Census Bureau: 'Occupation, Earnings & Job Characteristics' (Part 1 of 2)

WASHINGTON, July 28 (TNSrep) -- The U.S. Census Bureau issued the following report (No. P70-178) by Clayton Gumber and Briana Sullivan entitled "Occupation, Earnings & Job Characteristics."

Here are excerpts:

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INTRODUCTION

Work is a critical component of our lives and provides a way to obtain material and nonmonetary benefits like employer-provided health insurance. Scholars suggest that our identities are also tied to the notion of "what we do" (Christiansen, 1999), and that who we are is determined partly by our occupational identity (Skorikov and Vondracek, 2011). However, work is time consuming--the American Time Use Survey shows that in 2017 workers spent an average 8.21 hours each day engaged in work and work-related activities (Bureau of Labor Statistics, 2018). Given the overarching centrality of work in daily life, researchers and policymakers have increasingly turned their attention to examining job quality.

Though it is not easily defined, job quality can broadly be described as the features of employment affecting an individual's well-being (OECD, 2014). Job quality is a multidimensional concept, with considerable disagreement regarding how to best measure it (Burchell et al., 2014; Findlay, Kalleberg, and Warhurst, 2013; Munoz de Bustillo et al., 2011). Studies examining job quality have focused on a wide range of indicators including nonwage benefits, employment security, and individual control over job schedule and autonomy (Howell and Kalleberg, 2019). Scholars also note that job quality - and more broadly work quality - may depend on workers' assessment of their own individual circumstances, values, and employment conditions (Cooke, Donaghey, and Zeytinoglu, 2013).

To further understand how some features of job quality vary across the labor market, the current report describes objective characteristics that are associated with individuals' employment and notes how these features differ by occupation. Moreover, this report evaluates the relationship between occupation and each objective characteristic separately. Because individuals may assign different value or meaning to similar jobs based on their own personal preferences, this report does not assess overall job quality or desirability./1

Using data from two surveys administered by the U.S. Census Bureau, this report highlights common features of employment among the U.S. population, including their occupations, work schedules, earnings, and other job characteristics./2

The data mainly come from the 2018 Survey of Income and Program Participation (SIPP) - a survey that is administered annually and asks respondents about their living situation and employment during the preceding calendar year./3

Select figures also use data from the 2018 American Community Survey (ACS) 1-year estimates to identify jobs with especially high or low earnings, and to highlight the earnings variation that exists within more broadly aggregated occupation categories.

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1 The overall job quality associated with an occupation likely depends on the joint relationship between occupation and all objective characteristics. This report does not attempt such an analysis.

2 The U.S. Census Bureau reviewed this data product for unauthorized disclosure of confidential information and approved the disclosure avoidance practices applied to this release. CBDRB-FY21-POP001-0225.

3 For technical documentation and more information about SIPP data quality, please visit the SIPP website's Technical Documentation page at <www.census.gov/programs-surveys/sipp/ tech-documentation.html>.

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ABOUT THE DATA

The Survey of Income and Program Participation

The Survey of Income and Program Participation (SIPP) is a nationally representative, longitudinal survey administered by the U.S. Census Bureau that provides comprehensive information on the dynamics of income, employment, household composition, and government program participation. In addition, the SIPP collects information on workers' full employment history during the year. If respondents hold more than one job, or change jobs during the year, the SIPP asks about each job they worked. In total, the SIPP collects detailed information on up to seven jobs worked during the year and summary characteristics on all additional jobs beyond the first seven. Because employment data are available at a weekly level, workers can also indicate whether they were unemployed or away from a specified job at any point during the year. The 2018 SIPP data used in this report reference the 2017 calendar year. For more information, visit the SIPP website at <www.census.gov/sipp>. Additional information about how the SIPP collects summary characteristics is available online at <www.census.gov/programs-surveys/sipp/tech-documentation/usernotes/2018-usernotes/2018-other-jobs-section.html>.

The American Community Survey

The American Community Survey (ACS) is an annual survey administered to over 3.5 million addresses across the United States (including Puerto Rico) that collects information on the nation's demographics, housing, and employment. In contrast with the SIPP, the ACS only asks workers about their current or most recent job. If ACS workers hold two or more jobs concurrently, they are asked only to describe the job at which they work the most hours. If respondents did not have a job in the last week, the ACS instead asks them to describe the job at which they most recently worked within the past 5 years. Although the 2018 ACS 1-year estimates reference the 2018 calendar year, they are used in this report to supplement selected findings from the SIPP since both surveys use the 2018 Census Occupation Code List. For information on the ACS sample design and other topics, visit <www.census.gov/programs-surveys/acs/>. For more information about the 2018 Census Occupation Code List, refer to <www.census.gov/topics/employment/industry-occupation/guidance/code-lists.html>.

