Monthly Labor Review • June 2009 39

Wage Inequality

What do OES data have to say

about increasing wage inequality?

Wage distribution data from the Occupational Employment

Statistics survey indicate that wages became more dispersed

over the 2002-08 period; occupations paying higher wages

tended to have workers with more education and higher level

technical skills, while occupations paying lower wages

tended to have workers with less education and lower skills

John I. Jones

John I. Jones is an economist in 

the Division of Publication and 

Analysis, Office of Employment 

and Unemployment Statistics, 

Bureau of Labor Statistics. E-mail: 

jones.john@bls.gov

Most economists concur that wage 

inequality has been increasing 

in the United States since the 

1970s.1 However, not all economists agree 

on the reasons behind this trend.2 One of 

the more widely held positions hypothesizes that increasing wage dispersion has been 

driven by skill-biased technical change benefiting those who possess greater technical 

skills. Specifically, advancements in technology have boosted the productivity and 

wages of skilled labor relative to that of unskilled labor.3

 This article uses Occupational 

Employment Statistics (OES) survey data 

to explore wage inequality, measure changes 

in wage dispersion over time, and examine 

wage growth by occupational group, wage 

rate, skill level, and ties to technology. 

The article first tests whether OES survey wage data support the notion that 

wage dispersion increased between 2002 

and 2008. Then, occupational data are 

used to determine (1) whether wages for 

higher skilled occupations increased by 

more than wages for lower skilled occupations, (2) if so, which occupational groups 

were exceptions, and (3) whether occupations with the highest wage growth were 

most closely associated with technological 

innovation. Educational attainment data from 

the Current Population Survey are used as a 

proxy for determining which workers in an occupation are “more skilled” and which are “less 

skilled.”4

OES data; testing wage dispersion

The OES survey is a survey of 1.2 million business establishments conducted in six semiannual panels over a 3-year period. Respondents 

are asked to list the occupation and wage range 

for each of their employees. Data from the six 

most recent panels are used each year to provide 

wage and employment estimates for more than 

800 occupations by area and industry. The OES

methodology that allows such detailed area and 

industry estimates also makes it difficult to use 

OES data for comparisons across short periods. 

To minimize both the difficulty of comparison 

over short periods and the difficulties associated with changes in occupational or methodological definitions, two nonoverlapping data 

sets, from 2002 and 2008, were selected for the 

analysis. The virtue of using OES data for this 

type of analysis is that each period examined 

includes wage and detailed occupational data 

on more than 80 million workers. 

One of the limitations of using OES data 
Wage Inequality

40 Monthly Labor Review • June 2009

to explore wage growth is the methodology of collecting data in wage ranges, especially for high-paying occupations. The OES program uses data from the 

National Compensation Survey to apply values to the 

wages within each of 12 wage ranges. Mean wage rates 

and wage growth for occupations with workers earning more than $145,600 per year may be underestimated because of the open-ended upper wage interval. 

Changes in percentile wage estimates should not be 

affected by changes in the upper interval as long as the 

percentile wages are below $145,600.

Results

If wage dispersion has increased over the study period, 

then the wage growth rate of higher wage earners will 

exceed that of lower wage earners. This hypothesis 

can be tested at the most aggregate levels by using the 

10th, 25th, 50th (median), 75th, and 90th percentiles 

of the wage distribution for all occupations and industries from the OES survey. Table 1 shows the national 

annual wage in 2002 and 2008 for each percentile, 

along with the percent change. If there is no increase 

in wage dispersion between 2002 and 2008, then the 

wage growth would be equivalent across the percentile 

wages. However, that is not what is observed. 

Wage growth by percentile 

Nationally, the 10th percentile of the wage distribution increased 15.4 percent over the period examined, 

while the median wage increased 17.0 percent and the 

90th percentile increased 21.8 percent. Inflation-adjusted figures are shown in the last column of table 1; 

the 90th-percentile workers are the only group to have 

experienced wage growth that exceeded inflation. As 

the wage percentiles increase, the growth in wages also 

increases: by 2008, wages for higher earners exceeded those 

for lower earners by a larger margin than in 2002. Another 

way to look at this phenomenon is that in 2002 a worker in 

the 90th percentile of the wage distribution earned 349 percent more than a worker in the 10th percentile, and by 2008 

the worker in the 90th percentile earned 374 percent more 

than the worker in the 10th percentile.

This evidence of increasing wage dispersion does not necessarily show that individuals or groups of workers experienced 

the same wage growth as others in their percentile, because 

a shift may have occurred in the occupations that make up 

each group over time. Rather, the evidence simply points to a 

wider distribution of wages, the result of faster wage growth 

in high-paying occupations, uneven growth in employment 

between high-paying and low-paying occupations, or a combination of both factors. Faster wage growth may be due to 

structural changes in the economy that increase the demand 

for one group of workers relative to others, such as highly 

skilled workers, technologically oriented workers, or workers 

in the health care professions. The rest of this article focuses 

on the wage growth experience of both individual occupations and groups of occupations, and finds evidence that skillbiased technical changes in the occupational structure of the 

United States are benefiting certain groups more than others. 

