SP6002_04_Moen 206..233

Limited Engagements? Women's and Men's Work/Volunteer Time in the Encore Life Course

Stage

Author(s): Phyllis Moen and Sarah Flood

Source:

Social Problems,

Vol. 60, No. 2 (May 2013), pp. 206-233

Published by: University of California Press on behalf of the Society for the Study of Social

Problems

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Limited Engagements? Women’sand

Men’s Work/Volunteer Time in the

Encore Life Course Stage

Phyllis Moen, University of Minnesota

Sarah Flood, University of Minnesota

Americans are living healthier and longer lives, but the shifting age distribution is straining existing and

projected social welfare protections for older adults (e.g., Social Security, Medicare). One solution is to delay retirement.

Another is an alternative to “total leisure” retirement—an “encore” stage of paid or unpaid engagement coming after

career jobs but before infirmities associated with old age. We draw on gendered life course themes together with data

from the American Time Use Survey (2003–2009) to examine the real time American men and women ages 50 to 75

apportion to paid work and unpaid volunteer work on an average day, as well as factors predicting their time

allocations. We find that while full-time employment declines after the 50s, many Americans allot time to more limited

engagements—working part time, being self-employed, volunteering, helping out—through and even beyond

their 60s. Caring for a child or infirm adult reduces the odds of paid work but not volunteering. While time working

for pay declines with age (though more slowly for men than women), time volunteering does not. Older men and

women in poor health, without a college degree, with a disability or SSI income are the least likely to be publicly

engaged. This social patterning illustrates that while the ideal of an encore of paid or unpaid voluntary, flexible,

and meaningful engagement is an emerging reality for some, it appears less attainable for others. This suggests the

importance of organizational and public policy innovations offering all Americans a range of encore opportunities.

Keywords: time use; older workers; encore; gendered life course; third age; retirement.

The twenty-first-century life course is being recast as a result of changes in demography,

the economy, and lifestyles. Scholars describe the appearance of two new life stages, a so-called

emerging adulthood throughout the 20s, where young people are able to experiment with various

adult roles (Arnett and Eisenberg 2007; Settersten and Ray 2010), and a so-called third age or

encore, coming after the first age of childhood and the second age of adult career and family build-

ing, but before the fourth age of infirmities associated with being old. We focus here on the third

age, a term first proposed by Peter Laslett (1987) to characterize an encore stage of ongoing

engagement in meaningful activities made possible by medical advances and lifestyle changes

improving population health and longevity (see also Gilleard and Higgs 2007; Karisto 2007;

McCullough and Polak 2007; Moen and Altobelli 2007; Sadler 2006; Silva 2008). It is defined as

the bonus years of healthy life expectancy, a period of later adulthood beyond career building,

when individuals are free to pursue meaningful engagement in education, paid work, volunteer-

ing for organizations, or other more informal forms of helping out (James and Wink 2007; Laslett

1989; Weiss and Bass 2002).

This research was made possible in part by the supportof the Minnesota Population Center at the University of Minnesota

(HD041023-01), funding for the Data Extract Builder of the ATUS (University of Maryland, R01 HD053654; University of

Minnesota, Z195701), the McKnight Foundation, and the Institute for Advanced Studies at the University of Minnesota. The

contents of this article are solely the responsibility of the authors and do not necessarily represent the official views of these

institutes and offices. We appreciate the assistance of Vincent Louis and Jane Peterson. Direct correspondence to: Phyllis

Moen, Department of Sociology, University of Minnesota, 909 Social Sciences, 267 19th Avenue S., Minneapolis, MN

55455. E-mail: phylmoen@umn.edu.

through the University of California Press’s Rights and Permissions website at www.ucpressjournals.com/reprintinfo/asp.

DOI: 10.1525/sp.2013.11120.

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The encore vision of mea ningfu l engagement contrasts with the convent ional view of

retirement as a one-way, one-time exit from full-time employment to full-time leisure. Both

social welfare and organizationa l policies (Social Security, Medicare, Medicaid, pensions,

retirement pa ckages ) were dev eloped in the second half of the twentieth century predicated

on the “leisure” model of retirement, with s ome people movin g into it at progress ively earlier

ages. But these policies and practices are increasingly probl ematic, out of step with the unrav-

eling of the social contract linking seniority with j ob and retirement security, along with the

aging of the population (Rubin 1996; Sweet and Meiksins 2013). Postponing the total leisure

of traditional retirement by encouraging those in their 50s and 60s to continue working full

time has been propo sed as a key strategy to deal with increasingly strained income and health

programs (Munnell and Sass 2008). But it is not clear that what Americans in later adulthood

want is to postpone exits from their full-time career jobs. We propose that many older Americans

are seeking more limited and flexible forms of public engagement as enc ore s, such as self- or part-

time employment and/or volunteering. However, like emerging adulthood, which is available

only to those whose parents can support their lengthening transition to adulthood, an emerg-

ingencoremayonlybes electively available to certain subgroups of Americans in their 50s, 60s,

and early 70s.

This study addresses two questions. First, how much time on an average day are Americans

ages 50 to 75 actually spending in public engagement (in terms of schooling, working, or volun-

teering), and how does this vary by age and gender? Second, what individual or family factors

predict different forms and amounts of public engagement in the encore years? We draw on a

gendered life course approach (Elder et al. 2003; Kim and Moen 2002; Moen 2001; Moen and

Spencer 2006), along with data from the nationally representative American Time Use Survey

(ATUS), to examine the real time older men and women in different age groups allocate to school-

ing, paid work, and two types of volunteering—formal civic engagement and informal “helping

out” of neighbors or friends (for distinctions between these two types of volunteer work see

Andersen, Curtis, and Grabb 2006; Musick and Wilson 2008; Wilson and Musick 1997). While

there is considerable evidence on the time allocated to housework and caring for children earlier

in the life course (e.g., Kending and Bianchi 2008; Wight, Raley, and Bianchi 2008), we know

little about how older Americans spend their time.

The Importance of Public Engagement

We define public engagement as participation in socially recognized roles involving interact-

ing with and often assisting individuals other than family members. The concept of productive,

active aging emphasizes the societal value of paid and volunteer work in the encore years, seeing

this age group as highly talented and highly motivated, an untapped source of human capital that

can be a key organizational and community resource for promoting the common good (Freedman

2011; Morrow-Howell, Hinterlong, and Sherraden 2001; Rowe and Kahn 1998).

How Americans spend their time during this life phase also matters for their health and well-

being. There is considerable research showing the health effects of engagement in paid work (Bird

and Rieker 2008; Luoh and Herzog 2002). But stressful job conditions can contribute to health

difficulties (Karasek and Theorell 1990), even for older adults who have since retired from their

career jobs (Wahrendorf et al. 2012). There is also evidence from studies using longitudinal

data showing positive effects of formal volunteering on well-being (Moen and Fields 2002;

Morrow-Howell et al. 2003; Thoits and Hewitt 2001), mental health (Li and Ferraro 2005,

2006), and longevity (Moen, Dempster-McClain, and Williams 1989; Musick, Herzog, and House

1999). More recent longitudinal research reaffirms earlier findings about the positive effects of

formal volunteering for older Americans’ cognitive and physical health (Thomas 2011) and lower

risks of mortality (Thomas 2012). Similarly, Emily Greenfield and Nadine Marks (2004) show that

volunteering has a protective effect on well-being, providing a sense of purpose in life for older

Limited Engagements? 207

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adults without other role-identities (partner, parent, employee), a finding also supported in a

recent German study (Pavlova and Silbereisen 2012).

Despite Laslett’s (1987, 1989) and others’ (Karisto 2007; Lawrence-Lightfoot 2009; Sadler

2006; Silva 2008; Weiss and Bass 2002) optimistic rhetoric about this period being a time of

opportunity, it is also defined as a social problem. Specifically, two demographic patterns—the

sheer numbers of Boomers (born 1946 through 1964) now moving through their 50s and

60s combined with increased healthy life expectancy—are challenging the fiscal systems under-

girding the rising costs of pensions, Social Security, and Medicare (Gendell 2008; Munnell and

Sass 2008; Pampel 1998; Shuey and O’Rand 2004). Contemporary older Americans also tend to

view these years as problematic because of two conflicting trends around retirement. On the

one hand, retirement remains embedded in established but now outdated social and organiza-

tional policies and practices that set retirement apart from unemployment as a work exit that can

be planned for, anticipated, and positively defined as a transition to total leisure (Costa 1998;

Graebner 1980). On the other hand, given that seniority is no longer accompanied by job security

(Kalleberg 2011), older employees often confront unexpected “early” exits through retirement

packages, buyouts, and forced layoffs (Appold 2004; Bidewall, Griffin, and Hesketh 2006; Hardy,

Hazelrigg, and Quadagno 1996) or else “delayed” retirements because of concerns about financial

security (Gendell 2008).

Simultaneously, there has been a legislative push to postpone the exit from paid work.

Federal policies, such as those prohibiting mandatory retirement and age discrimination, along

with delaying Social Security eligibility, have sought to make continued full-time employment

more attractive to or necessary for older adults (Johnson 2009; Munnell and Sass 2008). But

different pieces of legislation create mixed messages, further advancing the deinstitutionalization

of retirement. For example, pension policies limit employers’ ability to move their older employ-

ees to part-time or part-year arrangements, and there have been broad reductions in the provision

and nature of employer-sponsored pensions and health insurance (Hardy 2011; Hutchens 2007;

Shuey and O’Rand 2004).