Report Universe

The universe for the SIPP and ACS estimates in this report consists of employed, civilian, noninstitutionalized workers 16 years or older. People living outside the United States or in Puerto Rico, as well as unpaid family workers, are excluded from all estimates. Given the longitudinal nature of the SIPP, this report focuses exclusively on the first job listed chronologically for December 2017 to identify how individuals' employment characteristics are associated with a specified job. For people holding multiple jobs in December 2017, the first job listed is the one held longest. In some cases, a person's first job listed in December 2017 may not correspond with the job in which they worked the most hours during the year (for example, if the worker switched jobs in November). Workers who reported zero hours worked in December are excluded, as are workers who only reported summary characteristics about their job. Additionally, to avoid making comparisons with the unemployed or people who were not in the labor force, this report focuses only on those individuals in the ACS who reported they were employed during 2018.

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HIGHLIGHTS

* Over 30 percent of workers were employed in just three occupation groups: management (11.3 percent), office and administrative support (10.2 percent), and sales and related (9.5 percent).

* A standard, daytime schedule was the most common schedule arrangement for all workers. More workers (86.5 percent) reported their type of work schedule as a requirement of the job over any other reason, such as better child care arrangements.

* In the 2018 SIPP, the median monthly earnings for legal, architecture and engineering, and computer and mathematical occupations were higher than all other occupation groups, but not significantly different from each other. Among detailed occupations in the 2018 ACS, those with the highest annual earnings mainly comprised jobs within the broader group of health practitioners and technical occupations.

* Over 91 percent of all workers were paid a wage or salary. Workers can also receive commission, tips, overtime, and/ or bonus pay, either to supplement their wage or salary or as stand-alone earnings.

* A majority of workers with private health insurance coverage (approximately 86 percent) were covered by an employer-provided health insurance plan. Among workers receiving this type of coverage, about 73 percent in the private sector, 82 percent in government jobs, and 37 percent of the self-employed were policyholders.

WORKERS' DEMOGRAPHIC AND EMPLOYMENT CHARACTERISTICS

In the SIPP, work arrangements are classified in three ways: (1) employer-paid workers employed on a continuing basis, (2) self-employed workers who work for profit or fees in their own business, and (3) workers with other work arrangements, such as freelancers, consultants, or contractors, whose work may include informal, limited-time agreements.

According to the 2018 SIPP, in December 2017, 61.4 percent of the civilian, noninstitutionalized population 16 years or older had at least one job for a minimum of 1 week. Tables 1 and 2 present the demographic and employment characteristics of these workers./4

These tables highlight general features of the labor force and provide a baseline for understanding how certain jobs align with demographic characteristics like sex and race/ethnicity.

As shown in Table 1, the median age of workers was 41, and 81.1 percent of the employed population was between the ages of 25 and 64. Males held a slightly larger share of jobs: 52.7 percent of the employed population was male, and 47.3 percent of the employed population was female.

About 63 percent of workers were White, non-Hispanic; 11.7 percent were Black, non-Hispanic; 5.9 percent were Asian, non-Hispanic; and 17.0 percent were Hispanic.

Approximately 92 percent of workers had at least a high school diploma, and 67.2 percent of workers had at least some college.

Table 2 lists selected employment characteristics of the employed population./5

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4 All comparisons made in this report have undergone statistical testing and are significant at the 90 percent confidence level, unless otherwise noted.

5 If respondents held two or more jobs concurrently, then part- or full-time employment and class of worker were determined by the first job listed.

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TERMS AND DEFINITIONS

Occupation: The kind of work performed by people in their jobs. Occupations are classified into 570 specific occupational categories and arranged into 23 major occupational groups according to the 2018 Census Occupation Code List.

Class of worker: The ownership type of a worker's employer. Categories include private (for-profit or not-for-profit), government (federal, state, or local), and self-employed (incorporated or unincorporated).

Earnings: All monetary compensation from a work arrangement. This includes wages and salaries, commissions, tips, overtime, and bonus pay, as well as any profits or losses reported by self-employed workers.

Employer-provided health insurance: A health insurance plan obtained through an employer.

