1 

March 2005 Benchmarks for the Nonfarm Payroll Survey Kirk MuellerSupervisory Statistician 

With the release of data for January 2006, the Bureau of Labor Statistics (BLS) introduced its annual revi

estimates of employment, hours, and earnings from the Current Employment Statistics (CES) monthly survey of establishments. Each year, the CES survey realigns its sample-based estimates to reflect more currently availabl

employment—a process known as benchmarking. Comprehensive counts of employment, or benchmarks, are de

the unemployment insurance (UI) tax reports that nearly all employers are required to file with State EmploymenSummary of the benchmark revisions 

The March 2005 benchmark level for total nonfarm employment is 132,038,000; this figure is 158,000 be

estimate for March 2005, 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 2005, not seasonally adjusted, by industr

supersector dominated in terms of the size of revision. The largest downward revision occurred in other services 69,000, or -1.3 percent. The revision can primarily be attributed to membership associations and organizations wrevision of 69,200, or 2.4 percent. 
2 

Other supersectors had downward revisions of approximately the same magnitude. Estimates in financia

revised -68,000, or -0.8 percent, while estimates were revised downward by 64,000 in information and also in pr

business services, or 2.1 percent and 0.4 percent respectively. Within financial activities, credit intermediation revised -49,000, or -1.7 percent. Telecommunications revised in information by -25,200, or -2.5 percent, while awaste services revised -122,100, or -1.6 percent, in professional and business services. 

Manufacturing had a smaller revision of -47,000, or -0.3 percent, with non-durable goods accounting for 

downward revision of 50,000, or 0.9 percent. Minor downward revisions were present in education and health sethan 0.05 percent) and mining (-2,000, or -0.3 percent) 

Trade, transportation, and utilities revised upward by 74,000, or 0.3 percent. Retail trade dominated with 

or 0.5% percent, while an upward revision in wholesale trade of 25,000, or 0.4%, was offset by downward revisi(20,600, or 3.7 percent) and transportation and warehousing (4,800, or 0.1 percent). 

Construction estimate were raised by 35,000, or 0.5 percent, and government revised upward by 8,000, or 

percent. Changes to Direct life insurance carriers series Direct life insurance carriers population levels have historically included presumed non-covered employment tha

approximately 100,000, or between 20 and 25 percent, of the employment in the series. With the most recently a
3 

Business Pattern data, the industry refiling of the Economic Census Bureau led to a large shift of in employment 

insurance carriers (NAICS 524113) and direct health and medical insurance carriers (NAICS 524114). As a resu

presumed non-covered employment previously in direct life insurance is now associated with direct health and mcarriers, leading to large benchmark revisions for these two industries ( -93,000 and 95,600 respectively). Changes to the CES published series list 

Changes result from an annual review of sample employment and universe coverage for all estimation ce

employee series will no longer be published as a result of being collapsed into other cells, while other all employdiscontinued. Exhibit 3 shows the cells that will be collapsed and renamed. Exhibit 4 shows the discontinued seExhibit 3. Cells renamed/collapsed as of the 2004 benchmark release 

Tabcode Title Collapsed with New title New collapsed cell tabcode31-334411 Electron tubes 31-334414 and 

31-334419 

Misc. electronic components 

31-334419 

31-334414 Electronic capacitors 31-334411 and 

31-334419 

Misc. electronic components 

31-334419 

31-334419 Misc. electronic 

components 

31-334414 and 31-334411 

Misc. electronic components 

31-334419 

31-336213 Motor homes 31-336214 Motor homes, travel trailers, 

and campers 

31-336214 

31-336214 Travel trailers and 

campers 

31-336213 Motor homes, travel trailers, 

and campers 

31-336214 

32-311421 Fruit and vegetable 

canning 

32-311422 Fruit, vegetable, and 

specialty canning 

32-311422 
4 

32-311422 Specialty canning 32-311421 Fruit, vegetable, and 

specialty canning 

32-311422 

Exhibit 4. Discontinued series Industry title NAICS code CES industry code Next highest published level All other motor vehicle parts 

336399 31336399 Other motor vehicle parts 

(NAICS 33639) 

Sheer hosiery mills 315111 32315111 Hosiery and sock mills (NAICS 

31511) 

Other hosery and sock mills 

315119 32315119 Hosiery and sock mills (NAICS 

31511) 

Review of the sample receipts has also led to the discontinuation of production worker, hours, and earnin

small industries that no longer have sufficient sample. Exhibits 5 and 6 shows the series that will be discontinue