Given the aging of the population, how those in later adulthood spend their time matters for

the sustainability of social welfare programs geared to this age group. If adults in the encore years

continue to work for pay, they contribute to the Social Security system rather than drawing from

it. And if they engage in activities promoting their health, the costs of medical care (Medicare

and Medicaid) will rise at slower rates. Examining the real time invested in market work and

volunteering by this age group is thus of pragmatic and policy as well as scientific value, in terms

of managing the rising costs of Social Security, pensions, and health care, tapping the talents and

skills of Boomers moving away from career jobs, and recognizing patterned disparities in the social

inclusion of Americans in the encore years (Bidewall et al. 2006; Ekerdt 2010; Munnell and Sass

2008; OECD 2006; Williamson 2011).

Given the deeply engrained total leisure model of retirement, public engagement in later

adulthood is often treated as a matter of personal choice (van Solinge and Henkens 2007),

which can lead to blaming unengaged individuals fo r their lack of productive activity. And yet

“choices” about public engagement are constrained by policies and practices that recruit

young people for entry-level positions and “prime age” adults in their 40s and ear ly 50s to fill

important leadership roles in organizations. While older adults may wan t to keep working,

start a new career, work less intensively in self-employment or part-time jobs, go back to

sch ool, or volunteer o n a regular b asis, existing ins titutional arrangements often make it diffi-

cult for them to do so. For example, most colle ges and un iversities are design ed to train stu-

dents in the 18 to 24 age range. And most entry-level jobs assume applicants will be in their

20s and early 30s. Even volunteer opportunities like Teach for America are geared for young

or “emerging” adults. As Carroll Estes, J. L. Mahakian, and Tracy Weitz (2001) observe, the

concept of productive aging “obfuscates what is a macro problem—a society that stigmatizes

and ‘throws away’ a particular age segment (and more) of its peop le—and redefines it as a

micro problem of individuals who are aging” (p. 194).

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The encore life stage may therefore reflect a new arena for inequality in the form of selective

social exclusion of some subgroups of older people from the public activities valued by society.

While we cannot establish definitively whether there is or is not a putative “third age” or “encore”

stage of the life course, we can examine the real time contemporary Americans approaching or

moving through the encore years (50s, 60s, and early 70s) allocate to roles and relationships that

extend beyond their family and friendship networks. We can also chart whether such time allo-

cations are socially patterned, in terms being unequally distributed across gender, age groups,

educational levels, and other markers of stratification.

Large segments of the contemporary older workforce are opting to retire from their primary

career jobs “early,” irrespective of traditional social norms or federal policies aimed at postponing

this status passage (Ekerdt 2004, 2010). Others are finding themselves “retired” unexpectedly,

through buyouts and layoffs in the face of a competitive global workforce (Rubin 1996; Sweet and

Meiksins 2013; Sweet and Moen 2012; Sweet, Moen, and Meiksins 2007). Some older workers

love their jobs and don’t want to retire, putting it off as long as possible (Hedge, Borman, and

Lammlein 2006; Johnson 2009). Marc Freedman (2007, 2011) suggests that growing numbers

want new, meaningful encores of public service. Still others find they can’t afford to retire, and

can’t envision a time when they won’t have to be employed (Burr, Mutchler, and Caro 2007;

Johnson 2009; Mermin, Johnson, and Murphy 2007), rendering the encore vision of voluntary

meaningful engagement marginal to the realities of their lives. But half of contemporary Ameri-

can men have exited the workforce by age 63, while half of contemporary American women have

done so even earlier, by age 61 (Warner, Hayward, and Hardy 2010). In the face of enormous

pressures from diverse governmental and corporate policy incentives and constraints both to exit

and to remain in the workforce, we expect considerable heterogeneity in the time spent in paid

work in the 50s, 60s, and 70s.

Employment is the dominant but not the only form of public participation. The notion of

service, of giving back to one’s community and of helping those less fortunate runs deep in

American culture (Musick and Wilson 2008; Wuthnow 1991). Such civic engagement as part of

religious or other organizations has provided the glue connecting citizens to their communities,

to their cities and states, to particular causes and interest groups, to a vision of the greater good,

and to one another (Putnam 2000; Skocpol 2003; Zukin et al. 2006). To what degree are older

Americans allocating time on the average day to schooling, paid work, formal volunteering, or

informal helping out of others? Conversely, to what extent are certain subgroups of Americans in

their50s,60s,andearly70snot publicly engaged?

We propose that public engagement during these years reflects both control over and constraints

narrowing options of late midlife adults as to how to spend their time. For example, most organi-

zational and governmental policies are designed around full-time employment or full-time retire-

ment (cf. Ekerdt 2010; Metlife 2009), with few options in between.

Factors Associated with Public Engagement

Different subgroups of Americans have different opportunities and face different constraints

during these transitional years. We draw on three life-course themes—biographical pacing, social

location, and linked lives—to promote understanding of who in the encore years is more likely to

spend time on an average day in different forms of public engagement.

Biographical Pacing

Biographical pacing refers to the timing and sequencing of roles over the life course, and is

directly related to the “problem” of an aging society. Should social and organizational policies

encourage older workers to postpone retirement from their career jobs? Or should governments

and organizations fashion alternative forms of public engagement as encores?

Limited Engagements? 209

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Biographical pacing also relates to the timing of paid work and unpaid volunteering. Harold

Wilensky (1961) theorized that both paid work and volunteering occur in tandem, especially for

those with “orderly careers,” such as educated, white men. Alternatively, volunteering may

replace paid work in the encore stage, a substitute for the loss of activities and identities associated

with career jobs. To see whether those engaged in market work are also more likely to allocate

time to volunteer activities on an average day, or whether volunteering occurs instead of, not

along with time devoted to paid work, we examine whether working during this age period

increases or reduces time spent volunteering and vice versa, recognizing their potentially recipro-

cal relationship (see also Butrica, Johnson, and Zedlewski 2009; Kahn, McGill, and Bianchi 2011;

McNamara and Gonzales 2011; Mutchler, Burr, and Caro 2003).

Social-Locational Contexts

Education, age, gender, race, health, and disability are ma rkers of life course inequality

(O’Rand and Henretta 1999), facilit ating or constraining the public engagement of different

subgroups of older Americans. Consider the effects of age. Helga Krüger (2003; see also

Biggart and Beamish 2003; Pampel 1998) uses the te rm life-course regime to underscore age-

graded institutionalized guidelines th at open up or close down opportunities as adults mo ve

through the encore years. What is not clear i s whether being older amplifies or reduces sub-

group disparities in public engagement. For example, does the time women and men allocate

to paid work or volunteering on an average day converge with age? Cumulative advantage/

disadvantag e theory proposes an amplifying process, with those advantaged earlier in life more

likel y to contin ue to be advantaged in the encore years (Dannefer 2011; O’Rand 1996;

Wilson, Shue y, and Elder 2007). A variant of cumulative advantage/dis advantage proposes

heightened disadvant age as a result of an accumulation of adverse risk factors (Ferraro,

Shippee, and Schafer 2009).

This is the first time in history that married women are retiring in large numbers, but most

come to this age period with lower occupational status than men and a history of intermittent

employment (Harrington Meyer and Herd 2007; Pleau 2010; Shuey and O’Rand 2004; Venn,

Davidson, and Arber 2011). Men’s traditional breadwinning roles in combination with women’s

checkered employment trajectories suggest that more men than women in their 60s spend time

working for pay.

Social class is another powerful force linked to opportunities and resources in later adulthood

(O’Rand and Henretta 1999), shaping how older adults allocate their time in the encore years.

College-educated adults are less likely to retire from full-time employment or from the workforce

altogether than are those with less education (Cahill, Giandrea, and Quinn 2006; Han and Moen

1999; Reitzes and Mutran 2004), and more likely to formally volunteer for an organization (Choi

et al. 2007; McNamara and Gonzales 2011). What is not clear is whether having a college educa-

tion means more time spent on the job or in volunteering.

Race and ethnicity may also shape time use in this encore period, with whites both better

positioned in the labor market and having more resources (health, education) than blacks,

Hispanics, or other minority groups (Thomas 1993; Thomas, Herring, and Horton 1994; Willson

2003), favoring greater time in paid work. Prior research (of adults of all ages) shows that whites

are more likely than other races/ethnicities to formally volunteer (Brown and Warner 2008;

Martin and Soldo 1997; Musick and Wilson 2008); they may also spend more time doing so.

Despite the vision of the encore years as a time of vitality, health difficulties are often atten-

dant with growing older. Poor health and disability are key contingencies pushing people out of

paid work (Cahill et al. 2006; Henretta, Chan, and O’Rand 1992; Kim and DeVaney 2005) and

limiting volunteering (Choi et al. 2007; McNamara and Gonzales 2011).

These observations lead to our first hypothesis about real time use on an average day.

Hypothesis 1: Individuals ages 50 to 75 most at risk of (1) age-related and other discrimination and

(2) not being able to meet existing demands of public engagement—women, as well as those who

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are older, less educated, minority, or in poor health—will be less likely to spend time working or

volunteering.

