Monthly Labor Review • September 2010 33

Evaluating the 1996-2006 Projections

Ian D. Wyatt Every 2 years the Bureau of Labor 

Statistics (BLS, the Bureau) publishes long-term economic projections. 

In 1997, BLS published the 1996–2006 

projections.1

 These projections are used by 

policymakers, economists, and even students 

making career decisions, and are one of the 

most popular products on the BLS Web site. 

With such a popular product, it is important 

to ask the question, How accurate are these 

projections?

BLS has published numerous articles evaluating its earlier projections.2

 Most past articles focused on a specific part of the projections: the labor force, industry employment, or occupational employment. In 2005, 

two researchers from outside the Bureau (on 

a contract with BLS), H.O. Stekler and Rupin Thomas, wrote an article evaluating the 

accuracy of the Bureau’s 1988–2000 projections and suggested metrics and methods, 

including naïve models, for evaluating future 

projections.3

 Subsequently, BLS decided to 

revamp how it evaluates its own projections 

and convened a team that used Stekler and 

Thomas’ ideas as a starting point when it developed recommendations for future projection evaluations. Following the team’s recommendations, this article evaluates all four 

parts of the projections in a holistic manner 

and attempts to show how problems in earlier parts of the projections process affected 

the later parts. 

Ian D. Wyatt was an 

economist in the BLS 

Office of Occupational 

Statistics and 

Employment Projections. 

Also contributing 

to the article were 

Betty Su, Mitra Toossi, 

Tom DiVincenzo, and 

Rose Woods. Betty Su 

and Mitra Toossi are 

economists in the Office 

of Occupational Statistics 

and Employment 

Projections, and Tom 

DiVincenzo and Rose 

Woods were economists 

in the same office. Email: 

ep-info@bls.gov.

Evaluating the 1996–2006 

employment projections

On the whole, the BLS 1996–2006 employment projections 

outperformed alternative naïve models, but not projecting 

the housing bubble or the rise in oil prices did cause 

some inaccuracies in the projections

The first step in evaluating any projection 

is to compare actual data with projected 

data. Although such a comparison may seem 

simple, revisions to GDP definitions, occupation and industry classification systems, 

and historical data make such a comparison 

quite complex. The first section of the article 

discusses how BLS attempted to match and 

compare projected data, which were created 

on the basis of one set of definitions, classifications systems, and historical data (pre1997 data), with actual data, which were 

created under a different set of definitions 

and classification systems, and were based 

on revised historical data. After discussing 

data comparability, the article will evaluate 

the accuracy of the four parts of the projections: the population and labor force projections, the macroeconomic projections, the 

industry employment projections, and the 

occupational employment projections. The 

metrics used in this article are described in 

the appendix. 

Following Stekler and Thomas’ recommendations and the BLS projection evaluation team’s recommendations, this article 

will not only quantify the accuracy of the 

projections; it will attempt to explain, when 

possible, why differences occurred, and will 

compare the accuracy of the BLS projections 

with the accuracy of naïve models. (See the 

appendix for an explanation of the naïve 

models used in this article.) The compari-
Evaluating the 1996–2006 Projections

34 Monthly Labor Review • September 2010

son with naïve models is necessary because accuracy can 

only be judged through comparisons. Because of a lack 

of comparable projections, naïve models provide the basis 

for comparison. Most of the naïve models employed in 

this article assume that the rate of change over the next 

10 years will equal the rate of change over the previous 

10 years. The section of the article on occupational employment projections describes additional types of naïve 

models employed in that section. 

Data comparability

The 1996–2006 projections, created in 1996 and 1997, 

used 1996 data and the racial, gross domestic product 

(GDP), occupational, and industrial definitions, and occupational and industrial classification systems, used in 

1996. Analyzing the accuracy of economic projections requires comparing projected values with actual data. In the 

case of the 1996–2006 projections, direct comparisons between the 2006 projections and the 2006 actual data were 

more difficult because the aforementioned definitions and 

classification systems changed between 1996 and 2006. In 

addition to those changes, the results of the 2000 Census 

brought into question the accuracy of the 1996 estimates 

of the U.S. population, and the rebasing and revising of 

GDP data altered the historical data (1986–1996) that 

were used to create the projections.

Population. The 2000 Census counted 281.4 million 

residents, 6.8 million more residents than the Census 

Bureau had projected just a year earlier. Subsequent 

analysis suggested the Census Bureau underestimated 

the level of immigration throughout the 1990s.4

 If this 

analysis is correct, the actual 1996 resident population was 

larger, more Hispanic, and more male than the estimated 

resident population used in creating the projections. 

Because young Hispanic men participate in the labor 

force at above-average rates, underestimating immigration 

affected the labor force estimate more than the overall 

population estimate.

Race categories. To better capture and reflect the 

multiracial nature of the U.S. population, the 2000 

Census incorporated changes to race categories. The 2000 

Census, for the first time, allowed respondents to classify 

themselves in more than one racial category. When the 

1996–2006 projections were created, no multiracial race 

category existed and no projections had been made for the 

multiracial population. The new race category reduced the 

accuracy of comparisons of the projected race categories 

(which did not include a multiracial category) with the 

actual race categories (which did include a multiracial 

category). Although the impact of the new multiracial 

category reduced the population estimates for all singlerace categories,5

 the impact was small because the 

multiracial category accounted for just 1.4 percent of the 

total population. 

GDP. Definitional changes between 1996 and 2006 

went far beyond race groups. Every 5 years, the Bureau 

of Economic Analysis publishes comprehensive revisions 

of the National Income and Product Accounts and the 

associated GDP data; these revisions incorporate major 

definitional and classification changes, methodological 

changes, adjustments stemming from the results of the 

most recent economic census and other surveys, and other 

statistical improvements. Since GDP data are time-series 

data, changes not only affect projected levels of GDP, but 

also lead to revisions of historical levels of GDP.

6 GDP data 

revisions led to the average annual growth rate in the decade preceding the projections (1986–1996) to be revised 

from 2.3 percent to 2.9 percent. The 1999 revisions altered 

the total level of GDP and the distribution of GDP among 

its various components.7

In the 1996–2006 projections, real GDP and its components were stated in 1992 chain-weighted dollars. When 

the 2006 evaluation was conducted, they were stated in 

2000 chain-weighted dollars. Although the levels of GDP

cannot be compared without adjustments, the growth rate 

of GDP is directly comparable.

Industrial classification. In 1996, industry data were 

constructed under the Standard Industrial Classification 

(SIC) system. As a general rule, the names and structures 

used in this article follow the SIC system. In 2001, BLS

began collecting and reporting employment data based 

on the North American Industrial Classification System 

(NAICS). The transition to the NAICS was not simply a 

change of definitions and titles of industries; it was a major philosophical change in how businesses were classified 

into industries. Comparable industry data were created by 

converting the NAICS-based 2006 Current Employment 

Statistics data to an SIC basis, by use of the NAICS-toSIC crosswalk; a mix of three-digit and four-digit NAICS 

industries were converted to a mix of two-digit and threedigit SIC industries. Data from these industries were aggregated to create data for industry divisions.8

 The crosswalk was developed from the 2001 establishment data 

that were “dual coded” (recorded under both the old (SIC) 

and the new (NAICS) industry classification systems). 
Monthly Labor Review • September 2010 35

Although the ratios used for the conversion process are 

likely to be accurate for the year 2001 and are the most 

reasonable option for converting data from other years, 

the further one gets from 2001, the more the accuracy of 

the crosswalk is expected to decline. Because of differences due to definitional changes and revisions to the data 

that occurred since the 1996 data were initially published, 

some of the tables in this article contain two sets of actual 

1996 data for industry divisions.9

Occupational classification. Before 1999, Occupational 

Employment Statistics (OES) staffing pattern data were 

collected under an occupational classification system 

unique to the OES program. Starting in 1999 the OES

staffing pattern data were collected under a classification 

system based on the 2000 Standard Occupational Classification (SOC) system. Although BLS staff created an 

occupational crosswalk that matched the old OES occupations to SOC occupations,10 the lack of dual-coded microdata lessened the comparability of old and new occupations and resulted in only about half of the occupations 

projected in 1996 being included in this article.11

The shift to the SOC system resulted not only in mundane definitional changes, but also in some broader, more 

philosophical changes. In 1998, under the older classification system, the OES survey estimated that there were 

8,321,000 managers. In 2006, under the SOC system, 

there were 5,893,000 managers. Though it is possible that 

the much-talked-about flattening of management structures caused this decline, the most likely possibility is that 

the shift to the SOC system’s more restrictive definition 

of managers and first-line supervisors caused the decline.

Although all of the changes to the definitions and classification systems underlying the relevant economic data 

made it more difficult to analyze the accuracy of the 

1996–2006 projections, careful adjustments to the data 

made it possible to conduct such an analysis. However, 

the adjustments to the data were not able to completely 

eliminate comparability issues. 

The labor force

BLS begins its economic projections by projecting the size 

of the labor force, which requires calculating the workingage resident population and the labor force participation 

rate. The Census Bureau projects the working-age civilian 

noninstitutional population (CNIP)

12 of the United States 

by detailed age, sex, race, and ethnic categories. BLS projects the labor force participation rate for these same categories. Multiplying the CNIP projections by the respective labor force participation rates provides the labor force 

projections for 136 age, sex, race, and ethnic categories. 

The total labor force projection is the sum of the projections of the 136 detailed groups. Some of the projected 

and actual working-age resident population statistics are 

presented in table 1. Labor force participation rates (actual and projected) are presented in table 2, labor force 

levels in table 3. 

BLS projected the labor force to be 148.9 million in 

2006, and the actual labor force in 2006 was 151.4 million, an underprojection of 2.6 million, or 1.7 percent. The 

first statistic that goes into calculating the size of the labor 

force, the CNIP, was underprojected. The Census Bureau 

projected the 2006 CNIP to be 221.2 million, and the actual CNIP was 228.8 million, an underprojection of 7.6 

million, or 3.3 percent. The second statistic that goes into 

calculating the size of the labor force, the labor force participation rate, was overprojected. The projected participation rate was 67.6 percent, and the actual rate in 2006 

was 66.2 percent, an overprojection of 1.4 percentage 

points. The magnitude of the underprojection of the CNIP

was too large to be completely cancelled out, and, consequently, the labor force was underprojected. If the size of 

the CNIP had been perfectly projected, the overprojected 

labor force participation rate would have resulted in the 

labor force being overprojected by 3.3 million people.

The main reason that the Census Bureau underprojected the population was that it underprojected immigration. During the 1990s and 2000s immigrants tended 

to be young, Hispanic men, so it is unsurprising that the 

differences for men were larger than the differences for 

women,13 the differences for Hispanics were larger than 

for non-Hispanics, and the differences for 16- to 24-yearolds were larger than those for older age groups. Although 

both men and women were underprojected, the underprojection for men, 4.3 million (3.9 percent), was larger than 

that for women, 3.3 million (2.8 percent).14 (See table 1.) 

To a small extent (estimated to be about 0.1 or 0.2 percent) the labor force participation rate was intentionally 

overprojected to offset what BLS thought to be an underestimation of immigration by the Census Bureau.15

Overprojecting the labor force participation rate to adjust 

for an underprojected CNIP should have produced a more 

accurate total labor force figure. However, the size of the 

adjustment to the participation rate was quite small, and 

the adjustment does not fully explain the 1.0 percentage 

point overprojection of the participation rate.

Sex groups. When the labor force participation rates 

are broken down by sex, it becomes apparent that the 
Evaluating the 1996–2006 Projections

36 Monthly Labor Review • September 2010

Table 1. Civilian noninstitutional population, by age, sex, race, and ethnicity, 1996 and 2006 (projected and actual)

Labor force group

Thousands of people Percent change Numerical 

error

Percent 

error Share of population

1996 2006 1996–06 2006 2006

Actual Projected Actual Projected Actual Projected versus actual Projected Actual

Total, 16 years and older.... 200,591 221,191 228,815 10.3 14.1 –7,624 –3.3 100.0 100.0 

16 to 24................................................. 32,343 38,106 36,943 17.8 14.2 1,163 3.1 17.2 16.1 

 16 to 19............................................... 14,934 17,245 16,678 15.5 11.7 567 3.4 7.8 7.3 

 20 to 24 .............................................. 17,409 20,862 20,265 19.8 16.4 597 2.9 9.4 8.9 

25 to 54 ................................................ 115,506 119,500 124,884 3.5 8.1 –5,384 –4.3 54.0 54.6 

 25 to 34............................................... 40,252 36,370 39,230 –9.6 –2.5 –2,860 –7.3 16.4 17.1 

 35 to 44............................................... 43,086 41,550 42,753 –3.6 –.8 –1,203 –2.8 18.8 18.7 

 45 to 54............................................... 32,167 41,580 42,901 29.3 33.4 –1,321 –3.1 18.8 18.7 

55 and older........................................ 52,742 63,584 66,988 20.6 27.0 –3,404 –5.1 28.7 29.3 

 55 to 64 ............................................. 20,990 29,956 31,375 42.7 49.5 –1,419 –4.5 13.5 13.7 

 65 to 74.............................................. 18,244 18,140 18,685 –0.6 2.4 –545 –2.9 8.2 8.2 

 75 and older...................................... 13,507 15,488 16,928 14.7 25.3 –1,440 –8.5 7.0 7.4 

Men, 16 and older............................. 96,206 106,267 110,605 10.5 15.0 –4,338 –3.9 48.0 48.3 

 16 to 24.............................................. 16,210 19,518 18,650 20.4 15.1 868 4.7 8.8 8.2 

 16 to 19 ............................................ 7,600 8,675 8,459 14.1 11.3 216 2.6 3.9 3.7 

 20 to 24............................................. 8,611 10,844 10,191 25.9 18.3 653 6.4 4.9 4.5 

 25 to 54 ............................................. 56,671 58,290 61,640 2.9 8.8 –3,350 –5.4 26.4 26.9 

 25 to 34............................................. 19,775 17,839 19,568 –9.8 –1.0 –1,729 –8.8 8.1 8.6 

 35 to 44............................................. 21,222 20,392 21,082 –3.9 –.7 –690 –3.3 9.2 9.2 

 45 to 54............................................. 15,674 20,058 20,991 28.0 33.9 –933 –4.4 9.1 9.2 

 55 and older...................................... 23,324 28,459 30,315 22.0 30.0 –1,856 –6.1 12.9 13.2 

 55 to 64............................................ 9,997 14,131 15,095 41.4 51.0 –964 –6.4 6.4 6.6 

 65 to 74............................................. 8,194 8,361 8,574 2.0 4.6 –213 –2.5 3.8 3.7 

 75 and older.................................... 5,134 5,967 6,646 16.2 29.5 –679 –10.2 2.7 2.9 

Women, 16 and older....................... 104,385 114,924 118,210 10.1 13.2 –3,286 –2.8 52.0 51.7 

 16 to 24............................................... 16,132 18,588 18,292 15.2 13.4 296 1.6 8.4 8.0 

 16 to 19 ........................................... 7,335 8,570 8,218 16.8 12.0 352 4.3 3.9 3.6 

 20 to 24 ........................................... 8,798 10,018 10,074 13.9 14.5 –56 –.6 4.5 4.4 

 25 to 54.............................................. 58,835 61,210 63,243 4.0 7.5 –2,033 –3.2 27.7 27.6 

 25 to 34............................................ 20,477 18,531 19,662 –9.5 –4.0 –1,131 –5.8 8.4 8.6 

 35 to 44............................................ 21,865 21,158 21,671 –3.2 –.9 –513 –2.4 9.6 9.5 

 45 to 54............................................ 16,493 21,521 21,910 30.5 32.8 –389 –1.8 9.7 9.6 

 55 and older...................................... 29,417 35,125 36,675 19.4 24.7 –1,550 –4.2 15.9 16.0 

 55 to 64 ........................................... 10,993 15,825 16,280 44.0 48.1 –455 –2.8 7.2 7.1 

 65 to 74............................................ 10,050 9,780 10,111 –2.7 .6 –331 –3.3 4.4 4.4 

 75 and older.................................... 8,374 9,521 10,284 13.7 22.8 –763 –7.4 4.3 4.5 

Race:

White...................................................... 168,317 182,147 186,264 8.2 10.7 –4,117 –2.2 82.3 81.4 

 Men...................................................... 81,489 88,893 91,021 9.1 11.7 –2,128 –2.3 40.2 39.8 

 Women................................................ 86,828 93,255 95,243 7.4 9.7 –1,988 –2.1 42.2 41.6 

Black....................................................... 23,604 26,548 27,007 12.5 14.4 –459 –1.7 12.0 11.8 

 Men...................................................... 10,575 11,483 12,130 8.6 14.7 –647 –5.3 5.2 5.3 

 Women................................................ 13,029 15,064 14,877 15.6 14.2 187 1.3 6.8 6.5 

Asian and other.................................. 8,671 12,496 12,315 44.1 42.0 181 1.5 5.6 5.4 

 Men...................................................... 4,142 5,891 5,880 42.2 42.0 11 .2 2.7 2.6 

 Women................................................ 4,530 6,605 6,435 45.8 42.1 170 2.6 3.0 2.8 

Multiple race group......................... ... ... 3,229 ... ... ... ... ... 1.4 

 Men...................................................... ... ... 1,574 ... ... ... ... ... .7 

 Women................................................ ... ... 1,655 ... ... ... ... ... .7 
Monthly Labor Review • September 2010 37

Ethnicity:

Hispanic origin.................................. 19,213 26,459 30,103 37.7 56.7 –3,644 –12.1 12.0 13.2 

 Men...................................................... 9,604 13,270 15,473 38.2 61.1 –2,203 –14.2 6.0 6.8 

 Women................................................ 9,610 13,189 14,630 37.2 52.2 –1,441 –9.8 6.0 6.4 

White non-Hispanic origin............. 150,026 158,638 158,308 5.7 5.5 330 .2 71.7 69.2 

 Men...................................................... 72,318 77,013 76,597 6.5 5.9 416 .5 34.8 33.5 

 Women................................................ 77,708 81,625 81,711 5.0 5.2 –86 –.1 36.9 35.7 

Table 1. Continued—Civilian noninstitutional population, by age, sex, race, and ethnicity, 1996 and 2006 

 (projected and actual)

Labor force group

Thousands of people Percent change Numerical 

error

Percent 

error Share of population

1996 2006 1996–06 2006 2006

Actual Projected Actual Projected Actual Projected versus actual Projected Actual

overprojection of the overall participation rate resulted 

mostly from an overprojected female participation rate. 

The 2006 participation rate for men, 73.5 percent, was 

only one-tenth of a percentage point below the projected 

rate of 73.6 percent. The female labor force participation 

rate rose during the 1960s, 1970s, and 1980s, and was the 

main factor increasing the overall labor force participation 

rate. The female labor force participation rate grew from 

55.3 percent in 1986 to 59.3 percent in 1996. It peaked 

in 1999 at 60.0 percent and then started declining 

gradually. Although BLS had anticipated slowing growth 

in the female labor force participation rate, it had failed 

to project that the trend would actually reverse and the 

rate would decline. On the basis of the upward historical 

trend in the women’s labor force participation rate, BLS

had projected the female labor force participation rate to 

continue increasing and to reach 61.4 percent in 2006. 

The actual participation rate in 2006 was 59.4 percent, an 

overprojection of 2.0 percentage points.

With the female CNIP underprojected by 3.3 million 

and the female labor force participation rate overprojected 

by 2.0 percentage points, the two differences largely offset each other and resulted in an overprojection of only 

400,000 in the female labor force. The 2006 female labor 

force, projected to be 70.6 million, was actually 70.2 million. With the male CNIP underprojected by 4.3 million 

(a larger error than that of the female population) and the 

male participation rate projected to within one-tenth of 

a percentage point of the true value, there was no large 

overprojection to offset the underprojected CNIP, which 

resulted in an underprojected male labor force. The 2006 

male labor force, projected to be 78.2 million, was actually 

81.3 million. 

Race groups. The CNIP for Whites was underprojected 

by 4.1 million. Whites, projected to make up 82.3 percent 

of the 2006 CNIP, made up 81.4 percent in the actual 2006 

data. The white labor force participation rate, projected to 

be 68.1 percent, was actually 66.3 percent. The difference 

in the participation rate between the projection and reality was concentrated in the white female population. The 

underprojected white population and overprojected white 

labor force participation rate largely offset each other and 

resulted in a projected white labor force of 123.6 million, 

compared with the actual white labor force of 123.8 million.

The black CNIP was underprojected by less than half a 

million. Blacks, projected to be 12.0 percent of the CNIP, 

were actually 11.8 percent. The black labor force participation rate was overprojected, but was more accurately 

projected than the white participation rate. The projected 

2006 black participation rate was 64.9 percent, and the 

actual participation rate was 63.8 percent. The underprojected population and the overprojected participation rate 

resulted in the black labor force being underprojected by 

fewer than 100,000 people. The projected 2006 black labor force was 17.2 million, and the actual 2006 black labor 

force was 17.3 million.

