods Benchmark adjustment procedure. Establishment survey benchmarking is done on an annual basis to a populatiofrom the administrative file of employees covered by unemployment insurance (UI). The time required to complprocess--from the full collection of the UI population data to publication of the revised industry estimates--is abo
benchmark adjustment procedure replaces the March sample-based employment estimates with UI-based popula

March. The benchmark therefore determines the final employment levels, while sample movements capture monBenchmarks are established for each basic estimating cell and are aggregated to develop published levels. On a nadjusted basis, the sample-based estimates for the year preceding and the year following the benchmark also are revision. Employment estimates for the months between the most recent March benchmark and the previous yeaadjusted using a "wedge-back" procedure. In this process, the difference between the benchmark level and the p

March estimate for each estimating cell is computed. This difference, or error, is linearly distributed across the 1

subsequent to the previous benchmark; eleven-twelfths of the March difference is added to February estimates, teestimates, and so on, ending with the previous April estimates, which receive one-twelfth of the March differencprocedure assumes that the total estimation error accumulated at a steady rate since the last benchmark. Applyinover-the-month sample changes to the revised March level yields revised estimates for the months following the New net birth/death model estimates also are calculated and applied during post-benchmark estimation, and new from the annual update. Benchmark source material. The principal source of benchmark data for private industries is the Quarterly Censand Wages (QCEW). These employment data are provided to State Employment Security Agencies by employelaws. BLS uses several other sources to establish benchmarks for the remaining industries partially covered or emandatory UI coverage, accounting for nearly 3 percent of the nonfarm employment total. Data on employees covered under Social Security laws, published by the U.S. Census Bureau in County Business 

augment UI data for industries not fully covered by the UI scope, such as nonoffice insurance sales workers, chilreligious organizations, and private schools and hospitals. Benchmarks for State and local government hospitals institutions are based on the Annual Census of Governments conducted by the Census Bureau. Benchmark data are available only on a lagged basis. Extrapolation to a current level is accomplished by applying the employmecovered part of the population in these industries to the noncovered part. Universe data for interstate railroads ar

Railroad Retirement Board. Business birth and death estimation. Regular updating of the CES sample frame with information from the UI ukeep the CES survey current with respect to employment from business births and business deaths. The timeliesavailable, however, always will be a minimum of 9 months out of date. The CES survey thus can not rely on reg

maintenance alone to provide estimates for business birth and death employment contributions. BLS has researcbased and model-based approaches to measuring birth units that have not yet appeared on the UI universe frame. demonstrated that sampling for births was not feasible in the very short CES production timeframes, the Bureau 

based approach for this component. 
Earlier research indicated that while both the business birth and death portions of total employment are generally 

contribution is relatively small and stable. To account for this net birth/death portion of total employment, BLS estimation procedure with two components. The first component uses business deaths to impute employment for is incorporated into the sample-based link relative estimate procedure by simply not reflecting sample units going imputing to them the same trend as the other firms in the sample. The second component is an ARIMA time seriestimate the residual net birth/death employment not accounted for by the imputation. The historical time series the ARIMA model was derived from the UI universe micro level database, and reflects the actual residual net of the past five years. The net birth/death model component figures are unique to each month and include negative months. Furthermore, these figures exhibit a seasonal pattern similar to the seasonal patterns of the continuing bAvailability of revised data LABSTAT, the BLS public database on the Internet, contains all historical employment, hours, and earnings data 

this benchmark, including both unadjusted and seasonally adjusted data. The data can be accessed at https://www

Current Employment Statistics homepage. Changes to the CES published series All CES series are evaluated annually for sample size, coverage, and response rates. The following series change

evaluation of the sample and universe coverage for NAICS industries. Some series proved to have sufficient sam

more detail. Other small industries no longer have sufficient sample to be estimated and published separately and with other similar industries for estimation and publication purposes, as shown below. Most of the collapsed and the manufacturing sector where employment has been declining over a number of years. Historical data for the sescope were reconstructed to provide consistent time series. Exhibit 1. Newly published series effective with the March 2008 benchmark revisions

Industry title NAICS code CES industry code New industry 

Biotechnology research 541711 60541711 Biotechnology research was broken out from Research 

the physical, engineering, and life sciences (NAICS 541

Physical, engineering, and 

life sciences research 541712 60541712 Physical, engineering, and life sciences was broken out 

development in the physical, engineering, and life scien
Exhibit 2. Series with changed scope

Industry title NAICS code 

CES 

industry 

code 

Industries collapsed 

All other 

plywood and 

engineered 

wood products 

321213,4,9 31321214 

Engineered wood members and trusses (NAICS 321213,4) is collapswood products (NAICS 321219). The collapsed series is renamed Alengineered wood products. 

Glass 

containers and 

products made 

of purchased 

glass 

327213,5 31327215 

Glass containers (NAICS 327213) is collapsed into Glass products mglass (NAICS 327215). The collapsed series is renamed Glass contaimade of purchased glass. 

Miscellaneous 

electronic 

instruments 

334514,6,7,8,9 31334519 Irradiation apparatus (NAICS 334517) is collapsed into Miscellaneou

instruments (NAICS 334519). 