Linked Lives

The life course theme of linked lives points to the social embeddedness of individuals in

relationships (Elder et al. 2003). This encore period of the life course can involve the end of active

parenting and even marriage, as well as assuming care obligations for grandchildren and/or ailing

parents or other infirm relatives. Women are more likely to be the care providers for children,

grandchildren, and/or infirm relatives (e.g., Arber and Timonen 2012; Chesley and Moen 2006).

The growing numbers of dual-earner couples along with the growing population of older

singles (Lin and Brown 2012) underscore the importance of considering both the effects of marital

status and couple work status on the patterning of individuals’ time use. Since divorced or

widowed women are less likely than men to remarry (Schoen and Standish 2001) and thus must

rely on their own incomes (often with little or no pensions and lower amounts of Social Security;

see Harrington Meyer and Herd 2007), they may be more likely than married women to engage

in paid work. During the 50 to 75 age period, dual-earner couples engage in interdependent

processes involving two sets of labor market transitions, “his” and “hers” (Ho and Raymo 2009;

Kim and Moen 2001, 2002; Moen et al. 2006; Moen, Kim, and Hofmeister 2001). Spouses tend

to aim for joint retirements, though often in gendered ways, with married women molding their

retirement plans to those of their husbands (Moen, Sweet, and Swisher 2005). While it has been

established that older married women are less likely to work for pay (Warner et al. 2010), it is not

clear whether this is also the case for volunteering, or whether it is marriage or their spouses’

employment that predicts the time adults in the encore years spend working or volunteering

on an average day. Given traditional gender scripts (Ridgeway and Correll 2004), we propose:

Hypothesis 2: Being married and having a wife who is employed will increase the likelihood of men

ages 50 to 75 allocating time on an average day to paid employment and/or volunteer work.

By contrast,

Hypothesis 3: Third-age women married to employed husbands will be less likely than single women

to allot time to paid work on an average day.

Since volunteering (formal civic engagement and informal helping out) also conforms to gender

scripts, women—and especially wives—may be equally likely to volunteer regardless of their

husbands’ employment status. Prior research (Musick and Wilson 2008) suggests that being

married should increase formal volunteering for both men and women.

Research suggests that gender norms also complicate the relationship between caregiving

responsibilities and the timing of exits from paid work, such that having children at home and/or

caring for ailing family members increases the likelihood of men engaging in and spending more

time in paid work (as breadwinners) while decreasing women’s tendency to do so (Chesley and

Moen 2006; Dentinger and Clarkberg 2002). Men with children at home or caregiving responsi-

bilities may be more likely to delay their exits from full-time work due to their normative provider

role, while women have been shown to retire early to take care of ailing spouses (Dentinger and

Clarkberg 2002). Evidence suggests that caregivers are more likely than noncaregivers to be vol-

unteers (Burr et al. 2005; Choi et al. 2007; Hank and Stuck 2008), though whether caregiving

increases the actual time spent in formal or informal volunteering is unclear. Given prevailing

gender norms, we propose that:

Hypothesis 4: Caring for children at home, nonresidential grandchildren, parents, partners,

or other relatives decreases time women allocate to paid work on an average day, while it

increases time women allocate to volunteer activities (both formal civic engagement and infor-

mal helping out).

Limited Engagements? 211

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Data and Procedures

Drawing on data (2003 through 2009) from the American Time Use Survey (ATUS) linked to

the Annual Social and Economic Supplement (ASEC) of the Current Population Survey (CPS),

we examine both the likelihood of and the time spent in paid and volunteer work on an average

day by men and women ages 50 to 75, including, for comparison, younger (45 to 49) and older

(75 to 79) respondents. Using binary logistic, ordinary least squares, and zero-truncated negative

binomial regression, we estimate: (1) the distribution and heterogeneity of various forms of and

time spent in both employment and volunteering by age group and gender, and (2) how social-

locational markers (e.g., a college education, health, and disability) and social relations (linked

lives) predict the likelihood of and time spent in public engagement by women and men moving

into or through the encore life stage.

Data

The ATUS is a time diary study of a nationally representative sample of Americans (Abraham

et al. 2010). Respondents describe the activities they engaged in over a 24-hour period from

4:00 a.m. of a specified day until 4:00 a.m. of the following day, with different people interviewed

every day throughout the year. Reported activities are coded using a coding scheme of over

400 activity categories. The ATUS sample was selected from respondents to the (larger) CPS; one

person per household was surveyed. We match ATUS respondents to their earlier participation in

the March CPS (two to six months prior) to include measures of income sources, self-reported

health, and disability (King et al. 2010). Analysis weights for the subsample are adjusted accor-

dingly (ATUS-X 2010).

Dependent Variables

Our dependent variables capture (1) any engagement in paid work and volunteer activities

on the ATUS diary day (including the odds of no public engagement), and (2) the actual time

older Americans allocate to those activities during the 24-hour diary day. Only 1.2 percent of our

sample spent any time in educational pursuits (Appendix A details specific activities included),

making it impossible to estimate multivariate models of schooling. Paid work includes time spent

on work and work-related activities (see Appendix A) such as working at main or other jobs

and performing other income-generating activities on the diary day. Formal volunteering captures

activities for community organizations, including administrative duties as well as social services

such as serving food, collecting and delivering goods, and mentorship (see Appendix A for the

entire list of codes and activities). Informal volunteering (helping out) involves helping nonresident

adults (such as neighbors) by doing housework or home repair, providing transportation, and

other forms of assistance (see Appendix A). We differentiate informal volunteering from family

caregiving for adults and children since family caregiving is often less voluntary (see also Choi

et al. 2007). We define no public engagement as neither working for pay nor volunteering nor

engaging in educational activities on the diary day.

Independent Variables

We include indicators of the biographical pacing of employment, volunteer work (whether

being employed changes the odds of volunteering and vice versa), and educational activities, as

well as social-locational context (including health and disability), and linked lives (marital status,

spouses’ work status, caregiving). Employment status indicates whether respondents are working

full time, part time, are self-employed, or not working for pay (reference category). We recognize

that self-employment can be both full and part time. However, we distinguish self-employment

from other full-time and part-time employment for an organization because of the prevalence of

212 MOEN/FLOOD

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movement into self-employment during the transition to retirement (Zissimopoulos and Karoly

2007, 2009). Self-employment has been found to be more satisfying than organizational employ-

ment because it provides more autonomy, variety, flexibility, and job security (Hundley 2001).

Formal volunteering is a dichotomous measure that captures civic engagement for an organi-

zation and informal volunteering is a binary indicator of helping out of nonresident adults (such as

neighbors). Educational activities capture time spent in schooling or learning.

Social-locational context measures include gender, 5-year age groups (45 to 49 is the refer-

ence), self-reported health (representing combined response categories of good, very good, and

excellent versus a combined response of fair and poor health), and disability (whether respondent

reports a health condition that limits or prevents paid work). We include college degree (yes/no)

as a proxy for social class; we collapsed education categories to create a binary variable because

preliminary analyses did not reveal any major differences in time use among those with less than

a high school, only a high school degree or some college, or among those with only a college

compared to an advanced degree. We also consider economic context in terms of nonwage

income sources. Three binary variables indicate respondents’ sources of nonwage income, includ-

ing whether they receive a pension or retirement income from a previous employer or union,

excluding Social Security and Veterans’ Administration payments; Supplemental Security Income

(SSI) is defined as payments by federal, state, and local welfare agencies to low-income persons

regardless of work history who are age 65 or older, blind, or disabled; and Social Security (SS)

includes Social Security payments (pensions, survivors’ benefits, and permanent disability insur-

ance benefits); the reference category for each is none received. Note that identification of disabled

as a reason for not working typically attenuates with age, as individuals move into receiving

Social Security and begin defining themselves as “retired.”

Indicators of social relations capture the “linked lives” shaping involvement in paid and

unpaid volunteer work. We combine marital status and spouses’ employment to construct a

three-category independent variable, where “not married” is the reference category and respond-

ents who are married are distinguished by whether or not their spouses are employed. We also

include three dichotomous caregiving measures: (1) the presence of children under 18 in the home

(reference is no children under 18); (2) providing nonresident childcare;and(3)providingadult care

for an ailing (household or nonhousehold) adult. Controls not shown on our tables are survey

year and day of the week (weekend versus weekday).

Analysis

Our analytic strategy was to first model whether respondents engage in any paid work and

unpaid volunteer work on the ATUS diary day, and then estimate the number of minutes that

they spend in paid and unpaid volunteer work, conditional on that participation. We chose this

modeling strategy rather than a Tobit model or an OLS model with zeros included because we

theorize that participation in an activity is a process separate from the amount of time allocated

to the activity, which is more consistent with our approach (similar to the two-part model

proposed by John Cragg [1971]). Unlike many analyses of time diary data where there is almost

universal participation (such as parents’ time with children—most parents spend at least some

time with their children on an average day, meaning very few zeros in the data and thus a suitable

use of OLS models—see Kending and Bianchi 2008; Wight et al. 2008), we are analyzing activities

in which for each age group progressively fewer sample members are involved. Our decision

is further bolstered by evidence that estimates from two-part models are less biased than esti-

mates from Tobit models in cases such as ours, where there is interest in both the likelihood

of engagement and the time spent doing so (Daunfeldt and Hellstrom 2007; Stewart 2009).

In addition, models are estimated separately by gender, and this decision is generally supported

by model-level Chow tests; we also conduct variable-level Chow tests of gender differences, and

report where these tests are statistically significant (see Tables 2 and 3).