Among those benefiting most are workers with higher levels 

of skills or education and workers whose jobs are technological in nature.

Wage growth by occupational group

Because national wage data showed evidence of increasing 

wage dispersion between 2002 and 2008, the data will be 

examined by occupational group in order to see whether increasing wage growth is found across high-wage or high-skill 

occupations or is concentrated in just a few occupations. Such 

an examination also will aid in determining whether increasing wage growth is more prevalent in occupations related to 

Table 1. National percentile wage growth, 2002–08

 

10th...................................................................................................................... $14,450 $16,680 15.4 –3.6

25th...................................................................................................................... 18,580 21,590 16.2 –2.9

50th...................................................................................................................... 27,690 32,390 17.0 –2.3

75th...................................................................................................................... 43,340 51,540 18.9 –.7

90th...................................................................................................................... 64,900 79,020 21.8 1.7

Table 1.

Year Percent

change

in wage

Adjusted for

 inflation Percentile wage 1

2002 2008

1 The inflation rate over the 2002–08 period was 19.7 percent.
Monthly Labor Review • June 2009 41

improved technology. The Standard Occupational Classification (SOC) system groups occupations by similar skills 

or work activities, so analysis of the OES data by SOC occupational group will serve as a starting point in looking 

for patterns in the occupational data. 

Table 2 shows the mean annual wage for each occupational group in 2002 and 2008. Also listed is the wage 

difference for each group over the 2002–08 period and the 

percent change in the wage. To test the hypothesis that 

those occupational groups which had higher wages in 2002 

had the greatest growth between 2002 and 2008, the data 

in the table are sorted by mean annual wage in 2002. If the 

highest percent wage growth corresponded perfectly to the 

highest annual mean wage, then the percent changes in the 

wage would appear in descending order. In general, as the 

2002 wage for the occupational groups decreases, the percent change in the wage decreases with a correlation coefficient of 0.75—although there are notable exceptions.

In most cases, the occupational groups that earned 

above the mean wage of $35,560 in 2002 experienced 

wage growth greater than 18.9 percent and those which 

earned below the mean wage in 2002 experienced lower 

wage growth. However, there were exceptions. Each occupational group’s 2002 wage and percent increase are 

plotted in chart 1. The upper right-hand quadrant of the 

chart shows occupations with above-average wages and 

above-average wage growth, the lower left-hand quadrant 

occupations with below-average wages and below-average 

growth. The other two quadrants show the occupational 

groups that fall outside the trend.

In general, the occupations listed toward the top of table 

2 and shown in the upper right quadrant of chart 1 had both 

the highest wages and the highest wage growth. Among 

these occupations are architecture and engineering occupations and business and financial operations occupations. 

Those occupations with the lowest wages had the lowest 

wage growth and are shown in the lower left quadrant. Included in this group are food preparation and serving related 

occupations and building and grounds cleaning and maintenance occupations. Two occupations fell outside this trend, 

experiencing above-average wages and lower-than-average 

wage growth, and are shown in the lower right quadrant: 

construction and extraction occupations and installation, 

maintenance, and repair occupations. Finally, among those 

occupations with below-average wages were community 

and social services occupations and protective service occuTable 1. Wage growth of Standard Occupational Classification (SOC) major groups, 2002–08 

11–0000 Management................................................................................................ $78,870 $100,310 $21,440 27.2 

23–0000 Legal................................................................................................................. 77,330 92,270 14,940 19.3

15–0000 Computer and mathematical ................................................................. 61,630 74,500 12,870 20.9 

17–0000 Architecture and engineering................................................................ 58,020 71,430 13,410 23.1

29–0000 Health care practitioners and technical.............................................. 53,990 67,890 13,900 25.7

13–0000 Business and financial operations......................................................... 53,350 64,720 11,370 21.3

19–0000 Life, physical, and social science............................................................ 52,380 64,280 11,900 22.7

27–0000 Arts, design, entertainment, sports, and media............................... 41,660 50,670 9,010 21.6

25–0000 Education, training, and library.............................................................. 40,160 48,460 8,300 20.7

47–0000 Construction and extraction................................................................... 36,340 42,350 6,010 16.5 

49–0000 Installation, maintenance, and repair.................................................. 35,780 41,230 5,450 15.2

00–0000 Mean wage for all occupations ............................................................. 35,560 42,270 6,710 18.9

21–0000 Community and social services............................................................. 34,630 41,790 7,160 20.7

33–0000 Protective service........................................................................................ 33,330 40,200 6,870 20.6

41–0000 Sales and related ......................................................................................... 30,610 36,080 5,470 17.9

51–0000 Production..................................................................................................... 28,190 32,320 4,130 14.7

43–0000 Office and administrative support........................................................ 27,910 32,220 4,310 15.4

00–0000 Median wage for all occupations.......................................................... 27,690 32,390 4,700 17.0

53–0000 Transportation and material moving................................................... 27,220 31,450 4,230 15.5

31–0000 Health care support.................................................................................... 22,410 26,340 3,930 17.5 

39–0000 Personal care and service......................................................................... 21,370 24,120 2,750 12.9

37–0000 Building and grounds cleaning and maintenance.......................... 20,850 24,370 3,520 16.9 

45–0000 Farming, fishing, and forestry................................................................. 20,220 23,560 3,340 16.5

35–0000 Food preparation and serving related................................................. 17,180 20,220 3,040 17.7

 

Table 2.

