Report | Unions and Labor Standards

Part-time workers pay a big-time penalty: Hourly wages-and-benefits penalties for part-time work are largest for those seeking full-time jobs and for men, but affect more women

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There is a penalty for working part time in America that goes beyond the lower annual earnings and fewer employee benefits that part-time workers get. Part-time workers are also face an hourly wage penalty: they are paid 29.3% less in wages per hour than workers with similar demographic characteristics and education levels who work full time. And when controls for industry and occupation are added, part-time workers are paid 19.8% less than their full-time counterparts. This part-time wage penalty is on par with the gender and racial wage penalties in the United States.

This report provides new analysis of data on the part-time wage penalty overall, by race/ethnicity and gender, and by the reasons workers give for working part time. White men and black men suffer the largest wage penalty for working part time. However, because women constitute a disproportionate 60% share of the part-time work force, they bear the brunt of the wage penalty for working part-time jobs. Moreover, the part-time wage penalty is worse for people who work part time but want full-time hours, relative to part-time workers who cannot or do not want to work full time. In addition, there is a broader compensation penalty in employee benefits, faced by part-time workers, in particular part-time workers employed in service occupations. (Note: penalties are calculated using 2003–2018 microdata from the Current Population Survey.)

Following are the key findings from the report:

  • Part-time workers earn 29.3% less per hour worked than other workers with similar demographic characteristics and education levels.
  • The part-time wage penalty is smaller but still substantial, 19.8%, when the worker’s industry and occupation (as well as demographics and education) are controlled (these controls yield the “fully adjusted wage penalty.”) This reduction with the industry and occupation controls added suggests that a share of the wage penalty is attributable to being relegated to certain lower-paying sectors or job types dominated by part-time work.
  • By race and ethnicity, the fully adjusted wage penalty is across the board—it is 20.7% for white workers, 20.2% for African American workers and 14.2% for Hispanic workers, suggesting majority workers are just as prone to the part-time wage penalty.
  • By gender, the adjusted wage penalty is 15.9% for women and 25.8% for men, suggesting that men pay a noticeably higher price for working part time. However, women constitute nearly two-thirds (63.3% in 2019) of those employed part time, and are much more likely to work part time: 22.8% of all female workers work part time, compared with 11.8% of all male workers in 2019). Thus, a greater proportion of women than men bear the brunt of the wage penalty, albeit smaller in size relative to the part-time men.
  • By gender and race, white men face the highest wage penalty, at 28.1%, followed by black men at 24.6%, while the penalty for black women is 17.2%, for white women it is 16.4%, and for Hispanic men it is 16.9% while it is 12.3% for Hispanic women. The racial gap in part-time wage penalties likely reflects a combination of whites’ advantage in wage rates at their full-time jobs along with a shared disadvantage when they are in part-time jobs.
  • The part-time wage penalty is greater for those working part time but wanting a full-time job (i.e., those whose reasons for working part time are categorized by the BLS as “for economic reasons,” which includes “slack work or business conditions” and “could only find part-time work”). Part-time workers who say they work reduced hours because of “slack work or business conditions” experienced a 22.3% wage penalty, while those who say they work part time because they “could only find part-time work” experienced a 29.5% wage penalty. Those working part time for “noneconomic reasons” (such as child care problems and family or personal obligations) still experienced a wage penalty, 18.3%, though a smaller-sized penalty than those who were part time for “economic reasons.” (Though respondents who work part time for “noneconomic reasons” may prefer to work full time if, say, they could afford child care, they are not included in the standard count of part-timers who want full-time work.)
  • The penalty for part-time workers who want full-time work can be characterized as a double penalty: they are constrained to working fewer hours than they want and thus have lower total earnings, while they also make less for each hour they do work.
  • There has been a notable increase in the part-time pay penalty over time. A 2005 study by Barry T. Hirsch, using data from 1995–2002, found a part-time pay penalty of about 10% for women and 22% for men. Our present analysis using a comparable method but with 2003–2018 data show a pay penalty of about 16% for women and 26% for men. Since the hourly pay penalty estimates control for year, this 6 percentage-point increase for women and 4 percentage-point rise for men likely reflects some kind of change in the labor market affecting both genders in the more recent period, beyond that attributable to just the Great Recession.
  • Part-time workers face even more of a disadvantage in benefits than in wage rates. Benefits make up about 20.1% of full-time workers’ compensation, but only about 16.4% of part-time workers’ compensation. The inequity in benefits means that the compensation penalty (including wages and benefits) is a full 5.5 percentage points larger than the wage penalty. Thus, a part-time worker on average faces a full compensation penalty of 25.3%–a 5.5% benefit penalty on top of the 19.8% wage penalty.
  • Policy priorities should include an array of reforms directed toward all part-time jobs, not just its incumbents, to address the large and apparently growing inequity in both wages and in benefits. Reforms could specifically promote more pay parity and income-earning opportunities for workers with relatively shorter weekly hours, specifically for those who work part time but prefer to work longer or full-time hours.

Introduction and overview: Part-time working—why should we care?

Part-time work is an essential component of the labor market for both employers and employees. Working part time can be both a blessing and a curse for workers. It is more of a blessing if a part-time job provides the incumbent worker with the number of work hours and schedule that meets their needs or preferences for working, without unduly sacrificing other aspects. Indeed, part-time positions originated to integrate those who might otherwise prefer to be entirely out of the labor force. It is more of a curse when the job provides chronically fewer than preferred hours, schedules that fluctuate so much that they create rather than resolve time conflicts with other commitments and, our focus in this paper, reduced wages and benefits for those whose hours are shorter, even if seemingly preferred. Employers benefit from the partial commitment as well, to cover or extend their office, shop, or opening hours; receive human capital that complements their full-time work force; and have buffer stocks of employees to cushion their labor demand for unforeseen cyclical fluctuations. Employers also benefit from their short-term cost savings.

Part-time employment constituted just under 17% (16.9%) of the work force in 2019, a bit higher than the 16% rates witnessed in the pre-recession 2000s, although lower than the spike of up to 20% after the recession (BLS 2020a; BLS 2020b). About one in six (17.1%) of part-time workers explicitly prefers a full-time workweek (i.e., the reasons they give for working part time are categorized by the BLS as “economic reasons,” which includes “slack work or business conditions” and “could only find part-time work”). The number of people working in part-time jobs in the U.S. economy who explicitly prefer to work full-time hours in 2019 was about 4.3 million. This number has declined since the start of the recovery in 2009 from more than 9 million workers but remains above the 4 million observed before the Great Recession;  in percentage terms, part-timers who explicitly prefer full-time work declined from over 6% of the overall workforce to nearly 3% (BLS 2020a; BLS 2020b; Valletta, Bengali, and van der List 2020). Moreover, part-time working for what the BLS considers “noneconomic” reasons (which others sometimes label “voluntary” part-time work) has been increasing in number, and remains consistently greater than 20 million (Dunn 2018; BLS 2020a; BLS 2020b). While not traditionally counted among those explicitly preferring full-time work, many of these “voluntary” part-time workers also are constrained by the inadequate systems of child care and support for the disabled and elderly, effectively forcing the “choice” of part-time working to fulfill family responsibilities.

Part-time working, and its associated wage and benefit penalties and frequent underemployment, is about 17 times as common as the attention-getting “gig”/on-demand platform-based jobs (Appelbaum and Rho 2018).1 Given that part-time working remains so prevalent, not only with a cyclical element but with an apparent structural change, part-time work conditions matter more greatly than ever (Kroll 2011; Golden 2016; Glauber 2017; Valletta 2018; Borowczyk-Martins and Lalé 2019; Bell and Blanchflower 2019).2

Furthermore, “involuntary” part-time work is more widespread than conventional measures show. A forthcoming report from the Center for Law and Social Policy (Golden and Kim 2020) creates a more complete picture than BLS measures of “involuntary” part-time working, for three reasons. One is because the former captures part-timers who want to work more hours, but not necessarily full time. A second is because part-time workers who hold multiple jobs to piece together full-time (35 or more) hours are actually not counted as part-time workers by BLS. Third and finally, because working parents who take part-time jobs because of “child care problems,” which might include a lack of affordability or availability, are actually not counted as involuntary part-time workers. The data published in the upcoming CLASP report provides a more accurate analysis of what it calls “underemployment”—workers who desire more hours—finding that the share of total employed that were part-time and underemployed is double the rate suggested by BLS using the CPS data.

