10 Monthly Labor Review October 1996

Elderly Consumers

Anne E. Polivka is a

research economist in

the Office of

Employment Research

and Program

Development, Bureau

of Labor Statistics.

of continuing in their jobs. Under this definition,

there were approximately 2.7 million contingent

workers in February 1995.

The second estimate of contingent workers

added self-employed workers and independent

contractors who expected their employment to

last for an additional year or less and who had

been self-employed or an independent contractor for 1 year or less. It also changed the measure of actual and expected job tenure for contract workers and temporary help workers from

tenure with these employment intermediaries to

tenure in their current assignment. Under these

criteria, 3.4 million workers were classified as

contingent in February 1995.

The third estimate of contingency expanded

the second estimate by removing the 1-year requirement on actual and expected tenure for

wage and salary workers. (The tenure constraint

could not be removed for self-employed workers and independent contractors because they

were asked a different set of questions.) Essentially, under estimate 3, contingent workers were

defined as workers who did not expect their jobs

to last, except those who, for personal reasons,

expected to leave jobs that they would otherwise

be able to retain. Under this broadest estimate,

6 million workers were classified as contingent.

In this article, the characteristics of continT o some, the terms “contingent work” and

“bad jobs” are synonymous, although that

was not necessarily what was intended

when the phrase was originally coined. To examine how closely these two notions may be

linked, it is necessary to analyze specific attributes of contingent jobs, along with the personal characteristics of those who fill them. This

article profiles contingent workers using data

collected through a special supplement to the

February 1995 Current Population Survey (CPS).

This supplement provides the first comprehensive measurement of contingent workers using

carefully constructed definitions.

The underlying concept that was operationalized in the supplement defines contingent

workers as individuals who do not have an explicit or implicit contract for ongoing employment. The introductory article in this issue

(pages 3–9) discusses three estimates of the

number of contingent workers constructed from

the February 1995 CPS supplement data. The first

estimate was restricted to wage and salary workers who expected their jobs to last for an additional

year or less and who had worked at their jobs for 1

year or less. Individuals who did not expect to continue in their jobs for personal reasons, such as retirement or returning to school, were not considered contingent if they would have had the option

A profile of

contingent workers

Contingent workers were more likely to be female,

black, young, enrolled in school,

and employed in services and construction industries

than were noncontingent workers;

more than 10 percent were teachers

Anne E. Polivka

A Profile of Contingent Workers
Monthly Labor Review October 1996 11

gent workers under each of these three definitions are examined. The characteristics of

noncontingent workers, defined as those who

were not contingent even under the broadest estimate of contingency (estimate 3), are provided

as a point of reference.

Demographic characteristics

Sex and race. Given concerns about discrimination and equality of job opportunities,1 two of

the most important characteristics of contingent

workers are their gender and race. Examination

of the figures in table 1 indicates that contingent

workers were slightly more likely to be women

or blacks than were noncontingent workers. Specifically, more than 50 percent of contingent

workers across all three estimates of contingency

were women. In comparison, only 46 percent of

noncontingent workers were women. Similarly,

the data in table 1 indicate that about 14 percent

of contingent workers were black, compared

with a little more than 10 percent of noncontingent workers. In exploring the gender and racial

composition of contingent workers, it is important to examine the gender and racial composition of contingent workers within specific industries and occupations. It could be that women

and blacks were more likely to be contingent

simply because they were more likely to be employed in industries and occupations that had a

higher proportion of contingent workers.

Age. One of the most startling differences between contingent and noncontingent workers

was in the age distributions of the two groups.

Although the age distribution of contingent

workers varied to some degree across the estimates of contingency, under all three estimates,

contingent workers were more than twice as

likely as noncontingent workers to be between

the ages of 16 and 24. Under the first estimate,

41.6 percent of contingent workers were under

age 25, while only 13.9 percent of noncontingent

workers were in this age group. Further, depending on the definition chosen, contingent workers

were 2-1/2 to 4 times more likely to be 16 to 19

years old than were noncontingent workers, with

estimates 1 and 2 having proportionately more

young workers than estimate 3. (See table 1.)

Under the two estimates that require workers

to have been with their current employer or in

their arrangements for no more than a year

 Characteristic

Estimate 1 Estimate 2 Estimate 3

Noncontingent

workers 1

 Contingent workers

Table 1. Employed contingent and noncontingent workers, by 

 sex, race , Hispanic origin, age, and educational 

 attainment, February 1995

[Percent distribution]

Total, 16 years and older ............. 100.0 100.0 100.0 100.0

 Sex

Men ............................................. 49.3 49.4 49.6 54.0

Women ........................................ 50.7 50.7 50.4 46.0

 Race and Hispanic origin

White ........................................... 80.1 80.1 80.9 85.7

Black ........................................... 14.0 13.6 13.3 10.5

Hispanic origin ............................ 13.6 12.9 11.3 8.3

 Age (in years)

Total ............................................ 100.0 100.0 100.0 100.0

16 to 19 ..................................... 16.7 15.2 10.7 4.3

20 to 24 ..................................... 25.0 22.1 19.8 9.6

25 to 34 ..................................... 26.0 27.5 26.3 26.1

35 to 44 ..................................... 18.5 19.8 21.0 28.0

 45 to 54 ..................................... 8.2 9.5 12.6 19.8

 55 to 64 ..................................... 3.8 3.7 5.9 9.4

 65 and older .............................. 1.8 2.1 3.7 2.8

Men ............................................. 100.0 100.0 100.0 100.0

16 to 19 ..................................... 14.6 13.9 9.7 4.0

20 to 24 ..................................... 24.4 21.7 19.6 9.6

25 to 34 ..................................... 26.2 27.5 27.8 26.4

35 to 44 ..................................... 20.3 20.9 20.5 28.0

45 to 54 ..................................... 6.7 8.6 11.4 19.5

55 to 64 ..................................... 5.3 4.9 7.2 9.4

65 and older .............................. 2.4 2.6 3.9 3.1

Women ........................................ 100.0 100.0 100.0 100.0

16 to 19 ..................................... 18.7 16.6 11.7 4.6

20 to 24 ..................................... 25.7 22.6 20.1 9.6

25 to 34 ..................................... 25.8 27.4 24.8 25.7

35 to 44 ..................................... 16.8 18.8 21.4 28.1

45 to 54 ..................................... 9.6 10.5 13.8 20.2

55 to 64 ..................................... 2.3 2.6 4.6 9.4

65 and older .............................. 1.2 1.7 3.6 2.5

 Educational attainment

(those not enrolled in school)

Total ............................................ 100.0 100.0 100.0 100.0

 Less than a high school

 diploma ................................... 17.2 16.9 14.6 10.5

 High school graduate,

 no college ............................... 28.7 28.4 29.4 33.6

 Less than a bachelor’s degree .. 28.7 28.8 25.8 28.7

 College graduates ..................... 17.8 17.8 17.5 18.2

 Advanced degree ..................... 7.6 8.2 12.7 9.1

1 Noncontingent workers are those who do not fall into any estimate of “contingent” workers.

NOTE: Detail for the above race and Hispanic-origin groups will not sum to totals because data for the “other races” group are not presented and Hispanics are included in both

the white and black population groups. Detail for other characteristics may not sum to totals

due to rounding.
12 Monthly Labor Review October 1996

Elderly Consumers

(estimates 1 and 2), contingent workers also were less likely to

be age 65 and older. When the restrictions on job tenure were

removed (estimate 3), however, the proportion of workers in

this age group was slightly larger for contingent than

noncontingent workers (3.7 percent versus 2.8 percent).