All other 

electrical 

equipment and 

components 

33592,9 3133599 Communication and energy wires and cables (NAICS 33592) is colla

electrical equipment and components (NAICS 33599). 

All other 

miscellaneous 

manufacturing 

33993,9 3133999 Dolls, toys, and games (NAICS 33993) is collapsed into All other mi

manufacturing (NAICS 33999). 

Women's and 

all other cut 

and sew 

apparel 

31523,9 3231529 

Women's cut and sew apparel (NAICS 31523) is collapsed into Othe

(NAICS 31529). The collapsed series is renamed Women's and all o

apparel. 

Petrochemicals, 

industrial 

gases, s

ynthetic 

dyes, and 

pigments 

32511,2,3 3232513 

Petrochemicals and industrial gases (NAICS 32511,2) is collapsed in

pigments (NAICS 32513). The collapsed series is renamed Petroche

gases, synthetic dyes, and pigments. 

Urban transit 

systems and 

interurban and 

rural bus 

transportation 

4851,2 434852 

Urban transit systems (NAICS 4851) is collapsed into Interurban and transportation (NAICS 4852). The collapsed series is renamed Urban interurban and rural transportation. 
Exhibit 2. Series with changed scope

Industry title NAICS code 

CES 

industry 

code 

Industries collapsed 

Support 

activities for 

water 

transportation, 

except marine 

cargo handling 

48831,3,9 4348839 

Port and harbor operations (NAICS 48831) is collapsed into Navigatiother water transportation support activities (NAICS 48833,9). The crenamed Support activities for water transportation, except marine ca

Historical sites, 

zoos, botanical 

gardens, nature 

parks, and 

similar 

institutions 

71212,3,9 707121219

Historical sites (NAICS 71212) is collapsed into Zoos, botanical gard

and similar institutions (NAICS 71213,9). The collapsed series is rensites, zoos, botanical gardens, nature parks, and similar institutions. 

Exhibit 3. Discontinued all employee series

Industry title NAICS code CES industry code Next highest publishe

Pottery, ceramics, and plumbing fixtures 32711 3132711 Clay products and refractories (NAIC

Clay building materials and refractories 32712 3132712 Clay products and refractories (NAIC

Glass containers 327213 31327213 Glass and glass products (NAICS 32

Iron, steel pipe, and tube from purchased steel 33121 3133121 Steel products from purchased steel (

Rolling and drawing of purchased steel 33122 3133122 Steel products from purchased steel (

Rolled steel shapes 331221 31331221 Steel products from purchased steel (

Nonferrous metal, except CU and AL, shaping 33149 3133149 Other nonferrous metal production (N

Steel foundries 331512,3 31331513 Ferrous metal foundries (NAICS 331

Air and gas compressors 333912 31333912 Pumps and compressors (NAICS 333

Pumps and pumping equipment, including 

measuring and dispensing 333911,3 31333913 Pumps and compressors (NAICS 333

Irradiation apparatus 334517 31334517 Electronic Instruments (NAICS 3345

Small electronic appliances 33521 3133521 Household appliances (NAICS 3352
Exhibit 3. Discontinued all employee series

Industry title NAICS code CES industry code Next highest publishe

Major appliances 33522 3133522 Household appliances (NAICS 3352

Communication and energy wires and cables 33592 3133592 Other electrical equipment and comp

Dolls, toys, and games 33993 3133993 Other miscellaneous manufacturing (

Sugar 31131 3231131 Sugar and confectionary products (N

Women's cut and sew apparel 31523 3231523 Cut and sew apparel (NAICS 3152) 

Leather and hide tanning and finishing and 

other leather products 3161,9 323169 Leather and allied products (NAICS 

Petrochemicals and industrial gases 32511,2 3232512 Basic chemicals (NAICS 3251) 

Resin and synthetic rubber 32521 3232521 Resin, rubber, and artificial fibers (N

Synthetic rubber 325212 32325212 Resin, rubber, and artificial fibers (N

Unlaminated plastics profile shapes 326121 32326121 Plastics pipe, fittings, and profile sha

Plastics pipe and pipe fittings 326122 32326122 Plastics pipe, fittings, and profile sha

Other chemicals 42469 4142469 Chemicals (NAICS 4246) 

Sea, coastal, and Great Lakes transportation 4831 434831 Water transportation (NAICS 483) 

Urban transit systems 4851 434851 Transit and ground passenger transpo

Port and harbor operations 48831 4348831 Support activities for water transport

Historical sites 71212 7071212 Museums, historical sites, zoos, and 

Amusement and theme parks 71311 7071311 Amusement parks and arcades (NAIC

Amusement arcades 71312 7071312 Amusement parks and arcades (NAIC

Exhibit 4. Discontinued production worker, hours, and earnings series

Industry title NAICS code CES industry code

Office supplies, except paper 33994 3133994 

Paperboard mills 32213 3232213 

Manifold business forms printing 323116 32323116 

Dried and dehydrated food 311423 32311423 
Exhibit 5. Discontinued average overtime series

Industry title NAICS code CES industry code 

Office supplies, except paper 33994 3133994 

Paperboard mills 32213 3232213 

Exhibit 6. Change in title

CES industry code Original industry title New industry title 

10000000 Natural resources and mining Mining and logging 

Small domain model The employment estimator for lessors of nonfinancial intangible assets (CES industry code 555330000) has been 

standard CES weighted-link-relative technique to the CES Small Domain Model (SDM). The SDM is used for insample alone is insufficient for reliable estimates. The CES SDM is a Weighted Least Squares model with two eman estimate based on available CES sample for that series, and (2) an ARIMA projection based on 10 years of hisFurther background on the SDM is provided in the CES technical notes. 

