Monthly Labor Review • May 2012 19

Older Workers and Jobs 

Older workers and short-term jobs: 

patterns and determinants

Data from the longitudinal Health and Retirement Study

indicate that, among older Americans with work experience

since age 50, approximately 12 percent of men and 32 percent

of women never held a full-time career job; the retirement

patterns of these non-full-time career older workers are

diverse, just as they are for individuals with career jobs

Kevin E. Cahill,

Michael D. Giandrea,

and

Joseph F. Quinn

Kevin E. Cahill is a research 

economist at the Sloan Center on 

Aging & Work at Boston College, 

Chestnut Hill, MA; Joseph F. Quinn 

is the James P. McIntyre Professor 

of Economics in the Department 

of Economics at Boston College 

and is also affiliated with the 

Sloan Center on Aging & Work; 

Michael D. Giandrea is a research 

economist in the Office of Productivity and Technology, Bureau 

of Labor Statistics, Washington, 

DC. Email: giandrea.michael@bls.

gov. All views expressed in this 

paper are those of the authors 

and do not necessarily reflect the 

views or policies of the Bureau 

of Labor Statistics. The Alfred P. 

Sloan Foundation supported this 

research through a grant to the 

Sloan Center on Aging & Work at 

Boston College.

The retirement patterns of career 

workers have been studied extensively. One of the main findings of 

this literature is that a majority of older 

Americans with career jobs make at least 

one job change prior to leaving the labor 

force; only a minority leave a career job 

and the labor force simultaneously.1 Kevin 

Cahill, Michael Giandrea, and Joseph 

Quinn found that 60 percent of older 

workers who left full-time career employment moved to short-duration or parttime employment (known as bridge jobs) 

before exiting the labor force.2 In another 

paper, these authors found that a substantial minority (approximately 10 percent) 

of individuals with wage-and-salary career jobs move into self-employment later 

in life.3 Likewise, evidence suggests that 

many workers (approximately 15 percent) 

with career jobs reenter the labor force after “retiring,” that these reentry decisions 

are often voluntary, and that they are frequently anticipated prior to the workers’ 

leaving career employment.4 Collectively, 

these findings suggest that many career 

workers change jobs later in life and exit 

the labor force gradually.

An important question is whether the findings also apply to individuals who have never 

held a full-time career job. This question is relevant because a sizable fraction of older American workers—approximately 12 percent of men 

and about one-third of women—did not have 

a career job.5 Thus, policy decisions based upon 

the existing literature may have different and 

unintended consequences for workers with intermittent work histories and a more tenuous 

connection to the labor force. For example, policies that promote work later in life are often proposed as a way to alleviate the financial burden 

of an aging population. As the ratio of workers 

to retirees shifts from about 3 to 1 today to near 

2 to 1 by 2030, policymakers may keep looking 

for ways to encourage continued labor force participation among individuals who have reached 

traditional retirement ages.6

Retirement studies often analyze factors, 

such as wealth, private pensions, and employerprovided health insurance, that are more likely 

to be important to full-time career workers than 

they are to others. For example, Courtney Coile 

and Phillip Levine used data from the Health 

and Retirement Study, the Current Population 

Survey, and the Survey of Consumer Finances to 

examine the effect of wealth on labor force activ-
Older Workers and Jobs

20 Monthly Labor Review • May 2012

ity,7 and several studies from the 1990s addressed the role 

of defined-benefit pensions in the labor force behavior 

of older workers.8 More recent studies have examined 

the impact of defined-contribution plans on retirement 

outcomes, but these, too, are still unlikely to apply to 

many non-full-time career workers.9 Similarly, many 

studies have focused on the impact of health insurance 

on the work-vs.-leisure decisions of older Americans, 

but this coverage is also unlikely to apply to most parttime or short-duration workers.10

Other studies that do address topics related to noncareer workers by and large do not focus on older individuals, or they focus on short-term involuntary job 

losses late in life. For example, examining how intermittent work histories affect the wages of women, Julie 

Hotchkiss and Melinda Pitts found that intermittency 

resulted in a wage penalty even at low levels of labor 

force absence.11 In another study, Jay Stewart used data 

from the Current Population Survey and the National 

Longitudinal Survey of Youth to examine the work 

histories of noncareer men and found that it was generally the same cadre of men who did not work from 

year to year. Stewart, however, did not follow these men 

through retirement.12 Two other papers, one by Julie 

Whittaker and the other by Sewin Chan and Ann Huff 

Stevens, focus on unemployment among older workers 

and the likelihood that they will drop out of the labor 

force permanently after a spell of unemployment.13 Although these two papers examine the role that retirement income sources play in the labor force outcomes 

of older workers, a topic that is relevant to the present 

study, the research presented in them focuses on individuals who experienced a spell of nonemployment later 

in life, as opposed to those with an entire work history 

without full-time career employment.

This article combines two strands of the literature by 

examining the labor force behavior of older individuals 

with a history of short-duration jobs and comparing 

their behavior with that of older career workers. The 

next section provides a brief description of the dataset 

used—the Health and Retirement Study (HRS)—and 

the research methods employed. The third section examines demographic and economic characteristics and 

labor force outcomes, by career job status, and the last 

section summarizes and discusses the main findings.

Data and methods

The HRS is a rich, nationally representative dataset 

with an initial base of more than 12,600 individuals 

born between 1931 and 1941 (hence aged 51–61 in 1992).14

The data are longitudinal, with interviews conducted every 2 

years since 1992. Attrition across waves ranged from 4 percent to 9 percent per year, and after 16 years about 62 percent 

of the original HRS core sample remained.