 Exhibit 5. Discontinued production worker, hours, and earnings series 

Industry title NAICS code CES industry code 

Prefabricated metal buildings and components 

332311 31-332311 

Exhibit 6. Discontinued average overtime series 

Industry title NAICS code CES industry code 

Small arms, ammunition, and other ordnance and assessories 

332992,3, 4, 5 31-332995 
5 

Photographic and photocopying equipment 

333315 31-333315 

Motor vehicle steering and suspension parts 

33633 31-336330 

Accessories and other apparel 3159 32-315900 Miscellaneous coated and treated paper and paper bags 

322223, 4, 5, 6 32-322226 

Agricultural chemicals 3253 32-325300 

Revisions in the post-benchmark period 

Post-benchmark period estimates from April 2005 to October 2005 were calculated for each month based 

levels, new model-based estimates for the net of birth/death employment, and a slightly new sample composition annual sample update (beginning with November.) 

Text table A shows the net birth/death model figures for the supersectors over the post-benchmark period

December 2005, the cumulative net birth/death model added 817,000, compared with 866,000 in the previously pDecember estimates. Revisions to production worker data for Wired Telecommunications (NAICS 51711) During the benchmark review process, an error was found in the production worker series that affected the Decemand as a result the production worker level from that point forward. The production worker series has been correfrom December 2004 forward. 
6 

Revisions to historical average weekly earnings annual averages In reviewing the benchmark data, small differences in the annual average calculation for average weekly earning1990 to 2001 for four series that changed their composition with the 2003 Benchmark. The differences were attr

conventions associated with the data. The annual averages have been corrected to be consistent with annual averaverage weekly earnings for all other series. The four series are other pressed and blown glass and glassware (BL31327212), other computer peripheral equipment (BLS tabulating code 31334119), other major household applia

code 31335228), and miscellaneous commercial printing (BLS tabulating code 32323119). Why benchmarks differ from estimatesA 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. 
7 

Like all sample surveys, the establishment survey is susceptible to two sources of error: sampling error a

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

coverage, response, and processing errors. The error structures for both the CES monthly survey and the UI univ

Still, the two programs generally produce consistent total employment figures, each validating the other. Over thbenchmark revisions at the total nonfarm level have averaged 0.2 percent, with an absolute range from less than percent. Benchmark revisions effects for other datatypes 

The routine benchmarking process results in revisions to the series for production and nonsupervisory wo

benchmark employment levels for these series; they are revised by preserving ratios of employment for the partic

employees 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. 
8 

Average weekly hours and average hourly earnings are not benchmarked; they are estimated solely from 

survey respondents at the basic estimating cell level. 

The aggregate industry levels of the hours and earnings series are derived as a weighted average. The pro

nonsupervisory worker employment estimates for the basic cells are used as weights for the hours and earnings eindustry groupings. Adjustments of the all-employee estimates to new benchmarks may alter the weights, whichthe 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 grou

the hours and earnings estimates of a broader group, employment revisions have to be relatively large and must ahave hours or earnings averages that are substantially different from those of other industries in their group. Tab

on the levels of specific hours and earnings series resulting from the March 2005 benchmark. At the total private 0.1 of an hour decrease in average weekly hours from the previously published level, while average hourly earninfrom the previously published level. Methods Benchmark adjustment procedure. Establishment survey benchmarking is done on an annual basis to a populatio

from 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 ab
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benchmark adjustment procedure replaces the March sample-based employment estimates with UI-based populaThe benchmark therefore determines the final employment levels, while sample movements capture month-to-m

Benchmarks are established for each basic estimating cell and are aggregated to develop published levels

adjusted 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 pr

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 employe
10 

laws. 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 B

used to augment UI data for nonoffice insurance sales workers, child daycare workers, religious organizations, anhospitals. Benchmarks for State and local government hospitals and educational institutions are based on the AnGovernments conducted by the Census Bureau. Benchmark data from these sources are available only on a laggExtrapolation to a current level is accomplished by applying the employment trends from the UI-covered part of these industries to the noncovered part. Universe data for interstate railroads are obtained from the Railroad RetiBusiness birth and death estimation. Regular updating of the CES sample frame with information from the UI unkeep the CES survey current with respect to employment from business births and business deaths. The timeliest available, however, always will be a minimum of 9 months out of date. The CES survey thus can not rely on regumaintenance alone to provide estimates for business birth and death employment contributions. BLS has researchbased 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. 
11 

Earlier research indicated that while both the business birth and death portions of total employment are ge

the net contribution is relatively small and stable. To account for this net birth/death portion of total employmentestimation 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 serie

estimate 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 ARIMA model component is reviewed on a quarterly basis. The net birth/death model co

unique to each month and include negative adjustments in some months. Furthermore, these figures may exhibit observed in the historical UI universe data series. 