This brings the number of industries estimated by using SDM to six. The other industries are direct health and mcarriers, tax preparation services, other technical consulting services, remediation services, and recreational and v

Seasonal adjustment procedure BLS uses X-12 ARIMA software developed by the U.S. Census Bureau to seasonally adjust national employmenseries derived from the CES program. Individual series are seasonally adjusted using either a multiplicative or a(Exhibit 7), and seasonal adjustment factors are directly applied to the component levels. For employment, indiv

levels are seasonally adjusted, and higher level aggregates are formed summing these components. Seasonally ahours and earnings are obtained by taking weighted averages of the seasonally adjusted data for the component s
Special model adjustments 

Variable survey intervals. Beginning with the release of the 1995 benchmark, BLS refined the seasonal adjustmcontrol for survey interval variations, sometimes referred to as the 4- versus 5-week effect. Although the CES sua consistent concept - the pay period including the 12th of each month - inconsistencies arise because there are sosometimes 5 weeks between the week including the 12th in a given pair of months. In highly seasonal industriesbe an important determinant of the magnitude of seasonal hires or layoffs that have occurred at the time the survecomplicating seasonal adjustment. Standard seasonal adjustment methodology relies heavily on the experience of the most recent 3 years to determi

seasonal change in employment for each month of the current year. Prior to the implementation of the adjustmen

not distinguish between 4- and 5-week survey intervals, and the accuracy of the seasonal expectation depended in 

how well the current year’s survey interval corresponded with those of the previous 3 years. All else the same, thfor distortion occurred when the current month being estimated had a 5-week interval but the 3 years preceding iintervals, or conversely when the current month had a 4-week interval but the 3 years preceding it were all 5-weeBLS adopted REGARIMA (regression with auto-correlated errors) modeling to identify the estimated size and sicalendar effect for each published series. REGARIMA combines standard regression analysis, which measures cor more variables, with ARIMA modeling, which describes and predicts the behavior of data series based on its omany economic time series, including nonfarm payroll employment, observations are auto-correlated over time; value is significantly dependent on the observations that precede it. These series, therefore, usually can be succeARIMA models. If auto-correlated time series are modeled through regression analysis alone, the measured rela

variables of interest may be distorted due to the influence of the auto-correlation. Thus, the REGARIMA techniqmeasuring relationships among variables of interest in series that exhibit auto-correlation, such as nonfarm payroIn this application, the correlations of interest are those between employment levels in individual calendar monththe survey intervals for those months. The REGARIMA models evaluate the variation in employment levels attrseparate survey interval variables, one specified for each month, except March. March is excluded because there weeks between the February and March surveys. Models for individual basic series are fit with the most recent 1

available, the standard time span used for CES seasonal adjustment. The REGARIMA procedure yields regression coefficients for each of the 11 months specified in the model. Theprovide estimates of the strength of the relationship between employment levels and the number of weeks betwee

modeled months. The X-12 ARIMA software also produces diagnostic statistics that permit the assessment of thsignificance of the regression coefficients, and all series are reviewed for model adequacy. 
Because the 11 coefficients derived from the REGARIMA models provide an estimate of the magnitude of varia

levels associated with the length of the survey interval, these coefficients are used to adjust the CES data to remo

effect. These "filtered" series then are seasonally adjusted using the standard X-12 ARIMA software. 

For a few series, REGARIMA models do not fit well; these series are seasonally adjusted with the X-12 software 

interval effect adjustment. There are several additional special effects modeled through the REGARIMA procesbelow. Construction series. Beginning with the 1996 benchmark revision, BLS utilized special treatment to adjust cons

series. In the application of the interval effect modeling process to the construction series, there initially was diff

identifying and measuring the effect because of the strong influence of variable weather patterns on employment 

industry. Further research allowed BLS to incorporate interval effect modeling for the construction industry by dconstruction series into its finer industry and geographic estimating cells and tightening outlier designation parama more precise identification of weather-related outliers that had masked the interval effect and clouded the seasopatterns in general. With these outliers removed, interval effect modeling became feasible. The result is a seaso

for construction that is improved because it is controlled for two potential distortions: unusual weather events an

week effect. Floating holidays. BLS is continuing the practice of making special adjustments for average weekly hours and aovertime series to account for the presence or absence of religious holidays in the April survey reference period aLabor Day in the September reference period, back to the start date of each series. Local government series. A special adjustment also is made in November each year to account for variations in the presence or absence of poll workers in the local government, excluding educational services series. Refinements in hours and earnings seasonal adjustment. With the release of the 1997 benchmark, BLS impleme