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Results: Engagement Patterns by Age Group and Gender

Table 1 describes the incidence of paid work and unpaid volunteer work of men and women

in the 50 to 75 age span, as well as five years pre- and post- these encore or third-age years.

The percent of men employed full time drops between ages 55 and 59 and 60 and 64, from 57 to

40 percent. It then drops markedly to 10 percent for those ages 65 to 69, underscoring the transi-

tional nature of the 60s. Only 8 percent of men age 70 to 74, and even fewer (5 percent) of those

ages 75 to 79, are employed full time. These trends suggest men’sexitsfromfull-time employment

follow the conventional model of retirement as occurring in the 60s.

However, significant numbers of men continue more limited engagements of paid work. For

example, part-time work is more prevalent among men in their 60s and early 70s (6 to 11 percent)

than among younger men. Over one in ten (12 to 14 percent) men in their 50s and 60s are self-

employed, dropping to under 10 percent among men in their 70s. Some men engage in formal

and informal volunteering throughout this age period; by ages 70 to 74 fully 10 percent of men

are formally volunteering and 9 percent informally helping out on an average day.

Women’s full-time employment is lower than men’s at all ages; just over 50 percent of

women 45 to 59 work full time, dropping to 28 percent for those ages 60 to 64, and further down

to less than 10 percent for women 65 and older. A relatively stable percentage (greater than

10 percent) of women in their 40s, 50s, and 60s engage in part-time work, though fewer (less

than 8 percent) women in their 70s work part time. Self-employment is less common for women

than men in the 50 to 75 range (12+ percent of men in their 50s and 60s versus less than 7 percent

of same age women). More women (8.9 percent) than men (4.8 percent) ages 60 to 64 formally

volunteer on an average day; and more women than men in their 50s and early 60s tend to

provide informal help to others.

Nearly one quarter or more of men and women in their late 50s through early 70s are active

in some form of limited public engagement. This point is key to the encore concept: while full-

time employment does indeed decline sharply over this age period, significant numbers are partic-

ipating in some form of public engagement. Turning to real time allocations

on an average day,

we find that while time in paid work declines with age, time spent volunteering varies between

about 1.5 and 2.5 hours per day for men and women 50 to 75, with no clear age pattern. Full-time

employed men spend an average of eight or more hours per day in paid work, except among 70

to 74 year olds who average 402 minutes (6.7 hours) of full-time work. Men employed part time

work 4 to 6 hours a day, with no pronounced drop off at older ages. Self-employed men ages 45 to

64 work about eight hours per day, while self-employed men ages 65 and older put in “part-time”

hours. Self-employed women work about 6 hours per day through their 60s, dropping to an

average of about 3 hours per day among women in their 70s.

Among those who volunteer (either formally or informally), there are few statistically signif-

icant gender differences in time allocated to these forms of public engagement on an average day.

Men and women volunteering for community organizations spend about 1.5 to 2.5 hours per day

doing so; those who informally help out do so for around an hour per day.

Results: Predicting Public Engagement

Who Works and Volunteers in their Encore Years?

Table 2 shows results for men and women separately from binary logit models predicting the

likelihood of Americans in their 50s, 60s, and 70s being engaged on any given day in paid work,

formal volunteering, and informal helping out, as well as the odds of their having no public

1. While we reference means in the text, there is considerable variability around the means (see high standard devia-

tions) in the time third agers allocate to paid work and unpaid volunteer work.

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Table 1 • Means/Percentages of Selected Characteristics by Age Group and Gender, ATUS 2003–2009

Men ( N = 5,847) Women ( N = 7,491)

Pre-Third Third Age: 50–75 Post-Third Pre-Third Third Age: 50–75 Post-Third

45–49 50–54 55–59 60–64 65–69 70–74 75–79 45–49 50–54 55–59 60–64 65–69 70–74 75–79

Mean/% Mean/% Mean/% Mean/% Mean/% Mean/% Mean/% Mean/% Mean/% Mean/% Mean/% Mean/% Mean/% Mean/%

Biographical pacing

Employment status

Full time 67.98 66.44 56.96 39.36 10.06 8.11 5.41 54.40* 53.05* 44.46* 28.44* 9.89 3.66* 1.10*

Minutes in paid

work

500.67 496.05 494.06 500.68 484.93 402.05 523.92 461.43* 454.99* 455.89* 462.33

†

458.11 456.50 454.82

†

(sd) (172.63) (186.22) (172.54) (184.63) (169.87) (216.27) (101.14) (148.50) (178.76) (167.32) (171.91) (150.87) (151.62) (59.71)

Part time 3.48 2.88 4.65 5.90 11.48 7.11 6.57 13.15* 14.45* 12.85* 12.43* 11.32 7.66 2.38*

Minutes in paid

work

369.60 387.34 283.93 358.28 295.55 280.74 289.65 368.00 359.78 346.89 322.57 294.07 275.97 304.71

(sd) (166.73) (168.96) (162.52) (164.27) (192.81) (105.22) (136.88) (169.65) (148.12) (161.44) (153.16) (152.63) (134.63) (104.22)

Self employed 14.21 12.20 13.96 13.03 11.73 7.73 5.12 8.06* 6.39* 6.55* 6.70* 4.05* 2.20* 1.77*

Minutes in paid

work

515.75 504.13 491.63 466.58 340.35 394.66 205.50 398.54* 422.38

†

363.83* 345.65* 355.93 176.43* 193.53

(sd) (227.03) (211.13) (181.09) (240.86) (215.84) (194.35) (143.30) (226.66) (251.21) (214.94) (242.21) (323.24) (121.91) (196.23)

Not employed 14.33 18.49 24.43 41.72 66.73 77.06 82.90 24.40* 26.11* 36.14* 52.43* 74.74* 86.48* 94.75*

NILF: retired

.00 2.18 8.76 24.81 53.82 69.52 78.03 .00 4.02

†

9.90 34.17* 60.59* 78.40* 87.52*

NILF: disabled

6.49 8.78 8.87 10.58 6.41 2.66 1.77 6.62 8.08 11.58 7.56

†

5.59 3.76 2.28

NILF: other

7.84 7.53 6.80 6.33 6.50 4.87 3.10 17.78* 14.00* 14.66* 10.70* 8.57 4.32 4.94

% any paid work on diary

day

61.94 61.14 54.46 43.55 22.90 19.15 10.55 52.03* 50.69* 40.89* 34.71* 16.65* 10.28* 3.35*

Minutes in paid

work

497.55 490.24 481.50 468.65 380.81 341.06 337.55 435.75* 433.70* 420.75* 405.08* 372.67 312.51 298.88

(sd) (186.35) (196.53) (180.73) (209.06) (213.42) (196.44) (189.25) (169.21) (186.59) (182.81) (195.52) (206.85) (177.75) (164.32)

Volunteer work

Formal (yes) 6.74 6.16 7.09 4.84 9.33 10.28 7.71 7.24 8.24 6.95 8.91* 7.63 9.48 10.33

Minutes formally

volunteered

157.39 142.24 87.31 168.73 135.54 163.96 169.98 103.22* 133.70 98.70 130.44 117.28 134.41 140.13

(sd) (167.93) (125.09) (77.71) (161.57) (141.99) (149.19) (150.24) (117.97) (159.74) (92.90) (111.38) (107.81) (130.02) (126.31)

(continued )

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Table 1 • Means/Percentages of Selected Characteristics by Age Group and Gender, ATUS 2003–2009 (Continued)

Men ( N = 5,847) Women ( N = 7,491)

Pre-Third Third Age: 50–75 Post-Third Pre-Third Third Age: 50–75 Post-Third

45–49 50–54 55–59 60–64 65–69 70–74 75–79 45–49 50–54 55–59 60–64 65–69 70–74 75–79

Mean/% Mean/% Mean/% Mean/% Mean/% Mean/% Mean/% Mean/% Mean/% Mean/% Mean/% Mean/% Mean/% Mean/%

Informal (yes) 7.98 7.48 7.14 7.08 6.86 9.37 5.40 7.95 12.14* 10.37* 10.94* 9.64 8.38 8.91*

Minutes informally

volunteered

82.99 77.77 68.03 44.67 72.94 68.82 71.22 49.81

†

37.65* 56.30 5 2.38 44.49 41.13 43.41

(sd) (122.35) (97.26) (101.42) (64.05) (88.03) (104.41) (93.26) (89.35) (64.97) (96.90) (74.78) (96.89) (68.40) (84.18)

Educational activities (yes) .96 1.29 1.13 .33 .64 .82 .30 1.85 1.67 1.94 1.18 1.46 1.38 .68

Minutesineducational

activities

221.82 144.86 116.70 174.71 131.11 61.09 159.71 184.72 175.94 159.29 82.90 124.60 59.93 96.29

(sd) (218.23) (125.23) (89.63) (220.80) (110.08) (16.18) (261.40) (147.63) (157.06) (126.85) (55.36) (106.07) (53.66) (63.85)

Any public engagement

87.79 83.12 78.62 64.23 44.06 38.27 27.42 79.47* 79.08* 68.93* 59.09

†

38.50

†

27.94* 22.62

Any less than full-time

public engagement

19.81 16.68 21.67 24.88 34.00 30.16 22.02 25.07* 26.03* 24.47 30.64* 28.61

†

24.28

†

21.51

No public engagement

11.65 16.60 20.84 35.71 55.61 61.49 72.31 19.84* 20.36

†

30.82* 40.25 60.38 70.98* 77.00

Social location

Health

Self-reported good/

excellent (CPS)