The analysis that follows focuses on men and women who 

have never held a full-time career job, defined here as a job in 

which an individual works 1,600 or more hours per year for at 

least 10 years. To identify these individuals, information from 

the initial 1992 interview is combined with employment information from subsequent interviews to construct a labor force 

history for each individual. Questions in the first interview ask 

about a respondent’s current job and all previous jobs that lasted 5 or more years. If a respondent was not working at the time 

of the first interview, he or she was asked about the most recent 

job held, if any. The large majority of men and women responding to the HRS had work experience later in life, as shown in 

table 1. More than 90 percent of men and nearly 80 percent of 

women had worked since age 50. Those with work experience 

since age 50 were stratified according to whether they had ever 

held a full-time career job. A sizable minority of individuals 

with work experience after age 50—12 percent of men and 32 

percent of women—had not held a full-time career position.

Results

Demographic and economic characteristics by full-time career 

job status. The demographic and economic characteristics 

Sample size, by gender, survey participation, and work 

status, respondents ages 51–61 in 1992

Survey participation and work status Total Men Women

Participated in first wave:

 n 12,652 5,869 6,873

 Worked since age 50:

 n 10,639 5,353 5,286

 Percentage of all respondents 84 91 78

 No full-time career job in work history:

 n 2,298 633 1,665

 Percentage of respondents who

 have worked since age 50 22 12 32

 Full-time career job in work history:

 n 8,312 4,719 3,593

 Percentage of respondents who 

 have worked since age 50 78 88 68

NOTE: Full-time career job status could not be determined for 1 man 

and 28 women, all of whom were deleted from the sample.

SOURCE: Authors’ calculations based on Health and Retirement Study.

Table 1.
Monthly Labor Review • May 2012 21

examined, stratified by gender and full-time career job 

status, are based on responses from the first interview in 

1992. On average, for HRS respondents in 1992 who had 

worked since age 50, those who had never held a full-time 

career job were older and in poorer health than those who 

did hold a full-time career job, and the former also were 

less likely to have a college degree. (See table 2.)15 Men 

without full-time career job experience were less likely to 

be married than men with such experience, but their female counterparts were slightly more likely to be married. 

One-half of the men who never had a full-time career 

job had an employed spouse, compared with 57 percent 

of those with full-time career job experience. This statistic may indicate that employment and attachment to the 

labor force are complementary among spouses, as some of 

the literature suggests.16 The lower marriage rates among 

Demographic characteristics in 1992, by gender and full-time career job status, respondents with work experience 

since age 50

Characteristic Total

Men Women

All men

No full-time 

career job in

work history

Full-time 

career job in

work history

All women

No full-time 

career job in

work history

Full-time 

career job in

work history

Age:1

Younger than 54 37 29 20 30 45 33 51

54–57 29 29 27 30 29 32 27

58–61 25 25 31 25 25 33 21

62 and older 9 17 22 16 2 2 2

Subjective health status:1

Excellent or very good 54 52 36 54 56 48 59

Good 29 30 33 30 27 27 28

Fair or poor 18 18 31 17 17 25 13

Educational attainment:1

College degree 19 22 18 23 16 12 18

Less than college degree 81 78 82 77 84 88 82

Marital status:1

Married 82 88 81 89 75 77 74

Not married 18 12 19 11 25 23 26

Children:2

Dependent children 15 17 19 16 14 12 15

No dependent children 85 83 81 84 86 88 85

Spouse’s health status:3

Excellent or very good 53 56 48 56 51 50 51

Good 28 27 29 27 29 31 29

Fair or poor 18 17 23 16 20 19 20

Spouse’s employment status:3

Employed spouse 55 56 50 57 55 53 55

No employed spouse 45 44 50 43 45 47 45

n 10,639 5,352 633 4,719 5,258 1,665 3,593

1 Difference by full-time career job status is significant at p < .01 

among both men and women. 2 Difference by full-time career job status is significant at p < .05 

among women. 3 Difference by full-time career job status is significant at p < .01

among men.

NOTE: Detailed entries may not sum to totals because of rounding. Sample 

size n for spouse’s health status is 4,602 for men and 3,814 for women.

SOURCE: Authors’ calculations based on Health and Retirement Study.

Table 2.

[In percent]
Older Workers and Jobs

22 Monthly Labor Review • May 2012

women likely reflect a combination of women marrying 

older men, on average, and higher mortality rates among 

men.

The economic characteristics of the HRS respondents as 

of 1992 are presented in table 3. Men and women without a full-time career job in their work history were less 

likely than those with career jobs to have health insurance 

and also much less likely to have a defined-benefit or a 

defined-contribution pension on the job they reported in 

the first wave. In fact, two-thirds of these men and more 

than three-quarters of the women had no pension, compared with 31 percent of the men and 39 percent of the 

women with career job experience.

Consistent with their lower levels of education, men 

and women who never held a full-time career job were 

almost twice as likely as those with a full-time career job 

to be employed in a blue-collar position that did not require highly skilled labor.17 Moreover, the wage distributions of those with and those without a full-time career 

job in their work history were significantly different for 

both men and women. Men who never had a full-time 

career job were 3 times as likely as full-time career men to 

be making $6 to $10 per hour on their 1992 job and were 

half as likely to be earning between $20 and $50 per hour. 

Women who never held a full-time career job were about 

twice as likely as women who did to earn between $6 and 

$10 per hour and nearly half as likely to earn between $20 

and $50 per hour.

