BLS WORKING PAPERS 

 U.S. Department of Labor 

U.S. Bureau of Labor Statistics

Office of Productivity and Technology 

Employment Patterns and Determinants Among Older Individuals with a History of 

Short-Duration Jobs

Kevin E. Cahill, Analysis Group, Inc.

Michael D. Giandrea, U.S. Bureau of Labor Statistics

Joseph F. Quinn, Boston College

Working Paper 440

August 2010

All views expressed in this paper are those of the authors and do not necessarily reflect the views or policies of the

U.S. Bureau of Labor Statistics.
Employment Patterns and Determinants 

Among Older Individuals with a History of Short-Duration Jobs

Kevin E. Cahill, Ph.D. 

(corresponding author)

Analysis Group, Inc. 

111 Huntington Avenue, 10th Floor 

Boston, MA 02199 

Email: kcahill@analysisgroup.com

Phone: (617) 425-8380 

Michael D. Giandrea, Ph.D.

U.S. Bureau of Labor Statistics 

Office of Productivity and Technology 

Postal Square Building, Room 2180 

2 Massachusetts Ave., NE 

Washington, DC 20212-0001 

Email: giandrea.michael@bls.gov

Phone: (202) 691-5628 

Joseph F. Quinn, Ph.D. 

Department of Economics 

Boston College 

Chestnut Hill, MA 02467-3859 

Email: joseph.quinn@bc.edu

Phone: (617) 552-2393 

July 16, 2010 

 

All views expressed in this paper are those of the authors and do not necessarily reflect the views or 

policies of the U.S. Bureau of Labor Statistics. The Alfred P. Sloan Foundation supported this research 

through a grant to the Sloan Center on Aging and Work at Boston College.
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Abstract

Many studies of labor force withdrawal patterns have focused on individuals who have 

had career jobs. This paper compares the demographic and economic characteristics of 

individuals who have never had a full-time career (FTC) job with those who have, and compares 

the timing and types of job switches that both groups make later in life. The comparison 

between non-FTC and FTC individuals is important because decisions by policymakers based on 

the existing retirement literature may have unintended consequences for individuals with only a 

series of short-duration jobs. 

 We use a sample of respondents from the Health and Retirement Study (HRS) who have 

worked since age 50, and stratify respondents according to whether an individual has ever had a 

job that consists of 1,600 or more hours per year and lasts for at least ten years (i.e., a full-time 

career job). We find that individuals without FTC jobs are a heterogeneous group, representing 

individuals in many wage and occupational categories. Not surprisingly, we also find that 

individuals without FTC jobs are less likely than those with FTC jobs to be working in 

subsequent survey years. However, we find that the labor force withdrawal patterns of non-FTC 

individuals are similar to those of FTC individuals in many respects. In particular, individuals 

without FTC jobs change jobs later in life just as frequently as those with FTC jobs. Switching 

rates between wage-and-salary employment to self-employment and between white-collar and 

blue-collar jobs are largely similar by FTC status, as are reductions in wages later in life. 

Overall, the findings reveal that the work decisions later in life of individuals who have never 

had career employment are diverse, just as they are for individuals with career jobs. 

Key words: Economics of Aging, Bridge Jobs, Gradual Retirement 

JEL No.: J26, J14, J32, H55 
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I. Introduction

Many studies of labor force withdrawal patterns have focused on individuals who have had 

career jobs. One of the main findings from this research is that, more often than not, individuals 

with career jobs make at least one job change prior to exiting the labor force.1 Further, a 

substantial minority of individuals with wage-and-salary career jobs, approximately 10 percent, 

transition into self employment later in life.2 Evidence also suggests that many individuals with 

career jobs, approximately 15 percent, re-enter the labor force after initially “retiring” and that 

these re-entry decisions are often expected prior to leaving career employment.3

An important question is whether these findings from the retirement literature also apply to 

individuals who have never held a full-time career job because policy decisions based upon the 

existing literature may have different and unintended consequences for workers with intermittent 

work histories and with 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 2 to 1 by 

2030, policymakers may look for ways to encourage continued labor force participation among 

individuals who reach traditional retirement ages. The existing literature on job transitions later 

in life provides evidence that such a policy may be welfare enhancing as the majority of 

individuals with career jobs do not exit the labor force abruptly, but instead transition to gradual 

retirement voluntarily. 

 These job 

transitions also appear to be voluntary for most individuals. Collectively, these findings suggest 

that many career individuals view a job change later in life as a valuable option that can be 

exercised in order to exit the labor force gradually.

 

1 See Cahill, Giandrea, and Quinn (2006) and Giandrea, Cahill, and Quinn (2008).

2 See Giandrea, Cahill, and Quinn (2008).

3 See Maestas (2007) and Cahill, Giandrea, and Quinn (2010).
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Individuals without career jobs represent a sizable fraction of older Americans. Existing 

studies show that approximately 25 percent of men and nearly 50 percent of women have never 

had a career job, at least not later in life.4

This paper addresses the issue of retirement among people with a history of short duration 

jobs by comparing them to those who have had career employment, either currently or in the 

past. We first compare the demographic and economic characteristics of individuals with and 

without career jobs in their work histories. We then focus on retirement outcomes by examining 

how long individuals who have never had a career job stay in the labor force relative to those 

with career job experience, and the extent to which job changes later in life are a significant 

phenomenon within the two groups. We then examine the types of job changes that career and 

non-career workers make later in life. In particular, we focus on switches between full-time and 

part-time work, between wage-and-salary and self employment, and between white-collar and 

blue-collar occupations. We also explore the extent to which wages are reduced when a job 

change is made later in life. Throughout the analysis, we examine men and women separately to 

take into account potential differences in retirement patterns and determinants. 

 Therefore, the results from the retirement literature on 

career employment might be limited in scope. 