88.88 84.96 82.99 75.68 72.78 73.65 70.35 87.83 85.56 79.98 80.46* 75.76 72.08 68.74

Work disability (yes) 8.43 10.27 12.57 19.25 16.65 17.09 18.53 7.85 10.98 13.99 15.28

†

18.53 17.53 25.34*

Social class

College degree (yes) 31.26 31.30 32.68 34.15 29.41 29.63 26.14 30.71 32.20 27.67* 25.03* 18.82* 14.85 18.20*

Race

White 73.70 75.18 77.38 81.63 79.45 82.13 82.97 70.44 74.57 76.57 78.91 79.76 83.20 81.13

Black 11.39 12.03 10.19 10.19 10.15 9.78 7.30 14.46

†

13.17 12.61 9.30 10.73 9.27 11.00*

Hispanic 11.28 8.08 8.62 6.21 6.75 4.52 7.98 10.58 7.90 6.90 8.03 6.66 6.44 4.64

†

Other 3.63 4.71 3.81 1.97 3.65 3.57 1.75 4.52 4.35 3.93 3.76* 2.86 1.09* 3.23

Nonwage income sources (CPS)

Retirement (Pension) 1.40 3.44 11.55 25.32 39.47 43.43 46.51 1.14 2.14 7.03* 15.61* 24.22* 24.06* 30.01*

SSI 3.14 1.96 1.67 2.90 1.26 .88 1.09 2.29 2.54 2.61 3.90 3.43* 2.45* 4.40*

SS 3.21 5.08 7.91 25.47 80.56 89.32 93.98 3.02 5.94 8.06 28.59 77.49 90.53 91.47

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Linked lives

Marital status-spouse’s

employment

Married, spouse

employed

48.45 48.34 50.43 39.69 26.21 13.74 10.68 57.66* 56.48* 46.17 31.53* 16.85* 10.13 3.50*

Married, spouse not

employed

20.61 22.31 24.64 35.29 51.07 59.13 56.90 10.80* 11.41* 20.66 32.33 39.95* 44.18* 38.22*

Not married 30.95 29.36 24.93 25.03 22.72 27.13 32.42 31.54 32.10 33.17* 36.14* 43.20* 45.69* 58.28*

Children under 18 in the

home (yes)

49.24 28.90 14.20 8.12 4.25 4.56 5.13 43.96* 24.02* 12.41 7.15 5.02 3.93 2.40

†

Nonresident child care (yes) 3.69 3.82 4.00 4.20 4.73 3.94 2.46 5.83* 8.09* 7.84* 12.12* 11.78* 7.98* 4.15

Adult care (yes) 2.46 1.89 2.97 3.11 3.66 1.67 3.43 3.91 6.30* 4.75 7.57* 5.82 5.50* 6.65

†

N of observations 1,363 1,194 1,002 827 591 470 400 1,561 1,414 1,191 1,120 795 710 700

Source:Authors’ calculations using the 2003–2009 American Time Use Survey (ATUS).

Of the entire sample.

Of those who engaged in the activity.

Public engagement here includes paid work, unpaid formal and informal volunteering, and educational activities.

Less than full-time engagement here includes part time and self-employment, formal and informal volunteering, and educational activities.

No public engagement here means no engagement in paid work, formal or informal volunteering, or educational activities.

*Age-specific t-test of mean/% for women compared to men significant (p <.05).

†

Age-specific I-test of mean/% for women compared to men significant (p <.10).

Notes: Means are weighted; sample sizes are not. Standard deviations in parentheses.

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Table 2 • Odds Ratios and Log Odds from Binary Logit Models: Paid Work, Formal Volunteering, Informal Volunteering, and No Public Engagement

by Gender, ATUS 2003–2009

Men Women

Paid Work

1,2

Formal

Volunteering

Informal

Volunteering

No Public

Engagement

1,2

Paid Work

Formal

Volunteering

Informal

Volunteering

No Public

Engagement

OR β OR β OR β OR β OR β OR β OR β OR β

Biographical pacing

Third age

50–54 1.02 .02 .95 −.05 .88 −.13 1.46 .38* .96 −.04 1.16 .15 1.42 .35* 1.03 .03

55–59 .81 −.21 1.08 .08 .75 −.29 1.73 .55** .64 −.45*** .99 −.01 1.11 .10 1.75 .56***

60–64 .77 −.26 .71 −.34 .70 −.36 2.41 .88*** .64 −.45*** 1.21 .19 .94 −.06 2.13 .75***

65–69 .58 −.54* 1.90 .64* .56 −.59* 2.65 .97*** .40 −.91*** .99 −.01 .67 −.40 3.31 1.20***

70–74 .52 −.65* 2.18 .78* .82 −.19 3.02 1.10*** .28 −1.27*** 1.30 .26 .55 −.61* 4.81 1.57***

Post-third age

75–79

.30 −1.21*** 1.84 .61 .44 −.82* 4.33 1.46*** .08 −2.53*** 1.49 .40 .58 −.54 6.51 1.87***

Employment status

Full time — .54 −.61** .77 −.26 ——.68 −.39* .79 −.24 —

Part time — .73 −.31 1.48 .39 ——.95 −.05 1.02 .02 —

Self employed — .73 −.31 .72 −.33 ——1.12 .11 1.01 .01 —

Volunteer work

Formal (yes) .75 −.29 — 1.60 .47* — .92 −.08 — 1.43 .36 —

Informal (yes) .54 −.61*** 1.59 .46 ——.68 −.39** 1.42 .35 ——

Educational activities (yes) .70 −.36 .49 −.72 ——.52 −.65 1.01 .01 ——

Social location

Health

Good/excellent (CPS) 2.24 .81*** .93 −.07 1.20 .18 .47 −.76*** 1.54 .43** 1.55 .44* 1.18 .16 .51 −.67***

Work disability (yes) .23 −1.49*** .62 −.47 1.10 .10 4.03 1.39*** .34 −1.08*** .84 −.18 .86 −.15 3.15 1.15***

Social class

College degree (yes)

1.64 .49*** 2.38 .87*** 1.02 .02 .59 −.53*** 1.27 .24** 1.96 .67*** 1.17 .16 .61 −.49***

Race

Black

.72 −.33** .73 −.31 .92 −.08 1.48 .39** .91 −.09 .96 −.04 .80 −.22 1.03 .03

Hispanic

1.31 .27* .52 −.66* .78 −.25 1.10 .09 .84 −.18 .68 −.38 .77 −.27 1.59 .46***

Other 1.12 .11 .61 −.49 1.27 .24 1.00 .00 1.18 .16 .88 −.13 .61 −.50 1.07 .07

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Nonwageincomesources

Retirement (pension)

.40 −.92*** .98 −.02 1.15 .14 2.37 .86*** .56 −.57*** 1.11 .10 1.23 .20 1.58 .46***

SSI .20 −1.61** .19 −1.66** .33 −1.10 5.72 1.74*** .20 −1.60** .71 −.34 .46 −.78* 4.09 1.41***

F,N

.26 −1.33*** .54 −.62* 1.24 .21 3.69 1.31*** .28 −1.26*** 1.08 .08 1.34 .30 2.15 .76***

Linked lives

Marital status-spouse’s

employment

Married, spouse

employed

W,F,N

1.23 .21 2.14 .76*** 1.00 .00 .61 −.49*** .65 −.43*** 1.30 .26 .79 −.23 1.28 .25**

Married, spouse not

employed

W,I,N

.86 −.15 1.85 .62** .56 −.59*** 1.03 .03 .48 −.72*** 1.38 .32* .97 −.03 1.89 .64***

Children under 18 in the

home (yes)

W,N

1.06 .06 1.28 .25 .68 −.38* .90 −.11 .68 −.39*** 1.13 .13 .71 −.34* 1.54 .43***

Nonresident child care (yes) .61 −.49* 1.32 .28 1.22 .20 1.41 .34 .45 −.81*** 1.38 .32 1.62 .48** 1.11 .11

Adult care (yes) .34 −1.07*** 1.02 .02 2.43 .89** 1.07 .07 .65 −.43* 1.01 .01 2.18 .78*** 1.11 .10

Constant −1.29*** −2.89*** −1.73*** −1.85*** −.97*** −3.17*** −2.15*** −1.27***

Model fit

F-test/likelihood ratio

chi-square

31.04*** 5.44*** 3.28*** 31.03*** 30.71*** 3.93*** 3.22*** 38.31***

df 30 32 32 27 30 32 32 27

Total observations 5,847 5,847 5,847 5,847 7,491 7,491 7,491 7,491

Source:Authors’ calculations using the 2003–2009 American Time Use Survey (ATUS).

Estimated models differ without constant based on Chow test (p <.05).

Estimated models differ with constant based on Chow test (p <.05).

W,F,I,N

Estimated coefficients differ by gender based on Chow test (p < .05) in work model (W), formal volunteering model (F), informal volunteering model (I), or nonengagement model (N).