Individuals without full-time career jobs also had lower 

levels of wealth than others. More than one-half of the 

men with no full-time career job in their work history had 

nonpension financial wealth of less than $25,000, compared with about one-third of men with a career job. At 

the other end of the wealth spectrum, less than one-quarter of the men with no full-time career job in their work 

history had nonpension financial wealth of $100,000 or 

more, compared with more than one-third of men with 

full-time career job experience. Among men, increased labor force attachment is associated with increased nonpension wealth, a relationship consistent with more and larger 

paychecks providing increased opportunities for saving. 

Among women, however, differences in nonpension financial wealth by full-time career job status were much less 

pronounced. This finding may reflect the extent to which 

wealth among women is dependent on marital status.

Retirement outcomes. The labor force outcomes examined in this article include work status and work intensity (i.e., part-time versus full-time work) at the time of 

each biennial HRS interview and the number and types 

of job switches since the first interview. Not surprisingly, 

respondents were less likely to be working in later survey 

waves, regardless of career job status. (See chart 1). The 

patterns for men and women were remarkably similar, 

although women were somewhat more likely to be working in most survey years, reflecting in part the facts that 

(1) women with work experience since age 50 were, as a 

whole, younger than their male counterparts and (2) the 

spouses could be younger than the minimum age in the 

age range for respondents. In all survey years for both men 

and women, individuals with a full-time career job in their 

work history were significantly more likely to be working 

than those without.

Although the work status patterns of HRS respondents 

were similar by full-time career job status (i.e., a gradual 

monotonic decline in employment with age), those with 

and those without full-time career jobs in their work histories had different experiences with respect to part-time 

employment. (See chart 2.) As the respondents aged, parttime employment became increasingly common among 

individuals with a full-time career job in their work history, with substantial numbers of them moving into parttime work. When the career job respondents were 51 

to 61 years old in 1992, only 10 percent of the men and 

15 percent of the women were working part time. These 

percentages increased steadily to 50 or more percent (of 

a reduced number who were working at all) by 2008. In 

contrast, at the time of the first interview, the percentage 

of individuals who had never had a full-time career job 

and who were working part time was much higher (66 

percent among men and 84 percent among women), and 

the percentage remained high and relatively stable (near 

60 percent or above for men and 75 percent or above for 

women) through 2008. Those without full-time job experience are primarily part-time workers when they reach 

age 50 and beyond.

Job switching is also an important part of labor force 

transitions later in life. Table 4 shows the number of job 

switches since 1992 among those respondents who were 

working at the time of the first interview. Overall, men and 

women without full-time career jobs were significantly less 

likely to still be on their 1992 job (or to be last observed 

on their 1992 job) in 2008 and were significantly more 

likely to have left the labor force directly from their 1992 

job, compared with those who had had a full-time career 

job in their work history. These two differences in behavior 

largely offset each other, so the numbers of job switches 

since 1992 were similar by career job status for both men 

and women: about one-third had one or two job switches, 

and relatively few respondents—6 or 7 percent—had more 
Monthly Labor Review • May 2012 23

Economic characteristics in 1992, by gender and full-time career job status, respondents with work experience 

since age 50

Characteristic Total

Men Women

All men

No full-time 

career job 

in work 

history

Full-time 

career job 

in work 

history

All women

No full-time 

career job 

in work 

history

Full-time 

career job 

in work 

history

Health insurance status:1

Not covered on first-wave job 14 13 28 11 14 21 11

Covered and would maintain coverage 78 79 67 80 78 76 79

Covered and would lose coverage 8 9 5 9 8 3 10

Pension status:1

Defined benefit only 37 44 20 47 30 14 38

Defined contribution only 16 16 11 17 17 9 21

Defined benefit and defined contribution 4 5 3 5 2 1 3

No pension 43 35 67 31 51 77 39

Worker status:2

Self-employed 14 18 21 17 11 12 10

Wage and salary 86 82 79 83 89 88 90

Occupation status:1

White collar, highly skilled 31 32 28 33 29 20 31

White collar, other 26 16 16 16 37 32 38

Blue collar, highly skilled 24 37 32 38 11 9 11

Blue collar, other 19 15 25 14 24 39 20

Wage rate:1

$6.00–$9.99/hour 17 12 30 10 22 37 18

$10.00–$19.99/hour 29 21 26 21 36 36 36

$20.00–$49.99/hour 38 44 23 46 33 20 37

$50.00/hour or more 16 23 21 23 8 7 9

Wealth:3

$0 or less 9 8 19 6 11 13 10

$1–$24,999 32 30 37 30 33 33 33

$25,000–$49,999 13 14 11 14 13 11 14

$50,000–$99,999 15 15 11 16 14 13 15

$100,00–$499,999 24 25 16 26 23 22 23

$500,00 or more 7 8 7 8 6 8 5

Homeownership status:3

Do not own home 18 16 30 15 19 22 18

Own home 82 84 70 85 81 78 82

n 10,639 5,352 633 4,719 5,258 1,665 3,593

1 Percentages based on respondents who were working in first wave; 

difference by full-time career job status is significant at p < .01 among both 

men and women. 2 Percentages based on respondents who were working in first wave; 

difference by full-time career job status is significant at p < .05 among both 

men and women.

3 Difference by full-time career job status is significant at p < .01 among 

both men and women.

NOTE: Detailed entries may not sum to totals because of rounding. Sample 

size for health insurance status is 4,959 for men and 4,767 for women. Sample 

size for occupation status is 4,159 for men and 4,058 for women. 

SOURCE: Authors’ calculations based on Health and Retirement Study.

Table 3.

[In percent]
Older Workers and Jobs

24 Monthly Labor Review • May 2012

 Chart 1. 

100

90

80

70

60

50

40

30

20

10

0

Percentage working, by full-time career job status, 1992–2008, respondents who have worked

since age 50

SOURCE: Authors’ calculations based on Health and Retirement Study.