the seasonal adjustment process for the hours and earnings series to correct for distortions related to the method ovarying length of payroll periods across months. There is a significant correlation between over-the-month chanaverage weekly hour (AWH) and the average hourly earnings (AHE) series and the number of weekdays in a mononeconomic fluctuations in these two series. Both AWH and AHE show more growth in "short" months (20 or "long" months (22 or 23 weekdays). The effect is stronger for the AWH than for the AHE series. The calendar effect is traceable to response and processing errors associated with converting payroll and hours in

sample respondents with semi-monthly or monthly pay periods to a weekly equivalent. The response error comerespondents reporting a fixed number of total hours for workers regardless of the length of the reference month, wconversion process assumes that the hours reporting will be variable. A constant level of hours reporting most li
employees are salaried rather than paid by the hour, as employers are less likely to keep actual detailed hours rec

employees. This causes artificial peaks in the AWH series in shorter months that are reversed in longer months. The processing error occurs when respondents with salaried workers report hours correctly (vary them according month), which dictates that different conversion factors be applied to payroll and hours. The CES processing sysconversion factor for both fields, resulting in peaks in the AHE series in short months and reversals in long montREGARIMA modeling is used to identify, measure, and remove the length-of-pay-period effect for seasonally adweekly hours and average hourly earnings series. The length-of-pay-period variable proves significant for explamovements in all the service-providing industries except utilities. For AHE, the length-of-pay-period variable is wholesale trade, retail trade, information, financial activities, professional and business services, and other servicin the service-providing industries except utilities have been adjusted from January 1990 forward. The AHE seritrade, retail trade, information, financial activities, professional and business services, and other services have beJanuary 1990 forward as well. For this reason, calculations of over-the-year change in the establishment hours ashould use seasonally adjusted data. The series to which the length-of-pay-period adjustment is applied are not subject to the 4- versus 5-week adjustm

cannot support the number of variables that would be required in the regression equation to make both adjustmen

series that have the calendar effects modeling described above. Exhibit 7. Model specifications

Seasonal Adjustment - AE 

NAICS Tabcode Tabcode title Mode 4/5 week adj Other adj 

1011331000 Logging MULT X 1021100000 Oil and gas extraction MULT X 1021200000 Mining, except oil and gas - X Indirect11021210000 Coal mining MULT X 1021300000 Support activities for mining ADD X 2023610000 Residential building - X Indirect 2023620000 Nonresidential building - X Indirect 2023700000 Heavy and civil engineering construction ADD X 2023800000 Specialty trade contractors - X Indirect 2023800100 Residential specialty trade contractors MULT X Raked22023800200 Nonresidential specialty trade contractors ADD X Raked 3132100000 Wood products ADD X 
Exhibit 7. Model specifications

Seasonal Adjustment - AE 

NAICS Tabcode Tabcode title Mode 4/5 week adj Other adj 

3132700000 Nonmetallic mineral products ADD X 3133100000 Primary metals MULT X 3133200000 Fabricated metal products MULT X 3133300000 Machinery MULT X 3133400000 Computer and electronic products - X Indirect 3133410000 Computer and peripheral equipment MULT X 3133420000 Communications equipment MULT X 3133440000 Semiconductors and electronic components MULT X 3133450000 Electronic instruments MULT X 3133500000 Electrical equipment and appliances MULT X 3133600000 Transportation equipment ADD3133600100 Motor vehicles and parts ADD3133700000 Furniture and related products ADD X 3133900000 Miscellaneous manufacturing MULT X 3231100000 Food manufacturing MULT X 3231200000 Beverages and tobacco products MULT X 3231300000 Textile mills MULT X 3231400000 Textile product mills MULT X 3231500000 Apparel MULT X 3231600000 Leather and allied products MULT X 3232200000 Paper and paper products MULT X 3232300000 Printing and related support activities MULT X 3232400000 Petroleum and coal products MULT X 3232500000 Chemicals MULT X 3232600000 Plastics and rubber products MULT X 4142300000 Durable goods MULT X 4142400000 Nondurable goods MULT X 4142500000 Electronic markets and agents and brokers MULT X 4244100000 Motor vehicle and parts dealers - X Indirect 4244110000 Automobile dealers ADD X 4244200000 Furniture and home furnishings stores MULT X 
Exhibit 7. Model specifications

Seasonal Adjustment - AE 

NAICS Tabcode Tabcode title Mode 4/5 week adj Other adj 

4244300000 Electronics and appliance stores MULT X 4244400000 Building material and garden supply stores MULT X 4244500000 Food and beverage stores MULT X 4244600000 Health and personal care stores MULT X 4244700000 Gasoline stations MULT X 4244800000 Clothing and clothing accessories stores MULT X 4245100000 Sporting goods, hobby, book, and music stores MULT X 4245200000 General merchandise stores - X Indirect 4245210000 Department stores MULT X 4245300000 Miscellaneous store retailers MULT X 4245400000 Nonstore retailers MULT X 4348100000 Air transportation MULT X 4348200000 Rail transportation MULT X 4348300000 Water transportation MULT X 4348400000 Truck transportation ADD X 4348500000 Transit and ground passenger transportation ADD4348600000 Pipeline transportation MULT X 4348700000 Scenic and sightseeing transportation ADD X 4348800000 Support activities for transportation ADD X 4349200000 Couriers and messengers MULT X 4349300000 Warehousing and storage ADD X 4422100000 Utilities MULT X 5051100000 Publishing industries, except Internet MULT X 5051200000 Motion picture and sound recording industries MULT X 5051500000 Broadcasting, except Internet MULT X 5051700000 Telecommunications MULT X 5051800000 Data processing, hosting, and related services MULT X 5051900000 Other information services MULT X 5552100000 Monetary authorities-central bank MULT X 5552200000 Credit intermediation and related activities - X Indirect 
Exhibit 7. Model specifications