The most significant potential drawback to this or any model-based approach is that time series modeling 

predictable continuation of historical patterns and relationships and therefore is likely to have some difficulty pro

estimates at economic turning points, or during periods when there are sudden changes in trend. BLS will continu

alternative model-based techniques for the net birth/death component; it is likely to remain the most problematic process. 
12 

Availability of revised dataLABSTAT, 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://wwCurrent Employment Statistics homepage. Employment, hours, and earnings estimates are also published monthEarnings.Seasonal adjustment procedure BLS uses X-12 ARIMA software developed by the U.S. Census Bureau to seasonally adjust national employmen

series 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, indivlevels are seasonally adjusted, and higher level aggregates are formed by summing these components. Seasonallhours and earnings are obtained by taking weighted averages of the seasonally adjusted data for the component sSpecial 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 sa consistent concept – the pay period including the 12th of each month – inconsistencies arise because there are s

sometimes 5 weeks between the week including the 12th in a given pair of months. In highly seasonal industries, 
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be 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 

expected seasonal change in employment for each month of the current year. Prior to the implementation of the procedure did not distinguish between 4- and 5-week survey intervals, and the accuracy of the seasonal expectatimeasure on how well the current year’s survey interval corresponded with those of the previous 3 years. All els

greatest potential for distortion occurred when the current month being estimated had a 5-week interval but the 3 were all 4-week intervals, or conversely when the current month had a 4-week interval but the 3 years preceding 

intervals. 

BLS adopted REGARIMA (regression with auto-correlated errors) modeling to identify the estimated siz

the calendar effect for each published series. REGARIMA combines standard regression analysis, which measurtwo or more variables, with ARIMA modeling, which describes and predicts the behavior of data series based on For many economic time series, including nonfarm payroll employment, observations are auto-correlated over timmonth’s value is significantly dependent on the observations that precede it. These series, therefore, usually can using ARIMA models. If auto-correlated time series are modeled through regression analysis alone, the measureamong other variables of interest may be distorted due to the influence of the auto-correlation. Thus, the REGAR
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appropriate for measuring relationships among variables of interest in series that exhibit autocorrelation, such as employment. 

In this application, the correlations of interest are those between employment levels in individual calenda

lengths of the survey intervals for those months. The REGARIMA models evaluate the variation in employment 11 separate survey interval variables, one specified for each month, except March. March is excluded because th4 weeks between the February and March surveys. Models for individual basic series are fit with the most recenavailable, the standard time span used for CES seasonal adjustment. 

The REGARIMA procedure yields regression coefficients for each of the 11 months specified in the mod

provide estimates of the strength of the relationship between employment levels and the number of weeks betweemodeled 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 o

employment levels associated with the length of the survey interval, these coefficients are used to adjust the CES calendar 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 X-12 soft

interval effect adjustment. There are several additional special effects modeled through the REGARIMA procesbelow. 
15 

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 d

construction series into its finer industry and geographic estimating cells and tightening outlier designation param

a more precise identification of weather-related outliers that had masked the interval effect and clouded the seaso

patterns 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 implementhe seasonal adjustment process for the hours and earnings series to correct for distortions related to the method o
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varying 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 

from sample respondents with semi-monthly or monthly pay periods to a weekly equivalent. The response error respondents 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 liemployees are salaried rather than paid by the hour, as employers are less likely to keep actual detailed hours recemployees. 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 ac

of the month), which dictates that different conversion factors be applied to payroll and hours. The CES process

hours conversion factor for both fields, resulting in peaks in the AHE series in short months and reversals in long 

REGARIMA modeling is used to identify, measure, and remove the length-of-pay-period effect for seaso

average weekly hours and average hourly earnings series. The length-of-pay-period variable proves significant f

movements in all the service-providing industries except retail trade. For AHE, the length-of-pay-period variablwholesale trade, financial activities, professional and business services, and other services. All AWH series in th
17 

industries except retail trade have been adjusted from January 1990 forward. The AHE series for wholesale trad

professional and business services, and other services have been adjusted from January 1990 forward as well. Focalculations of over-the-year change in the establishment hours and earnings series should use seasonally adjuste

The series to which the length-of-pay-period adjustment is applied are not subject to the 4- versus 5-week 

modeling cannot support the number of variables that would be required in the regression equation to make both Exhibit 7 for 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 