Percent

 1992 1994 1996 1998 2000 2002 2004 2006 2008

(53–63) (55–65) (57–67) (59–69) (61–71) (63–73) (65–75) (67–77)

Percent

Survey year

(Age range of respondents)

No FTC job in work history

Had FTC job in work history

100

90

80

70

60

50

40

30

20

10

0

Men

No full-time career job in work history

Had full-time career job in work history

100

90

80

70

60

50

40

30

20

10

0

Percent

 1992 1994 1996 1998 2000 2002 2004 2006 2008

(53–63) (55–65) (57–67) (59–69) (61–71) (63–73) (65–75) (67–77)

Survey year

(Age range of respondents)

Percent

No FTC job in work history

Had FTC job in work history

100

90

80

70

60

50

40

30

20

10

0

Women

No full-time career job in work history

Had full-time career job in work history

(51–61)

(51–61)
Monthly Labor Review • May 2012 25

No FTC job in work history

Had FTC job in work history

No full-time career job in work history

Had full-time career job in work history

No FTC job in work history

Had FTC job in work history

No full-time career job in work history

Had full-time career job in work history

 Chart 2. Percentage working part time, by full-time career job status, 1992–2008, respondents who are 

working in each wave

100

90

80

70

60

50

40

30

20

10

0

Percent

SOURCE: Authors’ calculations based on Health and Retirement Study.

 1992 1994 1996 1998 2000 2002 2004 2006 2008

(53–63) (55–65) (57–67) (59–69) (61–71) (63–73) (65–75) (67–77)

Survey year

(Age range of respondents)

Percent

100

90

80

70

60

50

40

30

20

10

0

Survey year

(Age range of respondents)

100

90

80

70

60

50

40

30

20

10

0

Percent

 1992 1994 1996 1998 2000 2002 2004 2006 2008

(53–63) (55–65) (57–67) (59–69) (61–71) (63–73) (65–75) (67–77)

Percent

100

90

80

70

60

50

40

30

20

10

0

Women

Men

(51–61)

(51–61)
Older Workers and Jobs

26 Monthly Labor Review • May 2012

than two job changes, since the first interview.

Table 5 details the types of job changes among those 

who were working in 1992. Slightly more than one-third 

of men and women who had work experience since age 

50 and who were working full time in 1992 moved from 

full-time to part-time work, with non-full-time career 

job respondents being somewhat more likely than career 

respondents to do so. Switches from self-employment 

to wage-and-salary work were more than twice as likely 

as switches from wage-and-salary employment to selfemployment.18 Specifically, 26 percent of men and 31 

percent of women who were self-employed in 1992 subsequently reported a switch to wage-and-salary work, 

whereas 13 percent of men and 10 percent of women 

who were wage-and-salary workers in 1992 subsequently 

reported a switch to self-employment. Switches from 

wage-and-salary work to self-employment were similar 

by full-time career status; however, switches from selfemployment to wage-and-salary work were less common 

among those without a full-time career job in their work 

history. Switches from white-collar to blue-collar positions and vice versa were not significantly different by 

career job status.

Most workers experienced changes in hourly wage 

rates when a job switch was made. The distributions were 

similar among men and women. About two-thirds of job 

switches involved a wage change of more than 10 percent, with declines (38 percent) outweighing increases 

(29 percent). A small percentage of job changers (13 percent) suffered wage reductions of 51 percent or more, and 

another quarter had wage decreases of 11 to 50 percent. 

About 20 percent enjoyed wage gains in the range from 

11 percent to 50 percent, with another 10 percent doing 

even better than that.

When wage changes are disaggregated by career job 

status, the two groups of women are similar. Among men, 

the percentages suffering wage declines were nearly identical (41 percent and 42 percent), but men with no career 

job history were about 10 percentage points less likely 

than men with a full-time career job in their work history 

to have a wage change of less than 10 percent and were 10 

percentage points more likely to enjoy a wage increase of 

more than 10 percent. The difference may be because the 

noncareer men were starting from a lower wage base, from 

which a raise of 10 percent or more was easier to attain.

Multivariate analysis. Multivariate analysis is used to 

determine whether the existence of a full-time career job 

in an individual’s work history affects the person’s likelihood of working as he or she approaches traditional retirement ages. In general, one would expect those who never 

held a full-time career job to be less attached to the labor 

force and therefore less likely to be working at any given 

time. This subsection presents two multivariate models. 

The first model explores the timing of the retirement decision, defined here as leaving the labor force, with career 

status as a regressor. The model was estimated for men 

and women separately, with logistic regression used on the 

sample that includes just those with work experience since 

age 50. Table 6 presents the marginal effects from the reNumber of observed job switches since 1992, by gender and full-time career job status, respondents working in 1992 

First-wave job status and 

number of job switches1 Total

Men Women

All men

No full-time 

career job 

in work 

history

Full-time 

career job 

in work 

history

All women

No full-time 

career job 

in work 

history

Full-time 

career job 

in work 

history

Still on, or last observed on, first-wave job 17 17 8 18 16 11 18

Exited directly from first-wave job 43 43 53 42 43 50 42

Number of job switches:

1 23 24 26 24 23 23 23

2 10 10 8 10 10 10 10

3 4 4 3 4 4 3 4

4 or more 3 2 3 2 3 3 3

n 8,206 4,173 371 3,802 4,033 921 3,112

1 Difference by full-time career job status is significant at p < .01 

among both men and women.

NOTE: Detailed entries may not sum to totals because of rounding. 

SOURCE: Authors’ calculations based on Health and Retirement Study.

Table 4.