Noncontingent workers were more likely than contingent

workers to be 45 to 64 years of age under every estimate, but

the gap narrowed as contingent workers were more broadly

defined. The slight shift of the age distribution to older workers

under estimate 3 is consistent with the correlation between age

and tenure. Removal of the maximum tenure restrictions seems

to capture some workers who had been with their employers a

fair amount of time and who either always had an uncertain

employment relationship or who had been switched from a

stable to an unstable relationship.

When comparing contingent and noncontingent workers,

both men and women displayed similar age distributions. However, it is interesting to note that female contingent workers

were somewhat more likely to be teenagers and less likely to

be over the age of 55 than were male contingent workers.

School enrollment, educational attainment

Two other personal characteristics of contingent workers to examine are the proportion of contingent workers enrolled in

school and their educational attainment. The data indicate that

contingent workers were three to four times more likely to be

enrolled in school than were noncontingent workers. School

enrollment rates ranged from 17.7 percent of contingent workers under estimate 3 to 23.0 percent under estimate 1, compared with only 5.3 percent for noncontingent workers. Even

among those ages 16 to 24, an age when people are more likely

to be enrolled in school, a higher proportion of contingent workers were enrolled in school, compared with noncontingent

workers—58.1 percent and 38.4 percent, respectively.2 Apparently, a lack of long-term commitment between workers and

employers accords well with school attendance. This seems to

be especially true for full-time college students. Of those contingent workers who were students, 74.0 percent under contingent estimate 3 were attending college, of whom 85.1 percent

were full-time students.

Among those not enrolled in school, a larger proportion of

contingent than noncontingent workers did not have a high

school diploma. Under contingent estimate 1, 17.2 percent of

those not enrolled in school were classified as having only some

high school. This proportion edged down to 16.9 percent under

estimate 2 and 14.6 percent under estimate 3. By comparison,

only 10.5 percent of noncontingent workers were classified as

having only some high school. (See table 1.)

In contrast, the proportions of contingent and noncontingent

workers who had some college or a college degree were fairly

equal across estimates. With respect to advanced degrees, contingent workers under estimates 1 and 2 were less likely than

noncontingent workers to have a masters degree, a doctorate, or a professional degree (such as a law degree). This

relationship was reversed, however, when the tenure requirements were removed. Almost 13 percent of contingent workers under estimate 3 had an advanced degree,

compared with 9.1 percent of noncontingent workers. To

the extent that education and job skills are correlated, these

figures indicate that under estimates 1 and 2, contingent

workers were less likely to be skilled workers than were

noncontingent workers, while under estimate 3, contingent

workers appeared to be both less skilled and more skilled

than their noncontingent counterparts. An examination of

the occupational distributions of contingent and noncontingent workers will shed more light on the skill levels embodied in the jobs these workers are occupying.

Occupations

Contingent workers were more likely to be in professional,

service, administrative support, and labor occupations, and

were less likely to be in managerial or sales occupations.

Contingent and noncontingent workers were about equally

likely to be in precision production and farming occupations. (See table 2.)

At first glance, it might seem surprising that contingent

workers were over represented in professional specialty occupations. This finding was driven by the fact that the professional specialty occupations include teachers, who had

above-average rates of contingency. In fact, teachers accounted for more than 10 percent of all contingent workers

under estimate 3. It is interesting to note that teachers at

institutions of higher education had higher rates of contingency than did their counterparts at the grade school level.

Teachers at the college and university level had rates ranging from 10.0 percent under the narrowest estimate to 25.9

percent under the broadest estimate. In comparison, elementary and secondary teachers’ rates of contingency,

while still considerably above average, ranged from 3.1

percent under estimate 1 to 7.8 percent under estimate 3.

Apparently, colleges and universities use more adjunct or

temporary teachers with short-term contracts. It also could

be, however, that the inherent uncertainties of the tenure

process play an important role for college and university

teachers.

The other group within the professional ranks that constituted a fairly large proportion of all contingent workers

was “other professional specialty.” This category alone

contained 5.1 percent of all contingent workers under estimate 1. Detailed occupations within the “other professional

specialty” group that had above-average rates of contingency across all three estimates included editors and reporters, photographers, actors and directors, and athletes.

The relatively large proportion of contingent workers in

Profile of Contingent Workers
Monthly Labor Review October 1996 13

Table 2. Distribution by occupation of employed contingent and 

 noncontingent workers, and contingency rates by occupation,

 sex, and race, February 1995

 Contingent workers Non-

 Occupation, sex, and race contingent

 workers1

Total, 16 years and older (thousands) ................ 2,739 3,422 6,034 117,174

Percent distribution ............................................ 100.0 100.0 100.0 100.0

Executive, administrative, and managerial .... 4.9 5.5 7.6 14.0

Professional specialty .................................... 17.2 16.6 20.6 14.6

Technicians and related support .................... 1.8 2.2 2.7 3.2

Sales occupations .......................................... 6.2 6.9 6.4 12.2

Administrative support, including clerical ....... 20.9 18.7 17.7 15.0

Service occupations ....................................... 17.9 19.8 16.0 13.4

Precision production, craft, and repair ........... 11.0 11.3 10.0 10.8

Operators, fabricators, and laborers .............. 17.4 16.1 15.8 14.2

Farming, forestry and fishing ......................... 2.6 3.0 3.0 2.6

 Contingency rates2

Total ................................................................... 2.2 2.8 4.9 ....

Executive, administrative, and managerial .... .8 1.1 2.7 ....

Professional specialty ................................... 2.6 3.1 6.8 ....

Technicians and related support ................... 1.3 1.9 4.2 ....

Sales occupations ......................................... 1.2 1.6 2.6 ....

Administrative support, including clerical ...... 3.1 3.4 5.8 ....

Service occupations ...................................... 3.0 4.1 5.8 ....

Precision production, craft, and repair .......... 2.3 2.9 4.6 ....

Operators, fabricators, and laborers ............. 2.7 3.1 5.4 ....