Seasonal Adjustment - AE 

NAICS Tabcode Tabcode title Mode 4/5 week adj Other adj 

5552210000 Depository credit intermediation MULT X 5552211000 Commercial banking MULT X 5552300000 Securities, commodity contracts, investments MULT X 5552400000 Insurance carriers and related activities MULT X 5552500000 Funds, trusts, and other financial vehicles MULT X 5553100000 Real estate MULT X 5553200000 Rental and leasing services MULT X 5553300000 Lessors of nonfinancial intangible assets MULT X 6054100000 Professional and technical services - X Indirect 6054110000 Legal services MULT X 6054120000 Accounting and bookkeeping services ADD X 6054130000 Architectural and engineering services ADD X 6054150000 Computer systems design and related services ADD X 6054160000 Management and technical consulting services MULT X 6055100000 Management of companies and enterprises MULT X 6056100000 Administrative and support services - X Indirect 6056130000 Employment services MULT X 6056132000 Temporary help services MULT X 6056140000 Business support services ADD X 6056170000 Services to buildings and dwellings MULT X 6056200000 Waste management and remediation services ADD X 6561100000 Educational services ADD X 6562100000 Ambulatory health care services - X Indirect 6562110000 Offices of physicians MULT X 6562140000 Outpatient care centers MULT X 6562160000 Home health care services ADD X 6562200000 Hospitals MULT X 6562300000 Nursing and residential care facilities - X Indirect 6562310000 Nursing care facilities MULT X 6562400000 Social assistance - X Indirect 6562440000 Child day care services ADD X 
Exhibit 7. Model specifications

Seasonal Adjustment - AE 

NAICS Tabcode Tabcode title Mode 4/5 week adj Other adj 

7071100000 Performing arts and spectator sports MULT X 7071200000 Museums, historical sites, zoos, and parks MULT X 7071300000 Amusements, gambling, and recreation ADD X 7072100000 Accommodation MULT X 7072200000 Food services and drinking places ADD X 8081100000 Repair and maintenance MULT X 8081200000 Personal and laundry services MULT X 8081300000 Membership associations and organizations ADD9091100000 Federal, except U.S. Postal Service ADD X 9091912000 U.S. Postal Service MULT X 9092161100 State government education ADD X 9092200000 State government, excluding education MULT X 9093161100 Local government education ADD X 9093200000 Local government, excluding education ADD X Election adjustment3

Seasonal Adjustment - WW 

NAICS Tabcode Tabcode title Mode 4/5 week adj Other adj 

1000000000 Mining and Logging MULT X 1021000000 Mining MULT X 2000000000 Construction MULT X 3100000000 Durable goods MULT X 3200000000 Nondurable goods MULT X 4142000000 Wholesale trade MULT X 4200000000 Retail trade MULT X 4300000000 Transportation and warehousing MULT X 4422000000 Utilities MULT X 5000000000 Information MULT X 5552000000 Finance and insurance MULT X 
Seasonal Adjustment - WW 

NAICS Tabcode Tabcode title Mode 4/5 week adj Other adj 

5553000000 Real estate and rental and leasing MULT X 6054000000 Professional and technical services ADD X 6055000000 

Management of companies and enterprises 

MULT X 

6056000000 Administrative and waste services MULT X 6561000000 Educational services ADD X 6562000000 Health care and social assistance ADD X 7071000000 Arts, entertainment, and recreation ADD X 7072000000 Accommodation and food services ADD X 8000000000 Other services ADD X 9091000000 Federal MULT X 9092000000 State government ADD X 9093000000 Local government MULT X Election adjustment3

Seasonal Adjustment - PW 

NAICS Tabcode Tabcode title Mode 4/5 week adj Other adj

1000000000 Mining and Logging MULT X 2000000000 Construction ADD X 3132100000 Wood products ADD X 3132700000 Nonmetallic mineral products ADD X 3133100000 Primary metals MULT X 3133200000 Fabricated metal products MULT X 
Seasonal Adjustment - PW 

