26  Monthly Labor Review • June 20

Wages and Employment

How shifting occupational composition 

has affected the real average wage

Between November 2002 and May 2007, 

the cross-occupational average hourly 

wage in the United States increased by 

$2.46, from $17.10 to $19.56, or by about 14 

percent, according to the Occupational Employment Statistics (OES) program. Adjusting 

the 2002 figure to May 2007 dollars1 shows the 

real average hourly wage increased from $19.48 

to $19.56, approximately a .41-percent increase. 

There have been numerous studies and programs devoted to understanding this recent 

slow growth in the Real Average Wage (RAW). 

Many studies attribute slow wage growth to 

the increasing cost of employee benefits and 

health insurance—a phenomenon that results 

in employees’ wages becoming a smaller part of 

their total compensation.2 Other studies have 

analyzed how wage growth relates to income or 

wage inequality.3 This article seeks to contribute 

towards an understanding of RAW growth by 

quantifying how changes in the occupational 

composition of U.S. employment have affected 

the average wage.

 This article analyzes occupational wage and 

employment data from the OES program to 

understand how changes in occupations’ wages 

and changes in occupations’ levels of employment each have contributed to growth in the 

U.S. RAW. Overall wage growth could stem 

Rebecca Keller is an

economist in the Office of Employment

and Unemployment

Statistics, Bureau of

Labor Statistics. Email:

keller.rebecca@bls.gov

Rebecca Keller

OES data from 2002–2007 reveal that an overall shift in employment

towards occupations with lower mean wages hindered growth in the U.S. 

real average wage and that wage growth was concentrated in higher paying 

occupations; the data also show a shift in employment from the 

middle-paying occupations to the highest and lowest paying occupations 

from increases in the mean wages of particular 

occupations, from a shift in employment towards occupations with higher wages, or from 

a combination of the two factors. This article’s 

analysis of OES data from November 2002 to 

May 2007 finds that a shift in employment towards lower paying occupations hindered U.S. 

RAW growth, that increases in the real mean 

wages of individual occupations was the only 

factor that caused growth in the U.S. RAW, and 

that most of the average wage growth was due 

to increases in the wages of the highest paying occupations. This analysis also finds a shift 

in employment towards the highest paying 

and lowest paying occupations and away from 

middle-paying occupations. This article will 

show which occupations experienced growth 

and which experienced decline in real mean 

wages or in share of employment, and how 

these changes influenced the U.S. RAW. It will 

also reveal patterns of lower and higher paying occupations and of education and training 

categories, and give a brief analysis of changes 

in the average wages of U.S. States. 

Methods

The OES program estimates national employment and wages by occupation and provides a 
Monthly Labor Review • June 2009  

data set for understanding changes in the average wage 

over the medium term. The OES program surveys 1.2 million business establishments, using 3 years of data collected 

in six semiannual panels to produce estimates for over 800 

occupations.4 Because of the survey methods employed, it 

can be difficult to use the data for time-series analysis, but 

this study mostly overcomes the issue because it compares 

wage and employment data 41⁄2 years apart and analyzes 

cross-industry wage and employment estimates that have 

been retabulated on the basis of a common coding system.5

 However, between November 2002 and May 2007, 

OES implemented refinements in occupational coding 

procedures that have caused some management workers 

to be moved from one occupation to another. Therefore, 

some results of this analysis may have been affected by 

this worker classification change and must be interpreted 

cautiously. 

Change in the U.S. average wage may be due to changes 

in the mean wages of individual occupations or to shifts 

in employment among higher and lower paying occupations. An occupation’s share of national employment is 

the percent of total jobs in the Nation for which the occupation accounts. This article uses a “shift-share analysis” of OES data to quantify the effect of changes in mean 

wages and the effect of changes in employment share on 

the U.S. RAW from November 2002 to May 2007.6 OES

data previously have been employed to examine the role of 

occupational composition, or the assortment of shares of 

national employment held by occupations, in the average 

wage differentials of U.S. States for one point in time.7 In 

this article, change in the U.S. RAW over time is analyzed 

in a similar fashion, by decomposing the components of 

the change. 

To calculate the U.S. RAW, each occupation’s mean 

wage is multiplied by its share of national employment 

and then the products are summed. Change in the U.S. 

RAW from time t to time t+1 is found by subtracting the 

U.S. RAW at time t from the U.S. RAW at time t+1. Just 

as the U.S. RAW is influenced by the two factors of occupational mean wages and occupational composition, 

change in the U.S. RAW is influenced by the two factors 

of changes in occupational real mean wages and change 

in occupational composition. The decomposition of U.S. 

RAW change into these two factors, expressed in words 

and in mathematical notation, is

Change in U.S. RAW = National Wage Component + 

National Employment Component + National Residual 

Component

 

where

j = {1, 2,...J} index occupations

∆ = Change from November 2002 to May 2007

 = U.S. real average wage (in May 2007 dollars)

 = Occupational real average wage (in May 2007 dollars)

N = National employment; Nj = Occupational employment 

 t = November 2002; t+1 = May 2007

Table 1 shows the results and constituents of this 

analysis for the sum of all occupations and for major occupational groups (obtained by summing the results of all 

occupations within each group), and includes mean wages 

(in May 2007 dollars) and national employment shares in 

November 2002 and May 2007. Table 2 shows the results 

and constituents of this analysis for selected occupations. 

The contribution of changes in the mean wages of occupations to the change in the U.S. RAW, represented by 

the first term in the aforementioned equation, is called the 

“wage component.” The wage component of an occupation is found by holding the occupation’s share of national 

employment constant while considering only the change 

in the mean wage of the occupation. The wage component is measured by multiplying the change in mean wage 

from November 2002 (in May 2007 dollars) to May 2007 

by the occupation’s share of November 2002 national employment. 

A positive wage component indicates that the mean 

wage of an occupation or group of occupations increased, 

while a negative result indicates that the mean wage decreased. For example, as seen in table 2, the occupation 

of accountants and auditors has a wage component of 

1 cent, found by multiplying the occupation’s real mean 

wage increase of $1.23 by its November 2002 employment share of .70 percent. The national wage component 

is found by summing all occupations’ wage components. 