The “Asians and others” CNIP was overprojected by 

fewer than 200,000 people. The Asians and others group 

includes Asians, Native Americans and Native Alaskans, 

and Native Hawaiians and other Pacific Islanders.16 The 

2006 Asian and others CNIP, projected to be 12.5 million, 

actually was 12.3 million. Asians and others, projected to 

make up 5.6 percent of the CNIP in 2006, actually made 

up 5.4 percent. The 2006 Asians and others labor force 

participation rate was projected to be 65.7 percent, and 

the actual rate was 66.2. The overprojected population and 

the underprojected labor force participation rate resulted 

in the 2006 Asian and others labor force being underprojected by about 100,000 people. The projected 2006 Asian 

and others labor force was 8.0 million, and the actual la-
Evaluating the 1996–2006 Projections

38 Monthly Labor Review • September 2010

Table 2. Civilian labor force participation rates, by age, sex, race, and ethnicity, 1996 and 2006 (projected and actual)

Labor force group

1996 2006

Numerical change Numerical 

difference

Percent 

difference

1996–06 2006

Actual Projected Actual Projected Actual Projected verses actual

Total, 16 years and older......................... 66.8 67.6 66.2 0.8 –0.6 1.4 2.1

16 to 24...................................................................... 65.5 62.4 60.6 –3.1 –4.9 1.8 3.0

 16 to 19 ................................................................... 52.3 51.8 43.7 –.5 –8.6 8.1 18.5

 20 to 24.................................................................... 76.8 74.3 74.6 –2.5 –2.2 –.3 –.4

25 to 54 ..................................................................... 83.8 85.5 82.9 1.7 –.9 2.6 3.1

 25 to 34.................................................................... 84.1 84.8 83.0 .7 –1.1 1.8 2.2

 35 to 44.................................................................... 84.8 85.3 83.8 .5 –1.0 1.5 1.8

 45 to 54.................................................................... 82.1 84.6 81.9 2.5 –.2 2.7 3.3

55 and older............................................................. 30.3 36.8 38.0 6.5 7.7 –1.2 –3.2

 55 to 64 ................................................................... 57.9 62.6 63.7 4.7 5.8 –1.1 –1.7

 65 to 74.................................................................... 17.5 18.2 23.6 .7 6.1 –5.4 –22.9

 75 and older........................................................... 4.7 5.9 6.4 1.2 1.7 –.5 –7.8

Men, 16 and older................................................... 74.9 73.6 73.5 –1.3 –1.4 .1 .1

 16 to 24..................................................................... 68.8 65.8 63.3 –3.0 –5.5 2.5 3.9

 16 to 19.................................................................. 53.2 52.5 43.7 –.7 –9.5 8.8 20.1

 20 to 24................................................................... 82.5 76.5 79.6 –6.0 –2.9 –3.1 –3.9

 25 to 54 .................................................................... 91.8 90.8 90.6 –1.0 –1.2 .2 .2

 25 to 34.................................................................. 93.2 92.3 91.7 –.9 –1.5 .6 .7

 35 to 44.................................................................. 92.4 90.6 92.1 –1.8 –.3 –1.5 –1.6

 45 to 54.................................................................. 89.1 89.5 88.1 .4 –1.0 1.4 1.6

 55 and older........................................................... 38.3 43.8 44.9 5.5 6.6 –1.1 –2.4

 55 to 64 ................................................................. 67.0 70.2 69.6 3.2 2.6 .6 .9

 65 to 74.................................................................. 22.9 23.9 28.8 1.0 5.9 –4.9 –17.0

 75 and older......................................................... 7.3 9.2 9.5 1.9 2.2 –.3 –3.2

Women, 16 and older............................................. 59.3 61.4 59.4 2.1 .1 2.0 3.4

 16 to 24.................................................................... 62.2 62.2 57.9 .0 –4.3 4.3 7.4

 16 to 19.................................................................. 51.3 51.0 43.7 –.3 –7.6 7.3 16.7

 20 to 24 ................................................................. 71.3 71.8 69.5 .5 –1.8 2.3 3.3

 25 to 54 ................................................................... 76.1 79.3 75.5 3.2 –.6 3.8 5.0

 25 to 34.................................................................. 75.2 77.6 74.4 2.4 –.8 3.2 4.3

 35 to 44.................................................................. 77.5 80.2 75.9 2.7 –1.6 4.3 5.7

 45 to 54.................................................................. 75.4 79.9 76.0 4.5 .6 3.9 5.1

 55 and older........................................................... 23.9 29.9 32.3 6.0 8.4 –2.4 –7.4

 55 to 64 ................................................................. 49.6 55.8 58.2 6.2 8.6 –2.4 –4.1

 65 to 74.................................................................. 13.1 13.3 19.2 .2 6.1 –5.9 –30.7

 75 and older......................................................... 3.1 3.9 4.4 .8 1.3 –.5 –11.4

Race:

White.......................................................................... 67.2 68.1 66.3 .9 –.9 1.8 2.7

 Men.......................................................................... 75.8 74.3 74.1 –1.5 –1.7 .2 .3

 Women................................................................... 59.1 62.0 58.9 2.9 –.2 3.1 5.3

Black 64.1 64.9 63.8 .8 –.3 1.1 1.7

 Men.......................................................................... 68.7 69.6 66.7 .9 –2.0 2.9 4.3

Women................................................................... 60.4 61.3 61.5 .9 1.1 –.2 –.3

Asian and other....................................................... 65.8 65.7 66.2 –.1 .4 –.5 –.7

Men.......................................................................... 73.4 71.6 74.4 –1.8 1.0 –2.8 –3.8

Women................................................................... 58.8 60.1 58.7 1.3 –.1 1.4 2.4

Multiple race group............................................... ... ... 65.9 ... ... ... ...

Men.......................................................................... ... ... 72.3 ... ... ... ...

Women................................................................... ... ... 59.7 ... ... ... ...
Monthly Labor Review • September 2010 39

bor force was 8.2 million. When adjusted for rounding, 

the difference between the projected and actual levels was 

much closer to 100,000 than 200,000.

Since the multiple race group did not exist in 1996, no 

projections were made for the group. In 2006, the multiple 

race group accounted for 3.2 million people, or 1.4 percent of the CNIP. The general overprojection of shares of 

the CNIP for other race groups can be attributed to some 

people reclassifying themselves from being of a single race 

to being a member of the new multiple race group. Within the labor force, the multiple race group accounted for 

2.1 million people, or 1.4 percent of the labor force. If the 

multiple race category did not exist, the members of this 

group would have been assigned to one of the other three 

race categories and would have increased the actual labor 

force and CNIP numbers for those groups.

Ethnic groups. In BLS statistics, Hispanics are considered to be an ethnic, not racial, group. Hispanics can be 

of any race, but more than 90 percent classify themselves 

as white when they are asked to choose among the race 

groups in the tables. Thus, the differences associated with 

the projection of Hispanics affect mostly the white race 

category. Estimates of Hispanics were revised more after 

the 2000 Census than estimates of any other group. In the 

1996–2006 projections, Hispanics were underprojected by 

3.6 million, or 12.1 percent. The 2006 Hispanic CNIP was 

projected to be 26.5 million, and the actual level was 30.1 

million. Since Hispanics have high immigration rates and 

constitute the majority of undocumented immigrants,17

they are a difficult group to project accurately, and they 

tend to be underprojected. Hispanic labor force participation also was underprojected: the actual 2006 participation rate, 68.6 percent, was a full 3.0 percentage points 

above the projected 65.7 percent rate. With both the CNIP 

Table 2. Continued—Civilian labor force participation rates, by age, sex, race, and ethnicity, 1996 and 2006 (projected 

 and actual)

Labor force group

1996 2006

Numerical change Numerical 

difference

Percent 

difference

1996–06 2006

Actual Projected Actual Projected Actual Projected verses actual

Ethnicity

Hispanic origin......................................................... 66.5 65.7 68.6 –0.8 2.1 –2.9 –4.2

Men........................................................................... 79.6 77.1 80.4 –2.5 .8 –3.3 –4.1

Women..................................................................... 53.4 57.2 56.1 3.8 2.7 1.1 2.0

White non-Hispanic origin................................. 67.3 68.7 65.9 1.4 –1.4 2.8 4.2

Men........................................................................... 75.3 74.1 73.0 –1.2 –2.3 1.1 1.5

Women..................................................................... 59.8 63.7 59.3 3.9 –.5 4.4 7.4

and labor force participation rate for Hispanics underprojected, the Hispanic labor force also was underprojected. 

The projected size of the 2006 Hispanic labor force was 

17.4 million, and the actual number was 20.7 million. 

The white non-Hispanic CNIP was overprojected by 

about 300,000, or 0.2 percent. The projected CNIP was 

158.6 million, and the actual CNIP was 158.3 million. The 

problems in projecting the white CNIP can be attributed 

to underprojecting the white Hispanic population. The 

2006 white non-Hispanic labor force participation rate, 

projected to be 68.7 percent, was actually 65.9 percent. 

The overprojected participation rate and fairly accurately 

projected CNIP resulted in the 2006 white non-Hispanic 

labor force projection of 108.2 million being above the 

actual level of 104.6 million.

Naïve model. The BLS population and labor force 

participation rate projections outperformed those of the 

naïve model (which assumed that the historical rates of 

growth would continue). The results presented in table 4 

show that the BLS labor force participation rate and labor 

force projection outperformed the naïve model in 7 out of 

11 (with one tie) and 8 out of 11 categories, respectively.

Macroeconomic projections

The BLS projections of the aggregate economy are based 

on a long-term view of the U.S. economy that assumes 

a long-run full-employment economy. The 1996–2006 

projections created a reasonable model of what the 

economy might look like in 2006. Different assumptions 

about key variables can lead to different projections for 

the macroeconomy. The GDP projection is based on 

projections of the supply of labor and on assumptions 

affecting energy, taxes, Federal expenditures and grants, 
Evaluating the 1996–2006 Projections

40 Monthly Labor Review • September 2010

Table 3. Civilian labor force, by age, sex, race, and ethnicity, 1996 and 2006 (projected and actual)

Labor force group

Thousands of people Percent change Numerical 

difference

Percent 

difference Share of labor force

1996 2006 1996–06 2006 2006

Actual Projected Actual Projected Actual Projected verses actual Projected Actual

Total, 16 years and older... 133,943 148,847 151,428 11.1 13.1 –2,581 –1.7 100.0 100.0 

16 to 24................................................ 21,183 24,418 22,394 15.3 5.7 2,024 9.0 16.4 14.8 

 16 to 19............................................... 7,806 8,924 7,281 14.3 –6.7 1,643 22.6 6.0 4.8 

 20 to 24............................................... 13,377 15,494 15,113 15.8 13.0 381 2.5 10.4 10.0 

25 to 54................................................ 96,786 101,454 103,566 4.8 7.0 –2,112 –2.0 68.2 68.4 

 25 to 34............................................... 33,833 30,842 32,573 –8.8 –3.7 –1,731 –5.3 20.7 21.5 

 35 to 44............................................... 36,556 35,455 35,848 –3.0 –1.7 –393 –1.1 23.8 23.7 

 45 to 54............................................... 26,397 35,157 35,146 33.2 33.1 11 .0 23.6 23.2 

55 and older....................................... 15,974 22,974 25,468 43.8 59.4 –2,494 –9.8 15.4 16.8 

 55 to 64............................................... 12,146 18,753 19,984 54.4 64.5 –1,231 –6.2 12.6 13.2 

 65 to 74............................................... 3,194 3,300 4,404 3.3 37.9 –1,104 –25.1 2.2 2.9 

 75 and older...................................... 634 921 1,080 45.3 70.3 –159 –14.7 .6 .7 

Men, 16 and older............................. 72,087 78,226 81,255 8.5 12.7 –3,029 –3.7 52.6 53.7 

 16 to 24.............................................. 11,147 12,848 11,810 15.3 5.9 1,038 8.8 8.6 7.8 

 16 to 19 ............................................ 4,043 4,551 3,693 12.6 –8.7 858 23.2 3.1 2.4 

 20 to 24............................................. 7,104 8,297 8,116 16.8 14.2 181 2.2 5.6 5.4 

 25 to 54.............................................. 51,999 52,908 55,840 1.7 7.4 –2,932 –5.3 35.5 36.9 

 25 to 34............................................. 18,431 16,469 17,944 –10.6 –2.6 –1,475 –8.2 11.1 11.8 

 35 to 44............................................ 19,602 18,478 19,407 –5.7 –1.0 –929 –4.8 12.4 12.8 

 45 to 54............................................. 13,967 17,961 18,489 28.6 32.4 –528 –2.9 12.1 12.2 

 55 and older...................................... 8,941 12,470 13,605 39.5 52.2 –1,135 –8.3 8.4 9.0 

 55 to 64............................................. 6,693 9,919 10,509 48.2 57.0 –590 –5.6 6.7 6.9 

 65 to 74............................................ 1,872 1,999 2,466 6.8 31.7 –467 –18.9 1.3 1.6 

 75 and older...................................... 375 552 630 47.2 68.0 –78 –12.4 .4 .4 

Women, 16 and older....................... 61,857 70,620 70,173 14.2 13.4 447 .6 47.4 46.3 

 16 to 24.............................................. 10,036 11,570 10,584 15.3 5.5 986 9.3 7.8 7.0 

 16 to 19 ........................................... 3,763 4,373 3,588 16.2 –4.7 785 21.9 2.9 2.4 

 20 to 24............................................ 6,273 7,197 6,997 14.7 11.5 200 2.9 4.8 4.6 

 25 to 54 ............................................. 44,787 48,546 47,726 8.4 6.6 820 1.7 32.6 31.5 

 25 to 34............................................ 15,403 14,373 14,628 –6.7 –5.0 –255 –1.7 9.7 9.7 

 35 to 44............................................ 16,954 16,977 16,441 .1 –3.0 536 3.3 11.4 10.9 

 45 to 54............................................ 12,430 17,196 16,656 38.3 34.0 540 3.2 11.6 11.0 

 55 and older...................................... 7,033 10,504 11,863 25.6 68.7 –1,359 –11.5 7.1 7.8 

 55 to 64 ........................................... 5,452 8,834 9,475 62.0 73.8 –641 –6.8 5.9 6.3 

 65 to 74............................................ 1,321 1,301 1,937 –1.5 46.6 –636 –32.8 .9 1.3 

 75 and older.................................... 260 369 451 41.9 73.5 –82 –18.2 .2 .3 

Race:

White...................................................... 113,108 123,581 123,834 9.3 9.5 –253 –.2 83.0 81.8 

 Men..................................................... 61,783 66,008 67,613 6.8 10.3 –1,605 –2.4 44.3 44.7 

 Women............................................... 51,325 57,572 56,221 12.2 9.5 1,351 2.4 38.7 37.1 

Black...................................................... 15,134 17,225 17,314 13.8 14.4 –89 –.5 11.6 11.4 

 Men..................................................... 7,264 7,996 8,128 10.1 11.9 –132 –1.6 5.4 5.4 

 Women............................................... 7,869 9,229 9,186 17.3 16.7 43 .5 6.2 6.1 

Asian and other................................. 5,703 8,041 8,152 41.0 18.0 –111 –1.4 5.4 5.4 

 Men..................................................... 3,039 4,222 4,375 38.9 19.2 –153 –3.5 2.8 2.9 

 Women.............................................. 2,664 3,818 3,777 43.3 16.6 41 1.1 2.6 2.5 

Multiple race group........................ ... ... 2,127 ... ... ... ... ... 1.4 

 Men..................................................... ... ... 1,138 ... ... ... ... ... .8 

 Women............................................... ... ... 989 ... ... ... ... ... .7 

Ethnicity:

Hispanic origin................................... 12,774 17,401 20,694 36.2 62.0 –3,293 –15.9 11.7 13.7 

 Men...................................................... 7,646 10,235 12,488 33.9 63.3 –2,253 –18.0 6.9 8.2 

 Women................................................ 5,128 7,166 8,206 39.7 60.0 –1,040 –12.7 4.8 5.4 
Monthly Labor Review • September 2010 41

and other transfer payments. 

The key general assumptions in the projections are 

consistent with a long-term focus: there will be no major 

wars, natural disasters, or oil embargoes, and the long-term 

horizon will not change drastically because short-term 

fluctuations tend to smooth out substantially over the long 

term. Although these assumptions may seem unrealistic, 

projecting shocks is impossible, and therefore it is more 

reasonable to build a projection without them. Part of why 

it is reasonable to build a model without projecting shocks 

is that, over the long run, despite large fluctuations, the 

economy tends to regress to the typical long-run trend. 

In the end, the 1996–2006 period did see a number of 

White non-Hispanic origin............ 100,915 108,166 104,629 7.2 3.7 3,537 3.4 72.7 69.1 

 Men...................................................... 54,451 56,856 55,953 4.4 2.8 903 1.6 38.2 37.0 

 Women................................................ 46,464 51,310 48,676 10.4 4.8 2,634 5.4 34.5 32.1 

Table 3. Continued—Civilian labor force, by age, sex, race, and ethnicity, 1996 and 2006 (projected and actual)

Labor force group

Thousands of people Percent change Numerical 

difference

Percent 

difference Share of labor force

1996 2006 1996–06 2006 2006

Actual Projected Actual Projected Actual Projected verses actual Projected Actual

Table 4. Civilian labor force: projected, actual, and naïve model, 2006

Group Projected Actual Naïve model Actual minus 

naïve

Actual minus 

projected

Which model 

performed better?

Civilian labor force participation rates

Total, 16 years and older......................................... 67.6 66.2 68.3 –2.1 –1.4 BLS

16 to 24 years.................................................................. 62.4 60.6 62.5 –1.9 –1.8 BLS

25 to 54 years.................................................................. 85.5 82.9 85.6 –2.7 –2.6 BLS

55 years and older......................................................... 36.8 38.0 30.5 7.5 1.2 BLS

Men..................................................................................... 73.6 73.5 73.5 0.0 –0.1 Naïve

Women.............................................................................. 61.4 59.4 63.6 –4.2 –2.0 BLS

One race:

 White................................................................................ 68.1 66.3 68.9 –2.6 –1.8 BLS

 Black................................................................................. 64.9 63.8 64.9 –1.1 –1.1 Tie

 Asian and other........................................................... 65.7 66.2 66.1 .1 .5 Naïve

Hispanic origin............................................................... 65.7 68.6 67.6 1.0 2.9 Naïve

 White non-Hispanic................................................... 68.7 65.9 69.1 –3.2 –2.8 BLS

Civilian labor force levels

Total, 16 years and older.......................................... 148,847 151,428 152,254 –826 2,581 Naïve

16 to 24 years................................................................... 24,418 22,394 19,203 3,191 –2,024 BLS

25 to 54 years................................................................... 101,454 103,566 117,737 –14,171 2,112 BLS

55 years and older.......................................................... 22,974 25,468 17,121 8,347 2,494 BLS

Men...................................................................................... 78,226 81,255 79,431 1,824 3,029 Naïve

Women............................................................................... 70,620 70,173 73,003 –2,830 –447 BLS

One race:

 White.................................................................................. 123,581 123,834 125,671 –1,837 253 BLS

 Black.................................................................................. 17,225 17,314 18,100 –786 89 BLS

 Asian and other............................................................. 8,041 8,152 9,648 –1,496 111 BLS

Hispanic origin................................................................. 17,401 20,694 20,205 489 3,293 Naïve

 White non-Hispanic..................................................... 108,166 104,629 108,309 –3,680 –3,537 BLS

major events that changed the economy: the attacks of 

September 11th, the wars in Iraq and Afghanistan, the 

dot-com and housing bubbles, and a sharp runup in oil 

prices.

Some of the assumptions built into the model are 

major economic factors such as demographics, fiscal 

policy, monetary policy, productivity growth, and the 

fluctuations of the unemployment rate: they affect the 

long-term projections of the value of GDP, the makeup of 

final demand, and the level of employment necessary to 

produce that GDP.

18

Demographics in general and the size of the labor force 

in particular are the most important elements in deter-
Evaluating the 1996–2006 Projections

42 Monthly Labor Review • September 2010

mining the economy’s potential output. A sensitivity 

analysis of exogenous and endogenous variables in the 

macro model points to the importance of the demographic factors in determining long-run levels of GDP.

19 As previously discussed, BLS underprojected the growth of the 

labor force by 1.7 percent, which consequently reduced 

the BLS projection of GDP. An article that accompanied 

the original publication of the 1996–2006 projections discussed the impact of underprojecting labor force growth: 

“A 0.8-percent increase in GDP results from a 1.0-percent 

increase in the labor force.”20 According to that relationship, if BLS had not underprojected labor force growth, 

the projected average annual growth rate of GDP would 

have been 2.3 percent, higher than the originally projected 2.1 percent growth rate. The major demographic 

projections and other key macroeconomic projections are 

compared with actual results in table 5.

Productivity projections are partly based on assumptions 

and partly based on the results of the model. From 1996 

through 2004, productivity grew faster than it did during 

the 1980s and early 1990s. From 2001 to 2004, productivity growth averaged 3.5 percent annually. Although the 

Table 5. Major economic variables, actual and projected, 2006 

Economic variable

2006 2006 Average annual rate of change, 

1996–2006

Actual Projected

Difference 

Percent Level Actual Projected Difference

[In millions]

Population, including overseas armed forces....................... 299.1 288.7 –3.5 –10.4 1.1 0.8 –0.3

Population, aged 16 and older.................................................... 228.8 225.5 –1.4 –3.3 1.3 1.0 –.3

Population, aged 65 and older.................................................... 37.3 36.6 –1.9 –0.7 .9 .8 –.1

Civilian labor force........................................................................... 151.4 148.8 –1.7 –2.6 1.2 1.1 –.1

Unemployment rate (in percent)................................................ 4.6 5.4 17.4 .8 –1.5 –.1 1.4

Household employment................................................................ 144.4 140.9 –2.4 –3.5 1.3 1.1 –.2

Nonfarm payroll employment..................................................... 136.2 137.3 0.8 1.1 1.3 1.4 .1

[In billions]

Nominal disposable personal income (DPI)................................. 9,640.7 8,997.1 –6.7 –643.6 5.4 4.9 –.5

Real DPI (in chained 2000 dollars for the actual statistics

and chained 1992 dollars for the projected statistics)... 8,407.0 6,154.3 ... ... 3.3 1.9 –1.4

Real DPI per capita (chained 2000 dollars for actual and

chained 1992 dollars for projected)...................................... 28,134.0 21,317.9 ... ... 1.1 1.1 .0

Federal deficit (nominal)............................................................... –201.1 –.8 –99.6 200.3 ... ... ...

Federal deficit as a percent of nominal GDP........................... –1.5 –.0 –100.0 1.5 ... ... ...

Net exports (chained 2000 dollars for actual and

chained 1992 dollars for projected)..................................... –615.7 –63.8 ... ... ... ... ...

 Merchandise trade balance......................................................... –720.3 –237.1 ... ... ... ... ...