NAICS Tabcode Tabcode title Mode 4/5 week adj Other adj

3133300000 Machinery MULT X 3133400000 Computer and electronic products MULT X 3133500000 Electrical equipment and appliances MULT X 3133600000 Transportation equipment ADD 3133600100 Motor vehicles and parts ADD 3133700000 Furniture and related products MULT X 3133900000 Miscellaneous manufacturing MULT X 3231100000 Food manufacturing MULT X 3231200000 Beverages and tobacco products ADD X 3231300000 Textile mills MULT X 3231400000 Textile product mills MULT X 3231500000 Apparel MULT X 3231600000 Leather and allied products MULT X 3232200000 Paper and paper products MULT X 3232300000 Printing and related support activities MULT X 3232400000 Petroleum and coal products MULT X 3232500000 Chemicals ADD X 3232600000 Plastics and rubber products MULT X 4142000000 Wholesale trade MULT X 4200000000 Retail trade MULT X 4300000000 Transportation and warehousing MULT X 4422000000 Utilities MULT X 5000000000 Information MULT X 5500000000 Financial activities MULT X 
Seasonal Adjustment - PW 

NAICS Tabcode Tabcode title Mode 4/5 week adj Other adj

6000000000 Professional and business services MULT X 6500000000 Education and health services ADD X 7000000000 Leisure and hospitality ADD X 8000000000 Other services MULT X 

Seasonal Adjustment - AWH 

NAICS 

Tabcode Tabcode title Mode 4/5 week adj 10/11 day adj Easter/Labor Day adj 

1000000000 Mining and Logging MULT X X 2000000000 Construction ADD X X 3132100000 Wood products MULT X X 3132700000 Nonmetallic mineral products MULT X X 3133100000 Primary metals MULT X X 3133200000 Fabricated metal products MULT X X 3133300000 Machinery MULT X X 3133400000 Computer and electronic products MULT X X 3133500000 Electrical equipment and appliances MULT X X 3133600000 Transportation equipment MULT X X 3133600100 Motor vehicles and parts MULT X X 3133700000 Furniture and related products MULT X X 3133900000 Miscellaneous manufacturing MULT X X 3231100000 Food manufacturing MULT X X 
Seasonal Adjustment - AWH 

NAICS 

Tabcode Tabcode title Mode 4/5 week adj 10/11 day adj Easter/Labor Day adj 

3231200000 Beverages and tobacco products MULT X X 3231300000 Textile mills ADD X X 3231400000 Textile product mills MULT X X 3231500000 Apparel MULT X X 3231600000 Leather and allied products MULT X X 3232200000 Paper and paper products MULT X X 3232300000 Printing and related support activities MULT X X 3232400000 Petroleum and coal products MULT X X 3232500000 Chemicals MULT X 3232600000 Plastics and rubber products MULT X X 4142000000 Wholesale trade MULT X X 4200000000 Retail trade MULT X 4300000000 Transportation and warehousing MULT X X 4422000000 Utilities MULT X 5000000000 Information MULT X 5500000000 Financial activities MULT X 6000000000 Professional and business services MULT X X 6500000000 Education and health services MULT X 7000000000 Leisure and hospitality MULT X 8000000000 Other services MULT X X 

Seasonal Adjustment - AHE 

NAICS 

Tabcode Tabcode title Mode 4/5 week adj 10/11 day adj 
Seasonal Adjustment - AHE 

NAICS 

Tabcode Tabcode title Mode 4/5 week adj 10/11 day adj 

1000000000 Mining and Logging MULT X 2000000000 Construction MULT X 3100000000 Durable goods ADD X 3200000000 Nondurable goods MULT X 4142000000 Wholesale trade ADD X 4200000000 Retail trade MULT X 4300000000 Transportation and warehousing MULT X 4422000000 Utilities ADD X 5000000000 Information MULT X 5500000000 Financial activities MULT X 6000000000 Professional and business services MULT X 6500000000 Education and health services ADD X 7000000000 Leisure and hospitality MULT X 8000000000 Other services MULT X 

Seasonal Adjustment Comparison - AOT 

NAICS 

Tabcode Tabcode title Mode 4/5 week adj 10/11 day adj Easter/Labor Day adj 

31000000 Durable goods MULT X X 32000000 Nondurable goods MULT X X 

1 Seasonal adjustment occurs at the lowest available industry level. 2 Residential and nonresidential specialty trade estimates are raked to the specialty trade estimates to ensure cons3Special adjustment for the presence/absence of poll workers in local government. 
Benchmark Tables

Table 1. Percent differences between nonfarm employment benchmarks and estimates by industry division, MarcTable 2. Nonfarm employment benchmarks by industry, March 2008Table 3. Differences in seasonally adjusted levels and over-the-month changes, total nonfarm employment, Janua2008Table 4. Hours and earnings estimates, selected industries, March 2008

Table 1. Percent differences between nonfarm employment benchmarks and estimates by industry supersec

Industry 1999 2000 2001 2002 2003 2004 

Total 0.2 0.4 - 0.1 - 0.2 - 0.1 0.2 

Total private .2 .3 - .2 - .4 - .2 .2 

Mining and logging .9 .7 

Construction -.8 .6 

Manufacturing -1.1 -.4 

Trade, transportation, and utilities (2) .2 

Information -2.6 -1.0 

Financial activities .2 .1 

Professional and business services -.7 -.2 

Education and health services .3 .2 

Leisure and hospitality .5 1.2 

Other services 1.4 .5 

Government .1 .6 .3 1.0 .3 .1 

(1) Differences are based on comparisons of final published March estimates and benchmark levels, as originally (2) Less than 0.05 percent. 
Table 2. Nonfarm employment benchmarks by industry, March 2008 (levels in thousands)