Because part-time work is here to stay, it is crucial to provide a fresh look at the relative wage and benefit rates of part-time work vis-à-vis full-time work, the extent of the existing “wage penalty” for working part time, and the causes of such a penalty. How much of this wage disadvantage reflects characteristics of how part-time workers are treated versus their personal attributes? Which workers face bigger (or no) penalties? Have wage gaps between part-time and full-time jobs decreased or increased over time? Are penalties different for people who say they work part time for noneconomic reasons such as child care issues and family or personal obligations (which we consider “reasons of choice under constraint”) than for those who explicitly say they would prefer full-time working (i.e., they say they work part time for economic reasons such as slack work or the inability to find full-time work)? Do penalties differ between those whose hours are closer to the full-time workweek vs. those with only very short weekly hours? In addition to wage rate gaps, what are the differences in various benefits coverage for part-time jobs versus full-time jobs, so that we can assess a “full compensation” penalty?

The part-time penalty consists of three main elements—hourly wage rates, nonwage benefit and social insurance coverages, and inadequacy and volatility of work hours (i.e., “schedule variability”). Though this report focuses on the compensation penalties, Lambert, Fugiel, and Henly (2015); Schneider and Harknett (2019) and McCrate, Lambert, and Henly (2019) show workweek and schedule variability as a third aspect of part-time workers’ work condition disadvantage.3 This paper explores the current wage and benefits penalties associated with part-time work, and differences by type of worker, as well as by their reason for working only a number of hours associated with part-time jobs.4 The size and distribution of these wage penalties should inform public policy measures to address existing or growing wage and benefit gaps of part-time jobs and their incumbents.5

As we seek to answer these questions, we build on the existing body of research that confirms that part-time wage and benefit penalties matter. We take a special look at the roughly one in six part-time workers who works fewer than 35 hours per workweek either because of business conditions or slack work, or because they cannot find a full-time job (2019 data from BLS 2020a). Our analyses confirm what past research has indicated: that these part-time workers for economic reasons suffer not only from shortened hours (akin to the adverse effects experienced by the unemployed), but also from a large pay rate per-hour penalty just for being part time (Glauber 2013; Zukin and Van Horn 2015; Horemans, Marx, and Nolan 2016; Mousteri, Daly, and Delaney 2020).6 Studies have also shown that such underemployment tends to disproportionately burden certain labor force subgroups—males, youth, Hispanics, immigrants and also blue-collar job holders (Kler, Potia, and Shankar 2017; Young and Mattingly 2016; Wilkins and Wooden 2011). The median income for families in which women work part time for economic reasons is far lower than for women ostensibly working more “voluntarily” part time (i.e., for noneconomic reasons (Glauber 2013)). (Contrary to common practice, we avoid labeling people who work part time for noneconomic reasons as those working “voluntarily” part time because someone who works part time to deal with child care issues or family or personal obligations is likely facing constraints that restrict their choices.) The proportion of part-time workers who are the “primary earners” in their households has risen over time.7 These part-time primary earners appear to face a relatively higher risk of poverty and be more likely to not have health insurance.8

The structure of the paper is as follows. It begins with a condensed review of the existing literature and descriptive evidence on the meaning and measurement of part-time compensation differentials. It then explains how we replicated and updated a systematic analysis of the part-time wage penalty that was definitive but used data from 1995 to 2002. In brief, as we explain, we pool the cross-sectional data from the U.S. Current Population Survey (CPS) Outgoing Rotation Group (ORG) files from 2003 through 2018 to form a large data set with more than 1.7 million observations. Three estimates of the part-time wage gap are constructed—a raw estimate, one adjusted partially (just for workers’ demographic characteristics and education), and a third adding adjustment fully, including for workers’ industry sector and occupation of employment. Following the methodology discussion is a section presenting key findings. As we discuss in more detail, the results show that the size of the wage penalty not only is substantial, but it has increased in size since the period ending in the early 2000s. The size of the wage penalties by race/ethnicity, gender, reason for working part time, and number of weekly hours are reported. In addition, the potential gulf in employee benefits coverage between part-time and full-time jobs then is estimated in order to complete the picture of the potential full compensation—wage and benefit—disadvantage for those working part time.

Literature review: Conventional versus alternative explanations of the part-time wage differential

Why might wage rates per hour be lower for part-time workers relative to full-time workers? The part-time hourly wage penalty reflects a combination of possible factors (Messenger and Ray 2015). Labor economic theory suggests that there may be lower human capital among part-time job incumbents, such as skills and experience, as compared with full-timers (Montgomery 1988). This would reduce part-time workers’ relative wages. In addition, part-time workers’ fixed costs, on a per-hour basis, may be relatively higher than per-hour costs of full-time workers. Thus, a wage differential found for part-time workers might reflect a traditional, equilibrium-compensating wage differential in hourly wages for part-time work (Blau and Kahn 2017; Goldin 2014; Friesen 1997)—although this would discount the gap as a pure penalty. Workers can be heterogeneous not only in skills, but also in preferences and job search. If workers prefer shorter hours, then “part-time wage differentials can result from differences in labor supply” factors (Hirsch 2005). In addition, a part-time wage differential can arise if workers are willing to take lower-paid part-time jobs as a way of queuing for higher-paying, full-time jobs (Hirsch 2005).9 Finally, to the extent that a part-time job provides a job amenity, e.g., schedule flexibility, the wage payment could be reduced and still attract and retain labor. Workers might choose part-time employment at least in part to comply with the role(s) or identity to which they adhere, perhaps at stages in their life cycle, working part time to better integrate the competing claims on their time made by their different roles (Russo 2012), thus they would be “willing to accept low wages” (Hirsch 2005).10 Moreover, in cases when the fixed costs per hour worked are higher for part-time workers, their wage rates might be adjusted downward, as an equalization of all labor costs. A wage differential for part-time workers can arise when workers are not fungible (homogeneous) and the employers have preferences regarding how they schedule hours among workers.11

On the other hand, part-time working might be more productive per hour if there are fatigue effects in the quantity of output (if not quality) over the course of a workday or workweek.12 The higher the skill level of employees, the higher might be both the administrative costs and their relative productivity rate per hour. Higher productivity per hour, and thus higher marginal revenue product for an hour of part-time work, would reduce the wage penalty and might even create a wage premium.13 Thus, differences in preferred hours are not a sufficient condition to produce a wage penalty for all part-time jobs, if part-time workers have identical skills and create no fixed labor costs to employers—wages would equalize as employers create a mix of jobs only to reflect the preferences of employees. For example, part-time work might command a premium if these two part-time positions generate greater productivity than one full-time job sufficient to more than overcome the fixed costs. In addition, there may be a compensating wage differential necessarily developed to recruit into and retain workers in part-time positions, given the other adverse working conditions, in particular, the fewer or outright lack of employee benefits, as well as undesirable schedule times or variability.

Thus, hourly wage rates for part-timers compared with otherwise comparable full-timers might reflect either a negative wage penalty or a positive pay premium. However, this also depends on whether employers share the financial benefits—the income from greater relative productivity or lower compensation costs per hour derived from hiring part-time workers—with the workers themselves in the form of a wage boost. Certain part-time workers indeed generate such gains (i.e., “rents”) for their employers, either from their relatively higher productivity per hour or relatively lower wage rates paid (Garnero, Kampelmann, and Rycx 2014). Thus, depending on the bargaining power of employers or employees, there may be a wage premium for some and a wage penalty for others (Jepsen et al. 2005; O’Dorchai, Plasman, and Rycx 2007).

While the more conventional explanations of the penalty dominate much of the economic theory and testing of the wage differential between full-time and part-time workers, valid alternative explanations of the size of the penalty involves labor market power, job downgrading, and outright discrimination. When labor market conditions are not very tight or employers have some monopsony power, they may be more able to exploit the vulnerabilities of workers with more limited options—those who need jobs that provide some income but allow time for family or personal reasons.14 Moreover, polarization (i.e., dualism) in labor markets suggests that certain jobs, including many part time, are structured simply to contain short-run labor costs and disconnect from full-time, regular positions (Tilly 1996; Howell and Kalleberg 2019; Fernández-Kranz and Rodríguez-Planas 2011; Benton, Kim, and Wilmers 2018). Thus, the larger the gap between part-time workers and otherwise comparable full-time workers, the more it reflects how employers may treat incumbents as second-class citizens, unworthy of the full value of their productivity.

