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Understanding the Aging Workforce: Defining a Research Agenda (2022)

Chapter: 2 The Emerging Older Workforce

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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
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2

The Emerging Older Workforce

During the two-decade period between 2000 and 2020, the share of employed workers ages 60 and over has doubled among both men and women (Figure 2-1). Specifically, the percent of all employed men who are in that age range rose from 7.4 to 14.8 percent, while among all employed women it rose from 6.3 to 14.0 percent. Although most of this increase, in absolute terms, was due to a growing share of the workforce entering their early 60s, the percentage of employed workers in each five-year age group over age 60 either doubled or nearly doubled during this period. The percentage ages 80 and over plateaued in the late-2010s (Figure 2-1, bottom panels).

This aging of the U.S. workforce is due in part to the overall aging of the U.S. population. Since 2006, when the sizable Baby Boom generation began to reach age 60, the proportion of the population that is ages 60 and over has grown dramatically, while younger age groups have remained steady or declined, with most of the decline occurring among those under age 40 (Figure 2-2, upper panels) as birth rates have continued to fall (Hamilton et al., 2021). The share of the population that falls in each of the over-60 age groups has increased substantially since 2010 (Figure 2-2, lower panels), particularly among those ages 60–74.

U.S. Census Bureau (2018) population projections predict that the U.S. population will continue to age with the median age of the population, which it projects to increase from 37.9 years in 2016 to 42.9 years by 2060. According to these projections, the percent of the population that is ages 60 and over will also continue to increase (Figure 2-2, upper panels). However, the largest increase is projected to occur among those ages 80 and over (Figure 2-2, lower panels), among whom employment rates are very low.

The percent of the population ages 60–69, those in the 60-and-over age group that are most likely to be employed, is expected to decline after 2020, before rising again after 2040 as the large Millennial cohort begins to reach age 60. If employment rates remained steady at their 2020 levels in subsequent decades among those ages 60 and over, the share of the workforce that is ages 60 and over would begin to decline after 2025, but would again increase after 2040, largely mirroring the share of the population in the 60–69 age group.

In fact, the aging of the U.S. population has not been as rapid as the aging of the workforce, suggesting that it is not only shifts in the age of the population that have led to the increasing number of older workers. If employment rates had remained steady throughout the 2000s and 2010s, the percentage of the workforce that was ages 60 and older would not have increased as dramatically. Thus, changes in labor force participation at all ages have also contributed to the increasing average age of the U.S. worker. The combination of decreasing labor

Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×
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FIGURE 2-1 The age distribution of employed adults in the U.S. by gender, 2000–2020.
NOTE: Figure 2-1 shows the percent of employed adults that falls in each age group among men (left panels) and women (right panels).
SOURCE: Data from 2000–2020 March Current Population Survey Annual Social and Economic Supplement data files calculated by U.S. Census Bureau online data table tool (Beta version).

force participation rates among younger adults and increasing labor force participation rates at older ages has also contributed to the growing share of older workers (Figure 2-3). Over this same two-decade period, among both men and women participation fell among those under age 55 but increased among those ages 55 and over (Figure 2-3, middle and bottom panels).1 This means that even if the age distribution of the population had not changed during this period, older workers would have constituted a larger share of the workforce in 2019 than they had in 2000.

HOW TRENDS IN LABOR FORCE PARTICIPATION ARE GENDERED

Although these overall trends have been present among both men and women, the magnitude of the changes at younger and older ages, as well as their relative importance, has differed by gender. The decline in labor force participation between 2000 and 2020 that occurred at younger ages has been larger among men than among women; however,

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1 To demonstrate the long-term trends and exclude any potential effects of the COVID-19 pandemic, the changes over time in labor force participation use 2019 as an endpoint.

Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×
Image
FIGURE 2-2 The age distribution of the U.S. population by gender, actual (2000–2020) and projected (2020–2060).
NOTE: Figure 2-2 shows the percent of the U.S. population that falls in each age group among men (left panels) and women (right panels). The age distribution for the 2000–2020 period is based on the actual age distribution of the U.S. population during this period. The distribution for the 2020–2060 period is based on U.S. Census Bureau 5-year population projections; this period is represented by dashed lines. Since the population projections are based on projecting from the base year of 2016, both the observed and projected distributions for 2020 (the first projected year) are included in the figure to show any discontinuities between the actual and projected numbers.
SOURCE: Data from 2000–2020 March Current Population Survey Annual Social and Economic Supplement data files calculated by U.S. Census Bureau online data table tool (Beta version) and 2020–2060 U.S. Census Bureau (2018) Population Projections.

the increase in labor force participation at older ages has been more pronounced among women, particularly among those in their sixties. These gender differences are the result of overall lower labor force participation among women. This lower participation holds true especially among younger women during the years in which they are raising children, but it carries forward into older ages as well.

The pattern of lower labor force participation among older women (relative to older men) is not unique to the United States; in fact, the United States enjoys higher labor force participation among older women than many other countries (Figure 2-4, right panel). Though both U.S. men and women were more likely to remain in the labor force after age 65 than similarly aged men in many other countries, this was particularly true among women. This is because many of the Latin American countries that have higher labor force participation among men than the United States also have lower participation among women. The countries with the smallest absolute difference in labor force participation rates between men and women (Figure 2-5) also tend to be those with low

Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×
Image
FIGURE 2-3 Labor force participation rates (and change in rates) by gender and age group, selected years, 2000–2019.
NOTE: Figure 2-3 shows the labor force participation rate by age group and gender in selected years between 2000 and 2019 (top panels), as well as the absolute change in the labor force participation rate (middle panel) and the percent change in the labor force participation rate (i.e., the absolute change in the labor force participation rate divided by the 2000 labor force participation rate; bottom panel). This figure is restricted to the 2000–2019 period to demonstrate the long-term trends without the influence of the COVID-19 pandemic.
SOURCE: Data from 2000–2019 March Current Population Survey Annual Social and Economic Supplement data files calculated by U.S. Census Bureau online data table tool (Beta version).
Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×
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FIGURE 2-4 2019 labor force participation, adults ages 65 and over by country and gender.
SOURCE: Data from International Labour Organization (2021).

rates overall. For this reason, the gender gap in labor force participation among those ages 65 and over in the United States falls in the middle of the distribution of 34 countries shown in Figures 2-4 and 2-5. However, in the United States, labor force participation rates for men are only 33.5 percent higher than the rates for women. Of the 34 countries considered, only Norway (27.5% higher), Sweden (30.1%), and France (30.9%) have a smaller relative difference.

One of the most important demographic changes of the last half of the twentieth century in the United States was the dramatic increase in labor force participation among married women and women with children. This trend is reflected in the large increases in labor force participation at all ages across successive birth cohorts of women born between 1930 and 1954 (Figure 2-6, top right panel). Among cohorts born after 1955, these rates continued to increase when women were ages 25–34 but began to fall when they reached middle age. If these cohorts continue this pattern as they reach older ages, the growth in labor force participation at older ages may slow in the future among women. In contrast, the participation of younger men has declined modestly across cohorts, but remains near 100 percent (Figure 2-6, top left panel). It is not until after age 55, when men begin to leave the labor force in substantial numbers, that one begins to see larger changes in labor force participation among men.

Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×
Image
FIGURE 2-5 Gender difference in labor force participation (LFP) rates in 2019 by country.
NOTE: The left panel shows the absolute difference in rates. The right panel shows the difference as a percent of men’s labor force participation.
SOURCE: Data from International Labour Organization (2021).

EMPLOYMENT CHARACTERISTICS OF OLDER WORKERS

What type of jobs are older workers most likely to be employed in? Table 2-1 shows the percent of workers within each age group who are employed within each of 25 broad occupation groups defined by their two-digit standard occupation code. The six occupation groups in which the highest percentages of workers ages 50 and over were employed in 2019 (Table 2-1, Panel A) were:

  1. Management occupations;
  2. Office and administrative support occupations;
  3. Sales and related occupations;
  4. Transportation and material moving occupations;
  5. Education, training, and library occupations; and
  6. Production occupations.
Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×
Image
FIGURE 2-6 Labor force participation by age, gender, and birth cohort, ages 25–79.
NOTE: Figure 2-6 shows the average labor force participation rate within five-year age groups among men (top left panel) and women (top right panel) who are ages 25 and over for each five-year birth cohort born between 1930–1979, as well as the change in the labor force participation rate from the previous cohort among men (middle panel) and women (bottom panel). Following the method used by Goldin and Mitchell (2017), the average labor force participation rate is the average rate calculated from the five single-year ages for each of the five single-years of birth (25 values). More information on this calculation can be found in this chapter’s Annex.
SOURCE: Data from 1965–2020 March Current Population Survey Annual Social and Economic Supplement data files.
Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×

TABLE 2-1 Distribution of Workers across Occupation Groups by Age Group, 2004 vs. 2019