Farming, forestry and fishing ......................... 2.2 3.2 5.6 ....

Men:

Executive, administrative, and managerial .... .6 .9 2.3 ....

Professional specialty ................................... 2.3 3.1 6.6 ....

Technicians and related support ................... 1.7 2.4 4.8 ....

Sales occupations ......................................... .8 1.3 2.0 ....

Administrative support, including clerical ...... 2.9 3.3 6.0 ....

Service occupations ...................................... 2.9 3.2 4.7 ....

Precision production, craft, and repair .......... 2.3 2.9 4.5 ....

Operators, fabricators, and laborers ............. 2.7 3.1 5.4 ....

Farming, forestry and fishing ......................... 2.4 3.4 5.9 ....

Women:

Executive, administrative, and managerial .... 1.1 1.3 3.2 ....

Professional specialty ................................... 2.8 3.1 7.0 ....

Technicians and related support ................... .9 1.5 3.6 ....

Sales occupations ......................................... 1.5 1.9 3.4 ....

Administrative support, including clerical ...... 3.1 3.5 5.7 ....

Service occupations ...................................... 3.0 4.6 6.5 ....

Precision production, craft, and repair .......... 1.6 3.3 4.9 ....

Operators, fabricators, and laborers ............. 2.8 3.2 5.7 ....

Farming, forestry and fishing ......................... 1.4 2.4 4.3 ....

White:

Executive, administrative, and managerial .... .7 1.0 2.6 ....

Professional specialty ................................... 2.6 3.1 6.8 ....

Technicians and related support ................... 1.3 2.0 3.9 ....

Sales occupations ......................................... 1.0 1.4 2.4 ....

Administrative support, including clerical ...... 2.8 3.2 5.5 ....

Service occupations ...................................... 2.9 4.1 5.7 ....

Precision production, craft, and repair .......... 2.1 2.7 4.1 ....

Operators, fabricators, and laborers ............. 2.6 2.9 5.0 ....

Farming, forestry and fishing ......................... 1.9 2.8 4.9 ....

Black:

Executive, administrative, and managerial .... 1.0 1.0 3.6 ....

Professional specialty ................................... 1.8 2.6 5.2 ....

Technicians and related support ................... .7 1.6 4.2 ....

Sales occupations ......................................... 1.4 2.1 4.2 ....

Administrative support, including clerical ...... 4.9 4.9 7.0 ....

Service occupations ...................................... 3.1 4.0 6.1 ....

Precision production, craft, and repair .......... 3.7 4.6 8.3 ....

Operators, fabricators, and laborers ............. 3.2 3.8 7.3 ....

Farming, forestry and fishing ......................... 2.5 5.5 5.5 ....

1 Noncontingent workers wre those who do not fall into any estimate of “contingent” workers. 2 A contingency rate is the proportion of all employed who are contingent.

NOTE: Distribution may not sum to 100 percent due to rounding.

these occupations in combination

with those in teaching occupations

seems to belie the image of all contingent jobs as being low-skilled

jobs.

On the other hand, the higher

proportion of contingent workers in

the administrative support occupations—20.9 percent to 17.7 percent

of contingent workers versus 15.0

percent of noncontingent workers—comes closer to the stereotypical notion that contingent workers

hold jobs that require relatively

little formal training. Within the administrative support category, detailed occupations with above-average rates of contingency across

all three estimates included secretaries, stenographers, typists, and

other clerical occupations. In the

latter subcategory, file clerks had a

particularly high rate of contingency, ranging from 18.4 percent to

25.3 percent. In addition to these

typical office support occupations,

computer equipment operators under

all three estimates, and mail and message distributors under the first estimate, also had higher rates of contingency. In fact, among nonsupervisory

workers, the only administrative support occupation that did not have an

above-average rate of contingency, at

least under the first estimate, was financial records processing.

Contingent workers also were

disproportionately represented in

service occupations, with 17.9 percent of contingent workers under

estimate 1, 19.8 percent under estimate 2, and 16.0 percent under estimate 3 in service occupations, compared with only 13.4 percent of

noncontingent workers. The subcategory within service occupations with the highest rate of contingency was food service occupations, which include waitresses and

waiters, cooks, and bartenders.

Within other subcategories of services occupations, three detailed

categories with above-average rates

Estimate 1 Estimate 2 Estimate 3
14 Monthly Labor Review October 1996

Elderly Consumers

Total, 16 years and older (thousands) .......... 2,739 3,422 6,034 117,174

Percent distribution ...................................... 100.0 100.0 100.0 100.0

Agriculture ................................................. 2.8 3.0 2.6 2.6

Mining ....................................................... .2 .2 .3 .6

Construction .............................................. 11.5 11.8 9.8 5.5

Manufacturing ........................................... 10.0 9.5 10.8 17.1

Transportation and public utilities .............. 3.8 3.2 4.3 7.2

Wholesale trade ........................................ 1.3 1.4 1.8 3.9

Retail trade ................................................ 12.1 11.9 10.3 17.0

Finance, insurance, and real estate .......... 2.0 1.9 2.6 6.7

Services .................................................... 53.5 54.8 54.0 34.5

Public administration ................................. 2.7 2.2 3.6 5.0

 Contingency rates2

Total, 16 years and older .............................. 2.2 2.8 4.9 ....

Agriculture ............................................... 2.5 3.3 5.0 ....

Mining ..................................................... 1.0 1.0 2.7 ....

Construction ............................................ 4.5 5.8 8.4 ....

Manufacturing ......................................... 1.3 1.6 3.1 ....

Transportation and public utilities ............ 1.2 1.3 3.0 ....

Wholesale trade ...................................... .7 1.0 2.3 ....

Retail trade .............................................. 1.6 2.0 3.0 ....

Finance, insurance, and real estate ........ .7 .8 2.0 ....

Services .................................................. 3.4 4.3 7.5 ....

Public administration ............................... 1.2 1.2 3.6 ....

Men:

Agriculture ................................................. 2.7 3.5 5.7 ....

Mining ....................................................... .6 .6 2.6 ....

Construction .............................................. 4.7 5.8 8.5 ....

Manufacturing ........................................... 1.2 1.4 3.0 ....

Transportation and public utilities .............. 1.1 1.2 2.7 ....

Wholesale trade ........................................ .5 .8 1.6 ....

Retail trade ................................................ 1.5 1.9 2.6 ....

Finance, insurance, and real estate .......... .4 .5 1.8 ....

Services .................................................... 3.4 4.3 7.5 ....

Public administration ................................. .6 .6 3.0 ....

Women:

Agriculture ................................................. 1.8 2.5 3.2 ....

Mining ....................................................... 3.5 3.5 3.5 ....

Construction .............................................. 2.5 5.3 7.5 ....

Manufacturing ........................................... 1.7 1.9 3.4 ....