Data for this study come from the Health and Retirement Study (HRS), a rich, nationally 

representative micro-level data set of approximately 12,600 individuals born between 1931 and 

1941 (i.e., aged 51–61 in 1992).5

 

4 See Cahill, Giandrea, and Quinn (2006).

 The data are longitudinal and ongoing with interviews 

conducted every two years since 1992, with the most recently released data covering the 2008 

survey. Attrition across waves ranged from three to ten percent, so that after 16 years about 62 

percent of the original HRS core sample remained. 

5 See Juster and Suzman (1995) for a description of the Health and Retirement Study.
- 5 -

The focus of this study is on HRS respondents who have worked, but who have never had a 

job that consisted of 1,600 or more hours per year and lasted for at least ten years (our definition 

of a full-time career (FTC) job). In order to construct work histories for each of the HRS 

respondents, we use all information available from each survey year from 1992 to 2008. In 

addition, we utilize information from the first HRS interview that asked about a respondent’s 

current job and all previous jobs that lasted five years or more. If a respondent was not working 

at the time of the wave 1 interview, he or she was asked about the most recent job held, if any. 

In addition to stratifying HRS respondents by FTC status, we also exclude individuals with no 

work experience after age 50 because this paper focuses on labor force behavior and retirement 

patterns, and transitions out of the labor force prior to age 50 are unlikely to be part of the 

retirement process. 

This paper is structured as follows. The next section provides some background and an 

overview of the relevant literature on transitional retirement. Section III describes the dataset – 

the Health and Retirement Study – and methods. Section IV provides a detailed description of 

the two key subgroups used in our analysis: (1) respondents who have worked since age 49 and 

who have never had a FTC job and (2) respondents who have worked since age 49 and who have 

had a FTC job. Section V summarizes the main findings. 

II. Background 

Much of the retirement literature on patterns of labor force withdrawal has focused on 

individuals with full-time career jobs, who often enjoy employer-provided benefits, or 

individuals with at least full-time employment into their 50s and 60s. For example, Cahill, 

Giandrea, and Quinn (2006) found that 60 percent of older workers who had left full-time career 

jobs had moved to short duration or part-time employment (known as bridge jobs) before 
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complete labor force exit. Since, by definition, a bridge job is one that follows a full-time career 

job, few researchers have specifically addressed workers with intermittent work histories. 

Among those who have, Hotchkiss and Pitts (2007) analyze how intermittent work histories 

affect the wages of women. They found that intermittency could result in a wage penalty that 

was experienced at even low levels of labor force absence. 

Most authors, however, have addressed labor force activity of older workers without 

considering the prior degree of labor force attachment. For example, Coile and Levine (2006) 

considered the effect of wealth on labor force activity utilizing data from the HRS, the Current 

Population Survey, and the Survey of Consumer Finances, but they did not stratify their findings 

by career job status. Similarly, Anderson, Gustman, and Steinmeier (1999) and Ruhm (1995) 

addressed the role of pensions in the labor force behavior of older workers. Gustman and 

Steinmeier (1994) and Madrian, Burtless, and Gruber (1994) investigated the role of health 

insurance in the work/leisure decision among older Americans. Other studies have examined 

switches to self employment later in life (Cahill, Giandrea, and Quinn, 2007), labor force reentry later in life (Maestas, 2007), and the voluntary nature of job transitions later in life, and 

have focused on individuals with career jobs. While these studies are valuable in describing the 

labor force behavior among older workers generally, they do not specifically address how 

workers of differing labor force attachment might retire differently. Our analysis attempts to fill 

this void in the retirement literature.

III. Data and Methods 

The large majority of HRS men and women had work experience later in life, as shown in 

Table 1. Over 90 percent of men and 78 percent of the women in the sample had worked since 

age 50. We stratified this sub-sample according to whether respondents had ever held a FTC job, 
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and found that, among those who worked since age 50, 88 percent of men (88% = 4,745 / 5,378) 

and 69 percent of women (69% = 3,635 / 5,300) had a FTC job in their work history. Therefore, 

a sizable minority of respondents – 12 percent of men (12% = 633 / 5,378) and 31 percent of 

women (31% = 1,665 / 5,300) – had worked since age 50 but did not have a FTC job. These are 

our comparison groups. 

Demographic and economic characteristics and labor force outcomes are compared across 

these two groups using descriptive statistics and multivariate analyses. The set of demographic 

and economic characteristics are based on responses from the first interview in 1992. Labor 

force outcomes, however, are based on an individual’s work history, and focus on work status in 

each wave and the number of job switches since the first interview. 

Using multivariate techniques, we first ask whether the existence of a FTC job in one’s 

work history affects the likelihood of working as respondents approach traditional retirement 

ages. Here, FTC employment status may represent an individual’s economic and emotional 

attachment to the labor force, after controlling for a number of economic and demographic 

characteristics. The first multivariate model explores the timing of the retirement decision 

among non-FTC and FTC individuals, and is specified as follows: 

_ )1( 21 3 4 5 6

*

it i FTC History t Y it RET it H it X i X it R ++++++= ββββββα + ε

Observations are person-year. The left-hand side of this binary choice model is a latent 

variable, Rit

*

, which determines the observed choice of whether or not to work in period t. Rit

indicates that observed choice and is equal to 1 if individual i is working at time t, and is equal to 

zero otherwise. Variables Xi and Xit represent, respectively, time invariant and time varying 

individual characteristics. Hit is an indicator of health status and RETit is a vector of retirement 

incentives associated with an individual’s private pension plan and health insurance plan. Yt is a 
- 8 -

series of year dummies that are intended to account for macroeconomic changes. FTC_Historyi

represents a dichotomous indicator for whether an individual has had a FTC job in his or her 

work history, and εit is a white noise error term. The model is estimated for all individuals in the 

sample who worked since age 50. Marginal effects from the regression are evaluated at the 

sample means.