PANEL A Ages 50 and Over Ages 40 and Under
2004 2019 2004 2019
Occupation Group Rank % Rank % Rank % Rank %
Management Occupations 2 11.3 1 12.5 7 6.1 5 7.2
Office and Administrative Support 1 15.7 2 12.0 1 14.8 2 10.1
Sales and Related 3 11.3 3 9.4 2 12.9 1 11.2
Transportation and Material Moving 6 6.3 4 7.9 6 6.3 4 8.0
Education, Training, and Library 5 6.9 5 6.6 8 4.9 6 5.7
Production 4 7.5 6 6.0 5 6.4 8 5.2
Healthcare Practitioners and Technical 7 4.7 7 5.9 10 3.8 7 5.4
Construction 8 4.7 8 4.6 4 6.7 9 5.0
Building/Grounds Maintenance 9 4.4 9 4.4 9 3.9 12 3.5
Business Operations 14 2.1 10 3.2 18 1.6 14 2.9
Installation, Maintenance, and Repair 10 3.3 11 3.2 12 3.2 15 2.8
Healthcare Support 16 1.9 12 3.2 13 2.5 11 3.6
Food Preparation and Serving 12 2.9 13 3.1 3 8.6 3 9.4
Computer and Mathematical 20 1.4 14 2.5 14 2.3 13 3.3
Personal Care and Service 11 3.0 15 2.3 11 3.7 10 3.7
Financial Operations 13 2.2 16 2.3 17 1.9 19 1.7
Architecture and Engineering 15 2.0 17 2.1 19 1.5 18 1.8
Protective Service 17 1.9 18 2.0 15 2.3 17 2.3
Arts, Entertainment, Sports, Media 18 1.8 19 1.9 16 2.0 16 2.3
Community and Social Service 19 1.8 20 1.9 20 1.2 20 1.6
Legal 21 1.2 21 1.3 22 0.9 22 0.8
Life, Physical, and Social Sciences 22 0.9 22 0.9 23 0.9 21 1.1
Farming, Fishing, and Forestry 23 0.7 23 0.6 21 0.9 23 0.8
Extraction 24 0.1 24 0.1 25 0.1 25 0.2
Military 25 0.0 25 0.1 24 0.4 24 0.6
PANEL B Ages 50–59 Ages 60–69 Ages 70 and Over
2004 2019 2004 2019 2004 2019
Occupation Group Rank % Rank % Rank % Rank % Rank % Rank %
Management Occupations 2 11.7 1 13.0 3 10.6 2 12.0 3 10.8 3 11.6
Office and Administrative Support 1 15.4 2 11.4 1 16.2 1 12.7 1 15.9 1 12.9
Sales and Related 3 10.3 3 8.8 2 12.2 3 9.5 2 15.0 2 12.0
Transportation and Material Moving 6 6.0 4 8.1 5 6.7 4 7.7 4 6.7 5 7.8
Production 4 7.7 5 6.4 4 7.7 7 6.0 6 5.3 7 4.2
Education, Training, and Library 5 7.3 6 6.0 6 6.6 5 6.9 7 5.2 4 8.0
Healthcare Practitioners and Technical 7 5.1 7 5.6 9 4.1 6 6.4 9 3.8 6 5.5
Construction 8 5.0 8 5.3 8 4.2 9 4.3 10 3.8 12 2.8
Building/Grounds Maintenance 9 4.0 9 4.5 7 4.9 8 4.4 5 5.7 8 4.1
Installation, Maintenance, and Repair 10 3.6 10 3.4 11 3.1 11 3.2 15 2.0 17 2.4
Food Preparation and Serving 12 2.7 11 3.4 10 3.2 13 2.8 11 3.6 16 2.5
Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×
PANEL B Ages 50–59 Ages 60–69 Ages 70 and Over
2004 2019 2004 2019 2004 2019
Occupation Group Rank % Rank % Rank % Rank % Rank % Rank %
Business Operations 14 2.2 12 3.3 14 2.0 10 3.2 17 1.9 11 2.8
Healthcare Support 16 2.0 13 3.2 16 1.9 12 3.2 19 1.7 10 2.9
Computer and Mathematical 20 1.7 14 2.9 20 1.0 16 2.3 23 0.4 21 1.3
Financial Operations 13 2.3 15 2.2 13 2.2 14 2.3 14 2.3 15 2.6
Personal Care and Service 11 2.7 16 2.2 12 3.1 17 2.2 8 4.3 9 3.3
Protective Service 18 1.8 17 2.1 15 2.0 20 1.7 13 2.4 18 2.1
Architecture and Engineering 15 2.0 18 2.1 17 1.9 15 2.3 18 1.7 19 2.0
Arts, Entertainment, Sports, Media 19 1.8 19 1.7 18 1.8 19 2.0 12 2.4 14 2.6
Community and Social Service 17 1.8 20 1.7 19 1.7 18 2.0 16 1.9 13 2.8
Legal 21 1.2 21 1.1 21 1.0 21 1.3 20 1.4 20 2.0
Life, Physical, and Social Sciences 22 0.9 22 0.8 22 0.8 22 1.0 22 0.8 22 1.2
Farming, Fishing, and Forestry 23 0.6 23 0.6 23 0.8 23 0.6 21 1.1 23 0.7
Extraction 24 0.1 24 0.1 24 0.1 24 0.1 24 0.0 24 0.1
Military 25 0.1 25 0.1 25 0.0 25 0.0 25 0.0 25 0.0

NOTE: In this table, the rank of each occupation is based on the percent of workers within each age group who are employed within that occupation. Occupation groups are assigned based on the two-digit Standard Occupational Classification (SOC) and are exhaustive of all paid occupations. Occupations are sorted in table based on 2019 rank for all older adults ages 50 and over in Panel A and the 2019 rank of adults ages 50–59 in Panel B. The 2019 data is classified using the 2018 version of SOC. The 2004 data is classified using the 2000 Census version of SOC. Differences in classification versions may affect comparisons over time.

SOURCE: Data from 2004 and 2019 American Community Survey Public-Use Microdata file calculated by U.S. Census Bureau online data table tool (Beta version).

In total, just over half of these older workers (54.4%) were employed within these six occupation groups in 2019. Though their rankings shifted slightly, workers ages 50 and over were also most likely to be employed in these six occupations in 2004, and these occupations groups then employed 59 percent of older workers. Within these six occupations there were declines in the percent employed in office and administrative support, sales and related, and production occupations and an increase in transportation and material moving occupations. With a few notable exceptions—business operations, healthcare support, computer and mathematical, and personal care and service occupations—rankings across all occupation groups changed little over the 2004–2019 period among older workers.

Since labor force participation drops significantly among those ages 60 and over, the rankings for those ages 50 and over largely reflect employment among those ages 50–59 (Table 2-1, Panel B). The three most common occupation groups for those ages 50 and over also employ the highest percentages of workers ages 60–69, and ages 70 and over, though their relative ranking shifts with age as higher proportions of older workers leave the labor force or shift their job arrangement to accommodate their changing preferences and needs. Office and administrative support occupations; sales and related occupations; and education, training, and library occupations each employed a higher percentage of those ages 70 and over than those ages 50–59. In contrast, the percentage of those ages 70 and over who were employed in management, production, and material moving occupations was lower than the percentage of those ages 50–59. This could suggest that these latter occupations have characteristics, such as long work hours or physical demands, that make them less preferable or accommodative to workers as they age (Ameriks et al., 2018; Angrisani et al., 2016). It could also be the result of broader changes in the occupational distribution of the workforce, in which younger workers are less likely to enter shrinking occupation groups while older workers who first entered these occupations in early periods (when the occupations were growing) remain.

Nevertheless, while these occupations employ much of the older workforce, this is not necessarily because they are more likely to accommodate the needs of these workers. Part of the reason such a high percentage of older

Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×

workers is employed in these occupation groups is simply that these occupations employ many workers overall. In fact, five of the six most common occupation groups for older workers in 2019 were also among the top six occupation groups in which workers under age 40 were employed. Together, the top five occupations among those ages 50 and over also employed 42 percent of all workers under age 40, just slightly below the percentage of older workers employed in them. The sixth occupation, production occupations, declined across all age groups between 2004 and 2019 and was only the eighth most common occupation among those under age 40, suggesting that the labor market was shifting away from this type of employment over the period.

In contrast, younger workers were far more likely to be employed in food preparation and serving occupations than older workers; these occupations ranked third among those ages 40 and under in both 2004 and 2019, but 12th and 13th (respectively) among those ages 50 and over. This suggests that these occupations have characteristics that make them less attractive to older workers.

A more instructive method for looking at the occupations of older workers is to examine the age distributions within occupation groups to determine in which groups older workers constitute the highest share of workers. These are the occupations in which the workforce is aging more rapidly than the rest of the labor force, a pattern that could reflect a declining need for or availability of younger workers to enter these occupations and (or) might indicate that these occupations can more easily accommodate the physical and cognitive needs of older workers. Table 2-2 shows these occupations ranked by the percentage of workers that fall within each age group in 2004 and 2019, separately by gender.2 The occupations with the highest percentage of older workers differ from those that employ the highest percentage of middle-aged and younger workers and these occupations differ by gender.

The five occupations with the highest percentages of workers who were ages 50 and over in 2019 were:

Men Women
1. Legal Office and administrative support
2. Management occupations Building/grounds maintenance
3. Community and social service Financial operations
4. Architecture and engineering Production
5. Financial operations Extraction

Comparing this list to the rankings in Table 2-1 shows that several of the occupations with the highest percentages of workers over age 50 are also those that employ fewer workers overall. Among men, only management occupations are also among the most common occupations in which older (or younger) men were employed, while among women, only office and administrative support occupations were. However, employment in management occupations increased among men (both older and younger) between 2004 and 2019, while employment in office and administrative support occupations decreased among women.

Among men, the three occupations that had the highest percentage of workers over age 70—legal, community and social service, and financial operations occupations—were among the five occupations that had the highest percentages of men ages 50 and over in 2019. However, among women, only office and administrative support occupations employed both the highest percentage of workers ages 50 and over as well as workers ages 70 and over in 2019. The occupations that had the second and third highest percentages of women ages 70 and over—arts, entertainment, sports, media, community, and social service occupations—had the 16th and ninth highest percentages of women ages 50 and over. This could be because these occupations have characteristics that allow workers to remain in them at older ages; however, community and social service occupations employed the third highest percentage of women in the 50–59 age group in 2004 and the 16th highest in 2019, suggesting that this could also reflect changes in the occupation distribution over time. In fact, the ranking of occupations among women changed substantially more than that among men between 2004 and 2019, perhaps reflecting the dramatic changes in the sex segregation of the labor market that occurred throughout these women’s lives (Blau et al., 2013).3

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2 Results are presented separately by gender because sex segregation of occupations declined substantially during the lives of these older workers (Blau et al., 2013), but segregation patterns when entering the labor market may persist throughout the life course. The percentage of workers within each age group is provided in the Annex at the end of this chapter.

3 They may also reflect changes in the overall distribution of occupations.

Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×

TABLE 2-2 Occupation Groups with the Highest Percentages of Oldest and Youngest Workers by Gender and Age Group, 2004 vs. 2019