The “gross” or “raw” wage gap—a simple comparison of part-time and full-time hourly wages —typically is considered as the average wage differential between part-time and full-time workers in a given sample. The size of the penalty or premium is an empirical issue. There is mixed evidence, with quite a wide range of estimates. Much of the research starts by estimating the “unadjusted” or “raw” wage difference between part-time and full-time jobs or work per hour. This is an important first estimate because it relates most directly to workers’ choices in the labor market regarding hours of work and to consequences of those choices for their income. Estimations typically then adjust this raw differential for demographic and human capital factors such as age, experience in the labor market, education, etc., to get an “adjusted” penalty (or premium). This typically lessens the size of the penalty, by controlling for the additional experience and education that full-time workers have compared with part-time workers, on average (Baffoe-Bonnie 2004). In addition, full-time workers are more likely to have better benefits, like pensions, and be represented by unions (Bishow 2015; BLS 2019).

Previous research notes at least some pay penalties, but considerable variation in the size of same. Virtually all research indicates the adjustments to control for these differences in worker and job characteristics considerably reduce the national wage differential between full-time and part-time workers, given the substantial variation across regions and industries in full-time versus part-time composition. Studies within specific industries and occupations suggest there are part-time penalties, but these are much reduced or quite small when controlling for schooling, experience, occupation, and establishment size.15 In the United States, the raw wage penalty for part-time working men was as high as a 67% (meaning men working part time made as much as 67% less than men working full time), while among women, this was on the order of about 22% (Bardasi and Gornick 2008; O’Dorchai, Plasman, and Rycx 2007). The size of the penalty in the United States generally gets reduced by about 10% when fully adjusted with controls (Fallick 1999). A sizable average part-time wage penalty of 21%–26% for men and 19% for women—was found using earlier cross-sectional data (Blank 1990, 1998).16 With data from 1995–2002, Hirsch (2005) intended to update and reestimate this. Without any controls for demographic and work characteristics in the full sample for the raw wage penalty, there was a pay gap of 49% among men and 26% for women. Adding these controls, there was a 37% penalty for men and about 20% for women.17 With the full battery of typical control variables (personal and location variables, industry, and occupation), the part-time wage penalty was 10% for women and 22% for men (or 9 and 19 log points difference, respectively) (Hirsch 2005). This estimate is fairly consistent with other North American data, which found a 12% pay penalty with controls for personal and job characteristics included (Bardasi and Gornick 2008).18

There may be some nuanced, important differences by hours of work, even among part-time workers, in proximity to a country’s full-time workweek.19 Indeed, in the United States, the penalties found for working shorter hours per week or per year may just mirror the flipside—the pay rate premium earned for those who work longer than standard full-time hours (Blau and Kahn 2017; Goldin 2014; Cha and Weeden 2014; Bertrand, Goldin, and Katz 2010).20 Thus, the wage penalty may be smaller for those part-timers who work nearer the full-time workweek threshold.21 Indeed, recent changes in the representation of gender and parents who are working part time is associated with a decline in the gender wage gap among parents and in the motherhood wage penalty, but also with an increase in the fatherhood wage premium (Preston and Yu 2015; Weeden, Cha, and Bucca 2016; Yu and Kuo 2017). The size of a wage penalty might be smaller for those groups that have a relatively higher preference for working part time—mothers of young children, students, retirees, etc.

No known previous study has focused on the degree of voluntariness of taking or holding a part-time job, which may be associated with different compensating differentials or some of the other reasons for a penalty. The degree of voluntariness may play a role, explaining why the penalty may be larger for those who are less likely to prefer part-time working, e.g., men. In addition, a part-time pay premium could reflect a combination of several possible sources—the lack of employee benefits (so cash in lieu), the variability of hours and thus weekly earnings among hourly self-employed people, the lower job security provided by part-time positions.22A penalty also may be smaller, if not become an outright premium, for those compensated as salaried as opposed to hourly paid. Moreover, the size of a penalty or premium might vary by industry sector. Finally, the institutions within a country help shape the existence and size of the penalty or premium (Blau and Kahn 2013; McGinnity and McManus 2007).23

New estimates of the wage and compensation penalties: Methodology

The Bureau of Labor Statistics’ Current Population Survey (CPS) is a monthly survey of households in the United States. One-fourth of the employed adults (age 16 and older) in the survey’s “Basic” monthly sample—a subgroup often referred to as the “Outgoing Rotation Group” (ORG)—are asked to answer a detailed set of questions about their earnings from work. Our empirical strategy is to replicate what Hirsch (2005) had generated, using updated CPS–ORG data, from 2003 through 2018.24

The part-time wage penalty may be measured in several ways. We compare the hourly earnings of those who usually work what is considered part-time hours with hourly earnings of those whose hours are defined as full time. Part-time workers in the CPS are defined as those who worked one to 34 hours as their “usual” work hours (or during the reference, last week). These workers are subdivided into two groups as classified by the BLS: those working “part time for economic reasons” and those working “part time for noneconomic reasons.” The part-time-for-economic-reasons group includes survey respondents who said they work part time due to “slack work or unfavorable business conditions”or “an inability to find full-time work.”25 Those who usually work less than 35 hours for what the BLS calls “noneconomic reasons” are those who say they work part time because of “child care problems,” “other family/personal obligations,” “health/medical limitations,” “school/training,” “retired/Social Security limit on earnings,” “full-time workweek is less than 35 hours,” and “other for non-economic reasons.” Those who work part time for noneconomic reasons often are considered to be “voluntary” part-time workers (even though these workers’ choices are constrained by existing policies and institutions, such as the lack of resources for child care or care for family members who are older or who have a disability). Workers typically are considered to be working part time “involuntarily” when they indicate they are willing, able, and available to work full-time hours, but either had to settle for working part-time hours, or had their hours reduced by their employer (from greater than to less than 35 hours).26 Herein, we will rely on the BLS’s “economic” versus “noneconomic” reasons for working part-time hours, rather than the commonly inferred “involuntary” versus “voluntary” terminology.

The total sample size applied here, pooled within the period 2003–2018, is 1,756,419 individual observations. The sample consists of hourly and non-hourly wage earners, ages 16 and older, in the 2003–2018 EPI extracts of the CPS-ORG. Observations with allocated hourly wages or weekly earnings are excluded, as are all observations with hourly wages less than $2.00 or more than $150.00 per hour (as in Hirsch (2005)). All standard errors are clustered by state.

Demographic controls include race, gender, and education dummies, and a quintic polynomial in age. Industry and occupation controls are dummies for Census recodes of major industry and occupation categories. The key independent variable is the part-time work status of the individual. We use the Basic CPS hourly earnings question, even though employed persons in the ORG are asked about hours per week. We define “part time” by using the “usual hours at your main job,” as Hirsch (2005) does.27 For workers with varying hours, last week’s hours are used for the 35-hour cutoff (in one’s primary job). The dependent variable is the log of the wage rate (average hourly earnings) for a worker. Hourly wages are defined first as the straight time wage for nontipped workers (observations with allocated values are dropped); when that value does not exist, hourly wages are weekly earnings divided by usual hours (observations with allocated values for either weekly earnings or usual hours are dropped); for workers whose “hours vary,” weekly earnings divided by last week’s hours (observations with allocated values for either weekly earnings or last week’s hours are dropped).

All multivariate regressions use logarithm of the hourly wage as the dependent variable and are weighted using the ORG sample weights. The regressions are on the same dependent variable with the same controls and same hierarchical approach. First the models are run with the entire sample of all workers, with no controls, except for the 15 years and 51 state fixed effects. Then, sequentially adding controls, first the set of demographic and work characteristics, and then adding industry and occupation controls. We break down the part-time penalty by types of workers by race and gender, and the type of part-time work (e.g., noneconomic and economic reasons).

Part-time wage penalty empirical tests: Findings with the latest data, 2003–2018

We test for the following questions to determine the extent to which the estimated size of the part-time wage penalty is different:

  • In size as it was in the earlier period, ending in 2002, as a raw or adjusted wage gap.
  • By the noneconomic versus economic motivations for working part-time hours.
  • By race and gender and its combinations, although part-time work is disproportionately female.
  • In size to a potential add-on penalty of reduced access (coverage) regarding nonwage benefits for part-time workers.