Mean

 annual wage,

 2008

Difference

 (2008 wage 

minus 2002 

wage)1

Occupational group

Mean 

annual wage,

 2002

SOC 

 code

Percent

change

1 Statistically significant at the 90-percent confidence level. 
Wage Inequality

42 Monthly Labor Review • June 2009

pations, both of which experienced wage increases slightly 

higher than the average. These two occupations are shown 

in the upper left quadrant. Groups falling outside the trend 

are examined further.

Three occupational groups had lower wage growth than 

would be expected on the basis of their relatively high wage: 

legal occupations; installation, maintenance, and repair occupations; and construction and extraction occupations. 

The legal occupations group showed one of the biggest differences between its 2002 wage and its subsequent wage 

growth: with the 2nd-highest average annual wage in 2002, 

this group had only the 11th-highest wage growth and is 

furthest from the trend line in chart 1. Further study of 

the group reveals that the relatively low wage growth was 

influenced primarily by lawyers, the legal group’s detailed 

occupation with the most employment, but a relatively low 

wage growth of 17.8 percent. This comparatively small wage 

growth may be a reflection of the limitation of the OES data 

and its methodology of collecting data in wage ranges. The 

top wage range in the OES survey is $145,600 or more per 

year, so the survey is less effective in measuring wages of the 

highest wage earners. Therefore, the wage growth figure for 

legal occupations may be underestimated. This explanation 

is supported by an examination of the wages of lawyers who 

are unaffected by the survey’s top-coding methodology. 

Even the relatively lower paid lawyers showed higher-thanaverage wage growth: the 10th through 50th percentile of 

the wage distribution for lawyers showed increases of at 

least 22.4 percent.

The occupational group with the next-largest difference 

between its rank in wages in 2002 and its rank in percent 

change in wages is installation, maintenance, and repair. 

This group had the 11th-highest overall annual average 

wage in 2002, but the 20th-highest wage growth. Lower 

wage growth seems to be the norm for most, but not all, of 

the detailed occupations within the group, with 41 of the 

51 detailed occupations having a percent change in wages 

that was below 18.9 percent for the period between 2002 

and 2008. Some occupations in installation, maintenance, 

and repair that had large percent-change wage increases 

include watch repairers; manufactured building and home 

installers; and powerhouse, substation, and relay electrical 

and electronics repairers, all of which had wage increases 

of 21.0 percent or more.

The third group with wage growth that was lower than 

would be expected on the basis of its 2002 wages was 

construction and extraction occupations, which had the 

10th-highest average wage in 2002, but only the 16thhighest wage growth. The slow growth in this group hides 

underlying trends for two subgroups: even slower growth 

 Chart 1. 

 Percent growth

in wages, 2002–08

 Percent growth 

in wages, 2002–08

Mean annual wage, dollars (2002)

Management

Architecture and engineering

Life, physical, and social science

Business and financial operations

Education, training, and library Community and social services Computer and mathematical

Protective service

25.00

20.00

15.00

10.00

5.00

0.00

Health care practioners and technical

Legal

Building and grounds cleaning 

Food preparation 

Farming, fishing, and forestry

Personal care and service 

Construction and extraction

Transportation and material moving

Production

×

▲

Wages and percent growth in wages, by occupational group, 2002–08

▲

and maintenance

and serving related

×

Office and administrative support

Health care support

Installation, maintenance, and repair

0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000

▲

25.00

20.00

15.00

10.00

5.00

0.00

× Sales and related

Arts, design, entertainment, sports, and media
Monthly Labor Review • June 2009 43

for construction-related occupations and faster-than-average wage growth for oil-and-gas-related occupations. 

Lower wage growth for occupations associated with residential and commercial construction may have been due 

to the slowdown in residential building after the housing 

bubble burst.5 Occupations associated with the commodities of oil and gas, which, as an industry, had experienced 

its own bubble in 2007,6 experienced much faster than 

average growth. For example, the wage percent change 

of 4 of the 5 occupations with the highest wage growth 

in the construction and extraction group, all linked to 

working with oil and gas, ranged from 31.3 percent to 

49.7 percent. In contrast, carpet installers; paperhangers; 

floor sanders and finishers; carpenters; carpenters’ helpers; 

plumbers’, pipefitters’, and steamfitters’ helpers; construction and maintenance painters; plumbers, pipefitters, and 

steamfitters; electricians; construction laborers; and other 

related occupations all had wage percent changes below 

the average of 18.9 percent.

