Union workers are more likely to have access to paid sick days and health insurance on the job than nonunion workers. The figure below shows the significant differences in those rates using the National Compensation Survey.

Only two-thirds of nonunion workers have health insurance from work compared to 94% of union workers. Having health insurance means workers are more able to seek and afford the care they need. We know in that the United States, millions of people delay getting medical treatment because of the costs. Without health insurance, many do not have a regular source of care and simply won’t go to the doctor to get the attention and information they need to not only get better but reduce the spreading of disease.

Figure A

Union workers are also more likely to be able to stay home when they are sick because they are more likely to have access to paid sick leave. 86% of unionized workers can take paid sick days to care for themselves or family members while only 72% of nonunion workers can.

Having a union allows workers and their families access to more tools to help them withstand the coronavirus pandemic. Union workers are more likely to be able to stay home and seek medical care, which will help strengthen their communities by being less likely to spread the virus.

With fears over COVID-19 spreading throughout the nation’s classrooms, there is understandably a push to maintain cleanliness in all schools. Even the Centers for Disease Control weighed in with recommendations for schools and teachers in particular too: clean and disinfect frequently touched surfaces and objects in the classroom.

The question is who’s going to pay for the products needed to protect students and teachers?

Turns out, some teachers are using their own money to cover the cost of things such as hand sanitizers and wipes, according to some published reports on the issue. That expense is in addition to the, on average, $459 teachers spend on school supplies for which they are not reimbursed (adjusted for inflation to 2018 dollars), found an analysis by Economic Policy Institute economist Emma García.

School supplies blogpost map

“What’s ahead for teachers in light of the threat of COVID-19 spreading will only add to the existing challenges and stress,” predicts García. “Teachers already act as first respondents when it comes to children’s basic needs, and schools are the only place where some students can have access to hot meals, medical care, washing their dirty laundry, or even to shelter. These, as well as the expense outlays, are worse in schools serving larger shares of low-income students.”Read more

The Trump administration has put forward the idea of cutting both employee and employer-side payroll taxes as the centerpiece of an economic response to the COVID-19 epidemic. This is a terrible opening bid. In late 2010, the Obama White House and a Republican-led Congress agreed on a temporary payroll tax cut for employees only as a compromise measure to provide economic stimulus.

But the employee-side payroll tax cut is an even worse potential compromise this time. One reason is that it would not get enough money out the door and into households’ pockets quickly enough. A COVID-19 recession will come fast and people will need lots of help quickly. A payroll tax cut will dribble out gradually over time. Another reason is the employee-side payroll tax cut is poorly targeted and sends lots of money to high-income households. A COVID-19 recession is laser-targeted at sectors with lots of low-wage workers, and the response should be too. So, even employee-side payroll tax cuts are a poor centerpiece of any policy package responding to the coming slowdown.

Employer-side payroll tax cuts are even much worse. They are a pure windfall to business and would do nothing for workers in the short run. These employer-side cuts should be flatly opposed.

There is, however, a potential role for employer tax credits as a way to stand-up emergency paid sick leave or work sharing or unemployment insurance. The optimal way for these programs to work is to have them be an ongoing part of our social safety net that take effect automatically during downturns. In the case of work sharing and unemployment insurance, these should be social insurance programs financed in the long run by payroll taxes. Paid sick leave should be a mandated labor standard. But since we do not have strong systems in place to provide these benefits to workers affected by the economic fallout of COVID-19 in the short run, and because placing new costs on employers just as revenue potentially craters might not be optimal, we could use employer tax credits to finance the emergency provision of key benefits like paid sick leave and expanded unemployment insurance.

Economists Jared Bernstein and Jesse Rothstein, for example, have a proposal to use employer tax credits to finance quicker-acting unemployment insurance that allows workers to stay on payroll and be paid even while not working during a COVID-19 downturn. Dean Baker made a similar proposal as the Great Recession loomed.

Policy discussions about buffering the economy from the COVID-19 shock are moving very quickly and lines are being drawn. It remains the case that large direct payments to households and having the federal government pick up states’ Medicaid spending for a year are likely the most valuable macroeconomic support that could be provided because they’re well-targeted to counteract the particular damage inflicted by a COVID-19 recession.

It also remains the case that unconditional employer tax cuts should be rejected flatly as a solution. But there does remain a potential role for employer tax credits in helping deliver benefits to workers. As long as these tax credits are used solely for this purpose, they should be considered.

We can’t take it for granted anymore. An obscure agency that most Americans have never heard of has issued a request for information that one-sidedly solicits input about how government is a problem, with the transparent goal of creating more roadblocks to government enforcement of environmental, consumer protection, labor, and other regulations. Right-wing groups are already mobilizing a campaign in response, prompting scores of comments expressing fervent yet vague support for the president. Many more comments are surely in the works, by corporations offering more polished and pointed explanations of their need to operate unfettered. The Trump administration has made clear its intent to do their bidding and more, but we don’t have to make it easy. Think tanks, public interest lawyers, community and advocacy organizations, and the general public can and should weigh in, to protect the government’s basic ability to protect our shared well-being.

