1 

March 2004 Benchmarks for the Nonfarm Payroll Survey 

Don Kim 

With the release of data for January 2005, the Bureau of Labor Statistics (BLS) 

introduced its annual revision of national estimates of employment, hours, and earnings from the 

Current Employment Statistics (CES) monthly survey of nonfarm establishments. Each year, the 

CES survey realigns its sample-based estimates to reflect more currently available universe 

counts of employment—a process known as benchmarking. Comprehensive counts of 

employment, or benchmarks, are derived primarily from the unemployment insurance (UI) tax 

reports that nearly all employers are required to file with State Employment Security Agencies. 

Summary of the benchmark revisions 

The March 2004 benchmark level for total nonfarm employment is 130,019,000; this 

figure is 203,000 above the NAICS sample-based estimate for March 2004, an adjustment of 0.2 

percent. Table 1 shows the total nonfarm percentage benchmark revisions for the past ten years. 

Table 2 shows the nonfarm employment benchmarks for March 2004, not seasonally 

adjusted, by industry. The majority of this year's benchmark revision is in leisure and 

hospitality. Estimates in leisure and hospitality were revised upward by 150,000, or 1.2 percent. 

Within leisure and hospitality, accommodations and food services contributed the greatest 

adjustment, with an upward revision of 113,000, or 1.1 percent. In addition, arts, entertainment, 

and recreation contributed an upward adjustment of 37,000, or 2.2 percent. 

 Benchmark revisions in other supersectors were smaller. Construction was revised 

upward by 39,000 or 0.6 percent. This was largely due to an upward revision of 64,000, or 1.5 

percent, in specialty trade contractors, and was partially offset by a downward revision of 

24,000, or 2.9 percent, in heavy and civil engineering construction. Trade, transportation, and 
2 

utilities were revised upward 38,000, or 0.2 percent. Most of the upward revision came from 

transportation and warehousing, which were revised upward 27,000, or 0.6 percent. Education 

and health services were revised upward 35,000, or 0.2 percent. The majority of the adjustment 

came from educational services, which contributed an upward revision of 21,000, or 0.7 percent. 

The other services supersector was revised upward 26,000, or 0.5 percent. Within other services, 

membership associations and organizations contributed 18,000, or 0.6 percent, while personal 

and laundry services contributed 17,000, or 1.3 percent. Government was revised upward 

23,000, or 0.1 percent. Within government, local government was revised upward by 56,000, or 

0.4 percent, and Federal government was revised upward by 15,000, or 0.6 percent. These 

upward adjustments were partially offset by State government, which contributed a downward 

adjustment of 48,000, or 0.9 percent. Only a minor upward revision of 8,000 occurred in 

financial activities. A downward revision of 21,000 in securities, commodity contracts, and 

investments was offset by an upward revision of 21,000 in credit intermediation and related 

activities. Natural resources and mining was revised upward by 4,000, or 0.7 percent. 

Manufacturing was revised downward by 52,000 or 0.4 percent. Both durable and 

nondurable goods were revised downward by 26,000, representing a 0.3 percent adjustment in 

durable goods and a 0.5 percent adjustment in nondurable goods. Professional and business 

services were revised downward 36,000, or 0.2 percent. An upward revision of 38,000 in 

management of companies and enterprises partially offset a downward revision of 92,000 in 

administrative and waste services. Information was revised downward 32,000, or 1.0 percent. 

Most of the downward revision in information came from ISPs, search portals, and data 

processing, which were revised downward 17,000, or 4.4 percent. 
3 

Addition of residential and nonresidential specialty trade contractors 

Concurrent with the release of the 2004 benchmark, the CES Program also began 

producing and publishing employment series for residential specialty trade contractors and 

nonresidential specialty trade contractors (see Exhibit 1 for publication detail). The two new 

employment series can be found in tables B-3 (employment, seasonally adjusted) and B-12 

(employment, not seasonally adjusted) in the Employment and Earnings publication. 

Exhibit 1. Component series to be published as of the 2004 benchmark release 

New component industries Aggregate industry 

Industry title 

CES industry 

code Industry title 

NAICS 

code CES industry code 

Residential specialty trade 

contractors 20-238001 

Nonresidential specialty trade 

contractors 20-238002 

Specialty trade 

contractors 238 20-238000 

Examination of the history available for the new series illustrates the differing trends 

between the residential and nonresidential specialty trade contractors industry (NAICS 238) 

series and indicates the analytical value associated with these new industries. 