Transportation and public utilities .............. 1.5 1.5 3.7 ....

Wholesale trade ........................................ 1.4 1.8 4.0 ....

Retail trade ................................................ 1.7 2.1 3.4 ....

Finance, insurance, and real estate .......... .9 1.0 2.1 ....

Services .................................................... 3.3 4.3 7.4 ....

Public administration ................................. 2.0 2.0 4.4 ....

Table 3. Distribution by industry of employed contingent and

noncontingent workers, and contingency rates by industry,

sex, and race, February 1995

Profile of Contingent Workers

Noncontingent

workers Estimate 1 Estimate 2 Estimate 3 1

Contingent workers

 Industry, sex, and race

of contingency were attendants at amusement and recreational facilities, child care

workers in private households, and janitors and cleaners. It is important to note,

however, that athough janitors and cleaners had above-average rates of contingency, even under the broadest estimate,

only 5.5 percent of all janitors and cleaners were contingent.

The only other major occupation group

with above-average rates of contingency

and a disproportionately large number of

contingent workers was operators, fabricators, and laborers. The detailed occupations

within this category that contained a disproportionate number of contingent

workers were welders and cutters, assemblers, production testers, miscellaneous machine operators, and construction laborers.

A major occupation group in which

there was no overall statistical difference

between the proportion of contingent and

noncontingent workers was precision production, craft, and repair. The lack of an

overall difference, however, concealed

large differences at the detailed level. For

example, rates of contingency in construction trades ranged from 4.8 percent

under estimate 1 to 8.5 percent under estimate 3. These were roughly double the

comparable estimates for all workers. In

contrast, the rate of contingency for mechanics and repairers ranged from 1.0 percent to 2.4 percent and the rates of contingency for those in the other precision

production, craft, and repair occupations

ranged from 0.7 percent to 2.3 percent,

about half the averages for all workers.

Overall, the occupational distribution

occupations with higher contingency rates, rather than a

higher rate of contingency within any occupation. The only

exceptions were the sales and services occupations, where

women’s rates of contingency were generally higher than

men’s. Blacks, in contrast, tended to have higher rates of

contingency within the occupations that employed the majority of contingent workers. Blacks actually had a lower

rate of contingency than whites in the professional specialty

occupations. However, blacks had markedly higher rates of

contingency in the administrative support; precision production, craft, and repair; and operators, fabricators, and laborers occupations. These occupations together employed 49.3

percent of those who were contingent under definition 1.

of contingent workers indicates that they are employed in a

wide variety of jobs. Some jobs, such as janitors, cleaners,

waitresses, and waiters are at the lower end of the skill ladder.

However, the high proportions of contingent workers in teaching and the construction trades indicate that at least some

contingent workers possess high levels of skill. The wide

variety of occupations in which contingent workers are employed makes it impossible to classify contingent jobs as just

low-skilled jobs.

Sex and race. Rates of contingency within occupations,

split by gender and race, are presented in table 2. For the most

part, women’s higher rates of contingency compared with

men’s can be accounted for by their higher concentration in

See footnotes at end of table.
Monthly Labor Review October 1996 15

White:

Agriculture ................................................. 2.2 3.0 4.6 ....

Mining ....................................................... 1.0 1.0 2.6 ....

Construction .............................................. 3.8 4.8 7.4 ....

Manufacturing ........................................... 1.3 1.5 3.0 ....

Transportation and public utilities .............. 1.0 1.0 2.7 ....

Wholesale trade ........................................ .8 .9 2.1 ....

Retail trade ................................................ 1.4 1.8 2.7 ....

Finance, insurance, and real estate .......... .6 .7 1.9 ....

Services .................................................... 3.3 4.2 7.3 ....

Public administration ................................. 1.0 1.0 3.6 ....

Black:

Agriculture ................................................. 1.1 1.1 1.1 ....

Mining ....................................................... (3

) (3) (3) ....

Construction .............................................. 12.1 14.3 17.4 ....

Manufacturing ........................................... 1.4 2.0 4.9 ....

Transportation and public utilities .............. 2.1 2.0 3.8 ....

Wholesale trade ........................................ .9 3.2 5.4 ....

Retail trade ................................................ 3.0 3.5 5.1 ....

Finance, insurance, and real estate .......... 1.8 1.5 2.5 ....

Services .................................................... 3.4 4.3 7.9 ....

Public administration ................................. 1.8 1.8 2.8 ....

1 Noncontingent workers are those who do not fall into any estimate of “contingent” workers.

2

 A contingency rate is the proportion of all employed who are contingent.

3 Less than 0.05 percent.

NOTE: Distribution may not sum to 100.0 percent due to rounding.

Industries

Although some contingent workers were found in every industry, contingent workers were much more likely to be concentrated in the services industry than were noncontingent

workers. (See table 3.) More than 53 percent of contingent

workers were employed in the services industry, compared

with only 34.5 percent of noncontingent workers. Within the

services industry, sectors that accounted for a large proportion of the contingent work force were business services,

which under estimate 3 employed 10.7 percent of contingent

workers, and educational services, which employed 21.5 percent of contingent workers. However, it is important to recognize that, although those in the services industry in general,

and business services and educational services in particular,

constitute a large proportion of contingent workers, the majority of workers in these services industries were not contingent. In fact, although considerably above average, only 12.8

percent of those employed in business services were contingent under estimate 3, and 12.3 percent of those in educational services were contingent.

The other industry in which contingent workers were disproportionately concentrated was construction. Almost 12

percent of contingent workers under estimates 1 and 2 and

9.8 percent of contingent workers under estimate 3 were in

the construction industry. In comparison, only about 5.5 percent of noncontingent workers were in the construction industry. Again, however, despite the fact that construction

workers were disproportionately represented among contingent workers, only

about 4 percent to 8 percent of construction workers were contingent.

It is interesting to note that, despite

being an industry with historically high

turnover rates, the rates of contingency

in the retail trade industry, ranging from

1.6 percent to 3.0 percent, were below

the overall average rates of contingency,

which ranged from 2.2 percent to 4.9

percent.3 Other industries which had

below-average rates of contingency

were manufacturing (1.3 to 3.1 percent);

finance, insurance, and real estate (0.7

to 2.0 percent); transportation and public utilities (1.2 to 3.0 percent); wholesale trade (0.7 to 2.3 percent); and public administration (1.2 to 3.6 percent).