At the hub of the agencies that report to the president is the Office of Management and Budget (OMB), which sets rules across the federal government for what agencies do and how they behave. In late January, the OMB issued a highly unorthodox request that assumes agencies behave unfairly, and asks how to make agency actions friendlier to alleged lawbreakers. It’s a clear invitation to corporate wrongdoers to provide anecdotes masquerading as evidence. The OMB’s head characterized the request as a means to end “bureaucratic bullying.” They’ve already decreed that agencies must repeal two rules for every new one they issue, no matter the harm to the public; this request is another effort to hamstring the government’s ability to pursue corporate wrongdoing.

The OMB’s request strangely floats importing criminal due process concepts into the civil administrative context. It asks whether there should be an “initial presumption of innocence,” for example, and whether investigated parties should be able “to require an agency to ‘show cause’ to continue an investigation.” But we are talking about corporations under civil investigation based on potential harm to broad swaths of people. If a business is suspected of polluting a playground, do we really want to slow down investigation and enforcement? Most of us would prefer swift government action in such circumstances.Read more

There are deficiencies in paid sick days coverage per sector, particularly among those workers with a lot of public exposure. The figure below displays access to paid sick leave by sector. Information and financial activities have the highest rates of coverage at 95% and 91%, respectively. Education and health services, manufacturing, and professional and business services have lower rates of coverage, but still maintain at least three-quarters of workers with access. Trade, transportation, and utilities comes in at 72%, but there are significant differences within that sector ranging from utilities at 95% down to retail trade at 64% (not shown). Over half of private-sector workers in leisure and hospitality do not have access to paid sick days. Within that sector, 55% of workers in accommodation and food services do not have access to paid sick days (not shown).

Figure

Of the public health concerns in the workforce related to COVID-19, two loom large: those who work with the elderly because of how dangerous the virus is for that population and those who work with food because of the transmission of illness. Research shows that more paid sick days is related to reduced flu rates. There is no reason to believe contagion of COVID-19 will be any different. When over half of workers in food services and related occupations do not have access to paid sick days, the illness may spread more quickly.

What exacerbates the lack of paid sick days among these workers is that their jobs are already not easily transferable to working from home. On average, about 29% of all workers can work from home. And, not surprisingly, workers in sectors where they are more likely to have paid sick days are also more likely to be able to work from home. Over 50% of workers in information, financial activities, and professional and business services can work from home. However, only about 9% of workers in leisure and hospitality are able to work from home.

Many of the 73% of workers with access to paid sick days will not have enough days banked to be able to take off for the course of the illness to take care of themselves or a family member. COVID-19’s incubation period could be as long as 14 days, and little is known about how long it could take to recover once symptoms take hold. The figure below displays the amount of paid sick days workers have access to at different lengths of service. Paid sick days increase by years of service, but even after twenty years, only 25% of private-sector workers are offered at least 10 days of paid sick days a year.

The small sliver of green shows that a very small share (only about 4%) of workers—regardless of their length of service—have access to more than 14 paid sick days. That’s just under three weeks for a five-day-a-week worker, assuming they have that many days at their disposal at the time when illness strikes. The vast majority of workers, over three-quarters of all workers, have nine days or less of paid sick time. This clearly shows that even among workers with access to some amount of paid sick days, the amounts are likely to be insufficient.

Chart

Simply put, smart responses must be tailored to the type of recession the outbreak could cause if policymakers didn’t act.

The three key elements of a potential COVID-19 recession are:

• If it comes it will come fast,
• It will hit lower-wage workers first and hardest, and
• It will impose even faster and larger costs on state and local governments than recessions normally do.

Each one of these should be targeted directly.

Any economic relief package should come online quickly, it should be even more targeted to help lower-wage workers than usual, and it should rapidly boost state and local government capacity on both the public health and economic fronts. Below I sketch out why these characteristics of the COVID-19 slowdown are likely, and what a tailored response to each would be.

First, if the COVID-19 outbreak slows the economy, it could happen very rapidly. This is quite different, for example, than the onset of the Great Recession. That recession was caused by the bursting of the home price bubble, which essentially began in mid-2006. From that point on the recession was near-inevitable, but it took literally years to gather steam. As the Great Recession loomed, the key characteristics policymakers should have demanded of any proposed stimulus package should have been: effective, large and sustained. Fiscal policymakers decisively failed on the last point, and dwindling fiscal support hampered recovery for years.