Our empirical procedure is to conduct a three-step process estimating the size of the wage penalty for part-time workers:

  • The “raw” wage gap in wage levels, with no controls for individual, state, or year fixed effects excluded and then included. The “raw” wage penalty is expected to be largest.
  • The “partially adjusted” penalty, the above model and controlling for all personal and demographic characteristics, education, and location. The penalty is contrasted between shorter versus longer part-time hours per week, and economic versus noneconomic reasons for working part-time weekly hours.
  • The “fully adjusted” wage penalty is estimated first without, then with, controls for both industry and occupation of the worker. Effects of the industry of employment are expected to be higher in certain industries, perhaps where part-time jobs are more prevalent.

The unadjusted wage penalty for part-time work

Part-time jobs during the period 2003 to 2018 averaged 52.4% less wages per hour compared with earnings from full-time jobs. When factoring in just the effects of location (states) and state of the economy in subperiods (year), the “raw” wage penalty is 53.1% (see Table 1). This represents a substantial size reduction in absolute earnings per hour, suggesting that part-time workers earn less than 50 cents per hour on the dollar earned by their full-time worker counterparts. To put this in perspective, the order of magnitude is more than twice the size of the raw gender gap in the United States (Blau and Kahn 2017; Yu and Kuo 2017; Weeden, Cha, and Bucca 2016; Goldin 2014; Matteazzi, Pailhé, and Solaz 2014; Leslie et al. 2012; Harkness and Waldfogel 2003). Furthermore, this represents a substantial increase in the size of the unadjusted wage penalty from 1995–2002, which was on the order of 33% (between the 46% found for men and 22% for women (Hirsch 2005)).

Adjusted pay penalties—partial, by demographic and education characteristics of workers

While the raw wage penalty for working part time is a massive one, how much of this represents different qualities of part-time and full-time workers, such as their age (a proxy for work experience) or education levels (a proxy for skills brought to a job)? Because of the many different possible characteristics of workers observable in the CPS, we next measure the adjusted wage penalty for working part time versus full time. Controlling for workers’ demographic and “human capital” (i.e., 16 educational levels) characteristics is arguably a more meaningful measure of the penalty experienced by a given worker for part-time work, and is the most common, accepted way of measuring it with large, representative surveys in the United States and other countries.28 The “partially adjusted wage penalty” estimates control for the “observable” differences among workers in their personal/demographic and education features, but also their location.29

As discussed above, the “raw” wage penalty is 52.4% and remains comparable when adding state and year controls. The partially adjusted wage penalty, controlling for workers’ demographic characteristics and education level, is 29.3% (see Table 1). So, the inclusion of demographic and education controls “knocks down” the size of the wage penalty for usually working part-time hours, as expected, but this partially adjusted wage penalty remains substantial. This means that otherwise comparable workers who usually work part-time hours earn almost 30% less than their full-time working counterparts. This is markedly higher than the 24% (18% for women, 33% for men) wage differential found for the 1995–2002 era.

The fully adjusted wage penalty, which controls also for the worker’s industry and occupation in which they are employed, is 19.8%. This suggests that part-time workers get paid about 20% less than otherwise comparable full-timers simply because they are in part-time jobs, independent of whatever occupation and industry they work in. Thus, we infer that about one-third of the only partially adjusted wage gap is attributable to part-time workers being employed in certain lower-paying sectors or job types. Nevertheless, two-thirds of the wage gap is not explained by their industry or occupation of employment. In the earlier period, “measurable” characteristics accounted for 60% of the raw wage penalty (Hirsch 2005). The fully adjusted wage penalty for part-time workers is markedly higher recently—about 20% compared with 16% in the earlier, 1995–2002 period. The increase is surprising since the skills required of part-time workers actually rose between 2007 and 2017 (Dangermond, Monaco, and Smyth 2019).

It is interesting to note that the part-time wage penalty is on par with the gender and racial wage penalties in the U.S. labor market. Female workers are paid 22.6% less than male workers with similar demographic characteristics and education levels and black workers are paid 14.9% less than white workers with similar demographic characteristics and education levels (Gould 2020).

Table 1

Estimated hourly wage penalty for part-time work: How much less part-time workers earn than full-time workers (in %)

Part-time hourly wage penalty
Raw Unadjusted Partially adjusted Fully adjusted Fully adjusted by type
Hourly wage penalty
All part time -52.4%*** -53.1%*** -29.3%*** -19.8%***
Part time for economic reasons
Due to “slack work or business conditions” -22.3%***
Because worker “could only find part-time work” -29.5%***
Part time for noneconomic reasons -18.3%***
State (51) X X X X
Year (16) X X X X
Gender (2) X X X
Race (4) X X X
Education (16) X X X
Age (5) X X X
Occupation (10) X X
Industry (13) X X

Notes: Part time is defined as usually working less than 35 hours per week on the primary job. Part time for noneconomic reasons category includes workers who say they work part time to take care of child care problems or for other family and personal reasons. The symbols *, **, and *** indicate that the wage penalty is significantly different from zero at the 0.10 level, 0.05 level, and 0.01 level, respectively, using heteroskedasticity-robust standard errors. Standard errors are available upon request from the authors.

Notes: Part time is defined as usually working less than 35 hours per week on the primary job. Part-time for noneconomic reasons category includes workers who say they work part time to take care of child care problems or for other family and personal reasons. The symbols *, **, and *** indicate that the wage penalty is significantly different from zero at the 0.10 level, 0.05 level, and 0.01 level, respectively, using heteroskedasticity-robust standard errors. Standard errors are available upon request from the authors. The noneconomic reasons include all those the BLS categorizes as "noneconomic" reasons: for working part time include “child care problems,” “other family/personal obligations,” “health/medical limitations,” “school/training,” “retired/Social Security limit on earnings,” “full-time workweek is less than 35 hours,” and “other for non-economic reasons.”  The sample of 1,756,419 observations is hourly and nonhourly wage earners, ages 16 and older, in the 2003–2018 EPI extracts of the CPS-ORG. Observations with allocated hourly wages or weekly earnings are excluded. Demographic controls include race, gender, and education dummies, and a quintic polynomial in age. Industry and occupation controls are dummies for Census recodes of major industry and occupation categories. Dependent variable is log hourly wages.

Source: Author's analysis of 2003–2018 Current Population Survey Outgoing Rotation Group (CPS-ORG) microdata.

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Part-time wage penalties, by reason for part-time work

There are differences in the part-time wage penalties based on the reason a worker works part time. The CPS asks employed persons who report “usually” working fewer than 35 hours a week, “What is your main reason for working part time?” As noted in the methodology section, the BLS divides the many reasons that workers give into “economic” and “noneconomic” reasons. (Note that the survey does not ask whether those who give noneconomic reasons would prefer full-time work were it not for these noneconomic reasons.) The main two reasons within the “part-time for economic reasons” category are those working part time because of “slack work or business conditions” and because the respondent “could only find part-time work.” Another economic reason, though cited much less often, is “seasonal work or between jobs.” Other reasons are characterized by the BLS as “part-time for noneconomic reasons.”30 Those working part time for noneconomic reasons include workers, disproportionately women, who seek part-time work more by choice, but under the constraint that they might have little access to any supports for child care, sick leaves, and other social or family obligations that, if supported more, would help enable them to work full-time hours. Thus, if one works part-time hours on a regular basis because of “child care problems” or “other family/personal obligations,” then BLS considers that one works part time “for noneconomic reasons.”

The results in Table 1 show that those working part time for economic reasons suffer a greater wage penalty. When working fewer than 35 hours for economic reasons, such as “slack work or business conditions,” the fully adjusted wage penalty is 22.3%. However, those working part time because they only have been able to find part-time work, there is a considerably higher penalty, at 29.5%. In contrast, those working part time for noneconomic reasons face a wage penalty of 18.3%, smaller in size than that faced by economic part-time workers. Thus, there is a gradation apparent: The greater the employer role in determining the part-time status of the work, the larger the wage penalty. This means workers who work part time but want full-time work not only are “hours-constrained” underemployed, but also suffer from even lower relative hourly earnings than part-time workers overall. This finding is not consistent with a compensating wage differential theory, which would imply that those working shorter hours as a personal choice should be more willing to sacrifice pay. Those who are part time for economic reasons, in post-recession years, increasingly make up a larger share of those who settle for part-time jobs in lieu of full-time jobs, rising to constitute one-third of the total among all (10) reasons provided for working fewer than 35 hours, i.e., part time (Golden 2016).