 Services trade balance.................................................................. 102.6 178.2 ... ... ... ... ...

Federal funds rate (in percent).................................................... 5.0 4.3 ... –.7 ... ... ...

Price of imported crude oil (dollars per barrel)..................... 58.9 27.0 –54.2 –31.9 11.1 2.8 –8.3

Savings rate (in percent).............................................................. .7 3.1 ... 2.4 ... ... ...

Nonfarm labor productivity (index)........................................... 1.4 1.1 –18.6 –.3 2.6 1.2 –1.4

SOURCE: 1996–2006 projections data are from BLS; actual 2006 data are from the Bureau of Economic Analysis.

contribution of productivity to the growth of the overall 

economy decreased in 2005 and 2006, the actual average 

annual 2.6 percent rate of productivity growth over the 

1996–2006 period was more than double the projected 

rate of 1.2 percent.21

A full-employment economy is a key assumption in the 

model. With persistently low unemployment and inflation through much of the 1996–2006 period, the actual 

level of unemployment associated with full employment 

became widely debated. The unemployment rate in the 

1996–2006 period twice dipped to levels unseen since the 

late 1960s. (See chart 1 for a graphical representation of 

the unemployment rate from 1960 to 2006.) When the 

annual unemployment rate data for the 1960–2006 period 

are examined, it can be seen that 4 of the 10 years with 

the lowest annual unemployment rate fall within the period in question. In 2006, the unemployment rate was 4.6 

percent, well below BLS’ assumption of full employment 

being 5.4 percent. (See table 5.)

Another assumption in the economic projections is that 

there would not be an oil embargo. Although there were 

no oil embargoes during the 1996–2006 period, the in-
Monthly Labor Review • September 2010 43

Chart 1. Average annual unemployment rate, 1960–2006

 1960 1970 1980 1990 2000 2006

Percent

Projection period

shaded

Projection period

shaded

Percent

10

9

8

7

6

5

4

3

2

10

9

8

7

6

5

4

3

2

Unemployment 

rate, annual 

average

Real price

Nominal price

 Chart 2. Real and nominal gasoline pump price, annual average, 1919–2009

Dollars per gallon

1919 1929 1939 1949 1959 1969 1979 1989 1999 2009

3.50

3.00

2.50

2.00

1.50

1.00

0.50

0.00

3.50

3.00

2.50

2.00

1.50

1.00

0.50

0.00

Dollars per gallon

SOURCE: U.S. Energy Information Administration 

crease in prices that did occur could be compared to what 

might have occurred if there had been an oil embargo. 

Starting in the late 1990s (see chart 2), there was a shift 

in the long-run trend in oil prices. With the exception of 

the politically driven oil shocks of the 1970s, real oil prices 

trended downwards from the invention of the automobile 

to the late 1990s, and nominal oil prices were fairly flat 

from the late 1970s until the late 1990s. Strong growth in 
Evaluating the 1996–2006 Projections

44 Monthly Labor Review • September 2010

the global demand for oil helped to change this long-run 

trend and shifted both nominal and real oil prices sharply 

upwards. BLS does not project oil prices; it uses projections produced by the Energy Information Agency. Although the Energy Information Agency had projected oil 

would be $27 a barrel in 2006, it was actually $59. Because 

the United States imported about 60 percent of its oil in 

2006,22 the increase in the price of oil raised the U.S. trade 

deficit that year.23

GDP. As shown in table 6, BLS underprojected average 

annual GDP growth for the 1996–2006 period by 1.0 percentage point. BLS projected 2.1 percent average annual 

growth, and actual growth was 3.1 percent. However, the 

numbers in table 6 fail to account for the substantial revisions to GDP data (previously mentioned) that occurred 

beginning in 1996 and led to revisions of historical data 

going back well before 1996. Table 7 shows that, in revising the projections to account for both the rebasing of 

GDP data and revisions to pre-1997 data, the projected 

average annual GDP growth rate should be adjusted from 

2.1 percent to either 2.5 percent or 2.7 percent (depending on the method used for adjusting the projections to 

account for revisions to the historical data.)24 Thus, once 

data revisions are accounted for, the underprojection of 

average annual GDP growth shrinks from 1.0 percentage 

point to about half a percentage point.

A combination of underprojecting the labor force and 

productivity growth and overprojecting the unemployment rate contributed to GDP growth being underprojected. The actual 3.1 percent average annual GDP growth 

rate was above both the projected 2.1 percent rate and the 

revised projected rate of 2.5 to 2.7 percent. 

Components of GDP. Projecting GDP necessitates projecting its underlying parts, which make up final demand. 

GDP consists of four categories of final demand: personal 

consumption expenditures (PCE), gross private domestic 

investment, foreign trade, and government consumption 

and investment. PCE accounts for more than two-thirds of 

GDP and is the largest and one of the most stable components of final demand. Private domestic investment is one 

of the most volatile factors in final demand and one of the 

hardest to project because it is strongly affected by business cycles, interest rates, and inflation. Foreign trade has 

grown as a share of the total economy and become more 

complex and harder to project. The government component of GDP is another relatively stable component, but it 

did change because of the wars fought over the latter half 

of the 1996–2006 period. 

Table 6. Real gross domestic product, by demand category, 2006

Demand category

Billions of chained Average annual rate of change

2000 dollars 1992 dollars 1996–2006

Actual Projected Actual Projected Difference

Gross domestic product.................................................. $11,294.9 $8,539.1 3.1 2.1 –1.0

 Personal consumption expenditures........................ 8,029.0 5,772.9 3.6 2.1 –1.5

 Durable goods................................................................. 1,185.1 867.3 7.1 3.6 –3.5

 Nondurable goods.......................................................... 2,335.3 1,683.8 3.3 1.6 –1.7

 Services............................................................................... 4,529.9 3,239.8 3.0 2.1 –0.9

 Gross private domestic investment............................ 1,912.5 1,469.7 4.5 3.3 –1.2

 Nonresidential.................................................................. 1,318.2 1,132.0 4.7 4.0 –.7

 Residential......................................................................... 552.9 302.7 3.8 0.9 –2.9

 Inventory changes.......................................................... 42.3 41.5 3.9 9.0 5.1

 Exports.................................................................................. 1,314.9 1,686.0 4.5 7.4 2.9

 Goods.................................................................................. 928.7 1,313.2 4.8 8.0 3.2

 Services............................................................................... 386.2 389.7 3.9 6.0 2.1

 Imports.................................................................................. 1,930.6 1,749.8 7.7 6.4 –1.3

 Goods................................................................................... 1,649.0 1,550.3 8.0 6.9 –1.1

 Services................................................................................ 283.8 211.5 5.9 3.9 –2.0

 Government......................................................................... 1,971.2 1,400.6 2.3 1.0 –1.3

 Federal defense consumption expenditures 

 and gross investment................................................. 490.0 257.3 2.5 –2.0 –4.5

 Federal nondefense consumption expenditures

and gross investment............................................... 250.8 141.5 2.8 –.8 –3

 State and local consumption expenditures

 and gross investment............................................... 1,230.2 1,005.9 2.2 2.3 .1

Residual –1.9 –44.4 ... ... ...
Monthly Labor Review • September 2010 45

Table 7. GDP with National Income and Product Account adjustments, 1986–2006

GDP 

Level Annual average rate of 

change

1986 1996 2006 1986–96 1996–2006

Original data, published in 1997 (billions of chained 1992 dollars)1

............ $5,489.9 $6,911.0 $8,539.1 2.3 2.1

Original data (billions of chained 2000 dollars)2 ................................................. 6,208.7 8,092.1 10,394.8 2.7 2.5

Revised data, published in 2007 (billions of chained 2000 dollars)3 ............ 6,263.6 8,328.9 11,294.9 2.9 3.1

Adjusted growth rate4 ................................................................................................... 2.9 2.7

1 Original data: Historical data for 1986 and 1996 and a projected value for 

2006 (in 1992 dollars) were published in the MLR in November 1997.

2

 Original data rebased to chained 2000 dollars with recalculated growth 

rates, 1986–96 = 2.7 percent and 1996–2006 = 2.5 percent 

3

 Revised historical data: historical data for 1986, 1996, and 2006 (in 2000 

dollars) were revised and then published by the Bureau of Economic Analysis in December 2007.

4

 The 1996–2006 projected growth rate was revised upwards by the same 

amount as the 1986–96 actual growth rate, resulting in a figure of 2.7 percent.

The components of GDP with the largest differences 

between projected and actual growth rates were expenditures for durable consumer goods, residential construction, and exports of goods and services. (See table 6 for 

the projections and actual GDP data on a real basis and 

table 8 for the results on a nominal basis. Real GDP data 

will be discussed on an average annual growth rate basis, 

and nominal GDP data will be discussed as a share of total 

GDP.)

During the 1996–2006 period, PCE grew faster than 

the overall economy. BLS had projected PCE to grow as a 

share of nominal GDP from 68.0 percent in 1996 to 70.1 

percent in 2006, and PCE did grow, from 67.3 percent (revised share) in 1996 to 69.9 percent in 2006. On a real 

basis, BLS had projected PCE to grow at the same average annual rate as GDP—2.1 percent. Of course, revisions 

to historical GDP data that occurred after the projections 

were produced suggest that the projected average annual 

rate should be revised up to 2.5 percent to 2.7 percent. 

Real PCE, projected to grow at a 2.1 percent rate, grew at 

an average annual rate of 3.6 percent over the 1996–2006 

period.

All three categories of PCE (durable goods, nondurable 

goods, and services) grew faster, on a real basis, than BLS

had projected, but durable goods consumption grew at 

the fastest rate. Durable goods—which include big-ticket 

items such as automobiles, home furnishings, major household appliances, and televisions—grew at a 7.1 percent average annual rate over the 1996–2006 period, whereas BLS

had projected 3.6 percent growth. The growth in spending 

on durable goods was linked to the housing bubble in a 

few ways. First, evidence shows that the wealth effect generated by rising home prices increased consumer spending, particularly on durable goods.25 Second, the high levels of investment in residential structures, which includes 

both building new homes and renovating existing homes, 

are intuitively linked to consumption of new appliances, 

which are durable goods. Third, survey evidence shows 

that consumers cite moving to a new home or renovating an existing home as a major reason for buying new 

furniture, which also is a durable good.26 Automobile sales 

did decline in 2006, but strong demand for other durable 

goods offset the decline. Although BLS underprojected 

the real growth rate in the two other categories of PCE as 

well—services (3.0 percent actual growth, compared with 

2.1 percent projected) and nondurable goods (3.3 percent 

actual growth, compared with a projected rate of 1.6 percent)—these categories were underprojected by amounts 

more consistent with the underprojection in the overall 

rate of growth of GDP, which can be attributed to the revisions in historical data, the underprojected labor force 

growth, and the general underprojection in growth.

BLS underprojected the growth of gross private domestic investment. The real average annual growth rate, 

projected to be 3.3 percent, was 4.5 percent. When gross 

private domestic investment is broken down into its two 

largest components, nonresidential and residential investment, it becomes apparent that residential investment was 

the underprojected component. The final component of 

gross private domestic investment, inventories, is quite 

small relative to the other two categories and has very little impact on total investment growth. Although BLS underprojected the average annual real growth rate of nonresidential investment (4.0 percent projected, compared 

with 4.7 percent actual—see table 6), the underprojection 

could be attributed to the revisions in data that resulted in 

the 1986–1996 growth rate for nonresidential investment 

being revised upwards, from 3.4 percent to 4.6 percent. 

Residential investment grew at an average annual rate 

of 8.3 percent between 2003 and 2005. Starting in 2006, 
Evaluating the 1996–2006 Projections

46 Monthly Labor Review • September 2010

it began to retreat from its 2005 peak, but residential 

investment and home sales and prices remained well above 

historical levels. As previously discussed, BLS does not 

attempt to project large economic fluctuations. Because 

BLS did not project the bubble, it is unsurprising that it 

underprojected growth in residential investment. The 

annual population growth rate was faster than projected 

for the 1996–2006 period, but the housing bubble was the 

primary reason that the annual residential construction 

growth rate during the period, 3.8 percent, was four times 

higher than the projected growth rate, 0.9 percent. 

The trend towards increased globalization can be seen 

in the growth of the foreign trade sector outpacing the 

growth of the aggregate economy. The projected real average annual growth rate of exports for the 1996–2006 period, 7.4 percent, exceeded the actual 4.5 percent rate for 

the same period. Whereas the growth of exports was overprojected, the growth of imports was underprojected. On 

a real basis, imports were projected to grow at a 6.4 percent 

average annual rate but actually grew at a 7.7 percent rate. 

With imports underprojected and exports overprojected, 

it is unsurprising that the BLS projection of net exports 

(the trade deficit) as a share of nominal GDP in 2006 was 

not accurate: BLS projected that net exports would be –1.1 

percent of GDP, but in reality they were –5.8 percent. The 

difference between the projected and actual level of net 

exports could be partly attributed to the underprojected 

oil price. The San Francisco Federal Reserve Bank stated 

that “these numbers [the trade deficit and oil imports] 

imply that higher oil prices and the resulting higher cost 

of petroleum imports have accounted for over 50 percent 

of the deterioration in the overall U.S. trade deficit during 

this period [from January 2002 to July 2006].”27 Another 

reason for the underprojection of imports is that durable 

goods make up a large share of imports,28 and the housing 

bubble increased consumption of durable goods.

BLS breaks up Federal Government consumption expenditures and investment into the categories of defense 

and nondefense. Since BLS did not project the two wars, 

it projected Federal defense consumption expenditures 

and gross investment to decline at a 2.0 percent real average annual rate, whereas in actuality they grew by 2.5 

percent per year on average. Over the projection period, 

defense, which had been projected to fall from 4.6 percent (4.5 percent revised) of nominal GDP in 1996 to 3.3 

percent in 2006, actually held fairly steady at 4.7 percent 

in 2006. Nondefense consumption expenditures and gross 

investment followed a pattern similar to that of defense 

consumption and investment. Real nondefense spending, 

projected to decline at a 0.8 percent rate, grew at a 2.8 

percent rate. On a nominal basis, nondefense consumption and investment, projected to decline from 2.3 percent 

(2.2 percent revised) of GDP in 1996 to 1.8 percent in 

2006, actually held steady at 2.3 percent of GDP in 2006. 

Federal budget. The Federal deficit, which amounted to 

1.5 percent of nominal GDP in 1996, was projected to decline. However, after 2000, various factors combined to 

shift the Federal budget towards higher deficits: following September 11, 2001, defense spending surged to pay 

for military operations in Iraq and Afghanistan and for 

conducting other antiterrorism activities29; government 

revenues were negatively affected by the tax cuts enacted 

from 200130 through 2006; and the Medicare prescripTable 8. Nominal GDP by major category, 1996 and 2006 

Category

Level Percent distribution

1996 2006 1996 2006

Original1 Revised2 Projected Actual Original1 Revised2 Projected Actual

Gross domestic product............................................................. $7,580.0 $7,816.8 $12,288.8 $13,178.4 100.0 100.0 100.0 100.0 

 Personal consumption expenditures.................................. 5,152.0 5,256.8 8,619.1 9,207.2 68.0 67.3 70.1 69.9 

 Gross private domestic investment..................................... 1,119.8 1,240.3 1,772.1 2,220.4 14.8 15.9 14.4 16.8 

 Exports............................................................................................ 855.4 868.5 1,880.0 1,480.8 11.3 11.1 15.3 11.2 

 Imports............................................................................................ 954.9 964.8 2,015.1 2,238.1 12.6 12.3 16.4 17.0 

 Federal defense consumption expenditures and gross

 investment.................................................................................. 348.1 354.6 400.6 624.1 4.6 4.5 3.3 4.7 

 Federal nondefense consumption expenditures

 and gross investment............................................................. 176.0 172.8 221.8 308.0 2.3 2.2 1.8 2.3 

 State and local consumption expenditures and gross

 investment................................................................................. 883.6 888.6 1,410.2 1,575.9 11.7 11.4 11.5 12.0 

1 Original 1996 data, published in 1997

[In billions of dollars]

2 Revised 1996 data, published in 2006
Monthly Labor Review • September 2010 47

tion drug benefit increased government expenses.31 As a 

result of these factors, the 2006 budget deficit, as a share 

of nominal GDP, was at the same level as in 1996, 1.5 

percent.

Conclusion. Several factors combined to cause BLS to underproject GDP growth for the 1996–2006 period. About 

half of the difference between the projected 2.1 percent 

growth rate and the actual 3.1 percent growth rate can be 

explained by revisions to how GDP growth was calculated. 

Another 0.2 percent of the 1.0 percent difference can be 

explained by the underprojected growth of the labor force. 

Thus, 0.3 percent of the 1.0 percent underprojection can 

be attributed to the macroeconomic projections. 

Industry employment

This section evaluates the data for employment by industry in the 1996–2006 projections. As explained earlier, 

employment growth and levels were projected for both 

industry divisions and for two-digit and three-digit SIC

industries. The industry projections are influenced by both 

the labor force projections and the macroeconomic projections. Errors in projecting employment in specific industry divisions were far larger, relatively, than the error in 

the labor force projection, and the industry division projection errors should not be attributed to the labor force 

projection error. For example, the labor force was underprojected by 2.6 million people, and the manufacturing 

sector alone was overprojected by 2.7 million jobs. The 

macroeconomic projections not only determine the total 

number of workers projected, but they also influence the 

expected distribution of employment among industries by 

determining both the expected levels of consumption of 

broad categories of goods and services and the expected 

levels of consumption of a few key products, such as automobiles and new homes. This section begins by examining 

the accuracy of the projections of employment in industry 

divisions and then moves into the accuracy of the projections for individual industries. When possible, it will 

discuss how the macroeconomic projections affected the 

industry employment projections. Finally, the projections 

are compared with the results of a naïve model.

As discussed previously, data revisions and changes to 

industry classification systems substantially altered the 

structure of the data. The conversion of data back to the 

1996 SIC-based industry classification system and the revisions that occurred after the employment projections 

were produced caused some discrepancies that resulted in 

the two distinct columns of 1996 data in table 9. Subtracting the actual statistic from the adjusted projected statistic 

should provide a better measure of the accuracy of the 

projected employment change in each sector than subtracting the actual statistic from the unadjusted projected 

statistic, because using the adjusted statistic takes account 

of revisions to the 1996 data. The results found with the 

adjusted statistic were quite similar to those found with 

the unadjusted statistic, with the exception of the results 

for the Federal Government, in which the sign changes. 

This change is due to revisions of the 1996 employment 

data for the Federal Government that were made after the 

employment projections were produced. 

Only wage and salary employment in nonagricultural 

industries is included in this analysis.32 The 2006 dataset 

used in this analysis accounts for approximately 135 million jobs and represents about 98 percent of 2006 wage 

and salary employment. (The other 2 percent, of course, is 

in agriculture.) 

Results for industry divisions. BLS overprojected employment for the following divisions, in order of largest overprojection to smallest in percent terms: manufacturing, 

utilities, transportation, services, and communications. 

BLS underprojected employment for the following divisions, in order of largest underprojection to smallest: mining; construction; finance, insurance, and real estate; State 

and local government; and trade. Federal Government 

employment was either underprojected or overprojected 

by about 2 percent, depending upon whether the adjusted 

1996 data or the original 1996 data are used. 

The largest numerical differences were in manufacturing, with employment overprojected by approximately 3.3 

million jobs, and services, with employment overprojected 

by 2.4 million jobs. Part of the differences in both sectors 

could be attributed to adjustments made to the data: the 

adjusted differences are 2.7 million jobs in manufacturing 

and 1.6 million jobs in services. Because services is the 

largest division in the economy, the adjusted percent difference was not very large, only 4 percent. Manufacturing 

is much smaller, so the overprojection of 2.7 million jobs 

meant that the percent difference in manufacturing, 18 

percent, was the third largest of any division. The largest 

percent differences were in mining and construction, in 

which employment levels were underprojected by 32 percent and 21 percent, respectively. 

The direction of change (that is, whether the change in 

employment was positive or negative) was correctly projected for all the industry divisions except mining and 

utilities; employment in mining was projected to fall by 

an average annual rate of 2.5 percent, but in fact it grew 
Evaluating the 1996–2006 Projections

48 Monthly Labor Review • September 2010

Table 9. Projected and actual employment in selected industry divisions, 2006

Division

Thousands of jobs

Percent difference, 

2006

Average annual 

rate of change, 

1996–2006

Percent 

change, 

1996 

Original 

1996 

data, 

published in 

1997

Revised 

and remapped 

1996 

data, 

published in 

2006

Projected Actual

Projected 

minus 

actual

Adjusted 

projected 

minus 

actual

1996 2006 2006

Projected 

minus 

actual

Adjusted 

projected 

minus 

actual

Projected

Adjusted 

projected

Original 

1996 to 

revised 

1996

Construction................ 5,400.0 5,376.9 5,899.9 7,478.1 –1,578.2 –1,601.4 –21.1 –21.4 0.9 3.4 –0.4

State and local 

government.............. 16,690.0 16,662.1 18,480.2 19,261.7 –781.5 –809.4 –4.1 –4.2 1.0 1.5 –.2

Finance, insurance, 

and real estate.......... 6,899.2 6,893.6 7,651.0 8,284.4 –633.4 –639.1 –7.6 –7.7 1.0 1.9 –.1

Trade............................... 28,108.0 27,968.7 31,103.1 31,430.4 –327.3 –466.6 –1.0 –1.5 1.0 1.2 –.5

Mining............................ 573.9 557.0 443.4 626.1 –182.7 –199.6 –29.2 –31.9 –2.5 1.2 –2.9

Federal Government 2,757.0 2,877.0 2,670.0 2,728.3 –58.3 61.7 –2.1 2.3 –.3 –.5 4.4

Communications....... 1,337.4 1,340.2 1,360.4 1,340.4 20.0 22.8 1.5 1.7 .2 .0 .2

Utilities.......................... 884.9 859.3 976.1 824.9 151.2 125.6 18.3 15.2 1.0 –.4 –2.9

Transportation............ 4,038.1 4,001.0 4,774.2 4,420.2 354.0 316.9 8.0 7.2 1.7 1.0 –.9

Services......................... 34,513.6 33,675.2 45,626.9 43,185.9 2,441.0 1,602.6 5.7 3.7 2.8 2.5 –2.4

Manufacturing............ 18,457.4 17,806.7 18,107.8 14,759.6 3,348.2 2,697.5 22.7 18.3 –.2 –1.9 –3.5

Total................................ 119,659.5 118,017.5 137,093.0 134,340.0 2,753.0 1,111.0 2.0 .8 1.4 1.3 –1.4

by 1.2 percent per year. Utilities were projected to grow by 

1.0 percent annually, but this sector fell by 0.4 percent per 

year on average. (See table 9.)