10113310 Logging MULT X 10211000 Oil and gas extraction MULT X 10212000 Mining, except oil and gas - X Indirect1 10212100 Coal mining MULT X 10213000 Support activities for mining ADD X 20236100 Residential building - X Indirect 20236200 Nonresidential building - X Indirect 20237000 Heavy and civil engineering ADD X 
18 

construction 

20238000 Specialty trade contractors - X Indirect 20238001 Residential specialty trade contractors MULT X Raked220238002 

Nonresidential 

specialty trade 

contractors 

MULT X Raked 

31321000 Wood products ADD X 31327000 Nonmetallic mineral products ADD X 31331000 Primary metals MULT X 31332000 Fabricated metal products ADD X 31333000 Machinery MULT X 31334000 Computer and electronic products - X Indirect 31334100 Computer and peripheral equipment MULT X 31334200 Communications equipment ADD X 31334400 

Semiconductors and 

electronic 

components 

MULT X 

31334500 Electronic instruments ADD X 31335000 Electrical equipment and appliances MULT X 31336000 Transportation equipment MULT 31336001 Motor vehicles and parts MULT 31337000 Furniture and related MULT X 
19 

products 

31339000 Miscellaneous manufacturing MULT X 32311000 Food manufacturing MULT X 32312000 Beverages and tobacco products ADD X 32313000 Textile mills MULT X 32314000 Textile product mills ADD X 32315000 Apparel MULT X 32316000 Leather and allied products MULT X 32322000 Paper and paper products ADD X 32323000 Printing and related support activities MULT X 32324000 Petroleum and coal products MULT X 32325000 Chemicals MULT X 32326000 Plastics and rubber products MULT X 41423000 Durable goods MULT X 41424000 Nondurable goods MULT X 41425000 

Electronic markets 

and agents and 

brokers 

MULT X 

42441000 Motor vehicle and parts dealers - X Indirect 42441100 Automobile dealers MULT X 42442000 Furniture and home furnishings stores MULT X 42443000 Electronics and appliance stores MULT X 42444000 Building material MULT X 
20 

and garden supply 

stores 

42445000 Food and beverage stores MULT X 42446000 Health and personal care stores MULT X 42447000 Gasoline stations MULT X 42448000 

Clothing and 

clothing accessories 

stores 

MULT X 

42451000 

Sporting goods, 

hobby, book, and 

music stores 

MULT X 

42452000 General merchandise stores - X Indirect 42452100 Department stores MULT X 42453000 Miscellaneous store retailers ADD X 42454000 Nonstore retailers MULT X 43481000 Air transportation MULT X 43482000 Rail transportation MULT X 43483000 Water transportation MULT X 43484000 Truck transportation ADD X 43485000 

Transit and ground 

passenger 

transportation 

ADD 

43486000 Pipeline transportation MULT X 43487000 

Scenic and 

sightseeing 

transportation 

MULT X 

43488000 Support activities for transportation MULT X 
21 

43492000 Couriers and 

messengers 

ADD X 

43493000 Warehousing and storage MULT X 

44221000 Utilities MULT X 50511000 

Publishing 

industries, except 

Internet 

MULT X 

50512000 

Motion picture and 

sound recording 

industries 

MULT X 

50515000 Broadcasting, except Internet MULT X 50516000 Internet publishing and broadcasting MULT X 50517000 Telecommunications MULT X 50518000 ISPs, search portals, and data processing MULT X 50519000 Other information services MULT X 55521000 Monetary authorities - central bank MULT X 55522000 Credit intermediation and related activities - X Indirect 55522100 Depository credit intermediation MULT X 55522110 Commercial banking MULT X 55523000 

Securities, 

commodity 

contracts, 

investments 

MULT X 

55524000 Insurance carriers and related activities MULT X 
22 

55525000 

Funds, trusts, and 

other financial 

vehicles 

MULT X 

55531000 Real estate ADD X 55532000 Rental and leasing services MULT X 55533000 

Lessors of 

nonfinancial 

intangible assets 

MULT X 

60541000 Professional and technical services - X Indirect 60541100 Legal services MULT X 60541200 

Accounting and 

bookkeeping 

services 

ADD X 

60541300 Architectural and engineering services MULT X 60541500 

Computer systems 

design and related 

services 

MULT X 

60541600 

Management and 

technical consulting 

services 

ADD X 

60551000 

Management of 

companies and 

enterprises 

MULT X 

60561000 Administrative and support services - X Indirect 60561300 Employment services MULT X 60561320 Temporary help services MULT X 60561400 Business support ADD X 
23 

services 

60561700 Services to buildings and dwellings MULT X 60562000 

Waste management 

and remediation 

services 

MULT X 

65611000 Educational services MULT X 65621000 Ambulatory health care services - X Indirect 65621100 Offices of physicians ADD X 65621400 Outpatient care centers MULT X 65621600 Home health care services MULT X 65622000 Hospitals MULT X 65623000 