A positive national wage component indicates that occupational mean wages grew overall, whereas a negative 

result indicates mean wages declined overall.

The contribution of changes in occupational composition to the change in the U.S. RAW, represented by the 

second term in the above equation, is called the “employment component.” The employment component of an occupation is found by multiplying the occupation’s change 

in employment share by its November 2002 mean wage 

(in May 2007 dollars). In other words, an occupation’s 

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Wages and Employment

28  Monthly Labor Review • June 20

Table 1. Mean hourly wage, employment share, and components of change in the U.S. real average wage, 

 by occupational group, Nov. 2002–May 2007

 

2002 

mean 2007 Change 2002 2007 Change Wage Employ- Residual Total 

 Occupational group wage, mean in real employ- employ- incompo- ment compo- of three 

 in May wage mean ment ment employ- nent compo- nent compo- 

 2007 wage1 share share ment nent nents1 

dollars share1 

 

 

 Total, all occupations.......... $19.48 $19.56 $0.08 100.0 100.0 — $0.22 $–0.11 $–0.03 $0.0

Management occupations2 ........ 43.19 46.27 3.08 5.56 4.47 –1.09 .20 –.49

Business and financi

operations occupations............. 29.20 30.07 .87 3.74 4.48 .74 .02

Computer and mathematical

science occupations.................... 33.75 34.71 .96 2.17 2.38 .20 .01 .

Architecture and engineeri

occupations ................................... 31.77 33.11 1.34 1.89 1.85 –.04 .02 –.

Life, physical, and soci

science occupations.................... 28.69 29.79 1.11 .85 .93 .09 .01 

Community and social servic

occupations.................................... 18.96 19.49 .53 1.24 1.33 .10 .01 

Legal occupations ......................... 42.35 42.53 .18 .73 .74 .01 .0

Education, training, and libra

occupations ................................... 22.01 22.41 .40 6.09 6.19 .10 .01 .

Arts, design, entertainmen

sports, and media

occupations.................................... 22.81 23.27 .46 1.18 1.31 .13 .00 

Healthcare practitioner

and technical occupations........ 29.75 31.28 1.53 4.87 5.12 .25 .06 

Healthcare suppo

occupations ................................... 12.27 12.31 .03 2.49 2.70 .21 .00 .02 .00

Protective servi

occupations.................................... 18.25 18.84 .58 2.35 2.30 –.05 .02 – .0

Food preparation and servi

related occupations..................... 9.40 9.34 –.06 7.89 8.39 .50 .00 .04

Building and groun

cleaning and maintenance

occupations.................................... 11.44 11.33 –.11 3.34 3.28 –.06 .00 –.01 

Personal care and servi

occupations.................................... 11.70 11.53 –.17 2.29 2.49 .20 .00 .02

Sales and relat

occupations.................................... 16.76 16.94 .18 10.46 10.67 .21 .02 .04 

Office and administrative

support occupations .................. 15.28 15.00 –.28 17.84 17.32 –.52 –.04 –.09 

Farming, fishing, and forestry

occupations ................................... 11.05 10.89 –.16 .35 .33 –.02 .00 

Construction and extraction

occupations.................................... 19.93 19.53 –.40 4.80 4.99 .19 –.02 

Installation, maintenance,

and repair occupations.............. 19.59 19.20 –.39 4.09 4.01 –.08 –.02 –.02 

Production occupations............... 15.43 15.05 –.38 8.41 7.55 –.86 –.03 –.13 

Transportation and material

moving occupations .................. 14.93 14.75 –.18 7.37 7.17 –.20 –.02 –.02 .

Employment

effect

mean wage is held constant and only the change in an 

occupation’s employment share is taken into account. A 

positive employment component indicates that the employment share of an occupation or group of occupations 

increased, while a negative result indicates that its employment share declined. For example, as seen in table 1, 

the employment component of the production occupational group is –13 cents, found by multiplying the pro1 Numbers may not add precisely because of rounding.

2 The results for management occupations should be interpreted with

caution because they may be affected by refinements in occupational

coding procedures.
Monthly Labor Review • June 2009  

Table 2. Mean hourly wage, employment share, and components of change in the U.S. real average wage, for selected 

 occupations, Nov. 2002–May 2007 

 

 2002 

 mean 2007 Change 2002 2007 Change

Wage Employ- Resid- Total Employ- Occupation title wage, mean in real employ- employ- in

com- ment ual of ment in May wage mean ment ment employponent com- com- compo- effect 2007 wage1 share share ment ponent ponent nents1

dollars share1

 

 

Total, all occupations....... $19.48 $19.56 0.08 100.0 100.0 — 0.22 –0.11 $–0.03 $0.08 $–0.11

Selected occupations with large positive wage components (sorted by wage component)2

   

Registered nurses.............. 27.29 30.04 2.74 1.76 1.84 .08 .05 .02 .00 .07 .01

Pharmacists.......................... 41.15 47.58 6.43 .17 .19 .02 .01 .01 .00 .02 .00

Sales representatives,

wholesale

and manufacturing,

except technical

and scientific

products............................. 28.00 28.94 .94 1.08 1.12 .04 .01 .01 .00 .02 .00

Accountants

and auditors...................... 29.15 30.37 1.23 .70 .83 .13 .01 .04 .00 .05 .01

First-line supervisors/

managers of nonretail sales workers.......... 35.19 37.58 2.39 .26 .21 –.05 .01 –.02 .00 –.01 –.01

Sales representatives,

wholesale

and manufacturing,

technical and scientific

products............................. 34.75 36.76 2.01 .29 .30 .01 .01 .00 .00 .01 .00

Licensed practical

and licensed vocational

nurses.................................. 17.69 18.72 1.03 .54 .54 –.01 .01 .00 .00 .00 .00

Waiters and waitresses..... 8.64 8.93 .29 1.64 1.75 .12 .00 .01 .00 .02 –.01

Computer software

engineers, systems

software.............................. 41.53 43.65 2.12 .20 .26 .06 .00 .02 .00 .03 .01