Results at the industry level. Table 10 displays accuracy 

metrics for the industry divisions and for all industries 

taken together. The unweighted mean absolute percent 

error (MAPE) for all industries was 24.7 percent. When 

weighted by industry employment, the MAPE dropped to 

11.7 percent. The fact that the weighted MAPE was much 

lower than the unweighted MAPE indicates that BLS was 

more accurate when projecting large industries than small 

industries. BLS correctly projected whether an industry 

would grow or decline 72 percent of the time. The dissimilarity index—which focuses more on structural change 

by measuring how much each industry’s projected share 

of total employment would have to change to match the 

actual share and, therefore, is not affected by differences 

in the total level of employment—was 5.9 percent. A detailed description of the dissimilarity index is available in 

the appendix.

When the results for all the industries within each division are compared with the results at the division level, 

two divisions, construction and communications, stand 

out because each contained only one industry in the 1996 

industry employment projections. Consequently, the performance metrics for these divisions are identical to those 

of their respective industries.

Tables 11 and 12 present the employment data for the 

individual industries, by their original rankings for fastest 

projected growth and largest projected numerical growth. 

Computer and data processing services, management and 

public relations, residential care, personnel supply services, 

and individual and miscellaneous social services all were 

expected to be among the 10 fastest growing industries, 

and they were. Industries that were projected to grow 

rapidly, but did not, include miscellaneous transportation 

services, which was projected to be the third fastest at 4.8 

percent average annual growth; water and sanitation, projected to grow the seventh fastest at 4.2 percent annually; and automobile parking, repair, and services, which 

rounded out the original top 10 and was projected to grow 

at 3.3 percent annually. All of these industries did grow in 

employment, but not at the rapid rates projected.

The industries among that original top 10 that did 

grow rapidly but had not been projected to do so were 
Monthly Labor Review • September 2010 49

State and local government enterprises; oil and gas field 

services; personal services; and nondepository credit institutions, and holding and other investment offices. The 

industries that were projected to decline the fastest and 

did were watches, clocks, and parts; footwear, except rubber and plastic; luggage, handbags, and leather products; 

apparel; and tires and inner tubes. All of the 10 industries 

that were projected to decline the most rapidly in terms of 

employment did in fact decline, and for the most part they 

are near the bottom of the list. 

Of the 10 industries projected to grow by the largest 

numbers of jobs, 6 were among the actual largest growing. Personnel supply services, eating and drinking places, 

State and local government education, computer and data 

processing services, offices of health practitioners, and 

retail trade (excluding eating and drinking places) contributed the most to job growth in numerical terms, as 

expected. (See table 12.) The other four rounding out the 

original top 10 were among the top 20 job gainers over 

the 1996–2006 period.

Because BLS did not anticipate the housing bubble, it 

underprojected the magnitude of job growth in the construction industry. Construction grew by about 2 million 

jobs—more than quadruple the anticipated growth of 

500,000. Investment in residential construction, which 

drives much of the employment in the construction industry, was projected to grow 0.9 percent per year, much 

less than the actual 3.8 percent growth that occurred over 

the 1996–2006 period.

The housing bubble was not the only shift from historical trends that affected the accuracy of the projections. The 

large increase in the price of oil that occurred after 1999 

is the main factor that caused BLS not to correctly project 

the direction of change in the mining division. When the 

mining division is broken down into its five component 

industries, it becomes apparent that the growth in the price 

of oil caused employment in the oil and gas field services 

industry to increase enough not only to offset employment 

declines in the other industries in the mining division, but 

also to increase total employment in the division. 

Most of the industries projected to have the largest 

losses in employment did decline. Apparel, private households, and computer and office equipment were among 

the industries with the largest losses, as expected. Federal 

general government, State and local government enterprises, and depository institutions also were expected to 

decline; however, these industries were among the 25 with 

the greatest absolute job growth. Upward revisions in 1996 

Table 10. Accuracy metrics by industry division and for all industries, 1996–2006 employment

Division Projection technique Direction of change 

(in percent)

MAPE1 (unweighted, 

in percent)

MAPE1 (weighted, 

in percent)

Dissimilarity 

index

Mining...................................................................... BLS 80.0 27.6 32.3 11.4

Naïve 60.0 50.9 48.9 21.8

Construction......................................................... BLS 100.0 21.1 21.1 .0

Naïve .0 30.5 30.5 .0

Manufacturing...................................................... BLS 65.3 29.8 24.9 .4

Naïve 57.1 33.5 27.7 .6

Transportation...................................................... BLS 62.5 20.5 13.9 7.3

Naïve 75.0 25.1 22.6 10.6

Communications................................................. BLS 100.0 1.5 1.5 .0

Naïve 100.0 1.0 1.0 .0

Utilities.................................................................... BLS 66.7 34.6 33.6 10.5

Naïve 66.7 26.2 23.1 9.4

Trade........................................................................ BLS 100.0 3.8 3.2 2.7

Naïve 100.0 2.4 2.4 1.3

Finance, insurance, and real estate.............. BLS 83.3 9.2 10.0 3.3

Naïve 83.3 12.7 13.9 5.1

Services.................................................................. BLS 89.7 12.4 11.0 4.6

Naïve 89.7 11.5 10.7 4.7

Federal Government.......................................... BLS 25.0 76.7 27.7 9.4

Naïve 50.0 44.0 17.8 6.0

State and local government............................ BLS 83.3 22.7 11.5 6.4

Naïve 83.3 23.2 14.2 6.7

All industries.......................................................... BLS 72.4 24.7 11.7 5.9

Naïve 67.8 26.7 13.0 6.4

1 Mean absolute percent error.
Evaluating the 1996–2006 Projections

50 Monthly Labor Review • September 2010

Table 11. Actual and projected wage and salary employment levels and growth rates (in percent), by industry, in order 

 of fastest to slowest projected growth, 1996–2006

Industry

Thousands of jobs Change, 

projected

Change, 

actual

Average 

annual rate 

of change, 

projected

Average 

annual rate 

of change, 

actual

Rank by 

actual average annual 

growth

1996 2006, 

projected

2006, 

actual 1996–2006 1996–2006 1996–2006 1996–2006 1996–2006

Computer and data processing

services...................................................... 1,207.9 2,509.1 1,978.4 1,301.2 770.5 7.6 5.1 3

Health services, not elsewhere 

classified.................................................... 1,171.9 1,968.3 1,553.2 796.4 381.3 5.3 2.9 17

Management and public relations..... 873.2 1,400.0 1,435.6 526.8 562.4 4.8 5.1 2

Miscellaneous transportation

services....................................................... 204.4 327.4 250.8 123.0 46.4 4.8 2.1 27

Residential care......................................... 672.1 1,069.8 976.5 397.7 304.4 4.8 3.8 8

Personnel supply services..................... 2,646.0 4,039.3 3,741.1 1,393.3 1,095.1 4.3 3.5 10

Water and sanitation............................... 230.9 349.1 236.8 118.2 5.9 4.2 .3 63

Individual and miscellaneous social

services....................................................... 846.3 1,265.9 1,347.0 419.6 500.7 4.1 4.8 5

Offices of health practitioners.............. 2,751.4 4,045.9 3,680.3 1,294.5 928.9 3.9 3.0 16

Amusement and recreation 

services, not elsewhere 

classified.................................................... 1,108.6 1,565.3 1,412.2 456.7 303.6 3.5 2.4 21

Automobile parking, repair, and

services....................................................... 890.3 1,236.2 1,014.4 345.9 124.1 3.3 1.3 42

Nursing and personal care facilities... 1,732.2 2,377.0 1,944.3 644.8 212.1 3.2 1.2 45

Producers, orchestras, and 

entertainers............................................... 151.7 204.6 176.3 52.9 24.6 3.0 1.5 38

Miscellaneous equipment rental

and leasing................................................ 237.8 320.2 287.8 82.4 50.0 3.0 1.9 28

Security and commodity brokers........ 551.4 740.4 765.0 189.0 213.6 3.0 3.3 12

Passenger transportation 

arrangement............................................. 212.9 277.2 167.3 64.3 –45.6 2.7 –2.4 123

Child day care services............................ 569.3 733.5 806.7 164.2 237.4 2.6 3.5 9

Miscellaneous business services......... 2,022.8 2,599.3 2,318.6 576.5 295.8 2.5 1.4 40

Museums, botanical, zoological

gardens....................................................... 84.7 108.8 118.8 24.1 34.1 2.5 3.4 11

Nondepository credit institutions,

and holding and other investment 

offices.......................................................... 725.6 928.2 1093.5 202.6 367.9 2.5 4.2 6

Research and testing services.............. 568.5 726.2 742.3 157.7 173.8 2.5 2.7 20

Legal services............................................. 929.9 1,186.7 1,061.5 256.8 131.6 2.5 1.3 41

Automotive rentals, without drivers.. 193.3 246.0 199.5 52.7 6.2 2.4 .3 62

Engineering and architectural

services...................................................... 839.1 1,051.7 1,140.3 212.6 301.2 2.3 3.1 15

Commercial sports................................... 123.6 154.5 154.1 30.9 30.5 2.3 2.2 23

Air transportation..................................... 1,122.1 1,401.0 1,118.4 278.9 –3.7 2.2 .0 66

Job training and related services........ 315.4 391.7 399.4 76.3 84.0 2.2 2.4 22

Motion pictures......................................... 367.6 454.9 417.2 87.3 49.6 2.2 1.3 43

Carpets and rugs....................................... 61.1 75.5 40.3 14.4 –20.8 2.1 –4.1 156

Drugs............................................................. 258.6 319.3 310.6 60.7 52.0 2.1 1.8 32

Accounting, auditing, and other

services....................................................... 612.5 751.6 666.2 139.1 53.7 2.1 .8 47

Educational services................................ 2,020.1 2,478.1 2,801.4 458.0 781.3 2.1 3.3 13

Federal Government enterprises, not

elsewhere classified............................... 134.6 165.0 45.1 30.4 –89.5 2.1 –10.4 172

Services to buildings................................ 897.1 1,097.2 1,177.1 200.1 280.0 2.0 2.8 18

Local and interurban passenger

transit.......................................................... 439.1 527.2 513.2 88.1 74.1 1.8 1.6 37

Miscellaneous plastics products, not

elsewhere classified.............................. 714.0 855.3 635.2 141.3 –78.8 1.8 –1.2 92

Eating and drinking places.................... 7,499.4 8,883.5 9,347.1 1,384.1 1,847.7 1.7 2.2 24
Monthly Labor Review • September 2010 51

Toys and sporting goods........................ 113.5 134.0 76.4 20.5 –37.1 1.7 –3.9 152

State and local electric utilities............ 85.4 100.0 77.8 14.6 –7.6 1.6 –.9 83

Miscellaneous repair services............... 233.3 271.2 248.4 37.9 15.1 1.5 .6 54

Medical equipment, instruments,

and supplies............................................ 267.7 310.3 265.6 42.6 –2.1 1.5 –.1 67

Railroad equipment................................. 36.3 42.0 26.5 5.7 –9.8 1.5 –3.1 136

State and local government 

education................................................... 8,671.3 10,002.3 10,233.4 1,331.0 1,562.1 1.4 1.7 34

Hotels and other lodging places......... 1,716.0 1,977.9 1,833.4 261.9 117.4 1.4 .7 53

Electronic components and 

accessories................................................ 610.0 700.0 474.8 90.0 –135.2 1.4 –2.5 128

Personal services, not elsewhere 

classified.................................................... 238.3 272.8 351.1 34.5 112.8 1.4 4.0 7

Meat products........................................... 481.3 550.8 497.7 69.5 16.4 1.4 .3 60

Trucking and warehousing................... 1,640.9 1,860.0 1,934.2 219.1 293.3 1.3 1.7 35

Real estate.................................................. 1,381.3 1,561.0 1,699.7 179.7 318.4 1.2 2.1 26

Beauty and barber shops..................... 411.8 462.3 511.7 50.5 99.9 1.2 2.2 25

Insurance carriers.................................... 1,510.0 1,694.0 1,595.2 184.0 85.2 1.2 .6 57

Electrical repair shops........................... 114.3 128.2 102.1 13.9 –12.2 1.2 –1.1 91

Video tape rental..................................... 154.8 173.1 146.7 18.3 –8.1 1.1 –.5 74

Wholesale trade....................................... 6,483.1 7,228.3 6,881.7 745.2 398.6 1.1 .6 55

Advertising................................................ 242.4 270.0 278.5 27.6 36.1 1.1 1.4 39

Paperboard containers and boxes.... 217.4 241.9 172.6 24.5 –44.8 1.1 –2.3 119

Membership organizations.................. 2,185.0 2,427.6 2,258.6 242.6 73.6 1.1 .3 61

Office and miscellaneous furniture

and fixtures............................................... 143.5 159.2 131.0 15.7 –12.5 1.0 –.9 82

Hospitals...................................................... 3,813.5 4,229.0 4,466.9 415.5 653.4 1.0 1.6 36

Partitions and fixtures............................. 85.0 94.1 69.0 9.1 –16.0 1.0 –2.1 113

Greeting cards........................................... 26.8 29.5 13.9 2.7 –12.9 1.0 –6.4 168

Insurance agents, brokers, and

service........................................................ 707.4 777.4 843.0 70.0 135.6 .9 1.8 33

Miscellaneous transportation 

equipment............................................... 75.3 82.5 78.7 7.2 3.4 .9 .4 58

State and local general government,

not elsewhere classified....................... 6,085.9 6,658.4 5,947.3 572.5 –138.6 .9 –.2 70

Construction............................................. 5,400.0 5,899.9 7,478.1 499.9 2,078.1 .9 3.3 14

Industrial machinery, not elsewhere 

classified.................................................... 348.6 379.3 341.9 30.7 –6.7 .8 –.2 69

Aerospace................................................... 549.9 595.9 480.5 46.0 –69.4 .8 –1.3 94

Metal coating, engraving, and allied

services..................................................... 133.4 144.4 123.7 11.0 –9.7 .8 –.8 78

Miscellaneous fabricated textile

products.................................................... 221.0 239.2 155.1 18.2 –65.9 .8 –3.5 145

Refrigeration and service industry

machinery................................................ 204.9 220.0 170.1 15.1 –34.8 .7 –1.8 105

Miscellaneous food and kindred

products.................................................... 185.4 198.6 173.9 13.2 –11.5 .7 –.6 77

Wood buildings and mobile homes.. 88.7 95.0 72.3 6.3 –16.4 .7 –2.0 108

Periodicals................................................... 131.5 140.0 124.4 8.5 –7.1 .6 –.6 75

Construction and related

machinery.................................................. 232.3 247.0 213.2 14.7 –19.1 .6 –.9 80

Retail trade, except eating and

drinking places...................................... 14,125.5 14,991.3 15,201.6 865.8 1,076.1 .6 .7 52

Millwork, plywood, and structural

members.................................................. 287.6 304.0 303.9 16.4 16.3 .6 .6 56

Table 11. Continued—Actual and projected wage and salary employment levels and growth rates (in percent), by industry, 

 in order of fastest to slowest projected growth, 1996–2006

Industry

Thousands of jobs Change, 

projected

Change, 

actual

Average 

annual rate 

of change, 

projected

Average 

annual rate 

of change, 

actual

Rank by 

actual average annual 

growth

1996 2006, 

projected

2006, 

actual 1996–2006 1996–2006 1996–2006 1996–2006 1996–2006
Evaluating the 1996–2006 Projections

52 Monthly Labor Review • September 2010

Laundry, cleaning, and shoe repair... 439.1 460.0 404.4 20.9 –34.7 0.5 –0.8 79

Books........................................................... 124.4 129.5 101.1 5.1 –23.3 .4 –2.1 112

Converted paper products except

containers................................................ 240.4 249.9 184.3 9.5 –56.1 .4 –2.6 129

Funeral service and crematories........ 95.0 98.7 102.7 3.7 7.7 .4 .8 50

Blankbooks and bookbinding............. 66.3 68.7 44.5 2.4 –21.8 .4 –3.9 153

U.S. Postal Service.................................... 856.2 880.0 770.1 23.8 –86.1 .3 –1.1 88

Wood containers and miscellaneous 

wood products....................................... 141.2 145.0 133.0 3.8 –8.2 .3 –.6 76

Soap, cleaners, and toilet goods......... 154.0 157.0 137.9 3.0 –16.1 .2 –1.1 89

Manufactured products, not

elsewhere classified.............................. 224.0 228.1 190.0 4.1 –34.0 .2 –1.6 103

Communications....................................... 1,337.4 1,360.4 1,340.4 23.0 3.0 .2 .0 64

Concrete, gypsum, and plaster

products..................................................... 211.5 213.8 254.6 2.3 43.1 .1 1.9 31

Logging........................................................ 80.1 80.7 65.3 .6 –14.8 .1 –2.0 109

Fabricated structural metal 

products..................................................... 438.5 440.0 474.7 1.5 36.2 .0 .8 49

Local government passenger 

transit.......................................................... 211.4 212.0 255.6 .6 44.2 .0 1.9 29

Commercial printing and business

forms............................................................ 608.6 610.0 475.0 1.4 –133.6 .0 –2.4 126

Nonferrous foundries.............................. 89.2 89.3 70.5 .1 –18.7 .0 –2.3 120

Preserved fruits and vegetables.......... 237.2 237.2 189.6 .0 –47.6 .0 –2.2 117

Electric utilities........................................... 473.7 472.0 370.3 –1.7 –103.4 .0 –2.4 125

Agricultural chemicals............................. 52.4 52.2 38.7 –.2 –13.7 .0 –3.0 135

Metalworking machinery and

equipment................................................ 345.4 344.0 244.7 –1.4 –100.7 .0 –3.4 142

Industrial chemicals................................. 262.7 261.0 152.5 –1.7 –110.2 –.1 –5.3 165

Grain mill products and fats 

and oils....................................................... 158.0 156.8 130.9 –1.2 –27.1 –.1 –1.9 106

Miscellaneous electrical 

equipment................................................. 152.9 151.1 99.6 –1.8 –53.3 –.1 –4.2 158

Special industry machinery................... 177.4 175.0 126.3 –2.4 –51.1 –.1 –3.3 140

Paints and allied products..................... 52.5 51.6 41.9 –.9 –10.6 –.2 –2.2 118

State and local government 

hospitals..................................................... 1,037.8 1,017.3 1,010.5 –20.5 –27.3 –.2 –.3 71

Miscellaneous fabricated metal

products..................................................... 253.5 248.0 219.6 –5.5 –33.9 –.2 –1.4 96

General industrial machinery and

equipment................................................. 257.2 250.0 207.1 –7.2 –50.1 –.3 –2.1 115

Miscellaneous publishing...................... 86.2 83.4 78.5 –2.8 –7.7 –.3 –.9 84

Motor vehicles and equipment........... 962.5 929.3 841.0 –33.2 –121.5 –.4 –1.3 95

Water transportation............................... 173.1 167.1 193.4 –6.0 20.3 –.4 1.1 46

Depository institutions........................... 2,023.5 1,950.0 2,288.0 –73.5 264.5 –.4 1.2 44

Watch, jewelry, and furniture repair... 27.0 26.0 21.7 –1.0 –5.3 –.4 –2.2 116

Sugar and confectionery products... 98.5 94.8 71.8 –3.7 –26.7 –.4 –3.1 137

Federal electric utilities........................... 26.2 25.0 22.5 –1.2 –3.7 –.5 –1.5 99

Communications equipment............... 269.2 255.0 173.1 –14.2 –96.1 –.5 –4.3 159

Sawmills and planing mills.................... 182.1 172.3 156.3 –9.8 –25.8 –.6 –1.5 100

Pulp, paper, and paperboard mills..... 223.2 210.0 136.0 –13.2 –87.2 –.6 –4.8 162

Rubber products and plastic hose

and footwear............................................ 187.5 176.2 132.4 –11.3 –55.1 –.6 –3.4 143

All other primary metals......................... 45.0 42.2 33.9 –2.8 –11.1 –.6 –2.8 131

Table 11. Continued—Actual and projected wage and salary employment levels and growth rates (in percent), by industry, 

 in order of fastest to slowest projected growth, 1996–2006

Industry

Thousands of jobs Change, 

projected

Change, 

actual

Average 

annual rate 

of change, 

projected

Average 

annual rate 

of change, 

actual

Rank by 

actual average annual 

growth

1996 2006, 

projected

2006, 

actual 1996–2006 1996–2006 1996–2006 1996–2006 1996–2006
Monthly Labor Review • September 2010 53

Jewelry, silverware, and plated 

ware............................................................. 49.1 46.0 36.7 –3.1 –12.4 –.7 –2.9 133

Miscellaneous petroleum and coal

products..................................................... 41.5 38.8 37.4 –2.7 –4.1 –.7 –1.0 87

Dairy products........................................... 143.7 134.0 131.7 –9.7 –12.0 –.7 –.9 81

Nonmetallic minerals, except fuels.... 106.2 98.9 105.0 –7.3 –1.2 –.7 –.1 68

Household furniture................................ 275.3 255.8 235.6 –19.5 –39.7 –.7 –1.5 101