A COVID-19 driven recession would be quite different in that it would hit quickly. The spread of the disease has been quite rapid in each country it has affected. Further, the public health response to maintain “social distancing” to thwart its spread tends to take effect rapidly as well. Even before the reported cases in the U.S. have reached large numbers the news are full of cascading cancellations of business and entertainment gatherings. We are almost certainly already feeling the economic effects of the COVID-19 slowdown—it just has not appeared in economic statistics yet (since these statistics tend to appear with a small lag).Read more

Oliver took a characteristically in-depth look at the issues and was largely positive about how M4A could help a “badly broken” health care system given the millions of people who are uninsured and underinsured. Crucially, he noted that we’re going to pay for healthcare one way or the other, and M4A largely doesn’t add to the costs we pay (indeed, it could well reduce them significantly in the long run), instead it just changes how we pay these costs—substituting taxes for premiums.

Oliver provided a comprehensive accounting of the benefits of the healthcare proposal, but he also raised some possible pitfalls, including the jobs that could be lost given the elimination of the private health insurance industry. The problem is he quoted a 1.8 million job-loss figure that’s been widely circulated but is widely misleading when presented without context, as I explain in my new analysis of M4A’s impact on the labor market.

Read more

In terms of the economy, there has already been an impact on the manufacturing sector as inputs from China are delayed because of temporary factory closures. The Federal Reserve has cut interest rates in expectation of further economic disruptions. Many employers are making contingencies for workers to telecommute rather than risk illness. Unfortunately, this isn’t an option for millions of workers in direct service professions across the economy. Another likely side-effect of the pandemic is a pull-back on social consumption. Either because people become sick themselves or are avoiding public spaces, there will likely be a drop in certain types of spending across the economy.Read more

• Boost wages and salaries by allowing employers to redirect money they are spending on health care costs to their workers’ wages.
• Increase job quality by ensuring that every job now comes bundled with a guarantee of health care—with the boost to job quality even greater among women workers, who are less likely to have employer-sponsored health care.
• Lessen the stress and economic shock of losing a job or moving between jobs by eliminating the loss of health care that now accompanies job losses and transitions.
• Support self-employment and small business development—which is currently super low in the U.S. relative to other rich countries—by eliminating the daunting loss of/cost of health care from startup costs.
• Inject new dynamism and adaptability into the overall economy by reducing “job lock”—with workers going where their skills and preferences best fit the job, not just to workplaces (usually large ones) that have affordable health plans.
• Produce a net increase in jobs as public spending boosts aggregate demand, with job losses in health insurance and billing administration being outweighed by job gains in provision of health care, including the expansion of long-term care.

While the overall effect of fundamental health reform on the labor market would be unambiguously positive, this does not mean policymakers should ignore the distress caused by job transitions forced by this reform. Specifically, policy support should be provided to help displaced health insurance and billing administration workers move into new positions. But we should not let critics of Medicare for All inflate the scale of this transition challenge or falsely present the number of jobs displaced in individual sectors as the net effect of reform on labor markets. The number of health insurance and billing administration workers who would need to transition implies an increase in the rate of overall job market churn that is relatively small: Job losses for these workers would be equivalent to one-twelfth the size of economywide layoffs in 2018.

Background: The need for fundamental health reform

Currently, despite the significant gains in health care coverage spurred by the passage of the Affordable Care Act (ACA) in 2010, roughly 23 million Americans between the ages of 19 and 64 are uninsured, and another 64 million are underinsured (Collins, Bhupal, and Doty 2019).1 In addition to problems with access, the American health care system also suffers from excess costs.2 While excess health care cost growth has slowed notably in the last decade, it would be prudent for policymakers to try to keep this cost growth in check with significant policy reforms rather than simply hoping for the best going forward. Some highly important health-related prices have begun rising rapidly in the very recent past. Insurance premiums, for example, rose 20% in 2019.3 Overall spending on prescription drugs rose more than 9% between the fourth quarter of 2018 and the fourth quarter of 2019—the largest year-over-year change since 2015.4

Bivens 2018b provides data demonstrating that health spending in the U.S. is higher than in advanced peer countries and has risen faster over time—and yet continues to buy worse health outcomes. The higher and faster-growing spending of the United States is driven by faster growth of prices, not by growth in the volume of health care goods and services consumed. Further, international evidence shows that a key component of controlling cost growth is a strong public role in setting and negotiating the prices of health care goods and services.

A fundamental reform like Medicare for All (M4A) would make coverage universal. Further, by providing a counterweight to (or outright eliminating) the substantial market power that keeps prices high and that is currently wielded by many key players in the health care sector (e.g., insurance companies, drug companies, specialty physicians, and device makers), such a reform could also have great success in containing health care cost growth. This could in turn provide relief from many of the ways that rising health costs squeeze family incomes.

An underappreciated benefit of such a reform is that it would also lead to a much better functioning labor market in many areas. Job quality would increase, job switching would become less stressful, better “matches” between workers and employers would boost productivity, and small businesses would be much easier to launch.