Executive secretaries

and administrative

assistants............................ 19.19 19.57 .38 1.10 1.13 .03 .00 .00 .00 .01 .00

       

Selected occupations with large negative wage components (sorted by wage component)2

           

Office clerks, general ....... 12.89 12.48 –.41 2.24 2.22 –.02 –.01 .00 .00 –.01 .00

Truck drivers, heavy

and tractor-trailer........... 18.81 18.06 –.76 1.19 1.26 .07 –.01 .01 .00 .00 .00

Stock clerks

and order fillers............... 11.63 10.93 –.71 1.26 1.35 .09 –.01 .01 .00 .00 –.01

Cashiers................................ 9.14 8.84 –.30 2.65 2.64 –.01 –.01 .00 .00 –.01 .00

Customer service

representatives................ 15.46 14.93 –.54 1.45 1.63 .18 –.01 .03 .00 .02 –.01

Team assemblers............... 13.53 12.72 –.81 .89 .87 –.02 –.01 .00 .00 –.01 .00

Securities,

commodities,

and financial services

sales agents...................... 46.94 43.49 –3.44 .20 .20 .00 –.01 .00 .00 –.01 .00

Secretaries, except

legal, medical,

and executive................... 14.45 14.04 –.42 1.41 1.36 –.04 –.01 –.01 .00 –.01 .00

Computer support

specialists.......................... 23.18 21.78 –1.40 .38 .39 .02 –.01 .00 .00 .00 .00

Construction laborers..... 15.64 14.88 –.76 .65 .78 .13 .00 .02 .00 .01 –.01

See footnotes at end of table.
Wages and Employment

30  Monthly Labor Review • June 20

Computer software

engineers,

applications......................    40.41 41.18 0.77 0.28 0.37 0.09 0.00 0.04 0.00 0.04 0.02

Computer software

engineers, systems

software.............................    41.53 43.65 2.12 .20 .26 .06 .00 .02 .00 .03 .01

Accountants

and auditors.....................    29.15 30.37 1.23 .70 .83 .13 .01 .04 .00 .05 .01

Packers and packagers,

hand....................................    9.94 9.77 –.17 .73 .59 –.13 .00 –.01 .00 –.01 .01

Management analysts.....    38.42 38.68 .26 .31 .37 .06 .00 .02 .00 .03 .01

Market research

analysts..............................    33.00 32.20 –.80 .10 .16 .07 .00 .02 .00 .02 .01

Personal financial

advisors..............................    42.96 42.89 –.07 .06 .10 .04 .00 .02 .00 .02 .01

Loan officers.......................    28.56 30.10 1.54 .17 .27 .09 .00 .03 .00 .03 .01

Network systems

and data

communications

analysts..............................    33.62 34.02 .41 .10 .16 .06 .00 .02 .00 .02 .01

Financial analysts..............    36.79 39.28 2.50 .13 .17 .04 .00 .02 .00 .02 .01

Selected occupations with large negative employment effects (sorted by employment effect)2

             

     

Combined food preparation and serving

workers, including

fast food..............................    8.30 8.03 –.27 1.57 1.94 .37 .00 .03 .00 .03 –.04

Retail salespersons............    11.91 11.79 –.12 3.05 3.30 .24 .00 .03 .00 .03 –.02

Home health aides............    10.43 10.03 –.40 .45 .62 .17 .00 .02 .00 .02 –.02

Waiters and waitresses.....    8.64 8.93 .29 1.64 1.75 .12 .00 .01 .00 .02 –.01

Computer programmers.    34.88 34.62 –.26 .36 .29 –.06 .00 –.02 .00 –.02 –.01

Personal and home care

aides.....................................    9.20 9.11 –.09 .35 .44 .09 .00 .01 .00 .01 –.01

Cooks, restaurant...............    10.87 10.56 –.31 .56 .65 .09 .00 .01 .00 .01 –.01

First–line supervisors/

managers of non–retail

sales workers.....................    35.19 37.58 2.39 .26 .21 –.05 .01 –.02 .00 –.01 –.01

Stock clerks and order

fillers.....................................    11.63 10.93 –.71 1.26 1.35 .09 –.01 .01 .00 .00 –.01

Customer service

representatives.................    15.46 14.93 –.54 1.45 1.63 .18 –.01 .03 .00 .02 –.01

duction group’s November 2002 mean wage (in May 2007 

dollars) of $15.43 by its employment share decline of .86 

percentage point. A higher paying occupation will have an 

employment component of a greater degree than a lower 

paying occupation with the same change in employment 

share. The national employment component is found by 

summing all occupations’ employment components. A 

positive national employment component indicates that 

higher paying occupations gained employment share relative to lower paying occupations, while a negative result 

indicates lower paying occupations gained employment 

share.

The final component of change in the U.S. RAW is 

the residual component, which captures the part of the 

Table 2. Continued—Mean hourly wage, employment share, and components of change in the U.S. real average wage, for 

 selected occupations, Nov. 2002–May 2007 

 2002 Change 

 mean 2007 Change 2002 2007 in Wage Employ- Resid- Total Employ- Occupation title wage, mean in real employ- employ- employ- com- ment ual of ment in May wage mean ment ment ment ponent com- com- compo- effect 2007 wage1 share share share1 ponent ponent nents1

dollars 

 

Selected occupations with large positive employment effects (sorted by employment effect)2

1 Numbers may not add precisely because of rounding.

2 Management occupations and residual occupations are not included.
Monthly Labor Review • June 2009  

change in the RAW that is not attributable solely to either 

the employment component or the wage component. The 

residual component is less meaningful to this study than 

the wage and employment components, because it is small 

and does not represent either the change in occupational 

composition alone or the changes in occupations’ wages 

alone. 

The sums of the three components for each occupation or occupational group are the figures in the “total 

of components” column of tables 1 and 2. The sum of all 

three components of all occupations is equal to the change 

in the U.S. RAW. In addition to decomposing U.S. RAW

change into its three components, this article also seeks 

to show how the change in each occupation’s mean wage 

and the change in its employment share have affected 

the U.S. RAW. The effect of the change in an occupation’s 

mean wage on the U.S. RAW is captured through its wage 

component. Occupations whose real mean wages have increased will have positive wage components and increase 

the U.S. RAW, while occupations whose real mean wages 

have declined will have negative wage components and 

decrease the U.S. RAW. For example, accountants and auditors’ real mean wage increase of $1.23 would have increased the U.S. RAW by 1 cent were employment shares 

to have remained constant, as seen in table 2. 