Despite the fact that the manufacturing

sector as a whole did not have an aboveaverage rate of contingency, there were

certain industries within manufacturing

whose rates were above average. For example, the proportion of workers who

were contingent in furniture and fixtures

 Table 3. ContinuedDistribution by industry of employed contingent and

noncontingent workers, and contingency rates by industry, sex,

and race, February 1995

Contingent workers

Industry, sex, and race

 Contingency rates2Continued

Non-

 contingent

 workers 1

Estimate 1 Estimate 2 Estimate 3

 and transportation equipment (other

than motor vehicle and aircraft) manufacturing were both

above average under contingent estimate 3, at 7.5 percent

and 6.9 percent, respectively. This suggests that although

the majority of employees in manufacturing industries have

relatively stable, long-term employment relationships, a few

manufacturing industries may be structured to use more contingent workers, perhaps due to seasonality or lumpiness in

demand.4 In summary, the industry distributions indicate

that overall, although contingent workers were found in

each of the major industrial sectors, the services industry

accounted for more than half of their total and construction

firms hired a disproportionate share as well.

Sex and race. As was alluded to earlier, part of the explanation of why contingent workers were slightly more likely

to be female and black may not be due to a bias in the employment of women and blacks as contingent workers within

any industry, but because women and blacks were disproportionately employed in industries that use more contingent workers. To address this question, table 3 contains

rates of contingency for men, women, whites, and blacks

within each industry.

These estimates indicate that the slightly larger proportion of contingent workers who were female can be largely

accounted for by the greater concentration of women in industries that used more contingent workers. Specifically,

48.0 percent of all women working in February 1995 were

employed in the services industry, while only 24.8 percent
16 Monthly Labor Review October 1996

Elderly Consumers

 Table 4. Percent distribution of employed contingent and

noncontingent workers by full- and part-time

status, multiple jobholding rate, and hours

of work, February 1995

 Percent distribution

Total, 16 years and older ..... 100.0 100.0 100.0 100.0

Full- or part-time status:2

Full-time workers ............... 52.9 53.6 57.1 81.8

Part-time workers .............. 47.1 46.4 42.9 18.2

At work part time for:

Economic reasons ....... 77.5 77.7 80.3 85.5

Noneconomic

 reasons ..................... 22.5 22.4 19.7 14.5

 Multiple jobholders

Multiple job holding rate ...... 10.4 9.3 8.8 6.5

Percent distribution 3 ......... 100.0 100.0 100.0 100.0

Primary job full time,

secondary job part time . 41.0 42.0 40.2 59.4

Primary and secondary

 jobs both part time ........ 43.4 42.0 40.5 20.0

Primary and secondary

 jobs both full time .......... 2.8 2.5 2.2 3.3

 Hours vary on primary

 or secondary jobs ....... 11.4 12.3 16.2 16.7

Proportion of full-time

 workers who combined

 part-time jobs ................ 3.2 2.7 2.7 1.0

 Usual hours of work

 (on all jobs)

1 to 4 hours ......................... 1.5 2.5 1.8 .4

5 to 14 hours ....................... 11.9 11.1 10.0 2.5

15 to 29 hours ..................... 19.7 18.4 17.6 8.9

30 to 34 hours ..................... 6.2 6.2 5.5 4.1

35 to 39 hours ..................... 5.9 5.8 5.8 6.2

40 hours .............................. 30.8 30.1 31.2 44.8

41 to 48 hours ..................... 3.6 4.0 4.5 8.2

49 to 59 hours ..................... 4.7 4.8 5.6 10.2

60 hours or more ................. 3.3 3.9 4.8 7.0

Usual hours on primary

job vary ............................ 12.0 12.0 12.1 7.6

Usual hours on primary

 job not reported .............. .5 1.2 1.0 .1

1

 Noncontingent workers are those who do not fall into any estimate of

“contingent” workers. 2 Part-time is defined as 1 to 34 hours per week; full time is 35 hours or

more. The classification of full- and part-time workers is based on the number of hours usually worked. The sum of the at-work part time categories

would not equal the estimate for part-time workers as the latter includes

those who had a job but were not at work in the reference week. Persons

who are at work part time for an economic or noneconomic reason are limited to those who usually work part time. 3 A small number of individuals who work part time on their primary jobs

and full time on their secondary jobs are not shown separately.

NOTE: Detail may not sum to total due to rounding.

 Table 4.

of all men were so employed. Men’s and women’s rates of

contingency in the services industry were virtually identical, at 7.5 percent and 7.4 percent, respectively, under estimate 3. Further, women were more than 2-1/2 times as likely

as men to be employed in educational services (12.9 percent

versus 4.9 percent) and that industry employed more than

one-fifth of all contingent workers. Both of these factors

undoubtedly contributed to women’s greater overall contingency rate, even though within educational services, men

actually had slightly higher rates of contingency.

The only major industry groups in which women had a

higher rate of contingency than men were retail trade and

finance, insurance, and real estate, both of which had relatively low overall rates of contingency and, with respect to

the distribution of men’s and women’s employment, employed proportionately fewer women. Overall, these estimates indicate that a slightly larger proportion of women

were contingent not because of differences in employment

within specific industries, but rather because women were

employed in industries which used more contingent workers.

The picture for blacks is dramatically different. Blacks

were slightly more likely to be employed in the services

sector than were whites. Given that blacks and whites had

virtually identical rates of contingency within the services

industry, this could account for some of the differences in the

racial composition of contingent and noncontingent workers.

But, perhaps more importantly, blacks had higher rates of

contingency than whites within the other industries that

employed close to the majority of contingent workers. For

example, in the construction industry, 12.1 percent to 17.4

percent of blacks were contingent, compared with only 3.8

percent to 7.4 percent of whites. Similarly, in retail trade,

blacks’ rates of contingency ranged from 3.0 percent to 5.1

percent, about double the rates for whites. The proportion of

blacks employed in each of these industries was slightly

smaller than the proportion of whites; however, the

differences in the rates of contingency more than compensated. Even in the one major industry—transportation

and public utilities—where blacks were disproportionately

employed, their rates of contingency were higher. Specifically, in the transportation and public utilities industry,

blacks’ rates of contingency ranged from 2.1 percent to 3.8

percent, with the proportion of all blacks employed in this

industry equaling 9.7 percent. By comparison, whites’

contingency rates in this industry ranged from 1.0 percent to

2.7 percent and the proportion of all whites employed in this

industry equaled 6.8 percent. Overall, these industry

estimates suggest that blacks’ higher rates of contingency

were not simply a function of their employment distribution

among various industries. Rather, blacks’ higher rates of

contingency also were a function of labor market factors

within industries.

Hours of work

Another area of concern with respect to contingent workers

is whether they are working as many hours as they wish or

whether they are forced to accept jobs that are both insecure

and offer them fewer hours of work than they need or desire.

Profile of Contingent Workers

 Characteristics

Noncontingent

workers1 Estimate 1 Estimate 3 Estimate 2

Contingent workers
Monthly Labor Review October 1996 17

The estimates in table 4 indicate that contingent workers

were more likely to work part time than were noncontingent

workers (where working part time was defined as usually

working fewer than 35 hours a week). Specifically, the proportion of contingent workers who worked part time ranged

from 47.1 percent under the narrowest estimate to 42.9 percent under the broadest estimate. In comparison, only about

18.2 percent of noncontingent workers worked part time. It

is important to note, however, that although contingent workers were disproportionately part time in comparison with

noncon-tingent workers, only 11 percent of all part-time

workers were contingent even under the broadest definition.

