Current Employment Statistics - CES (National)

CES National Benchmark Article (PDF)

BLS Establishment Survey National Estimates Revised to Incorporate March 2014 Benchmarks

Authored by Nicholas Fett and Caila Pinkleton.

Nicholas Fett and Caila Pinkleton are economists in the Division of Current Employment Statistics – National, Office of Employment and Unemployment Statistics, Bureau of Labor Statistics. Telephone: (202) 691-6555; e-mail: Contact CES

Introduction

With the release of January 2015 data on February 6, 2015, 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 incorporate universe counts of employment—a process known as benchmarking. Comprehensive counts of employment, or benchmarks, are derived primarily from unemployment insurance (UI) tax reports that nearly all employers are required to file with State Workforce Agencies.

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Summary of the benchmark revisions

The March 2014 benchmark level for total nonfarm employment is 137,214,000; this figure is 67,000 above the sample based estimate for March 2014, an adjustment of less than 0.05 percent.

Table 1 below shows the recent history of total nonfarm percentage benchmark revisions. Over the prior ten years, the annual benchmark revision at the total nonfarm level has averaged 0.3 percent (in absolute terms), with an absolute range of 0.1 percent to 0.7 percent.

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Table 1. Percent differences between nonfarm employment benchmarks and estimates by industry supersector, March 2004 – 2014(1)
CES Industry Code CES Industry Title 2004 2005 2006 2007 2008 2009 2010 2011(2) 2012 2013(3) 2014

00-000000

Total nonfarm 0.2 -0.1 0.6 -0.2 -0.1 -0.7 -0.3 0.1 0.3 -0.1 (4)

(Level difference in thousands)

(203) (-158) (752) (-293) (-89) (-902) (-378) (67) (424) (-119) (67)

05-000000

Total private .2 -.2 .7 -.2 -.1 -.9 -.4 (4) .4 -.1 .1

10-000000

Mining and logging .7 -.3 1.2 (4) .4 -3.5 -3.0 -.4 1.6 -1.2 -1.8

20-000000

Construction .6 .5 2.6 .1 .7 -2.9 -1.3 -.5 1.8 .3 1.6

30-000000

Manufacturing -.4 -.3 -.1 -1.0 -.1 -.7 -1.0 .1 -.2 .2 .4

40-000000

Trade, transportation, and utilities .2 .3 .6 .5 .2 -1.2 -.6 .4 .6 -.5 -.1

50-000000

Information -1.0 -2.1 -.5 -1.8 .3 -1.5 -.4 -.4 1.8 -.2 2.4

55-000000

Financial activities .1 -.8 .4 -1.3 -.3 -.1 .4 -.2 .6 -.1 .2

60-000000

Professional and business services -.2 -.4 1.3 .2 -.4 -.8 (4) .7 (4) (4) -.8

65-000000

Education and health services .2 (4) .5 -.2 -.1 -.3 (4) -.6 (4) -.3 -.1

70-000000

Leisure and hospitality 1.2 .4 .3 -.8 -1.1 -.6 -.6 .7 .8 .5 .3

80-000000

Other services .5 -1.3 .5 .3 .2 -.8 .2 -2.0 1.1 -.4 1.1

90-000000

Government .1 (4) (4) -.2 .2 .1 .1 .1 -.3 (4) -.2

Footnotes
(1)The differences listed in this table reflect the error due to normal benchmarking procedures. Typically this error is equal to the March benchmarked level minus the published March estimated level. However in some years, other factors beyond normal benchmarking procedures influence the difference between the benchmarked and published March estimate levels. Those years are footnoted.
(2)A review of industries for the possible presence of noncovered employment in benchmark 2011 yielded 13 additional industries. As a result of including these industries, employment in the amount of 95,000 was added to the Total nonfarm benchmark level. The difference between the benchmarked and published March 2011 estimate level was 162,000. For this table, the 95,000 amount was added to the original published Total nonfarm and Total private March 2011 estimates before calculating the percent and level differences. Portions of the 95,000 amount were also added as appropriate to the original published March 2011 estimates of supersectors Financial activities and Education and health services before calculating the percent differences.
(3)The percent and level differences in this column reflect reconstructions to series within CES supersectors Financial activities and Education and healthcare services. Each first quarter, the Quarterly Census of Employment and Wages (QCEW) program, whose data account for approximately 97 percent of the CES universe scope (see www.bls.gov/web/empsit/cestn.htm#section1), incorporates updated industry assignments. In 2013, these updates included two substantial groups of nonrandom, noneconomic code changes, one to Funds, trusts, and other financial vehicles (NAICS 525), and the other, a reclassification of approximately 466,000 in employment from Private households (NAICS 814), which is out of scope for CES, to Services for the elderly and persons with disabilities (NAICS 62412), which is in scope. These changes also had an impact, beyond what would be considered typical for a given benchmark year, on corresponding CES series. For more information about the changes to these industries, see the QCEW First Quarter 2013 News Release available at www.bls.gov/news.release/archives/cewqtr_09262013.htm.
(4)Less than 0.05 percent.