Whereas the wage component indicates the effect that 

the change in an occupation’s mean wage has on the U.S. 

RAW, the employment component does not indicate the 

effect that the change in an occupation’s employment 

share has on the U.S. RAW. For example, a below-average 

paying occupation with a decline in employment share 

will have a negative employment component, but this decline in employment share will actually increase the U.S. 

RAW. There is, however, a calculation that can determine 

the effect that the change in one occupation’s employment share has on the U.S. RAW, and the result of this 

calculation is referred to as the “employment effect.” The 

employment effect takes into account both the change in 

an occupation’s share of employment and the difference 

between the occupation’s mean wage and the national 

mean wage. The overall employment effect of a group or 

category of occupations is calculated by summing the employment effects of all the occupations within that group 

or category. The national employment effect—that is, the 

employment effect of all occupations taken together—is 

found by summing the employment effects of all occupations in the United States, and it is equal to the national 

employment component. The occupational employment 

effect is shown in tables 1 and 2, and its equation is 

where 

j = {1, 2,...J} index occupations

E = Occupational employment effect 

 = U.S. real average wage (in May 2007 dollars)

 = Occupational real average wage (in May 2007 dollars)

 = Change in occupational employment share 

 t = November 2002

A positive employment effect indicates that the change 

in an occupation’s employment share was a factor pushing the U.S. average wage upward. An occupation with a 

below-average mean wage and a decline in employment 

share will have a positive employment effect, as will an 

occupation with an above-average mean wage and an increase in employment share. Similarly, a negative employment effect indicates that the change in an occupation’s 

employment share was a factor pushing the U.S. average 

wage downward. A negative employment effect is a result of either an occupation with a below-average mean 

wage gaining employment share or an occupation with an 

above-average mean wage losing employment share. For 

example, computer programmers’ above-average November 2002 wage of $34.88 and their loss of .06 percentage 

point in employment share from November 2002 to May 

2007 resulted in an employment effect of –1 cent on the 

U.S. RAW. 

Results

The U.S real average wage increase of 8 cents was the 

combined result of a –11 cent employment component, 

indicating an employment shift toward lower paying jobs; 

a 22 cent wage component, indicating that the mean wages of occupations increased overall; and a –3 cent residual 

component.

The national wage component. The national wage component was 22 cents, indicating the U.S. RAW would have 

increased by 22 cents, or 1.1 percent, if the employment 

shares of occupations had remained constant. The national 

wage component more than offset the national employment component of –11 cents, and it alone propelled the 

U.S. RAW to positive growth. So, while the mean wages 

of occupations increased overall, growth in the U.S. RAW

was hindered because lower paying occupations gained 

employment share relative to higher paying occupations. 

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∆S
Wages and Employment

32  Monthly Labor Review • June 20

The positive wage component indicates either that a majority of employment was in occupations with mean wage 

growth or that those occupations with mean wage growth 

had a greater degree of change in wage than did occupations whose mean wages declined. In fact, in November 

2002 only about 41 percent of employment was in occupations whose mean wage was to grow through May 2007, 

and the remaining 59 percent was in occupations whose 

mean wage was to decrease or remain unchanged during 

the same period. Therefore, the positive wage component 

was driven by occupations with growth in the mean wage 

having a greater degree of change than occupations with a 

decline in the mean wage. 

The influences of occupational wage components. Overall, 

about 51 percent of occupations, making up about 41 

percent of employment, had positive wage components. 

The wage components of occupations depend on their 

employment shares in November 2002 and on the change 

in their mean wage from November 2002 to May 2007. 

An occupation with a higher employment share or greater 

growth in the mean wage will have a larger wage component. Conversely, an occupation with a lower employment share or lesser wage growth will have a smaller wage 

component. Those occupations with the largest wage 

components are generally higher paying and are mostly 

from the management, computer and mathematical science, healthcare practitioner and technical, and sales and 

related groups. As seen in table 2, registered nurses had 

one of the highest wage components, 5 cents, because 

the occupation had both strong real mean wage growth 

of $2.74 and a high November 2002 employment share 

of 1.76 percent. General office clerks, heavy and tractortrailer truck drivers, and stock clerks and order fillers all 

had some of the most negative wage components, at –1 

cent each, because of the occupations’ high employment 

shares coupled with declines in their real mean wages. The 

management occupational group and the healthcare practitioner and technical occupational group had the largest 

wage components of all occupational groups, as shown in 

table 1. Production occupations and office and administrative support occupations had the most negative wage 

components.

The national employment component. The shifting occupational composition of the United States would have 

decreased the RAW by 11 cents, or .6 percent, had occupational mean wages remained constant. In other words, if the 

mean wages of all occupations had remained unchanged, 

changes in the distribution of employment among occupations would have decreased the U.S. RAW by 11 cents. 

This negative employment component indicates that lower 

paying occupations gained employment share relative to 

higher paying occupations. In other words, lower paying 

occupations had faster employment growth than higher 

paying occupations, accounting for a greater share of total 

employment in May 2007 than in November 2002. Because the national employment component aggregates the 

employment components of all occupations, it signifies a 

trend that takes all occupations into account and does not 

necessarily indicate that only the lowest paying occupations gained employment share or that only the highest 

paying occupations lost employment share. Occupations 

that gained and lost employment share will be further explored later in this article. 

The influences of occupational employment effects. Whereas 

the national employment component has documented the 

shift in employment share from higher paying to lower 

paying occupations, the employment effect of an occupation shows precisely the degree and direction that the 

occupation’s change in employment share has had on the 

U.S. RAW. Overall, 42 percent of occupations, making up 

46 percent of employment, had a negative or zero employment effect on the U.S. RAW. For example, the occupation 

of combined food preparation and serving workers, including fast food, has one of the most negative employment 

effects, –4 cents, on the U.S. RAW because this below-average paying occupation increased in employment share 

from 1.57 percent to 1.94 percent. Major occupational 

groups that had negative employment effects on the U.S.