Some of the higher rate of part-time work among those

who were contingent is due to their greater concentration in

industries, such as services, that utilize more part-time workers. However, the higher rate of part-time work among the

contingent is mostly accounted for by their higher rate of

part-time work within each industry. The proportion of contingent workers who worked part time was larger than that

for noncontingent workers in every major industry group,

ranging from 1.3 times larger in the agriculture industry under contingent estimate 3, to 4.6 times larger in manufacturing, and 5.6 times larger in public administration. Even

within the services industry, the proportion of contingent

workers who were working part time was about twice as large

as the proportion of noncontingent workers who worked part

time.

A similar pattern exists with respect to the occupational

distribution of contingent and noncontingent workers who

worked part time. Contingent workers were overrepresented

in administrative support and sales occupations, which had

proportionately more part-time workers than other occupations. However, within every occupational group, contingent workers were more likely to work part time than were

their noncontingent counterparts.

Data in table 4 on the distribution of usual hours of work

provide additional evidence of differences in work schedules. For example, the proportion of contingent workers who

usually worked from 1 to 14 hours a week ranged from 11.8

percent under estimate 3 to 13.4 percent under estimate 1,

while only 2.9 percent of noncontingent workers usually

worked less than 15 hours per week. Conversely, contingent

workers were much less likely to usually work more than 40

hours a week. More than 18 percent of the noncontingent

usually worked 41 to 59 hours a week, and 7 percent worked

60 hours or more a week, about double the proportions of

contingent workers.

Despite the larger proportion of contingent workers who

were part time and usually worked a small number of hours a

week, it is important to note that under all estimates, about

80 percent of contingent workers who worked part time did

so for personal, noneconomic reasons.5 Further, contingent

workers working the smallest number of hours per week were

much more likely to be voluntarily working part time than

were contingent workers who usually worked 15 to 34 hours

per week. Specifically, under contingent estimate 3, only

10.6 percent of those who usually worked from 1 to 14 hours

a week were part time for economic reasons, compared with

23.2 percent of contingent workers who usually worked from

15 to 34 hours per week. However, the proportion of parttime contingent workers who were at work part time for economic reasons (19.7 to 22.5 percent) was larger than the comparable proportion of noncontingent workers (14.5 percent).6

But it should be pointed out that only 15.2 percent of those

who were part time for economic reasons were contingent.

Consequently, although workers who were part time for economic reasons wanted a job in which they could work more

hours, the vast majority could keep the job they had for as

long as they wished.

Multiple jobholding

One way to obtain additional hours of work is to work at

more than one job. The estimates in table 4 indicate that

contingent workers were more likely than noncontingent

workers to have two or more jobs. The proportion of

contingent workers who were multiple jobholders

ranged from about 8.8 percent to 10.6 percent, with the

narrowest estimate having the highest multiple

jobholding rate. Only 6.5 percent of noncontingent

workers held more than one job. The estimates in table

4 also indicate that, unlike noncontingent workers, the largest proportion of contingent workers who were multiple jobholders had two or more parttime jobs. In contrast, noncontingent workers who were

multiple jobholders were more likely to have one fulltime and one part- time job. Besides being more likely to

have two or more part-time jobs, contingent workers

were also more likely to combine part-time jobs to obtain a full-time status than were noncontingent workers.

Although relatively small as a proportion of full-time

workers, be they contingent or noncon-tingent, approximately 3 percent of full-time contingent workers under

any definition obtained this status by combining parttime jobs, compared with about 1.0 percent of

noncontingent workers who usually worked more than

34 hours a week.

Of course, part of the reason contingent workers were

more likely to be multiple jobholders could be related to

the occupations and industries in which contingent

workers were concentrated. For example, contingent

workers were disproportionately represented in professional specialty occupations, which had above-average

multiple jobholding rates even among noncontingent

workers. Nearly one in ten noncontingent workers in a

professional specialty occupation was a multiple jobholder, compared with 6.5 percent of all noncontingent

workers. However, within every occupation, the proportion

of contingent workers who were multiple jobholders was

higher than the proportion of noncon-tingent workers who
18 Monthly Labor Review October 1996

Elderly Consumers

Contingent workers

Estimate 1 Estimate 2 Estimate 3

Percent married:

16 years and older ...... 36.0 39.6 44.7 61.9

25 years and older .. 55.2 57.9 60.3 68.9

This is at least partially attributable to the younger age of

contingent workers. However, even for individuals who were

over the age of 24, contingent workers were less likely to be

married than were their noncontingent counterparts, although

the difference was reduced.

Even among contingent workers who were married, the

 Table 5. Union affiliation of wage and salary contingent and noncontingent workers by industy, February 1955

[Percent distribution]

Total, 16 years and older ..................... 8.4 8.9 8.0 8.6 9.8 11.4 15.7 17.5

Agriculture ....................................... (2

) (2) (2) (2) (2) 2.4 1.2 2.8

Mining .............................................. 39.6 39.6 39.6 39.6 14.2 14.2 8.3 9.1

Construction .................................... 37.4 37.7 36.4 36.8 39.4 40.2 17.0 19.1

Manufacturing .................................. 5.0 5.0 4.5 4.5 8.6 10.5 19.2 20.4

Transportation and public utilities .... 12.3 13.6 15.4 16.7 22.1 26.8 35.4 37.5

Wholesale trade .............................. 18.2 18.2 12.7 12.7 15.3 15.3 4.7 5.6

Retail trade ...................................... 1.0 1.3 .8 1.2 1.1 1.4 5.7 6.4

Finance, insurance, and real estate 7.5 7.5 8.3 8.3 7.4 7.4 3.5 3.9

Services ........................................... 4.3 4.9 3.8 4.6 5.8 7.4 15.4 17.8

Public administration ....................... 10.0 10.0 10.0 10.0 8.6 14.3 37.0 42.3

tabulation presented below indicates that the vast majority had

spouses in noncontingent jobs:

Contingent workers,

estimate 3

 Total With children

 under 18

Married men (in percent):

Wife employed, noncontingent ............. 59.6 58.3

Wife employed, contingent ................... 7.0 7.7

Wife unemployed ................................. 3.0 4.0

Wife not in labor force .......................... 30.4 30.1

Married women (in percent):

Husband employed, noncontingent ...... 79.4 84.8

Husband employed, contingent ............ 6.7 6.6

Husband unemployed ........................... 2.7 3.0

Husband not in labor force .................. 9.8 4.5

When examining the possible effect of contingent work on

children, it is necessary to examine the proportion of all women

with children under age 18 who were contingent, along with the

employment status of the husbands of married women in contingent jobs who had children under age 18. Overall, only about

3 percent of all women with children under age 18 were contingent even under the broadest estimate. Further, more than fourfifths of married women with children under age 18 who were

in contingent jobs had husbands who were in noncontingent jobs.