Like construction and extraction, production occupations had wage growth that was lower than expected. The 

group had the 15th-highest average wage in 2002, but 

the 21st-highest wage growth. Low growth was prevalent 

throughout the occupational group, with 91 of the 111 

comparable occupations, representing 91 percent of the 

group’s employment, having below-average wage growth.

Eleven occupation groups had higher wage growth 

than would be expected on the basis of their 2002 wage 

rank. The 5 groups with the greatest positive difference 

between their 2002 wage positions and wage growth positions were food preparation and serving; building and 

grounds cleaning and maintenance; farming, fishing, and 

forestry occupations; health care support occupations; and 

community and social services occupations. All 5 groups 

had below-average wages, and 4 of the 5 had below-average wage growth, resulting in wages in 2008 that were 

even further from the average than they were in 2002 and 

contributing to increased wage dispersion. These lower 

paying groups of occupations had smaller wage increases 

compared with the groups of occupations that grew less 

than their wage rank would indicate: the average annual 

wage increase of the 5 groups that went up in wage percent growth rank was $4,198, whereas the average annual 

wage increase of the 5 groups that went down in rank was 

$8,680, more than double.

Two of the occupational groups with higher growth 

than would be expected from their 2002 wages were food 

preparation and serving related occupations and building and grounds cleaning and maintenance occupations. 

Food preparation and serving related occupations had the 

lowest overall wage in 2002, but the 13th-highest wage 

increase. Relatively high wage growth was seen in only 5 

of the 16 occupations in this group and was concentrated 

in just 1 occupation: waiters and waitresses, an occupation 

making up approximately 21 percent of total employment 

in the group and having a wage percent change of 24.2 

percent. In contrast, combined food preparation and serving workers including fast-food workers, an occupation 

making up nearly 24 percent of total employment in the 

group, had a wage percent change of 14.9 percent. 

Building and grounds cleaning and maintenance occupations also had a large difference between the group’s 

annual average wage position in 2002, namely, 20th, and its 

wage growth position, 15th. The wage percent change was 

set predominantly by maids and housekeeping cleaners, an 

occupational component that accounted for approximately 

49 percent of the group’s total employment and had a wage 

percent change of 16.6 percent. Wage growth for the building and grounds cleaning and maintenance group was in a 

narrower range than that of most other groups, with a low 

of 15.7 percent and a high of 20.2 percent.

Skills, technology, and wage growth

To measure the impact of the demand for workers of different skill levels on wage growth (under the assumption 

that occupations in which wages have climbed the most 

are the most in demand), education data7 from the CPS 

were linked to occupational data from the OES survey. The 

BLS Employment Projections program has identified the 

typical educational background of workers in each occupation: high school (HS); high school/some college (HS/SC); 

high school/some college/college (HS/SC/C); some college 

(SC); some college/college (SC/C); and college (C). (See 

note 4.) The 741 matching detailed occupations between 

2002 and 2008 were sorted by percent change in wage, 

and the 50 occupations with the lowest and highest statistically significant percent changes in wages are shown 

in tables 3 and 4, respectively. Among occupations with 

the lowest growth, the ones that are most likely affected 

by the OES wage methodology, such as lawyers, were excluded from the table, because the top wage range might 

mask higher wage growth.8

Chart 2 shows the general relationship between educational clusters and wage growth over the 2002–08 period 

for all occupations in each educational cluster. In general, 

higher average wage growth is associated with increasing 

levels of education. An exception is the “some college” (SC) 

category, whose average wage growth was lower than that 

of the “high school/some college/college” (HS/SC/C) cat-
Wage Inequality

44 Monthly Labor Review • June 2009

Table 1.

 

53–4013 Rail yard engineers, dinkey operators, and hostlers....... $40,600 $34,850 High school/ –$5,750 –14.2

 some college

33–2022 Forest fire inspectors and prevention specialists............. 40,720 36,400 High school/ –4,320 –10.6

 some college/

 college

41–9091 Door-to-door salesworkers, news and street vendors, 

 and related workers.................................................................... 30,120 27,600 High school/ –2,520 –8.4

 some college/

 college

47–4091 Segmental pavers........................................................................ 29,630 28,450 High school/ –1,180 –4.0

 some college

29–1011 Chiropractors................................................................................. 83,440 81,340 College –2,100 –2.5

49–9093 Fabric menders, except garment........................................... 28,580 27,920 High school/ –660 –2.3

 some college

15–2091 Mathematical technicians........................................................ 42,920 42,100 College –820 –1.9

25–1043 Forestry and conservation science teachers, 

 postsecondary .............................................................................. 68,030 67,400 College –630 –.9

39–6011 Baggage porters and bellhops............................................... 22,440 23,170 High school/ 730 3.3

 some college

53–7071 Gas compressor and gas pumping station operators.... 42,920 44,410 High school/ 1,490 3.5

 some college

51–9031 Cutters and trimmers, hand..................................................... 24,630 25,540 High school 910 3.7