Nursing and 

residential care 

facilities 

- X Indirect 

65623100 Nursing care facilities ADD X 65624000 Social assistance - X Indirect 65624400 Child day care services ADD X 70711000 Performing arts and spectator sports MULT X 70712000 Museums, historical sites, zoos, and parks MULT X 70713000 

Amusements, 

gambling, and 

recreation 

MULT X 

70721000 Accommodations MULT X 70722000 Food services and drinking places ADD X 
24 

80811000 Repair and maintenance ADD X 80812000 Personal and laundry services MULT X 80813000 

Membership 

associations and 

organizations 

ADD 

90911000 Federal, except U.S. Postal Service MULT X 90919120 U.S. Postal Service MULT X 90921611 State government education ADD X 90922000 State government, excluding education MULT X 90931611 Local government education ADD X 90932000 Local government, excluding education ADD X Election adjustment3 
25 

Seasonal Adjustment - WW 

NAICS 

Tabcode Mode 

4/5 

week 

adj 

Other adj 

10000000 Natural resources and mining MULT X 10210000 Mining MULT X 20000000 Construction MULT X 31000000 Durable goods MULT X 32000000 Nondurable goods MULT X 41420000 Wholesale trade MULT X 42000000 Retail trade MULT X 43000000 Transportation and warehousing ADD X 44220000 Utilities MULT X 50000000 Information MULT X 55520000 Finance and insurance MULT X 55530000 Real estate and rental and leasing ADD X 60540000 Professional and technical services MULT X 60550000 

Management of 

companies and 

enterprises 

ADD X 

60560000 Administrative and waste services ADD X 65610000 Educational services MULT X 65620000 Health care and social assistance MULT X 70710000 Arts, entertainment, MULT X 
26 

and recreation 

70720000 Accommodations and food services MULT X 

80000000 Other services MULT X 90910000 Federal MULT X 90920000 State government MULT X 90930000 Local government MULT X Election adjustment 
27 

Seasonal Adjustment - PW 

NAICS 

Tabcode Mode 

4/5 

week 

adj 

Other adj 

10000000 Natural resources and mining ADD X 20000000 Construction ADD X 31321000 Wood products ADD X 31327000 Nonmetallic mineral products ADD X 31331000 Primary metals MULT X 31332000 Fabricated metal products MULT X 31333000 Machinery MULT X 31334000 Computer and electronic products MULT X 31335000 Electrical equipment and appliances MULT X 31336000 Transportation equipment MULT 31336001 Motor vehicles and parts MULT 31337000 Furniture and related products MULT X 31339000 Miscellaneous manufacturing MULT X 32311000 Food manufacturing MULT X 32312000 Beverages and tobacco products ADD X 32313000 Textile mills MULT X 32314000 Textile product mills ADD X 
28 

32315000 Apparel MULT X 32316000 Leather and allied products MULT X 32322000 Paper and paper products ADD X 32323000 Printing and related support activities MULT X 32324000 Petroleum and coal products MULT X 32325000 Chemicals ADD X 32326000 Plastics and rubber products MULT X 41420000 Wholesale trade MULT X 42000000 Retail trade MULT X 43000000 Transportation and warehousing MULT X 44220000 Utilities MULT X 50000000 Information MULT X 55000000 Financial activities ADD X 60000000 Professional and business services MULT X 65000000 Education and health services MULT X 65620001 Health care MULT X 70000000 Leisure and hospitality MULT X 80000000 Other services ADD X 
29 

Seasonal Adjustment - AWH 

NAICS 

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

Labo

Day a

10000000 Natural resources and mining MULT X X 20000000 Construction ADD X X 31321000 Wood products MULT X X 31327000 Nonmetallic mineral products MULT X X 31331000 Primary metals MULT X X 31332000 Fabricated metal products MULT X X 31333000 Machinery MULT X X 31334000 Computer and electronic products MULT X X 31335000 Electrical equipment and appliances MULT X X 31336000 Transportation equipment MULT X X 31336001 Motor vehicles and parts MULT X X 31337000 Furniture and related products MULT X X 31339000 Miscellaneous manufacturing MULT X X 32311000 Food manufacturing MULT X X 32312000 Beverages and tobacco products ADD X X 32313000 Textile mills MULT X X 32314000 Textile product mills MULT X X 
30 