We also examine job switching after the first interview using a multinomial logistic 

regression model with a three-way outcome variable: remained on the wave one job, switched to 

another job, or exited the labor force directly. We use FTC job status as an indicator of 

attachment to the current job, and hypothesize that those with FTC jobs in their work history will 

display more attachment to their current work position while controlling for economic and 

demographic characteristics. A latent dependent variable determines the observed choice to 

remain working on the wave one job, switch to another job, or exit the labor force. The observed 

choice is set equal to 0 for those who are still on their 1992 job when we last observe them, 1 if 

an individual switched to at least one other job since the wave one interview, and 2 if the 

individual exited the labor force directly without any job switches. The set of right-hand side 

variables include the demographic and economic characteristics described above, and are 

measured at the time of the first interview. The model is estimated for all individuals in the 

sample who were working in wave one. Marginal effects from the regression are evaluated at 

the sample means.

IV. Results

As noted above and as shown in Table 1, 88 percent of men who worked since age 50 

also held a FTC job at some point in their work history, as did 69 percent of women. The 
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remaining 12 percent of men and 31 percent of women who worked since age 50 never held a 

FTC job. 

Demographic and Economic Characteristics by FTC Status 

Table 2 presents demographic characteristics measured at the time of the first HRS 

interview, by gender and FTC status. Among the men who never held a FTC job, we find a 

nearly equal distribution of self-assessed subjective health status across three categories: 

excellent or very good, good, and fair or poor. In contrast, this distribution is skewed towards 

excellent or very good health for those with FTC jobs in their work history; these male 

respondents were three times more likely to describe their health as excellent or very good 

instead of fair or poor. 

Regarding higher education, there was only a slight difference by FTC status; 82 percent 

of men without a FTC job had less than a college degree compared to 77 percent of men with a 

FTC job in their work history. Men who had never had a FTC job were almost twice as likely as 

those with a FTC job to be unmarried in 1992 (19 versus 11 percent). About one half of men who 

had never had a FTC job had an employed spouse, compared to 57 percent of those who had a 

FTC job. This may indicate that, to a certain extent, employment and attachment to the labor 

force are complementary among spouses.6

 Among women, including both primary HRS respondents and spouses of the age-eligible 

male respondents, we find that the distribution of ages was nearly uniform from 51 to 61 for 

those who have never held a FTC job. Those with FTC jobs, however, were more than twice as 

likely to be younger than 53 in 1992 than 54 to 57 or 58 to 61. This age difference may reflect a 

greater labor force attachment and reduced labor force intermittency among the younger women 

 

 

6 See Coile (2004) and Kapur and Rogowski (2007), among others, for recent analyses of retirement patterns of 

couples.
- 10 -

in the sample. Among the other demographic characteristics, however, differences by FTC 

status were somewhat less pronounced among the women than for the men. We also note that 

the percentage of women who were married as of the first interview was much lower than the 

percentage of men who were married. This difference is likely due to a combination of women 

marrying older men, on average, and higher mortality rates among men. 

In Table 3, we describe the economic characteristics of the sample as measured in 1992. 

Among men without FTC jobs in their work history, 67 percent had health insurance on their 

1992 job that would be maintained if they left the job, compared to 80 percent among men with 

FTC jobs in their work history. More than one quarter (28%) of men without a FTC job did not 

have health insurance coverage on their wave one job, compared to only 11 percent of men with 

a FTC job. Regarding pension status, men who did not have a FTC job in their work history 

were much less likely than those with FTC jobs to have a defined-benefit (DB) pension (20 

percent versus 47 percent) or a defined-contribution (DC) pension (11 percent versus 17 

percent). Two thirds of men without a FTC job in their work history had no pension. 

We also analyze occupational status, broadly defined, as of 1992.7

We find very clear and statistically significant differences in the wage distributions of 

those with and without FTC jobs. Non-FTC men were three times as likely as FTC men to be 

 Among men who 

never held a FTC job, 25 percent were employed in blue collar / not highly skilled positions in 

1992. Among men with a FTC job, only 14 percent were blue collar / not highly skilled, while 

one third were white collar / highly skilled, and 38 percent were blue collar / highly skilled. 

 

7 Occupation is categorized as blue/white collar, and then categorized as highly/not highly skilled. Individuals 

working in managerial or professional occupations are considered white collar, highly skilled. Individuals working 

in technical, sales, and administrative support occupations are considered white collar, not highly skilled. 

Individuals working 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. All other occupations are considered blue collar, not highly 

skilled. 
- 11 -

making $6 to $10 per hour on their 1992 job (30 percent versus 10 percent) and were half as 

likely to be earning between $20 and $50 per hour (23 percent versus 46 percent). 

We find a similar result when examining wealth in 1992. More than one half (56 

percent) of men with no FTC job in their work history had non-pension financial wealth of 

$25,000 or less, compared to 36 percent of men with FTC jobs. At the other end of the wealth 

spectrum, only 23 percent of the men with no FTC job in their work history had non-pension 

financial wealth of $100,000 or more compared to 34 percent of men who had a FTC job. 

Increasing labor force attachment among men is associated with increased non-pension wealth. 

This may be indicative of more and larger paychecks providing increased opportunities for 

saving. 

Among women, we find that those with no FTC job in their work history were about one 

third as likely as those with a FTC job to have a DB pension (15 percent versus 41 percent and 

almost twice as likely to have no pension (77 percent versus 39 percent). We also observe 

similar distributions as we saw with men vis-à-vis wage rate on the 1992 job. Women who did 

not have a FTC job were about twice as likely as those with FTC jobs to earn between $6 and 

$10 per hour (37 percent versus 18 percent) and were nearly half as likely as those with FTC jobs 

to earn between $20 and $50 per hour (20 percent versus 37 percent). Differences in nonpension financial wealth by FTC status, however, were much less pronounced than those among 

the men. This result may reflect the extent to which wealth among women is dependent on 

marital status.