RAW include the healthcare support, food preparation and 

serving related, and personal care and service occupational 

groups.

Still, most occupations had positive employment effects on the U.S. RAW. Many of those occupations with 

the greatest positive employment effects were from the 

business and financial operations group or computer and 

mathematical science group, as many of these above-average-paying occupations gained employment share. For 

example, the occupation of computer software engineers, 

applications had a positive employment effect of 2 cents 

on the U.S. RAW, as this high-paying occupation increased 

in employment share from .28 to .37 percent. 

Grouping occupations by mean wage. Besides identifying 

how each occupation’s mean wage and change in employment share affected the U.S. RAW, broader trends in the 

U.S. labor market can be understood through grouping 

occupations on the basis of mean wage. Doing so will illus-
Monthly Labor Review • June 2009  

Table 3. Employment shares and components of change in the U.S. real average wage, by pay category, Nov. 2002–May 2007

 Pay categories ( organized by mean hourly wage)

Lowest Lower Average Highest All

Category of occupations or percentage summary paying paying paying paying occupations

Below $11.80 to $15.68 to Abo

$11.80 $15.67 $24.11 $24.11

All occupations

Employment share, Nov. ‘02, in percent.............. 24.86 24.41 25.49 25.24 100.00

Employment share, May ‘07, in percent.............. 25.46 23.67 25.29 25.57 100.00

Percentage point change in employment

share, Nov. ‘02–May ‘07     .60 –.74 –.20 .33 .00

   

Total wage component............................................. –.03 –.06 –.04 .35 .22

Total employment component.............................. .05 –.10 –.03 –.03 –.11

Total residual component........................................ .00 .00 .00 –.03 –.03

Total of three components...................................... .02 –.16 –.08 .30 .08

Employment effect –.06 .04 .01   –.09 –.11

Occupations whose mean wage increased

Nov. ‘02–May ‘07

   

Employment share, Nov. ‘02, in percent.............. 6.73 5.10 9.66 19.55 41.03

Employment share, May ‘07, in percent.............. 6.63 4.80 9.57 19.83 40.81

Percentage point change in employment

share, Nov. ‘02–May ‘07........................................... –.10 –.30 –.09 .28 –.22

Occupations whose mean wage declined or 

 remained the same Nov. ‘02–May ‘07    

Employment share, Nov. ‘02, in percent.............. 18.13 19.31 15.84 5.69 58.97

Employment share, May ‘07, in percent.............. 18.83 18.88 15.73 5.75 59.18

Percentage point change in employment

share, Nov. ‘02–May ‘07........................................... .71 –.44 –.11 .06 .22

   

 Percentage summaries     

Percent of pay category’s Nov. ‘02 employment

that was in occupations whose mean wa

increased Nov. ‘02–May ‘07.................................... 27.08 20.88 37.88 77.

Percent of pay category’s Nov. ‘02 employment

that was in occupations whose mean wa

declined or remained the same Nov. ‘02–May ‘07 72.92 79.12 62.12 2

   

Percent of Nov. ‘02 employment in occupations

whose mean wage increased that comes fr

this pay group ............................................................ 16.41 12.42 23.54 47.

Percent of Nov. ‘02 employment in occupations

whose mean wage declined or remained the

same that comes from this pay category......... 30.74 32.75 26.86 9.

trate how occupations with higher and lower mean wages 

experienced changes in mean wage and employment as a 

group, and how these changes influenced the U.S. RAW. 

Table 3 distributes occupations into four categories that 

had roughly equal shares of the Nation’s employment in 

2002. The categories vary by their 2002 mean wages, and 

they are labeled as follows: “highest paying” (mean wage 

over $24.11); “average paying” (mean wage of $15.68 to 

$24.11), a range within which the U.S. RAW of $19.48 

falls; “lower paying” (mean wage of $11.80 to $15.67); 

and “lowest paying” (mean wage below $11.80). Table 3 

also presents employment shares in November 2002 and 

May 2007, employment components, wage components, 

residual components, and employment effects for each of 
Wages and Employment

34  Monthly Labor Review • June 20

Mean wage Mean wage of Mean wage of Mean wage 

Occupational group Total below $11.80 to $15.68 to above

$11.80 $15.67 $24.11 $24.11

  All occupations 762 76 150 285 

Management occupations 30 0 0 4

Business and financial operations occupations 28 0 0 4

Computer and mathematical science occupations    16 0 0 2 14

Architecture and engineering occupations 34 0 0 

Life, physical, and social science occupations 

Community and social services occupations    14 0 2 11 1

Legal occupations 9 0 0 

Education, training, and library occupations 58 1 3 

Arts, design, entertainment, sports,

  and media occupations 37 1 3 20

Healthcare practitioner and technical

  occupations 46 0 7 12 27

Healthcare support occupations 15 4 

Protective service occupations 20 2 3 9 6

Food preparation and serving related

  occupations 16 14 1 

Building and grounds cleaning

  and maintenance occupations 9 3 4 2 0

Personal care and service occupations 33 17 9 6 1

Sales and related occupations 21 3 6 4 8

Office and administrative support occupations 55 6 21 2

Farming, fishing, and forestry occupations    13 4 4 5 0

Construction and extraction occupations    58 0 13 42 3

Installation, maintenance, and repair

  occupations 51 1 10 3

Production occupations 110 13 47 43 7

Transportation and material moving

  occupations 50 7 9 22 12

 

Table 4. The number of occupations in the major occupational groups whose mean hourly wages are in each of 4 pay 

 categories, Nov. 2002

the four categories of pay. 

Table 4 displays the occupational makeup of each pay 

category. The highest paying category consists mainly of 

management; business and financial operations; computer 

and mathematical science; life, physical, and social science; architecture and engineering; healthcare practitioner and technical; and education, training, and library occupations. However, some occupations from other groups 

also are included, such as power plant operators from the 

production group. The average-paying category consists of 

occupations from every occupational group. Still, accounting for most of this category of pay are occupations in 

the office and administrative support; arts, design, entertainment, sports, and media; construction and extraction; 

installation, maintenance, and repair; production; and 

transportation and material moving occupational groups. 