32315000 Apparel MULT X X 32316000 Leather and allied products MULT X X 32322000 Paper and paper products MULT X X 32323000 Printing and related support activities MULT X X 32324000 Petroleum and coal products MULT X X 32325000 Chemicals MULT X 32326000 Plastics and rubber products MULT X X 41420000 Wholesale trade MULT X X 42000000 Retail trade MULT X 43000000 Transportation and warehousing MULT X X 44220000 Utilities MULT X 50000000 Information MULT X 55000000 Financial activities MULT X 60000000 Professional and business services MULT X X 65000000 Education and health services MULT X 65620001 Health care MULT X 70000000 Leisure and hospitality MULT X 80000000 Other services MULT X X 
31 

Seasonal Adjustment - AHE 

NAICS 

Tabcode Mode 

4/5 

week 

adj 

10/11 

day adj 

10000000 Natural resources and mining ADD X 20000000 Construction ADD X 31000000 Durable goods ADD X 32000000 Nondurable goods MULT X 41420000 Wholesale trade ADD X 42000000 Retail trade ADD X 43000000 Transportation and warehousing MULT X 44220000 Utilities MULT X 50000000 Information MULT X 55000000 Financial activities MULT X 60000000 Professional and business services MULT X 65000000 Education and health services MULT X 70000000 Leisure and hospitality ADD X 80000000 Other services MULT X 
32 

Seasonal Adjustment Comparison - AOT 

NAICS 

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

Labor 

ad

31000000 Durable goods MULT X X 32000000 Nondurable goods ADD 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 cons3 Special adjustment for the presence/absence of poll workers in local government Table 1. Percent differences between nonfarm employment benchmarks and estimates by indust1996-2005 1

Industry 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

Total (2) 0.4 (2) 0.2 0.4 -0.1 -0.2 -0.1 0.2 -0.1 Total Private 0.1 0.5 0.1 0.2 0.3 -0.2 -0.4 -0.2 0.2 -0.2 Government -0.1 -0.4 -0.2 0.1 0.6 0.3 1.0 0.3 0.1 (2) (1) Differences are based on comparisons of final published March estimates and benchmark levels, as orig(2) Less than 0.05 percent. 
33 

Table 2. Nonfarm employment benchmarks by industry, March 2005(Numbers in thousands) 

Difference

Industry Benchmark Estimate

Amount Percent

Total nonfarm 132,038 132,196 -158 -0.1 Total private 109,892 110,058 -166 -0.2 Goods-producing 21,640 21,654 -14 -0.1 Service-providing 110,398 110,542 -144 -0.1Private service-providing 88,252 88,404 -152 -0.2 Natural resources and mining 602 604 -2 -0.3 Logging 64 65 -1 -1.6 Mining 539 540 -1 -0.2 Oil and gas extraction 124 123 1 0.8 Mining, except oil and gas 203 209 -6 -3.0 Coal mining 72 76 -4 -5.6Support activities for mining 213 208 5 2.3 
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Construction 6,838 6,803 35 0.5 

Construction of buildings 1,628 1,635 -7 -0.4 Heavy and civil engineering construction 842 827 15 1.8 Specialty trade contractors 4,369 4,341 28 0.6 Manufacturing 14,200 14,247 -47 -0.3 Durable goods 8,930 8,927 3 (1) Wood products 551 547 4 0.7 Nonmetallic mineral products 491 489 2 0.4 Primary metals 469 466 3 0.6 Fabricated metal products 1,511 1,513 -2 0.4 Machinery 1,157 1,153 4 0.3 Computer and electronic products 1,312 1,323 -11 -0.8 Computer and peripheral equipment 205 211 -6 -2.9 Communications equipment 147 153 -6 -4.1 Semiconductors and electronic components 450 446 4 0.9 Electronic instruments 434 435 -1 -0.2 Electrical equipment and appliances 438 444 -6 -1.4 Transportation equipment 1,785 1,778 7 0.4 Furniture and related products 568 566 2 0.4 Miscellaneous manufacturing 649 649 0 0 Nondurable goods 5,270 5,320 -50 -0.9 Food manufacturing 1,458 1,470 -12 -0.8 
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Beverages and tobacco products 187 186 1 0.5 