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Table 1. Demographic Characteristics of Employed Workers: 2017 (Employed, civilian, noninstitutionalized population, 16 years and older)

Source: U.S. Census Bureau, 2018 Survey of Income and Program Participation.

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Table 2. Employment Characteristics of Employed Workers: 2017 (Employed, civilian, noninstitutionalized population, 16 years and older)

Source: U.S. Census Bureau, 2018 Survey of Income and Program Participation.

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About 93 percent of workers held only one job in a given week in December 2017; 7.2 percent held at least two overlapping jobs for more than 1 week./6

Additionally, 76.6 percent of workers worked full-time, or a minimum of 35 hours per week, at their first-listed job./7

Workers in the private sector (across both for-profit and not-for-profit employers) made up the largest share of workers, about 75 percent. Government workers comprised 14.0 percent, and 11.1 percent were self-employed workers.

About 39 percent of the businesses owned by self-employed workers were incorporated. Of the 60.6 percent of self-employed workers whose businesses were unincorporated, 84.6 percent were sole proprietorships.

Workers' Occupations

Occupation broadly refers to the kind of work a person does on a job. Generally, occupations vary in observable characteristics that may correspond to overall job quality, such as their employment criteria, work conditions, and offers of employee benefits or rewards. To this end, Williams, Zhou, and Zou (2020) noted how jobs in different socioeconomic classes (largely grouped by occupation) will generally correspond with broad differences in job quality. Yet it is also possible that jobs may vary within these wider categories due to the individual indicators composing job quality.

In surveys administered by the Census Bureau, occupations are categorized by individuals' reported duties and activities while at work. In both the SIPP and the ACS, a person's occupation is determined through two open-ended questions. The first question asks people about the kind of work they perform in their job, while the second question asks about their usual activities completed at work. Responses to both questions are recorded verbatim and assigned a 4-digit numeric occupation code from the 2018 Census Occupation Code List.8 Excluding military-specific occupations, there are 570 possible occupations split among 23 major occupation groups.

Figure 1 shows the distribution of occupations in the SIPP. Overall, management (11.3 percent), office and administrative support (10.2 percent), and sales and related (9.5 percent) were among the largest groups of jobs in 2017. In contrast, legal (1.2 percent); life, physical, and social science (1.2 percent); and farming, fishing, and forestry (0.5 percent) were among the smallest groups./9

Type of Work Schedule

Schedule arrangements are another important factor related to job quality. Specifically, "good jobs" are often typified as those that offer workers steady employment and a favorable work/life balance (Howell and Kalleberg, 2019). To this end, the SIPP asks workers about their type of schedule for each job reported. Survey questions ask about the days each week that individuals work, the time their work usually begins and ends, and the reason for the reported schedule. For this report, type of work schedule was measured using three broad categories: (1) a standard, daytime work schedule; (2) a nonstandard, but predictable, work schedule; and (3) a nonstandard and unpredictable work schedule./10,11

Table 3 presents the share of workers in each of the three work schedule categories by occupation. Overall, about 75 percent of workers in the SIPP reported a standard, daytime schedule for their job. This type of work schedule was also the most common arrangement across the 23 occupation groups examined./12

Further, an especially high percentage of workers (about 90 percent) held a standard, daytime schedule among four occupation groups: business and financial operations, computer and mathematical, architecture and engineering, and legal occupations./13

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6 For more information on the patterns and extent of multiple jobholding, refer to "Multiple Jobholders in the United States: 2013" at <www.census.gov/library/publications/2019/demo/p70br-163.html>.

7 "Hours worked per week" is defined as the total number of hours worked in December for a respondent's first job listed chronologically divided by the number of weeks worked in December at that job. Unpaid leave from a job and time away without pay are not included in calculations for average hours worked per week.

8 For more information, refer to <www.census.gov/topics/employment/industryoccupation/guidance/code-lists.html>.

9 The percentage of workers in life, physical, and social science occupations was not significantly different from the percentage of workers in legal occupations.

10 The measure used in this report for type of work schedule is consistent with that of Lozano, Hamplova, and Le Bourdais (2016).

11 For this report, a nonstandard, predictable work schedule is defined as a regular evening or night shift, rotating shift, or split shift. A nonstandard, unpredictable work schedule is defined as any other kind of irregular work schedule.

12 Only in food preparation and serving related occupations were nonstandard schedules (either predictable or unpredictable) more common relative to standard schedules. Protective service occupations had no statistically significant difference between the share of workers reporting a nonstandard or standard schedule.