Notes: Reference categories are ages 45–49, not working for pay (in formal/informal volunteer models), not a formal volunteer (in paid work and informal volunteer models), not an informal volunteer (in paid work

and formal volunteer models), no educational activities (in paid work, formal/informal volunteer models), less than a college degree, does not receive retirement income, does not receive SSI, does not receive SS,

white, fair/poor health, no work disability, not married, no children under 18 in the household, not giving adult care, not providing care to non-resident children, 2003, weekend interview.

* p < .05 ** p < .01 *** p < .001 (two-tailed tests)

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engagement. An odds ratio greater than 1 means a greater likelihood, while an odds ratio less than

1 means a lower likelihood of time engaged in an activity on an average day, compared to the

reference group. We expected to find social patterns in engagement, with women as well as those

who are older, in poor health, and less educated less likely to spend time working or volunteering

(Hypothesis 1). Considering first age, we find that while working for pay is lower among older

men and women, formal volunteering is not. Net of other factors in the model, men ages 65 to

69 have almost double the odds (1.9) of formally volunteering for civic organizations than men

ages 45 to 49, even as they have lower odds of engaging in paid work (.58) or informally helping

out neighbors and friends (.56). Moreover, men in their early 70s are over twice as likely (2.18) to

formally volunteer as are those ages 45 to 49. There are no significant age differences in formal

volunteering among women, nor are there age-related patterns in either men’sorwomen’s

informal volunteering.

As expected (Hypothesis 1), good health increases the odds of men and women engaging in

paid work (2.24 and 1.54, respectively) and increases women’s odds of formal volunteering by

55 percent. Having a work-related disability considerably reduces the odds of paid work (.23 for

men and .34 for women). However, neither health nor disability is significantly associated with

the odds of men or women formally or informally volunteering.

Having a college degree increases the odds of both men and women in the encore years

spending time in paid work (1.64 and 1.27, respectively), though the effects are stronger for

men than women (as indicated by Chow tests). A college education also doubles the odds of

men and women formally volunteering. Receiving nonwage income (pension, SSI, Social Secu-

rity) reduces men’s odds of working for pay or volunteering for an organization, but not their

informal helping out. Nonwage income also reduces the odds that women work for pay, but not

their formal volunteering. Black men have lower odds and Hispanic men have higher odds of

paid work compared to white men. Hispanic men have lower odds of formal volunteering than

white men, while race/ethnicity is not associated with women’s paid or volunteer work on an

average day.

We hypothesized that the ways in which men’s and women’s lives are linked to those around

them affect their public engagement (Hypotheses 2 and 3). In support of Hypothesis 2, married

men are more likely to engage in paid work than singles. Compared to single men, those with

employed wives have double the odds (2.14) of formally volunteering, as do men with non-

employed wives (OR 1.85), suggesting that marriage rather than their wives’ employment status

promotes men’s formal civic engagement. Conversely, men with nonemployed wives have about

half the odds (.56) of informally helping out neighbors and friends. There are, as expected, reverse

effects of husbands’ employment for women’s paid work (Hypothesis 3). Married women have

lower odds of engagement in paid work than unmarried women, while women whose husbands

are not employed have higher odds (1.38) of formally volunteering. Chow tests indicate that

the effects of having an employed spouse are indeed different in predicting men’s and women’s

paid work and volunteering on an average day.

We anticipated that women with caregiving responsibilities would be less likely to be engaged

in paid work but more likely to volunteer (Hypothesis 4). We find that nonresidential (grand)child

and adult caregiving responsibilities do indeed depress women’s engagement in paid work com-

pared to other women (.45 and .65, respectively). And, though not hypothesized, men who care

for nonresidential children (most likely grandchildren) and/or provide care for ailing relatives also

have lower odds engaging in paid work (.61 and .34). Women with children under age 18 in the

home have lower odds of working (.68), while having children at home does not predict men’s

participation in paid work.

Contrary to our expectations, men and women with children at home or with other

caregiving responsibilities are not more likely to formally volunteer. However, as hypothesized for

women (Hypothesis 4), we find that caring for an infirm adult doubles both men’s and women’s

odds of informally helping out friends and neighbors (2.43 and 2.18, respectively). By contrast,

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having children at home is negatively associated with the odds that men (.68) and women (.71)

informally help out neighbors and friends on any given day.

There appears to be a trade-off between full-time employment and formal volunteering.

Full-time workers have lower odds of formally volunteering (.54 for men, .68 for women). By

contrast, part-time work and self-employment have no significant association with either formally

volunteering or informally helping out for women or men.

While engagement in full-time employment is a story of declining participation with age,

men’s formal volunteer work follows a different life course rhythm. Specifically, we find higher

odds of men in their late 60s and early 70s formally volunteering (compared to men ages 45 to 49).

By contrast, we find no evidence of women’s formal volunteering changing with age. Nor do we

find clearly patterned age differences in informal volunteering for either women or men.

Who is Excluded from Public Engagement?

Thus far we have examined engagement in different types of public activities; we now ana-

lyze who does not participate in schooling, paid work, or volunteering. As expected (Hypothesis 1),

we find that age is associated with higher odds of nonengagement for encore men and women

compared to those 45 to 49. A college degree and good health are protective against nonengage-

ment, while having a work disability quadruples (4.03) the odds of men’s, and triples (3.15) the

odds of women’s, nonengagement. Black men and Hispanic women are less likely to be publicly

engaged. For women, being married and having children or grandchildren under 18 in the home

limits engagement, while men who are married with employed wives have higher odds of public

engagement (1.64). Overall, the patterns of nonengagement do indeed follow the fault lines of

gender, health, race/ethnicity, and social class, reinforcing the notion that public engagement is

not equally distributed across the older adult population.

Results: Predicting Time Spent Working and Volunteering

Table 3 shows multivariate estimates of minutes spent in paid work and unpaid volunteer

work on the ATUS diary day among men and women engaging in them. OLS models are specified

except for the case of women’s informal volunteering where we show marginal effects from zero-

truncated negative binomial models.

We theorized (Hypothesis 1) and find that those older

Americans who are publicly engaged allocate progressively less time with age to paid work compared

to those ages 45 to 49. Men (ages 45 to 49) spend about 6.5 hours per day in paid work; men still

working for pay in their late 60s and 70s spend nearly two hours less per day, net of other controls

in the model. Working women in their 70s spend about 90 fewer minutes on the job (see Table 3)

than do working women in their late 40s.

Hypothesis 1, predicting less public engagement at older ages, does not hold for time spent in

either formal or informal volunteering. But negative associations between time spent in paid work

and time volunteering suggest trade-offs between these forms of engagement. Men spend

2. The OLS model for women’s informal volunteering fit poorly (F =1.08,df = 32). For this reason, we estimated a zero-

truncated negative binomial model (ZTNB), which provided an acceptable fit to the data. To interpret the results, we show the

marginal effects and accompanying standard errors that were generated using the Stata mfx command. We also fit ZTNB

models for each dependent variable to address possible effects of over dispersion, finding that differences compared to OLS

estimates were minimal and that OLS estimates were generally conservative. To examine whether the coefficient estimates

were sensitive to potential outliers, we estimated each OLS and ZTNB model with dependent variables Winsorized at the 90th,

95th, and 99th percentiles, where values above the 90th, 95th, and 99th percentiles on the dependent variables are re-

assigned to the values associated with those percentiles, respectively (Dixon and Yuen 1974). The results presented are quali-

tatively similar when we include the extreme values, suggesting that the relationships we observe are not the result of outliers.

Limited Engagements? 221

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Table 3 • Coefficients from Regressions: Minutes Spent in Paid Work, Formal Volunteering, and Informal Volunteering on the Diary Day by Gender, ATUS 2003–2009

Men Women

Paid Work

Formal Volunteering

1,2

Informal Volunteering

Paid Work Formal Volunteering Informal Volunteering

β SE β SE β SE β SE β SE Marginal Effect SE

Biographical pacing

Third age

50–54 −18.41 (12.53) −12.23 (25.42) −6.64 (15.83) 4.32 (11.17) 28.46 (20.34) −10.75 (8.21)

55–59

−30.26* (12.73) −73.94** (28.60) −28.06 (19.66) −17.92 (12.75) −3.57 (18.33) .03 (9.78)

60–64 −40.71* (16.10) −2.52 (35.82) −40.67* (17.23) −30.71* (15.39) 24.28 (23.35) −9.68 (9.42)

65–69 −116.90*** (30.91) −49.55 (43.32) −7.02 (23.49) −34.47 (29.74) 1.90 (30.36) −15.46 (12.71)

70–74 −135.28*** (39.14) −43.42 (53.78) −15.41 (26.59) −93.08** (34.21) 18.54 (29.53) −19.09 (14.01)

Post-third age

75–79 −137.66** (52.85) −54.24 (47.58) −19.28 (28.70) −95.64* (45.07) 17.16 (29.79) −6.37 (14.49)

Employment status

Full time ——−92.30*** (27.62) −4.81 (15.69) ——−46.14* (18.18) −6.03 (6.92)

Part time ——−81.67** (24.91) −15.93 (17.15) ——−34.27 (20.12) 12.16 (8.02)

Self employed

——−119.39*** (31.91) −33.59 (17.75) ——−28.60 (19.50) 14.02 (14.34)

Volunteer work

Formal (yes) −55.76** ( 20.60) ——−15.32 (15.82) −86.55*** (18.93) ——−13.44 (8.71)

Informal (yes)