Part-time wage penalties by race and by gender

Within the 19.8%, fully adjusted wage gap for all part-time workers, there are notable differences by workers’ race or ethnicity, as shown in Table 2. For white workers, the penalty is 20.7%, a tick higher than the overall average, on par with the 20.2% penalty for black workers. The wage gap is 14.2% for Hispanic workers, or about three-fourths of the average overall. The similar size of the part-time wage group across groups suggests that the penalty for part-time working appears to be due to the part-time job itself, experienced by all incumbents across racial/ethnic groups, with only slight differences in size.

Table 2 breaks down the overall and race results by gender. Women experience a substantial wage penalty for working part-time hours of just under 16%. For men, it is substantially larger; the wage penalty is greater than 25%. Again, these differentials are somewhat greater than those found in the earlier period, which were 11% for women and 22% for men (Hirsch 2005).

Table 2

Estimated hourly wage penalty for part-time work by gender and race/ethnicity: How much less part-time workers earn than full-time workers (in %)

Part-time wage penalty
All -19.8%***
By race/ethnicity
White -20.7%***
Black -20.2%***
Hispanic -14.2%***
By gender
Female -15.9%***
Male -25.8%***
By gender and race/ethnicity
White male -28.1%***
White female -16.4%***
Black male -24.6%***
Black female -17.2%***
Hispanic male -16.9%***
Hispanic female -12.3%***

Notes:  Part time is defined as usually working less than 35 hours per week on the primary job. The symbols *, **, and *** indicate that the wage penalty is significantly different from zero at the 0.10 level, 0.05 level, and 0.01 level, respectively, using heteroskedasticity-robust standard errors. Standard errors are available upon request from the authors. Regressions include controls for age (5), education (16), years (16), industry (13), occupation (10), and state (51).

Source: Author's analysis of 2003–2018 Current Population Survey Outgoing Rotation Group (CPS-ORG) microdata.

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While smaller in size, the scope and the impact of working part time is greater for women than men, even though the actual size of the part-time wage penalty is larger for men than women. This is because—though not shown in the table—women are twice as likely to work part time as men—22.8% of all female workers worked part time in 2019, compared with 11.8% of all male workers. Even starker, there are 73% more women part-time workers than men part-time workers (16.1 million part-time women versus 9.3 million part-time men (BLS 2020a)).

Indeed, findings (unreported here) regarding the size of the wage penalty by the length of workweeks (also Hirsch 2005), reveal that the part-time penalty is, in large part, more of a penalty for fewer work hours. When broken out by subranges of weekly hours, there appears to be an hours gradient to the part-time wage penalty. Working 20 or fewer hours has the largest penalty, although not that much larger than working 20–29 hours, but noticeably larger than in the 30–34 hours range. However, even when working more than 35 but less than 39 hours, there also is some penalty vis-à-vis those usually working 40. Thus, there appears to be an hours-related wage penalty within part-time jobs.31 Moreover, if the Bureau of Labor Statistics definition of what constitutes “full time” (working 35 hours or more) was changed to the more legal and normative “standard” workweek of 40 hours, the impact of the wage penalty would be more widespread, given how many millions of workers work 35–39 hours.

Table 3

Share of workers with given demographic characteristics, by part- and full-time status, 2019


Share of workers by part-time and full-time status, 2019
All workers* Part time Full time
Total Noneconomic Economic
All 100.0% 100.0% 100.0% 100.0% 100.0%
By gender
Female 47.0% 63.3% 66.1% 50.0% 43.2%
Male 53.0% 36.7% 33.9% 50.0% 56.8%
By race/ethnicity**
Black 12.5% 11.1% 10.0% 16.7% 12.9%
Hispanic 17.6% 17.5% 15.7% 26.5% 17.7%
White 77.4% 79.0% 80.2% 73.3% 77.0%
By gender and race/ethnicity**
Black male 5.9% 4.3% 3.6% 8.1% 6.3%
Black female 6.6% 6.8% 6.4% 8.6% 6.5%
Hispanic male 10.0% 6.8% 5.4% 13.6% 10.7%
Hispanic female 7.6% 10.8% 10.3% 12.8% 7.0%
White male 41.8% 28.7% 26.9% 37.3% 44.8%
White female 35.6% 50.3% 53.2% 36.1% 32.2%

*All workers includes the universe of individuals who were “at work” in the reference week of the survey.

**Column data do not add up to 100% because the categories are not mutually exclusive, e.g., white includes Hispanic white and non-Hispanic white.

Note: Part time is defined as usually working less than 35 hours per week on the primary job. Part time for noneconomic reasons category includes workers who say they work part time to take care of child care problems or for other family and personal reasons. Part-time for economic reasons includes workers whose reasons for working part time include “slack work or business conditions” or “could only find part-time work.” See methodology and expanded note.

Note: Part time is defined as usually working less than 35 hours per week on the primary job. Part-time for noneconomic reasons category includes workers who say they work part time to take care of child care problems or for other family and personal reasons. Part-time for economic reasons includes workers whose reasons for working part time include “slack work or business conditions” or “could only find part-time work.” Noneconomic reasons for working part time include “child care problems,” “other family/personal obligations,” “health/medical limitations,” “school/training,” “retired/Social Security limit on earnings,” “full-time workweek is less than 35 hours,” and “other for non-economic reasons.” Economic reasons includes “slack work or unfavorable business conditions,” “an inability to find full-time work,” and for a small number of respondents, because of “seasonal declines” in demand or because the respondent’s “job ended or started” during the reference week.

Source: Labor Force Statistics from the Current Population Survey (BLS 2020a).

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Table 3 shows the gender and race distribution of part-time workers, by reason. By gender, it shows that women make up a greater share of those who work part-time hours generally, both for noneconomic and economic reasons. Women make up 63.3% of part-time workers, even though women make up just 47.0% of those “at work.” Women clearly are disproportionately working part time and so a much larger share of women are affected by the part-time pay penalty.

Hispanic women and black women both make up a disproportionate share of those working part time (both for noneconomic and economic reasons). By race/ethnicity alone, black and Hispanic workers make up a disproportionate share of those working part time for economic reasons: Hispanics constitute 26.5% of all those working part time for economic reasons, in contrast to being only 17.6% of all those at work. Black workers constitute 16.7% of all those working part time for economic reasons while they are only 12.5% of all those at work. Broken by gender and race, black men and women and Hispanic men women all disproportionately work part time for economic reasons.32 But in summary, women of color appear to bear a disproportionate brunt of the part-time earnings penalty because they make up a disproportionate share of those working part time for any reason.

Differentials in employee benefits

The results so far focus on the hourly wage penalty faced by part-time workers. However, part-time workers also receive less in such benefits as retirement and health care because they frequently are excluded from such plans. Analysis of National Compensation Survey 2013 data showed that part-time workers had far less access to benefit plans than full-timers did (Bishow 2015; BLS 2015). For instance, only 37% of part-time workers had access to the employer’s retirement plan, far less than the 74% of full-time workers who did. Similarly, part-time workers had access to health care plans only 24% of the time, while full-time workers had access to health care plans 85% of the time. Part-time workers also were excluded from holiday, sick leave, and vacation plans. Access to benefits depends on the scheduled number of weekly work hours, not only whether the responding establishment reports the job as full time or part time (Bishow 2015).33

The challenge is how to incorporate analysis of these benefit gaps along with wage penalties, because the monthly survey data source (CPS) used to estimate wage penalties does not have benefit data. The only data available are from BLS’s Employer Costs for Employee Compensation series, in the National Compensation Survey, which provides breakdowns of wages and benefits separately for full-time and part-time workers (for major occupation categories). Unfortunately, these data do not allow us to control directly for differences in education, experience, or industry; however, some of these factors will be reflected in the occupation differences (i.e., workers in a similar occupation will have similar education levels).

Table 4 provides an analysis of the full compensation—both wages and benefits—for all private-sector workers and for two general occupational categories (blue-collar and service occupations). “Blue collar” includes “production, transportation, and material moving” occupations, and “service occupations” includes a variety of mostly low-wage occupations such as health care support occupations, food preparation and serving-related occupations, building and grounds cleaning and maintenance occupations, and personal care and service occupations, along with protective service occupations (firefighters, police, corrections officers).