As a whole, specialty trade contractors shows a slight decrease in employment (-2.9%) 

from March 2001 to March 2003, mirroring a general decline in employment in the Construction 

sector (-3.1%) during that time period. However, focusing on a decrease in employment at the 3-

digit NAICS level masks a small increase in employment in the residential sector of specialty 

trade contractors. This growth in employment in the residential sector was overshadowed by a 

decrease in employment in the nonresidential sector of specialty trade contractors, leading to an 
4 

overall decline in employment at the 3-digit NAICS level during this time period. Without the 

new breakout, these trends would not be observable. 

Estimates are made at the four-digit NAICS, regional, residential and nonresidential 

levels. As the residential series are subsets of previously published series, the estimates are 

made independently and raked, or controlled, to the traditional NAICS structure to ensure 

consistency between the series. Research indicated that the amount of raking needed to achieve 

this consistency was minimal. There are no estimates of hours and earnings for the new 

residential and nonresidential specialty trade contractor series. 

To complement the two new construction industry employment series, the CES program 

has begun including employment estimates for residential building (NAICS 2361) and 

nonresidential building (NAICS 2362) in the Employment and Earnings tables. Traditionally, 

not seasonally adjusted employment estimates for these industries were published with a 1-

month lag, and seasonally adjusted estimates were not available at all. 

Other changes to the CES published series list 

The 2004 benchmark brings a number of changes to the list of CES published series. 

There are two new aggregate series that will be published beginning with the 2004 benchmark 

release: motor vehicles and parts, and health care. Publishing the new series will facilitate the 

analysis of labor-market trends in these important industry groups. 

Exhibit 2. Aggregate series to be published as of the 2004 benchmark release 

New industry Component industries 

Industry title CES industry 

code 

Industry title NAICS 

code 

CES industry 

code 

Motor vehicles and Motor vehicles 3361 31-336100 

parts 

31-336001 

Motor vehicle bodies and trailers 3362 31-336200 
5 

Motor vehicle parts 3363 31-336300 

Ambulatory health 621 65-621000 

Hospitals 622 65-622000 

Health care 65-620001 

Nursing and residential care 

facilities 

623 65-623000 

 

Furthermore, changes result from a review of sample employment and universe coverage 

for all estimation cells. The only all employee series that will no longer be published are those 

that are being collapsed into other cells. Exhibit 3 shows the cells that will be collapsed and 

renamed. 

Exhibit 3. Cells renamed/collapsed as of the 2004 benchmark release 

Tabcode Title Collapsed with Title New collapsed cell tabcode

31-336419 Other guided missile 

and space vehicle 

parts 

31-336419 Guided missiles, space 

vehicles, and parts 

31-336419 

31-336414 Guided missiles and 

space vehicles 

31-336419 Guided missiles, space 

vehicles, and parts 

31-336419 

31-336415 Space vehicle 

propulsion units and 

parts 

31-336419 Guided missiles, space 

vehicles, and parts 

31-336419 

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

hours, and earnings estimates for some small industries that no longer have sufficient sample. 

Exhibits 4 and 5 shows the series that will be discontinued. 

 

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

Industry title NAICS code CES industry code 

Computer terminals and other 

computer peripheral equipment 

334113,9 31-334119 

Other direct selling 

establishments 

45439 42-454390 

Air transportation 481 43-481000 

Scheduled air transportation 4811 43-481100 
6 

Heavy machinery rental and 

leasing 

53241 55-532410 

Exhibit 5. Discontinued average overtime series 

Industry title NAICS code CES industry code 

Computer and peripheral 

equipment 

3341 31-334100 

Frozen specialty food 311412 32-311412 

Changes to the average hourly earnings series for scheduled air transportation 

In addition to the removal of scheduled air transportation, NAICS 4811, from publication, the 

average hourly earnings data has been revised to account for the low response rate in that 

industry. Estimates from March 2004 forward have been recalculated with a reweighting of the 

sample respondents to account for the response rate. The average weekly hours series is not 

affected due to the relatively consistent hours reports across the industry. These data are 

unpublished and available upon request. 

Revisions in the post-benchmark period 

Post-benchmark period estimates from April 2004 to October 2004 were calculated for 

each month based on new benchmark levels, new model-based estimates for the net of 

birth/death employment, and a slightly new sample composition resulting from the annual 

sample update (beginning with November.) 