[In percent]
Monthly Labor Review • May 2012 27

gressions, evaluated at the sample means.19

The results reveal that both men and women were more 

likely to be working the younger and healthier they were. At 

age 62, when most respondents first became eligible for Social Security retirement benefits, there was a large decrease 

in their likelihood of working. Respondents also were more 

likely to be working, all else being equal, if they were selfemployed, had a spouse who was working (suggesting joint 

retirement decisions), had a spouse in poor health (women 

only), or were employed in a white-collar occupation or a 

high-skill blue-collar occupation. Respondents were less 

likely to be working if they were in fair or poor health or if 

their spouse was in excellent or very good health.

Older workers responded to economic incentives as 

well. Men and women with no health insurance (and 

therefore no benefits to lose) or with health insurance that 

was portable (i.e., that would not be lost if they left their 

job) were significantly less likely to remain working than 

were those with health insurance that was not portable. 

Men and women with defined-benefit pension plans were 

significantly less likely to be working than those without pensions, a finding that is consistent with the earlyretirement incentives (or, equivalently, work disincentives) 

typically found in such plans. Men and women with a 

full-time career job in their work history were significantly 

more likely (16 percentage points for women, 21 percentage points for men) to be working, all else being equal, 

compared with their counterparts without career job experience. This finding reinforces the differences by full-time 

career status noted earlier with respect to the percentage of 

Number of observed job switches since 1992, by gender and full-time career job status, respondents working in 1992

Work status Total

Men Women

All men

No full-time 

career job 

in work 

history

Full-time 

career job 

in work 

history

All women

No full-time 

career job 

in work 

history

Full-time 

career job

 in work 

history

Full time or part time:

Any switch from full time to part time 36 35 41 35 36 39 36

Any switch from part time to full time1 19 22 22 6 18 18 13

Wage and salary or self-employed:

Any switch from wage and salary to selfemployed 12 13 13 14 10 10 9

Any switch from self-employed to wage

and salary 28 26 21 27 31 28 33

White collar or blue collar:

Any switch from white collar to blue collar 12 15 11 15 8 7 8

Any switch from blue collar to white collar 11 10 7 10 12 11 12

Hourly wage rates:2

Reduction in wage of 51 percent or more 13 16 17 16 10 12 9

Reduction in wage of 11 percent to 

50 percent 25 25 25 25 25 23 25

Reduction in wage of up to 10 percent

or increase in wage of up to 10 percent 34 31 22 32 36 35 36

Increase in wage of 11 percent to 50

percent 19 17 19 17 20 19 21

Increase in wage of 51 percent to 100

percent 4 4 5 4 4 4 4

Increase in wage of 101 percent or more 6 7 12 6 5 6 5

1 Difference by full-time career job status at p < .01 among both men 

and women. 2 Difference by full-time career job status is significant at p < .05

among men. 

NOTE: Detailed entries may not sum to totals because of rounding. 

SOURCE: Authors’ calculations based on Health and Retirement Study.

Table 5.

[In percent]
Older Workers and Jobs

28 Monthly Labor Review • May 2012

Marginal effects from logistic regression, dependent variable = working at time t, respondents with work experience 

since age 50

Category 

Men Women

Marginal effect p-value Marginal effect p-value

Full-time career status:

 No full-time career job in work history – – – –

 Full-time career job in work history 0.2143 0.000 0.1626 0.000

Age:

 57 or younger – – – –

 58–61 –.1352 .000 –.1318 .000

 62–64 –.3488 .000 –.2946 .000

 65–69 –.4474 .000 –.4015 .000

 Older than 70 –.5733 .000 –.5152 .000

Self-assessed health:

 Excellent/very good .0624 .000 .0473 .000

 Good – – – –

 Fair/poor –.2317 .000 –.2172 .000

Spouse's health:

 Excellent/very good –.0476 .000 –.0387 .001

 Good – – – –

 Fair/poor .0147 .287 .0398 .003

Education:

 Less than high school .0127 .401 .0353 .024

 High school – – – –

 College degree .0248 .133 –.0096 .582

Race:

 Black .0108 .552 .0572 .000

 White – – – –

 Other .0225 .573 .0669 .099

Married .0425 .077 –.0425 .067

Children at home .0283 .034 .0315 .003

Spouse employed .1703 .000 .1837 .000

Health insurance status:

 Portable –.4924 .000 –.4867 .000

 Not portable – – – –

 None –.4968 .000 –.4755 .000

Pension status:

 Defined benefit –.2652 .000 –.1101 .000

 Defined contribution .0064 .646 .0026 .853

 Defined benefit and defined contribution .0514 .110 .0416 .213

 None – – – –

Occupational status:

 White collar, high skill .2414 .000 .2570 .000

 White collar, other .2476 .000 .2884 .000

 Blue collar, high skill .2074 .000 .2281 .000

 Blue collar, other – – – –

Self-employed .1695 .000 .1623 .000

Wage .0032 .000 .0061 .000

Wage squared .0000 .002 .0000 .000

Wealth –.0014 .000 –.0017 .000

Wealth squared .0000 .000 .0000 .000

Own home .0195 .213 .0219 .127

See notes at end of table.

Table 6.
Monthly Labor Review • May 2012 29

respondents working in each wave. (See chart 1.) 