Most occupations within the lower paying category are 

in the office and administrative support; production; and 

construction and extraction occupational groups. The lowest paying category contains many occupations from the 

personal care and service; food preparation and serving 

related; and production occupational groups.

Wage components by pay category. Analyzing the wage 

components of each category of pay as a whole illustrates 

how mean wage growth varied by category. When the 

wage components of occupations within each category 

are summed, only the highest paying category has a positive wage component, while the three other pay categories have negative wage components. When occupations 

are analyzed in the context of these four categories, only 

the highest paying category would have increased the 

U.S. RAW—by 35 cents—from November 2002 to May 

2007 had employment shares remained constant during that period. The lower paying category has the most 

negative wage component, –6 cents, while the lowest 

paying category has a wage component of –3 cents and 

the average-paying category has a wage component of –4 

cents. Breaking out occupations into these pay categories 

shows that the category of highest paying occupations is 

the largest factor in creating a positive national positive 

wage component of 22 cents. 
Monthly Labor Review • June 2009  

The highest paying category’s wage component of 35 

cents indicates either that occupations whose mean wage 

increased make up the majority of employment in this 

category or that those occupations whose mean wage 

grew had a greater degree of wage change than did those 

whose mean wage declined or remained unchanged. The 

analysis shows that in fact about 77 percent of November 2002 employment in this category was in occupations 

with growth in the mean wage. 

For each of the other three pay categories, all of which 

have negative wage components, the majority of employment was in occupations with declines in the mean wage. 

About 62 percent of November 2002 employment within 

the average-paying category, 79 percent of employment 

from that time within the lower paying category, and 73 

percent of employment from that time within the lowest 

paying category was in occupations with a decline in the 

mean wage or an unchanged mean wage from November 

2002 to May 2007. Thus, most employment in the average-, lower, and lowest paying categories was in occupations with decline or no growth in mean wages, whereas 

the majority of employment in the highest paying category was in occupations whose mean wage increased. 

Employment share by pay category. One can see from the 

negative national employment component that lower 

paying occupations gained employment share overall, but 

breaking out occupations into pay categories reveals that 

there also was an employment shift from the middle two 

pay categories to the lowest and highest paying categories. 

The lowest paying category had the largest increase in employment share, .60 percentage point, while the highest 

paying category increased employment share by about half 

that (.33 percentage point). The average-paying category 

lost .20 percentage point of its share of employment, and 

the lower paying category lost the greatest employment 

share, with a decrease of .74 percentage point. This same 

“polarization” of the U.S. labor market was studied by David H. Autor, Lawrence F. Katz, and Melissa S. Kearney in 

the 1990s; they found “employment polarizing into highwage and low-wage jobs at the expense of traditional 

middle-skill jobs.”8 

Employment components and employment effects by pay 

category. Analyzing the overall employment effect of 

each category of pay reveals how shifts in employment 

share have influenced the U.S. RAW. The lowest paying 

category’s gain of .60 percentage point in employment 

share resulted in an employment effect of –6 cents on the 

RAW. Still, the employment component of the category is 

positive, at 5 cents, showing that within the lowest paying category, occupations with higher mean wages gained 

employment share. Meanwhile, the lower paying category 

lost .74 percentage point of employment share, causing a 

positive employment effect of 4 cents on the U.S. RAW.

Within the lower paying category, however, employment 

share shifted away from higher paying occupations, evidenced by the category’s employment component of –10 

cents. The average-paying category had an employment 

effect of about 1 cent on the U.S. RAW, although its employment component of –3 cents indicates that among 

the occupations within the category, employment share 

shifted slightly towards lower paying occupations. Because 

the highest paying category contains many management 

occupations, the results of this analysis for the highest 

paying category should be interpreted with caution. 

Examination of employment trends within the four 

pay categories shows that the negative national employment component is explained by the trend of an overall 

shift in employment towards the lowest paying category. 

There was also a shift in employment towards occupations 

with lower mean wages within two or three of the pay 

categories. 

Grouping occupations by change in mean wage. In addition to grouping occupations on the basis of their November 2002 mean wage, another way to allow hidden 

patterns to emerge is to separate occupations into those 

with growth in the mean wage and those with a decline 

in the mean wage or an unchanged mean wage. Table 3 

displays employment components, wage components, 

and changes in employment share for occupations whose 

mean wage increased from November 2002 to May 2007 

and for occupations whose mean wage decreased or remained unchanged during the same period. As described 

earlier, in November 2002 only about 41 percent of employment was in occupations whose mean wage increased 

during the 41⁄2-year period, and the remaining 59 percent 

was in occupations whose mean wage declined or remain 

unchanged during that time. The highest paying category 

accounted for about 48 percent of the November 2002 

employment of occupations whose mean wage was to 

grow through May 2007. So, not only was most employment in the highest paying category in occupations that 

experienced growth in the mean wage, as discussed earlier, 

but the highest paying category accounted for almost half 

of employment among occupations whose mean wage increased. The average-paying category made up about 24 

percent of employment in occupations whose mean wage 

increased, and the remaining 29 percent came from the 
Wages and Employment

36  Monthly Labor Review • June 20

Table 5. Employment shares, wage components, and employment effects for categories of education and training, 

 Nov. 2002–May 2007

 

Number Employof ment Change in Employoccupa- share, employ- Wage ment

Mean Mean Mean Mean 

tions November ment component effect wage wage wage wage 

2002 share below of $11.80 of $15.68 above

$11.80 to $15.67 to $24.11 $24.11

All categories..................... 759 100.00 — 0.22 –0.11 76 1

First professional degree.......... 16 1.09 0.09 –.01 .04 0 0 0 16

Doctoral degree.......................... 45 1.09 .07 .02 .01 0 0 1 44

Master’s degree........................... 29 1.13 .09 .01 .01 0 1 6 22

Bachelor’s or higher degree,

plus work experience1 ............ 33 5.03 –.77 .17 –.22 0 0 4 29

Bachelor’s degree ....................... 103 11.48 .95 .06 .10 0 1 28 74

Associate degree......................... 39 4.07 .12 .06 .01 0 2 25 12

Postsecondary vocational

award............................................ 48 5.00 –.07 .01 .00 3 12 27 6

Work experience in a related

occupation ................................. 47 8.92 –.34 .06 –.05 1 2 22 22

Long-term on-the-job

training 

Moderate-term on-the-job

training........................................ 180 19.63 –.34 –.07 .04 13 62 9

Short-term on-the-job

training....................................... 133 35.83 .03 –.07 –.04 57 55

Not classified2................................ 3 .27

Education or 

training category

1 The results of this category should be interpreted with caution because

they may be affected by refinements in occupational coding procedures.