To Table of Figures


Table 2 shows the nonfarm employment benchmarks for March 2014, not seasonally adjusted, by industry. The revision to the reconstructed total nonfarm employment is 67,000.

Six supersectors had upward revisions. The largest upward revision occurred in construction by an amount of 90,000, or 1.6 percent. Within this supersector, the revision was concentrated in specialty trade contractors, which was revised upward by 92,700, or 2.5 percent. Information had an upward revision of 66,000, or 2.4 percent. Other services ws revised upward by 59,000 or 1.1 percent. Manufacturing was revised upward by 43,000 or 0.4 percent, with the majority of the increase attributed to nondurable goods, which experiences an upward revision of 30,000, or 0.7 percent. Leisure and hospitality was also revised upward by 38,000, or 0.3 percent. The smallest upward revision of 19,000, or 0.2 percent occurred in financial activities.

The remaining five supersectors saw negative revisions. The largest downward revision occurred in professional and business services, which decreased by 147,000, or 0.8 percent. Within this supersector, the largest revision was in administrative and support services with a revision of ‑169,400, or ‑2.2 percent. The next largest revision occured in government, which experienced a drop of ‑38,000, or ‑0.2 percent. Trade, transportation, and utilities was also revised downward by ‑31,000, or ‑0.1 percent, with a large decrease occurring in wholesale trade (‑45,400, or ‑0.8 percent). Mining and logging and education and health services exhibited identical level decreases of ‑16,000 (‑1.8 percent and ‑0.1 percent, respectively).

Table 2. Nonfarm employment benchmarks by industry, March 2014 (in thousands)
CES Industry Code CES Industry Title Benchmark Estimate Differences
Amount Percent

00-000000

Total nonfarm 137,214 137,147 67 (1)

05-000000

Total private 114,989 114,884 105 0.1

06-000000

Goods-producing 18,675 18,558 117 0.6

07-000000

Service-providing 118,539 118,589 -50 (1)

08-000000

Private service-providing 96,314 96,326 -12 (1)

10-000000

Mining and logging 868 884 -16 -1.8

10-113300

Logging 50 52.8 -2.8 -5.6

10-210000

Mining 817.6 830.8 -13.2 -1.6

10-211000

Oil and gas extraction 192.7 206.2 -13.5 -7

10-212000

Mining, except oil and gas 201 205.8 -4.8 -2.4

10-212100

Coal mining 73.6 77.7 -4.1 -5.6

10-213000

Support activities for mining 423.9 418.8 5.1 1.2

20-000000

Construction 5,746 5,656 90 1.6

20-236000

Construction of buildings 1,283.4 1,286.2 -2.8 -0.2

20-236100

Residential building 615.2 621.7 -6.5 -1.1

20-236200

Nonresidential building 668.2 664.5 3.7 0.6

20-237000

Heavy and civil engineering construction 823.9 823.8 0.1 (1)

20-238000

Specialty trade contractors 3,638.2 3,545.5 92.7 2.5

30-000000

Manufacturing 12,061 12,018 43 0.4

31-000000

Durable goods 7,600 7,587 13 0.2

31-321000

Wood products 361.9 358 3.9 1.1

31-327000

Nonmetallic mineral products 369.1 371.4 -2.3 -0.6

31-331000

Primary metals 396.3 396.6 -0.3 -0.1

31-332000

Fabricated metal products 1,438.5 1,440.2 -1.7 -0.1

31-333000

Machinery 1,116.1 1,115.2 0.9 0.1

31-334000

Computer and electronic products 1,048.3 1,055.7 -7.4 -0.7

31-334100

Computer and peripheral equipment 158.2 161.9 -3.7 -2.3

31-334200

Communications equipment 95.3 99.5 -4.2 -4.4

31-334400

Semiconductors and electronic components 368 368.6 -0.6 -0.2

31-334500

Electronic instruments 389.6 387.7 1.9 0.5

31-335000

Electrical equipment and appliances 357.3 374.8 0.5 0.1

31-336000

Transportation equipment 1,547.4 1,533.9 13.5 0.9

31-337000

Furniture and related products 366 362.5 3.5 1

31-339000

Miscellaneous durable goods manufacturing 581 578.4 2.6 0.4

32-000000

Nondurable goods 4,461 4,431 30 0.7

32-311000

Food manufacturing 1,460.8 1,458 2.8 0.2

32-313000

Textile mills 117.2 116.9 0.3 0.3

32-314000

Textile product mills 113.2 110.7 2.5 2.2

32-315000

Apparel 142.6 135.6 7 4.9

32-322000

Paper and paper products 372.1 374.5 -2.4 -0.6

32-323000

Printing and related support activities 452.7 440.7 12 2.7

32-324000

Petroleum and coal products 107.5 110.5 -3 -2.8

32-325000

Chemicals 797.9 797.4 0.5 0.1

32-326000

Plastics and rubber products 668.6 659.2 9.4 1.4

32-329000

Miscellaneous nondurable goods manufacturing 228.3 227.6 0.7 0.3

40-000000

Trade, transportation, and utilities 25,852 25,883 -31 -0.1

41-420000

Wholesale trade 5,758.3 5,803.7 -45.4 -0.8

41-423000

Durable goods 2,883.8 2,917.2 -33.4 -1.2

41-424000

Nondurable goods 1,989 1,985.6 3.4 0.2

41-425000

Electronic markets and agents and brokers 885.5 900.9 -15.4 -1.7

42-000000

Retail trade 15,009.5 15,004 5.5 (1)