The next set of findings examines the determinants of 

job switching among the subset of respondents who were 

working at the time of the first interview. Over the observation period, each respondent with a job in 1992 either 

remained on the 1992 job, switched to another job (e.g., a 

bridge job for those moving from a full-time career job), 

or left the labor market directly from the 1992 job. As 

shown in table 7, men were more likely to remain working 

on the 1992 job if they were younger, were in excellent or 

very good health, had a college degree, or were self-employed, and were less likely to remain working on the firstwave job if they had a defined-benefit pension plan (again 

consistent with the early-retirement incentives typically 

incorporated into such plans). Men also were more likely 

to switch jobs before exiting the labor force if they were 

younger or had health insurance (portable or not), and 

were less likely to switch if they were blue-collar workers, were self-employed, or had a defined-benefit pension. 

Men who had a full-time career job in their work history 

were more likely (by a statistically significant 15 percentage points) to remain on the job they held in 1992 than 

those who never held a full-time career job, as one might 

expect, but were slightly less likely (3.5 percentage points) 

to switch jobs prior to exiting the labor force, although 

the latter effect was not statistically significant. The results were similar, but smaller, for women; still, women 

with defined-benefit pensions and women with definedcontribution pensions were more likely to remain working 

on the first-wave job and less likely to make at least one 

job switch. (See table 7.) 

Continued—Marginal effects from logistic regression, dependent variable = working at time t, respondents with 

work experience since age 50

Category

Men Women

Marginal effect p-value Marginal effect p-value

Year:

 1992 .2408 .000 .2375 .000

 1994 .1403 .000 .1778 .000

 1996 .0937 .000 .1193 .000

 1998 .0834 .000 .1319 .000

 2000 .0476 .021 .0996 .000

 2002 .0324 .090 .0639 .001

 2004 .0383 .019 .0787 .000

 2006 .0124 .212 .0491 .000

 2008 – – – –

NOTE: Dash indicates reference, or base, category. SOURCE: Authors’ calculations based on Health and Retirement Study.

Table 6.

THIS ARTICLE HAS EXAMINED THE RETIREMENT

decisions of workers who have had less attachment to 

the labor force than those workers who are typically 

studied in the retirement literature. The aim was to examine more closely the timing of retirement and the 

number and types of job switches that are made later in 

life by older workers who have not had a full-time career job in their work histories. These workers constitute 

12 percent of the men and 32 percent of the women in 

the sample with work experience after age 50.

In each survey year, individuals who never held a fulltime career job were less likely to be working than those 

who have or had held career jobs—a not unexpected finding. However, individuals without a full-time career job in 

their work history were found to change jobs later in life 

just as frequently as those with career jobs. The types of 

job switches were similar as well, including switches from 

wage-and-salary employment to self-employment and 

switches between white-collar and blue-collar jobs. Both 

groups that switched jobs later in life were more likely 

to experience wage reductions (of more than 10 percent) 

than enjoy wage increases (also of more than 10 percent).

Some notable differences by full-time career status do 

exist. For example, part-time employment became more 

pronounced over time for full-time career individuals, 

whereas it remained fairly constant (and high) among individuals without a full-time career job. Also, the percentage of men without a full-time career job who were working part time was near or above 60 percent in all survey 

years; for women, the percentage was above 70 percent. 

By contrast, among individuals with a full-time career job, 
Older Workers and Jobs

30 Monthly Labor Review • May 2012

Table 7. Marginal effects from logistic regression, dependent variable = still on 1992 job, switched jobs, or direct exit,1

respondents working in 1992

Category 

Men Women

Remained on first-wave job Experienced at least one 

job switch Remained on first-wave job Experienced at least one job switch

Marginal 

effect p-value Marginal effect p-value Marginal effect p-value Marginal effect p-value

Full-time career status:

 No full-time career job

 in work history – – – – – – – –

 Full-time career job in

 work history 0.1476 0.000 –0.0347 0.260 0.0420 0.012 0.0162 0.459

Age in 1992:

 51–52 .1063 .000 .1127 .000 .1302 .003 .2235 .000

 53–54 .0712 .002 .0897 .003 .0964 .015 .1251 .012

 55–56 .0642 .006 .0576 .062 .1061 .009 .0950 .060

 57–58 .0340 .155 .0020 .949 .0398 .286 .1351 .006

 59–60 .0179 .472 .0119 .707 .0094 .807 .0938 .057

 61 – – – – – – – –

Self-assessed health:

 Excellent/very good .0324 .018 .0270 .139 .0347 .012 .0436 .030

 Good – – – – – – – –

 Fair/poor –.0056 .790 –.0572 .037 –.0037 .843 –.1050 .000

Spouse's health:

 Excellent/very good –.0008 .958 .0375 .056 .0035 .789 .0131 .550

 Good – – – – – – – –

 Fair/poor .0107 .601 –.0050 .855 .0140 .414 .0114 .695

College degree .0529 .001 –.0178 .421 –.0015 .921 .0048 .848

Race:

 Black .0422 .021 –.0431 .092 .0027 .848 –.0054 .816

 White – – – – – – – –

 Other .0017 .964 –.0108 .841 .0572 .080 .0174 .770

Married .0222 .326 .0496 .108 .0074 .674 –.0283 .320

Children at home .0073 .623 .0160 .452 .0288 .048 .1041 .000

Spouse employed –.0252 .052 .0028 .877 –.0112 .403 –.0205 .358

Occupational status:

 Blue collar, high skill .0292 .082 –.0782 .001 –.0314 .181 –.0126 .700

 Blue collar, other .0366 .081 –.1231 .000 .0340 .043 –.0412 .126

 White collar, high skill – – – – – – – –

 White collar, other .0182 .323 –.0249 .320 .0256 .062 –.0270 .233

Health insurance status:

 Portable –.0055 .693 .0338 .074 –.0117 .336 .0154 .450

 Not portable –.0366 .093 .0941 .001 –.0326 .115 .0943 .002

 None – – – – – – – –

Self-employed .1333 .000 –.0819 .001 .0843 .000 –.0586 .040

Pension status:

 Defined benefit –.0355 .016 –.0465 .029 .0296 .051 –.1405 .000

 Defined contribution –.0033 .847 .0269 .279 .0455 .010 –.0864 .000

 Defined benefit and

 defined contribution –.0798 .009 .1269 .001 –.0193 .586 .1273 .015

 None – – – – – – – –

Own home –.0149 .396 –.0322 .171 –.0016 .911 –.0412 .069

Wage .0001 .693 –.0009 .161 .0003 .676 –.0004 .506

Wage squared .0000 .424 .0000 .391 .0000 .393 .0000 .385

Wealth .0043 .060 –.0026 .517 –.0025 .322 –.0009 .822

Wealth squared .0000 .331 .0001 .553 .0000 .408 .0000 .793

1 Direct exit from the 1992 job is the reference category with which 

the other two alternatives are compared.

NOTE: Dash indicates reference, or base, category. 

SOURCE: Authors’ calculations based on Health and Retirement Study.
Monthly Labor Review • May 2012 31

the percentage working part time increased steadily from 

1992 to 2008, moving from approximately 10 percent in 

the first wave to around 50 percent when the respondents 

were 65 years or older.20

Respondents with career jobs generally rated their 

health status higher than those without career jobs and 

had jobs with more desirable characteristics, such as pension and health insurance benefits. A question remains, 

therefore, about the extent to which the shift to definedcontribution pension plans, such as 401(k)s, will affect the 

retirement decisions of noncareer workers, if at all. The 

descriptive statistics examined in this study reveal that the 

large majority—two-thirds of non-full-time career male 

respondents and three-quarters of non-full-time career 

female respondents—did not have an employer-provided 

pension on their 1992 job. For these workers, the shift 

away from defined-benefit pensions will be of little consequence. Further, more than one-half of non-full-time 

career men and 46 percent of non-full-time career women 

had less than $25,000 in savings. These two findings combined—the paucity of defined-benefit pensions and the 

low level of savings—indicate that the traditional threelegged stool of retirement income—employer pensions, 

savings, and Social Security—appears to have only one 

strong leg for most non-full-time career workers.

A theme in the recent retirement literature is the importance of a fourth leg on the traditional retirement 

income stool: earnings. With two of the three legs missing for most non-full-time career workers, reliance on 

earnings later in life is very real for these workers. By 

switching jobs, these workers appear flexible with respect 

to the kind of work they do later in life, and many of 

them weather the fluctuations that come with late-life 

job changes, including reductions in wages. Earnings 

from work play a key role for many non-full-time career 

workers who would otherwise have to rely solely on Social Security.

One well-established conclusion from the retirement 

literature is that retirement is not a one-time, permanent 

event for many career workers. In fact, the majority of 

older Americans retire gradually, in stages, and often reenter the labor market after a significant time away from 

it. The findings presented in this article show that, like the 

retirement decisions of full-time career workers, those of 

noncareer workers are diverse. This flexibility with respect 

to the labor force withdrawal patterns of both career and 

noncareer older workers may be the key to retirement income security in the years ahead, as earnings from work 

fill the gap where other retirement income sources fall 

short.

Notes

1 See Joseph F. Quinn, “Retirement Patterns and Bridge Jobs in 

the 1990s,” EBRI Issue Brief No. 206 (Washington, DC, Employee 

Benefit Research Institute, February 1999), http://www.ebri.org/

publications/ib/index.cfm?fa=ibDisp&content_id=119; Joseph F. 

Quinn, Kevin E. Cahill, and Michael D. Giandrea, “Early Retirement: 

The Dawn of a New Era?” TIAA-CREF Institute Policy Brief (New 

York, TIAA-CREF Institute, July 2011), http://www.tiaa-cref.org/

institute/research/briefs/pb_earlyretirement0711.html; Michael 

D. Giandrea, Kevin E. Cahill, and Joseph F. Quinn, “Bridge Jobs: A 

Comparison Across Cohorts,” Research on Aging, September 2009, pp. 

549–576; and Christopher J. Ruhm, “Bridge Jobs and Partial Retirement,” Journal of Labor Economics, October 1990, pp. 482–501.

2 See Kevin E. Cahill, Michael D. Giandrea, and Joseph F. Quinn, 

“Retirement Patterns from Career Employment,” The Gerontologist, 

August 2006, pp. 514–523.

3 See Michael D. Giandrea, Kevin E. Cahill, and Joseph F. Quinn, 

“Self-Employment Transitions among Older American Workers 

with Career Jobs,” Working Paper Series WP-418 (U.S. Bureau of 

Labor Statistics, April 2008), http://www.bls.gov/osmr/abstract/ec/

ec080040.htm. 

4 See Nicole Maestas, “Back to Work: Expectations and Realizations of Work after Retirement,” Journal of Human Resources, summer 

2010, pp. 719–748; and Kevin E. Cahill, Michael D. Giandrea, and 

Joseph F. Quinn, “Reentering the Labor Force after Retirement,” 

Monthly Labor Review, June 2011, pp. 34–42, http://www.bls.gov/

opub/mlr/2011/06/art2full.pdf. 

5 Cahill, Giandrea, and Quinn, “Retirement Patterns.” 

6 See The 2011 Annual Report of the Board of Trustees of the Federal 

Old-Age and Survivors Insurance and Federal Disability Insurance Trust 

Funds (Washington, DC, U.S. Government Printing Office, 2011), 

p. 53; Alicia H. Munnell, “Working Longer: A Potential Win–Win 

Proposition,” in Teresa Ghilarducci and John Turner, eds., Work Options 

for Older Americans (Notre Dame, IN, University of Notre Dame Press, 

2007), pp. 11–43; and Nicole Maestas and Julia Zissimopoulos, “How 

Longer Work Lives Ease the Crunch of Population Aging,” Journal of 

Economic Perspectives, winter 2010, pp. 139–160.