PANEL A: MEN Ages 50+ Ages 50–59 Ages 60–69 Ages 70+ Under Age 40
Occupation 2004 2019 2004 2019 2004 2019 2004 2019 2004 2019
Legal 1 1 1 9 4 1 2 1 24 24
Management Occupations 3 2 2 1 5 3 7 8 25 25
Community and Social Service 2 3 3 12 2 2 1 2 23 23
Architecture and Engineering 8 4 7 4 10 4 16 12 20 22
Financial Operations 6 5 8 11 6 6 5 3 19 19
Business Operations 5 6 5 6 3 9 4 11 22 21
Healthcare Practitioners and Technical 7 7 6 13 13 7 8 5 21 20
Installation, Maintenance, and Repair 15 8 11 2 18 11 21 18 15 18
Building/Grounds Maintenance 11 9 14 7 7 10 9 14 13 15
Education, Training, and Library 4 10 4 16 1 8 12 4 18 17
Life, Physical, and Social Sciences 9 11 9 19 11 5 15 7 17 14
Production 12 12 10 3 16 12 19 20 16 16
Transportation and Material Moving 13 13 13 8 12 14 14 15 12 11
Sales and Related 10 14 12 14 8 13 10 9 14 10
Arts, Entertainment, Sports, Media 16 15 15 20 19 15 11 10 10 9
Protective Service 14 16 17 10 14 19 13 16 11 12
Construction 22 17 20 5 22 18 20 21 8 13
Farming, Fishing, and Forestry 19 18 22 18 15 17 6 13 5 7
Office and Administrative Support 17 19 18 17 17 16 17 17 7 6
Healthcare Support 21 20 19 21 21 20 18 19 4 4
Computer and Mathematical 23 21 21 15 23 23 24 22 6 8
Personal Care and Service 18 22 23 23 9 22 3 6 3 3
Extraction 20 23 16 22 20 21 23 23 9 5
Food Preparation and Serving 24 24 24 24 24 24 22 24 1 2
Military 25 25 25 25 25 25 25 25 2 1
PANEL B: WOMEN Ages 50+ Ages 50–59 Ages 60–69 Ages 70+ Under Age 40
Occupation 2004 2019 2004 2019 2004 2019 2004 2019 2004 2019
Office and Administrative Support 6 1 8 6 3 1 5 1 17 20
Building/Grounds Maintenance 4 2 9 3 1 3 1 8 23 24
Financial Operations 12 3 11 2 13 2 16 10 18 25
Production 3 4 5 5 2 4 7 12 24 21
Extraction 24 5 19 1 24 15 24 20 3 15
Management Occupations 2 6 2 4 7 8 9 11 25 23
Legal 16 7 10 7 20 7 19 6 12 22
Education, Training, and Library 1 8 1 13 4 6 8 4 22 19
Community and Social Service 5 9 3 16 6 9 12 3 20 18
Healthcare Practitioners and Technical 7 10 6 14 11 5 17 16 21 17
Transportation and Material Moving 9 11 12 8 5 14 13 14 15 14
Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×
PANEL B: WOMEN Ages 50+ Ages 50–59 Ages 60–69 Ages 70+ Under Age 40
Occupation 2004 2019 2004 2019 2004 2019 2004 2019 2004 2019
Business Operations 11 12 7 9 16 12 20 18 16 16
Healthcare Support 15 13 16 15 12 11 11 9 8 12
Installation, Maintenance, and Repair 8 14 4 12 15 10 21 19 19 11
Computer and Mathematical 19 15 13 10 23 17 23 24 13 13
Arts, Entertainment, Sports, Media 10 16 15 21 8 13 3 2 14 8
Sales and Related 17 17 20 20 9 16 4 5 4 4
Construction 21 18 18 11 22 22 18 22 10 9
Farming, Fishing, and Forestry 18 19 23 17 14 19 6 17 7 10
Protective Service 20 20 21 18 19 23 14 15 5 6
Personal Care and Service 13 21 17 22 10 21 2 7 9 3
Life, Physical, and Social Sciences 14 22 14 23 17 18 15 13 11 7
Architecture and Engineering 22 23 22 19 21 20 22 23 6 5
Food Preparation and Serving 23 24 24 24 18 24 10 21 2 2
Military 25 25 25 25 25 25 24 25 1 1

NOTE: Table 2-2 shows the 25 occupation groups ranked by the percentage of workers within that occupation who fall within each age in 2004 and 2019 by gender. Panel A shows the occupation rankings among men, while Panel B shows the occupation rankings among women. 2019 occupation groups are based on two-digit codes assigned using the 2018 version of the Standard Occupational Classification (SOC). The 2004 data is classified using the 2000 Census version of SOC. Differences in classification versions may affect comparisons over time. Each percentage is ranked from highest percentage to lowest percentage. Occupations are sorted in the table based on their ranking among all workers ages 50 and over.

SOURCE: Data from 2004 and 2019 American Community Survey Public-Use Microdata file calculated by U.S. Census Bureau online data table tool (Beta version).

WORK PREFERENCES OF OLDER WORKERS

Older workers are disproportionately more likely to value jobs that require moderate physical activity, sitting, and team-based evaluation and that offer schedule flexibility and work autonomy (Maestas et al., 2018). As noted above, several occupations ranked considerably higher among those ages 70 and over than they did among those ages 50–59. In 2019, these included: community and social service occupations; education, training, and library occupations; and arts, entertainment, sports, and media occupations. Among women, sales and related occupations and personal care and service occupations also ranked higher in their employment of workers ages 70 and over than of workers ages 50–59. Among men, financial operations occupations; education, training, and library occupations; healthcare practitioners and technical occupations; and life, physical, and social sciences occupations also ranked considerably higher in employing workers ages 70 and over than in employing those ages 50–59. Though these occupations cover a wide range, they likely possess characteristics that allow workers to continue working at older ages and make them more desirable occupations to older workers, such as autonomy and schedule flexibility.

The preference for greater work autonomy leads many workers to shift to self-employment, and this becomes increasingly common at older ages. Though the probability of being self-employed increases across the age range, it increases more dramatically after age 65 (Abraham, 2020). Figure 2-7 (top panel) shows the percentage of employed adults over age 50 who were self-employed in their current main job in 2004 and in 2019, by gender and age.4 In 2019, only 8.6 percent of employed men ages 50–54 were self-employed, but this rose with age, reaching 15.4

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4 The committee also examined similar comparisons using self-employment measured by self-employment status of longest-held job and receipt of any self-employment income. Though the overall levels of self-employment differ somewhat—for example, using any self-employment income overall rates of self-employment across the age distribution are 10–20% higher than those in Figure 2-5—the trends by age, gender, and over time are similar.

Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×
Image
FIGURE 2-7 Self-employment in current main job, by age and gender, 2004 and 2019.
NOTE: Figure 2-7 shows the percentage of employed adults (top panel) and all adults (bottom panel) ages 50 and over who are self-employed in their current main job.
SOURCE: Data from 2004 and 2019 March Current Population Survey Annual Social and Economic Supplement data files calculated by U.S. Census Bureau online data table tool (Beta version).
Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×

percent of those ages 65–69 and 23.0 percent of those ages 75–79. These percentages marked a sizable decline in self-employment since 2004, when 11.5 percent of employed men ages 50–54 were self-employed, 22.0 percent of those ages 65–69, and 33.6 percent of those ages 75–79. Older employed women were less likely than men to be self-employed at every age; however, employed women over age 65 experienced smaller declines in self-employment between 2004 and 2019 than similarly aged men, and employed women who were ages 75–79 were more likely to be self-employed in 2019 than in 2004.

Though self-employment rates declined among all adults in their 50s—especially among men—between 2004 and 2019 (Figure 2-7, bottom panel), the decline in self-employment among workers ages 65 and over was in part due to the growth in employment among wage and salary workers during this period, which exceeded the growth among self-employed workers. Though the percentage of all men ages 65–74 who were self-employed also declined during this period (Figure 2-7, bottom panel)—indicating that self-employment rates within this age group did decline over the period—the declines are much smaller than those among employed men (Figure 2-7, top panel). In addition, self-employment increased within the oldest age groups. The percent of men ages 75 and over who were self-employed remained steady or increased even as the percentage of employed men who were self-employed declined. The percentage of women who were self-employed also increased among those ages 70 and over, while remaining stable among women ages 65–69.

Self-employment can take on a number of different forms. A small fraction of older self-employed adults engages in informal work, such as babysitting or elder care, maintenance work, or making and selling handcrafts (Abraham, 2020). Some older workers return to their prior employer as an independent contractor. These relationships allow employers to continue to benefit from their former employees without taking on the full cost and risk of employing them. Though these independent contractors often gain flexibility and greater autonomy over their schedules and work, they lose some of the benefits and protections of being an employee. About half of older self-employed workers work as independent contractors, independent consultants, or freelance workers, and about one-quarter of these workers are performing work for a prior employer (Abraham, 2020). It is not clear to what degree these workers choose this independent contractor relationship or are pushed into these arrangements by their prior employers as a condition of continuing their employment.

Accurate estimates of these employment relationships have proved elusive due to limitations in the most commonly used measures of employment characteristics (National Academies of Sciences, Engineering, and Medicine, 2020). These measures can lead to misclassification of some forms of self-employment, particularly informal, gig, mobile-platform-enabled, and contract work, as well as an underestimation of employment and labor force participation (see Box 2-1). The underestimation of labor force participation is particularly acute for the youngest and oldest workers in the labor market, who are more likely to work fewer than 15 hours per week and to engage in informal work arrangements (Abraham et al., 2021).

Older Workers Work Fewer Hours

The shift to self-employment among older workers is often driven by a desire for shorter or more flexible work hours. Few employers offer a phased retirement plan, which allows workers to reduce their work hours as they approach retirement (Society for Human Resource Management, 2018), and most workers do not believe their employer would allow them to reduce their hours (Abraham and Houseman, 2005). Nevertheless, many older workers who remain in the labor force reduce their work hours to part-time, and this is particularly true for those who are self-employed (Abraham et al., 2021). As was true for self-employment, part-time working arrangements become increasingly common with age (up until age 80), with steep increases occurring after age 65 (Figure 2-8).

Older women are more likely than similarly aged older men to work part-time. For example, at ages 50–54, employed women are twice as likely as employed men (22.8% vs. 10.6% in 2019) to work part-time, with part-time defined as working fewer than 35 hours per week. This gender disparity narrows among those in their 70s and older. In fact, in 2004 there was no difference by gender in the probability of working part-time among those ages 75 and over. Between 2004 and 2019, as labor force participation increased among older adults, the percentage working part-time declined, as those who remained in the labor force became more likely to work at least 35 hours

Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
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per week. This change was very small among those in their 50s and primarily occurred among those ages 60 and over, with the largest changes among those ages 65 and over. Though both men and women were less likely to work part-time in 2019 than they were in 2004, the age-specific decreases in part-time work were larger among men. This meant that the gender gap in work hours either opened (ages 75 and over) or increased (ages 50–75) at each age throughout the age distribution.

THE CHANGING COMPOSITION OF THE OLDER WORKFORCE

The older workforce, like the U.S. population as a whole, has become more diverse and more educated over time. Immigrants, Hispanic Americans, and non-White populations alongside those who have a college degree each constitute a greater share of the older workforce in 2019 than they did in 2004 (Figure 2-9).5 The gender distribution of the labor force changed little over the period (Figure 2-9, Panel A); 47.6 percent of adults ages 50 and over who were in the labor force in 2019 were women, compared with 47.3 percent in 2004. The gender gap in labor force participation is larger at ages 70 and over than at younger ages, though this older age group also

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5 The change in the demographic composition of the older workforce is presented for the period 2004–2019. Though data were available for 2020, they were not used for these analyses in order to exclude the effects of the COVID-19 pandemic. These comparisons could not be extended back to 2000 to match the figures in Tables 2-1 to 2-4, because beginning in 2003 Current Population Survey began to allow respondents to report more than one racial identity. It is not possible to generate comparable race-ethnicity measures for 2000.

Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
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FIGURE 2-8 Percent of employed adults ages 50 and over currently working part-time, by age and gender, 2004 and 2019.
SOURCE: Data from 2004 and 2019 March Current Population Survey Annual Social and Economic Supplement data files calculated by U.S. Census Bureau online data table tool (Beta version).

saw the largest increase in the representation of women among labor force participants; the share in this age group who were women rose slightly between 2004 and 2019, from 42.5 to 43.6 percent.