42-441000

Motor vehicle and parts dealers 1,826.3 1,822.9 3.4 0.2

42-441100

Automobile dealers 1,163.7 1,157.5 6.2 0.5

42-442000

Furniture and home furnishings stores 444 442.2 1.8 0.4

42-443000

Electronics and appliance stores 483.2 497.8 -14.6 -3

42-444000

Building material and garden supply stores 1,210.5 1,207.2 3.3 0.3

42-445000

Food and beverage stores 2,943.8 2,957.8 -14 -0.5

42-446000

Health and personal care stores 1,010.3 1,008.4 1.9 0.2

42-447000

Gasoline stations 863.4 859.7 3.7 0.4

42-448000

Clothing and clothing accessories stores 1,320.5 1,338.5 -18 -1.4

42-451000

Sporting goods, hobby, book, and music stores 591.9 574.6 17.3 2.9

42-452000

General merchandise stores 3,043.7 3,053.9 -10.2 -0.3

42-452100

Department stores 1,312.8 1,301.3 11.5 0.9

42-453000

Miscellaneous store retailers 791.3 774.1 17.2 2.2

42-454000

Nonstore retailers 480.6 466.9 13.7 2.9

43-000000

Transportation and warehousing 4,534.5 4,524.8 9.7 0.2

43-481000

Air transportation 440.2 455.2 -15 -3.4

43-482000

Rail transportation 230.3 232.7 -2.4 -1

43-483000

Water transportation 64.9 65.3 -0.4 -0.6

43-484000

Truck transportation 1,374.3 1,367.7 6.6 0.5

43-485000

Transit and ground passenger transportation 476.9 468.3 8.6 1.8

43-486000

Pipeline transportation 46.5 45.1 1.4 3

43-487000

Scenic and sightseeing transportation 24.5 23.8 0.7 2.9

43-488000

Support activities for transportation 613.7 599.8 13.9 2.3

43-492000

Couriers and messengers 539.2 541 -1.8 -0.3

43-493000

Warehousing and storage 724 725.9 -1.9 -0.3

44-220000

Utilities 549.7 550.3 -0.6 -0.1

50-000000

Information 2,719 2,653 66 2.4

50-511000

Publishing industries, except Internet 723.7 726.5 -2.8 -0.4

50-512000

Motion picture and sound recording industries 380.1 313 67.1 17.7

50-515000

Broadcasting, except Internet 281.5 287.5 -6 -2.1

50-517000

Telecommunications 849.4 854.4 -5 -0.6

50-518000

Data processing, hosting and related services 274.4 267.8 6.6 2.4

50-519000

Other information services 209.6 203.3 6.3 3

55-000000

Financial activities 7,889 7,870 19 0.2

55-520000

Finance and insurance 5,894.9 5,868.9 26 0.4

55-521000

Monetary authorities - central bank 18.2 18 0.2 1.1

55-522000

Credit intermediation and related activities 2,562.8 2,571.1 -8.3 -0.3

55-522100

Depository credit intermediation 1,712.6 1,705 7.6 0.4

55-522110

Commercial banking 1,301.2 1,280.9 20.3 1.6

55-523000

Securities, commodity contracts, investments, and funds and trusts 874.2 870.5 3.7 0.4