51–3093 Food cooking machine operators and tenders................ 23,160 24,110 High school/ 950 4.1

 some college

27–2022 Coaches and scouts.................................................................... 34,170 35,580 Some college/ 1,410 4.1

 college

53–2022 Airfield operations specialists................................................. 40,850 42,550 Some college/ 1,700 4.2

 college

53–4011 Locomotive engineers............................................................... 51,280 53,470 High school/ 2,190 4.3

 some college

27–2023 Umpires, referees, and other sports officials...................... 27,010 28,330 Some college/ 1,320 4.9

 college

53–4041 Subway and streetcar operators............................................ 46,810 49,330 High school/ 2,520 5.4

 some college

51–9192 Cleaning, washing, and metal pickling equipment 

 operators and tenders............................................................... 24,780 26,140 High school/ 1,360 5.5

 some college

51–4081 Multiple machine tool setters, operators, and tenders, 

 metal and plastic.......................................................................... 31,050 32,780 High school/ 1,730 5.6

 some college

51–9197 Tire builders................................................................................... 35,990 38,080 High school/ 2,090 5.8

 some college

33–3052 Transit and railroad police ........................................................ 45,750 48,540 Some college/ 2,790 6.1

 college

53–7072 Pump operators, except wellhead pumpers...................... 38,640 41,020 High school/ 2,380 6.2

 some college

17–3021 Aerospace engineering and operations technicians...... 52,990 56,280 High school/ 3,290 6.2

 some college

45–4021 Fallers............................................................................................... 32,090 34,180 High school 2,090 6.5

43–5111 Weighers, measurers, checkers, and samplers, 

 recordkeeping............................................................................... 26,740 28,500 High school/ 1,760 6.6

 some college

Table 3.

Average

 annual wage,

 2008

CPS

education

level

Occupational title

Average 

annual wage,

 2002

SOC 

code

Percent

change

Occupations with the lowest percent growth in wages, 2002–08

Difference

(2008 wage 

minus 2002 

wage)
Monthly Labor Review • June 2009 45

51–4122 Welding, soldering, and brazing machine setters, 

 operators, and tenders............................................................... 31,620 33,700 High school/ 2,080 6.6

 some college

25–9021 Farm and home management advisors............................... 41,850 44,630 College 2,780 6.6

23–1022 Arbitrators, mediators, and conciliators.............................. 55,970 59,650 College 3,680 6.6

39–6032 Transportation attendants, except flight attendants 

 and baggage porters.................................................................. 20,940 22,370 High school/ 1,430 6.8

 some college/

 college

41–9011 Demonstrators and product promoters.............................. 25,360 27,150 High school/ 1,790 7.1

 some college/

 college

47–5051 Rock splitters, quarry.................................................................. 28,070 30,160 High school/ 2,090 7.4

 some college

51–6064 Textile winding, twisting, and drawing-out machine 

 setters, operators, and tenders............................................... 22,810 24,600 High school 1,790 7.8

51–9132 Photographic processing machine operators................... 21,080 22,740 High school/ 1,660 7.9

 some college

49–2096 Electronic equipment installers and repairers, motor

 vehicles............................................................................................ 27,600 29,770 High school/ 2,170 7.9

 some college

19–4093 Forest and conservation technicians.................................... 32,700 35,320 Some college/ 2,620 8.0

 college

53–4021 Railroad brake, signal, and switch operators..................... 45,750 49,400 High school/ 3,650 8.0

 some college

51–4034 Lathe and turning machine tool setters, operators, and 

 tenders, metal and plastic ........................................................ 31,450 34,070 High school/ 2,620 8.3

 some college

49–9063 Musical instrument repairers and tuners............................ 33,210 35,950 High school/ 2,740 8.3

 some college

51–9041 Extruding, forming, pressing, and compacting machine

 setters, operators, and tenders............................................... 28,070 30,430 High school/ 2,360 8.4

 some college

51–9022 Grinding and polishing workers, hand ................................ 24,940 27,100 High school/ 2,160 8.7

 some college

39–4011 Embalmers..................................................................................... 36,160 39,320 High school/ 3,160 8.7

 some college/

 college

43–5081 Stock clerks and order fillers.................................................... 21,240 23,140 High school/ 1,900 8.9

 some college

49–9098 Helpers—installation, maintenance, and repair workers 23,560 25,670 High school 2,110 9.0

47–3011 Helpers—brickmasons, blockmasons, stonemasons, 

 and tile and marble setters...................................................... 27,170 29,610 High school 2,440 9.0

51–4194 Tool grinders, filers, and sharpeners..................................... 31,080 33,880 High school/ 2,800 9.0

 some college

31–9095 Pharmacy aides............................................................................ 19,700 21,500 High school/ 1,800 9.1

 some college

49–2092 Electric motor, power tool, and related repairers............. 34,030 37,110 High school/ 3,080 9.1

 some college

47–2171 Reinforcing iron and rebar workers....................................... 40,640 44,380 High school 3,740 9.2

47–3014 Helpers—painters, paperhangers, plasterers, and stucco 

 masons............................................................................................ 22,260 24,330 High school 2,070 9.3

19–4051 Nuclear technicians..................................................................... 61,220 66,910 Some college/ 5,690 9.3

 college

Table 3.