Text table A shows the net birth/death model figures for the supersectors over the postbenchmark period. From April 2004 to December 2004, the cumulative net birth/death model 

added 827,000, compared with 889,000 in the previously published April to December estimates. 

Why benchmarks differ from estimates
7 

A benchmark revision is the difference between the benchmark employment level for a given 

March and its corresponding sample-based estimate. The overall accuracy of the establishment 

survey is usually gauged by the size of this difference. The benchmark revision often is regarded 

as a proxy for total survey error, but this does not take into account error in the universe data. 

The employment counts obtained from quarterly unemployment insurance tax forms are 

administrative data that reflect employer record-keeping practices and differing State laws and 

procedures. The benchmark revision can be more precisely interpreted as the difference between 

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 nonsampling error. Sampling error is present any time a sample is used to 

make inferences about a population. The magnitude of the sampling error, or variance, relates 

directly to sample size and the percentage of the universe covered by that sample. The CES 

monthly survey captures slightly under one-third of the universe, exceptionally high by usual 

sampling standards. This coverage insures a small sampling error at the total nonfarm 

employment level. 

Both the universe counts and the establishment survey estimates are subject to 

nonsampling errors common to all surveys—coverage, response, and processing errors. The 

error structures for both the CES monthly survey and the UI universe are complex. Still, the two 

programs generally produce consistent total employment figures, each validating the other. Over 

the last decade, annual benchmark revisions at the total nonfarm level have averaged 0.2 percent, 

with an absolute range from less than 0.05 percent to 0.5 percent. 

Benchmark revisions effects for other datatypes 
8 

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

nonsupervisory workers. There are no benchmark employment levels for these series; they are 

revised by preserving ratios of employment for the particular data type to all employees 

employment prior to benchmarking, and then applying these ratios to the revised all-employee 

figures. These figures are calculated 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 supplied by 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 production or nonsupervisory worker employment estimates for the basic cells are 

used as weights for the hours and earnings estimates for broader industry groupings. 

Adjustments of the all-employee estimates to new benchmarks may alter the weights, which, in 

turn, may change the 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. To influence the hours and earnings estimates of a broader group, 

employment revisions have to be relatively large and must affect industries that have hours or 

earnings averages that are substantially different from those of other industries in their group. 

Table 4 gives information on the levels of specific hours and earnings series resulting from the 

March 2004 benchmark. At the total private level, there was no change in average weekly hours 

from the previously published level, while average hourly earnings decreased by 1 cent from the 

previously published level. 
9 

Methods 

Benchmark adjustment procedure. Establishment survey benchmarking is done on an annual 

basis to a population derived primarily from the administrative file of employees covered by 

unemployment insurance (UI). The time required to complete the revision process—from the 

full collection of the UI population data to publication of the revised industry estimates—is about 

10 months. The benchmark adjustment procedure replaces the March sample-based employment 

estimates with UI-based population counts for March. The benchmark therefore determines the 

final employment levels, while sample movements capture month-to-month trends. 

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

published levels. On a not seasonally adjusted basis, the sample-based estimates for the year 

preceding and the year following the benchmark also are then subject to revision. Employment 

estimates for the months between the most recent March benchmark and the previous year's 

benchmark are adjusted using a "wedge back" procedure. In this process, the difference between 

the benchmark level and the previously published March estimate for each estimating cell is 

computed. This difference, or error, is linearly distributed across the 11 months of estimates 

subsequent to the previous benchmark; eleven-twelfths of the March difference is added to 

February estimates, ten-twelfths to January estimates, and so on, ending with the previous April 

estimates, which receive one-twelfth of the March difference. The wedge procedure assumes 

that the total estimation error accumulated at a steady rate since the last benchmark. Applying 

previously derived over-the-month sample changes to the revised March level yields revised 

estimates for the months following the March benchmark. New net birth/death model estimates 

also are calculated and applied during post-benchmark estimation, and new sample is introduced 

from the annual update. 
10 

Benchmark source material. The principal source of benchmark data for private industries is the 

Quarterly Census of Employment and Wages (QCEW). These employment data are provided to 

State Employment Security Agencies by employers covered by State UI laws. BLS uses several 

other sources to establish benchmarks for the remaining industries partially covered or exempt 

from mandatory 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 Patterns, are used to augment UI data for non-office insurance sales 

workers, child daycare workers, religious organizations, and private schools and hospitals. 