Table 4

Benefits penalty for private-sector part-time workers, 2018

Occupation group:
All private Service occupations Blue collar
Full time Part time Full time Part time Full time Part time
Compensation ($)
Total compensation 39.86 18.00 19.28 13.15 30.66 17.67
W-2 wages 31.84 15.04 15.29 11.16 23.29 13.35
Nonwage benefits 8.02 2.96 3.99 1.99 7.37 4.32
Shares of compensation
W-2 wages 79.9% 83.6% 79.3% 84.9% 76.0% 75.6%
Nonwage benefits 20.1% 16.4% 20.7% 15.1% 24.0% 24.4%
Compensation/wage ratio 1.252 1.197 1.261 1.178 1.316 1.324
Part-time benefit penalty* 5.5% 8.3% -0.7%

* Percentage points by which the penalty for compensation exceeds that for wages alone.

Notes: W-2 wages are the sum of direct wages, paid leave, and supplemental pay. Nonwage benefits include insurance, retirement, and payroll taxes. Blue-collar occupations are production, transportation, and material moving occupations.

Source: Bureau of Labor Statistics Employer Costs for Employee Compensation data from June 2018 (BLS 2018)

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The analysis is focused on estimating the degree to which the full compensation penalty (incorporating both wages and benefits) is larger than that for wages only. To do so, the analysis adopts W-2 wages, a measure of wages that mirrors that used in the analysis of CPS data above. “W-2 wages” includes the BLS category of direct wages, but adds costs for paid leave and supplemental pay (because these categories are embedded in the CPS definition of wages). Nonwage benefits include insurance, retirement, and payroll taxes paid by the employer.

In the private sector, nonwage benefits make up 20.1% of full-time workers’ compensation, but account for only 16.4% of part-time workers’ compensation. As Table 4 shows, this implies that for every dollar of wages, there is 25.2 cents for benefits for full-time workers, but only 19.7 cents per dollar for part-time workers. This implies, in turn, that even if part-time and full-time workers had equivalent wages, there would be a compensation penalty of 5.5 percentage points. Thus, we can add another 5.5 percentage points to the estimated wage penalty to obtain the full compensation penalty for part-time jobs. Moreover, there is an even bigger benefits penalty, 8.3 percentage points, for those in low-wage service occupations. However, there is no apparent add-on benefits penalty among workers in the group of blue-collar jobs.34

Implications of the findings for policies to address the penalties associated with working part time

Working part-time hours clearly involves a willing sacrifice of income, sometimes an acceptable trade-off for those workers who prefer less-than-full-time work, and the flexibility that part-time jobs potentially provide compared with a full-time commitment to work or the workforce.

However, having significantly reduced per-hour compensation for the same work characteristics, hurts part-time workers, whether they are working part-time hours for either the economic or noneconomic reasons. The hourly wage penalty for working part time, in the recent U.S. labor market, is a 20% reduction in earnings per hour, even after one’s education, experience, occupation, and industry are taken into account. The part-time workers’ relative wage gap is thus on par with observed gender and racial wage gaps in the United States, and is similarly persistent and inequitable. Indeed, the wage penalty is measurably higher now than it was a decade and a half ago when Hirsch (2005) did his analysis with the same CPS data. In addition, the over 4 million U.S. workers in part-time jobs who prefer to work full-time hours (at least 35 weekly) (BLS 2020a) pay an even stiffer penalty. Even those working part time for various noneconomic reasons—which includes those who likely would prefer full-time work if they did not have such constraints as a lack of support for parenting, health issues, and the need to obtain more education—pay a penalty of over 18%.

Furthermore, part-time workers have less access to various employee benefits, suffering an additional 5.5 percentage-point benefits penalty, in the private sector, in addition to their wage penalty. These substantial compensation consequences likely reflect underlying structural and institutional factors in the U.S. economy that could and should be addressed, with a range of policy innovations. Listed below are several policies that we would need to adopt to address the part-time wage and benefits penalties and some of the key legislative efforts under way to bring them to fruition.

  • Compensation parity for part-time jobs and workers. A codified measure to ensure rights for part-time workers would need to include provisions for wage fairness and pro-rated benefit coverage. Pay parity for part-time work is a basic, accepted precept of the International Labour Organization (ILO)’s Part-Time Work Convention, 1994 (No. 175)—the globally accepted standard for providing proportional parity for part-time workers. It recognizes “the economic importance of part-time work, the need for employment policies to take into account the role of part-time work in facilitating additional employment opportunities, and the need to ensure protection for part-time workers in the areas of access to employment, working conditions and social security” (Preamble), relative to “comparable full-time workers” (who have the same type of employment relationship; are engaged in the same or a similar type of work or occupation; and are employed in the same establishment) (Article 1). This standard articulates that “national law and practice shall be taken to ensure that part-time workers do not, solely because they work part time, receive a basic wage which, calculated proportionately on an hourly, performance-related, or piece-rate basis, is lower than the basic wage of comparable full-time workers.” (Article 5). “These conditions may be determined in proportion to hours of work, contributions or earnings.” (Article 6). It extends this proportional parity in pay norm to statutory social security schemes that are based on occupational activity, “so that part-time workers enjoy conditions equivalent to those of comparable full-time workers” (Article 6). Finally, it promotes that measures be taken to ensure that part-time workers receive conditions equivalent to those of comparable full-time workers for maternity leave, paid annual leave, paid public holidays, and sick leave—provided in proportion to hours of work or earnings (Article 7). The Netherlands (where 75% of women employed work fewer than 35 hours per week) has been at the forefront of creating pro-rata equivalence for part-time workers, particularly regarding salary levels and, where reasonable, also for employee benefits (Visser et al. 2004). In the United States, San Francisco’s Formula Retail Employee Rights Ordinances have such parity for part-time workers (San Francisco Office of Labor Standards Enforcement 2020, see Section 3300G.5 ).
  • Access to hours for part-time workers. Work schedules that often do not provide as many hours as they want or need are a significant challenge faced by many part-time workers. The Part-Time Workers Bill of Rights Act to be introduced by Sen. Elizabeth Warren (D-Mass.) and Rep. Jan Schakowsky (D-Ill.) would address that challenge by requiring that large employers offer available hours first to current, available, qualified part-time employees before hiring new employees or temporary or subcontract workers. Some local jurisdictions are already offering such protections. Seattle’s Secure Scheduling Ordinance, adopted in 2017, provides “Access to hours” which ensures that, before new employees are hired, an employer must post notice for current employees of available hours for three days and offer the job or work to qualified current employee(s). In San Jose, California, the Opportunity to Work Ordinance requires, without specifying the number of hours for the period, that employers first offer available additional hours of work to its existing part-time workforce (who in the employer’s good faith and reasonable judgment have the skills and experience to perform the work) before hiring (sub)contractors, temps, or new part-time workers. The employer also must use a transparent and nondiscriminatory process to distribute the hours of work among those existing employees. Employers are not obliged to allocate those hours to existing employees in the event the additional hours would result in premium-owed overtime hours (The Center for Popular Democracy and Working Partnerships USA 2016). In addition to Seattle and San Jose, several cities such as Chicago; Emeryville, California;  New York City; Philadelphia; and San Francisco have introduced or passed fair workweek laws that include “access to hours” provisions.
  • Control over work schedules and protections from volatile scheduling practices. Lower pay for part-time work is compounded when people do not know or control their own hours or have enough advance notice when their schedules are set or changed. Legislation to help ensure that lower-wage employees are provided with more certainty about their work schedules, hours, and income has been proposed in the U.S. Congress and proposed or passed in many statehouses and city councils across the United States. The national Schedules That Work Act of 2019 (STWA) and the local and state measures contain provisions that would diminish the income and pay disadvantages experienced by incumbents of part-time jobs. The bills generally permit employees to request changes to or stability in their work schedules without fear of retaliation, and ensure that employers consider these requests. The measures also require employers to provide a minimum advance notice of schedules, typically between seven to 14 days, that will make hours more predictable and stable for all the hourly employees in the industries covered. The provisions in fair workweek laws for New York City, the state of Oregon, San Francisco, Seattle, and elsewhere include some requirement for “predictability pay”—if a worker’s posted schedule is altered or their shift length or hours are cut, the employee is owed at least some pay for that. In certain cases, the employee is owed just an hour or two hours’ pay; in other cases, hours cuts made within 24 hours of the shift start time, employees are owed pay for no less than half the hours of the originally scheduled shift. Similarly, reporting pay requirements, which predate the proposed scheduling ordinances (CLASP, Retail Action Project, and Women Employed 2014; Ben-Ishai 2016), require a minimum payment for those showing up to work and having one’s hours eliminated or cut. All of these measures would clearly mitigate the pay suppression experienced by workers in part-time positions, not only for those who work part time for economic reasons—where the pay gap is more egregious—but for those working part time for noneconomic reasons as well, who also deserve such protections. Because part-time workers are far more likely to be given unfavor­able work schedules or face greater schedule volatility (Zukin and Van Horn 2015; Ruan and Reichman 2014; Alexander and Haley-Lock 2015; Schneider and Harknett 2019), other provisions of the STWA and local ordinances—such as prohibition of on-call work and “clopening” (being scheduled to close the business one night and be back to open the business the next morning)—would improve dimensions of part-time workers’ well-being less directly associated with pay. Similarly part-time workers would benefit from the “right to request” modifications in hours (and schedules) in the STWA and in such laws in cities and two states (New Hampshire and Vermont): Under these provisions part-time employees could expressly request additional work hours. Moreover, a minimum hours standard for part-time workers could guarantee a certain number of hours per week (such as 24 in France) to workers when hired, unless they prefer otherwise (Peck and Traub 2011). Indeed, all EU member states by 2022 will have to comply with the European Commission’s Directive for Transparency and Predictability in Work, which will incorporate elements similar to these ordinances, including “good faith estimates” of hours and schedules upon hiring of employees (European Commission 2019).
  • A lower overtime pay threshold of hours for hourly paid part-time workers: Under federal law, almost all hourly workers are automatically eligible for overtime pay—1.5 times the regular rate of pay for any hours over 40 hours in a week. A lower threshold for part-time workers to be owed overtime pay—such as beyond 35 hours— would surely help address the part-time pay gap. Indeed, the proportion of part-time workers whose actual weekly hours exceeded 40 were a nontrivial 4%, and likewise, a far-greater proportion likely have weekly hours of 35 or more, given that part-time workers are more than twice as likely to report working irregular shift times.35
  • Provisions allowing part-time workers to continue receiving unemployment insurance benefits while working part-time hours, for both “economic” and “noneconomic” reasons: Eligibility for partial unemployment insurance (UI) should be extended to not only those taking part-time work in lieu of finding full-time jobs, but also to anyone who seeks to reduce his or her own work schedule for compelling reasons, including personal health and child care responsibilities. UI eligibility for individuals who voluntary quit for “good cause” should be extended to workers who are forced to quit due to their erratic schedules (Ben-Ishai and McHugh 2016). The federal government should enact a minimum eligibility standard for UI benefits, as long as the work being sought is for at least 20 hours per week.36 Currently, in 28 states and the District of Columbia employees can qualify for receiving  partial unemployment insurance as “short-time compensation” (STC) payments. They are eligible if their employer (not the employees themselves) initiated cuts in their workdays or shift lengths to part-time workweeks (i.e., “work sharing”) in lieu of instituting layoffs among a group of five or more employees.
  • Paid time off: Paid sick, vacation, and personal time off are available to a far lower share of workers at the bottom of the income scale, especially those in part-time jobs. National minimum paid sick time, vacation, and personal time laws are another tool that would help mitigate the income penalties part-time workers face. Having greater access to prorated paid time off may induce many workers to remain in their part-time jobs so as to best combine work with caregiving and/or schooling activities, rather than quitting for a different job or leaving the labor force. The national FAMILY Act would, if enacted, create a national family and medical leave insurance program that would apply coverage to part-time workers (National Partnership for Women & Families 2019).