55-524000

Insurance carriers and related activities 2,439.7 2,409.3 30.4 1.2

55-530000

Real estate and rental and leasing 1,994.2 2,000.6 -6.4 -0.3

55-531000

Real estate 1,459.4 1,458.3 1.1 0.1

55-532000

Rental and leasing services 511.3 520.2 -8.9 -1.7

55-533000

Lessors of nonfinancial intangible assets 23.5 22.1 1.4 6

60-000000

Professional and business services 18,685 18,832 -147 -0.8

60-540000

Professional and technical services 8,310.3 8,326.6 -16.3 -0.2

60-541100

Legal services 1,118 1,134.4 -16.4 -1.5

60-541200

Accounting and bookkeeping services 1,058 1,052.3 5.7 0.5

60-541300

Architectural and engineering services 1,344.1 1,369.1 -25 -1.9

60-541500

Computer systems design and related services 1,742.1 1,728.6 13.5 0.8

60-541600

Management and technical consulting services 1,208.2 1,199.1 9.1 0.8

60-550000

Management of companies and enterprises 2,146.5 2,112.8 33.7 1.6

60-560000

Administrative and waste services 8,228 8,392.2 -164.2 -2

60-561000

Administrative and support services 7,852.1 8,021.5 -169.4 -2.2

60-561300

Employment services 3,251.7 3,427.2 -175.5 -5.4

60-561320

Temporary help services 2,626 2,741.2 -115.2 -4.4

60-561400

Business support services 873.8 858.5 15.3 1.8

60-561700

Services to buildings and dwellings 1,803.9 1,802.3 1.6 0.1

60-562000

Waste management and remediation services 375.9 370.7 5.2 1.4

65-000000

Education and health services 21,465 21,481 -16 -0.1

65-610000

Educational services 3,555.4 3,539.1 16.3 0.5

65-620000

Health care and social assistance 17,909.8 17,941.4 -31.6 -0.2

65-621000

Ambulatory health care services 6,556.1 6,597.3 -41.2 -0.6

65-621100

Offices of physicians 2,448.7 2,473.9 -25.2 -1

65-621400

Outpatient care centers 698.5 705.9 -7.4 -1.1

65-621600

Home health care services 1,240 1,265.7 -25.7 -2.1

65-622000

Hospitals 4,767.3 4,792.7 -25.4 -0.5

65-623000

Nursing and residential care facilities 3,239.6 3,234.9 4.7 0.1

65-623100

Nursing care facilities 1,644.3 1,644.1 0.2 (1)

65-624000

Social assistance 3,346.8 3,316.5 30.3 0.9

65-624400

Child day care services 866.4 876.1 -9.7 -1.1

70-000000

Leisure and hospitality 14,181 14,143 38 0.3

70-710000

Arts, entertainment, and recreation 1,927.5 1,939.7 -12.2 -0.6

70-711000

Performing arts and spectator sports 421 420.9 0.1 (1)

70-712000

Museums, historical sites, and similar institutions 138 134.5 3.5 2.5

70-713000

Amusements, gambling, and recreation 1,368.5 1,384.3 -15.8 -1.2

70-720000

Accommodation and food services 12,253.4 12,203.2 50.2 0.4

70-721000

Accommodation 1,819.2 1,805.9 13.3 0.7

70-722000

Food services and drinking places 10,434.2 10,397.3 36.9 0.4

80-000000

Other services 5,523 5,464 59 1.1

80-811000

Repair and maintenance 1,232.3 1,209 23.3 1.9

80-812000

Personal and laundry services 1,351.9 1,351.7 0.2 (1)

80-813000

Membership associations and organizations 2,938.6 2,903.4 35.2 1.2

90-000000

Government 22,225 22,263 -38 -0.2

90-910000

Federal 2,716 2,705 11 0.4

90-911000

Federal, except U.S. Postal Service 2,127.5 2,117.6 9.9 0.5

90-919120

U.S. Postal Service 588.2 587.1 1.1 0.2

90-920000

State government 5,211 5,217 -6 -0.1

90-921611

State government education 2,565.4 2,565.2 0.2 (1)

90-922000

State government, excluding education 2,645.1 2,651.8 -6.7 -0.3

90-930000

Local government 14,298 14,341 -43 -0.3

90-931611

Local government education 8,129 8,147.8 -18.8 -0.2

90-932000

Local government, excluding education 6,169.3 6,193.1 -23.8 -0.4

Footnotes
(1) Less than 0.05 percent.

To Table of Figures


Revisions in the postbenchmark period

From April 2014 to December 2014, also known as the postbenchmark period, estimates were calculated for each month based on new benchmark levels and new net birth/death factors. Net birth/death factors were revised to incorporate information from the most recent year of universe employment counts. Table 3 shows the net birth/death model values for the supersectors over the postbenchmark period. From April 2014 to December 2014, the net birth/death model cumulatively added 968,000, compared with 841,000 in the previously published April to December employment estimates.

Table 3. Net birth/death estimates by industry supersector, April – December 2014 (in thousands)
CES Industry Code CES Industry Title Apr May Jun Jul Aug Sep Oct Nov Dec Cumulative
Total

10-000000

Mining and logging 2 2 2 2 1 1 1 1 0 12

20-000000

Construction 35 37 24 12 12 7 12 -10 -21 108

30-000000

Manufacturing 0 6 4 -3 4 1 3 2 0 17

40-000000

Trade, transportation, and utilities 21 24 12 7 14 9 28 10 4 129

50-000000

Information 0 5 0 -1 3 -1 6 3 0 15

55-000000

Financial activities 8 8 4 3 4 -1 16 3 10 55

60-000000

Professional and business services 81 22 5 35 19 -12 76 14 -10 230

65-000000

Education and health services 22 13 -14 7 21 12 35 14 -3 107

70-000000

Leisure and hospitality 82 81 86 62 23 -33 -17 -22 4 266

80-000000

Other services 12 6 6 -2 3 -2 4 1 1 29

Total nonfarm birth/death adjustment

263 204 129 122 104 -19 164 16 -15 968

To Table of Figures


Table 4 presents revised total nonfarm employment data on a seasonally adjusted basis for January 2014 through December 2014. The revised data for April 2014 forward incorporate the effect of applying the rate of change measured by the sample to the new benchmark level, as well as updated net birth/death model adjustments and new seasonal adjustment factors. Revisions to November and December also reflect incorporation of the annual CES sample update.