Immigration status, in contrast, has changed a lot among older workers. The Immigration and Naturalization Act of 1965 abolished the immigration quota system that had been in place for decades and had restricted immigration to the United States based on nation of origin. This change in the law paved the way for dramatic changes in the nativity and racial-ethnic composition of the United States that occurred in subsequent decades and are ongoing as of the writing of this report. Though the effect of these compositional changes is lagged within the older population because individuals are more likely to immigrate at younger ages, the percent of the older workforce that is foreign-born has increased steadily over time (Figure 2-9, Panel B). In the period between 2004 and 2019, the foreign-born share of the labor force rose from 11.0 to 17.3 percent among those ages 50 and over, with the largest increase occurring among those ages 50–59 (from 11.0% to 19.1%). The accelerated increase at younger ages suggests that this trend is likely to continue in the near future.

As members of the foreign-born population and their native-born children aged, they began to constitute a larger share of the older labor force, changing and diversifying the racial-ethnic composition6 of that population (Figure 2-9, Panel C). The fastest growth occurred in the number of Hispanic adults, though there

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6 The racial-ethnic composition of the older workforce is coded based on two measures included in the Current Population Survey (CPS) data files beginning in 2004: Hispanic/Latino origin and race. CPS race categories follow the Office of Management and Budget guidelines (first issued in 1997) that allow respondents to report more than one race and recommend that race categories be restricted to the following: White, Black, American Indian and Alaska Native, Asian, and Native Hawaiian and Pacific Islander. Respondents who report being of Hispanic or Latino origin are coded as Hispanic, regardless of race. Respondents who report themselves as multiracial are coded into a separate multiracial category. These racial-ethnic categories may not line up to individuals’ self-identification. For example, many Hispanic respondents or those of Middle Eastern/Northern Africa descent report their race as “other” and are recoded into the existing Office of Management and Budget categories—often to White.

Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
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FIGURE 2-9 Demographic characteristics of the older labor force, ages 50 and over, 2004 vs. 2019.
SOURCE: Data from 2004 and 2019 March Current Population Survey Annual Social and Economic Supplement data files calculated by U.S. Census Bureau online data table tool (Beta version).

were also increases in the non-Hispanic Black and other non-White populations. Between 2004 and 2019, the Hispanic share of adults ages 50 and over in the labor force rose from 7.4 to 11.9 percent, while the share who were non-Hispanic Black rose from 8.8 to 10.0 percent, and the share who were of another non-White race (predominantly Asian)7 increased from 5.0 to 7.0 percent. This movement toward greater racial-ethnic diversity occurred within each age group, though here too the largest shift occurred among those ages 50–59, suggesting that this population will continue the trend toward greater racial-ethnic diversity as these and younger cohorts age.

After World War II, the United States began to experience an expansion in educational attainment over time. This was driven by higher rates of college completion across birth cohorts born before the mid-1970s (Bauman, 2016). The share of workers ages 50 and over who had completed a four-year college degree increased from 33.6 percent to 39.1 percent between 2004 and 2019 (Figure 2-9, Panel D). The largest increase occurred among workers ages 70 and over, among whom it increased from 28.5 percent in 2004 to 42.8 percent in 2019, a 50 percent increase over the period. Though the share of workers in their 50s with a college degree increased slightly, from 34.8 to 38.0 percent, this change was small relative to the change among older age groups.

In part, this reflects a slowdown of the dramatic expansion of college education in the post-war period; however, it also reflects the increasingly important role that education plays in both health and changes in labor force participation at older ages. College completion rates did not increase significantly enough across birth cohorts to explain the large increase of college graduates among those ages 70 and over; much of this increase over time

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7 In addition to Asians, this category also includes non-Hispanic Native Hawaiians and Pacific Islanders, non-Hispanic American Indians and Alaska Natives, and non-Hispanic multiracial individuals. Due to the small number of Current Population Survey respondents within these other racial groups, these categories were collapsed with Asians who make up about three-quarters of those who fall in this category.

Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×

is due to both differential mortality and differences in labor force participation by education. (The latter trend is discussed in the next section.)

The United States has long experienced differential mortality rates by education, which have resulted in lower life expectancy for those with less education (first noted in Kitagawa and Hauser, 1973). However, these disparities have widened such that those with the highest levels of education can expect to live more than a decade longer than those with the lowest levels of education (the National Academies, 2021). As a result, those with a college degree are overrepresented among surviving adults in the oldest age groups.

DIVERSITY IN LABOR FORCE PARTICIPATION PATTERNS

In the previous section we noted that changes in the demographic composition of the labor force were sometimes larger than could be explained by concomitant changes in the composition of the U.S. population, but also reflected disparities in labor force participation. In this section, we examine differences in labor force participation by nativity, race-ethnicity, and educational attainment to assess how these factors shape labor force participation at older ages.8

Labor force participation varies significantly by nativity, race-ethnicity, and education. These differences reflect differential access both to employment and to alternative sources of support in retirement. Though many of those who immigrate to the United States become naturalized citizens and enjoy access to public programs that enable retirement, such as Social Security and Medicare, due to a combination of their immigration status and program eligibility requirements a sizable number remain ineligible for these programs and other retirement benefits and must rely on employment for financial support at older ages. Long-standing race-ethnic disparities in employment and work are often cumulative, leading to different trajectories at older ages. Finally, education shapes the opportunities available to individuals in the labor market, influencing their ability to continue to work, as well as their preferences regarding retirement.

At most ages, foreign-born men maintained higher labor force participation in 2019 (Figure 2-10, top panels) and experienced larger increases in participation between 2004 and 2019 than native-born men (Figure 2-10, middle and bottom panels). Between ages 30 and 54, the share of foreign-born men who were in the labor force in 2019 remained about four percentage points higher than that of native-born men, but this gap widened to 10 percentage points between ages 55 and 64 before narrowing at older ages. This higher labor force participation among foreign-born men may be the result of legal restrictions on immigration and public program eligibility. Immigration law requires immigrants and their families to maintain income support in order to remain in the United States. At the same time, many public programs have eligibility restrictions that prevent noncitizens from receiving benefits, increasing their reliance on employment at older ages. Among men ages 75 and over, there was no longer a difference in labor force participation by nativity. In 2004, foreign-born men ages 70 and over were less likely to be in the labor force than native-born men, but labor force participation at older ages increased more rapidly among foreign-born than native-born men between 2004 and 2019.

A different pattern was present among women. In 2019, foreign-born women had similar or lower labor force participation rates than native-born women at every age, except ages 65–69, when the rate of foreign-born women slightly exceeded that of native-born women. Foreign-born women were more likely than native-born women to be out of the labor force during their child-raising years but had similar labor force participation rates at older ages. Labor force participation among foreign-born women in their 30s was about 15 percentage points lower than that of native-born women, but this gap narrowed to two to three percentage points at ages 55–74.

Though foreign-born women were less likely than native-born women to be in the labor force in 2019, the gap was much smaller than it had been in previous decades—except among women ages 35–49. In 2004, labor force participation rates of foreign-born women were far below those of native-born women at every age. Between 2004

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8 Labor force participation is the sum of employment and unemployment rates, both of which are likely to differ by nativity, race-ethnicity, and educational attainment. Unemployment rates are difficult to measure and interpret for older workers. For those over age 65, unemployment rates are very low, which means estimates are less precise within this group and it is difficult to see trends. This is because they are based on whether an individual looked for work in the past week and older workers who have difficulty finding work are more likely to leave the labor force. For these reasons, trends in unemployment are not presented here.

Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
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FIGURE 2-10 Labor force participation among adults ages 25 and over by gender and nativity, 2004–2019.
NOTE: Figure 2-10 shows the labor force participation rate in 2019 (top panels), the absolute change in the labor force participation rate between 2004 and 2019 (middle panels), and the percent change in the labor force participation rate over this period (i.e., the absolute change in the labor force participation rate divided by the 2004 labor force participation rate).
SOURCE: Data from 2004 and 2019 March Current Population Survey Annual Social and Economic Supplement data files calculated by U.S. Census Bureau online data table tool (Beta version).
Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×

and 2019, labor force participation increased more among foreign-born than native-born women. The only exception was in the 35–49 age range, within which foreign-born women experienced declining labor force participation, while native-born women experienced little change. Though native-born women ages 55 and older participated in the labor force at increasing rates, foreign-born women experienced much larger increases. These trends marked a convergence in the labor force participation rates of older foreign-born and native-born women over time.

Racial-ethnic disparities in the labor force are deeply entrenched and long-standing in the United States. Black men of all ages have long encountered reduced employment opportunities compared to other men due to structural racism, which has led them to leave the labor force in greater numbers. In 2019, non-Hispanic Black men had substantially lower labor force participation than other men (Figure 2-11, top left panel). At ages 34–44, the gaps between non-Hispanic Black men, on the one hand, and Hispanic, non-Hispanic White, and non-Hispanic Asian or Pacific Islander men, on the other, is greater than 10 percentage points. Beginning at age 50, non-Hispanic Black men leave the labor force at much higher rates than other men, so that by ages 60–64, labor force participation rates among these men are more than 16 percentage points lower than those of non-Hispanic White and Asian/Pacific Islander men and 20 points lower than Hispanic men.

The differences in labor force participation rates among Hispanic, non-Hispanic White, and non-Hispanic Asian/Pacific Islander workers were smaller. Hispanic men had the highest rates among men in their 30s and approaching retirement at ages 60–64. Between ages 40 and 59, non-Hispanic Asian/Pacific Islander men had the highest labor force participation rate, while non-Hispanic White men were most likely to be in the labor force at ages 65–74. Overall, non-Hispanic White and Asian/Pacific Islander men were more likely to remain in the labor force after age 65 than either Hispanic or non-Hispanic Black men. These two groups also experienced the largest and most consistent increases in labor force participation after age 65 between 2004 and 2019. The higher labor force participation among Hispanic and Asian men before age 65 might reflect the higher proportion of foreign-born men with higher overall rates of labor force participation within this population. The trends over time are more difficult to interpret for these two racial-ethnic groups because their composition has changed over time in response to shifts in migration from Latin American and Asian countries and, as well, labor force participation may differ by nativity (Budiman and Ruiz, 2021; Flores and Radford, 2017).

Among women, Hispanic women were consistently less likely than other women to be in the labor force at nearly every age. Younger non-Hispanic Asian/Pacific Islander women (ages 25–39) also had lower labor participation than non-Hispanic White and Black women; however, between ages 40 and 69, labor force participation among this group was comparable to that of non-Hispanic White women. Unlike non-Hispanic Black men, non-Hispanic Black women were as likely as non-Hispanic White women to be in the labor force between the ages of 25 and 49. However, as was true among non-Hispanic Black men, the labor force participation rates of non-Hispanic Black women ages 50–65 were lower than those of non-Hispanic White women, though this difference was much smaller than the one that occurred among men. After age 65, labor force participation was largely similar among non-Hispanic women, regardless of race; only Hispanic women experienced lower rates than other women. The changes in labor force participation between 2004 and 2019 among women were also largely similar across the four racial-ethnic groups.