7 See Courtney C. Coile and Phillip B. Levine, “Bulls, Bears, and 

Retirement Behavior,” Industrial and Labor Relations Review, April 

2006, pp. 408–429.

8 See, for instance, Andrew A. Samwick, “New Evidence on Pensions, Social Security, and the Timing of Retirement,” Journal of Public 

Economics, vol. 70, no. 2, 1998, pp. 207–236; Patricia M. Anderson, Alan 

L. Gustman, and Thomas L. Steinmeier, “Trends in Male Labor Force 

Participation and Retirement: Some Evidence on the Role of Pensions 

and Social Security in the 1970s and 1980s,” Journal of Labor Economics, October 1999, pp. 757–783; and Christopher J. Ruhm, “Secular 

Changes in the Work and Retirement Patterns of Older Men,” The 

Journal of Human Resources, spring 1995, pp. 362–385.

9 See Alicia H. Munnell, Kevin E. Cahill, and Natalia A. Jivan, 

“How Has the Shift to 401(k)s Affected the Retirement Age?” Issue 

Brief no. 13 (Boston, Center for Retirement Research, September 

2003); Leora Friedberg and Anthony Webb, “Retirement and the Evolution of Pension Structure,” Journal of Human Resources, spring 2005, 

pp. 281–308; and Alicia H. Munnell and Pamela Perun, “An Update 
Older Workers and Jobs

32 Monthly Labor Review • May 2012

on Private Pensions,” Issue Brief no. 50 (Boston, Center for Retirement 

Research, August 2006).

10 See, for example, Jonathan Gruber and Brigitte Madrian, 

“Health Insurance Availability and the Retirement Decision,” American Economic Review, September 1995, pp. 938–948; Alan L. Gustman 

and Thomas L. Steinmeier, “Employer Provided Health Insurance and 

Retirement Behavior,” Industrial and Labor Relations Review, October 

1994, pp. 124–140; Lynn A. Karoly and Jeannette Rogowski, “The Effect of Access to Post-Retirement Health Insurance on the Decision 

to Retire Early,” Industrial and Labor Relations Review, October 1994, 

pp. 103–123; David M. Blau and Donna B. Gilleskie, “The Role of 

Retiree Health Insurance in the Employment Behavior of Older 

Men,” International Economic Review, May 2008, pp. 475–514; and 

Eric French and John Bailey Johns, “The Effects of Health Insurance and Self-Insurance on Retirement Behavior,” Working Paper 

2007-170 (Ann Arbor, MI, Michigan Retirement Research Center, 

October 2007).

11 See Julie L. Hotchkiss and M. Melinda Pitts, “Female Labour 

Force Intermittency and Current Earnings: Switching Regression 

Model with Unknown Sample Selection,” Applied Economics, March 

2005, pp. 545–560.

12 See Jay Stewart, “Male Nonworkers: Who Are They and Who 

Supports Them?” Demography, August 2006, pp. 537–552.

13 See Julie Whittaker, Unemployment and Older Workers, CRS Report to Congress (Congressional Research Service, August 29, 2007); 

and Sewin Chan and Ann Huff Stevens, “Job Loss and Employment 

Patterns of Older Workers,” Journal of Labor Economics, April 2001, pp. 

484–521.

14 For a description of the HRS, see F. Thomas Juster and Richard 

Suzman, “An Overview of the Health and Retirement Study,” Journal of 

Human Resources, vol. 30, special issue, 1995, pp. S7–S56; and Growing 

Older in America: The Health & Retirement Study (U.S. Department of 

Health and Human Services, 2007), http://www.nia.nih.gov/health/

publication/growing-older-america-health-and-retirement-study.

15 The HRS sample includes the spouses of age-eligible respondents, 

a factor that explains the higher percentage of women who were less 

than 54 years old in 1992 (45 percent), compared with men (29 percent).

16 For an analyses of the retirement patterns of couples, see Courtney C. Coile, “Retirement Incentives and Couples’ Retirement Decisions,” Topics in Economic Analysis and Policy, July 2004, pp. 1–28; and 

Kanika Kapur and Jeannette Rogowski, “The Role of Health Insurance 

in Joint Retirement among Married Couples,” Industrial and Labor 

Relations Review, April 2007, pp. 397–407.

17 Occupations are categorized as blue or white collar and then as 

highly skilled or not highly skilled. Individuals working in managerial 

or professional occupations are considered as being white-collar, highly 

skilled workers. Those working in technical, sales, and administrative 

support occupations are categorized as being in white-collar positions 

that are not highly skilled. Workers in precision production, craft, and 

repair occupations; construction trades; machine operator, assembler, 

and inspector occupations; transportation and material moving occupations; and protective service occupations are considered blue-collar, 

highly skilled workers. All other occupations are labeled blue collar and 

not highly skilled.

18 For an analysis of bridge jobs among the self-employed, see 

Giandrea, Cahill, and Quinn, “Self-Employment Transitions.” 

19 Estimation was performed in two additional ways: with a linear 

probability model and a fixed-effects linear probability model. Similar 

results were obtained with all three methods.

20 Although the level of part-time employment was associated with 

the way in which respondents were stratified in the first wave (i.e., 

full-time career status is defined, in part, by whether the respondent 

was working full time during that wave), the two groups also were 

compared many years later, including in the last survey (2008), 16 years 

after the first interview.