13 There was no statistically significant difference between the share of workers holding a standard, daytime schedule for business and financial operations, computer and mathematical, architecture and engineering, and legal occupations.

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Figure 1. Percentage of Employed Workers by Occupation Group

Source: U.S. Census Bureau, 2018 Survey of Income and Program Participation.

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About one-quarter of workers in the SIPP were not employed in a standard, daytime schedule arrangement. Among those working a nonstandard schedule, more workers had a predictable work schedule (14.0 percent) as opposed to an unpredictable schedule (11.4 percent). Predictable schedule arrangements also were more prevalent among select occupation groups. For instance, over one-quarter of people in material moving (30.4 percent), protective service (36.0 percent), and food preparation and serving related (39.8 percent) occupations reported working nonstandard, but predictable, schedules./14

Two occupation groups had about 25 percent of workers reporting a nonstandard and unpredictable work schedule: arts, design, entertainment, sports, and media; and transportation./15

One factor that may also affect the relationship between work schedule arrangements and job quality is whether individuals had control over their reported schedule. Alongside type of work schedule, SIPP workers are asked about the main reason for their reported schedule. They select that reason from a list of involuntary or voluntary reasons, such as a requirement of the job or better child care arrangements.

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14 There was no statistically significant difference between the share of workers holding a nonstandard, but predictable, schedule for protective service and food preparation and serving related occupations.

15 There was no statistically significant difference between the share of workers holding a nonstandard, and unpredictable, schedule for arts, design, entertainment, sports, and media, and transportation occupations.

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Table 3. Schedule Arrangements of Employed Workers Within Occupation Group

Note: A standard schedule is defined as a regular daytime schedule. A nonstandard, predictable schedule is defined as a regular evening or night shift, rotating shift, or split shift. A nonstandard, unpredictable work schedule refers to any other kind of irregular work schedule.

Source: U.S. Census Bureau, 2018 Survey of Income and Program Participation.

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Overall, most workers (86.5 percent) indicated their schedule was a "requirement of the job." However, workers' reasons for reported schedule differed by sex and race (Table 4). Compared with men, women less often indicated their schedule was a work requirement (88.5 percent and 84.1 percent, respectively). More women than men also indicated improved caregiving arrangements - either better child care arrangements, or better arrangements for the care of other family members - as a main reason for their reported work schedule. Concerning differences by ethnicity and race, Hispanic and White, non-Hispanic workers also cited job requirements as the main reason for their schedule arrangement (87.2 and 86.9 percent, respectively) more often than Black (84.5 percent), Asian (84.5 percent), and workers of other races (83.2 percent)./16

Figure 2 shows how workers' reasons for their schedule differed across occupations. By occupation, the share of workers citing "requirement of the job" as the reason for their work schedule varied between 75 and 93 percent. Occupations in which more workers had standard schedule arrangements also had a larger share of workers whose schedule was a requirement for their job. Conversely, workers in nonstandard schedule arrangements less frequently reported their schedule was a job requirement. For example, only about 75 percent of people in arts, design, entertainment, sports, and media occupations - which are among those occupations with the largest share reporting a nonstandard and unpredictable work schedule - reported their schedule arrangement as a job requirement./17

Similarly, about 80 percent (or fewer) of workers indicated that their job schedule was a job requirement in personal care and service (78.5 percent), food preparation and serving related (78.6 percent), and healthcare support (80.1 percent) occupations./18

Workers in food preparation and serving related and healthcare support occupations were also more likely to report a nonstandard, predictable schedule than the average worker.

Work schedule can also be quantified using hours worked per week. Table 5 lists the percentage of workers employed in each occupation group by part-time and full-time status in December 2017. Across all occupations, 23.4 percent of workers worked part-time at their first-listed job, and 76.6 percent of workers worked fulltime. Among those who worked full-time, 22.3 percent worked over 50 hours per week.

But, as Table 5 illustrates, there is large variation in hours worked per week across occupations. Computer and mathematical occupations were among those with the lowest rates of part-time work only - 8.7 percent of workers in these occupations worked part-time./19

Management occupations were among those with the highest rates of working at least 50 hours per week (33.6 percent); as shown in Figure 2, about 91 percent reported their schedule was a requirement of the job.