Average

 annual wage,

 2008

CPS

education

level

Occupational title

Average 

annual wage,

 2002

SOC 

code

Percent

change

Continued—Occupations with the lowest percent growth in wages, 2002–08

Difference

(2008 wage 

minus 2002 

wage)
Wage Inequality

46 Monthly Labor Review • June 2009

Table 1. Occupations with the highest percent growth in wages, 2002–08 

47–5012 Rotary drill operators, oil and gas.......................................... $36,320 $54,370 High school $18,050 49.7

11–2031 Public relations managers........................................................ 69,870 101,220 College 31,350 44.9

11–3061 Purchasing managers................................................................. 66,250 94,300 Some college/ 28,050 42.3

 college

27–4032 Film and video editors............................................................... 44,540 62,500 Some college/ 17,960 40.3

 college

25–1071 Health specialties teachers, postsecondary....................... 72,820 102,000 College 29,180 40.1

45–1012 Farm labor contractors............................................................... 26,220 36,640 High school/ 10,420 39.7

 some college

27–2041 Music directors and composers.............................................. 39,270 54,840 Some college/ 15,570 39.6

 college

17–2171 Petroleum engineers.................................................................. 85,540 119,140 College 33,600 39.3

29–1051 Pharmacists.................................................................................... 75,140 104,260 College 29,120 38.8

19–3022 Survey researchers...................................................................... 30,360 42,060 College 11,700 38.5

11–9081 Lodging managers...................................................................... 38,110 52,550 High school/ 14,440 37.9

 some college

 college

19–4041 Geological and petroleum technicians................................ 41,470 57,080 High school/ 15,610 37.6

 some college

 college

11–2011 Advertising and promotions managers.............................. 69,200 94,720 College 25,520 36.9

53–7033 Loading machine operators, underground mining ........ 32,480 44,230 High school 11,750 36.2

11–9121 Natural sciences managers...................................................... 90,400 123,140 College 32,740 36.2

33–9021 Private detectives and investigators..................................... 34,250 46,480 Some college/ 12,230 35.7

 college

11–2021 Marketing managers.................................................................. 87,170 118,160 Some college/ 30,990 35.6

 college

47–5071 Roustabouts, oil and gas........................................................... 24,160 32,660 High school 8,500 35.2

19–3091 Anthropologists and archeologists....................................... 42,380 57,300 College 14,920 35.2

27–2012 Producers and directors............................................................ 61,500 83,030 College 21,530 35.0

19–1021 Biochemists and biophysicists................................................ 65,620 88,450 College 22,830 34.8

19–2021 Atmospheric and space scientists......................................... 61,000 82,080 College 21,080 34.6

11–3011 Administrative services managers......................................... 59,350 79,500 High school/ 20,150 34.0

 some college/

 college

25–1021 Computer science teachers, postsecondary...................... 55,330 74,050 College 18,720 33.8

19–3041 Sociologists.................................................................................... 56,520 75,460 College 18,940 33.5

11–3031 Financial managers..................................................................... 83,080 110,640 Some college/ 27,560 33.2

 college

29–2034 Radiologic technologists and technicians.......................... 40,150 53,230 Some college/ 13,080 32.6

 college

35–1011 Chefs and head cooks................................................................ 32,000 42,410 High school/ 10,410 32.5

 some college

51–6092 Fabric and apparel patternmakers........................................ 31,890 42,190 High school 10,300 32.3

47–5011 Derrick operators, oil and gas.................................................. 31,780 41,980 High school 10,200 32.1

45–2011 Agricultural inspectors............................................................... 31,380 41,330 High school/ 9,950 31.7

 some college

 college

Table 4.

Average

 annual wage,

 2008

CPS

education

level

Occupational title

Average 

annual wage,

 2002

SOC 

code

Percent

change

Difference

(2008 wage 

minus 2002 

wage)
Monthly Labor Review • June 2009 47

egory. This relatively low growth was due to changes in the 

occupational employment composition of the group. The 

SC category has only four occupations in it, each of which 

grew between 20.4 percent and 31.1 percent; however, employment increases in the lowest paid occupation—emergency medical technicians and paramedics—lowered the 

wage growth for the group. Another exception is the “college” (C) category, whose average wage growth was lower 

than that of both the “high school/some college/college” 

(HS/SC/C) and “some college/college” (SC/C) categories. 

The college category is dominated by the employment of 

elementary, middle, and secondary school teachers, who 

make up nearly 25 percent of total employment in the 

category. Teachers had wage growth rates ranging from 

18.2 percent to 19.2 percent. In addition, the wage percent change of the “some college/college” (SC/C) category 

was higher than that of the “college” (C) category, largely 

because of both registered nurses, who made up 14.1 percent of employment with a wage percent change of 30.7 

percent, and business managers, accounting for approximately 20.8 percent of employment with wage percent 

changes from 21.8 percent to 33.2 percent.

Table 3, which lists the 50 occupations with the lowest wage growth during 2002–08, provides evidence of 

the link between skills or education and wage dispersion. 