To summarize, we note that increasing attachment to the labor force via a FTC job is 

associated with having a job with good characteristics, such as health insurance, pension 

benefits, and higher wages. Whether the attachment is due to the quality of the jobs or the 
- 12 -

quality of jobs is due to continued labor force attachment, we are unable to determine in this 

analysis.

Retirement Outcomes 

The first two outcomes we address are work status and the prevalence of part-time 

employment. We examine each of these outcomes over time, from 1992 through 2008, for men 

and women separately. Not surprisingly, respondents were less likely to be working in 

subsequent surveys (Figures 1a and 1b for men and women, respectively). The patterns by 

gender were remarkably similar, though women were somewhat more likely to be working in 

each survey year, reflecting in part the fact that these women with work experience since age 49 

were, as a whole, younger than their male counterparts. In all survey years for both men and 

women, individuals with FTC jobs in their work histories were significantly more likely to be 

working than those without. 

While the work status patterns were similar by FTC status (i.e., a gradual monotonic 

decline in employment), the role of part-time employment was different across these two groups 

(Figures 2a and 2b). Part-time employment became increasingly common over time among 

individuals with a FTC job in their work history, as some full-time career workers moved into 

part-time employment, whereas the percentage of individuals without FTC jobs who were 

working part time was much higher and remained relatively stable, especially for women. Only 

10 percent of the men with a FTC job in their work history were working part time in 1992. This 

percentage increased steadily through 2008, when more than one half of these men were working 

part time. Among men who never held a FTC job, more than 60 percent were working part time 

in 1992. This percentage remained fairly constant through 2000, and then increased to between 

70 and 80 percent from 2002 to 2006 before declining somewhat in 2008. A similar pattern is 

observed among women where the percent working part time increased steadily among those 
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with FTC jobs in their work history and the percent working part time remained relatively stable 

at approximately 80 percent for those women without a FTC job. 

Table 4 describes the number of job switches since 1992 among those respondents who 

were working at the time of the first interview. Overall, we find that for both men and women, 

approximately one half of workers with no FTC job in their work history had exited the labor 

force directly from their 1992 job, compared to 42 percent of those with a FTC job. About one in 

ten respondents without a FTC job were still on their wave one job when they were last observed 

(8 percent of men and 11 percent of women), compared with 18 percent of the men and women 

with FTC jobs in their work histories. Among all respondents who had switched employment 

since wave one, most had switched only once; relatively few respondents, between 6 and 7 

percent, had more than two job switches. In summary, those without FTC jobs in their work 

histories were less likely than those with FTC jobs to remain working on their wave one job; 

however, the number of job switches since wave one were similar by FTC status for both men 

and women. These qualitative findings remained when we restricted the sample to respondents 

who participated in all 9 waves of the HRS through 2008 (bottom panel of Table 4). 

Table 5 provides more information relating to the nature of job switches among those 

with different FTC job histories. We find that slightly more than one third of men and women 

who had work experience since age 49 and who were working in 1992 experienced a switch 

from full-time to part-time work, with the percentage of non-FTC respondents making the switch 

being somewhat higher than those with FTC jobs (41 percent versus 35 percent for men and 39 

percent versus 36 percent for women). We also find that 26 percent of the men and 32 percent of 

the women reported a switch from self employment to wage-and-salary work while only 13 

percent of men and 10 percent of women reported a switch from wage-and-salary work to self 
- 14 -

employment.8

Finally, we consider the changes in wage that resulted from job switches. We divide job 

switches into those that result in a wage reduction of 50 percent or more, a reduction from 10 to 

50 percent, a change between +/-10 percent (essentially unchanged), an increase of 10 to 50 

percent, an increase of 50 to 100 percent, and finally and increase of 100 percent or more. The 

majority of job switches (69 percent for men and 64 percent for women) involved a significant 

change in wage rate (more than 10 percent), with declines outweighing increases. About 16 

percent of men and 10 percent of the women in the sample had job switches with a reduction in 

wage of 50 percent or more. Similarly, one quarter of men and women had wage reductions of 

10 to 50 percent. We find that only 22 percent of those men with no FTC job in their work 

history had job switches with little to no change in wage (+/- 10 percent), compared with 32 

percent of the men on a FTC job in wave one. This is particularly notable because these FTC 

men on average had higher wages. The most interesting finding relates to job switches where 

wages increased. Men with less attachment to the labor force were essentially just as likely to 

have job switches where wages increased as were those with FTC jobs in their work histories. 

 Switches from wage-and-salary work to self employment were similar by FTC 

status; however, switches from self employment to wage-and-salary work were less common 

among those without FTC jobs than those with FTC jobs (21 percent versus 27 percent among 

men and 28 percent versus 33 percent among women). We find that switches from white-collar 

to blue-collar positions were more likely than switches from blue-collar to white-collar for men 

(15 percent versus 10 percent) while the opposite was true for women (8 percent versus 12 

percent). The occupation switch rate for men differed slightly by FTC status, with non-FTC 

workers being less likely to make a switch. The differences, however, were not statistically 

significant. 

 

8 See Giandrea, Cahill, and Quinn (2008) for an analysis of bridge jobs among the self employed.
- 15 -

Indeed, men with no FTC job were twice as likely as men with FTC jobs to experience a job 

switch where wages increased by 100 percent or more (12 percent versus 6 percent). This 

reflects the generally lower wages that the non-FTC men were earning before the switch (see 

Table 3).

If we instead track only those men who participated in all 9 waves of the HRS, we lose a 

portion of the sample but obtain a complete record of job switches from 1992 to 2008 for many 

workers. In this sample and for both those with and without FTC jobs in their work histories, we 

continued to observe that, among men, about 45 percent of switches led to a decrease in wage 

while about 26 percent of switches resulted in an increase in wage of more than 10 percent. The 

findings among women with respect to changes in wages were similar to those among the men, 

with 36 percent of women experiencing a reduction in wage of 10 percent or more and 30 

percent of women experiencing an increase in wage of 10 percent or more. Non-FTC individuals 

remained less likely than FTC individuals to experience a change in wage of less than 10 percent 

(23 percent versus 29 percent for men and 31 versus 34 percent for women). 