2 The occupations represented in these data were assigned to more than

one category of education or training. 

Number of occupations by pay category

lower paying and lowest paying categories. 

Among occupations for which the mean wage declined 

or remained the same from November 2002 to May 2007, 

the lowest and lower paying categories made up 63 percent of November 2002 employment. The average-paying 

category made up 27 percent of employment among the 

same occupations, and the highest paying category accounted for the remaining 10 percent. This finding further 

explains the strong positive wage components of the highest paying category and the negative wage components of 

the three other categories. 

A final underlying trend behind the .41-percent 

growth of the RAW was faster overall growth in employment among occupations whose mean wage declined or 

did not change, in comparison with occupations whose 

mean wage increased. Overall, those occupations whose 

mean wage decreased or remained the same gained .22 

percentage point of employment share. Most of the loss in 

employment share from occupations with growth in the 

mean wage came from the average-paying, lower paying 

and the lowest paying categories, which lost a combined 

.49 percentage point of employment share. The highest 

paying occupations with mean wage growth gained .28 

percentage point of employment share. In contrast, the 

lowest paying occupations whose mean wage decreased 

or remained the same gained .71 percentage point of employment share; the lower paying and average-paying categories whose mean wage declined or stayed the same lost 

employment share. As mentioned earlier in this article, the 

lowest paying and highest paying categories were the two 

pay categories that gained employment share. Categorizing occupations by change in mean wage reveals that for 

the lowest paying category, most of the occupations that 

gained employment share were occupations with a decline 

or no change in the mean wage, and that for the highest paying category, most of the occupations that gained 

employment share were occupations whose mean wage 

increased. 

Additional applications 

There are many potential additional applications for this 
Monthly Labor Review • June 2009  

Table 6. Components of change in the real average hourly

 wages of U.S. States, Nov. 2002–May 2007

 

 Wage Employ- Residual Total of

 com- ment com- three State

ponent com- ponent compo-

 ponent nents1

 

Alabama ........................      $0.05 $–0.13 $–0.02 $–0.10

Alaska .............................      .11 –.03 –.13 –.04

Arizona...........................      .19 –.18 –.12 –.11

Arkansas........................      .24 –.01 –.04 .19

California .......................      .11 .32 –.05 .38

Colorado........................      .03 .03 .02 .08

Connecticut..................      –.31 .24 –.02 –.09

Delaware .......................      1.00 –.29 –.28 .44

Florida ...........................      .60 –.21 –.16 .24

Georgia ..........................      –.32 .10 –.01 –.23

Hawaii.............................      –.07 .21 –.03 .11

Idaho...............................      –.01 .07 –.17 –.12

Illinois.............................      1.24 –.31 –.16 .76

Indiana ...........................      –.12 –.25 –.02 –.38

Iowa ................................      .30 –.17 –.12 .01

Kansas............................      –.17 –.09 –.02 –.28

Kentucky........................      –.19 .02 –.06 –.22

Louisiana .......................      .18 –.24 –.05 –.12

Maine..............................      .44 –.14 –.07 .24

Maryland.......................      1.25 –.24 –.16 .85

Massachusetts.............      .78 .03 –.06 .75

Michigan........................      –.30 .04 .04 –.22

Minnesota.....................      –.06 .24 –.02 .15

Mississippi.....................      .49 –.04 –.06 .39

Missouri .........................      .52 –.49 –.20 –.17

Montana ........................      .42 –.29 –.10 .03

Nebraska........................      .37 –.36 –.13 –.12

Nevada...........................      –.11 –.09 .05 –.15

New Hampshire ..........      .55 .04 –.01 .58

New Jersey....................      .20 .29 –.05 .44

New Mexico..................      .73 –.51 .01 .23

New York........................      –.14 .34 .05 .25

North Carolina.............      .02 –.10 –.10 –.18

North Dakota...............      .81 –.09 –.18 .54

Ohio.................................      .15 –.33 –.06 –.24

Oklahoma .....................      –.25 .05 .02 –.18

Oregon...........................      .00 .09 –.04 .05

Pennsylvania................      .49 –.60 –.15 –.25

Rhode Island ................      .38 .26 –.09 .55

South Carolina.............      .12 –.20 –.11 –.18

South Dakota...............      .11 –.09 .00 .02

Tennessee .....................      .00 –.13 –.02 –.15

Texas...............................      .11 –.28 –.12 –.29

Utah ................................      .16 –.02 .00 .14

Vermont.........................      .18 .10 .05 .32

Virginia...........................      1.18 –.19 –.04 .95

Washington .................      .32 –.04 .02 .30

Washington, DC............      1.22 .29 .47 1.98

West Virginia ................      –.03 –.36 –.07 –.47

Wisconsin......................      .07 –.06 .02 .03

Wyoming.......................      .33 .27 .00 .61

  1 Numbers may not add precisely because of roundi

article’s analysis of the effects of changing employment 

shares and of changing occupational composition on 

change in the U.S. RAW. Two applications that will be 

briefly explored in this section are patterns among education and training categories and an analysis of the average 

wages of U.S. States. 

Education and training categories. Just as this article 

groups occupations on the basis of their mean wage to 

demonstrate trends among lower and higher paying occupations, it also groups occupations into education and 

training categories to reveal trends among occupations 

associated with greater or lesser education and training. 