Benchmarks for State and local government hospitals and educational institutions are based on 

the Annual Census of Governments conducted by the Census Bureau. Benchmark data from 

these sources are available only on a lagged basis. Extrapolation to a current level is 

accomplished by assuming and applying the employment trends from the UI-covered part of the 

population in these industries to the non-covered part. Universe data for interstate railroads are 

obtained from the Railroad Retirement Board. 

Business birth and death estimation. Regular updating of the CES sample frame with 

information from the UI universe files helps to keep the CES survey current with respect to 

employment from business births and business deaths. The timeliest UI universe files available, 

however, always will be a minimum of 9 months out of date. The CES survey thus can not rely 

on regular frame maintenance alone to provide estimates for business birth and death 

employment contributions. BLS has researched both sample-based and model-based approaches 

to measuring birth units that have not yet appeared on the UI universe frame. Since the research 
11 

demonstrated that sampling for births was not feasible in the very short CES production 

timeframes, the Bureau is utilizing a model-based approach for this component. 

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

employment are generally significant, the net contribution is relatively small and stable. To 

account for this net birth/death portion of total employment, BLS is utilizing an estimation 

procedure with two components. The first component uses business deaths to impute 

employment for business births. This is incorporated into the sample-based link relative estimate 

procedure by simply not reflecting sample units going out of business, but imputing to them the 

same trend as the other firms in the sample. The second component is an ARIMA time series 

model designed to estimate the residual net birth/death employment not accounted for by the 

imputation. The historical time series used to create and test the ARIMA model was derived 

from the UI universe micro level database, and reflects the actual residual net of births and 

deaths over the past five years. The ARIMA model component is reviewed on a quarterly basis. 

The net birth/death model component figures are unique to each month and include negative 

adjustments in some months. Furthermore, these figures may exhibit a seasonal pattern 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 assumes a predictable continuation of historical patterns and relationships and 

therefore is likely to have some difficulty producing reliable estimates at economic turning 

points, or during periods when there are sudden changes in trend. BLS will continue researching 

alternative model-based techniques for the net birth/death component; it is likely to remain the 

most problematic part of the estimation process. 

Availability of revised data
12 

LABSTAT, the BLS public database on the Internet, contains all historical employment, hours, 

and earnings data revised as a result of this benchmark, including both unadjusted and seasonally 

adjusted data. The data can be accessed at https://www.bls.gov/ces/, the Current Employment 

Statistics homepage. Employment, hours, and earnings estimates are also published monthly in 

Employment and Earnings. 

Seasonal adjustment procedure 

BLS uses X-12 ARIMA software developed by the U.S. Census Bureau to seasonally adjust 

national employment, hours, and earnings series derived from the CES program. Individual 

series are seasonally adjusted using either a multiplicative or an additive model. For 

employment, seasonal adjustment factors are directly applied to the component levels. 

Individual 3-digit NAICS levels are seasonally adjusted, and higher level aggregates are formed 

by summing these components. Seasonally adjusted totals for hours and earnings are obtained 

by taking weighted averages of the seasonally adjusted data for the component series. 

Special model adjustments 

Variable survey intervals. Beginning with the release of the 1995 benchmark, BLS refined the 

seasonal adjustment procedures to control for survey interval variations, sometimes referred to as 

the 4- versus 5- week effect. Although the CES survey is referenced to a consistent concept – 

the pay period including the 12th of each month – inconsistencies arise because there are 

sometimes 4 and sometimes 5 weeks between the week including the 12th in a given pair of 

months. In highly seasonal industries, these variations can be an important determinant of the 

magnitude of seasonal hires or layoffs that have occurred at the time the survey is taken, thereby 

complicating seasonal adjustment. 
13 

Standard seasonal adjustment methodology relies heavily on the experience of the most 

recent 3 years to determine the expected seasonal change in employment for each month of the 

current year. Prior to the implementation of the adjustment, the procedure did not distinguish 

between 4- and 5-week survey intervals, and the accuracy of the seasonal expectation depended 

in large measure on how well the current year’s survey interval corresponded with those of the 

previous 3 years. All else the same, the greatest potential for distortion occurred when the 

current month being estimated had a 5-week interval but the 3 years preceding it were all 4-week 

intervals, or conversely when the current month had a 4-week interval but the 3 years preceding 

it were all 5-week intervals. 