Most of the occupations in this table require relatively 

Table 1. Table 4. Continued—Occupations with the highest percent growth in wages, 2002–08 

Average

 annual wage,

 2008

CPS

education

level

Occupational title

Average 

annual wage,

 2002

SOC 

code

Percent

change

Difference

(2008 wage 

minus 2002 

wage)

53–5021 Captains, mates, and pilots of water vessels...................... 51,430 67,730 High school/ 16,300 31.7

 some college

 college

17–2061 Computer hardware engineers............................................... 76,150 100,180 Some college/ 24,030 31.6

 college

53–7031 Dredge operators......................................................................... 29,740 39,040 High school 9,300 31.3

47–5013 Service unit operators, oil, gas, and mining....................... 31,480 41,320 High school 9,840 31.3

17–1022 Surveyors........................................................................................ 42,630 55,980 College 13,350 31.3

25–1192 Home economics teachers, postsecondary....................... 53,650 70,420 College 16,770 31.3

11–3021 Computer and information systems managers................ 90,440 118,710 Some college/ 28,270 31.3

 college

31–2011 Occupational therapist assistants.......................................... 36,950 48,440 Some college 11,490 31.1

17–2131 Materials engineers..................................................................... 64,310 84,200 College 19,890 30.9

29–1111 Registered nurses........................................................................ 49,840 65,130 Some college/ 15,290 30.7

 college

17–2021 Agricultural engineers............................................................... 55,730 72,850 College 17,120 30.7

27–1027 Set and exhibit designers......................................................... 37,250 48,660 Some college/ 11,410 30.6

 college

29–1126 Respiratory therapists................................................................ 40,700 53,150 Some college/ 12,450 30.6

 college

25–1193 Recreation and fitness studies teachers, postsecondary..... 46,480 60,700 College 14,220 30.6

13–2041 Credit analysts............................................................................... 49,530 64,580 Some college/ 15,050 30.4

 college

53–2012 Commercial pilots........................................................................ 58,000 75,500 Some college/ 17,500 30.2

 college

11–3071 Transportation, storage, and distribution managers...... 65,070 84,520 High school/ 19,450 29.9

 some college/

 college

41–9031 Sales engineers............................................................................. 69,200 89,770 College 20,570 29.7

11–9033 Education administrators, postsecondary.......................... 71,630 92,920 College 21,290 29.7
Wage Inequality

48 Monthly Labor Review • June 2009

low levels of skill. Twelve of the 50 occupations listed are 

production occupations, 7 are from the transportation 

and material-moving group, and there are 5 occupations 

each from the construction and extraction group and the 

installation, maintenance, and repair group. Thirty-nine 

of the occupations with the lowest wage growth have 

educational levels ranging from high school through high 

school/some college/college. Only 11 of the occupations 

have high educational levels of some college or college.

Table 4 offers further evidence of the connection between skills or education and wage dispersion. The table 

lists the 50 occupations with the highest wage growth 

from 2002 to 2008, most of which require relatively high 

levels of skill. Eleven of the occupations are from the management group; 6 are in the life, physical, and social science group; and 5 are in the architecture and engineering 

group. In contrast to the occupations listed in table 3, only 

15 occupations in table 4 have educational levels ranging 

from high school through high school/some college/college. Thirty-five of the 50 occupations have an educational 

level of either some college or college.

In comparing Tables 3 and 4, a few generalizations 

may be made in support of the skill- or education-biased 

wage-change hypothesis. According to this hypothesis, 

occupations that work with computers and new technology should have the highest wage growth and college-educated workers are in the best position to take advantage 

of such productivity-increasing technology. In fact, table 

4 does have a preponderance of college-educated occupations, compared with table 3.

Although the broad group of computer and mathematical science occupations, which are the most directly related 

to many types of technology, did not show the highest 

wage growth, there is support for the hypothesis within the 

occupational group. In this regard, the detailed occupation 

consisting of computer and information research scientists 

had the highest percent change in wages in the group. This 

is an occupation that requires high levels of education or 

talent to invent or design solutions to problems in the field 

of computer hardware and software. In comparison, the 

occupation consisting of computer support specialists had 

the lowest percent change in wages of all detailed occupations in the group and may indeed be suffering stagnating 

wages because technology has allowed workers in the occupation to be replaced by automated assistants, online help, 

and technical support workers located overseas. This is the 

downside of advancing technology: workers are finding 

that their skills are being replaced by that very technology, 

in one way or another. Simply put, one of the occupations 

in the computer and mathematical science occupational 

 Chart 2. Wage growth, by education level, 2002–08

 College Some college/ Some college High school/ High school/ High school

college some college/ some college

college

Percent growth 

in wages, 2002–08

Education level

30.0

25.0

20.0

15.0

10.0

5.0

0.0

30.0

25.0

20.0

15.0

10.0

5.0

0.0

Percent growth 

in wages,2002–08
Monthly Labor Review • June 2009 49

group is taking advantage of higher education while the 

other is losing ground because of automation.