The BLS Employment Projections program assigns each 

occupation to 1 of 11 education and training categories, 

which range from “short-term on-the-job training” to 

“first professional degree.” The most common source(s) 

and level of education for workers in a given occupation 

serves as the basis for placing the occupation in a particular category. Table 5 displays the employment shares, wage 

components, and employment effects of these categories 

of occupations. 

The wage components of the three on-the-job training categories are negative, and the wage components of 

most of the eight other education and training categories 

are positive. The moderate-term on-the-job training and 

short-term on-the-job training categories both have the 

most negative wage components, –7 cents, and the longterm on-the-job training category has a wage component 

of –1 cent. Occupations in the category of bachelor’s 

or higher degree, plus work experience had the greatest 

overall wage component, 17 cents, even though these 

occupations made up only 5 percent of employment in 

November 2002. This shows that this category had the 

greatest increase in real average wage of all the education 

and training categories. The categories of bachelor’s degree, associate degree, and work experience in a related 

occupation each had relatively high wage components of 

about 6 cents. 

Regarding shifts in employment share among the education and training categories, those occupations in the 

category of bachelor’s degree gained the most employment 

share, .95 percentage point. Other education and training 

categories that made slight gains in employment share 

are long-term on-the-job training, short-term on-the-job 

training, associate degree, master’s degree, doctoral degree, and first professional degree. The categories of work 

experience in a related occupation and moderate-term 

on-the-job training each lost about .34 percentage point 

of employment share, and the category of postsecondary vocational award decreased in employment share by 

.07 percentage point. Autor, Katz, and Kearney, observed 

“more rapid employment growth in the bottom end of the 
Wages and Employment

38  Monthly Labor Review • June 20

education distribution than in the middle” in the 1990s, 

but this article’s findings from the 2000s indicate that the 

trend has changed. 

Wage analysis by State. Just as OES data are used to 

analyze the U.S. RAW, they also can be used to analyze 

the components of changes in the average wages of U.S. 

States. The wage component, employment component, 

residual component, and total component for each State 

and the District of Columbia are shown in table 6. The 

patterns in employment and mean wages found at the 

national level also occur in most States. For example, the 

overall shift toward occupations with lower mean wages 

is found in 32 States. The States with the most negative 

employment components—that is, the most pronounced 

shift in employment toward occupations with lower mean 

wages—are Pennsylvania, New Mexico, Missouri, West 

Virginia, and Nebraska. The five places with the greatest 

positive employment components, or the most pronounced 

employment shift towards occupations with higher mean 

wages, are New York; California; New Jersey; Washington, DC; and Wyoming. 

Most States have a positive wage component (35 

States and the District of Columbia), but 15 States have 

negative occupational wage components, indicating that 

occupational mean wages declined overall in the State. 

The States with the most negative wage components are 

Georgia, with wage component of –32 cents; Connecticut, with wage component of –31 cents; and Michigan, 

with a wage component of –30 cents. The places with the 

greatest positive wage components are Maryland; Illinois; 

Washington, DC; and Virginia. Some States that have 

positive wage components still had a decline in the average wage—Pennsylvania being one example—because the 

negative employment component is greater in degree than 

the wage component. As seen in table 6, wage components and employment components differ greatly by State, 

with some States having an employment component and 

a wage component that are both negative, such as Kansas and Indiana, and some States having an employment 

component and wage component that are both positive, 

such as Vermont and California. 

USING OES DATA TO UNDERSTAND COMPONENTS

of U.S. real average wage growth from November 2002 

to May 2007 reveals many trends in occupational mean 

wages and employment shares. The analysis revealed that 

the increase of 8 cents in the U.S. RAW could be decomposed into an employment component of –11 cents, a 

wage component of 22 cents, and a residual component 

of –3 cents. These components indicate that overall, the 

mean wages of individual occupations grew faster than is 

evident from the national average wage growth statistic 

because the national average wage was suppressed by occupations with lower mean wages gaining employment 

share. Another finding was that a majority of employment was in occupations that experienced a decline or no 

change in the mean wage, and the group of occupations 

whose mean wage decreased or remained the same made 

a slight gain in employment share; these two phenomena 

also hampered the growth of the U.S. RAW. 

Grouping occupations by mean wage revealed that 

the lowest, lower, and average-paying categories of occupations each have overall negative wage components, 

indicating that taken together, occupations within each 

of these categories experienced a decline in their mean 

wage. An additional finding of this article was a shift in 

employment from the two middle-paying categories of 

occupations to the lowest and highest paying categories. 

The lowest paying category increased the most in employment share, .60 percentage point, and most of this gain 

was made by occupations whose mean wage decreased or 

did not change. The pay categories also revealed that the 

increase in the U.S. RAW is due mostly to growth in the 

mean wages of occupations in the highest paying category, 

which had a wage component of 35 cents and made up 48 

percent of employment among occupations whose mean 

wage increased from November 2002 to May 2007. 

1

 The adjustment for inflation was made using the BLS Consumer Price 

Index for Urban Wage Earners and Clerical Workers. 

2

 Katherine Baicker and Amitabh Chandra, “The Labor Market Effects 

Of Rising Health Insurance Premiums,” Journal of Labor Economics, July 2006, 

pp. 609–34. 

3 John Jones, “What do OES data have to say about increasing wage inequality?” Monthly Labor Review, June 2009, pp. 39–49. 

4 OES statistics cover part-time and full-time wage and salary workers, and 

do not cover the self-employed, owners and partners in unincorporated firms, 

household workers, or unpaid family workers.

5

 The common coding system is the 2002 OES occupational coding structure. 

6

 Mean wages for November 2002 have been adjusted for inflation to May 

2007 dollars. All wages are discussed in terms of May 2007 dollars. 

7

 Patrick Kilcoyne, “The Role of Occupational Composition in State Wage 

Differentials,” Occupational Employment and Wages, May 2005, Bulletin 2585 

(Bureau of Labor Statistics, May 2007).

8 David H. Autor, Lawrence F. Katz, and Melissa S. Kearney, “The Polarization of the U.S. Labor Market,” American Economic Review, May 2006, pp. 

189–194.

Notes