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

the estimated size and significance of the calendar effect for each published series. REGARIMA 

combines standard regression analysis, which measures correlation among two or more 

variables, with ARIMA modeling, which describes and predicts the behavior of data series based 

on its own past history. For many economic time series, including nonfarm payroll employment, 

observations are auto-correlated over time; that is, each month’s value is significantly dependent 

on the observations that precede it. These series, therefore, usually can be successfully fit using 

ARIMA models. If auto-correlated time series are modeled through regression analysis alone, 

the measured relationships among other variables of interest may be distorted due to the 

influence of the auto-correlation. Thus, the REGARIMA technique is appropriate for measuring 

relationships among variables of interest in series that exhibit autocorrelation, such as nonfarm 

payroll employment. 

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

individual calendar months and the lengths of the survey intervals for those months. The 
14 

REGARIMA models evaluate the variation in employment levels attributable to 11 separate 

survey interval variables, one specified for each month, except March. March is excluded 

because there are almost always 4 weeks between the February and March surveys. Models for 

individual basic series are fit with the most recent 10 years of data 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. These coefficients provide estimates of the strength of the relationship 

between employment levels and the number of weeks between surveys for the 11 modeled 

months. The X-12 ARIMA software also produces diagnostic statistics that permit the 

assessment of the statistical significance 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 variation in employment levels associated with the length of the survey 

interval, these coefficients are used to adjust the CES data to remove the calendar effect. These 

“filtered” series then are seasonally adjusted using the standard X-12 ARIMA software 

previously used. 

For a few series, REGARIMA models do not fit well; these series are seasonally adjusted 

with X-12 software but without the interval effect adjustment. There are several additional 

special effects modeled through the REGARIMA process; they are described below. 

Construction series. Beginning with the 1996 benchmark revision, BLS utilized special 

treatment to adjust construction industry series. In the application of the interval effect modeling 

process to the construction series, there initially was difficulty in accurately identifying and 
15 

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

movements in the industry. Further research allowed BLS to incorporate interval effect 

modeling for the construction industry by disaggregating the construction series into its finer 

industry and geographic estimating cells and tightening outlier designation parameters. This 

allowed a more precise identification of weather-related outliers that had masked the interval 

effect and clouded the seasonal adjustment patterns in general. With these outliers removed, 

interval effect modeling became feasible. The result is a seasonally adjusted series for 

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

weather events and the 4- versus 5-week effect. 

Floating holidays. BLS is continuing the practice of making special adjustments for average 

weekly hours and average weekly overtime series to account for the presence or absence of 

religious holidays in the April survey reference period and the occurrence of Labor 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 employment due to 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 implemented refinements to the seasonal adjustment process for the hours and 

earnings series to correct for distortions related to the method of accounting for the varying 

length of payroll periods across months. There is a significant correlation between over-themonth changes in both the average weekly hour (AWH) and the average hourly earnings (AHE) 

series and the number of weekdays in a month, resulting in non-economic fluctuations in these 

two series. Both AWH and AHE show more growth in "short" months (20 or 21 weekdays) than 
16 

in "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 information from sample respondents with semi-monthly or 

monthly pay periods to a weekly equivalent. The response error comes from sample respondents 

reporting a fixed number of total hours for workers regardless of the length of the reference 

month, while the CES conversion process assumes that the hours reporting will be variable. A 

constant level of hours reporting most likely occurs when employees are salaried rather than paid 

by the hour, as employers are less likely to keep actual detailed hours records for such 

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 to the length of the month), which dictates that different 

conversion factors be applied to payroll and hours. The CES processing system uses the hours 

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

reversals in long months. 

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

effect for seasonally adjusted average weekly hours and average hourly earnings series. The 

length-of-pay-period variable proves significant for explaining AWH movements in all the 

service-providing industries except retail trade. For AHE, the length-of-pay-period variable is 

significant for wholesale trade, financial activities, professional and business services, and other 

services. All AWH series in the service-providing industries except retail trade have been 

adjusted from January 1990 forward. The AHE series for wholesale trade, financial activities, 
17 

professional and business services, and other services have been adjusted from January 1990 

forward as well. For this reason, calculations of over-the-year change in the establishment hours 

and earnings series should 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 adjustment, as the modeling cannot support the number of variables that would 

be required in the regression equation to make both adjustments. 