Multivariate Analysis

Tables 6a and 6b present marginal effects from a logistic regression of work status (1 if 

working; 0 if not) in each wave for men and women, separately.9

 

9

 We also performed this estimation two additional ways, using a linear probability model and a linear probability 

model with fixed effects. We obtain similar results using all three methods.

 Both men and women were 

more likely to be working the healthier and younger they were, with a particularly large decrease 

at age 62, when most respondents became eligible for Social Security retirement benefits. 

Respondents were also more likely to be working, all else equal, if they were self-employed, had 

a spouse who was working (suggesting joint retirement decisions), a spouse in poor health 

(women only), or were employed in a white collar occupation or a blue collar, highly skilled 
- 16 -

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 health 

insurance that was “portable” (i.e., would not be lost if they left their job) were significantly less 

likely to remain working than those with health insurance that was not portable. Men and 

women with no health insurance were also less likely to remain working than those with health 

insurance that was not portable. Men and women with defined-benefit pension plans were 

considerably less likely to be working than those without pensions, a result that is consistent with 

the age-specific early retirement incentives typically incorporated in such plans. 

A focus of this analysis is how work decisions differ by FTC status. We find that for 

both men and women, individuals with a FTC job in their work history were more likely to be 

working, all else equal, compared to those without a FTC job. This result reinforces the 

differences by FTC status noted earlier with respect to the percentage of respondents working in 

each wave (Figures 1a and 1b). 

The next set of multivariate analyses examine the determinants of job switching among 

respondents who were working at the time of the first interview. Each respondent with a job in 

1992 either remains on the 1992 job as long as we can follow them, switches to another job (e.g., 

a bridge job for those with a FTC job), or leaves the labor market directly from the 1992 job. As 

shown in Table 7a we find that men were more likely to remain working on the wave one 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 wave one job if they had a definedbenefit pension plan. Men were more likely to switch jobs before exiting the labor force if they 

were younger or had health insurance (portable or not portable), and were less likely to switch if 
- 17 -

they were blue collar, self employed, or had a defined-benefit pension. Men who had a FTC job 

were more likely to remain on the wave one job than those who did not have a FTC job, and less 

likely to switch jobs prior to labor force exit, though the latter effect was not statistically 

significant. The results were similar among women though, notably, women with pensions (DB 

or DC) more likely to remain working on the wave one job (Table 7b). 

V. Conclusion 

This paper compares the demographic and economic characteristics and work decisions 

of older Americans who did not have FTC jobs in their work histories with those who had FTC 

jobs. The goal is to examine more closely the retirement decisions of non-FTC workers with 

respect to the timing of retirement and the number and types of job switches that are made later 

in life. We find that non-FTC individuals are a heterogeneous group, representing individuals in 

many wage and occupational categories. Not surprisingly, descriptive statistics reveal that 

individuals who never held a full-time career job were less likely to be working in subsequent 

survey years than those who held career jobs at some point. However, we find that individuals 

without full-time career jobs in their work history change jobs later in life just as frequently as

those with career jobs. Switching rates from wage-and-salary employment to self-employment 

and between white-collar and blue-collar jobs were generally similar by full-time career job

status, as were reductions in wages later in life. 

Some notable differences by FTC status do exist. For example, part-time employment 

became more pronounced over time for FTC individuals while it remained fairly constant among 

individuals without FTC jobs. The percentage of men without FTC job experience who were 

working part time was consistently above 50 percent in all survey years and above 70 percent 

among women without FTC jobs, whereas among individuals with FTC jobs the percentage 
- 18 -

working part time increased from approximately 10 percent in wave one to more than 50 percent 

in wave 9. While the level of part-time employment was associated with the way in which 

respondents were stratified in wave one (i.e., FTC status is defined, in part, by working full 

time), the two groups were compared many years later, such as in the last survey, 16 years after 

the first interview.

One well-established conclusion from the retirement literature is that, for career workers, 

retirement is not a one-time, permanent event. This appears to be true for non-career workers as 

well, as the pathways that non-FTC individuals utilize to exit the labor force are also very 

diverse.
- 19 -

References

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the 1970s and 1980s,” Journal of Labor Economics, Vol. 17, No. 4, pp. 757-783. 

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Employment,” The Gerontologist, 46(4), 514-523. 

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Men Women Total

Participated in wave 1

n 5,869 6,783 12,652

Worked since age 50

n 5,378 5,300 10,678

% of all HRS respondents 92% 78% 84%

No FTC job in work history

n 633 1,665 2,298

% of HRS respondents who 12% 31% 22%

have worked since age 50

FTC job in work history

n 4,745 3,635 8,380

% of HRS respondents who 88% 69% 78%

have worked since age 50

Source: Authors’ calculations based on the Health and Retirement Study.

HRS Respondents Aged 51-61 in 1992

Table 1

Sample Size

by Gender, Survey Participation, and Work Status
No FTC job in FTC job in No FTC job in FTC job in

Characteristic All work history work history All work history work history

Age ##,^^

<53 29% 20% 30% 45% 33% 51%

54-57 29 27 30 29 32 27

58-61 25 31 25 25 33 21

62+ 17 22 16 2 2 2

Subjective Health Status ##,^^

excellent or very good 52 36 54 56 48 59

good 30 33 30 27 27 28

fair or poor 18 31 17 17 25 13

College Degree ##,^^ 22 18 23 16 12 18

Less than College Degree 78 82 77 84 88 82

Married ##,^^ 88 81 89 75 77 74

Not Married 12 19 11 25 23 26

Dependent Children ^ 17 19 16 14 12 15

No Dependent Children 83 81 84 86 88 85

Spouse's Health Status ##

excellent or very good 56 48 56 51 50 51

good 27 29 27 29 31 29

fair or poor 17 23 16 20 19 20

Employed spouse ## 56 50 57 55 53 55

No employed spouse 44 50 43 45 47 45

n 5,378 633 4,745 5,300 1,665 3,635

#, ## Difference by full time career job status among men is significant at a 5% or 1% level, respectively.