The author thanks Larry Mishel and Ben Zipperer of EPI for their assistance with data and reviews of this report.

About the author

Lonnie Golden is a professor of economics and labor-employment relations at Pennsylvania State University, Abington College. He is an affiliate with the Project for Middle Class Renewal at the University of Illinois at Urbana-Champaign and the Employment Instability, Family Well-being and Social Policy Network (EINet) at the University of Chicago. He holds a Ph.D. in economics from the University of Illinois at Urbana-Champaign. His research has centered on the labor market and hours of work—specifically, the economic and noneconomic determinants of hours, including legal, organizational, and individual preferences, and their effects on employment and well-being, including work-life and worker happiness. He is coeditor of the books Working Time: International Trends, Theory and Policy Perspectives (Routledge Press) and Nonstandard Work: The Nature and Challenges of Changing Employment Arrangements (Cornell University Press), and author of many research articles that have appeared in such journals as Industrial Relations, Monthly Labor Review, Cambridge Journal of Economics, and Journal of Marriage and Family.


1. According to Appelbaum and Rho, “despite all the hype, gig work is an extremely small share of employment. Just 1.6 million workers—1.0 percent of total employment—were engaged in electronically mediated work in 2017.” In 2017, the total number of part-time workers was nearly 28 million (BLS 2020b).

2. The level of part-time jobs, in a state, is not significantly associated with the cost of health benefits, so the structural change involved is not mainly health care costs (Valletta, Bengali, and Van der List 2020).

3. Human capital investment such as training could be a fourth and job insecurity a fifth inherent disadvantage, leading to long-run effects on earnings trajectories (e.g., Ferber and Waldfogel 1998; Green and Ferber 2005; Wolf 2014; Paul 2016; Messenger and Ray 2015; Pedulla 2016; Kyyrä, Arranz, and García-Serrano 2017) and their job satisfaction (e.g., Wheatley 2016). Voluntary part-time working has a positive effect on longer-term earnings for women.

4. See Mishel 2013.

5. As of the end of 2019, no national legislation concerning part-time work had been introduced in the United States since H.R. 3682, the Part-Time and Temporary Workers Protection Act of 1996, 104th Congress (1995–1996), sponsored by Rep. Patricia Schroeder (D-Colo.).

6. Past CPS data confirm that those classified as involuntary part-time workers indeed work part time “involuntarily” (Stratton 1996), because involuntary part-time work tracks other indicators of underemployment (Li and McCully 2016).

7. Part-time workers who are primary earners increased from 1970, making up almost four in 10 of all part-time workers (Shaefer 2009).

8. A preference for working part time is high, particularly among mothers with children, including those who work full time and those not employed who prefer to work. Mothers in the bottom half of the income scale are more likely to prefer full-time work (Wang, Parker, and Taylor 2013).

9. This implies an “occupational crowding model” at work, where there not only is an efficiency wage leading to higher pay for full-time work, but an enlarged supply of workers with preferences for fewer than full-time hours (e.g., mothers and students). The labor demand side provides a foundation regarding why employers may favor creation of more jobs with part-time hours, or fewer in favor of more full-time positions. Employer preferences regarding the ratio of full-time and part-time jobs will depend on the ratio of fixed labor costs to the hourly wage rate, a variable cost (Zeytinoglu 1992; Montgomery and Cosgrove 1995; Lettau 1997; Barrett and Doiron 2001; Hamermesh and Stancanelli 2015; Golden 2015a; Elsayed, de Grip, and Fouarge. 2016). This would lead employers to curb the ratio of part-time to full-time jobs. A lower variable cost of wage rates, alternatively, might lead employers to hire more part-time workers, if their total compensation per hour worked is sufficiently less than that of full-time workers (Carré and Tilly 2012). On the other hand, the total administrative cost of having two part-time workers rather than one full-time worker to oversee may be higher on a per-unit basis for part-time jobs, incentivizing employers to hire fewer part-time workers.

10. To wit, across virtually all countries part-time working corresponds closely to the female share of the labor force. For more direct indicators of “schedule flexibility,” see Golden 2009 and Berg et al. 2014.

11. Hirsch (2005) uses college towns to illustrate where students are diverse in skills but care very much about which hours of the day are scheduled.

12. At least in medium-skilled service-sector work (Collewet and Sauermann 2017).

13. Indeed, Dutch firms with a large part-time employment share are relatively more productive—a 10% increase in the part-time share is associated with almost 5% higher productivity (Jepsen et al. 2005).

14. Ransom and Oaxaca (2010) find that workers who have lower labor supply elasticities get paid lower when firms have some monopsony power.

15. With panel data and the ability to control for potential individual heterogeneity among part-time and full-time workers, using individual-fixed effects models, the wage penalty estimates, not surprisingly, are lower; see Hirsch 2005 and Booth and Wood 2008.

16. Alternative methods to control for “unmeasured skill differences” to account for the potential self-selection (endogeneity) into part-time status typically find a reduced penalty size, particularly for women. One study found a 25% wage penalty for men who cut their workweek from 40 to 20 hours at retirement ages, but no such effect was noted among women (Aaronson and French 2004).