Additive and multiplicative models. Prior to the 2002 benchmark release, all CES series were 

adjusted using multiplicative seasonal adjustment models. Although the X-12 method provides 

for either an additive or a multiplicative adjustment, depending on which model best fits the 

individual series, the previous CES processing system was unable to utilize additive adjustments. 

A new processing system, introduced simultaneously with the NAICS conversion, is able to 

utilize both additive and multiplicative adjustments. See Exhibit 6 for a list of which series are 

adjusted with additive and multiplicative models, and designation of the calendar effects 

modeling described above. 

Exhibit 6. Additive and multiplicative models.

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 - X Indirect 
18 

building 

20237000 

Heavy and civil 

engineering 

construction 

ADD X 

20238000 Specialty trade 

contractors - X Indirect 

20238001 Residential specialty 

trade contractors MULT X Raked2

20238002 

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 

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 

32315000 Apparel MULT X 

32316000 Leather and allied MULT X 
19 

products 

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 

and garden supply 

stores 

MULT X 

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 
20 

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 

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 

55525000 Funds, trusts, and 

other financial MULT X 
21 

vehicles 

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 

services ADD X 

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 
22 

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 

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 

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 
23 

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, 

and recreation MULT X 

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 
24 

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 

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 
25 

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 

Seasonal Adjustment - AWH 

NAICS 

Tabcode Mode 4/5 week adj 

10/11 day 

adj 

Easter/ 

Labor 

Day adj 

 

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 ADD X X 
26 

tobacco products 

32313000 Textile mills MULT X X 

32314000 Textile product mills MULT X X 

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 
27 

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 
28 

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 indust1995-2004 1

Industry 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

Total 0.5 (2) 0.4 (2) 0.2 0.4 -0.1 -0.2 -0.1 0.2 Total Private 0.5 0.1 0.5 0.1 0.2 0.3 -0.2 -0.4 -0.2 0.2 Government 0.2 -0.1 -0.4 -0.2 0.1 0.6 0.3 1.0 0.3 0.1 (1) Differences are based on comparisons of final published March estimates and benchmark levels, as orig(2) Less than 0.05 percent. 
29 

Table 2. Nonfarm employment benchmarks by industry, March 2004(Numbers in thousands) 

Difference

Industry Benchmark Estimate

Amount Percent

Total nonfarm 130,019 129,816 203 .2 Total private 108,027 107,847 180 .2 Goods-producing 21,341 21,350 -9 (1) Service-providing 108,678 108,466 212 .2Private service-providing 86,686 86,497 189 .2 Natural resources and mining 570 566 4 .7 Logging 64 61 3 4.7 Mining 505 504 1 .2 Oil and gas extraction 120 129 -9 -7.5 Mining, except oil and gas 196 197 -1 -.5 Coal mining 69 70 -1 -1.4Support activities for mining 189 179 10 5.3 
30 

Construction 6,551 6,512 39 .6 Construction of buildings 1,548 1,548 0 0 Heavy and civil engineering construction 818 842 -24 -2.9 Specialty trade contractors 4,186 4,122 64 1.5 Manufacturing 14,220 14,272 -52 -.4 Durable goods 8,844 8,870 -26 -.3 Wood products 535 531 4 .7 Nonmetallic mineral products 486 481 5 1.0 Primary metals 464 461 3 .6 Fabricated metal products 1,476 1,475 1 .1 Machinery 1,133 1,147 -14 -1.2 Computer and electronic products 1,317 1,336 -19 -1.4 Computer and peripheral equipment 213 219 -6 -2.8 Communications equipment 148 155 -7 -4.7 Semiconductors and electronic components 449 451 -2 -.4 Electronic instruments 427 426 1 .2 Electrical equipment and appliances 445 446 -1 -.2 Transportation equipment 1,765 1,770 -5 -.3 Furniture and related products 571 573 -2 -.4 Miscellaneous manufacturing 653 651 2 .3 Nondurable goods 5,376 5,402 -26 -.5 
31 