^, ^^ Difference by full time career job status among women is significant at a 5% or 1% level, respectively.

Source: Authors’ calculations based on the Health and Retirement Study.

Table 2

Demographic Characteristics at the Time of the First Interview

Sample: HRS Respondents with Work Experience Since Age 50

Men Women

by Gender and FTC Job Status 
No FTC job in FTC job in No FTC job in FTC job in

Work status All work history work history All work history work history

Health Insurance Status *,##,^^

Not covered on wave 1 job 13% 28% 11% 14% 21% 11%

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

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

Pension Status *,##,^^

Defined - Benefit only 44 20 47 30 14 38

Defined - Contribution only 16 11 17 17 9 21

Both 5 3 5 2 1 3

No Pension 35 67 31 51 77 39

Self-Employed *,#,^ 18 21 17 11 12 10

Wage and Salary* 82 79 83 89 88 90

Occupation Status *,##,^^

White collar, highly skilled 32 28 33 29 20 31

White collar, other 16 16 16 37 32 38

Blue collar, highly skilled 37 32 38 11 9 11

Blue collar, other 15 25 14 24 39 20

Wage Rate *,##,^^

$6 - $10/hour 12 30 10 22 37 18

$10 - $20/hour 21 26 21 36 36 36

$20 - $50/hour 44 23 46 33 20 37

> $50/hour 23 21 23 8 7 9

Wealth ##,^^

$0 8 19 6 11 13 10

$0-$25k 30 37 30 33 33 33

$25k-$50k 14 11 14 13 11 14

$50k-$100k 15 11 16 14 13 15

$100k-$500k 25 16 26 23 22 23

>$500k 8 7 8 6 8 5

Do not own home ##,^^ 16 30 15 19 22 18

Own home 84 70 85 81 78 82

n 5,378 633 4,745 5,300 1,665 3,635

*: Percentages based on respondents who were working in wave one.

#, ## Difference by full time career job status among men is significant at a 5% or 1% level, respectively.

^, ^^ Difference by full time career job status among women is significant at a 5% or 1% level, respectively.

Source: Authors’ calculations based on the Health and Retirement Study.

Table 3

Economic Characteristics at the Time of the First Interview

Sample: HRS Respondents with Work Experience Since Age 50

Men Women

by Gender and FTC Job Status
No FTC job in FTC job in No FTC job in FTC job in

Work status All work history work history All work history work history

All waves ##,^^

Still on wave one job1 17% 8% 18% 16% 11% 18%

Exited directly from wave one job1 43 53 42 43 50 42

1 job switch 24 26 24 23 23 23

2 job switches 10 8 10 10 10 10

3 job switches 4 3 4 4 3 4

4 or more job switches 2 3 2 3 3 3

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

Participated in wave 9 ##,^^

Still on wave one job1 13% 3% 14% 12% 7% 13%

Exited directly from wave one job1 39 47 38 42 47 40

1 job switch 27 28 27 25 25 25

2 job switches 13 11 13 12 13 12

3 job switches 6 6 6 5 4 5

4 or more job switches 3 5 3 4 4 4

n 2,581 184 2,397 2,913 627 2,286

1

 For those without FTC jobs in their work history this category describes the most recent (and only) job observed for the individuals.

#, ## Difference by full time career job status among men is significant at a 5% or 1% level, respectively.

^, ^^ Difference by full time career job status among women is significant at a 5% or 1% level, respectively.

Source: Authors’ calculations based on the Health and Retirement Study.

Men Women

Table 4

Number of Observed Job Switches Since the First Interview

by Gender and FTC Job Status

Sample: HRS Respondents Working in 1992
No FTC job in FTC job in No FTC job in FTC job in

Work status All work history work history All work history work history

All Waves

Full Time or Part Time

Any switch from FT to PT 35% 41% 35% 36% 39% 36%

Any switch from PT to FT ##,^^ 22 22 ----- 18 18 -----

Wage & Salary or Self Employed

Any switch from WS to SE 13 13 14 10 10 9

Any switch from SE to W&S 26 21 27 31 28 33

White Collar or Blue Collar

Any switch from WC to BC 15 11 15 8 7 8

Any switch from BC to WC 10 7 10 12 11 12

Wages #

Reduction in wage of 50%+ 16 17 16 10 12 9

Reduction in wage of 10-50% 25 25 25 25 23 25

No change in wage of 10% 31 22 32 36 35 36

Increase in wage of 10-50% 17 19 17 20 19 21

Increase in wage of 50-100% 4 5 4 4 4 4

Increase in wage of 100%+ 7 12 6 5 6 5

In Wave 9

Full Time or Part Time

Any switch from FT to PT # 44% 57% 43% 43% 42% 43%

Any switch from PT to FT ##,^^ 27 27 ----- 20 20 -----

Wage & Salary or Self Employed

Any switch from WS to SE 17 18 17 12 13 12

Any switch from SE to W&S 33 29 34 39 37 40

White Collar or Blue Collar

Any switch from WC to BC 17 14 17 10 8 10

Any switch from BC to WC 13 10 13 14 13 15

Wages

Reduction in wage of 50%+ 17 20 16 10 13 10

Reduction in wage of 10-50% 28 27 28 26 26 26

No change in wage of 10% 29 23 29 34 31 34

Increase in wage of 10-50% 16 16 16 21 19 21

Increase in wage of 50-100% 4 6 4 4 4 4

Increase in wage of 100%+ 6 9 6 5 6 5

#, ## Difference by full time career job status among men is significant at a 5% or 1% level, respectively.