Table 4. Differences in seasonally adjusted levels and over-the-month changes, total nonfarm employment, January – December 2014 (in thousands)
2014 Levels Over-the-month changes
As Previously Published As Revised Difference As Previously Published As Revised Difference

January

137,539 137,642 103 144 166 22

February

137,761 137,830 69 222 188 -34

March

137,964 138,055 91 203 225 22

April

138,268 138,385 117 304 330 26

May

138,497 138,621 124 229 236 7

June

138,764 138,907 143 267 286 19

July

139,007 139,156 149 243 249 6

August

139,210 139,369 159 203 213 10

September

139,481 139,619 138 271 250 -21

October

139,742 139,840 98 261 221 -40

November

140,095 140,263 168 353 423 70

December(p)

140,347 140,592 245 252 329 77

Footnotes
(p) Preliminary.

To Table of Figures

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Changes to the CES published series

With the release of the January 2015 first preliminary estimates, CES incorporated series changes related to annual sample adequacy and disclosure review, and began publishing previously available but not published seasonally adjusted derivative series.

Series changes

All CES series are evaluated annually for sample size, coverage, and response rates. The following series changes result from a reevaluation of the sample and universe coverage for NAICS industries.

Some series have new CES industry codes or titles as a result of the series changes (Exhibit 1). These CES industry code or title changes have been applied to all data types published for the designated series. Historical data for those series with new CES industry codes or CES industry titles were impacted as noted on the remainder of this page; historical data are available under the new CES industry codes or CES industry titles.

Exhibit 1. Series with CES industry code or title changes
NAICS Code Previous New
CES Industry Code CES Industry Title CES Industry Code CES Industry Title

332996,9

31-332999 Miscellaneous fabricated metal products 31-332999 Miscellaneous fabricated metal products and ball and roller bearings

3346

31-334600 Miscellaneous media manufacturing and reproduction 31-334600 Miscellaneous computer and electronic products

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Exhibit 2 through Exhibit 7 show the new CES industry codes and titles, not the previous CES industry codes and titles, as noted in Exhibit 1.

Only directly estimated data types1 are included in the exhibits:

The directly estimated data types listed except for AE are collectively called non-AE data types. In order to more easily identify affected series, since AE series are published at a more detailed industry level than non-AE series, series changes exhibits are provided split by AE and non-AE data types. The non-AE tables cover all directly estimated non-AE data types.

The first group of series changes exhibits contains three exhibits referencing the AE data type and the second group contains three exhibits referencing all non-AE data types. The three exhibits in each group display the discontinued, collapsed, and new series. Discontinued series exhibits (Exhibit 2 and Exhibit 5) display series for which the data types noted are no longer published. Collapsed series exhibits (Exhibit 3 and Exhibit 6) display series for which the data types noted are no longer published because the industry no longer has sufficient sample to be estimated and published separately. Affected industries have been combined with other similar industries for estimation and publication purposes. Historical data for these series were reconstructed to provide consistent time series. New series exhibits (Exhibit 4 and Exhibit 7) display series for which the data types noted are now published.

AE exhibits

Exhibit 2. Discontinued AE series

There are no discontinued AE series.

To Table of Figures


Exhibit 3. Collapsed AE series
NAICS Code CES Industry Code CES Industry Title Collapsed into CES Industry

332991

31-332991 Ball and roller bearings Collapsed into miscellaneous fabricated metal products and ball and roller bearings (31-332999)

3343

31-334300 Audio and video equipment Collapsed into miscellaneous computer and electronic products(31-334600)

45393

42-453930 Manufactured and mobile home dealers Collapsed into all other miscellaneous store retailers (42-453990)

To Table of Figures


Exhibit 4. New AE series

There are no new AE series published.

To Table of Figures


To Table of Figures


Non-AE exhibits

Exhibit 5. Discontinued Non-AE series
NAICS Code CES Industry Code CES Industry Title Discontinued From Publication Next Highest Published Industry(2)

236116

20-236116 New multifamily general contractors AE AHE, AE AWH Residential building (20-236100)

236117

20-236117 New housing operative builders AE AHE, AE AWH Residential building (20-236100)

3311

31-331100 Iron and steel mills and ferroalloy production WE Primary metals (31-331000)

3313

31-331300 Alumina and aluminum production WE Primary metals (31-331000)

33151

31-331510 Ferrous metal foundries AE AHE, AE AWH, AE AWOH Foundries (31-331500)

33152

31-331520 Nonferrous metal foundries AE AHE, AE AWH, AE AWOH Foundries (31-331500)

332321

31-332321 Metal windows and doors AE AWOH Ornamental and architectural metal products (31-332320)

332323

31-332323 Ornamental and architectural metal work AE AWOH Ornamental and architectural metal products (31-332320)