Food manufacturing 1,470 1,475 -5 -.3 

Beverages and tobacco products 189 193 -4 -2.1 Textile mills 241 238 3 1.2 Textile product mills 177 179 -2 -1.1 Apparel 294 295 -1 -.3 Leather and allied products 43 45 -2 -4.7 Paper and paper products 496 506 -10 -2.0 Printing and related support activities 663 661 2 .3 Petroleum and coal products 110 111 -1 -.9 Chemicals 890 896 -6 -.7 Plastics and rubber products 803 804 -1 -.1 Trade, transportation, and utilities 25,130 25,092 38 .2 Wholesale trade 5,602 5,597 5 .1 Electronic markets and agents and brokers 688 663 25 3.6 Retail trade 14,771 14,753 18 .1 Motor vehicle and parts dealers 1,891 1,893 -2 -.1 Automobile dealers 1,259 1,262 -3 -.2 Furniture and home furnishings stores 555 541 14 2.5 Electronics and appliance stores 511 510 1 .2 Building material and garden supply stores 1,193 1,212 -19 -1.6 Food and beverage stores 2,797 2,805 -8 -.3 Health and personal care stores 937 953 -16 -1.7 
32 

Gasoline stations 869 863 6 .7 

Clothing and clothing accessories stores 1,311 1,285 26 2.0 Sporting goods, hobby, book, and music stores 626 622 4 .6General merchandise stores 2,766 2,743 23 .8 Department stores 1,556 1,550 6 .4 Miscellaneous store retailers 896 907 -11 -1.2 Nonstore retailers 420 421 -1 -.2 Transportation and warehousing 4,190 4,163 27 .6 Air transportation 513 510 3 .6 Rail transportation 222 215 7 3.2 Water transportation 54 48 6 11.1Truck transportation 1,313 1,320 -7 -.5 Transit and ground passenger transportation 400 394 6 1.5 Pipeline transportation 38 38 0 0 Scenic and sightseeing transportation 22 26 -4 -18.2 Support activities for transportation 527 514 13 2.5 Couriers and messengers 554 570 -16 -2.9 Warehousing and storage 548 529 19 3.5 Utilities 567 579 -12 -2.1 Information 3,126 3,158 -32 -1.0 Publishing industries, except Internet 909 914 -5 -.6 Motion picture and sound recording industries 374 374 0 0 Broadcasting, except Internet 324 333 -9 -2.8 
33 

Internet publishing and broadcasting 29 32 -3 -10.3 

Telecommunications 1,053 1,053 0 0 ISPs, search portals, and data processing 387 404 -17 -4.4 Other information services 50 49 1 2.0 Financial activities 7,966 7,958 8 .1Finance and insurance 5,929 5,923 6 .1 Monetary authorities--central bank 22 22 0 0 Credit intermediation and related activities 2,807 2,786 21 .7 Depository credit intermediation 1,747 1,759 -12 -.7 Commercial banking 1,277 1,280 -3 -.2 Securities, commodity contracts, investments 757 778 -21 -2.8 Insurance carriers and related activities 2,257 2,258 -1 (1) Funds, trusts, and other financial vehicles 86 79 7 8.1 Real estate and rental and leasing 2,037 2,036 1 (1) Real estate 1,382 1,385 -3 -.2 Rental and leasing services 629 622 7 1.1 Lessors of nonfinancial intangible assets 26 29 -3 -11.5 Professional and business services 15,995 16,031 -36 -.2 Professional and technical services 6,771 6,752 19 .3 Legal services 1,149 1,132 17 1.5 Accounting and bookkeeping services 927 928 -1 -.1 Architectural and engineering services 1,225 1,229 -4 -.3 Computer systems design and related services 1,129 1,105 24 2.1 Management and technical consulting services 760 768 -8 -1.1 
34 

Management of companies and enterprises 1,702 1,664 38 2.2 Administrative and waste services 7,523 7,615 -92 -1.2 Administrative and support services 7,205 7,297 -92 -1.3 Employment services 3,231 3,348 -117 -3.6 Temporary help services 2,207 2,268 -61 -2.8 Business support services 755 748 7 .9 Services to buildings and dwellings 1,557 1,543 14 .9 Waste management and remediation services 318 318 0 0 Education and health services 16,988 16,953 35 .2 Educational services 2,904 2,883 21 .7 Health care and social assistance 14,084 14,070 14 .1 Ambulatory health care services 4,890 4,857 33 .7 Offices of physicians 2,036 2,040 -4 .2 Outpatient care centers 443 431 12 2.7 Home health care services 757 739 18 2.4 Hospitals 4,268 4,293 -25 -.6 Nursing and residential care facilities 2,799 2,793 6 .2 Nursing care facilities 1,570 1,579 -9 -.6 Social assistance 2,127 2,127 0 0 Child day care services 772 789 -17 -2.2 Leisure and hospitality 12,077 11,927 150 1.2 Arts, entertainment, and recreation 1,694 1,657 37 2.2 Performing arts and spectator sports 353 348 5 1.4 
35 