The Role of Education in Defining Opportunity Increases at Older Ages

Educational attainment plays an important role in defining the labor market opportunities of older workers. Historically, employment opportunities have narrowed at older ages as physical ability to perform work tasks deteriorates (Rutledge et al., 2017). However, technological change and economic shifts to jobs that depend less on manual and routine skills and favor workers with cognitive and analytic skills (Autor et al., 2003) have allowed more Americans to remain in the labor force despite health limitations at older ages. The shift away from physically demanding occupations creates working environments in which health limitations are more easily accommodated by employers (Maestas and Zissimopoulos, 2010), but the higher-skill demands of these jobs prevent less educated workers from benefiting from these changes. This means that employment opportunities at older ages have increased for more educated workers but have remained narrow for those with less education (Rutledge et al., 2017).

Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×
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FIGURE 2-11 Labor force participation among adults ages 25 and over by age, gender, and race-ethnicity, 2004–2019.
NOTE: Figure 2-11 shows the labor force participation rate in 2019 (top panels), the change in the labor force participation rate between 2004 and 2019 (middle panels), and the percent change in the labor force participation rate over this period (bottom panels).
SOURCE: Data from 2004 and 2019 March Current Population Survey Annual Social and Economic Supplement data files calculated by U.S. Census Bureau online data table tool (Beta version).
Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×

In 2019, the largest differences in labor force participation rates the committee examined were those by educational attainment (Figure 2-12). At every age, labor force participation increased with education among men (Figure 2-12, top left panel), but the gap between the most and least educated group expanded with age, in part because those with less education began to leave the labor force at younger ages. The gap between college graduates and those with less than a high school degree was nearly 15 percentage points among those ages 25–29 (91.0% vs. 76.2%) and widened between ages 40 and 69, reaching 26 percentage points among those ages 65–69 (48.7% vs. 22.9%). Labor force participation rates began to decline at ages 40–44 among those who had not completed college, at ages 45–49 among those with a high school degree, at ages 50–54 among those who had attended college but not completed a degree, and at age 55–59 among those with a four-year college degree.

The changes in labor force participation between 2004 and 2019 (Figure 2-12, middle and bottom panels) did not differ substantively by education, with all four groups experiencing small declines in participation at younger ages and increases among those ages 60 and over. Men who had not completed college experienced somewhat larger decreases in labor force participation among those ages 25–29 and were also the only group to show declines in participation among those ages 65–69. Though the percent increase in labor force participation rates among men with a high school degree or less appears to be large for men ages 75 and over, this dramatic change should be interpreted with caution because it is the result of both low labor force participation rates in 2004 and a small sample size.

Among women in 2019 (Figure 2-12, top right panel), education-based disparities in labor force participation were significantly larger than those among men and followed a different age pattern. The gap in participation between those with the highest and lowest levels of education was largest at younger ages. Fewer than half (43.5%) of women ages 25–29 who did not complete high school were in the labor force, compared to 86.2 percent of those who had completed a college degree. Though labor force participation was higher among women ages 45–49 who did not have a high school degree (55.5%), it remained considerably below that of similarly aged women who had a college degree, among whom 85.4 percent were in the labor force. Among women in their 50s, labor force participation declined among all education groups but declined more among those with less than a high school degree than those with more education. The largest education-based gap occurred among women ages 55–59, reaching 37.3 percentage points (39.8% for women without a high school degree vs. 77.1% for women with a bachelor’s degree). Beginning in their 60s, labor force participation began to drop off more rapidly among women with a bachelor’s degree, narrowing the gap in labor force participation, though those with a college degree continued to be much more likely to remain in the labor force. After age 60, there was no difference in participation between those with a high school degree and those who had some college but had not completed a degree.

These disparities in labor force participation by educational attainment among women were much larger in 2019 than they had been in 2004 (Figure 2-12, middle and bottom panels), though there were already large gaps in that year. Between 2004 and 2019, participation rates fell among women under age 50 who had a high school degree or less,9 but they increased among those who had a college degree. Among older women, labor force participation increased across all education groups; however, women with a college degree experienced the largest increase. Together, these changes led to a widening gap in labor force participation between college-educated women and women without a college degree. As is also the case for the changes observed among men, the large percent increases in female labor force participation at the oldest age groups should be interpreted with caution.

Although the committee did not examine racial-ethnic differences by education, previous research (Lahey, 2018) suggests that the education gap in labor force participation is particularly large for Black women. Among women with a high school degree or less, Black women who are under age 60 are less likely than White women of the same age to be in the labor force, but are more likely to be in the labor force at older ages—in part because earlier cohorts of these Black women had higher labor force participation rates at younger ages than did similarly educated White women. However, among women with a college degree, Black women are consistently more likely

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9 The one exception was among women ages 25–29 with a high school degree, who saw a small increase in labor force participation during the period.

Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×
Image
FIGURE 2-12 Labor force participation among adults ages 25 and over by age, gender, and educational attainment, 2004 and 2019.
NOTE: Figure 2-12 shows the labor force participation rate in 2019 (top panels), the change in the labor force participation rate between 2004 and 2019 (middle panels), and the percent change in the labor force participation rate over this period (bottom panels).
SOURCE: Data from 2004 and 2019 March Current Population Survey Annual Social and Economic Supplement data files calculated by U.S. Census Bureau online data table tool (Beta version).
Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×

than White women to be in the labor force, regardless of age, though this race-based disparity has declined over time as more White women with college degrees have remained in the labor force at older ages.

These large and growing education-based disparities, especially among women, explain the large shift in the proportion of the older workforce possessing a college degree between 2004 and 2019, particularly among those ages 70 and over. Though educational attainment has risen across birth cohorts, this shift alone could not explain the large increase in the proportion of the older workforce (ages 60 and older) with a college degree over this period. What can explain it is the combination of this shift with the large increase in labor force participation among older adults with a college degree and the education-based disparities in mortality discussed above.

THE INITIAL EFFECTS OF COVID-19 ON LABOR FORCE PARTICIPATION AND EMPLOYMENT

The committee had completed its first meeting as the effects of the COVID-19 pandemic began to be felt; however, it was clear from the outset that this disease could have severe and lasting repercussions for the work lives of older workers. Persons over the age of 65 who contract COVID-19 are more likely to experience severe symptoms than those who contract it at younger ages; this older age group represented the vast majority of COVID-related hospitalizations and about 80 percent of all mortality from the disease in 2020 (NCHS, 2020).

Thus, older workers, particularly those working in jobs that were deemed essential, were at a much higher risk of contracting the disease and experiencing more severe health effects. This could affect both the supply of and demand for older workers in the labor market. Fears about exposure to the virus may have made older workers wary of participating in jobs that required regular in-person interactions with the public or with coworkers. At the same time, employer concerns about the effects of disease severity on productivity and health care costs, as well as the possibility of being held legally liable for infection transmission in the workplace, could reduce the value of hiring and keeping older workers. In addition, any general decrease in labor demand could have a disproportionate effect on older workers if they are concentrated in hard-hit industries or experience more difficulty in finding new work after a job loss due to age discrimination or other issues.

The pandemic is ongoing at the time of this writing, and its long-term effects on the employment and labor force participation of older workers are yet to be experienced. However, monthly data from the Current Population Survey (CPS) can be used to assess its initial impact. Between January 2020, before the infection rate in the United States was measurable, and January 2021, a year later, the employment rate declined among adults 25 and over, regardless of age group (Figure 2-13). Among both men and women, the largest declines in the employment rate occurred at younger ages (Figure 2-13, middle panel); however, this was because employment was already higher at these ages. The percentage change in employment rates was similar for those under age 65 (Figure 2-13, bottom panel); employment rates were approximately five percent lower in January 2021 than they were a year earlier. Though the percentage point decline in the percent employed was smaller among those ages 65 and over (Figure 2-13, middle panel), it represented a larger share of older workers (Figure 2-13, bottom panel), particularly among women in their 70s. In January 2021, employment rates among men ages 70 and over were about 12 percent lower than they were in January 2020. The largest decrease occurred among women ages 70–74, whose employment rates were nearly 25 percent lower in 2021 than in 2020.

Older adults who lost employment could respond by either looking for a new job or leaving the labor force altogether. Most of those who lost their jobs during this period continued to look for work and were, therefore, unemployed, though the probability of looking for work depended on the age of the worker. The smaller difference between the change in the labor force participation rate and the employment rate at older ages suggests that older workers were more likely to respond to the loss of employment by leaving the labor force, and this was particularly true of older women.

The health and mortality effects of the COVID-19 pandemic did not affect the U.S. population equally. Racial and ethnic minorities have experienced much higher rates of infection, hospitalization, and mortality than non-Hispanic Whites persons (NCHS, 2020). Similarly, due to the broader socioecological effects of racial/ethnic inequality, the effects of the pandemic on employment and labor force participation have also been distributed unequally. For this reason, the committee also examined employment and labor force participation

Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
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FIGURE 2-13 Labor force participation and employment status among adults by gender and age, January 2020–January 2021.
NOTE: The top panels of Figure 2-13 show the labor force participation (solid lines) and employment (dashed lines) rates for men (left panel) and women (right panel) in January 2020 and January 2021. The unemployment rate is represented as the gap between the labor force participation rate and the employment rate. The middle panel shows the change in each rate between January 2020 and January 2021, while the bottom panel shows the percent change in each rate over this period. A larger decrease in the employment rate than the labor force participation rate suggests that an increase in the unemployment rate occurred.
SOURCE: Data from 2020 and 2021 January Current Population Survey monthly data files calculated by U.S. Census Bureau online data table tool (Beta version).
Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×

(the sum of employment and unemployment) rates by gender, race-ethnicity, and age in January 2021 to that of January 2020 to determine the differential impact of COVID-19 on employment and labor force participation by race-ethnicity. The results for men can be found in Figure 2-14, and the results for women can be found in Figure 2-15.

Though men in all four racial-ethnic groups experienced declines in employment and labor force participation between January 2020 and January 2021, the largest decreases occurred among Hispanic and Asian men (Figure 2-14, middle panels). Across all age groups, Hispanic men most consistently saw larger decreases in employment than White or Black men. Asian men who were under age 50 experienced losses in employment that were comparable to those of White men; however, those age 50 and over experienced larger declines than men in any other racial-ethnic group. In general, changes in labor force participation largely mirrored those in employment, particularly at older ages. Younger men, in their late 20s, experienced the largest increase in their unemployment rates, while older men were more likely to leave the labor force altogether. The one exception was among Asian men approaching retirement: their unemployment rates increased most among those ages 50–64, even as labor force participation also declined. Only those ages 60–64 did not experience a contemporaneous decline in labor force participation.