−75.08*** (20.01) −57.14** (19.12) ——−86.00*** (16.84) −3.21 (14.41) —

Educational activities (yes) −118.57* (53.36) −72.9 2 (55.65) −58.78** (19.65) −59.11 (31.07) −62.41*** (18.69) −18.45 (13.48)

Social location

Health

Self-reported good/

excellent (CPS)

5.89 (20.66) −9.28 (31.78) 16.23 (14.17) −2.72 (16.14) 51.04** (17.69) −12.48 (10.04)

Work disability (yes)

−3.88 (26.11) −108.16*** (31.94) 6.45 (16.94) −50.32 (32.32) 4.72 (21.20) .68 (9.62)

Social class

College degree (yes) −31.82*** (9.28) −17.29 (17.17) −23.99* (10.23) −18.27 (9.66) −1.60 (11.42) −18.45 (13.48)

Race

Black −15.92 (19.13) −10.0 1 (31.58) −21.29 (19.33) 24.93 (13.36) 1.79 (16.61) −20.26** (7.62)

Hispanic .73 (15.13) 6.59 (34.72) 30.88 (25.09) 1.66 (14.57) 51.88** (18.52) −17.04 (15.22)

Other 36.78 (23.50) 67.67 (93.17) −23.55 (24.02) 43.01* (21.43) 48.10 (40.04) −5.70 (10.49)

Nonwage income sources

Retirement (pension) −9.12 (17.62) −48.1 4* (23.13) 8.86 (13.90) −17.90 (26.14) −3.41 (16.25) 2.94 (7.96)

SSI 28.68 (95.25) 11.54 (76.50) −35.37 (21.82) 63.18 (68.46) .12 (38.87) 4.92 (15.23)

SS −35.16 (32.58) 2.81 (36.37) −17.78 (18.20) −35.87 (24.57) −14.01 (15.99) 1.38 (7.77)

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Linked lives

Marital status-spouse’s

employment

Married, spouse

employed

W,F

18.47 (11.50) 25.56 (22.81) −.72 (14.19) −25.64** (9.68) −30.74 (15.71) −8.87 (6.63)

Married, spouse not

employed

W,F

26.20 (13.78) 22.75 (21.03) 5.13 (15.57) −24.47 (13.65) −40.16** (14.37) −4.35 (6.90)

Children under 18 in the

home (yes)

−24.45* (10.80) −26.10 (22.44) −23.51 (15.47) −25.72* (11.01) −13.11 (16.25) 3.48 (6.69)

Nonresident child care (ees)

−78.48*** (23.49) −97.86*** (19.59) −21.47 (17.42) −48.86* (21.33) −22.31 (16.19) −14.82 (8.41)

Adult care (yes) −67.15* (30.60) −3.82 (32.95) 1.46 (22.41) −89.55*** (27.15) −34.61 (24.12) 6.55 (6.36)

Constant 391.58*** (25.45) 272.41*** (49.34) 109.03*** (23.25) 361.29*** (23.31) 144.92*** (36.56)

Model fit

F 13.01*** 2.62*** 2.74*** 14.68*** 2.43*** 1.79**

df 30 32 32 30 32 32

Total observations 2381 416 495 2186 627 750

Source:Authors’ calculations using the 2003–2009 American Time Use Survey (ATUS).

Estimated OLS models differ without constant based on Chow test (p <.05).

Estimated OLS models differ with constant based on Chow test (p <.05).

Chow tests not conducted because male and female

models are specified differently.

W,F

Estimated coefficients differ by gender based on Chow test (p < .05) in work model (W), formal volunteering model (F).

Notes: Data shown for OLS models are regression coefficients with standard error in parentheses. Results for women’s informal volunteering are from a zero-truncated negative binomial model and show mar-

ginal effects with standard errors in parentheses. Reference categories are ages 45–49, not working for pay (in formal/informal volunteer models), not a formal volunteer (in paid work and informal volunteer

models), not an informal volunteer (in paid work and formal volunteer models), no educational activities, less than a college degree, does not receive retirement income, does not receive SSI, does not receive

SS, white, fair/poor health, no work disability, not married, no children under 18 in the household, not giving adult care, not providing care to nonresident children, 2003, and weekend interview.

* p <.05**p < .01 *** p < .001 (two-tailed tests)

Limited Engagements? 223

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less time volunteering if they are also doing any work for pay—whether full time, part time or

self-employed. For example, self-employed men spend two hours less volunteering for a civic

organization than those who do not work for pay. For women, only full-time work is associated

with less time volunteering (46 minutes). Similarly, employed men and women who formally

volunteer or informally “help out” spend at least an hour less working for pay (56 and 75 minutes

less for men and 87 and 86 minutes less for women, respectively).

Despite their greater tendency to work for pay, men college graduates in this life stage spend

less time in paid work, on average, compared to those with less education. Women in good health

spend nearly an hour more formally volunteering per day compared to women in poor health,

while men volunteers with a disability tend to put in roughly 1.5 hours less formally volunteering.

Disability status does not predict the time women in later adulthood allocate to volunteering for

an organization or helping out others. Hispanic women who volunteer for a community organi-

zation spend 52 minutes more doing so than white women volunteers.

Family relations are a major source of gender differences in the time older adults allocate to

paid work and formal volunteering. Being married limits the time women but not men apportion

to paid work and formal volunteering (supporting Hypotheses 2 and 3). Working wives of work-

ing husbands spend about a half hour less per day on the job than do unmarried working women.

Married women volunteers with nonworking husbands spend less time formally volunteering

than unmarried women (40 minutes less). Caregiving responsibilities are negatively associated

with time spent in paid work for men and women in this age group (Hypothesis 4 predicted this

only for women), ranging from 25 fewer minutes for working men and women who have chil-

dren under 18 in the home to about one hour less for workers who are caregivers for an infirm

adult or else a nonresident (grand)child (see Table 3).

Conclusions

Recall that we began by describing two new stages of the twenty-first century life course, an

emerging adulthood lasting to age 30, and an emerging third age or encore stage roughly between

ages 50 and 75. While the life stage of emerging adulthood has captured the imagination of many,

leading to concrete policy developments (such as permitting children to remain covered by their

parents’ health insurance through their mid-20s), policy responses to the encore life stage are less

clearly articulated.

Employers, policy makers, and older workers have operated under the assumption that

retirement from career jobs signals the cessation of public engagement and a turn to full-time

leisure. Is the aging of the population—as a result of medical advances promoting life expectancy,

lower fertility, and the aging of the large Boomer cohort—a social problem straining both health

and welfare programs and policies, or does it portend a new life stage of encore public engage-

ment? One alternative is to simply delay exits from career jobs by postponing ages of eligibility to

Social Security or Medicare. Another involves the facilitating of this new stage of the life course,

tapping the talents and experiences of adults in their 50s, 60s, and 70s in innovative types of

encore employment, training, and volunteer service as a way of tackling societal issues, containing

health care and Social Security costs, and promoting the health and well-being of those in this age

group.

This study makes four contributions to understanding the challenges of an aging workforce

and growing “retired” force, including the possibility of an encore life stage. First, our findings

underscore this phase of the life course as a time of transition out of paid work. Prior to the third

age or encore years, 86 percent of American men and 76 percent of American women (ages 45

to 49) in the ATUS are working for pay (Table 1). Beyond the third-age or encore years (at ages

75 to 79), fully 83 percent of men and 95 percent of women do not work, with 78 percent of men

and 88 percent of women in their late 70s saying they are “retired.”

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Second, these transitional years are also a time of ongoing public engagement. Our evidence

is that a significant portion of Americans in their 50s, 60s, and early 70s are allocating time to some

form of limited engagement in paid work or unpaid volunteering, although few are spending time

in educational activities. If something of a tipping point occurs when half the members of a group

are not spending time in an activity, the tipping age away from full-time work occurs remarkably

early—on average at age 59 for men and age 55 for women. However, the tipping point of less

than 50 percent of any combination of various forms of public engagement occurs at age 65 for

both men and women, fully seven and ten years later, respectively, than the tipping point away

from full-time employment (results not shown). There are no precipitous drops; significant pro-

portions of those in their 60s and early 70s remain involved in some public activity on an average

day. And there is a notable narrowing of the gap between men’s and women’s public engagement

across these years, especially in the absence of full-time work. The ability to capture differences in

various forms of public engagement (both likelihood and amount of time) for men and women at

different points in the third-age or encore years at the beginning of the twenty-first century is a

real strength of the ATUS data.

Third, we observe considerable variability in public engagement among those in the 50 to

75 age range, depending in large part on their ages and gender, as well as whether they have the

resources of a college degree and good health. Our evidence supports Hypothesis 1, that individ-

uals more at risk of not being able to meet the demands of, or else not having easy access to,

desirable forms of engagement—those who are older, in poorer health, and less educated—tend

to spend less time publicly engaged, especially in full-time work. Cumulative advantage theory

suggests (and we find) disparities in public engagement along the fault lines of gender and educa-

tion. For example, the tipping age away from full-time employment occurs at age 60 among

college-educated men versus age 59 for men without a college degree. For college-educated

women, the tipping age from full-time employment is 60, while it is age 55 for women without

a college degree. In terms of not allocating time to any form of public participation, declines are

evident for college-educated men and women beginning in the early 70s; for those without

college degrees, declines occur much earlier, in the mid-60s. However, a college degree and good

health matter more for whether older adults participate in paid work than for the time they spend

doing so, and even those with a health limitation are likely to help out others. But note that

disability status and poor health do not reduce the odds of men in this age group volunteering for

an organization, or the odds of men and women informally helping out friends and neighbors.