332999

31-332999 Miscellaneous fabricated metal products AE AHE, AE AWH, AE AWOH, PE, PE AHE, PE AWH, PE AWOH, WE All other fabricated metal products (31-332990)

333517

31-333517 Machine tool manufacturing AE AHE, AE AWH, AE AWOH, PE, PE AHE, PE AWH, PE AWOH Metalworking machinery (31-333500)

337122

31-337122 Nonupholstered wood household furniture AE AHE, AE AWH, AE AWOH, PE, PE AHE, PE AWH, PE AWOH, WE Other household and institutional furniture (31-337120)

337124,5,7

31-337127 Miscellaneous household and institutional furniture AE AHE, AE AWH, AE AWOH, PE, PE AHE, PE AWH, PE AWOH, WE Other household and institutional furniture (31-337120)

311611

32-311611 Animal, except poultry, slaughtering AE AWOH Animal slaughtering and processing (32-311600)

311612,3

32-311613 Meat processed from carcasses, and rendering and meat byproduct processing AE AWOH Animal slaughtering and processing (32-311600)

45399

42-453990 All other miscellaneous store retailers AE AHE, AE AWH, PE, PE AHE, PE AWH, WE Other miscellaneous store retailers (42-453900)

54186

60-541860 Direct mail advertising PE, PE AHE, PE AWH Advertising and related services (60-541800)

Footnotes
(2) The industry listed is the next highest published industry for all data types discontinued from publication.

To Table of Figures


Exhibit 6. Collapsed Non-AE series

There are no collapsed non-AE series.

To Table of Figures


Exhibit 7. New Non-AE series

There are no new non-AE series published.

To Table of Figures

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Seasonally adjusted data publication change

Seasonally adjusted estimates for the indirectly estimated data types associated with series not available until the second preliminary release are now available with the second preliminary release. This change in publication status does not impact the seasonally adjusted series published for a given month with the first preliminary release of CES data. Approximately 8,300 more seasonally adjusted derivative series will be published.

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Why benchmarks differ from estimates

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 or infrequent events such as historical reconstructions. The employment counts obtained from quarterly UI 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 ensures 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 – measurement, 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.

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Benchmark revision effects for other data types

The routine benchmarking process results in revisions to the series for production and nonsupervisory employees and women employees. There are no benchmark employment levels for these series; they are revised by preserving ratios of employment for the particular data type to all employee 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, average hourly earnings, and in manufacturing industries, average weekly overtime hours 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 all employee employment estimates or the production and nonsupervisory employee employment estimates for the basic cells essentially act as weights for their respective hours and earnings estimates for broader industry groupings. Adjustments of the all employee estimates to new benchmarks may alter the weights used for both AE and PE hours and earnings, which, in turn, may change the estimates for both AE and PE hours and earnings at higher levels of aggregation.

Generally, new employment benchmarks have little effect on hours and earnings estimates for major industry groupings. To influence the hours and earnings estimates of a broader industry 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 broader group. Table 5 and Table 6 provide information on the levels of specific hours and earnings series resulting from the March 2014 benchmark. At the Total private level, there was no change in average weekly hours estimates for both AE and PE from the previously published level. Total private average hourly earnings increased by two cents for AE and PE from the previously published level.

Table 5. Effect of March 2014 benchmark revisions to AE AWH and AE AHE estimates, selected industries
CES Industry Code CES Industry Title Average Weekly Hours Average Hourly Earnings
Estimated Revised Difference Estimated Revised Difference