Screw machine products, bolts,

rivets, not elsewhere classified........ 100.8 93.0 97.9 –7.8 –2.9 –.8 –.3 72

Federal general government............... 1,740.0 1,600.0 1,890.6 –140.0 150.6 –.8 .8 48

Knitting mills.............................................. 179.5 165.0 57.7 –14.5 –121.8 –.8 –10.7 173

Nonferrous rolling and drawing......... 167.7 153.8 130.6 –13.9 –37.1 –.9 –2.5 127

Bakery products........................................ 210.1 191.9 181.5 –18.2 –28.6 –.9 –1.5 98

Plastics materials and synthetics........ 158.8 145.0 105.1 –13.8 –53.7 –0.9 –4.0 154

Plumbing and nonelectric heating

equipment................................................ 57.6 52.4 49.1 –5.2 –8.5 –.9 –1.6 102

Ship and boat building and 

repairing..................................................... 156.6 142.3 168.9 –14.3 12.3 –1.0 .8 51

Electric lighting and wiring 

equipment................................................ 177.8 161.4 128.8 –16.4 –49.0 –1.0 –3.2 138

Weaving, finishing, yarn, and thread

mills............................................................. 332.0 301.2 144.5 –30.8 –187.5 –1.0 –8.0 169

Miscellaneous textile goods................. 51.3 46.5 33.9 –4.8 –17.4 –1.0 –4.1 155

Miscellaneous chemical products...... 92.8 84.0 72.9 –8.8 –19.9 –1.0 –2.4 122

Iron and steel foundries......................... 128.9 116.0 91.6 –12.9 –37.3 –1.0 –3.4 141

Ophthalmic goods................................... 35.6 32.0 31.5 –3.6 –4.1 –1.1 –1.2 93

Bowling centers......................................... 81.8 73.1 107.0 –8.7 25.2 –1.1 2.7 19

Newspapers................................................ 442.3 394.9 360.3 –47.4 –82.0 –1.1 –2.0 110

Measuring and controlling devices.... 297.0 265.0 268.4 –32.0 –28.6 –1.1 –1.0 86

Ordnance and ammunition.................. 47.5 42.0 33.3 –5.5 –14.2 –1.2 –3.5 146

Household audio and video 

equipment................................................ 82.7 72.9 46.3 –9.8 –36.4 –1.3 –5.6 167

Primary nonferrous smelting and

refining....................................................... 39.4 34.6 25.3 –4.8 –14.1 –1.3 –4.3 160

Cutlery, hand tools, and hardware..... 124.9 109.3 76.3 –15.6 –48.6 –1.3 –4.8 161

Engines and turbines.............................. 84.0 73.4 67.9 –10.6 –16.1 –1.3 –2.1 114

Railroad transportation......................... 231.1 201.8 231.6 –29.3 .5 –1.3 .0 65

Service industries for the printing

trade........................................................... 51.6 45.0 36.2 –6.6 –15.4 –1.4 –3.5 144

Stone, clay, and miscellaneous

mineral products.................................... 164.1 143.1 135.1 –21.0 –29.0 –1.4 –1.9 107

Metal forgings and stampings............. 252.5 220.0 198.8 –32.5 –53.7 –1.4 –2.4 121

Computer and office equipment........ 363.0 313.7 217.8 –49.3 –145.2 –1.4 –5.0 163

Oil and gas field services........................ 169.3 146.0 272.3 –23.3 103.0 –1.5 4.9 4

Pipelines, except natural gas................ 14.5 12.5 11.4 –2.0 –3.1 –1.5 –2.4 124

Gas utilities.................................................. 180.3 155.0 217.8 –25.3 37.5 –1.5 1.9 30

Glass and glass products........................ 147.6 125.7 103.1 –21.9 –44.5 –1.6 –3.5 147

Farm and garden machinery and 

equipment................................................. 99.2 84.4 88.7 –14.8 –10.5 –1.6 –1.1 90

Hydraulic cement...................................... 17.4 14.8 18.1 –2.6 .7 –1.6 .4 59

Metal mining............................................... 53.8 45.0 35.4 –8.8 –18.4 –1.8 –4.1 157

Beverages.................................................... 178.5 149.3 171.4 –29.2 –7.1 –1.8 –.4 73

Private households................................... 928.0 775.2 802.5 –152.8 –125.5 –1.8 –1.4 97

Electric distribution equipment.......... 81.7 67.5 62.2 –14.2 –19.5 –1.9 –2.7 130

Table 11. Continued—Actual and projected wage and salary employment levels and growth rates (in percent), by industry, 

 in order of fastest to slowest projected growth, 1996–2006

Industry

Thousands of jobs Change, 

projected

Change, 

actual

Average 

annual rate 

of change, 

projected

Average 

annual rate 

of change, 

actual

Rank by 

actual average annual 

growth

1996 2006, 

projected

2006,

 actual 1996–2006 1996–2006 1996–2006 1996–2006 1996–2006
Evaluating the 1996–2006 Projections

54 Monthly Labor Review • September 2010

State and local government 

enterprises, not elsewhere 

classified..................................................... 598.2 490.2 1,575.9 –108.0 977.7 –2.0 10.2 1

Blast furnaces and basic steel

products..................................................... 240.3 196.7 161.8 –43.6 –78.5 –2.0 –3.9 151

Household appliances............................. 121.0 96.4 83.5 –24.6 –37.5 –2.2 –3.6 149

Petroleum refining.................................... 100.2 79.5 72.2 –20.7 –28.0 –2.3 –3.2 139

Electrical industrial apparatus.............. 156.0 122.4 108.7 –33.6 –47.3 –2.4 –3.5 148

Photographic equipment and 

supplies...................................................... 84.9 65.1 50.6 –19.8 –34.3 –2.6 –5.0 164

Tires and inner tubes............................... 79.5 59.3 58.9 –20.2 –20.6 –2.9 –2.9 134

Apparel......................................................... 642.9 475.1 189.5 –167.8 –453.4 –3.0 –11.5 174

Metal cans and shipping 

containers.................................................. 39.0 28.6 29.3 –10.4 –9.7 –3.1 –2.8 132

Tobacco products..................................... 41.4 30.3 28.4 –11.1 –13.0 –3.1 –3.7 150

Luggage, handbags, and leather

products, not elsewhere classified.. 49.4 34.4 20.2 –15.0 –29.2 –3.6 –8.5 170

Crude petroleum, natural gas, and

gas liquids................................................. 148.2 101.5 134.9 –46.7 –13.3 –3.7 –.9 85

Search and navigation equipment.... 160.7 109.5 135.2 –51.2 –25.5 –3.8 –1.7 104

Footwear, except rubber and 

plastic.......................................................... 46.5 30.8 16.0 –15.7 –30.5 –4.0 –10.1 171

Watches, clocks, and parts..................... 7.7 5.1 4.4 –2.6 –3.3 –4.0 –5.5 166

Coal mining................................................. 96.4 52.0 78.5 –44.4 –17.9 –6.0 –2.0 111

Table 11. Continued—Actual and projected wage and salary employment levels and growth rates (in percent), by industry, 

 in order of fastest to slowest projected growth, 1996–2006

Industry

Thousands of jobs Change, 

projected

Change, 

actual

Average 

annual rate 

of change, 

projected

Average 

annual rate 

of change, 

actual

Rank by 

actual average annual 

growth

1996 2006, 

projected

2006, 

actual 1996–2006 1996–2006 1996–2006 1996–2006 1996–2006

government employment may be a substantial factor in 

this result.

The large errors in the projections of industries that are 

part of State or Federal Government could be attributed 

to NAICS-to-SIC crosswalk problems. The data were recalculated for the aggregate industry of Federal Government 

(except the Postal Service) and that of State and local 

government, and the issues with the government industries were somewhat resolved. State and local government, 

as an industry, was projected to show the largest employment growth—1.8 million jobs. The actual job growth 

was approximately 2.6 million, making it the number one 

contributor to job growth. The 1.4 percent growth rate 

was higher than the projected 1.0 percent rate. Federal 

Government (except Postal Service) was projected to be 

among the industries with the largest employment declines (111,000); it actually increased in employment by 

57,000 jobs. This corresponds to an average annual growth 

rate of 0.3 percent, compared with the projected decline 

of 0.6 percent, and was near the middle of the rankings 

for fastest growth.

Naïve model. Tables 10 and 13 provide a comparison of 

the BLS industry employment projections with those of 

a naïve model across a range of accuracy metrics. Since 

higher values indicate greater accuracy for some metrics 

and less accuracy for others, the final row of table 13 provides a summary of which model performed better by 

each metric, and, as that row clearly shows, the BLS model 

outperformed the naïve model in every metric.

Occupational employment

The results of the industry and macroeconomic projections are used to project employment in specific occupations. The occupational employment projections are used 

by policymakers to determine which educational programs 

to support and by jobseekers making career choices. The 

first part of this section discusses the accuracy of the BLS 

occupational employment projections. The second part of 

this section discusses how the accuracy of the 1996–2006 

projections compares with that of alternative naïve models. 
Monthly Labor Review • September 2010 55

Table 12. Actual and projected numerical wage and salary employment levels and growth, by industry, in order of fastest

 to slowest projected numerical growth, 1996–2006

Industry

Thousands of jobs Change, 

projected

Change, 

actual

Average 

annual rate 

of change, 

projected

Average 

annual rate 

of change, 

actual

Rank by 

actual 

numerical 

change

1996 2006,

projected 2006, actual 1996–2006 1996–2006 1996–2006 1996–2006 1996–2006

Personnel supply services................... 2,646.0 4,039.3 3,741.1 1,393.3 1,095.1 4.3 3.5 4

Eating and drinking places................. 7,499.4 8,883.5 9,347.1 1,384.1 1,847.7 1.7 2.2 2

State and local government 

education................................................ 8,671.3 10,002.3 10,233.4 1,331.0 1,562.1 1.4 1.7 3

Computer and data processing

services.................................................... 1,207.9 2,509.1 1,978.4 1,301.2 770.5 7.6 5.1 9

Offices of health practitioners........... 2,751.4 4,045.9 3,680.3 1,294.5 928.9 3.9 3.0 7

Retail trade exclude eating and 

drinking places..................................... 14,125.5 14,991.3 15,201.6 865.8 1076.1 .6 .7 5

Health services, not elsewhere 

classified................................................. 1,171.9 1,968.3 1,553.2 796.4 381.3 5.3 2.9 14

Wholesale trade...................................... 6,483.1 7,228.3 6,881.7 745.2 398.6 1.1 .6 13

Nursing and personal care 

facilities.................................................... 1,732.2 2,377.0 1,944.3 644.8 212.1 3.2 1.2 26

Miscellaneous business services....... 2,022.8 2,599.3 2,318.6 576.5 295.8 2.5 1.4 20

State and local general

government, not elsewhere 

classified................................................... 6,085.9 6,658.4 5,947.3 572.5 –138.6 .9 –.2 171

Management and public 

relations................................................... 873.2 1,400.0 1,435.6 526.8 562.4 4.8 5.1 11

Construction............................................ 5,400.0 5,899.9 7,478.1 499.9 2,078.1 .9 3.3 1

Educational services.............................. 2,020.1 2,478.1 2,801.4 458.0 781.3 2.1 3.3 8

Amusement and recreation 

services, not elsewhere classified.. 1,108.6 1,565.3 1,412.2 456.7 303.6 3.5 2.4 18

Individual and miscellaneous 

social services........................................ 846.3 1,265.9 1,347.0 419.6 500.7 4.1 4.8 12

Hospitals.................................................... 3,813.5 4,229.0 4,466.9 415.5 653.4 1.0 1.6 10

Residential care....................................... 672.1 1,069.8 976.5 397.7 304.4 4.8 3.8 17

Automobile parking, repair, and

services.................................................... 890.3 1,236.2 1,014.4 345.9 124.1 3.3 1.3 31

Air transportation................................... 1,122.1 1,401.0 1,118.4 278.9 –3.7 2.2 .0 72

Hotels and other lodging places....... 1,716.0 1,977.9 1,833.4 261.9 117.4 1.4 .7 32

Legal services........................................... 929.9 1,186.7 1,061.5 256.8 131.6 2.5 1.3 30

Membership organizations................ 2,185.0 2,427.6 2,258.6 242.6 73.6 1.1 .3 39

Trucking and warehousing................. 1,640.9 1,860.0 1,934.2 219.1 293.3 1.3 1.7 21

Engineering and architectural

services.................................................... 839.1 1,051.7 1,140.3 212.6 301.2 2.3 3.1 19

Nondepository credit institutions,

and holding and other 

investment offices.............................. 725.6 928.2 1093.5 202.6 367.9 2.5 4.2 15

Services to buildings............................. 897.1 1,097.2 1,177.1 200.1 280.0 2.0 2.8 22

Security and commodity brokers..... 551.4 740.4 765.0 189.0 213.6 3.0 3.3 25

Insurance carriers................................... 1,510.0 1,694.0 1,595.2 184.0 85.2 1.2 .6 36

Real estate................................................. 1,381.3 1,561.0 1,699.7 179.7 318.4 1.2 2.1 16

Child day care services......................... 569.3 733.5 806.7 164.2 237.4 2.6 3.5 24

Research and testing services............ 568.5 726.2 742.3 157.7 173.8 2.5 2.7 27

Miscellaneous plastics products,

not elsewhere classified.................... 714.0 855.3 635.2 141.3 –78.8 1.8 –1.2 157

Accounting, auditing, and other

services.................................................... 612.5 751.6 666.2 139.1 53.7 2.1 .8 40

Miscellaneous transportation

services.................................................... 204.4 327.4 250.8 123.0 46.4 4.8 2.1 44

Water and sanitation............................. 230.9 349.1 236.8 118.2 5.9 4.2 .3 61
Evaluating the 1996–2006 Projections

56 Monthly Labor Review • September 2010

Electronic components and 

accessories.............................................. 610.0 700.0 474.8 90.0 –135.2 1.4 –2.5 170

Local and interurban passenger 

transit....................................................... 439.1 527.2 513.2 88.1 74.1 1.8 1.6 38

Motion pictures....................................... 367.6 454.9 417.2 87.3 49.6 2.2 1.3 43

Miscellaneous equipment rental

and leasing............................................. 237.8 320.2 287.8 82.4 50.0 3.0 1.9 42

Job training and related services...... 315.4 391.7 399.4 76.3 84.0 2.2 2.4 37

Insurance agents, brokers, and

service....................................................... 707.4 777.4 843.0 70.0 135.6 .9 1.8 29

Meat products......................................... 481.3 550.8 497.7 69.5 16.4 1.4 .3 55

Passenger transportation 

arrangement.......................................... 212.9 277.2 167.3 64.3 –45.6 2.7 –2.4 142

Drugs........................................................... 258.6 319.3 310.6 60.7 52.0 2.1 1.8 41

Producers, orchestras, and 

entertainers............................................ 151.7 204.6 176.3 52.9 24.6 3.0 1.5 53

Automotive rentals, without 

drivers....................................................... 193.3 246.0 199.5 52.7 6.2 2.4 .3 60

Beauty and barber shops..................... 411.8 462.3 511.7 50.5 99.9 1.2 2.2 35

Aerospace.................................................. 549.9 595.9 480.5 46.0 –69.4 .8 –1.3 155

Medical equipment, instruments,

and supplies........................................... 267.7 310.3 265.6 42.6 –2.1 1.5 –0.1 67

Miscellaneous repair services............. 233.3 271.2 248.4 37.9 15.1 1.5 0.6 57

Personal services, not elsewhere 

classified................................................... 238.3 272.8 351.1 34.5 112.8 1.4 4.0 33

Commercial sports................................. 123.6 154.5 154.1 30.9 30.5 2.3 2.2 51

Industrial machinery, not 

elsewhere classified............................ 348.6 379.3 341.9 30.7 –6.7 .8 –.2 76

Federal government enterprises,

not elsewhere classified.................... 134.6 165.0 45.1 30.4 –89.5 2.1 –10.4 161

Advertising................................................ 242.4 270.0 278.5 27.6 36.1 1.1 1.4 49

Paperboard containers and boxes.... 217.4 241.9 172.6 24.5 –44.8 1.1 –2.3 141

Museums, botanical, zoological 

gardens..................................................... 84.7 108.8 118.8 24.1 34.1 2.5 3.4 50

U.S. Postal Service................................... 856.2 880.0 770.1 23.8 –86.1 .3 –1.1 159

Communications..................................... 1337.4 1,360.4 1,340.4 23.0 3.0 .2 .0 63

Laundry, cleaning, and shoe repair.. 439.1 460.0 404.4 20.9 –34.7 .5 –.8 132

Toys and sporting goods..................... 113.5 134.0 76.4 20.5 –37.1 1.7 –3.9 135

Video tape rental.................................... 154.8 173.1 146.7 18.3 –8.1 1.1 –.5 81

Miscellaneous fabricated textile 

products.................................................. 221.0 239.2 155.1 18.2 –65.9 .8 –3.5 154

Millwork, plywood, and structural

members................................................. 287.6 304.0 303.9 16.4 16.3 .6 .6 56

Office and miscellaneous furniture

and fixtures............................................ 143.5 159.2 131.0 15.7 –12.5 1.0 –.9 94

Refrigeration and service industry

machinery............................................... 204.9 220.0 170.1 15.1 –34.8 .7 –1.8 133

Construction and related 

machinery................................................ 232.3 247.0 213.2 14.7 –19.1 .6 –.9 111

State and local electric utilities.......... 85.4 100.0 77.8 14.6 –7.6 1.6 –.9 79

Carpets and rugs..................................... 61.1 75.5 40.3 14.4 –20.8 2.1 –4.1 115

Electrical repair shops........................... 114.3 128.2 102.1 13.9 –12.2 1.2 –1.1 92

Miscellaneous food and kindred

products................................................... 185.4 198.6 173.9 13.2 –11.5 .7 –.6 90

Metal coating, engraving, and 

allied services......................................... 133.4 144.4 123.7 11.0 –9.7 .8 –.8 85

Table 12. Continued—Actual and projected numerical wage and salary employment levels and growth, by industry, in order

 of fastest to slowest projected numerical growth, 1996–2006

Industry

Thousands of jobs Change, 

projected

Change, 

actual

Average 

annual rate 

of change, 

projected

Average 

annual rate 

of change, 

actual

Rank by 

actual 

numerical 

change

1996 2006,

projected

2006, 

actual 1996–2006 1996–2006 1996–2006 1996–2006 1996–2006
Monthly Labor Review • September 2010 57

Converted paper products, except

containers................................................ 240.4 249.9 184.3 9.5 –56.1 .4 –2.6 153

Partitions and fixtures........................... 85.0 94.1 69.0 9.1 –16.0 1.0 –2.1 103

Periodicals................................................. 131.5 140.0 124.4 8.5 –7.1 .6 –.6 78

Miscellaneous transportation

equipment.............................................. 75.3 82.5 78.7 7.2 3.4 .9 .4 62

Wood buildings and mobile 

homes....................................................... 88.7 95.0 72.3 6.3 –16.4 .7 –2.0 106

Railroad equipment............................... 36.3 42.0 26.5 5.7 –9.8 1.5 –3.1 86

Books........................................................... 124.4 129.5 101.1 5.1 –23.3 .4 –2.1 117

Manufactured products, not 

elsewhere classified............................ 224.0 228.1 190.0 4.1 –34.0 .2 –1.6 130

Wood containers and 

miscellaneous wood products....... 141.2 145.0 133.0 3.8 –8.2 .3 –.6 82

Funeral service and crematories...... 95.0 98.7 102.7 3.7 7.7 .4 .8 59

Soap, cleaners, and toilet goods....... 154.0 157.0 137.9 3.0 –16.1 .2 –1.1 104

Greeting cards......................................... 26.8 29.5 13.9 2.7 –12.9 1.0 –6.4 95

Blankbooks and bookbinding........... 66.3 68.7 44.5 2.4 –21.8 .4 –3.9 116

Concrete, gypsum, and plaster

products.................................................. 211.5 213.8 254.6 2.3 43.1 .1 1.9 46

Fabricated structural metal 

products................................................... 438.5 440.0 474.7 1.5 36.2 .0 .8 48

Commercial printing and business

forms......................................................... 608.6 610.0 475.0 1.4 –133.6 .0 –2.4 169

Logging...................................................... 80.1 80.7 65.3 .6 –14.8 .1 –2.0 101

Local government passenger

 transit......................................................... 211.4 212.0 255.6 .6 44.2 .0 1.9 45

Nonferrous foundries............................ 89.2 89.3 70.5 .1 –18.7 .0 –2.3 110

Preserved fruits and vegetables........ 237.2 237.2 189.6 .0 –47.6 .0 –2.2 144

Agricultural chemicals.......................... 52.4 52.2 38.7 –.2 –13.7 .0 –3.0 98

Paints and allied products.................. 52.5 51.6 41.9 –.9 –10.6 –.2 –2.2 88

Watch, jewelry, and furniture 

repair......................................................... 27.0 26.0 21.7 –1.0 –5.3 –.4 –2.2 75

Grain mill products and fats and

 oils.............................................................. 158.0 156.8 130.9 –1.2 –27.1 –.1 –1.9 121

Federal electric utilities......................... 26.2 25.0 22.5 –1.2 –3.7 –.5 –1.5 71

Metalworking machinery and

 equipment.............................................. 345.4 344.0 244.7 –1.4 –100.7 .0 –3.4 163

Industrial chemicals............................... 262.7 261.0 152.5 –1.7 –110.2 –.1 –5.3 165

Electric utilities........................................ 473.7 472.0 370.3 –1.7 –103.4 .0 –2.4 164

Miscellaneous electrical 

equipment............................................. 152.9 151.1 99.6 –1.8 –53.3 –.1 –4.2 149

Pipelines, except natural gas............. 14.5 12.5 11.4 –2.0 –3.1 –1.5 –2.4 69

Special industry machinery................ 177.4 175.0 126.3 –2.4 –51.1 –.1 –3.3 148