The effect of the COVID-19 pandemic on racial-ethnic differences in employment and labor force participation followed different patterns among women, but these patterns also varied by age. The age-specific labor force participation profile changed most notably among younger Black and Hispanic women. In 2019 (Figure 2-11), labor force participation was flat between ages 25 and 49 among Black women, though it declined among other women in their 30s as they entered child-raising ages. However, in January 2021 (Figure 2-15, top panels), participation rates also declined among Black women in their 30s. In contrast, among Hispanic women though labor force participation rates were lower among Hispanic women in their 30s than those ages 25–29 in 2019, they held steady between ages 25 and 49 in January 2021 due to a decline in labor force participation among those ages 25–29 between 2020 and 2021 (Figure 2-15, middle panels). Asian women in their 50s experienced the largest declines in employment and increases in unemployment. However, in contrast to men, among older women there were no clear patterns in racial-ethnic differences in the changes in employment and labor force participation rates.

TRENDS IN HEALTH AND DISABILITY

Health is an important predictor of remaining in the labor market at older ages (Jason et al., 2017; Zajacova et al., 2014; Cahill et al., 2006). Poor health can limit work opportunities by reducing an individual’s physical, cognitive, or mental capacity for engaging in work activities, and also by altering preferences for job characteristics, remaining in the labor force, and the type of work in which to engage. The latter half of the twentieth century saw dramatic improvements in health and longevity due to advances in medical care and public health, and these changes have contributed significantly to the increases in labor force participation among older adults in the United States (Goldin and Katz, 2018a; Coile et al., 2017).

However, more recently, these gains in health have begun to flatten and perhaps even reverse. In fact, within the United States, mortality rates have increased among working-age adults due to drug and alcohol use, suicide, and obesity, leading to a three-year decline in overall life expectancy, the most sustained decline in more than a century (the National Academies, 2021). Though these changes were initially concentrated among those younger than age 55, more recently they have begun to expand into older ages as these younger cohorts have aged (the National Academies 2021).

Though the percentage of adults ages 60 and over who report they are in “fair” or “poor” health steadily declined between 2000 and 2020 (Figure 2-16), signaling improving health over time, this was not the case for younger adults. Among those under age 60, the percentage in fair or poor health either remained stable or increased between 2000 and 2014. After 2014, overall health improved among men and women in their 50s and women in their 40s, but remained stable among younger adults. Though health improved among adults ages 60 and over between 2000 and 2020, these improvements were smaller among those in their 60s than among those in their 70s, leading to a convergence in the percentage in fair or poor health across these five-year age groups. These trends

Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×
Image
FIGURE 2-14 Labor force participation and employment status among men ages 25 and over by race-ethnicity and age, January 2020–January 2021.
NOTE: Figure 2-14 shows the percent of men who are employed (top right panel) and in the labor force (top left panel) in January 2021. The middle panels show the absolute change in the labor force participation rate (left panel) and employment rate (right panel) between January 2020 and January 2021. The bottom panels show the percent change in the labor force participation rate (left panel) and employment rate (right panel).
SOURCE: Data from 2020 and 2021 January Current Population Survey monthly data files calculated by U.S. Census Bureau online data table tool (Beta version).
Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×
Image
FIGURE 2-15 Labor force participation and employment status among women ages 25 and over by race-ethnicity and age, January 2020–January 2021.
NOTE: Figure 2-15 shows the percent of women who are employed (top right panel) and in the labor force (top left panel) in January 2021. The middle panels show the absolute change in the labor force participation rate (left panel) and employment rate (right panel) between January 2020 and January 2021. The bottom panels show the percent change in the labor force participation rate (left panel) and employment rate (right panel).
SOURCE: Data from 2020 and 2021 January Current Population Survey monthly data files calculated by U.S. Census Bureau online data table tool (Beta version).
Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×
Image
FIGURE 2-16 Percent of U.S. adults reporting their health as fair or poor, by gender and age, 2000–2020.
NOTE: Figure 2-16 shows the percentage of men (left panels) and women (right panels) who report their overall health as “fair” or “poor” (rather than “excellent,” “very good,” or “good”).
SOURCE: Data from 2000–2020 March Current Population Survey monthly data files calculated by U.S. Census Bureau online data table tool (Beta version).

suggest that the gains in labor force participation among older adults that are due to improvements in health may be slowing. Moreover, the declining health among younger adults could presage future declines in labor force participation at older ages as these younger cohorts age and approach retirement.

As noted above, the United States has long experienced a large education-based gap in health and mortality that favors those with more education, particularly those with a college degree. The percentage of adults in fair or poor health decreases as levels of education increase, and the gap between those with the most and the least education widens with age (Figure 2-17, top panels). In 2019, among those ages 25 and over, adults with a four-year college degree were less likely to be in fair or poor health than those with less education, while those who did not complete a high school degree were the least healthy. This gap expanded with age, but more dramatically so after age 50. Among men with less than a high school degree, the percentage in fair or poor health was nearly twice as high among those ages 65–69 (at 42.2%) as it was among those ages 50–54 (at 22.1%). Among those with a bachelor’s degree the percentage was only marginally higher (10.9% vs. 6.4%), though this also represented a large percentage increase. Among women, the decline in health among those with less than a high school degree began earlier, at ages 45–49, when 21.2 percent were fair or poor health, and increased by more to reach 46.0 percent among those ages 65–69. The percentage of women with a bachelor’s degree who were in fair or poor health increased from 6.6 percent among those ages 45–49 to 12.9 percent among those ages 65–69.

This large education-based gap in overall health in 2019 represented an improvement from 2000 (Figure 2-17, bottom panels). Among both men and women who did not complete high school, the percentage in fair or

Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×
Image
FIGURE 2-17 Percentage of U.S. adults reporting their health as fair or poor, 2019, and change in percentage, 2000 vs. 2019, by gender, age, and education.
NOTE: Figure 2-17 shows the percent of U.S. adults in 2019 whose overall health is “fair” or “poor” (rather than “excellent,” “very good,” or “good”; top panels) and the change in this percentage from 2000 (bottom panels). Men are shown in the left panels, women are shown in the right panels. The year 2019 is used instead of 2020 to eliminate the effect of the COVID-19 pandemic on health in the March 2020 Current Population Survey monthly data file.
SOURCE: Data from 2000–2019 March Current Population Survey monthly data files calculated by U.S. Census Bureau online data table tool (Beta version).

poor health declined substantially, particularly among those under age 60.10 This was not the case for those who had a high school degree or more; among these more-educated adults, a higher percentage of those under age 50 were in fair or poor health in 2019 than in 2000. Though there was no clear relationship between the change in health and education among men, women who completed a bachelor’s degree experienced larger improvements in health than did other women with a high school degree or more, increasing their advantage over the period.

Figure 2-18 restricts the population to those in the labor force. In general, though the overall percentage of workers in fair or poor health is lower than that of the general population, the trends across age groups and over time are largely similar. However, two key differences stand out. First, in 2019, among men ages 60–64 and women ages 55–64 who have a high school degree, the percent in fair or poor health is lower than among younger men and women, but rises again with age among those ages 65 and over. This suggests that many of these adults who are in fair or poor health are leaving the labor force early, perhaps when the men reach eligibility for partial Social Security benefits at age 62. The second difference is that the change in health

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10 This change could be the result of changes in the composition of those with less than a high school education. As high school attendance is compulsory within the United States, new immigrant populations are overrepresented within this less educated group.

Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×
Image
FIGURE 2-18 Percent of labor force reporting their health as fair or poor, by gender, age, and education, 2000 vs. 2019.
NOTES: Figure 2-18 shows the percent of U.S. adults in the labor force in 2019 who reported their overall health as “fair” or “poor” (rather than “excellent,” “very good,” or “good”; top panels) and the change in this percentage from 2000 (bottom panels).
SOURCE: Data from 2000–2019 March Current Population Survey monthly data files calculated by U.S. Census Bureau online data table tool (Beta version).

between 2000 and 2019 among women with a college degree is similar to that of other women with a high school degree or more.

These differences suggest that changes in health are made manifest, in part, through changes in labor force participation. The rising rates of younger workers in fair or poor health could portend lower labor force participation among these younger cohorts as they reach conventional retirement ages. However, these rising rates could also signal a growing need to expand workplace accommodations for health conditions if more individuals in fair or poor health remain the labor force.

Though the CPS is not designed to capture detailed health or disability information about the U.S. population or workforce, it contains several questions that the U.S. Census Bureau uses to generate a composite measure of whether respondents have a health limitation or disability that limits or restricts their ability to work, a more stringent criterion than an overall assessment of fair or poor health (see Figure 2-19). This measure may underestimate the size of the population with disabilities (Burkhauser et al., 2014) and is discussed in greater detail in the annex to this chapter. The results are substantively similar to those obtained using the broader overall health measure. They show that though labor force participation has been increasing among older adults, the percentage who have a work disability has declined over the past two decades, suggesting that the employed population has become increasingly selective of those in better health. They also demonstrate that the percentage of younger workers with a work-limiting disability increased over the period.

Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×
Image
FIGURE 2-19 Presence (percent) of a work disability among labor force participants ages 25 and over, 2000–2020, and change in percent, 2000 vs. 2020.
NOTE: Figure 2-19 shows the percent of workers in the labor force who meet the Curret Population Survey criteria for having a work disability between 2000 and 2020 by gender and age group. These criteria are described in the annex at the end of this chapter.
SOURCE: Data from 2000–2020 March Current Population Survey Annual Social and Economic Supplement Data Files calculated by U.S. Census Bureau online data table tool (Beta version).

CONCLUSION

The U.S. workforce is aging, both because the population as a whole is aging and because more older adults are remaining in the labor force at older ages. Population projections suggest that the share of the U.S. population that is ages 65 and over will continue to grow, and current trends in labor force participation suggest the workforce will become increasingly diverse. The growing diversity of this labor force reflects changes in women’s labor force participation as well as changes in the racial-ethnic composition and nativity of the U.S. population. At the same time, the older workforce has increasingly become selective based on education, with workers with a college degree disproportionately remaining in the labor force at older ages.

Older workers who remain in the labor force are more likely to be self-employed and working part-time, a likelihood that increases with age. Although those in their 50s are overrepresented within management occupations, as well as within blue-collar occupations such as production, maintenance, repair, and installation occupations, these occupations are less common among those who remain in the labor force in their 60s and older ages.

Though health has improved among older adults, declines in overall health and increases in work-limiting disabilities among younger workers are worrying and could presage comparative declines in labor force participation as these cohorts enter retirement ages or an increase in work-limiting disabilities that will require greater workplace accommodations.

Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×

This points to an important caveat regarding the use of current trends to predict the future. Chronological age is a measure of stages of life course development, but individuals experience age within the contexts of the birth cohorts and historical periods in which they live (Elder and George, 2015). Historical events (period-based changes) with broad societal impacts may change the context for current and future decision-making and outcomes. Moreover, the effects of these period-based changes may vary depending on an individual’s life stage when the event happened. Thus, later life outcomes are shaped not only by an individual’s chronological age but also by his or her birth cohort and the historical periods in which the person has lived.

For example, The Civil Rights Act of 1964, which banned discrimination based on race, color, sex, religion, and national origin, was passed when the youngest members of the Baby Boom cohort were just reaching adulthood. This meant that the Baby Boom cohort was the first cohort to begin their careers in a labor market in which racial-ethnic and sex-based discrimination were illegal. This dramatically expanded the education and employment opportunities available to women and racial-ethnic minorities born in this and later cohorts. In contrast, those born before 1946 generally entered adulthood with fewer opportunities available to them, and despite also benefiting from the passage of the Civil Rights Act, the effects of these early disadvantages are likely to have cumulated over the life course, affecting retirement outcomes many decades later.

The recent cohort-based increases in morbidity and mortality among younger adults may portend future declines in labor force participation among these cohorts as they age. If this is the case, the projected aging of the population may not lead to continued aging of the U.S. labor force in the future as these birth cohorts reach retirement age. Similarly, the period-based effects of the COVID-19 pandemic may vary across birth cohorts. The contemporary effect of the pandemic disproportionately affected labor force participation among older workers. It remains to be seen whether their participation rates will recover or remain depressed as the economy improves. Further, the long-term effects of COVID-19, or Long COVID, particularly among younger adults and children who experience lasting health effects remain unknown. They could further erode the health and well-being of these cohorts, affecting their economic outcomes and labor force participation as they age.

Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×

ANNEX

Distributions Within Occupation Groups by Gender 2004 vs. 2019

ANNEX TABLE 2-1 Age Distribution Within Occupation Group Among Men, 2004

MEN 2004
Ages 50+ Ages 50–59 Ages 60–69 Ages 70+ Under Age 40
Occupation Rank Percent Rank Percent Rank Percent Rank Percent Rank Percent
Management Occupations 3 39.7 2 24.6 5 11.1 7 4.0 25 30.6
Business Operations 5 38.7 5 22.6 3 11.8 4 4.3 22 36.2
Financial Operations 6 35.5 8 20.9 6 10.4 5 4.3 19 40.5
Computer and Mathematical 23 19.0 21 14.0 23 4.3 24 0.6 6 55.0
Architecture and Engineering 8 33.1 7 21.1 10 9.1 16 2.9 20 38.4
Life, Physical, and Social Sciences 9 31.7 9 19.8 11 9.0 15 2.9 17 44.2
Community and Social Service 2 41.5 3 23.5 2 11.9 1 6.1 23 34.8
Legal 1 42.1 1 25.0 4 11.2 2 5.9 24 32.2
Education, Training, and Library 4 39.2 4 23.1 1 12.7 12 3.5 18 41.4
Arts, Entertainment, Sports, Media 16 27.1 15 16.5 19 7.0 11 3.6 10 50.9
Healthcare Practitioners and Technical 7 35.3 6 22.5 13 8.7 8 4.0 21 38.2
Healthcare Support 21 23.2 19 15.2 21 6.1 18 1.9 4 57.2
Protective Service 14 28.1 17 16.1 14 8.7 13 3.4 11 50.4
Food Preparation and Serving 24 10.1 24 6.1 24 2.9 22 1.1 1 78.3
Building/Grounds Maintenance 11 30.5 14 16.7 7 10.0 9 3.9 13 48.2
Personal Care and Service 18 25.7 23 11.7 9 9.1 3 4.8 3 58.4
Sales and Related 10 30.8 12 17.5 8 9.4 10 3.8 14 47.2
Office and Administrative Support 17 26.3 18 16.0 17 7.6 17 2.7 7 54.3
Farming, Fishing, and Forestry 19 25.5 22 12.8 15 8.5 6 4.2 5 55.4
Construction 22 22.5 20 15.0 22 5.9 20 1.7 8 52.8
Extraction 20 23.6 16 16.5 20 6.3 23 0.7 9 51.8
Installation, Maintenance, and Repair 15 27.9 11 18.7 18 7.6 21 1.5 15 44.9
Production 12 29.0 10 18.8 16 8.5 19 1.7 16 44.2
Transportation and Material Moving 13 28.9 13 17.0 12 8.9 14 3.0 12 48.3
Military 25 5.3 25 4.6 25 0.6 25 0.1 2 76.7

NOTES: Annex Table 2-1 shows the percent of male workers whose age falls within each age group in 2004 by occupation group and the rank of the occupation based on the percent of workers in that age group. The 2004 data is classified using the 2000 Census version of the Standard Occupation Classification. Differences in classification versions may affect comparisons over time. Each percentage is ranked from highest percentage to lowest percentage. Occupations are listed sorted based on their ranking among all workers ages 50 and over. Percentages for ages 50–59, 60–69, and 70 and over may not sum to Ages 50+ due to rounding. Table excludes percentage of employees who are ages 40–49.

SOURCE: Data from 2004 American Community Survey Public-Use Microdata file calculated by U.S. Census Bureau online data table tool (Beta version).

Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×

ANNEX TABLE 2-2 Age Distribution Within Occupation Group Among Men, 2019

MEN 2019
Ages 50+ Ages 50–59 Ages 60–69 Ages 70+ Under Age 40
Occupation Rank Percent Rank Percent Rank Percent Rank Percent Rank Percent
Management Occupations 2 46.7 1 24.0 3 16.9 8 5.8 25 30.1
Business Operations 6 39.2 6 19.1 9 14.7 11 5.4 21 41.2
Financial Operations 5 40.7 11 17.3 6 15.8 3 7.6 19 41.8
Computer and Mathematical 21 27.7 15 16.5 23 9.5 22 1.8 8 50.0
Architecture and Engineering 4 41.2 4 19.9 4 16.4 12 4.9 22 39.9
Life, Physical, and Social Sciences 11 37.5 19 15.4 5 15.9 7 6.2 14 45.3
Community and Social Service 3 45.5 12 17.3 2 17.7 2 10.5 23 35.9
Legal 1 50.1 9 18.2 1 19.7 1 12.1 24 31.6
Education, Training, and Library 10 38.0 16 15.6 8 14.9 4 7.5 17 43.2
Arts, Entertainment, Sports, Media 15 33.2 20 15.1 15 12.5 10 5.6 9 49.3
Healthcare Practitioners and Technical 7 38.7 13 17.3 7 15.0 5 6.5 20 41.5
Healthcare Support 20 28.8 21 14.9 20 10.7 19 3.2 4 55.5
Protective Service 16 33.0 10 17.8 19 10.9 16 4.3 12 46.7
Food Preparation and Serving 24 14.0 24 8.4 24 4.5 24 1.1 2 74.2
Building/Grounds Maintenance 9 38.2 7 19.0 10 14.6 14 4.6 15 44.1
Personal Care and Service 22 26.8 23 10.9 22 9.6 6 6.3 3 60.6
Sales and Related 14 35.8 14 16.7 13 13.5 9 5.7 10 47.6
Office and Administrative Support 19 31.4 17 15.5 16 12.0 17 3.9 6 52.8
Farming, Fishing, and Forestry 18 32.1 18 15.4 17 12.0 13 4.7 7 51.0
Construction 17 33.0 5 19.3 18 11.3 21 2.4 13 45.3
Extraction 23 25.2 22 13.9 21 9.6 23 1.7 5 55.1
Installation, Maintenance, and Repair 8 38.2 2 20.6 11 14.2 18 3.4 18 42.7
Production 12 37.2 3 20.2 12 13.9 20 3.0 16 43.9
Transportation and Material Moving 13 36.1 8 18.3 14 13.3 15 4.5 11 46.8
Military 25 5.3 25 4.1 25 0.7 25 0.5 1 82.3

NOTES: Annex Table 2-1 shows the percent of male workers whose age falls within each age group in 2019 by occupation group and the rank of the occupation based on the percent of workers in that age group. Occupation groups are based on two-digit codes assigned using the 2018 version of the Standard Occupational Classification. Differences in classification versions may affect comparisons over time. Each percentage is ranked from highest percentage to lowest percentage. Occupations are listed sorted based on their ranking among all workers ages 50 and over. Percentages for ages 50–59, 60–69, and 70 and over may not sum to Ages 50+ due to rounding. Table excludes percentage of employees who are ages 40–49.

SOURCE: Data from 2019 American Community Survey Public-Use Microdata file calculated by U.S. Census Bureau online data table tool (Beta version).

Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×

ANNEX TABLE 2-3 Age Distribution Within Occupation Group Among Women, 2004

WOMEN 2004
Ages 50+ Ages 50–59 Ages 60–69 Ages 70+ Under Age 40
Occupation Rank Percent Rank Percent Rank Percent Rank Percent Rank Percent
Management Occupations 2 33.3 2 23.2 7 8.1 9 2.1 25 37.0
Business Operations 11 27.8 7 20.2 16 6.3 20 1.2 16 44.9
Financial Operations 12 26.7 11 18.0 13 6.9 16 1.8 18 44.6
Computer and Mathematical 19 21.2 13 17.6 23 3.3 23 0.4 13 48.0
Architecture and Engineering 22 19.3 22 13.8 21 4.6 22 0.8 6 53.1
Life, Physical, and Social Sciences 14 25.4 14 17.3 17 6.3 15 1.8 11 51.1
Community and Social Service 5 32.2 3 22.2 6 8.1 12 1.9 20 43.5
Legal 16 24.8 10 18.3 20 5.2 19 1.3 12 48.3
Education, Training, and Library 1 34.2 1 23.4 4 8.7 8 2.1 22 41.1
Arts, Entertainment, Sports, Media 10 28.0 15 16.9 8 8.0 3 3.1 14 47.9
Healthcare Practitioners and Technical 7 29.4 6 20.3 11 7.4 17 1.7 21 42.0
Healthcare Support 15 25.0 16 15.9 12 7.1 11 2.0 8 52.6
Protective Service 20 21.2 21 13.9 19 5.4 14 1.8 5 55.6
Food Preparation and Serving 23 17.8 24 9.9 18 5.8 10 2.0 2 65.7
Building/Grounds Maintenance 4 32.3 9 19.0 1 9.8 1 3.5 23 41.0
Personal Care and Service 13 26.2 17 15.6 10 7.5 2 3.1 9 52.5
Sales and Related 17 24.7 20 14.0 9 7.7 4 3.0 4 56.1
Office and Administrative Support 6 31.7 8 19.5 3 9.4 5 2.9 17 44.6
Farming, Fishing, and Forestry 18 22.7 23 13.3 14 6.8 6 2.7 7 52.7
Construction 21 20.4 18 14.9 22 4.0 18 1.5 10 51.2
Extraction 24 16.9 19 14.2 24 2.8 24 0.0 3 60.0
Installation, Maintenance, and Repair 8 28.7 4 20.9 15 6.7 21 1.1 19 43.5
Production 3 32.8 5 20.6 2 9.7 7 2.5 24 39.8
Transportation and Material Moving 9 28.0 12 17.7 5 8.5 13 1.9 15 46.0
Military 25 4.6 25 3.5 25 1.1 24 0.0 1 81.0

NOTES: Annex Table 2-1 shows the percent of female workers whose age falls within each age group in 2004 by occupation group and the rank of the occupation based on the percent of workers in that age group. The 2004 data is classified using the 2000 Census version of the Standard Occupation Classification. Differences in classification versions may affect comparisons over time. Each percentage is ranked from highest percentage to lowest percentage. Occupations are listed sorted based on their ranking among all workers ages 50 and over. Percentages for ages 50–59, 60–69, and 70 and over may not sum to Ages 50+ due to rounding. Table excludes percentage of employees who are ages 40–49.