Technology may enhance the productivity of workers in 

fields other than computer science. For example, the collection, processing, and analysis of medical information is 

more efficient with advanced technology, allowing medical 

workers to serve more individuals. Also, pharmacists filling 

prescriptions for new drugs use technology to help screen 

customers for adverse drug interactions. In another application of technology, nurses may enter notes concerning 

a patient’s progress on a wireless portable memory device 

that instantly becomes available to the doctor. Finally, the 

nuclear medical technologist using a new magnetic resonance imaging (MRI) device to scan a patient for disease 

can improve productivity by having the results of the scan 

uploaded almost instantaneously to the patient’s electronic 

file for diagnosis. Again, workers with high levels of education and skill are in the best position to take advantage of 

productivity-increasing technology.

More support for this hypothesis is found in table 3, 

which lists lesser skilled occupations that are more likely to suffer from the other side of the increased use of 

technology: labor replacement. For instance, workers in 

manufacturing occupations may be replaced by robots or 

computerized manufacturing. Similarly, demonstrators 

and product promoters may be replaced with virtual online demonstrators and product promoters. Finally, doorto-door salesworkers, news and street vendors, and related 

workers may suffer from the availability of Internet news 

and targeted e-mail and phone advertising. 

OES DATA SUPPORT THE HYPOTHESIS that wage dispersion continued from 2002 to 2008. National wage distribution data show a clear positive correlation between percentile levels and wage increases: the higher the percentile, 

the higher is the percent change in wages. In addition, 

occupational groups with higher average wages in 2002 

tended to have the highest subsequent wage growth.

Examining wage growth by occupational group provides insight into the types of jobs that have experienced 

the largest wage increases. The five occupational groups 

with the highest wage growth are management occupations; health care practitioners and technical occupations; 

architecture and engineering occupations; life, physical, 

and social science occupations; and education, training, 

and library occupations. In contrast, the occupational 

groups with the lowest wage growth were personal care 

and service occupations; food preparation and serving 

related occupations; farming, fishing, and forestry occupations; construction and extraction occupations; and 

production occupations. In sum, occupations usually associated with higher education and higher technical skills 

have had higher wage growth than occupations with lower 

education and skill requirements.

Notes

1 Aaron Steelman and John A. Weinberg, “What’s Driving Wage Inequality?” 

Economic Quarterly (Federal Reserve Bank of Richmond), summer 2005, pp. 

1–17, cite this general consensus among economists.

2 David H. Autor, Lawrence F. Katz, and Melissa S. Kearney, “The 

Polarization of the U.S. Labor Market,” NBER Working Paper No. 11986 

(National Bureau of Economic Research, January 2006), pp. 1–19ff.

3 Steelman and Weinberg, “What’s Driving Wage Inequality?”

4 See “Occupational Projections and Training Data” (Bureau of Labor 

Statistics, no date), on the Internet at www.bls.gov/emp/optd (visited June 17, 

2009). Data on educational attainment by occupation come from the Current 

Population Survey and are given in Occupational Projections and Training 

Data, Bulletin 2602 (Bureau of Labor Statistics, December 2007). Chapter 1, 

“Education and Training Classification Systems,” says,

The educational attainment cluster system sorts occupations 

according to the highest level of educational attainment of current 

workers....

If an education level represents the highest educational attainment 

of at least 20 percent of workers in an occupation, that education level 

is included in the education category of the occupation. For example, 

if more than 60 percent of workers have a high school diploma or less, 

less than 20 percent have some college or an associate degree, and less 

than 20 percent have a bachelor’s or higher degree, that occupation is 

considered a high school (HS) occupation. However, if more than 20 

percent have a high school degree or less, more than 20 percent have 

attended some college or held an associate degree, and less than 20 

percent have a bachelor’s or higher degree, the occupation is considered 

to be a high school/some college (HS/SC) occupation.

5 For a discussion of job losses in residential construction, see the BLS news 

release “The Employment Situation: May 2008” (Bureau of Labor Statistics, June 6, 

2008), on the Internet at www.bls.gov/news.release/archives/empsit_06062008.

pdf (visited June 17, 2009). For a look at when the housing bubble burst, see 

“Nationally, Home Prices Began 2009 with Record Declines According to the S&P/

Case-Shiller Home Price Indices,” Standard & Poor’s Press Release, May 26, 2009, 

on the Internet at www2.standardandpoors.com/spf/pdf/index/CSHomePrice_

Release_052619.pdf (visited June 17, 2009); see especially chart, p. 1.

6 For an examination of the oil and gas industry, see “Oil Price History 

and Analysis,” on the Internet at www.wtrg.com/prices.htm (visited June 17, 

2009). 

7 Education is often linked with skill. Other influences on skill include 

experience, training, and individuals’ abilities—for instance, creativity.

8 The OES top wage range was $145,600 or more for panels prior to 

November 2005. Currently, the top wage range is $166,400 or more. In either 

case, because respondents cannot report their actual top wage, the top wage 

range may mask wage growth for the highest wage earners over time.