17. Studies from outside the United States show a pay penalty—in the United Kingdom, as high as 22% to 26%. About half of the pay gap, 13% among women, is “explained” by worker characteristics, but the remaining 3% to 10% (by gender) is unexplained (Manning and Petrongolo 2008). In several European countries, part-time jobs are flexible but insecure—analysis of labor market transitions in Denmark, France, Italy, the Netherlands, and Spain finds that being employed part time (mostly women) leaves one at higher risk of unemployment (Blázquez and Carcedo 2014; Anxo et al. 2007). However, wage differences between part-time and full-time workers are small in Norway (Hardoy and Schøne 2006), suggesting there is little systematic difference between part-time and full-time workers regarding the selection process or in earnings capacity, which they attribute to the Norwegian labor market providing more equal rights for part-time workers, strict rules against the discrimination of part-time workers, and a generous family policy enabling women to combine work and family life. The case of Norway suggests the importance of an institutional setting characterized by relatively strong employment protection that includes part-time workers. Partly as a consequence of this, a large proportion of Norwegian women are working part time. Similarly, with panel data on German workers, estimating a wage equation (using a random effects model), capturing the employment history and dynamic choice of employment status, controlling for the institutional context, finds that working part time with a relatively small number of weekly hours has a large causal effect on current wages. In contrast, more part-time work does not reduce current wages, although it leads to negative longer-term wage effects (Paul 2016). A study of women’s part-time work and wage penalties, using fixed-effects estimation, finds the smallest penalties for part-time employment where female labor force participation rates are lowest (McGinnity and McManus 2007).

18. Within occupations, one study finds almost a 9% wage penalty among workers in child care establishments, only a 7% gap among teacher aides and no more than 0% among teachers or among nurses, once instrumental variables or random effects estimations are conducted (Montgomery and Cosgrove 1995; MacPherson and Hirsch 1995). In caregiving jobs, being able to arrange part-time work is negatively associated with wages; i.e., care workers, on balance, trade off wages for this type of job flexibility (Smith and Folbre 2016). There may be changes over time. For example, in pharmaceutical occupations, the pay penalty has been shrinking, attributable to the reorganizing in that industry (Goldin and Katz 2016). There may be similar penalties for related forms of nonstandard jobs. The wage penalty associated with job outsourcing ranged from 4% to 7% for janitors and from 8% to 24% for security guards (with similar findings on health benefits), and were not a reflection of their lower hours (nor skill differences nor compensating differentials for higher benefits).

19. In particular, the share of female part-time workers is associated with wage penalties (whereas male part-time workers received a pay premium when working more than 25 hours). This is interpreted to reflect women’s different prime motive for reducing working hours and the types of part-time jobs available to them, or more to accommodate domestic constraints by downgrading to more flexible jobs. In Belgium, longer-hours part-time workers were more productive per hour than those at a much shorter weekly hours level (Garnero, Kampelmann, and Rycx 2014). In Germany (Wolf 2014), accounting for all available observed as well as time-constant unobserved individual characteristics yields a wage reduction for part-time workers of about 10%, with part-time men subject to higher wage penalties than women.

20. To the degree part-time work actually offers incumbents greater flexibility, there is an exponential return to greater current hours of work in high-paying occupations (Goldin 2014).

21. See Booth and Wood 2008 and Baffoe-Bonnie and Gyapong 2018 for the sensitivity of wage differential estimates to the definition of the number of weekly hours that is considered working full time.

22. Among Australia’s “casual” labor contracts, part-time workers explicitly lack long-term job security and social insurance security protections (Campbell, Whitehouse, and Baxter 2009). This lack of benefits explains the entire pay premium found for workers working part time there and in South Africa (Rodgers 2004; Posel and Muller 2008; Booth and Wood 2008). However, when controlling for unobserved individual heterogeneity (fixed effects) using panel data, part-time working men and women in Australia (Booth and Wood 2008) and in Germany (Wolf 2014) typically earn an hourly pay premium relative to those in full-time jobs.

23. See Booth and Wood 2008, Baffoe-Bonnie and Gyapong 2018 for the sensitivity of wage differential estimates to the definition of full time.

24. The matching is accomplished using IPUMS identifiers, which results in slightly different sample sizes than what Hirsch used.

25. We do not focus on the small number of respondents who say they work part time because of “seasonal declines” in demand or because their “job ended or started” during the reference week.

26. This group working part time for noneconomic reasons excludes the over 7.7 million who usually work full time but worked one to 34 hours in the last week because of vacations, holidays, weather, family obligations, or “other reasons” (according to 2019 data from BLS 2020a). An alternative way to count the number of workers part time for economic reasons who worked from one to 34 hours in the last week (whether they “usually work full time” or “usually work part time”) because of “economic reasons” is the universe of individuals who were “at work” in the reference week. Respondents who said they were not “at work” or were “absent,” but have a job, are counted as “employed.” Thus, part time for economic reasons is likely undercounted (Golden 2016).

27. Hirsch used the Basic CPS rather than ORG “usual” hours question. We substitute the answer regarding “usual hours” in the ORG with the same question in the Basic CPS to observe consistency. We also substitute the actual hours worked in the previous week being fewer than 35 and contrast. Finally, we used the “usually work part time” question as a dummy variable to contrast to “usual hours” being fewer or more than 35.

28. Controls for age show there is a significant positive effect of age on wages, but little influence of the exponentials. That is to say, earnings rise with age but neither more nor less than proportionally. In unreported results, the size of the penalty for working “usual part time” is contrasted briefly with measuring part time with workers’ “actual” hours last week being shorter than 35. The latter display somewhat lower pay penalties, which can be attributed to “actual” hours, including many full-time workers who worked fewer than 35 hours the previous week because of an absence.

29. Part-time employment appears in all major industry classifications. However, it is proportionately higher in some: private household services, leisure/hospitality, retail/wholesale trade, services-other, and education/health. Are pay penalties consistent across sectors or higher in some sectors, particularly where part-time work is more common? Unreported results show that among 50 different “intermediate” industry types, 49 have pay penalties. The variation in the partially adjusted pay penalty ranges up to 50% (with a small pay premium in only one outlier), although most fall in the 15% to 40% range. The pay penalty is above average in retail trade at 32%. Within the retail sector, working in clothing stores brings a sizably higher pay penalty, but somewhat lower in restaurants, where earnings include tips. In several industries, the pay penalty is above that of retail—more than 49% in rental and leasing services, at 46% in motion picture and sound recording and in other information services, 45% in internet publishing and broadcasting (though sample size is not large), 44% in petroleum and coal, 38% in beverage/tobacco products, 36% in publishing, and 35% in miscellaneous/nonspecified manufacturing. The sole exception to a penalty in part-time workers’ pay is in hospitals, where there is a slight pay premium of 3% (and only a small 3% pay penalty for those employed in private households). However, in health care industries other than hospitals, there is somewhat of a penalty of 6%. It suggests there is something unique about working part time in hospitals versus other health services. Even in hospitals, among those working one to 19 hours, the premium is zero. The lower penalties in certain sectors might reflect greater wage compression generally in those industries, in contrast to a wider pay disparity in other industries, particularly outside of health care.

30. Workers are provided three separate chances in the CPS to demonstrate that their part-time hours truly are “involuntary” (see Golden 2016).

31. This also suggests full-time work likely is better conceived of 40 or more hours, when it comes to pay, since working 35 to 39 hours appears to be more of a hybrid between full-time and part-time working, not entirely resembling full-time work at 40 hours or greater.

32. The totals by race and ethnicity in the table do not add up to 100% because the categories are not mutually exclusive, i.e., white includes Hispanic white workers and black includes Hispanic black workers.

33. Several other national surveys reinforce the large disparities between full-time and part-time workers in a wide range of employee benefits, or access to them. This includes parental leaves, paid sick time, paid vacation and personal time, and other perks (Kosar, van der Klaauw, and Zafar 2017; FRB 2016; AEI-Brookings-Urban Institute 2018; NWLC 2017; Glynn et al. 2016; Fronstin 2013; and Milli, Xia, and Min 2016).

34. See Bivens et al. 2017, which shows the union advantage in benefits, and supports (unreported) findings that unionized part-time workers have a 15.6% wage premium, higher than the overall average wage premium of 13.2%.

35. This policy is supported by both voluntary and involuntary part-time workers (Zukin and Van Horn 2015); see Golden 2009, 2015b.

36. See Stettner, Cassidy, and Wentworth 2016; Golden 2016; Ben-Ishai 2016; Glauber 2013; McKay 2017; Messenger and Ghosheh 2013; and NCSL 2019.


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