Hydraulic cement................................... 17.4 14.8 18.1 –2.6 .7 –1.6 .4 64

Watches, clocks, and parts.................. 7.7 5.1 4.4 –2.6 –3.3 –4.0 –5.5 70

Miscellaneous petroleum and coal

products.................................................. 41.5 38.8 37.4 –2.7 –4.1 –.7 –1.0 74

All other primary metals...................... 45.0 42.2 33.9 –2.8 –11.1 –.6 –2.8 89

Miscellaneous publishing.................... 86.2 83.4 78.5 –2.8 –7.7 –.3 –.9 80

Jewelry, silverware, and plated

 ware........................................................... 49.1 46.0 36.7 –3.1 –12.4 –.7 –2.9 93

Ophthalmic goods.................................. 35.6 32.0 31.5 –3.6 –4.1 –1.1 –1.2 73

Sugar and confectionery products.. 98.5 94.8 71.8 –3.7 –26.7 –.4 –3.1 120

Table 12. Continued—Actual and projected numerical wage and salary employment levels and growth, by industry, in order

 of fastest to slowest projected numerical growth, 1996–2006

Industry

Thousands of jobs Change, 

projected

Change, 

actual

Average 

annual rate 

of change, 

projected

Average 

annual rate 

of change, 

actual

Rank by 

actual 

numerical 

change

1996 2006,

projected 2006, actual 1996–2006 1996–2006 1996–2006 1996–2006 1996–2006
Evaluating the 1996–2006 Projections

58 Monthly Labor Review • September 2010

Primary nonferrous smelting and

refining..................................................... 39.4 34.6 25.3 –4.8 –14.1 –1.3 –4.3 99

Miscellaneous textile goods............... 51.3 46.5 33.9 –4.8 –17.4 –1.0 –4.1 107

Plumbing and nonelectric heating

equipment.............................................. 57.6 52.4 49.1 –5.2 –8.5 –.9 –1.6 83

Ordnance and ammunition................ 47.5 42.0 33.3 –5.5 –14.2 –1.2 –3.5 100

Miscellaneous fabricated metal

products.................................................. 253.5 248.0 219.6 –5.5 –33.9 –.2 –1.4 129

Water transportation............................. 173.1 167.1 193.4 –6.0 20.3 –.4 1.1 54

Service industries for the printing

trade.......................................................... 51.6 45.0 36.2 –6.6 –15.4 –1.4 –3.5 102

General industrial machinery and

equipment............................................. 257.2 250.0 207.1 –7.2 –50.1 –.3 –2.1 147

Nonmetallic minerals, except fuels.. 106.2 98.9 105.0 –7.3 –1.2 –.7 –.1 66

Screw machine products, bolts,

rivets, not elsewhere classified....... 100.8 93.0 97.9 –7.8 –2.9 –.8 –.3 68

Bowling centers...................................... 81.8 73.1 107.0 –8.7 25.2 –1.1 2.7 52

Metal mining........................................... 53.8 45.0 35.4 –8.8 –18.4 –1.8 –4.1 109

Miscellaneous chemical products... 92.8 84.0 72.9 –8.8 –19.9 –1.0 –2.4 113

Dairy products......................................... 143.7 134.0 131.7 –9.7 –12.0 –.7 –.9 91

Sawmills and planing mills................. 182.1 172.3 156.3 –9.8 –25.8 –.6 –1.5 119

Household audio and video 

equipment.............................................. 82.7 72.9 46.3 –9.8 –36.4 –1.3 –5.6 134

Metal cans and shipping 

containers............................................... 39.0 28.6 29.3 –10.4 –9.7 –3.1 –2.8 84

Engines and turbines............................ 84.0 73.4 67.9 –10.6 –16.1 –1.3 –2.1 105

Tobacco products................................... 41.4 30.3 28.4 –11.1 –13.0 –3.1 –3.7 96

Rubber products and plastic hose

and footwear.......................................... 187.5 176.2 132.4 –11.3 –55.1 –.6 –3.4 152

Iron and steel foundries....................... 128.9 116.0 91.6 –12.9 –37.3 –1.0 –3.4 137

Pulp, paper, and paperboard mills... 223.2 210.0 136.0 –13.2 –87.2 –.6 –4.8 160

Plastics materials and synthetics...... 158.8 145.0 105.1 –13.8 –53.7 –.9 –4.0 151

Nonferrous rolling and drawing....... 167.7 153.8 130.6 –13.9 –37.1 –.9 –2.5 136

Communications equipment............. 269.2 255.0 173.1 –14.2 –96.1 –.5 –4.3 162

Electric distribution equipment........ 81.7 67.5 62.2 –14.2 –19.5 –1.9 –2.7 112

Ship and boat building and 

repairing.................................................. 156.6 142.3 168.9 –14.3 12.3 –1.0 .8 58

Knitting mills............................................ 179.5 165.0 57.7 –14.5 –121.8 –.8 –10.7 167

Farm and garden machinery and

equipment.............................................. 99.2 84.4 88.7 –14.8 –10.5 –1.6 –1.1 87

Luggage, handbags, and leather

products, not elsewhere classified. 49.4 34.4 20.2 –15.0 –29.2 –3.6 –8.5 127

Cutlery, handtools, and hardware... 124.9 109.3 76.3 –15.6 –48.6 –1.3 –4.8 145

Footwear, except rubber and

plastic..................................................... 46.5 30.8 16.0 –15.7 –30.5 –4.0 –10.1 128

Electric lighting and wiring 

equipment.............................................. 177.8 161.4 128.8 –16.4 –49.0 –1.0 –3.2 146

Bakery products...................................... 210.1 191.9 181.5 –18.2 –28.6 –.9 –1.5 125

Household furniture.............................. 275.3 255.8 235.6 –19.5 –39.7 –.7 –1.5 139

Photographic equipment and

supplies.................................................... 84.9 65.1 50.6 –19.8 –34.3 –2.6 –5.0 131

Tires and inner tubes............................. 79.5 59.3 58.9 –20.2 –20.6 –2.9 –2.9 114

State and local government

hospitals................................................... 1,037.8 1,017.3 1,010.5 –20.5 –27.3 –.2 –.3 122

Petroleum refining................................. 100.2 79.5 72.2 –20.7 –28.0 –2.3 –3.2 123

Table 12. Continued—Actual and projected numerical wage and salary employment levels and growth, by industry, in order

 of fastest to slowest projected numerical growth, 1996–2006

Industry

Thousands of jobs Change, 

projected

Change, 

actual

Average 

annual rate 

of change, 

projected

Average 

annual rate 

of change, 

actual

Rank by 

actual 

numerical 

of change

1996 2006,

projected

2006, 

actual 1996–2006 1996–2006 1996–2006 1996–2006 1996–2006
Monthly Labor Review • September 2010 59

Table 12. Continued—Actual and projected numerical wage and salary employment levels and growth, by industry, in order

 of fastest to slowest projected numerical growth, 1996–2006

Industry

Thousands of jobs Change, 

projected

Change, 

actual

Average 

annual rate 

of change, 

projected

Average 

annual rate 

of change, 

actual

Rank by 

actual 

numerical 

change

1996 2006,

projected 2006, actual 1996–2006 1996–2006 1996–2006 1996–2006 1996–2006

Stone, clay, and miscellaneous

 mineral products................................... 164.1 143.1 135.1 –21.0 –29.0 –1.4 –1.9 126

Glass and glass products..................... 147.6 125.7 103.1 –21.9 –44.5 –1.6 –3.5 140

Oil and gas field services..................... 169.3 146.0 272.3 –23.3 103.0 –1.5 4.9 34

Household appliances.......................... 121.0 96.4 83.5 –24.6 –37.5 –2.2 –3.6 138

Gas utilities................................................ 180.3 155.0 217.8 –25.3 37.5 –1.5 1.9 47

Beverages.................................................. 178.5 149.3 171.4 –29.2 –7.1 –1.8 –.4 77

Railroad transportation........................ 231.1 201.8 231.6 –29.3 .5 –1.3 .0 65

Weaving, finishing, yarn, and

thread mills............................................. 332.0 301.2 144.5 –30.8 –187.5 –1.0 –8.0 173

Measuring and controlling devices. 297.0 265.0 268.4 –32.0 –28.6 –1.1 –1.0 124

Metal forgings and stampings........... 252.5 220.0 198.8 –32.5 –53.7 –1.4 –2.4 150

Motor vehicles and equipment......... 962.5 929.3 841.0 –33.2 –121.5 –.4 –1.3 166

Electrical industrial apparatus............ 156.0 122.4 108.7 –33.6 –47.3 –2.4 –3.5 143

Blast furnaces and basic steel

products.................................................. 240.3 196.7 161.8 –43.6 –78.5 –2.0 –3.9 156

Coal mining.............................................. 96.4 52.0 78.5 –44.4 –17.9 –6.0 –2.0 108

Crude petroleum, natural gas, and

gas liquids............................................... 148.2 101.5 134.9 –46.7 –13.3 –3.7 –0.9 97

Newspapers.............................................. 442.3 394.9 360.3 –47.4 –82.0 –1.1 –2.0 158

Computer and office equipment...... 363.0 313.7 217.8 –49.3 –145.2 –1.4 –5.0 172

Search and navigation equipment... 160.7 109.5 135.2 –51.2 –25.5 –3.8 –1.7 118

Depository institutions......................... 2,023.5 1,950.0 2,288.0 –73.5 264.5 –0.4 1.2 23

State and local government 

enterprises, not elsewhere 

classified.................................................. 598.2 490.2 1,575.9 –108.0 977.7 –2.0 10.2 6

Federal general government.............. 1,740.0 1,600.0 1,890.6 –140.0 150.6 –.8 .8 28

Private households................................. 928.0 775.2 802.5 –152.8 –125.5 –1.8 –1.4 168

Apparel....................................................... 642.9 475.1 189.5 –167.8 –453.4 –3.0 –11.5 174

Table 13. Accuracy metrics for all industries, 1996–2006 employment projections

Projection technique Direction of 

change

MAPE 

(unweighted) MAPE (weighted) Dissimilarity 

index

Spearman's rank correlation

For employment 

levels

For average 

annual percent 

change

BLS................................................ 72.4 24.7 11.7 5.9 0.60 0.59

Naïve............................................ 67.4 26.8 13.0 6.4 .56 .55

Which model performed

better?....................................... BLS BLS BLS BLS BLS BLS

Accuracy. Table 14 presents the results of both the 

overall accuracy of the BLS occupational projections and 

the accuracy by detailed occupation. The occupations 

evaluated accounted for about half of all employment in 

both the base (1996) and projection (2006) years. BLS 

correctly projected the direction of change for about 

two-thirds of the occupations. The fact that the weighted 

MAPE is lower than the unweighted MAPE means that 

the Bureau more accurately projected the employment of 

large occupations than that of small occupations, because 

weighting adjusts for the size of occupations. (See the 

note at the end of table 14.)

The dissimilarity index result shows that BLS was off by 

only 4.2 percent in projecting the distribution of employment among occupations. The dissimilarity index focuses 

on occupational employment shares and not levels of employment, and therefore it is not affected by errors in projecting the total level of employment. Since the dissimilarity index is not as skewed by large differences in a few 

occupations as MAPEs are, the result of the index is more 
Evaluating the 1996–2006 Projections

60 Monthly Labor Review • September 2010

Table 14. Actual and projected levels, and numeric and percent growth for wage and salary employment, by occupation,

 1996–2006

SOC 

code Occupation 1996 Projected, 2006

Actual, 

2006

Projected 

numeric 

change

Actual 

numeric 

change

Numeric 

difference b/t 

actual 

and projected

Projected 

percent 

change

Actual 

percent 

change

Sum of the occupations in the table ................................... 65,018,667 73,997,326 72,151,313 8,978,659 7,132,646 1,846,013 13.8 11.3 

Percent of all occupations....................................................... 49.1 49.0 47.9 48.3 39.0 ... ... ...

11–2000 Advertising, marketing, promotions, public relations, 

and sales managers................................................................. 482,044 619,597 582,664 137,553 100,620 36,933 28.5 20.9 

11–3031 Financial managers.................................................................... 800,060 946,468 506,347 146,408 –293,713 440,121 18.3 –36.7 

11–3040 Human resources managers................................................... 215,606 253,999 136,197 38,393 –79,409 117,802 17.8 –36.8 

11–3051 Industrial production managers........................................... 207,400 202,180 157,341 –5,219 –50,058 44,839 –2.5 –24.1 

11–3061 Purchasing managers............................................................... 232,463 250,644 69,526 18,181 –162,937 181,118 7.8 –70.1 

11–9021 Construction managers........................................................... 249,201 294,132 487,077 44,931 237,875 –192,944 18.0 95.5 

11–9030 Education administrators........................................................ 385,683 430,389 442,976 44,707 57,294 –12,587 11.6 14.9 

11–9061 Funeral directors......................................................................... 32,752 33,417 28,770 664 –3,982 4,647 2.0 –12.2 

11–9051/ 

11–9081 Food service managers/ lodging managers..................... 589,254 756,909 421,247 167,655 –168,006 335,662 28.5 –28.5 

13–1022 Wholesale and retail buyers, except farm products...... 182,625 182,507 156,568 –118 –26,056 25,938 –.1 –14.3 

13–1023 Purchasing agents, except wholesale, retail, and

farm products............................................................................ 224,043 238,446 287,429 14,403 63,386 –48,982 6.4 28.3 

13–1051 Cost estimators............................................................................ 187,944 217,154 221,100 29,210 33,156 –3,946 15.5 17.6 

13–2011 Accountants and auditors....................................................... 1,002,289 1,126,840 1,274,357 124,551 272,068 –147,517 12.4 27.1 

13–2031 Budget analysts........................................................................... 65,631 73,310 61,858 7,679 –3,773 11,452 11.7 –5.7 

13–2041 Credit analysts............................................................................. 39,611 45,877 67,132 6,266 27,521 –21,255 15.8 69.5 

13–2053 Insurance underwriters............................................................ 94,625 100,359 104,477 5,734 9,852 –4,118 6.1 10.4 

13–2070 Loan counselors and officers................................................. 209,035 267,709 405,939 58,674 196,905 –138,230 28.1 94.2 

13–2081 Tax examiners, collectors, and revenue agents............... 64,052 65,508 80,726 1,456 16,674 –15,217 2.3 26.0 

15–2011 Actuaries........................................................................................ 15,944 16,243 18,137 299 2,193 –1,894 1.9 13.8 

15–2041 Statisticians................................................................................... 13,818 13,912 22,416 94 8,598 –8,503 .7 62.2 

17–1011 Architects, except landscape and naval............................. 94,121 112,598 131,873 18,476 37,752 –19,275 19.6 40.1 

17–1012 Landscape architects................................................................ 16,672 20,124 27,839 3,452 11,167 –7,716 20.7 67.0 

17–2011 Aerospace engineers................................................................. 52,514 56,587 89,831 4,072 37,317 –33,244 7.8 71.1 

17–2041 Chemical engineers................................................................... 49,220 56,586 30,444 7,366 –18,776 26,142 15.0 –38.1 

17–2051 Civil engineers............................................................................. 196,135 231,301 256,330 35,167 60,195 –25,028 17.9 30.7 

17–2131 Materials engineers................................................................... 18,269 19,509 21,616 1,240 3,347 –2,107 6.8 18.3 

17–2141 Mechanical engineers............................................................... 227,861 263,826 225,797 35,965 –2,064 38,029 15.8 –.9 

17–2161 Nuclear engineers...................................................................... 13,642 14,346 15,273 704 1,631 –927 5.2 12.0 

17–2171 Petroleum engineers................................................................. 13,388 11,480 17,355 –1,908 3,967 –5,875 –14.3 29.6 

19–1010 Agricultural and food scientists............................................ 24,337 29,101 32,943 4,764 8,606 –3,842 19.6 35.4 

19–1020 Biological scientists................................................................... 82,580 103,270 86,646 20,690 4,066 16,624 25.1 4.9 

19–1040 Medical scientists....................................................................... 35,097 43,890 91,909 8,793 56,812 –48,019 25.1 161.9 

19–2010 Astronomers and physicists.................................................... 17,769 17,478 18,172 –290 403 –694 –1.6 2.3 

19–2021 Atmospheric and space scientists........................................ 7,330 7,931 8,759 601 1,429 –828 8.2 19.5 

19–2031 Chemists........................................................................................ 91,088 107,738 83,697 16,650 –7,391 24,041 18.3 –8.1 

19–2042/ 

19–2043

Geoscientists, except hydrologists and 

geographers/hydrologists.................................................... 47,409 54,347 39,375 6,937 –8,034 14,972 14.6 –16.9 

19–3030 Psychologists............................................................................... 142,833 154,215 165,915 11,381 23,082 –11,700 8.0 16.2 

19–3051 Urban and regional planners................................................. 29,379 30,774 33,809 1,395 4,430 –3,035 4.7 15.1 

21–1012 Educational, vocational, and school counselors............. 175,180 208,556 259,543 33,376 84,363 –50,987 19.1 48.2 

21–2021 Directors, religious activities and education.................... 85,131 115,331 99,230 30,200 14,099 16,101 35.5 16.6 

23–1011 Lawyers.......................................................................................... 621,846 740,215 760,672 118,369 138,826 –20,457 19.0 22.3 

25–2021 Elementary school teachers, except special 

education.................................................................................... 1,490,734 1,644,104 1,540,159 153,370 49,426 103,945 10.3 3.3 

25–2022/ 

25–2031

Middle school teachers, except special and 

vocational education/ secondary school teachers, 

except special and vocational education........................ 1,406,048 1,718,181 1,695,608 312,133 289,559 22,574 22.2 20.6 

25–2040 Special education teachers..................................................... 407,018 647,674 458,916 240,655 51,898 188,758 59.1 12.8 

25–4010 Archivists, curators, and museum technicians................. 19,919 22,854 27,487 2,934 7,568 –4,633 14.7 38.0 

25–4021 Librarians....................................................................................... 154,482 161,820 158,373 7,338 3,891 3,447 4.8 2.5 

See note at end of table.
Monthly Labor Review • September 2010 61

25–9021 Farm and home management advisors............................. 16,072 9,916 14,969 –6,155 –1,103 –5,053 –38.3 –6.9 

27–1010 Artists and related workers..................................................... 276,229 354,416 218,131 78,187 –58,099 136,285 28.3 –21.0 

27–1021/ 

27–1022/ 

27–1023/ 

27–1024/ 

27–1027/ 

27–1029

Commercial and industrial designers/ fashion 

designers/ floral designers/ graphic designers/ set

 and exhibit designers/ designers, all other................... 279,142 350,987 444,375 71,846 165,233 –93,387 25.7 59.2 

27–1025 Interior designers....................................................................... 62,861 80,136 71,856 17,275 8,995 8,280 27.5 14.3 

27–2010/ 

27–2099

Actors, producers, and directors/ entertainers and

performers, sports and related workers, all other........ 105,149 129,978 240,179 24,828 135,029 –110,201 23.6 128.4 

27–2030 Dancers and choreographers................................................. 23,362 29,910 40,196 6,548 16,834 –10,286 28.0 72.1 

27–3022 Reporters and correspondents.............................................. 59,847 57,995 59,212 –1,852 –635 –1,217 –3.1 –1.1 

27–3031 Public relations specialists...................................................... 110,375 140,381 243,275 30,006 132,899 –102,893 27.2 120.4 

27–4021 Photographers............................................................................. 134,219 157,406 122,480 23,187 –11,739 34,926 17.3 –8.7 

27–4031 Camera operators, television, video, and motion

picture.......................................................................................... 20,042 22,953 26,897 2,911 6,854 –3,943 14.5 34.2 

29–1011 Chiropractors............................................................................... 43,663 55,478 52,725 11,815 9,062 2,754 27.1 20.8 

29–1020 Dentists.......................................................................................... 162,206 175,363 161,127 13,157 –1,079 14,236 8.1 –.7 

29–1031 Dietitians and nutritionists..................................................... 58,027 68,597 57,126 10,570 –901 11,471 18.2 –1.6 

29–1041 Optometrists................................................................................ 41,253 46,090 32,740 4,837 –8,513 13,350 11.7 –20.6 

29–1051 Pharmacists.................................................................................. 171,864 193,507 243,482 21,642 71,617 –49,975 12.6 41.7 

29–1060 Physicians and surgeons.......................................................... 560,378 677,917 633,292 117,539 72,914 44,625 21.0 13.0 

29–1071 Physician assistants................................................................... 63,762 93,485 65,628 29,723 1,866 27,857 46.6 2.9 

29–1081 Podiatrists...................................................................................... 11,344 12,493 11,944 1,150 600 549 10.1 5.3 

29–1111 Registered nurses....................................................................... 1,971,433 2,382,280 2,504,664 410,848 533,231 –122,383 20.8 27.0 

29–1121/ 

29–1127 Audiologists/ speech-language pathologists.................. 87,280 131,451 121,929 44,172 34,650 9,522 50.6 39.7 

29–1122 Occupational therapists........................................................... 57,361 95,259 98,858 37,899 41,497 –3,598 66.1 72.3 

29–1123 Physical therapists...................................................................... 114,514 195,618 172,948 81,104 58,433 22,670 70.8 51.0 

29–1125 Recreational therapists............................................................. 37,650 45,679 25,115 8,029 –12,536 20,564 21.3 –33.3 

29–1126 Respiratory therapists............................................................... 81,822 119,286 102,406 37,464 20,584 16,880 45.8 25.2 

29–1131 Veterinarians................................................................................ 58,143 71,313 62,196 13,171 4,053 9,117 22.7 7.0 

29–2021 Dental hygienists........................................................................ 132,834 196,849 167,017 64,015 34,183 29,832 48.2 25.7 

29–2031 Cardiovascular technologists and technicians................ 32,061 34,471 45,378 2,410 13,317 –10,907 7.5 41.5 

29–2033 Nuclear medicine technologists........................................... 12,881 14,600 19,850 1,719 6,969 –5,250 13.3 54.1 

29–2041 Emergency medical technicians and paramedics.......... 149,662 217,092 201,099 67,431 51,437 15,994 45.1 34.4 

29–2052 Pharmacy technicians............................................................... 82,635 91,848 285,035 9,213 202,401 –193,187 11.1 244.9 

29–2053 Psychiatric technicians............................................................. 66,347 72,380 62,098 6,033 –4,250 10,283 9.1 –6.4 

29–2055 Surgical technologists.............................................................. 48,594 64,081 86,197 15,487 37,603 –22,116 31.9 77.4 

29–2061 Licensed practical and licensed vocational nurses........ 699,119 847,513 748,605 148,394 49,486 98,908 21.2 7.1 

29–2071 Medical records and health Information technicians... 87,347 131,827 169,742 44,480 82,395 –37,915 50.9 94.3 

29–2081 Opticians, dispensing................................................................ 66,642 76,064 65,904 9,422 –738 10,160 14.1 –1.1 

31–1011 Home health aides..................................................................... 494,685 872,893 787,315 378,208 292,629 85,578 76.5 59.2 

31–1012 Nursing aides, orderlies, and attendants........................... 1,312,136 1,645,133 1,447,233 332,997 135,097 197,900 25.4 10.3 

31–1013 Psychiatric aides.......................................................................... 103,072 111,969 61,735 8,898 –41,337 50,235 8.6 –40.1 

31–2010 Occupational therapist assistants and aides.................... 15,662 26,420 33,216 10,758 17,554 –6,796 68.7 112.1 

31–2020 Physical therapist assistants and aides............................... 84,482 150,854 106,538 66,372 22,057 44,316 78.6 26.1 

31–9091 Dental assistants......................................................................... 201,622 278,425 279,828 76,803 78,206 –1,403 38.1 38.8 

31–9095 Pharmacy aides........................................................................... 47,207 52,249 50,394 5,042 3,188 1,854 10.7 6.8 

33–1021 First-line supervisors/managers of firefighting and 

prevention workers................................................................. 53,532 54,128 52,468 596 –1,064 1,660 1.1 –2.0 

33–2011 Firefighters.................................................................................... 224,761 238,500 292,876 13,738 68,115 –54,377 6.1 30.3 

33–3012 Correctional officers and jailers............................................. 320,122 423,444 441,761 103,322 121,639 –18,317 32.3 38.0 

33–3051 Police and sheriff's patrol officers......................................... 500,866 582,432 648,418 81,566 147,552 –65,986 16.3 29.5 

33–9021/ 

33–9031

Private detectives and investigators/ gaming 

surveillance officers and gaming investigators............ 58,051 68,780 60,352 10,729 2,300 8,428 18.5 4.0 

33–9032 Security guards........................................................................... 954,644 1,175,257 1,040,287 220,613 85,643 134,969 23.1 9.0 

See note at end of table.