Taken together, the data shown above suggest that relatively few

families are at risk of losing their sole means of support through

the loss of a contingent job.

Demand factors

The previous sections have dealt with various attributes of contingent workers. There also is interest in factors that might be

contributing to the demand for contingent workers. Some have

Members

 of unions

Represented

by unions

Members

 of unions

Represented

 by unions

Members

 of unions

Represented

by unions

Members

 of unions

Represented

by unions

 Noncontingent

 workers1

Estimate 1 Estimate 3

Contingent workers

Estimate 2 Industry

1

 Noncontingent workers are those who do not fall into any estimate of

“contingent” workers. 2

 Less than 0.05 percent.

NOTE: Data refer to members of a labor union or an employee association similar to a union as well as workers who report no union affiliation but

whose jobs are covered by a union or employee association contract.

professional specialty occupations, contingent workers under estimate 3 had a higher multiple jobholding rate than did

noncontingent workers (12.4 percent versus 9.7 percent).

A similar pattern exists within industries. Contingent workers were concentrated in the services industry, which had a higher

multiple jobholding rate, but within every industry group,

the multiple jobholding rate for contingent workers was

greater than the multiple jobholding rate for noncontingent

workers. Although it is impossible to say for certain, some

proportion of contingent workers may be holding more than

one job to hedge against the loss of their contingent job.7

Contingent work and families

Beyond the issues surrounding contingent work and its effects on individuals, there also is concern that contingent

work and the lack of job security it embodies can threaten

the economic security of an entire family.8 The first thing to

note when examining contingency in the context of families

is that, as a group, contingent workers were much less likely

to be married than were noncontingent workers:

Profile of Contingent Workers

 Non-

 contingent

 workers
Monthly Labor Review October 1996 19

argued that, among many possible reasons, the use of contingent workers has arisen because of the decline in unionism,

which permits firms to take advantage of the cost savings

embodied in more flexible staffing arrangements.9 Others

have argued that firms might use contingent workers to buffer

against fluctuations in demand caused by either seasonality or

changes in the business cycle. According to this argument, for

firms facing an increase in demand, the alternative to using contingent workers may not be using noncontingent workers, but

using methods of meeting demand with a given level of workers, such as increasing overtime or drawing down inventory.

Consequently, without contingent employment, the choice for

some individuals may not be a noncontingent job, but rather

unemployment. As a preliminary examination of issues related to the use of contingent workers, this section explores

the unionization rates of contingent and noncontingent workers and compares rates of contingency within specific industries in February 1995 with these industries’ variation in employment.

Unionization. Without historical data, one cannot establish

a correlation between contingency and the decline in unionization. However, if such a correlation were to exist, one

might also expect industries with low unionization rates to

have relatively few contingent workers. Following are unionization rates for wage and salary workers and contingency

rates by industry in February 1995:

 Unionization rate

 Contingency

 Member Represented rate

of unions by unions (estimate 3)

Total employed, 16 years

and older (in percent) ...... 15.3 17.0 4.9

Agriculture ........................ 2.8 4.9 5.0

Mining ............................... 8.6 9.3 2.7

Construction ...................... 18.5 20.2 8.4

Manufacturing ................... 19.1 20.1 3.1

Transportation and

public utilities.................. 34.7 36.8 3.0

Wholesale trade ................. 5.1 5.9 2.3

Retail trade ........................ 5.7 6.3 3.0

Finance, insurance, and

real estate ......................... 3.2 3.6 2.0

Services ............................. 14.5 16.7 7.5

Public administration ........ 36.9 42.0 3.6

Industrywide unionization rates indicate that the two industries with the highest unionization rates—public administration and transportation and public utilities—also had

below-average rates of contingency.

At the same time, however, the finance, insurance, and real

estate industry had both the lowest rate of contingency and

one of the lowest rates of unionization. In addition, the two

industries with the highest rates of contingency—construction and services—had about average rates of unionization.

The lack of an obvious relationship between industrywide

unionization rates and contingency suggests that, at least in

the aggregate, the use of contingent workers may be more

related to the characteristics of specific industries rather than

the overall trend in unionization.

In addition to comparing rates of unionization and the rates

of contingency within industries, it also is interesting to compare the proportion of contingent and noncontingent workers

who are unionized. Given that a major goal of unions is to

obtain job security for their members, it is not surprising that

noncontingent workers were much more likely to be members of a union than were contingent workers. (See table 5.)

Contingent workers also were less likely to work at a job

covered by a union contract, a broader measure of unionization which includes individuals in jobs covered by a union or

employee association contract regardless of whether the individuals actually were union members. From 8.6 percent to

11.4 percent of wage and salary contingent workers, depending on the definition chosen, were covered by a union or employee association contract, compared with 17.5 percent of

noncontingent workers.

Despite the overall lower rates of union membership and

union coverage of contingent workers, there was a great deal

of heterogeneity among the various industries. In fact, there

were several industries in which the proportion of contingent

workers who were members of a union or covered by a union

contract was actually higher than the proportion of noncontingent workers. For instance, in the construction industry, 39.4

percent of contingent workers under estimate 3 were members

of a union, compared with only 17.0 percent of noncontingent

workers. In contrast, in several industries, the proportion of

contingent workers who were union members or covered by a

union contract was substantially lower than for noncontingent

workers. In manufacturing and services, union membership

rates for contingent workers under estimate 1 were only about a

third as high as they were for noncontingent workers. The large

degree of heterogeneity among the various industries in the

unionization rates of contingent and noncontingent workers suggests that the effect of unionization on contingent employment

and workers’ job security is industry specific. The rate of

unionization of contingent workers and unionization’s effect

on the level of contingent employment within an industry

such as construction may have more to do with the specific

industry and historical employment relationships than with

the presence or absence of a union. Consequently, making a

blanket statement about the relationship between unionization and contingent workers would be inappropriate.