Industry Benchmark Estimate Am

Total nonfarm 136,944 137,033 -89 

Total private 114,104 114,241 -137 

Goods-producing 21,347 21,312 35 

Mining and logging 741 738 3 

Logging 55 57 -2 

Mining 686 680 6 

Oil and gas extraction 155 155 0 

Mining, except oil and gas 215 219 -4 

Coal mining 78 79 -1 

Support activities for mining 316 307 9 

Construction 7,047 6,998 49 

Construction of buildings 1,651 1,609 42 

Heavy and civil engineering construction 909 896 13 

Specialty trade contractors 4,487 4,494 -7 

Manufacturing 13,559 13,576 -17 

Durable goods 8,599 8,626 -27 

Wood products 471 485 -14 

Nonmetallic mineral products 468 477 -9 

Primary metals 451 452 -1 

Fabricated metal products 1,551 1,552 -1 

Machinery 1,193 1,196 -3 

Computer and electronic products 1,254 1,252 2 

Computer and peripheral equipment 183 186 -3 

Communications equipment 128 129 -1 

Semiconductor and electronic components 437 428 9 

Electronic instruments 443 446 -3 

Electrical equipment and appliances 426 419 7 

Transportation equipment 1,656 1,653 3 

Furniture and related products 499 510 -11 

Miscellaneous manufacturing 633 631 2 

Nondurable goods 4,960 4,950 10 

Food manufacturing 1,459 1,450 9 
Table 2. Nonfarm employment benchmarks by industry, March 2008 (levels in thousands)

Industry Benchmark Estimate Am

Beverage and tobacco products 193 185 8 

Textile mills 159 159 0 

Textile product mills 151 154 -3 

Apparel 203 198 5 

Leather and allied products 33 34 -1 

Paper and paper products 447 455 -8 

Printing and related support activities 606 613 -7 

Petroleum and coal products 114 110 4 

Chemicals 852 859 -7 

Plastics and rubber products 743 733 10 

Service-providing 115,597 115,721 -124 

Private service-providing 92,757 92,929 -172 

Trade, transportation, and utilities 26,330 26,265 65 

Wholesale trade 5,981 6,024 -43 

Electronic markets and agents and brokers 846 836 10 

Retail trade 15,279 15,186 93 

Motor vehicle and parts dealers 1,875 1,890 -15 

Automobile dealers 1,220 1,230 -10 

Furniture and home furnishings stores 542 563 -21 

Electronics and appliance stores 549 531 18 

Building material and garden supply stores 1,242 1,229 13 

Food and beverage stores 2,849 2,865 -16 

Health and personal care stores 1,003 989 14 

Gasoline stations 844 844 0 

Clothing and clothing accessories stores 1,446 1,447 -1 

Sporting goods, hobby, book and music stores 637 643 -6 

General merchandise stores 3,023 2,908 115 

Department stores 1,545 1,498 47 

Miscellaneous store retailers 834 845 -11 

Nonstore retailers 435 434 1 

Transportation and warehousing 4,515 4,500 15 

Air transportation 503 505 -2 
Table 2. Nonfarm employment benchmarks by industry, March 2008 (levels in thousands)

Industry Benchmark Estimate Am

Rail transportation 230 232 -2 

Water transportation 63 59 4 

Truck transportation 1,389 1,396 -7 

Transit and ground passenger transportation 434 427 7 

Pipeline transportation 41 41 0 

Scenic and sightseeing transportation 23 26 -3 

Support activities for transportation 588 584 4 

Couriers and messengers 573 579 -6 

Warehousing and storage 672 652 20 

Utilities 555 555 0 

Information 3,016 3,008 8 

Publishing industries, except Internet 892 882 10 

Motion picture and sound recording industries 381 379 2 

Broadcasting, except Internet 318 322 -4 

Telecommunications 1,027 1,020 7 

Data processing, hosting, and related services 265 273 -8 

Other information services 134 132 2 

Financial activities 8,171 8,194 -23 

Finance and insurance 6,056 6,103 -47 

Monetary authorities - central bank 23 21 2 

Credit intermediation and related activities 2,765 2,814 -49 

Depository credit intermediation 1,823 1,820 3 

Commercial banking 1,361 1,343 18 

Securities, commodity contracts, investments 868 866 2 

Insurance carriers and related activities 2,311 2,315 -4 

Funds, trusts, and other financial vehicles 90 87 3 

Real estate and rental and leasing 2,115 2,091 24 

Real estate 1,469 1,441 28 

Rental and leasing services 618 618 0 

Lessors of nonfinancial intangible assets 28 31 -3 

Professional and business services 17,733 17,796 -63 

Professional and technical services 7,883 7,891 -8 
Table 2. Nonfarm employment benchmarks by industry, March 2008 (levels in thousands)