Museums, historical sites, zoos, and parks 110 108 2 1.8 

Amusements, gambling, and recreation 1,232 1,201 31 2.5 Accommodations and food services 10,383 10,270 113 1.1 Accommodations 1,727 1,694 33 1.9 Food services and drinking places 8,656 8,576 80 .9 Other services 5,404 5,378 26 .5 Repair and maintenance 1,232 1,241 -9 -.7 Personal and laundry services 1,264 1,247 17 1.3 Membership associations and organizations 2,908 2,890 18 .6 Government 21,992 21,969 23 .1 Federal 2,713 2,698 15 .6 Federal, except U.S. Postal Service 1,928 1,911 17 .9 U.S. Postal Service 785 787 -2 -.3 State government 5,116 5,164 -48 -.9 State government education 2,392 2,429 -37 -1.5 State government, excluding education 2,725 2,735 -10 -.4 Local government 14,163 14,107 56 .4 Local government education 8,111 8,075 36 .4 Local government, excluding education 6,052 6,032 20 .3 (1) Less than 0.05 percent. 
36 

Table 3. Differences in seasonally adjusted levels and over-the-month changes, total nonfarm eJanuary 2004-December 2004(In thousands) 

Levels Over-the-month changes

As previously 

published As revised As previously published As revised Difference

2004: January 130,194 130,372 159 117 -42 February 130,277 130,466 83 94 11 March 130,630 130,786 353 320 -33 April 130,954 131,123 324 337 13 May 131,162 131,373 208 250 42 June 131,258 131,479 96 106 10 July 131,343 131,562 85 83 -2 August 131,541 131,750 198 188 -10 September 131,660 131,880 119 130 11 October 131,972 132,162 312 282 -30 November(p) 132,109 132,294 137 132 -5 December(p) 132,266 132,427 157 133 -24 (p): Preliminary 
37 

Table 4. Hours and earnings estimates, selected industries, March 2004

Industry Average weekly hours Average hourly earnings

Total private 33.5 $15.54Goods-producing 40.1 17.00Natural resources and mining 43.9 18.10Construction 38.3 19.06Manufacturing 40.8 16.00Durable goods 41.4 16.68Wood products 40.6 12.93Nonmetallic mineral products 42.5 16.00Primary metals 43.1 18.33Fabricated metal products 41.0 15.25Machinery 41.9 16.50Computer and electronic products 40.8 16.94Electrical equipment and appliances 40.6 14.71Transportation equipment 43.0 21.29
38 

Furniture and related products 39.5 12.97

Miscellaneous manufacturing 38.8 13.79Nondurable goods 40.0 14.90Food manufacturing 38.7 12.91Beverages and tobacco products 38.9 19.10Textile mills 40.7 12.08Textile product mills 38.8 11.35Apparel 36.5 9.59Leather and allied products 39.8 11.62Paper and paper products 41.6 17.63Printing and related support activities 38.6 15.63Petroleum and coal products 43.5 24.79Chemicals 43.0 18.83Plastics and rubber products 40.8 14.45Private service-providing 32.1 15.16Trade, transportation, and utilities 33.2 14.48
39 

Wholesale trade 37.7 17.46

Retail trade 30.4 12.02Transportation and warehousing 36.7 16.35Utilities 40.9 25.38Information 35.9 21.16Financial activities 35.2 17.38Professional and business services 34.0 17.32Education and health services 32.1 15.99Leisure and hospitality 25.4 8.90Other services 30.9 13.93
40 

Text Table A. Net Birth/Death Estimates, Post-Benchmark 2004 

(In thousands) 2004: 

Natural 

Resources 

& Mining 

Construction Manufacturing 

Trade, 

Transportation, 

& Utilities 

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

Hospit

April 0 38 3 15 2 10 66 37 45 

May 1 39 8 26 3 7 26 11 77 

June 1 31 7 20 1 8 24 -2 84 

July 0 -7 -22 -25 -6 -12 -32 -10 45 

August 1 16 4 18 3 8 24 17 27 

September 0 10 6 19 -2 4 14 15 -24 

October 0 2 -10 11 2 8 41 29 -25 

November 0 -7 2 13 2 5 -5 9 -12 

December 0 -7 2 19 2 13 9 8 16 

Cumulative Total 3 115 0 116 7 51 167 114 233