Variation over time. Several authors have suggested that

employers use contingent and similar workers to address variability in demand for their products or to deal with increased

foreign competition.10 A measure that indicates that industry-wide variation in demand is at least partially met through

changes in employment, as opposed to some other means
20 Monthly Labor Review October 1996

Elderly Consumers Profile of Contingent Workers

such as stockpiling or overtime, is the relative variation of

employment within industries. One would expect that industries with higher relative variation in employment over

time would also employ more contingent workers. The tabulation below contain a measure of the relative variation in

employment along with rates of contingency by industry. The

measure of relative variation in employment is the standard deviation of employment divided by the mean level of employment, where employment is measured quarterly and the time

period covered is the second quarter of 1994 to the second

quarter of 1995:11

Relative variation Contingency

 in employment rate

(II 1994 to II 1995) (estimate 3)

Agriculture ........................ 0.098 5.0

Mining .............................. .022 2.7

Construction ..................... .042 8.4

Manufacturing .................. .005 3.1

Transportation

 and public utilities ......... .010 3.0

Wholesale trade ................ .013 2.3

Retail trade ....................... .015 3.0

Finance, insurance,

and real estate ............... .011 2.0

Services ............................ .015 7.5

Comparisons of the relative variation in employment and

the rates of contingency do indicate that two of the industries

with the highest relative variation in employment also had

two of the higher rates of contingency—construction and agriculture. Further, the three industries with the lowest relative

variation in employment—manufacturing, wholesale trade,

and finance, insurance, and real estate—had below-average

rates of contingency. However, the services industry, which

had a high rate of contingency, only had a moderate rate of

variation in employment. Overall, the comparisons within

industries of the relative variation in employment and rates

of contingency tentatively suggest that, by and large, industries with more relative variation in employment over time

also had higher rates of contingency. Whether this correspondence is due to seasonality or uncertainty in demand and

whether it would be true at more dissaggregate industry levels are areas for additional research. In addition, to further

explore the relation between variation in demand and the use

of contingent workers, it would be desirable to have both

firm level data and data on contingent workers over a longer

time span under different economic circumstances.

Summary

This article presented a profile of contingent workers as measured by the February 1995 supplement to the CPS, and briefly

touched on some of the factors that might be influencing the

demand for contingent workers. In summary, contingent

workers were more likely to be female, black, under the age

of 25, and enrolled in school than were noncontingent workers. Contingent workers were also more likely to be in the

services and construction industries. This higher concentration of contingent workers in the services industry at least

partially accounted for the disproportionate number of workers who were female. Blacks, however, had a higher rate of

contingency within every major industry group.

Contrary to their stereotypical image as low-skilled workers, contingent workers were found in a wide variety of occupations. More than 10 percent of contingent workers under the broadest estimate were teachers or professors. Contingent workers were more likely to be multiple jobholders

and work part time but it is important to point out that the

majority of contingent workers who worked part time did so

voluntarily. Further, while contingent workers were more

likely to be employed part time than were noncontingent

workers, only 11 percent of part-time workers were contingent even under the broadest estimate. Finally, the relationship between rates of contingency and unionization rates varied considerably by industry, with some industries, such as

construction, having higher rates of unionization among contingent workers than noncontingent workers. The relationship between the variation in the level of industry employment and the rate of contingency in these industries seem to

indicate that industries with more variable employment also

had higher rates of contingency.

Overall, examination of the characteristics of contingent

workers reveals that they are quite a diverse group of individuals. Some types of contingent workers, such as construction

workers and substitute teachers, have been a part of the American economy almost since the country’s inception. Other types

of contingent workers, such as computer operators who obtain

their assignments through temporary help agencies, are a relatively recent phenomenon. As the U.S. economy continues to

evolve into the next century, the analysis of contingent workers

will be of continued interest and the profile of contingent

workers may change. At the moment, however, the diversity

in the characteristics of contingent workers belies attempts

to classify all contingent jobs as bad jobs. 

Footnotes

1

 See, for example, Heidi Hartmann and June Lapidus, “Temporary Work,”

in Investing in People (Washington, DC, Commission on Workforce Quality

and Labor Market Efficiency, U.S. Department of Labor, September 1989),

pp. 1559–1608; and Polly Callaghan and Heidi Hartmann, Contingent Work:

A Chart Book on Part Time and Temporary Employment (Washington, DC,

Economic Policy Institute, 1991). 2

 Individuals aged 16 to 24 are the only ones actually asked the school

enrollment questions in the CPS. For the estimates presented in table 2, indi-
Monthly Labor Review October 1996 21

would like to include both individuals who are contingent and those who

usually work part time for economic reasons into a single category. Using

contingent estimate 3, if these two groups are combined and double counting

is eliminated, 7.3 percent of the employed in February would have been included. 7

 It also could be that contingent workers are more likely to be multiple

jobholders because of the professions they are in or the need and desire for

additional income regardless of their contingent status. The earnings of

contingent workers are analyzed in Steven Hipple and Jay Stewart, “Earnings and benefits of contingent and noncontingent workers,” this issue, pp.

22–30.” 8

 Jackie Chu, Sonya Smallets, and Jill Braunstein, The Economic Impact

of Contingent Work on Women and Their Families, Research-in-Brief (Washington, DC, Institute for Women’s Policy Research, September 1995). 9

 For example, Lonnie Golden and Eileen Appelbaum in “What Was

Driving the 1982–88 Boom in Temporary Employment?” (American Journal of Economics and Sociology, October 1992, p. 473) note, “The diminishing bargaining power of labor unions allows employers to exploit the labor

cost savings of temporary hires. . . .” 10 For example, see Katharine G. Abraham, “The Role of Flexible Staffing Arrangements in Employers’ Short-term Adjustment Strategies” (London, George Allen and Unwin, 1988), 11 The relative variation in employment for each industry was calculated

using levels of employment reported in administrative records on employees

covered by unemployment insurance tax laws (ES 202). Information on individuals in public administration is not available from these records.

viduals aged 25 and older were assumed not to be enrolled in school. 3

 High rates of turnover can be inferred from the historically low median

and mean years of tenure of workers in the retail trade industry. (See Report

on the American Workforce, U.S. Department of Labor, 1995). Malcolm

Cohen in “Study on the Feasibility of Using Labor Market Information for

Alien Labor Certification Determination” calculated “replacement demand”

from 1986 to 1987 which directly measured the extent of turnover within

occupations. This study found cashiers and salesworkers (other commodities) had extremely high turnover rates. Given that these occupations are

disproportionately represented in the retail trade industry, these occupational

turnover rates also can be used to infer that the turnover rate within the retail

industry is high. 4

 The other transportation equipment industrial sector includes ship

and boat building and repairing; railroad locomotives and equipment; and

guided missiles, space vehicles, and parts. Another industry which might

have a large amount of seasonality in demand, toys, amusement goods, and

sporting goods, had above-average rates of contingency, but the sample

size was to small to measure the number of contingent workers within this

industry with any precision. 5

 In the CPS, individuals who work part time are asked both if they

would like to work full time, and what their main reason for working part

time is. Reasons for voluntarily working part time include family or personal obligations, health or medical limitations, child care problems, or

being in school or training. 6

 Some critics (for example, the Employment Policy Institute in its Job

Fax “New survey provides snapshot of contingent workforce,” Aug. 17, 1995)