Textile mills 224 229 -5 -2.2 Textile product mills 172 178 -6 -3.5 Apparel 265 263 2 0.8 Leather and allied products 40 43 -3 -7.5 Paper and paper products 488 500 -12 -2.5 Printing and related support activities 648 655 -7 -1.1 Petroleum and coal products 109 113 -4 -3.7 Chemicals 877 878 -1 -0.1 Plastics and rubber products 802 805 -3 -0.4 Trade, transportation, and utilities 25,501 25,427 74 0.3 Wholesale trade 5,699 5,674 25 0.4 Electronic markets and agents and brokers 724 713 11 1.5 Retail trade 14,951 14,877 74 0.5 Motor vehicle and parts dealers 1,904 1,901 3 0.2 Automobile dealers 1,258 1,248 10 0.8 Furniture and home furnishings stores 567 557 10 1.8 Electronics and appliance stores 522 517 5 1.0 Building material and garden supply stores 1,243 1,240 3 0.2 Food and beverage stores 2,779 2,794 -15 -0.5 Health and personal care stores 941 943 -2 -0.2 Gasoline stations 860 865 -5 -0.6 
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Clothing and clothing accessories stores 1,354 1,346 8 0.6 

Sporting goods, hobby, book, and music stores 628 621 7 1.1General merchandise stores 2,847 2,784 63 2.2 Department stores 1,546 1,569 -23 -1.5 Miscellaneous store retailers 881 897 -16 -1.8 Nonstore retailers 425 412 13 3.1 Transportation and warehousing 4,298 4,303 -5 -0.1 Air transportation 504 505 -1 -0.2 Rail transportation 227 222 5 2.2 Water transportation 57 59 -2 -3.5Truck transportation 1,360 1,356 4 0.3 Transit and ground passenger transportation 402 404 -2 -0.5 Pipeline transportation 38 39 -1 -2.6 Scenic and sightseeing transportation 22 21 1 4.5 Support activities for transportation 548 550 -2 -0.4 Couriers and messengers 564 576 -12 -2.1 Warehousing and storage 577 570 7 1.2 Utilities 554 574 -20 -3.6 Information 3,056 3,120 -64 -2.1 Publishing industries, except Internet 904 906 -2 -0.2 Motion picture and sound recording industries 364 377 -13 -3.6 Broadcasting, except Internet 325 331 -6 -1.8 Internet publishing and broadcasting 30 35 -5 -16.7 
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Telecommunications 1,003 1,028 -25 -2.5 

ISPs, search portals, and data processing 379 394 -15 -4.0 Other information services 51 51 0 0 Financial activities 8,063 8,131 -68 -0.8Finance and insurance 5,980 6,034 -54 -0.9 Monetary authorities--central bank 21 20 1 4.8 Credit intermediation and related activities 2,844 2,893 -49 -1.7 Depository credit intermediation 1,761 1,792 -31 -1.8 Commercial banking 1,292 1,306 -14 -1.1 Securities, commodity contracts, investments 783 785 -2 -0.3 Insurance carriers and related activities 2,244 2,250 -6 -0.3 Funds, trusts, and other financial vehicles 88 85 3 3.4 Real estate and rental and leasing 2,083 2,097 -14 -0.7 Real estate 1,419 1,426 -7 -0.5 Rental and leasing services 638 647 -9 -1.4 Lessors of nonfinancial intangible assets 26 24 2 7.7 Professional and business services 16,540 16,604 -64 -0.4 Professional and technical services 7,024 6,986 38 0.5 Legal services 1,157 1,153 4 0.3 Accounting and bookkeeping services 951 983 -32 -3.4 Architectural and engineering services 1,268 1,277 -9 -0.7 Computer systems design and related services 1,178 1,175 3 0.3 Management and technical consulting services 824 789 35 4.2 
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Management of companies and enterprises 1,739 1,718 21 1.2 

Administrative and waste services 7,778 7,900 122 -1.6 Administrative and support services 7,448 7,581 -133 -1.8 Employment services 3,376 3,510 -134 -4.0 Temporary help services 2,377 2,396 -19 -0.8 Business support services 767 757 10 1.3 Services to buildings and dwellings 1,600 1,601 -1 -0.1 Waste management and remediation services 330 319 11 3.3 Education and health services 17,355 17,360 -5 (1) Educational services 2,961 2,973 -12 -0.4 Health care and social assistance 14,395 14,387 8 0.1 Ambulatory health care services 5,049 5,030 19 0.4 Offices of physicians 2,070 2,089 -19 -0.9 Outpatient care centers 467 453 14 3.0 Home health care services 806 796 10 1.2 Hospitals 4,311 4,340 -29 -0.7 Nursing and residential care facilities 2,834 2,823 11 0.4 Nursing care facilities 1,573 1,569 4 0.3 Social assistance 2,201 2,194 7 0.3 Child day care services 791 799 -8 -1.0 Leisure and hospitality 12,365 12,321 44 0.4 Arts, entertainment, and recreation 1,707 1,655 52 3.0 Performing arts and spectator sports 350 342 8 2.3 Museums, historical sites, zoos, and parks 112 108 4 3.6 
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Amusements, gambling, and recreation 1,245 1,204 41 3.3 