Table 14. Continued—Actual and projected levels, and numeric and percent growth for wage and salary employment, 

 by occupation,1996–2006

SOC 

code Occupation 1996 Projected, 2006

Actual, 

2006

Projected 

numeric 

change

Actual 

numeric 

change

Numeric 

difference b/t 

actual 

and projected

Projected 

percent 

change

Actual 

percent 

change
Evaluating the 1996–2006 Projections

62 Monthly Labor Review • September 2010

33–9091 Crossing guards.......................................................................... 60,543 54,962 69,320 –5,580 8,777 –14,357 –9.2 14.5 

35–2012 Cooks, institution and cafeteria ............................................ 434,708 455,279 401,027 20,571 –33,681 54,252 4.7 –7.7 

35–2014/ 

35–2019 Cooks, restaurant/cooks, all other........................................ 727,104 833,234 865,931 106,129 138,827 –32,697 14.6 19.1 

35–2021/ 

35–9021 Food preparation workers/ dishwashers........................... 1,253,240 1,487,158 1,419,018 233,917 165,778 68,140 18.7 13.2 

35–3011 Bartenders..................................................................................... 390,433 392,096 495,307 1,663 104,875 –103,211 .4 26.9 

35–3031 Waiters and waitresses............................................................. 1,956,833 2,162,914 2,360,630 206,081 403,797 –197,716 10.5 20.6 

35–9011 Dining room and cafeteria attendants and bartender

helpers......................................................................................... 438,539 500,536 416,276 61,997 –22,263 84,260 14.1 –5.1 

35–9031 Hosts and hostesses, restaurant, lounge, and coffee

shop.............................................................................................. 260,316 277,826 351,188 17,510 90,872 –73,362 6.7 34.9 

37–1011 First-line supervisors/managers of housekeeping

and janitorial workers............................................................. 108,452 114,671 282,237 6,219 173,785 –167,565 5.7 160.2 

37–2021 Pest control workers.................................................................. 59,710 72,974 69,722 13,264 10,012 3,252 22.2 16.8 

37–3012 Pesticide handlers, sprayers, and applicators, 

vegetation .................................................................................. 17,617 21,357 30,605 3,740 12,988 –9,249 21.2 73.7 

37–3013 Tree trimmers and pruners..................................................... 25,598 29,753 40,560 4,155 14,962 –10,807 16.2 58.5 

39–3021 Motion picture projectionists................................................ 8,382 4,604 11,493 –3,778 3,111 –6,889 –45.1 37.1 

39–3031 Ushers, lobby attendants, and ticket takers...................... 64,181 82,389 103,166 18,208 38,986 –20,777 28.4 60.7 

39–5011 Barbers........................................................................................... 59,453 53,737 60,034 –5,716 581 –6,297 –9.6 1.0 

39–5012/ 

39–5091/ 

39–5094

Hairdressers, hairstylists, and cosmetologists/ 

makeup artists, theatrical and performance/ skin 

care specialists.......................................................................... 585,729 643,665 657,807 57,937 72,078 –14,142 9.9 12.3 

39–5092 Manicurists and pedicurists.................................................... 43,123 62,402 78,121 19,279 34,997 –15,718 44.7 81.2 

39–5093 Shampooers................................................................................. 12,600 13,490 29,428 890 16,828 –15,938 7.1 133.5 

39–6011 Baggage porters and bellhops.............................................. 37,815 39,874 49,319 2,059 11,504 –9,445 5.4 30.4 

39–6031 Flight attendants........................................................................ 131,808 178,107 96,730 46,299 –35,078 81,378 35.1 –26.6 

39–9011 Child care workers...................................................................... 829,697 1,128,885 1,388,168 299,188 558,471 –259,283 36.1 67.3 

39–9021 Personal and home care aides............................................... 202,459 373,856 767,257 171,396 564,798 –393,401 84.7 279.0 

41–1010 First-line supervisors/managers, sales workers............... 2,315,560 2,561,901 2,205,894 246,341 –109,666 356,006 10.6 –4.7 

41–2021 Counter and rental clerks........................................................ 373,817 457,958 476,623 84,141 102,806 –18,666 22.5 27.5 

41–2031 Retail salespersons..................................................................... 4,072,266 4,480,520 4,476,942 408,253 404,676 3,577 10.0 9.9 

41–3031 Securities, commodities, and financial services sales

agents........................................................................................... 263,265 362,899 319,943 99,633 56,677 42,956 37.8 21.5 

41–3041 Travel agents................................................................................ 142,296 176,440 101,167 34,143 –41,129 75,272 24.0 –28.9 

41–9021 Real estate brokers..................................................................... 77,683 88,668 131,239 10,986 53,556 –42,571 14.1 68.9 

43–1011 First-line supervisors/managers of office and 

administrative support workers......................................... 1,368,631 1,630,133 1,418,494 261,502 49,863 211,639 19.1 3.6 

43–2011 Switchboard operators, including answering service... 237,468 246,171 177,485 8,703 –59,982 68,686 3.7 –25.3 

43–2021 Telephone operators................................................................. 81,437 43,152 26,681 –38,285 –54,757 16,472 –47.0 –67.2 

43–3011 Bill and account collectors...................................................... 268,645 381,058 434,200 112,413 165,556 –53,142 41.8 61.6 

43–3021 Billing and posting clerks and machine operators......... 462,764 515,857 541,869 53,093 79,105 –26,012 11.5 17.1 

43–3031 Bookkeeping, accounting, and auditing clerks............... 2,249,521 2,147,315 2,113,780 –102,206 –135,742 33,536 –4.5 –6.0 

43–3051 Payroll and timekeeping clerks............................................. 160,985 151,429 213,612 –9,555 52,628 –62,183 –5.9 32.7 

43–3061 Procurement clerks.................................................................... 56,382 55,289 77,798 –1,094 21,416 –22,509 –1.9 38.0 

43–3071 Tellers.............................................................................................. 545,419 550,040 607,609 4,620 62,189 –57,569 .8 11.4 

43–4011 Brokerage clerks.......................................................................... 76,380 90,965 73,309 14,585 –3,071 17,656 19.1 –4.0 

43–4071 File clerks....................................................................................... 293,030 314,743 233,808 21,713 –59,222 80,936 7.4 –20.2 

43–4081 Hotel, motel, and resort desk clerks.................................... 143,553 173,729 218,776 30,176 75,223 –45,047 21.0 52.4 

43–4141 New accounts clerks.................................................................. 110,015 115,009 81,422 4,993 –28,594 33,587 4.5 –26.0 

43–4161 Human resources assistants, except payroll and

timekeeping............................................................................... 123,830 125,602 168,201 1,771 44,371 –42,599 1.4 35.8 

43–4171 Receptionists and information clerks................................. 1,073,745 1,392,219 1,172,666 318,474 98,921 219,553 29.7 9.2 

43–5021 Couriers and messengers........................................................ 138,471 154,122 133,770 15,651 –4,701 20,352 11.3 –3.4 

43–5031 Police, fire, and ambulance dispatchers............................. 85,976 92,597 99,053 6,621 13,077 –6,456 7.7 15.2 

See note at end of table.

Table 14. Continued—Actual and projected levels, and numeric and percent growth for wage and salary employment, 

 by occupation,1996–2006

SOC 

code Occupation 1996 Projected, 2006

Actual, 

2006

Projected 

numeric 

change

Actual 

numeric 

change

Numeric 

difference b/t 

actual 

and projected

Projected 

percent 

change

Actual 

percent 

change
Monthly Labor Review • September 2010 63

43–5032 Dispatchers, except police, fire, and ambulance............. 148,456 165,441 190,231 16,985 41,775 –24,790 11.4 28.1 

43–5041 Meter readers, utilities.............................................................. 55,037 56,263 46,574 1,226 –8,463 9,689 2.2 –15.4 

43–5051 Postal service clerks................................................................... 71,435 74,169 79,505 2,734 8,071 –5,336 3.8 11.3 

43–5052 Postal service mail carriers...................................................... 331,553 368,560 337,768 37,007 6,215 30,791 11.2 1.9 

43–5061 Production, planning, and expediting clerks................... 238,846 253,826 292,794 14,979 53,948 –38,968 6.3 22.6 

43–5071 Shipping, receiving, and traffic clerks................................. 984,773 1,069,634 768,974 84,861 –215,799 300,660 8.6 –21.9 

43–5111 Weighers, measurers, checkers, and samplers, 

recordkeeping........................................................................... 47,488 50,362 79,021 2,874 31,533 –28,659 6.1 66.4 

43–6011/ 

43–6014

Executive secretaries and administrative assistants/

secretaries, except legal, medical, and executive......... 2,880,586 2,793,854 3,557,855 –86,732 677,269 –764,001 –3.0 23.5 

43–6012 Legal secretaries......................................................................... 283,673 319,162 275,269 35,489 –8,404 43,893 12.5 –3.0 

43–6013 Medical secretaries.................................................................... 238,690 314,454 408,369 75,764 169,679 –93,914 31.7 71.1 

43–9011 Computer operators.................................................................. 291,123 197,606 129,997 –93,518 –161,127 67,609 –32.1 –55.3 

43–9021 Data entry keyers........................................................................ 435,608 462,453 313,355 26,845 –122,253 149,098 6.2 –28.1 

43–9022 Word processors and typists.................................................. 652,543 552,075 178,998 –100,468 –473,545 373,077 –15.4 –72.6 

43–9031 Desktop publishers.................................................................... 30,446 52,837 31,833 22,391 1,387 21,004 73.5 4.6 

43–9061 Office clerks, general................................................................. 3,134,416 3,351,296 3,200,245 216,880 65,830 151,051 6.9 2.1 

43–9081 Proofreaders and copy markers............................................ 26,094 16,052 17,856 –10,042 –8,238 –1,805 –38.5 –31.6 

43–9111 Statistical assistants................................................................... 78,111 64,625 22,507 –13,486 –55,604 42,118 –17.3 –71.2 

45–4022 Logging equipment operators.............................................. 54,373 56,338 40,496 1,965 –13,877 15,842 3.6 –25.5 

47–2011 Boilermakers................................................................................ 18,293 17,699 17,571 –594 –722 128 –3.2 –3.9 

47–2041 Carpet installers.......................................................................... 64,400 72,235 73,205 7,836 8,805 –969 12.2 13.7 

47–2071 Paving, surfacing, and tamping equipment operators 79,300 103,027 64,255 23,727 –15,045 38,772 29.9 –19.0 

47–2073 Operating engineers and other construction 

equipment operators............................................................. 263,871 291,099 424,152 27,228 160,281 –133,053 10.3 60.7 

47–2130 Insulation workers...................................................................... 65,007 77,572 60,859 12,565 –4,148 16,713 19.3 –6.4 

47–2140 Painters and paperhangers..................................................... 443,720 509,293 472,732 65,573 29,013 36,561 14.8 6.5 

47–2161 Plasterers and stucco masons................................................ 31,871 36,104 61,148 4,233 29,277 –25,044 13.3 91.9 

47–2181 Roofers........................................................................................... 138,141 144,101 156,284 5,960 18,143 –12,183 4.3 13.1 

47–4011 Construction and building inspectors................................ 66,265 75,863 109,730 9,598 43,465 –33,867 14.5 65.6 

47–4021 Elevator installers and repairers............................................ 25,187 27,209 21,830 2,022 –3,357 5,379 8.0 –13.3 

47–4051 Highway maintenance workers............................................ 171,386 157,786 145,216 –13,600 –26,170 12,570 –7.9 –15.3 

47–5071 Roustabouts, oil and gas.......................................................... 27,806 18,437 44,085 –9,370 16,278 –25,648 –33.7 58.5 

49–2021 Radio mechanics......................................................................... 7,973 7,396 6,533 –577 –1,440 863 –7.2 –18.1 

49–2097 Electronic home entertainment equipment installers

 and repairers.............................................................................. 32,832 26,590 39,700 –6,242 6,869 –13,111 –19.0 20.9 

49–3011 Aircraft mechanics and service technicians...................... 136,643 154,683 122,472 18,040 –14,171 32,211 13.2 –10.4 

49–3021/ 

49–3022

Automotive body and related repairers/ automotive

glass installers and repairers................................................ 224,690 253,557 206,286 28,867 –18,404 47,271 12.8 –8.2 

49–3023 Automotive service technicians and mechanics............ 775,440 871,266 772,675 95,826 –2,765 98,591 12.4 –.4 

49–3031 Bus and truck mechanics and diesel engine 

specialists.................................................................................... 266,179 288,072 274,876 21,893 8,697 13,196 8.2 3.3 

49–3041 Farm equipment mechanics................................................... 44,098 37,084 30,672 –7,014 –13,426 6,412 –15.9 –30.4 

49–3042 Mobile heavy equipment mechanics, except engines. 104,349 111,114 130,570 6,765 26,220 –19,455 6.5 25.1 

49–3052 Motorcycle mechanics.............................................................. 11,947 12,627 21,211 680 9,264 –8,584 5.7 77.5 

49–3091 Bicycle repairers.......................................................................... 12,759 17,028 8,644 4,269 –4,115 8,384 33.5 –32.3 

49–3093 Tire repairers and changers.................................................... 94,283 100,853 105,842 6,570 11,559 –4,989 7.0 12.3 

49–9021 Heating, air conditioning, and refrigeration 

mechanics and Installers....................................................... 256,396 299,926 291,861 43,530 35,465 8,065 17.0 13.8 

49–9042 Maintenance and repair workers, general......................... 1,362,102 1,607,860 1,390,952 245,758 28,850 216,907 18.0 2.1 

49–9044 Millwrights.................................................................................... 77,999 76,319 54,884 –1,681 –23,115 21,434 –2.2 –29.6 

49–9051 Electrical power-line installers and repairers................... 108,081 111,330 112,183 3,249 4,102 –853 3.0 3.8 

49–9052 Telecommunications line Installers and repairers.......... 200,621 241,652 162,317 41,032 –38,303 79,335 20.5 –19.1 

49–9061 Camera and photographic equipment repairers............ 14,293 17,718 4,403 3,425 –9,890 13,315 24.0 –69.2 

49–9062 Medical equipment repairers................................................. 9,736 10,877 37,645 1,140 27,909 –26,769 11.7 286.6 

49–9063 Musical instrument repairers and tuners........................... 8,987 9,652 5,998 665 –2,989 3,654 7.4 –33.3 

49–9064 Watch repairers........................................................................... 7,353 6,977 3,814 –376 –3,538 3,162 –5.1 –48.1 

See note at end of table.

Table 14. Continued—Actual and projected levels, and numeric and percent growth for wage and salary employment, 

 by occupation, 1996–2006

SOC 

code Occupation 1996 Projected, 2006

Actual 

2006

Projected 

numeric 

change

Actual 

numeric 

change

Numeric 

difference b/t 

actual 

and projected

Projected 

percent 

change

Actual 

percent 

change
Evaluating the 1996–2006 Projections

64 Monthly Labor Review • September 2010

49–9069 Precision instrument and equipment repairers, all 

other............................................................................................. 38,449 37,600 16,327 –850 –22,122 21,273 –2.2 –57.5 

49–9094 Locksmiths and safe repairers................................................ 25,000 28,746 26,018 3,746 1,018 2,727 15.0 4.1 

49–9096 Riggers........................................................................................... 9,274 7,582 12,315 –1,693 3,040 –4,733 –18.3 32.8 

51–2011 Aircraft structure, surfaces, rigging, and systems

assemblers.................................................................................. 24,649 27,091 28,083 2,443 3,434 –991 9.9 13.9 

51–2021 Coil winders, tapers, and finishers........................................ 21,697 20,996 22,835 –701 1,139 –1,839 –3.2 5.2 

51–3011 Bakers............................................................................................. 226,486 277,761 149,266 51,275 –77,220 128,495 22.6 –34.1 

51–3022 Meat, poultry, and fish cutters and trimmers................... 151,452 186,225 144,228 34,773 –7,224 41,997 23.0 –4.8 

51–4051 Metal-refining furnace operators and tenders................ 20,889 19,939 18,386 –951 –2,503 1,552 –4.6 –12.0 

51–4111 Tool and die makers.................................................................. 133,908 124,475 100,788 –9,433 –33,120 23,687 –7.0 –24.7 

51–4121 Welders, cutters, solderers, and brazers............................. 378,391 415,515 409,024 37,124 30,633 6,491 9.8 8.1 

51–5012 Bookbinders................................................................................. 4,386 3,729 7,211 –657 2,826 –3,482 –15.0 64.4 

51–5021 Job printers................................................................................... 14,693 15,410 48,240 717 33,548 –32,830 4.9 228.3 

51–6031 Sewing machine operators..................................................... 582,975 462,222 232,810 –120,752 –350,165 229,412 –20.7 –60.1 

51–6052 Tailors, dressmakers, and custom sewers.......................... 87,346 72,735 53,910 –14,612 –33,436 18,825 –16.7 –38.3 

51–6092 Fabric and apparel patternmakers....................................... 14,382 13,911 9,209 –471 –5,174 4,703 –3.3 –36.0 

51–6093 Upholsterers................................................................................. 56,585 56,838 54,809 253 –1,776 2,029 0.4 –3.1 

51–7021 Furniture finishers...................................................................... 29,753 33,178 31,326 3,425 1,573 1,851 11.5 5.3 

51–8012 Power distributors and dispatchers..................................... 15,421 14,845 8,571 –576 –6,850 6,274 –3.7 –44.4 

51–8031 Water and liquid waste treatment plant and system

 operators.................................................................................... 98,290 121,070 110,840 22,779 12,549 10,230 23.2 12.8 

51–8091 Chemical plant and system operators................................ 36,485 36,206 53,243 –279 16,758 –17,037 –.8 45.9 

51–9012 Separating, filtering, clarifying, precipitating, and 

still machine setters, operators, and tenders................. 31,879 29,030 44,289 –2,849 12,410 –15,259 –8.9 38.9 

51–9021/ 

51–9023

Crushing, grinding, and polishing machine setters,

operators, and tenders/ mixing and blending 

machine setters, operators, and tenders......................... 144,610 144,202 185,326 –409 40,716 –41,125 –.3 28.2 

51–9022 Grinding and polishing workers, hand............................... 73,752 72,297 44,776 –1,455 –28,976 27,521 –2.0 –39.3 

51–9051 Furnace, kiln, oven, drier, and kettle operators and

 tenders........................................................................................ 27,970 25,368 31,596 –2,603 3,625 –6,228 –9.3 13.0 

51–9081 Dental laboratory technicians............................................... 47,337 47,671 53,439 335 6,102 –5,767 .7 12.9 

51–9083 Ophthalmic laboratory technicians..................................... 19,022 19,094 29,064 72 10,042 –9,970 .4 52.8 

51–9122 Painters, transportation equipment.................................... 49,187 58,465 54,322 9,278 5,135 4,143 18.9 10.4 

51–9131 Photographic process workers.............................................. 14,108 13,725 23,684 –383 9,576 –9,958 –2.7 67.9 

51–9132 Photographic processing machine operators................. 49,385 53,349 49,304 3,964 –81 4,045 8.0 –.2 

51–9141 Semiconductor processors..................................................... 58,276 65,427 42,397 7,150 –15,880 23,030 12.3 –27.2 

51–9191 Cementing and gluing machine operators and

tenders........................................................................................ 35,182 29,713 23,362 –5,469 –11,820 6,351 –15.5 –33.6 

51–9196 Paper goods machine setters, operators, and tenders. 51,255 43,799 113,107 –7,456 61,852 –69,308 –14.5 120.7 

51–9197 Tire builders.................................................................................. 14,433 12,274 22,664 –2,159 8,231 –10,389 –15.0 57.0 

53–2010 Airline pilots and flight engineers........................................ 110,007 125,166 107,040 15,159 –2,967 18,126 13.8 –2.7 

53–2020 Air traffic controllers and airfield operations 

specialists.................................................................................... 28,894 28,808 30,115 –86 1,221 –1,307 –.3 4.2 

53–3011 Ambulance drivers and attendants, except 

emergency medical technicians......................................... 18,394 25,102 21,538 6,709 3,145 3,564 36.5 17.1 

53–3021 Bus drivers, transit and intercity............................................ 167,108 191,568 198,488 24,460 31,380 –6,920 14.6 18.8 

53–3022 Bus drivers, school...................................................................... 425,238 518,042 454,800 92,804 29,562 63,242 21.8 7.0 

53–3031 Driver/sales workers.................................................................. 331,173 369,721 445,092 38,548 113,919 –75,371 11.6 34.4 

53–3041 Taxi drivers and chauffeurs..................................................... 106,338 114,402 228,531 8,064 122,193 –114,129 7.6 114.9 

53–3099 Motor vehicle operators, all other........................................ 26,705 27,594 75,942 889 49,237 –48,348 3.3 184.4 

53–4021 Railroad brake, signal, and switch operators.................... 17,792 12,771 24,609 –5,021 6,817 –11,838 –28.2 38.3 

53–4031 Railroad conductors and yardmasters................................ 25,330 24,872 40,152 –458 14,823 –15,280 –1.8 58.5 

53–4041 Subway and streetcar operators........................................... 12,864 14,043 6,936 1,179 –5,927 7,107 9.2 –46.1 

53–5031 Ship engineers............................................................................. 8,727 8,154 14,797 –573 6,070 –6,643 –6.6 69.6 

53–6021 Parking lot attendants.............................................................. 68,299 86,161 135,204 17,862 66,904 –49,042 26.2 98.0 

53–6031 Service station attendants...................................................... 173,794 174,043 96,199 249 –77,595 77,844 .1 –44.6 

53–7021 Crane and tower operators..................................................... 45,477 44,977 46,393 –500 916 –1,416 –1.1 2.0 

See note at end of table.