05-000000

Total private

34.7 34.7 0 $24.48 $24.50 $0.02

06-000000

Goods-producing

40.5 40.5 0 25.64 25.62 -.02

08-000000

Private service-providing

33.6 33.6 0 24.21 24.23 .02

10-000000

Mining and logging

45 45.1 .1 31.13 31.04 -.09

20-000000

Construction

38.7 38.6 -.1 26.55 26.53 -.02

30-000000

Manufacturing

41 41 0 24.80 24.79 -.01

31-000000

Durable goods

41.5 41.5 0 26.17 26.18 .01

31-321000

Wood products

41 41 0 18.20 18.17 -.03

31-327000

Nonmetallic mineral products

41.7 41.7 0 22.63 22.63 0

31-331000

Primary metals

43.6 43.6 0 24.92 24.94 .02

31-332000

Fabricated metal products

41.6 41.6 0 22.20 22.20 0

31-333000

Machinery

41.8 41.8 0 26.94 26.95 .01

31-334000

Computer and electronic products

40.2 40.2 0 33.73 33.73 0

31-335000

Electrical equipment and appliances

40.6 40.6 0 25.05 25.05 0

31-336000

Transportation equipment

43.1 43.1 0 29.85 29.94 .09

31-336001

Motor vehicles and parts

43.4 43.5 .1 24.40 24.50 .10

31-337000

Furniture and related products

39.9 39.9 0 19.43 19.46 .03

31-339000

Miscellaneous durable goods manufacturing

39.3 39.3 0 23.71 23.71 0

32-000000

Nondurable goods

40.3 40.2 -.1 22.38 22.34 -.04

32-311000

Food manufacturing

39.8 39.8 0 18.46 18.47 .01

32-313000

Textile mills

41.4 41.4 0 17.53 17.53 0

32-314000

Textile product mills

37.8 37.8 0 16.14 16.13 -.01

32-315000

Apparel

37.2 37.3 .1 17.15 17.17 .02

32-322000

Paper and paper products

42.4 42.4 0 24.58 24.60 .02

32-323000

Printing and related support activities

37.5 37.5 0 22.65 22.65 0

32-324000

Petroleum and coal products

43.6 43.4 -.2 38.09 37.58 -.51

32-325000

Chemicals

41.8 41.8 0 29.83 29.83 0

32-326000

Plastics and rubber products

41.3 41.3 0 20.53 20.52 -.01

32-329000

Miscellaneous nondurable goods manufacturing

37.4 37.4 0 21.32 21.32 0

40-000000

Trade, transportation, and utilities

34.6 34.6 0 21.45 21.44 -.01

41-420000

Wholesale trade

39.3 39.3 0 28.18 28.17 -.01

42-000000

Retail trade

31.3 31.3 0 16.94 16.95 .01

43-000000

Transportation and warehousing

38.6 38.6 0 22.88 22.90 .02

44-220000

Utilities

42.3 42.3 0 35.72 35.72 0

50-000000

Information

37.5 37.4 -.1 34.05 34.08 .03

55-000000

Financial activities

37.8 37.8 0 30.87 30.87 0

60-000000

Professional and business services

36.6 36.7 .1 29.39 29.49 .10

65-000000

Education and health services

32.8 32.8 0 24.57 24.59 .02

70-000000

Leisure and hospitality

26.5 26.5 0 13.78 13.79 .01

80-000000

Other services

32 32.1 .1 21.87 21.96 .09

To Table of Figures


Table 6. Effect of March 2014 benchmark revisions to PE AWH and PE AHE estimates, selected industries
CES Industry Code CES Industry Title Average Weekly Hours Average Hourly Earnings
Estimated Revised Difference Estimated Revised Difference

05-000000

Total private

33.8 33.8 0 $20.59 $20.61 $0.02

06-000000

Goods-producing

41.3 41.3 0 21.42 21.42 0

08-000000

Private service-providing

32.6 32.6 0 20.42 20.44 .02

10-000000

Mining and logging

47.6 47.6 0 26.79 26.75 -.04

20-000000

Construction

39.2 39.2 0 24.43 24.43 0

30-000000

Manufacturing

41.9 41.9 0 19.54 19.53 -.01

31-000000

Durable goods

42.4 42.4 0 20.63 20.65 .02

31-321000

Wood products

41.8 41.8 0 15.56 15.53 -.03

31-327000

Nonmetallic mineral products

42.5 42.5 0 18.63 18.64 .01

31-331000

Primary metals

44.1 44.2 .1 22.06 22.07 .01

31-332000

Fabricated metal products

42.5 42.5 0 18.63 18.63 0

31-333000

Machinery

43.2 43.3 .1 20.95 20.96 .01

31-334000

Computer and electronic products

40.8 40.8 0 23.57 23.57 0

31-335000

Electrical equipment and appliances

41.3 41.3 0 18.10 18.10 0

31-336000

Transportation equipment

43.7 43.7 0 24.91 24.98 .07

31-336001

Motor vehicles and parts

43.9 43.9 0 21.44 21.51 .07

31-337000

Furniture and related products

40.8 40.8 0 15.63 15.63 0

31-339000

Miscellaneous durable goods manufacturing

40 40 0 17.47 17.47 0

32-000000

Nondurable goods

41.2 41.2 0 17.72 17.68 -.04

32-311000

Food manufacturing

40.3 40.3 0 15.50 15.50 0

32-313000

Textile mills

41.7 41.7 0 14.09 14.09 0

32-314000

Textile product mills

37.5 37.5 0 13.25 13.25 0

32-315000

Apparel

39.1 39.2 .1 13.34 13.34 0

32-322000

Paper and paper products

43.7 43.7 0 20.16 20.18 .02

32-323000

Printing and related support activities

39 39 0 18.02 18.02 0

32-324000

Petroleum and coal products

45.9 45.7 -.2 36.37 35.70 -.67

32-325000

Chemicals

43 43 0 21.47 21.47 0

32-326000

Plastics and rubber products

41.9 41.9 0 16.36 16.36 0

32-329000

Miscellaneous nondurable goods manufacturing

40.3 40.3 0 18.72 18.72 0

40-000000

Trade, transportation, and utilities

33.6 33.6 0 18.26 18.26 0

41-420000

Wholesale trade

39 39 0 23.22 23.21 -.01

42-000000

Retail trade

29.8 29.8 0 14.34 14.35 .01

43-000000

Transportation and warehousing

38.3 38.4 .1 20.40 20.44 .04

44-220000

Utilities

42 42 0 32.84 32.84 0

50-000000

Information

36.4 36.2 -.2 28.84 28.83 -.01

55-000000

Financial activities

37.3 37.3 0 24.78 24.77 -.01

60-000000

Professional and business services

35.8 35.8 0 24.47 24.55 .08

65-000000

Education and health services

32.1 32 -.1 21.49 21.51 .02

70-000000

Leisure and hospitality

25.5 25.5 0 11.99 11.99 0

80-000000

Other services

31 31 0 18.40 18.50 .10

To Table of Figures

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Vintage data

Due to user interest in versions of CES estimates from original to current publication, CES compiled vintage data tables that display the CES published employment values for a given reference month across time. CES vintage can be found at www.bls.gov/ces/cesvininfo.htm