Accommodations and food services 10,657 10,667 -10 -0.1 Accommodations 1,748 1,769 -21 -1.2 Food services and drinking places 8,909 8,898 11 0.1 Other services 5,372 5,441 -69 -1.3 Repair and maintenance 1,239 1,235 4 0.3 Personal and laundry services 1,270 1,274 -4 -0.3 Membership associations and organizations 2,863 2,933 -70 -2.4 Government 22,146 22,138 8 (1) Federal 2,716 2,709 7 0.3 Federal, except U.S. Postal Service 1,946 1,932 14 0.7 U.S. Postal Service 770 777 -7 -0.9 State government 5,157 5,168 -11 -0.2 State government education 2,397 2,433 -36 -1.5 State government, excluding education 2,760 2,736 24 0.9 Local government 14,273 14,261 12 0.1 Local government education 8,186 8,177 9 0.1 Local government, excluding education 6,088 6,084 4 0.1 (1) Less than 0.05 percent. 
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Table 3. Differences in seasonally adjusted levels and over-the-month changes, total nonfarm eJanuary 2005-October 2005(In thousands) 

Levels Over-the-month changes

As previously 

published As revised As previously published As revised Difference

2005: January 132,573 132,471 124 76 -48 February 132,873 132,736 300 265 -35 March 132,995 132,876 122 140 18 April 133,287 133,104 292 228 -64 May 133,413 133,210 126 106 -20 June 133,588 133,376 175 166 -9 July 133,865 133,617 277 241 -36 August 134,013 133,792 148 175 27 September 134,030 133,840 17 48 31 October 134,055 133,877 25 37 12 (p): Preliminary 
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Table 4. Hours and earnings estimates, selected industries, March 2005

Industry Average weekly hours Average hourly earnings

Total private 33.4 $15.95Goods-producing 39.6 17.37Natural resources and mining 44.9 18.33Construction 37.8 19.24Manufacturing 40.4 16.42Durable goods 40.8 17.16Wood products 39.2 13.13Nonmetallic mineral products 41.1 16.30Primary metals 43.0 18.76Fabricated metal products 40.6 15.63Machinery 42.2 17.03Computer and electronic products 39.5 17.96Electrical equipment and appliances 40.0 15.11
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Transportation equipment 42.2 21.83

Furniture and related products 39.4 13.36Miscellaneous manufacturing 39.0 14.03Nondurable goods 39.6 15.19Food manufacturing 38.2 13.01Beverages and tobacco products 39.9 18.99Textile mills 40.3 12.26Textile product mills 39.6 11.57Apparel 36.3 10.07Leather and allied products 37.6 11.48Paper and paper products 41.7 17.95Printing and related support activities 38.4 15.68Petroleum and coal products 44.6 24.80Chemicals 42.3 19.48Plastics and rubber products 39.8 14.71Private service-providing 32.1 15.58
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Trade, transportation, and utilities 33.2 14.86

Wholesale trade 37.5 17.88Retail trade 30.3 12.35Transportation and warehousing 36.8 16.59Utilities 40.1 26.31Information 36.2 21.64Financial activities 35.6 17.76Professional and business services 33.9 17.89Education and health services 32.4 16.50Leisure and hospitality 25.4 9.08Other services 30.7 14.18
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Text Table A. Net Birth/Death Estimates, Post-Benchmark 2005 

(In thousands) 2005: 

Natural 

Resources 

& Mining 

Construction Manufacturing 

Trade, 

Transportation, 

& Utilities 

Information Financial Activities Professional & Business Services Education & Health Services Leisur

Hospit

April -2 34 1 11 -5 -3 64 21 90 

May 1 38 8 24 4 2 19 14 75 

June 1 29 8 22 0 5 25 -1 81 

July 1 -11 -21 -22 -6 -9 -15 -11 32 

August 1 16 0 23 4 8 23 19 27 

September 1 11 6 20 -2 4 13 19 -25 

October 1 0 -4 14 9 24 35 20 -42 

November -1 -6 1 14 4 5 4 8 -9 

December 0 -5 2 19 1 13 10 5 15 

Cumulative Total 3 106 1 125 9 49 178 94 244