Food preparation and serving related and personal care and service occupations were among those with the highest rates of part-time work (49.1 and 52.6 percent, respectively)./20 Food preparation and serving related occupations also were among those with the lowest rates of working 50 hours or more per week (6.1 percent)./21 However, it should be noted that this analysis focuses only on respondents' employment in one job and does not show whether a person worked 50 hours or more across multiple jobs in the same occupation group.

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16 Among workers reporting their schedule as a requirement for their job, the percentages were not significantly different between Hispanic and White, non-Hispanic workers. Similarly, the percentages were not significantly different between Black, Asian, and workers of other races.

17 There was no statistically significant difference between the share of workers reporting their schedule arrangement as a "requirement of the job" for arts, design, entertainment, sports, and media; food preparation and serving related; and personal care and service occupations.

18 There was no statistically significant difference between the share of workers reporting their schedule arrangement as a "requirement of the job" for personal care and service, food preparation and serving related, and healthcare support occupations.

19 The percentage of part-time workers was not statistically different between the following occupation groups: computer and mathematical; production; and installation, maintenance, and repair.

20 The percentage of part-time workers in food preparation and serving related occupations was not significantly different from the percentage in personal care and service.

21 The percentage of full-time workers reporting 50 hours or more per week was not significantly different between office and administrative support, healthcare support, and food preparation and serving related occupations.

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Work From Home

In addition to work schedule, job flexibility can be characterized by the ability to work from home. For some workers, working from home can give them more freedom to determine their own work schedule, allowing them to plan work around other nonwork commitments like child care. Working from home also reduces the time spent commuting. For some, this time can instead be devoted to leisure activities or responsibilities outside of work. For others, this time may translate into working additional hours, which can contribute to overwork since the boundaries between work and leisure can become less defined when working from home. Another disadvantage of working from home is that it reduces opportunities to engage with coworkers or clients in person (UNECE, 2015).

For each job reported in the SIPP, workers are asked to report the days of the week worked (Monday through Sunday). They are also asked whether any days are worked entirely at home, and if so, which days. Therefore, the SIPP can be used to estimate the prevalence of working from home. Table 6 presents the share of workers who worked any days entirely from home; among those who worked from home, it lists the mean number of days worked from home and the mean share of the workweek spent working from home (defined as the number of days worked from home divided by the number of days worked in a week).

Prior to 2020, working from home was not a common option. Only 13.6 percent of all workers worked at least 1 day per week from home in December 2017./22,23 Those who worked from home did so 4.1 days on average, or 77.4 percent of the workweek.

To better understand the type of workers who were more likely to work from home, estimates in Table 6 are separated by class of worker. About 42 percent of self-employed workers worked from home, compared to 10.4 percent of private sector workers and 8.3 percent of government employees. Among those who worked from home, government and private workers worked fewer days per week at home than did self-employed workers (3.5 and 3.8 days, respectively, relative to 4.8 days).

Moreover, within class of worker, there is variation in the share of individuals working from home and the average number of days worked from home. Among government workers, federal employees were more likely than state or local employees to work from home (15.9 percent relative to 9.4 and 3.9 percent, respectively). However, among those who worked from home, federal employees only worked an average of 2.5 days per week from home, while state and local workers worked about 4 days per week from home./24 Self-employed workers who owned incorporated businesses were slightly less likely than those owning unincorporated businesses to work from home (39.3 percent relative to 43.5 percent), and they spent a smaller share of their workweek working from home (81.9 percent relative to 88.1 percent).

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22 Because the 2018 SIPP data were collected before the COVID-19 pandemic, work-from-home trends described in this report may not reflect current estimates. In fact, Bloom (2020) finds that in May of 2020, about 62 percent of the individuals in a survey of 2,500 U.S. residents aged 20 to 64 were working from home.

23 For more information about how work-from-home trends changed during the COVID-19 pandemic, refer to <www.census.gov/library/stories/2021/03/working-from-home-during-the-pandemic.html>.

24 There was no statistically significant difference in the average number of days worked from home between state and local employees.

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Table 4. Reason for Work Schedule by Sex, Race, and Hispanic Origin

Source: U.S. Census Bureau, 2018 Survey of Income and Program Participation.

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Figure 2. Percentage of Workers Reporting the Work Schedule Was a "Requirement of the Job"

Source: U.S. Census Bureau, 2018 Survey of Income and Program Participation.

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Continues with Part 2 of 2

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The report is posted at: https://www.census.gov/content/dam/Census/library/publications/2022/demo/p70-178.pdf