Industry Benchmark Estimate Am

Legal services 1,163 1,166 -3 

Accounting and bookkeeping services 1,064 1,100 -36 

Architectural and engineering services 1,431 1,443 -12 

Computer systems design and related services 1,427 1,387 40 

Management and technical consulting services 989 989 0 

Management of companies and enterprises 1,896 1,830 66 

Administrative and waste services 7,955 8,075 -120 

Administrative and support services 7,604 7,717 -113 

Employment services 3,176 3,352 -176 

Temporary help services 2,372 2,397 -25 

Business support services 837 799 38 

Services to buildings and dwellings 1,721 1,727 -6 

Waste management and remediation services 352 358 -6 

Education and health services 18,833 18,850 -17 

Educational services 3,153 3,178 -25 

Health care and social assistance 15,679 15,672 7 

Ambulatory health care services 5,588 5,600 -12 

Offices of physicians 2,238 2,246 -8 

Outpatient care centers 528 512 16 

Home health care services 942 940 2 

Hospitals 4,588 4,595 -7 

Nursing and residential care facilities 2,994 2,974 20 

Nursing care facilities 1,611 1,605 6 

Social assistance 2,511 2,504 7 

Child day care services 879 875 4 

Leisure and hospitality 13,156 13,307 -151 

Arts, entertainment, and recreation 1,837 1,864 -27 

Performing arts and spectator sports 385 409 -24 

Museums, historical sites, zoos, and parks 124 124 0 

Amusements, gambling, and recreation 1,328 1,332 -4 

Accommodation and food services 11,319 11,443 -124 

Accommodation 1,825 1,791 34 
Table 2. Nonfarm employment benchmarks by industry, March 2008 (levels in thousands)

Industry Benchmark Estimate Am

Food services and drinking places 9,494 9,652 -158 

Other services 5,518 5,509 9 

Repair and maintenance 1,243 1,254 -11 

Personal and laundry services 1,317 1,303 14 

Membership associations and organizations 2,958 2,951 7 

Government 22,840 22,792 48 

Federal 2,732 2,710 22 

Federal, except Postal Service 1,977 1,976 1 

U.S. Postal Service 756 734 22 

State government 5,293 5,303 -10 

State government education 2,483 2,486 -3 

State government excl. education 2,810 2,817 -7 

Local government 14,815 14,779 36 

Local government education 8,441 8,408 33 

Local government excl. education 6,374 6,371 3 

(1)Less than 0.05 percent. Table 3. Differences in seasonally adjusted levels and over-the-month changes, total nonfarm employment

December 2008 (in thousands)

Levels Over-the-month ch

2008: As previously published As revised Difference As previously published As re

January 138,002 138,080 78 -76 -72 

February 137,919 137,936 17 -83 -144 

March 137,831 137,814 -17 -88 -122 

April 137,764 137,654 -110 -67 -160 

May 137,717 137,517 -200 -47 -137 

June 137,617 137,356 -261 -100 -161 

July 137,550 137,228 -322 -67 -128 

August 137,423 137,053 -370 -127 -175 
Table 3. Differences in seasonally adjusted levels and over-the-month changes, total nonfarm employment

December 2008 (in thousands)

 Levels Over-the-month ch

September 137,020 136,732 -288 -403 -321 

October 136,597 136,352 -245 -423 -380 

November 136,013 135,755 -228 -584 -597 

December (p) 135,489 135,178 -370 -524 -577 

(p): Preliminary Table 4. Hours and earnings estimates for selected industries, March 2008 

Industry Average Weekly Hours Average Hourly Earnings 

Total private 33.8 $17.97 

Goods-producing 40.4 19.06 

Mining and Logging 45.7 22.29 

Construction 38.5 21.44 

Manufacturing 41.1 17.62 

Durable goods 41.4 18.56 

Wood products 38.3 13.92 

Nonmetallic mineral products 42.6 16.79 

Primary metals 43.0 20.23 

Fabricated metal products 41.7 16.86 

Machinery 42.8 17.87 

Computer and electronic products 41.0 20.76 

Electrical equipment and appliances 41.2 15.64 

Transportation equipment 42.5 23.52 

Furniture and related products 38.5 14.42 

Miscellaneous manufacturing 39.4 15.08 

Nondurable goods 40.5 16.01 

Food manufacturing 40.3 13.85 

Beverages and tobacco products 39.9 19.73 

Textile mills 38.8 13.45 

Textile product mills 39.4 11.77 
Table 4. Hours and earnings estimates for selected industries, March 2008 

Industry Average Weekly Hours Average Hourly Earnings 

Apparel 36.9 11.35 

Leather and allied products 39.0 12.81 

Paper and paper products 43.3 18.70 

Printing and related support activities 38.7 16.64 

Petroleum and coal products 42.8 27.06 

Chemicals 41.9 19.31 

Plastics and rubber products 41.1 15.72 

Private service-providing 32.5 17.70 

Trade, transportation, and utilities 33.3 16.14 

Wholesale trade 38.6 20.08 

Retail trade 30.0 12.88 

Transportation and warehousing 36.7 18.20 

Utilities 43.0 28.90 

Information 36.7 24.62 

Financial activities 36.2 20.17 

Professional and business services 35.1 21.00 

Education and health services 32.7 18.74 

Leisure and hospitality 25.3 10.77 

Other services 30.9 16.11 

Last Modified Date: February 6, 2009