^, ^^ Difference by full time career job status among women is significant at a 5% or 1% level, respectively.

Source: Authors’ calculations based on the Health and Retirement Study.

Men Women

Table 5

Types of Job Switches

by Gender and FTC Job Status

Sample: HRS Respondents Working in 1992
marginal effect p-value

FTC Status

 No FTC job in work history ----- -----

 FTC job in work history 0.2143 0.000

Age

 57 or less ----- -----

 58-61 -0.1352 0.000

 62-64 -0.3488 0.000

 65-69 -0.4474 0.000

 greater than 70 -0.5733 0.000

Self Assessed Health

 excellent/very good 0.0624 0.000

 good ----- -----

 fair/poor -0.2317 0.000

Spouse's Health

 excellent/very good -0.0476 0.000

 good ----- -----

 fair/poor 0.0147 0.287

Education

 less than high school 0.0127 0.401

 high school ----- -----

 college degree 0.0248 0.133

Race

 black 0.0108 0.552

 white ----- -----

 other 0.0225 0.573

Married 0.0425 0.077

Children at Home 0.0283 0.034

Spouse employed 0.1703 0.000

Health Insurance Status

 portable -0.4924 0.000

 not portable ----- -----

 none -0.4968 0.000

Pension Status

 defined benefit -0.2652 0.000

 defined contribution 0.0064 0.646

 both 0.0514 0.110

 none ----- -----

Occupational Status

 white collar/high skill 0.2414 0.000

 white collar/other 0.2476 0.000

 blue collar/high sckill 0.2074 0.000

 blue collar/other ----- -----

Self Employed 0.1695 0.000

Wage 0.0032 0.000

Wage Squared 0.0000 0.002

Wealth -0.0014 0.000

Wealth Squared 0.0000 0.000

Own Home 0.0195 0.213

Year Indicators

 1992 0.2408 0.000

 1994 0.1403 0.000

 1996 0.0937 0.000

 1998 0.0834 0.000

 2000 0.0476 0.021

 2002 0.0324 0.090

 2004 0.0383 0.019

 2006 0.0124 0.212

 2008 ----- -----

Constant 0.3487 0.000

Source: Authors’ calculations based on the Health and Retirement Study.

Table 6a

Marginal Effects from Logistic Regression

Dependent Variable: Working at Time t

Sample: Male HRS Respondents Who Have Worked Since Age 50
marginal effect p-value

FTC Status

 No FTC job in work history ----- -----

 FTC job in work history 0.1626 0.000

Age

 57 or less ----- -----

 58-61 -0.1318 0.000

 62-64 -0.2946 0.000

 65-69 -0.4015 0.000

 greater than 70 -0.5152 0.000

Self Assessed Health

 excellent/very good 0.0473 0.000

 good ----- -----

 fair/poor -0.2172 0.000

Spouse's Health

 excellent/very good -0.0387 0.001

 good ----- -----

 fair/poor 0.0398 0.003

Education

 less than high school 0.0353 0.024

 high school ----- -----

 college degree -0.0096 0.582

Race

 black 0.0572 0.000

 white ----- -----

 other 0.0669 0.099

Married -0.0425 0.067

Children at Home 0.0315 0.003

Spouse employed 0.1837 0.000

Health Insurance Status

 portable -0.4867 0.000

 not portable ----- -----

 none -0.4755 0.000

Pension Status

 defined benefit -0.1101 0.000

 defined contribution 0.0026 0.853

 both 0.0416 0.213

 none ----- -----

Occupational Status

 white collar/high skill 0.2570 0.000

 white collar/other 0.2884 0.000

 blue collar/high sckill 0.2281 0.000

 blue collar/other ----- -----

Self Employed 0.1623 0.000

Wage 0.0061 0.000

Wage Squared 0.0000 0.000

Wealth -0.0017 0.000

Wealth Squared 0.0000 0.000

Own Home 0.0219 0.127

Year Indicators

 1992 0.2375 0.000

 1994 0.1778 0.000

 1996 0.1193 0.000

 1998 0.1319 0.000

 2000 0.0996 0.000

 2002 0.0639 0.001

 2004 0.0787 0.000

 2006 0.0491 0.000

 2008 ----- -----

Constant 0.2313 0.000

Source: Authors’ calculations based on the Health and Retirement Study.

Table 6b

Marginal Effects from Logistic Regression

Dependent Variable: Working at Time t

Sample: Female HRS Respondents Who Have Worked Since Age 50
marginal effect p-value marginal effect p-value