SOURCE: Data from 2004 American Community Survey Public-Use Microdata file calculated by U.S. Census Bureau online data table tool (Beta version).

Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×

ANNEX TABLE 2-4 Age Distribution Within Occupation Group Among Women, 2019

WOMEN 2019
Ages 50+ Ages 50–59 Ages 60–69 Ages 70+ Under Age 40
Occupation Rank Percent Rank Percent Rank Percent Rank Percent Rank Percent
Management Occupations 6 40.2 4 22.7 8 13.9 11 3.6 23 36.2
Business Operations 12 34.8 9 19.5 12 12.7 18 2.6 16 44.2
Financial Operations 3 41.8 2 23.0 2 15.0 10 3.8 25 35.5
Computer and Mathematical 15 32.2 10 19.4 17 11.1 24 1.7 13 47.1
Architecture and Engineering 23 28.0 19 16.0 20 10.2 23 1.8 5 53.8
Life, Physical, and Social Sciences 22 28.3 23 14.0 18 10.8 13 3.5 7 53.1
Community and Social Service 9 35.9 16 17.2 9 13.8 3 4.8 18 43.3
Legal 7 38.7 7 20.2 7 14.3 6 4.3 22 39.3
Education, Training, and Library 8 37.4 13 18.1 6 14.6 4 4.7 19 41.6
Arts, Entertainment, Sports, Media 16 32.1 21 14.7 13 12.3 2 5.0 8 51.3
Healthcare Practitioners and Technical 10 35.7 14 17.9 5 14.6 16 3.3 17 43.8
Healthcare Support 13 34.4 15 17.8 11 12.8 9 3.8 12 47.5
Protective Service 20 29.5 18 16.7 23 9.5 15 3.3 6 53.6
Food Preparation and Serving 24 21.0 24 11.3 24 7.4 21 2.3 2 67.1
Building/Grounds Maintenance 2 42.0 3 22.9 3 14.9 8 4.2 24 35.6
Personal Care and Service 21 28.5 22 14.4 21 9.9 7 4.2 3 55.9
Sales and Related 17 31.4 20 15.1 16 11.7 5 4.6 4 53.9
Office and Administrative Support 1 42.9 6 20.5 1 16.9 1 5.5 20 40.1
Farming, Fishing, and Forestry 19 30.0 17 17.0 19 10.2 17 2.8 10 49.2
Construction 18 30.7 11 19.2 22 9.6 22 1.9 9 49.8
Extraction 5 40.3 1 25.8 15 12.1 20 2.3 15 45.8
Installation, Maintenance, and Repair 14 34.2 12 18.8 10 12.9 19 2.5 11 47.7
Production 4 40.5 5 22.3 4 14.7 12 3.5 21 39.9
Transportation and Material Moving 11 35.4 8 19.9 14 12.2 14 3.3 14 46.2
Military 25 5.1 25 4.3 25 0.7 25 0.0 1 85.9

NOTES: Annex Table 2-1 shows the percent of female workers whose age falls within each age group in 2019 by occupation group and the rank of the occupation based on the percent of workers in that age group. Occupation groups are based on two-digit codes assigned using the 2018 version of the Standard Occupational Classification. Differences in classification versions may affect comparisons over time. Each percentage is ranked from highest percentage to lowest percentage. Occupations are listed sorted based on their ranking among all workers ages 50 and over. Percentages for ages 50–59, 60–69, and 70 and over may not sum to Ages 50+ due to rounding. Table excludes percentage of employees who are ages 40–49.

SOURCE: Data from 2019 American Community Survey Public-Use Microdata file calculated by U.S. Census Bureau online data table tool (Beta version).

Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×

Data Sources

Except where noted, the data used in the analyses presented in this chapter are drawn from the 1965–2020 March CPS Annual Social and Economic Supplement Data Files. Results for 2019–2020 were generated from raw data files downloaded from the U.S. Census Bureau.11 Results for 1988–2018 were generated from raw data files distributed by the National Bureau of Economic Research. Harmonized data on labor force participation for 1965–1987 were generated and distributed by the iPUMS project at the University of Minnesota.

Comparisons by race-ethnicity and educational attainment begin in 2004, because prior to 2003 respondents to the CPS could not report a multiracial background, which made the creation of similar race measures over time impossible.

Results from the 2004–2018 data were reproduced and verified using the U.S. Census Bureau’s Current Population Survey Table Creator, while results from the 2019–2020 data were reproduced using the beta version of the U.S. Census Bureau’s updated Table Creator, a publicly accessible online tool that allows users to produce weighted output tables based on Census Bureau data files. This tool was also used to generate the distributions of age within occupation and occupations within age in the 2019 American Community Survey, which are displayed in Tables 4-1 and 4-2.

Calculating Labor Force Participation Rate by Birth Cohort

The average labor force participation rate was generated using a similar method to that used in Goldin and Mitchell (2017) to calculate the labor force participation rate by birth cohort among women only. Though their results applied only to women and were displayed in figures that do not depict the exact values, their figure closely matches the one corresponding figure for women presented in this chapter.

To calculate the average labor force participation rate within each 5 × 5 (five-year age group by five-year birth cohort) combination, the single-year age-specific weighted population estimate for the number of adults in the labor force was divided by the adult civilian population for each year (wave) of the CPS. Each single-year age within each survey wave was allocated to a birth cohort using the method described below under Identification of birth cohort. Then, the 25 labor force participation rates for each five-year age group and five-year birth cohort group were averaged together with equal weight. All figures include averages only when all birth cohorts had reached the oldest age in the age range. For example, because the youngest member of the 1965–1969 birth cohort was age 50 in the 2020 March CPS data, the last labor force participation rate shown for this birth cohort is for ages 45–49.

Identification of Birth Cohort

The public use data files for the CPS include reported age in years but do not include information on date of birth. Birth cohort was determined by subtracting the reported age from the year in which the survey was conducted. However, because the reference week for the March CPS is the week in which the 12th day of the month falls, most individuals would not have had their birthday by the reference week. For this reason, the labor force participation rate for each single-year age was apportioned 20 percent to the current survey year birth cohort and 80 percent to the previous survey year birth cohort.

Definition of CPS Work Disability Indicator

The CPS measure used to indicate the presence of a work disability is constructed by the U.S. Census Bureau. It is based on responses to a series of questions about health limitations, disability, and enrollment in government

___________________

11 See https://www.census.gov/data/datasets/time-series/demo/cps/cps-basic.html

Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×

programs associated with having a disability that affects an individual’s ability to work. An individual is considered to have a work disability if she/he/they meets any of the following seven criteria:

  1. The individual has a health problem or disability that prevents them from working or which limits the kind or amount of work they can do;
  2. The individual ever retired or left a job for health reasons;
  3. The individual is not in the labor force because of a disability;
  4. The individual did not work at all in the previous year because of illness or disability;
  5. The individual is under age 65 and is enrolled in Medicare;
  6. The individual is under age 65 and received Supplemental Security Income in the previous year;
  7. The individual received Veterans Administration disability income in the previous year.

It is important to note that the survey questions on which this indicator was based were not designed to measure disability, and therefore this indicator is not a comprehensive measure of the overall health of an individual or the impact of health conditions on work.

The measures included in the indicator capture different types of health limitations and disabilities. Though some of these criteria preclude an individual from remaining in the labor force, not all of them do, and many of those who report a work disability remain in the labor force. In addition, some of the criteria used to determine the presence of a work disability are age-based in ways that can affect the age-distribution of the presence of a work disability. For example, criterion five, enrollment in Medicare, is conditional on being under age 65 because only those who have a disability that affects their ability to work are eligible to enroll in Medicare before age 65. However, once such an individual turns age 65, she or he would be eligible for Medicare regardless of health status; therefore, this individual may no longer be counted as having a work disability unless she or he also met one of the other criteria, because enrollment in Medicare at ages 65 and over is no longer linked to health status. This leads to a discontinuity in the age distribution at age 65 in the work disability measure when applied to the adult population; however, because eligibility requirements for enrolling in Medicare disability coverage generally require exiting the labor force, this discontinuity is less evident when the population is restricted to those in the labor force as it is within this chapter.

Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×
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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×
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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×
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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×
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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×
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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×
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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×
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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×
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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×
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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×
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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×
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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×
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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×
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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
×
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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
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Suggested Citation:"2 The Emerging Older Workforce." National Academies of Sciences, Engineering, and Medicine. 2022. Understanding the Aging Workforce: Defining a Research Agenda. Washington, DC: The National Academies Press. doi: 10.17226/26173.
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The aging population of the United States has significant implications for the workforce - challenging what it means to work and to retire in the U.S. In fact, by 2030, one-fifth of the population will be over age 65. This shift has significant repercussions for the economy and key social programs. Due to medical advancements and public health improvements, recent cohorts of older adults have experienced better health and increasing longevity compared to earlier cohorts. These improvements in health enable many older adults to extend their working lives. While higher labor market participation from this older workforce could soften the potential negative impacts of the aging population over the long term on economic growth and the funding of Social Security and other social programs, these trends have also occurred amidst a complicating backdrop of widening economic and social inequality that has meant that the gains in health, improvements in mortality, and access to later-life employment have been distributed unequally.

Understanding the Aging Workforce: Defining a Research Agenda offers a multidisciplinary framework for conceptualizing pathways between work and nonwork at older ages. This report outlines a research agenda that highlights the need for a better understanding of the relationship between employers and older employees; how work and resource inequalities in later adulthood shape opportunities in later life; and the interface between work, health, and caregiving. The research agenda also identifies the need for research that addresses the role of workplaces in shaping work at older ages, including the role of workplace policies and practices and age discrimination in enabling or discouraging older workers to continue working or retire.

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