Table 14. Continued—Actual and projected levels, and numeric and percent growth for wage and salary employment, 

 by occupation, 1996–2006

SOC 

code Occupation 1996 Projected, 2006

Actual, 

2006

Projected 

numeric 

change

Actual 

numeric 

change

Numeric 

difference b/t 

actual 

and projected

Projected 

percent 

change

Actual 

percent 

change
Monthly Labor Review • September 2010 65

53–7041 Hoist and winch operators........................................ 9,484 9,938 3,017 455 –6,467 6,922 4.8 –68.2 

53–7051 Industrial truck and tractor operators................... 479,088 536,244 637,034 57,156 157,945 –100,790 11.9 33.0 

53–7061 Cleaners of vehicles and equipment..................... 274,177 343,338 368,216 69,160 94,038 –24,878 25.2 34.3 

53–7063 Machine feeders and offbearers............................. 265,273 263,119 147,763 –2,154 –117,510 115,356 –.8 –44.3 

53–7064 Packers and packagers, hand................................... 986,099 1,207,983 833,812 221,883 –152,287 374,171 22.5 –15.4 

53–7081 Refuse and recyclable material collectors........... 115,705 122,654 135,970 6,949 20,265 –13,317 6.0 17.5 

NOTE: For the sum of the occupations in the table, the unweighted mean absolute percent error, weighted mean absolute percent error, direction of 

change, and dissimilarity index are the following, respectively: 31.4 percent, 17.6 percent, 67.1 percent, and 4.2 percent.

Table 14. Continued—Actual and projected levels, and numeric and percent growth for wage and salary employment, 

 by occupation, 1996–2006

SOC 

code Occupation 1996 Projected, 2006

Actual 

2006

Projected 

numeric 

change

Actual 

numeric 

change

Numeric 

difference b/t 

actual 

and projected

Projected 

percent 

change

Actual 

percent 

change

indicative of the difference between actual and projected 

employment for a typical occupation. (For more information on the metrics used in this article, see the metrics 

section in the appendix.) 

As previously mentioned, some errors in projecting occupational employment can be attributed to an imperfect 

OES–SOC crosswalk. The decline in the overall number of 

managers resulted in BLS overprojecting employment in 

seven of the nine managerial occupations included in this 

analysis, and also resulted in the unweighted MAPE for 

managerial occupations, 67 percent, being more than double the unweighted MAPE for all occupations, 31 percent. 

Only two managerial occupations were underprojected: 

education administrators, by 3 percent, and construction 

managers, by 40 percent.

Macroeconomic fluctuations that affected the accuracy 

of the industry projections also affected the occupational 

projections. Because of the housing bubble, BLS underprojected the employment of most construction-related 

occupations, not just that of construction managers. The 

Bureau underprojected the employment of architects, 

landscape architects, civil engineers, operating engineers 

Table 15. BLS occupational employment projections compared with those of naïve models, 1996–2006

Model Dissimilarity 

index (percent)

Unweighted 

MAPE1 (percent)

Weighted MAPE1

(percent)

Direction of change 

(percent)

BLS projection............................................................................................. 7.6 26.9 15.3 66.2

Naïve 2-point, 10-year linear model.................................................. 9.6 32.3 21.2 66.9

Naïve 2-point, 5-year linear model..................................................... 9.5 32.4 20.2 64.0

Naïve linear regression model.............................................................. 7.9 28.9 16.1 64.7

Naïve static model..................................................................................... 8.1 29.0 16.4 67.7

Which forecast performed best?.......................................................... BLS BLS BLS Static model

Second best?................................................................................................ Linear regression Linear regression Linear regression 2-point, 10-year forecast

1

 Mean absolute percent error.

and other construction equipment operators, plasterers 

and stucco masons, roofers, and construction and building inspectors. Underprojecting the price of oil led BLS to 

underproject the employment of petroleum engineers and 

that of oil and gas roustabouts. 

Naïve models. The level of accuracy of the BLS projections needs to be evaluated in comparison with the accuracy of alternative projections. Creating naïve models of 

the projections provides bases for comparison. The naïve 

models require additional historical data going back to 

1986, which further restricts the number of comparable 

occupations. This restriction led to the results in table 15 

not exactly matching the results in table 14. The Bureau 

created four different naïve models to create data to be 

compared with the original BLS occupational employment projections: (1) a two-point linear projection based 

on 1986 and 1996 data, (2) a two-point linear projection 

based on 1991 and 1996 data, (3) a linear regression projection based on 1986–1996 data, and (4) a static model 

which assumed that occupations would remain the same 

percentage of total employment in 2006 as they were in 
Evaluating the 1996–2006 Projections

66 Monthly Labor Review • September 2010

1996. As can be seen in table 15, the BLS projections were 

more accurate than all of the naïve models in three of four 

metrics. According to the direction-of-change metric, 

both the static model and the 10-year, two-point linear 

forecast outperformed the BLS projection. When evaluated across all the metrics used in this article, the BLS projection outperformed all of the naïve models. 

CHANGES IN DATA SERIES, definitions, and classification 

systems hampered this article’s analysis by decreasing the 

number of occupations available for analysis and creating 

substantial data comparison problems with regard to macroeconomic and industry employment data. Future evaluations, such as the analysis of the 2000–2010 projections, 

should be affected less by these types of changes because 

the NAICS and the SOC system have not undergone too 

many changes since 2000. Despite the data comparability 

problems, crosswalks and other adjustments to the data allowed this article to reasonably evaluate the accuracy of the 

projections and explain some of the causes of differences.

The differences between the projected size of the labor 

force and its actual size affected the macroeconomic 

projections more than they affected the industry and 

occupational employment projections because the latter 

projections focus more on the distributional nature of 

employment (what percent of total jobs are in a given 

industry or occupation) than on the total number of jobs. 

Compared with the differences in the projection of the 

labor force, large macroeconomic fluctuations—caused 

by the rise in the price of oil, two wars, and the housing 

bubble—caused larger problems in the industry and 

occupational employment projections. 

The housing bubble caused BLS to underproject the 

housing-related components of GDP, occupational employment, and industry employment projections, but data 

from 2007 onward suggest that part of the reason that they 

were off was that 2006 was near the peak of residential 

investment. The increase in the real oil price led to differences in several parts of the projections. In the future, BLS

could carefully examine oil price projections and perhaps 

present the results of alternative oil price scenarios as it did 

in the discussion of uncertainty about labor force growth 

and its impact on GDP in the original 1996–2006 projections article. 

Although the industry and occupational employment 

projections had weighted MAPEs of 11.7 percent and 17.6 

percent, respectively, they still outperformed comparable 

naïve models. In both the industry and occupational employment projections, the weighted MAPE was lower than 

the unweighted MAPE; that is, BLS was more accurate in 

projecting changes in the employment of large industries 

and occupations than changes in the employment of small 

industries and occupations. On the whole, the BLS 1996–

2006 labor force, occupational employment, and industry employment projections outperformed those of naïve 

models. 

Notes

1 Monthly Labor Review, November 1997, pp. 3–83.

2 For a complete list of the Bureau’s evaluations of its projections, 

see www.bls.gov/emp/ep_pub_projections_eval.htm (visited Sept. 1, 

2010). 

3 See H.O. Stekler and Rupin Thomas, “Evaluating BLS labor force, 

employment, and occupation projections for 2000,” Monthly Labor 

Review, July 2005, pp. 46–56, on the Internet at www.bls.gov/opub/

mlr/2005/07/art5full.pdf (visited Sept. 1, 2010).

4 See Michael E. Fix and Jeffrey S. Passel, “U.S. Immigration at the 

Beginning of the 21st Century,” (Washington, DC, Urban Institute, 

Aug. 2, 2001) on the Internet at www.urban.org/publications/900417.

html (visited May 25, 2010).

5 Annual Estimates of the Population by Sex, Race, and Hispanic or Latino Origin for the United States: April 1, 2000 to July 1, 2006 (Census 

Bureau), on the Internet at www.census.gov/popest/national/asrh/

NC-EST2006-srh.html (visited May 19, 2010).

6 One example of the changes to GDP involved computer software. 

In 1999 historical GDP was revised upwards when certain business 

expenditures for computer software were reclassified as investments. 

Previously, only software embedded in equipment by the producer of 

that equipment was counted as investment. Business purchases for 

own-account production (that is, software produced by a business for 

its own use) had been classified as inputs to production.

7 Government purchases of own-account production of software 

(software produced by a government agency for its own use) shifted 

from one category of GDP, government consumption expenditures, to 

another category, gross government investment.

8 Divisions in the SIC system are comparable to sectors in the NAICS. 

Because of data comparability issues, some of the industry divisions 

used in this article are not perfectly comparable to the divisions used in 

the November 1997 issue of the Monthly Labor Review or to the divisions in the official SIC manual. The transportation, communications, 

electric, gas, and sanitary services division was broken into three parts: 

transportation, communications, and utilities. The wholesale trade and 

retail trade divisions were combined into the trade sector. Federal Government is treated as a division, as is State and local government. The 

individual industries referred to in this article are a mix of two-digit 

and three-digit SIC industries.

9 The tables used to convert the NAICS-based CES data to an SIC

basis can be found on the Internet at www.bls.gov/ces/cesratiosemp.

htm (visited Sept. 1, 2010).
Monthly Labor Review • September 2010 67

19 Ibid, pp. 18-21.

20 Ibid, pp. 21.

21 Unless otherwise noted, growth rates in this article are average 

annual growth rates.

22 Analysis of Petroleum Imports/Exports & Movements (U.S. Energy 

Information Administration), on the Internet at http://tonto.eia.doe.

gov/dnav/pet/pet_pub_analysis_move.asp (visited May 19, 2010).

23 “Oil Prices and the U.S. Trade Deficit” Economic Letter, Federal 

Reserve Bank of San Francisco, Sept. 22, 2006, on the Internet at www.

frbsf.org/publications/economics/letter/2006/el2006-24.html (visited May 19, 2010).

24 Chain-weighting changes altered the growth rate enough that 

when the original data (the row titled “original data, published in 1997 

(billions of chained 1992 dollars)” in table 7) were simply moved from a 

1992 real dollar basis to a 2000 real dollar basis (the row titled “original 

data (billions of chained 2000 dollars)” in table 7) the projected growth 

rate went from 2.1 percent to 2.5 percent. Since the historical growth 

rate for the 1986-1996 period was revised upwards from 2.3 percent to 

2.9 percent because of the switch from chained 1992 dollars to chained 

2000 dollars and definitional changes to GDP, it would be reasonable 

to estimate that the projected growth rate for the 1996–2006 period 

should be revised upwards by the same amount—from 2.1 percent to 

2.7 percent. (See the last row of table 7.) 

25 See Eric Belsky and Joel Prakken, Housing Wealth Effects: Housing’s 

Impact on Wealth Accumulation, Wealth Distribution and Consumer 

Spending ( Joint Center for Housing Studies, Harvard University, 

2004), on the Internet at www.jchs.harvard.edu/publications/

finance/w04-13.pdf (visited May 28, 2010).

26 Unpublished online survey, January 2010, conducted by Furniture 

Today and HGTV.

27 “Oil Prices and the U.S. Trade Deficit” Economic Letter, Federal 

Reserve Bank of San Francisco.

28 See Jian Wang, “Durable Goods and the Collapse of Global 

Trade,” Economic Letter—Insights from the Federal Reserve Bank of Dallas, February 2010, on the Internet at www.dallasfed.org/research/

eclett/2010/el1002.html (visited May 28, 2010).

29 Peter Orszag, Estimated Costs of U.S. Operations in Iraq and Afghanistan and of Other Activities Related to the War on Terrorism (Congressional Budget Office, Oct. 24, 2007), on the Internet at www.cbo.

gov/ftpdocs/86xx/doc8690/10-24-CostOfWar_Testimony.pdf (visited May 19, 2010).

30 The Budget and Economic Outlook: Fiscal Years 2004-2013 (Congressional Budget Office, January 2003), p. 2, on the Internet at www.

cbo.gov/ftpdocs/40xx/doc4032/EntireReport_WithErrata.pdf

(visited May 19, 2010).

31 The Budget and Economic Outlook: Fiscal Years 2006 to 2015 (Congressional Budget Office, January 2005), p. 55, on the Internet at www.

cbo.gov/ftpdocs/60xx/doc6060/01-25-BudgetOutlook.pdf (visited 

May 19, 2010).

32 Industry employment data in this analysis come from the Current Employment Statistics survey, which is limited to nonagricultural 

wage and salary employment.

10 The OES–SOC crosswalk identified four kinds of occupational 

matches:

1) one OES occupation to one SOC occupation

2) one OES occupation and more than one SOC occupation

3) more than one OES occupation to one SOC occupation

4) more than one OES occupation to more than one SOC occupation

The fourth type of occupational match was eliminated because 

the lack of dual-coded data meant that ratios for converting the 

occupations did not exist. The results of the other three types of 

crosswalk matches were evaluated, and a list was compiled to look for 

trends in detailed occupations that were projected poorly. By looking 

at the year-over-year growth of several of these occupations, it became 

clear that the crosswalk was imperfect and missed a few occupations 

that changed significantly—increasing or decreasing by large amounts 

in the single year that the new classification system was implemented. 

The analysis was limited to occupations that fell into the first three 

types of occupational matches and did not show broader changes that 

could be attributed to the change in classification systems. 

11 The original occupational employment projections article is the 

following: George T. Silvestri, “Occupational employment projections 

to 2006,” Monthly Labor Review, November 1997, on the Internet at 

www.bls.gov/opub/mlr/1997/11/art5full.pdf (visited Sept. 1, 2010).

12 BLS uses Census Bureau data to calculate the size of the civilian 

noninstitutional population by subtracting those who are under the age 

of 16, in the active-duty armed forces, or institutionalized.

13 Unless specified otherwise, in this article the term “men” refers 

to males 16 and older, and the term “women” refers to females 16 and 

older.

14 More information on the Census Bureau’s population projections 

is available on the Internet at www.census.gov/population/www/

projections/index.html (visited Sept. 1, 2010). 

15 Interview with Mitra Toossi on May 21, 2010. In addition, see 

Howard N. Fullerton Jr., “Evaluating the BLS labor force projections to 

2000,” Monthly Labor Review, October 2003, pp. 3–12; see especially 

p. 11. 

16 In the broad race category system currently employed by BLS, Native Americans, Pacific Islanders, Native Hawaiians, and Native Alaskans are grouped with the multiple race category in a category called 

multiple race and other. For the analysis in this article, the group was 

moved back to the Asian group to reflect the categories used in creating the 2006 projections. Because the multiple race group cannot, by 

definition, be assigned to a single race category, it was impossible to 

adjust this group to reflect the race categories used to create the 2006 

projections in 1996. 

17 See figure 2 on p. 4 of Michael Hoefer, Nancy Rytina, and Bryan 

C. Baker, “Estimates of the Unauthorized Immigrant Population Residing in the United States: January 2008” (Department of Homeland 

Security, February 2009), on the Internet at www.dhs.gov/xlibrary/

assets/statistics/publications/ois_ill_pe_2008.pdf (visited July 19, 

2010).

18 For a list of the key assumptions, see table 2 on p. 8 of Thomas 

Boustead, “The U.S. economy to 2006,” Monthly Labor Review, November 1997, p. 6–22.
Evaluating the 1996–2006 Projections

68 Monthly Labor Review • September 2010

Appendix: Metrics employed in the article

The naïve model. The objective of a naive model is to provide 

a benchmark to be used as a basis for comparison. For example, 

an evaluation of employment projections might reveal that BLS 

was off by 10 percent in a particular projection. A naïve model 

is necessary to determine whether that 10 percent error is a 

reasonable level of error. The following four naïve projection 

models were employed in this article:

•	 Ten-year, two-point linear model. One basic way of projecting the labor force by demographic group and projecting employment by occupation or industry assumes that 

the growth rate of an occupation over the next 10 years 

will be equal to its growth rate over the previous 10 years. 

In such a model, year 2006 employment is projected by assuming that the growth rate between 1996 and 2006 will 

equal the growth rate over the 1986–1996 period. This is 

the only naïve model used in the labor force, macroeconomic, and industry employment sections of the article.

•	 Five-year, two-point linear model. It is possible that the 

recent growth rate of an occupation’s employment is a better predictor of future growth. This model assumes that the 

growth rate between 1991 and 1996 continues over the 

1996–2006 period.

•	 Ten-year linear regression. A linear regression differs from 

a two-point forecast because it includes data from intervening years in addition to the data from the end years of 

the forecast (in this case 1986 and 1996.) A line of best 

fit is determined by minimizing the sum of the squared 

residuals.

•	 Static model. The static model assumes that the distribution of employment among occupations will not change 

over the forecast period. In this case, the static model assumed that, although total employment would grow, each 

occupation, industry, or demographic group would remain 

the same percentage of overall employment in 2006 as it 

was in 1996. The static naïve model projects employment 

in every occupation increasing by 14 percent—which was 

the overall rate of employment growth projected by BLS in 

1996.

Numeric difference between projection and actual. 

Percent change or growth rate difference between projection and 

actual.

Ai = Actual employment in industry/occupation i

Pi = Projected employment in industry/occupation i

Rankings for largest numeric change. This metric shows where 

the 20 industries or occupations with the highest projected 

numeric employment change fell in the actual rankings of 

industries. 

Rankings for greatest percentage change. This metric shows 

where the 20 industries or occupations with the highest 

projected percentage change fell in the actual rankings. 

Direction of change. This metric measures accuracy in a binary 

way by calculating the percentage of occupations or industries 

that BLS correctly projected to grow or decline. The metric 

focuses only on whether the direction of the change was 

correctly projected and does not measure the size of the actual 

growth or decline compared with the size of the projected 

growth or decline.

Mean absolute percent error (MAPE), weighted and unweighted.

The MAPE is a measure of accuracy between points in a time 

series. It is similar to the standard deviation. Ultimately, it is 

one of the simplest metrics used to determine the accuracy 

of the labor force, industry employment, and occupational 

employment projections. It is typically expressed as a percentage. 

By measuring the percentage difference between projection 

data and actual data, it adjusts for varying sizes of the different 

occupations and industries. It can be weighted or unweighted. 

In a weighted MAPE, each occupation or industry is weighted 

on the basis of its relative size, rather than weighted the same as 

all other occupations or industries. 

Weighted equation: 

Unweighted equation: 

A = actual value of occupation/industry/labor force 

component i

P = projected value of occupation/industry/labor force 

component i

W = weight of the occupation/industry or percent of total 

actual employment

N = number of occupations/industries

Dissimilarity index. A dissimilarity index measures the 

amount by which a projected distribution would have to change 

to be identical to the actual distribution. It is typically expressed 

as a percentage, as in the following example: “The BLS 1986 

projection of the distribution of the labor force between men 

and women in the year 2000 would need to change by 0.7 of 

a percentage point to reflect the actual distribution.” A lower 

dissimilarity index means that the projection was more accurate.
Monthly Labor Review • September 2010 69

two sets of values. Occupations or industries are ranked by 

projected growth rate and actual growth rate. The rank-order 

correlation coefficient can be compared across projections. 

n = number of industries/occupations

di = Difference between actual and projected employment in 

industry/occupation i

n = number of industries/occupations/labor force components

ai

 = actual employment in industry/occupation/labor force 

component i

pi = Projected employment in industry/occupation/labor force 

component i

A = Actual total employment/labor force 

P = Projected total employment/labor force

Spearman’s rank correlation. Spearman’s rank correlation is used 

to test the direction and strength of the relationship between