Three-month moving averages

Effective with the release of January 2015 data, the establishment survey will introduce two new data series: total nonfarm employment, 3-month average change and total private employment, 3-month average change.

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 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 ten 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 nine months 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 nine months following the March benchmark (also referred to as the post benchmark period, see Revisions in the post benchmark period). New net birth/death model estimates also are calculated and applied during post benchmark estimation. The annual sample update is introduced in the November final sample-based estimates, which are released along with the January first preliminary sample-based estimates that coincide with the Benchmark release. The new sample is used for all subsequent estimates.

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Benchmark source material

The principal source of benchmark data for private industries is the Quarterly Census of Employment and Wages (QCEW). The QCEW scope is defined by employment data provided to state employment security agencies by employers covered by state UI laws. BLS uses several other sources to establish benchmarks for the 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 industries not fully covered by the UI scope, such as Non-office insurance sales workers, child daycare workers, Religious organizations, and Private schools and hospitals. Noncovered employment for state and local government hospitals and educational institutions is based on the Annual Survey of Public Employment and Payroll (ASPEP) conducted by the Census Bureau. Noncovered employment data from these sources are available only on a lagged basis. Extrapolation to a current level is accomplished by applying the employment trends from the UI-covered part of the population in these industries to the noncovered part. Universe data for interstate railroads are obtained from the Railroad Retirement Board. More information on calculating noncovered employment in the CES program is available in the CES Technical Notes at www.bls.gov/web/empsit/cestn.htm#NCE.

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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 deaths. However, the timeliest UI universe files available will always be a minimum of six to seven months out of date. The CES survey thus cannot 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 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. To account for this net birth/death portion of total employment, BLS is utilizing an estimation procedure with two components. The first component excludes employment losses from business deaths from sample-based estimation in order to offset the missing employment gains from 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 Autoregressive Integrated Moving Average (ARIMA) time series model designed to estimate the 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 net of births and deaths over the past five years. The net birth/death model component figures are unique to each month and include negative adjustments in some months. Furthermore, these figures exhibit a seasonal pattern similar to the seasonal patterns of the continuing businesses.

Only error from the second component is directly measurable. Error from this component is measured by comparing the actual net of births and deaths from March 2013-14 — once it becomes available — with the model-based estimate. As Table 7 shows, the actual net birth/death for April 2013 to March 2014 was approximately 202,000 above the forecasted amount used in the CES monthly estimates for the time period.

Table 7. Differences between forecasted and actual net birth/death, total private employment, April 2013 – March 2014 (in thousands)
Benchmark 2014 2013 2014 Total
Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar

Actual Net Birth/Death

277 201 129 143 127 -19 164 22 -26 -252 141 64 971

Forecast Net Birth/Death

236 210 140 86 99 -30 159 -11 -12 -307 124 75 769

Difference

41 -9 -11 57 28 11 5 33 -14 55 17 -11 202

Cumulative Difference

41 32 21 78 106 117 122 155 141 196 213 202

To Table of Figures

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Availability of revised data

LABSTAT, the BLS public database, contains all historical employment, hours, and earnings data revised as a result of this benchmark, including both not seasonally adjusted and seasonally adjusted data. The data can be accessed at www.bls.gov/ces/, the CES homepage.

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Seasonal adjustment procedure

For technical information on how seasonal adjustment is performed in the CES program, refer to the Seasonal Adjustment section of the CES Technical Notes, available at www.bls.gov/web/empsit/cestn.htm#section5e. For more information on seasonal adjustment model specifications and special model adjustments, please see the Seasonal Adjustment Model Specification List section of the CES Seasonal Adjustment Files and Documentation page, available at www.bls.gov/web/empsit/cesseasadj.htm#samodel.

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End Notes

1 CES estimates data in two ways: directly and indirectly. Directly estimated data types refer to data types for which estimates are calculated directly from the responding sample. Indirectly estimated data types refer to data types for which estimates are calculated from other directly estimated data types. Average weekly earnings of all employees and indexes of aggregate weekly hours of all employees are examples of indirectly estimated data types. For more information on indirectly estimated data types, see the CES Technical Notes available at www.bls.gov/web/empsit/cestn.htm.

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Table of figures

Tables

Exhibits

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Last Modified Date: April 3, 2015

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