FTC Status

 No FTC Job in Work History ----- ----- ----- -----

 FTC Job in Work History 0.1476 0.000 -0.0347 0.260

Age in 1992

 51-52 0.1063 0.000 0.1127 0.000

 53-54 0.0712 0.002 0.0897 0.003

 55-56 0.0642 0.006 0.0576 0.062

 57-58 0.0340 0.155 0.0020 0.949

 59-60 0.0179 0.472 0.0119 0.707

 61 ----- ----- ----- -----

Self Assessed Health

 excellent/very good 0.0324 0.018 0.0270 0.139

 good ----- ----- ----- -----

 fair/poor -0.0056 0.790 -0.0572 0.037

Spouse's Health

 excellent/very good -0.0008 0.958 0.0375 0.056

 good ----- ----- ----- -----

 fair/poor 0.0107 0.601 -0.0050 0.855

College Degree 0.0529 0.001 -0.0178 0.421

Race

 black 0.0422 0.021 -0.0431 0.092

 white ----- ----- ----- -----

 other 0.0017 0.964 -0.0108 0.841

Married 0.0222 0.326 0.0496 0.108

Children at Home 0.0073 0.623 0.0160 0.452

Spouse Employed -0.0252 0.052 0.0028 0.877

Occpational Status

 blue collar/high skill 0.0292 0.082 -0.0782 0.001

 blue collar/other 0.0366 0.081 -0.1231 0.000

 white collar/high skill ----- ----- ----- -----

 white collar/other 0.0182 0.323 -0.0249 0.320

Health Insurance Status

 portable -0.0055 0.693 0.0338 0.074

 not portable -0.0366 0.093 0.0941 0.001

 none ----- ----- ----- -----

Self Employed 0.1333 0.000 -0.0819 0.001

Pension Status

 defined benefit -0.0355 0.016 -0.0465 0.029

 defined contribution -0.0033 0.847 0.0269 0.279

 both -0.0798 0.009 0.1269 0.001

 none ----- ----- ----- -----

Own Home -0.0149 0.396 -0.0322 0.171

Wage 0.0001 0.693 -0.0009 0.161

Wage Squared 0.0000 0.424 0.0000 0.391

Wealth 0.0043 0.060 -0.0026 0.517

Wealth Squared -0.00005 0.331 0.00006 0.553

Constant -0.3864 0.000 0.0372 0.529

*: Direct exit is the reference category.

Source: Authors’ calculations based on the Health and Retirement Study.

Table 7a

Marginal Effects from Multinomial Logistic Regression

Dependent Variable: Still on Wave 1 Job, Switched Jobs, or Direct Exit*

Sample: Male HRS Respondents Working in 1992

Remained on Wave One Job

Experienced at Least One Job 

Switch
marginal effect p-value marginal effect p-value

FTC Status

 No FTC Job in Work History ----- ----- ----- -----

 FTC Job in Work History 0.0420 0.012 0.0162 0.459

Age in 1992

 51-52 0.1302 0.003 0.2235 0.000

 53-54 0.0964 0.015 0.1251 0.012

 55-56 0.1061 0.009 0.0950 0.060

 57-58 0.0398 0.286 0.1351 0.006

 59-60 0.0094 0.807 0.0938 0.057

 61 ----- ----- ----- -----

Self Assessed Health

 excellent/very good 0.0347 0.012 0.0436 0.030

 good ----- ----- ----- -----

 fair/poor -0.0037 0.843 -0.1050 0.000

Spouse's Health

 excellent/very good 0.0035 0.789 0.0131 0.550

 good ----- ----- ----- -----

 fair/poor 0.0140 0.414 0.0114 0.695

College Degree -0.0015 0.921 0.0048 0.848

Race

 black 0.0027 0.848 -0.0054 0.816

 white ----- ----- ----- -----

 other 0.0572 0.080 0.0174 0.770

Married 0.0074 0.674 -0.0283 0.320

Children at Home 0.0288 0.048 0.1041 0.000

Spouse Employed -0.0112 0.403 -0.0205 0.358

Occpational Status

 blue collar/high skill -0.0314 0.181 -0.0126 0.700

 blue collar/other 0.0340 0.043 -0.0412 0.126

 white collar/high skill ----- ----- ----- -----

 white collar/other 0.0256 0.062 -0.0270 0.233

Health Insurance Status

 portable -0.0117 0.336 0.0154 0.450

 not portable -0.0326 0.115 0.0943 0.002

 none ----- ----- ----- -----

Self Employed 0.0843 0.000 -0.0586 0.040

Pension Status

 defined benefit 0.0296 0.051 -0.1405 0.000

 defined contribution 0.0455 0.010 -0.0864 0.000

 both -0.0193 0.586 0.1273 0.015

 none ----- ----- ----- -----

Own Home -0.0016 0.911 -0.0412 0.069

Wage 0.0003 0.676 -0.0004 0.506

Wage Squared 0.0000 0.393 0.0000 0.385

Wealth -0.0025 0.322 -0.0009 0.822

Wealth Squared 0.00005 0.408 0.00002 0.793

Constant -0.2763 0.000 -0.0550 0.421

*: Direct exit is the reference category.

Source: Authors’ calculations based on the Health and Retirement Study.

Table 7b

Marginal Effects from Multinomial Logistic Regression

Dependent Variable: Still on Wave 1 Job, Switched Jobs, or Direct Exit*

Sample: Female HRS Respondents Working in 1992

Remained on Wave One Job

Experienced at Least One Job 

Switch
Source: Authors' calculations based on the Health and Retirement Study.

0

10

20

30

40

50

60

70

80

90

100

1992 1994 1996 1998 2000 2002 2004 2006 2008

Percent working

Year

Figure 1a

Percent Working, by FTC Job Status, Men, 1992 - 2008

Sample: HRS Core Men Who Have Worked Since Age 50

No FTC job in work history

Had FTC job in work history
Source: Authors' calculations based on the Health and Retirement Study.

0

10

20

30

40

50

60

70

80

90

100

1992 1994 1996 1998 2000 2002 2004 2006 2008

Percent working

Year

Figure 1b

Percent Working, by FTC Job Status, Women, 1992 - 2008

Sample: HRS Core Women Who Have Worked Since Age 50

No FTC job in work history

Had FTC job in work history
Source: Authors' calculations based on the Health and Retirement Study.

0

10

20

30

40

50

60

70

80

90

100

1992 1994 1996 1998 2000 2002 2004 2006 2008

Percent working

Year

Figure 2a

Percent Working Part Time, by FTC Job Status, Men, 1992 - 2008

Sample: HRS Core Men Who Are Working in Each Wave

No FTC job in work history

Had FTC job in work history
Source: Authors' calculations based on the Health and Retirement Study.

0

10

20

30

40

50

60

70

80

90

100

1992 1994 1996 1998 2000 2002 2004 2006 2008

Percent working

Year

Figure 2b

Percent Working Part Time, by FTC Job Status, Women, 1992 - 2008

Sample: HRS Core Women Who Are Working in Each Wave

No FTC job in work history

Had FTC job in work history