It could be that older men are engaged in organizations such as veterans’ groups where poor

health and disability are normative and may not serve as barriers to involvement, something

worth investigating in the future.

Fourth, our chronicling of different real time engagement patterns for men and women in

this stage of the life course illuminates the gendered ways in which family roles and relationships

continue to motivate and constrain public engagement. We anticipated this would be the case for

women caregivers, but find that men’saswellaswomen’s time in public engagement depends on

the nature of their ties with spouses, (grand)children, and infirm relatives. Marital status and, to

a lesser extent, caregiving responsibilities, are important sources of variation in men’sand

women’s time in public engagement. Being married generally decreases women’s engagement in

and time allocated to paid work, while marriage tends to promote men’s participation in formal

volunteering. Caregiving is negatively associated with participation in and time spent in paid

work. While having co-resident children (or grandchildren) is negatively associated with informal

helping out, other types of care activities promote it.

As hypothesized (Hypotheses 2 and 3), having an employed wife and being married

increases the likelihood that men in this age group are engaged in working and formally volun-

teering, while marriage reduces the odds that women work for pay. Providing care to an infirm

adult or to nonresident children reduces the time spent in paid work and, for men, in formal

volunteering.

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Limitations

There are, of course, important limitations to this investigation. Our estimates of engage-

ment in unpaid volunteer work are conservative, since we only know whether and how much

respondents volunteer on the ATUS diary day. Real time participation in paid work and

unpaid volunteering on the ATUS diary day are lower than rates based on questions with longer

reference periods. For example, while 34 percent of men age 65 to 69 in our sample are employed,

only 22 percent report engaging in paid work on the ATUS diary day. Similarly, according to

the 2005 CPS, fully one-third of Americans ages 45 to 54 report formally volunteering over the

last year, as do 30 percent of people ages 55 to 64 and one-quarter of those 65 and older (White

2006). By contrast, only about 10 percent of men and women ages 65 to 74 report volunteering

on the ATUS diary day (see Table 1).

To really capture the dynamics of public engagement requires longitudinal data on indivi-

duals over time. The absence of work and volunteer histories is a real handicap, meaning we can’t

capture continuity and change in participation over a week, a month, a year, or over the life

course.

We also face the confounding of age and cohort. Nearly all of the respondents in their 50s

(94 percent) and a third in their early 60s are Boomers, born between 1946 and 1964. Thus, some

of the age-related differences (such as educational attainment) reflect cohort differences; others

(such as health and receiving Social Security) reflect the effects of biological aging and social policy

regulations. We are unable with the data at hand to separate cohort differences from age differen-

ces in public engagement.

A key limitation: we cannot show the degree to which older Americans’ time allocations are

voluntary or involuntary, whether their time in paid work is in their long-term jobs or new

encores, or whether there is a portion of the nonengaged wishing to devote at least some time to

some form of publicly engagement. We presume that time spent in self-employment, formal

volunteering, and informal helping out occur more by choice than is the case for paid employ-

ment, though the motivations for pursuing less than full-time engagement are worth further

investigation.

But these data do show disparities in engagement that suggest processes of constraint as well

as choice. There may be more people in this age group wanting to remain engaged than actually

figure out ways of doing so, given age discrimination and labor market rigidities in terms of the

absence of institutionalized part-time or flexible alternatives to full-time employment (Blau and

Shvydko 2011). Earlier studies have documented a strong desire by older Americans to contribute

to the larger social fabric whether through paid or unpaid work (Metlife 2008). For example, a

survey by the Pew Research Center (2007) finds that 77 percent of current workers expect

to work for pay after retirement, while only 12 percent of current retirees are actually doing so.

Why is there such disparity between what people expect and their ability to achieve it? From this

perspective, the “social problem” may not be the aging of the population, but, rather, the absence

of institutionalized means of fostering older Americans’ participation in meaningful activities,

whether paid or unpaid.

Future Directions for Policy and Research

This study has important implications for reframing taken-for-granted schema in research

and policy development related to age-graded participation in schooling, as well as paid and

volunteer work. It points to the value of both studying and fashioning alternatives to the traditional

Hobbesian choice around retirement: either continued full-time employment in one’s career

job or else the full-time leisure of retirement. We show a sizable proportion of contemporary

Americans in this age group are spending their time in limited engagements of paid or unpaid

work, not extending their years of full-time employment or moving to full-time retirement.

But the bonus years of health and vitality producing an emerging encore life stage can only

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promote public engagement if those in this age group can find training options and jobs, paid

and unpaid, that are flexible and reduced in time commitments—opportunities that have yet

to be institutionalized and legitimized in either government or corporate policies and practices

(Blau and Shvydko 2011).

With the aging of the large Boomer cohort, life paths and opportunities in the encore life

stage will increasingly constitute a provocative and fertile agenda for research and policy. Dispar-

ities in social inclusion by gender, class, and age—as well as other social markers—are key issues

to be addressed. In light of current policies and practices, the promise of an encore of paid and/or

unpaid work may only be realized for those with a college degree, good health, and without

family-care obligations.

Appendix A • Activities included in Paid Work, Formal Volunteering,

Informal Volunteering: ATUS-X Codes and Labels

Code Label

Paid Work

050000 Work and work-related activities

050100 Working

050101 Work, main job

050102 Work, other job(s)

050103 Security procedures related to work

050104 Waiting associated with working (2004+)

050199 Working, n.e.c.

050200 Work-related activities

050201 Socializing, relaxing, and leisure as part of job

050202 Eating and drinking as part of job

050203 Sports and exercise as part of job

050204 Security procedures as part of job

050205 Waiting associated with work-related activities (2004+)

050299 Work-related activities, n.e.c.

050300 Other income-generating activities

050301 Income-generating hobbies, crafts, and food

050302 Income-generating performances

050303 Income-generating services

050304 Income-generating rental property activities

050305 Waiting associated with other income-generating activities (2004+)

050399 Other income-generating activities, n.e.c.

059900 Work and work-related activities, n.e.c.

059999 Work and work-related activities, n.e.c.

Educational Activities

060000 Education

060100 Taking class

060101 Taking class for degree, certification, or licensure

060102 Taking class for personal interest

060103 Waiting associated with taking classes

060104 Security procedures related to taking classes

060199 Taking class, n.e.c.

060200 Extracurricular school activities (except sports)

060201 Extracurricular club activities

060202 Extracurricular music and performance activities

060203 Extracurricular student government activities

(continued )

Limited Engagements? 227

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Code Label

060204 Waiting associated with extracurricular activities (2004+)

060299 Education-related extracurricular activities, n.e.c.

060300 Research or homework

060301 Research or homework for class (for degree, certification, or licensure)

060302 Research or homework for class (for personal interest)

060303 Waiting associated with research or homework

060399 Research or homework, n.e.c.

060400 Registration or administrative activities

060401 Administrative activities: class for degree, certification, or licensure

060402 Administrative activities: class for personal interest

060403 Waiting associated with administrative activities (education)

060499 Administrative for education, n.e.c.

069900 Education, n.e.c.

069999 Education, n.e.c.

Formal Volunteering

150000 Volunteer activities

150100 Administrative and support activities

150101 Computer use

150102 Organizing and preparing

150103 Reading

150104 Telephone calls (except hotline counseling)

150105 Writing

150106 Fundraising

150199 Administrative and support activities, n.e.c.

150200 Social service and care activities (except medical)

150201 Food preparation, presentation, clean-up

150202 Collecting and delivering clothing and other goods

150203 Providing care

150204 Teaching, leading, counseling, mentoring

150299 Social service and care activities, n.e.c.

150300 Indoor and outdoor maintenance, building, and clean-up activities

150301 Building houses, wildlife sites, and other structures

150302 Indoor and outdoor maintenance, repair, and clean-up

150399 Indoor and outdoor maintenance, building, and clean-up

activities, n.e.c.

150400 Participating in performance and cultural activities

150401 Performing

150402 Serving at volunteer events and cultural activities

150499 Participating in performance and cultural activities, n.e.c.

150500 Attending meetings, conferences, and training

150501 Attending meetings, conferences, and training

150599 Attending meetings, conferences, and training, n.e.c.

150600 Public health and safety activities

150601 Public health activities

150602 Public safety activities

150699 Public health and safety activities, n.e.c.

150700 Waiting associated with volunteer activities

150701 Waiting associated with volunteer activities (2004+)

150799 Waiting associated with volunteer activities, n.e.c. (2004+)

150800 Security procedures related to volunteer activities

150801 Security procedures related to volunteer activities (2007+)

150899 Security proecdures related to voluteer activities, n.e.c. (2007+)

(continued )

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Code Label

159900 Volunteer activities, n.e.c.

159999 Volunteer activities, n.e.c.

Informal Volunteering

040000 Caring for and helping nonhousehold members

040500 Helping nonhousehold adults

040501 Housework, cooking, and shopping assistance for non-household

adults

040502 House and lawn maintenance and repair assistance for non-household

adults

040503 Animal and pet care assistance for non-household adults

040504 Vehicle and appliance maintenance or repair assistance for non-

household adults

040505 Financial management assistance for non-household adults

040506 Household management and paperwork assistance for non-

household adults

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