Despite the fact that M4A could deliver these large benefits to efficient labor market functioning, the policy often comes under fire from critics making highly exaggerated claims about the potential job loss that could occur under such a reform. The grain of truth in some of the claims is that, like any productivity improvement, the adoption of a reform like M4A would require the redeployment of workers from one sector (the health insurance and medical billing complex) to other sectors (mostly the delivery of health care). But there is little in the M4A-induced redeployment of workers that would greatly stress the American labor market over and above the uncertainty and churn that characterizes this labor market every year. Smart policy could make this redeployment eminently manageable for those workers who would be required to make the transition.

This brief highlights some labor market implications of M4A and critically examines claims that large job losses in the health insurance and billing administration sectors would make M4A an undesirable policy.

Health reform as labor market policy: Key effects for workers

Fundamental reforms like M4A could greatly aid labor market outcomes for U.S. workers. The most obvious benefits would be higher wages and salaries, increased availability of good jobs, reduced stress during spells of job loss, better “matches” between workers and employers, and greater opportunity to start small businesses.

Higher cash wages and salaries

Medicare for All could increase wages and salaries for U.S. workers by reducing employers’ costs for health insurance—freeing up fiscal space to invest in wages instead. The share of total annual compensation paid to American employees in the form of health insurance premiums rather than wages and salaries rose from 1.1% in 1960 to 4.2% in 1979 to 8.4% in 2018.5 If this post-1960 increase had been only half as large—and employers had spent the health cost savings on wages and salaries—the take-home wages of American workers would have been almost $400 billion higher in 2018.6 Given that the share of total compensation spoken for by health insurance premiums is starting from a high base today, any reform that managed to slow the excess growth of health spending going forward would go a long way in making space for faster growth of cash compensation.7

Increased availability of ‘good jobs’

Medicare for All could increase job quality substantially by making all jobs “good” jobs in terms of health insurance coverage and by increasing the potential for higher wages. While the definition of a “good job” is always going to be a bit imprecise, the vast majority of U.S. workers would say that a good job is one that pays decent wages and that also provides the health insurance coverage and retirement income benefits that most of today’s workers can only reliably access through employment. Nearly half of jobs fail this test on account of health care coverage alone: In 2016, 46.9% of workers held jobs in which their employer made no contributions to the workers’ health care; for workers in the middle fifth of the wage distribution, 42.9% held jobs in which the employer made no contribution to their health care (EPI 2017).

By making health coverage universal and delinking from employment, M4A would make it far easier for employers to offer good jobs in this regard, as every job would now be accompanied by guaranteed health care coverage. Further, as noted above, wages and salaries would have substantial room to grow if health care costs were taken off of the backs of employers. Schmitt and Jones (2013) estimate the share of good jobs—jobs that clear a specified wage floor8 and provide health and retirement coverage—in overall employment each year between 1979 and 2011. They then look at various policy changes that would boost this share. They find that providing universal health coverage would boost the probability that any given job in the economy is a good job by almost 20%—and that’s even before any potential boost to the share of jobs that are good jobs coming from cash wage increases provided as employers shed health care costs.9 The boost to job quality from making health coverage universal would be even greater for women workers, as women are currently less likely to receive employer-sponsored health insurance benefits from their own employers.10

Less damaging spells of joblessness

Medicare for All could make job losses and transitions less stressful by delinking employment and access to health insurance, emulating the universal access to health care offered by our rich country peers. The U.S. is unique among the rich countries of the world in how much it ties crucial social benefits—like health insurance and retirement income—to specific jobs. Hacker (2002) has referred to this arrangement as the “divided welfare state,” with some Americans having relatively full access to health and retirement security while others have access to virtually none, all based on the specific jobs they have. This makes some jobs in the U.S. economy especially valuable, and hence especially damaging to lose. Manufacturing workers without a college degree, for example, likely incur enormous income and social benefits losses in the event of job loss stemming from either automation or trade. The ability of universal, public social benefits to make individual job losses less damaging has been long recognized by social scientists (see, for example, Estevez-Abe, Iversen, and Soskice 2001).

Smooth job transitions contribute to economic dynamism by helping ensure that vacancies are filled quickly by appropriate workers and that unemployed workers can quickly find new jobs that make good use of their skills. Smooth job transitions will also be an important components of meeting crucial policy goals such as mitigating greenhouse gas emissions with wholesale changes in how energy is created. Policies that make job transitions easier and inspire less resistance from workers should be encouraged. Fundamental health reform that, like M4A, guarantees access to insurance regardless of one’s current job status is a key part of making such transitions easier.

Better labor market matches between workers and employers

Medicare for All could decrease inefficient “job lock” and boost small business creation and voluntary self-employment. Making health insurance universal and delinked from employment widens the range of economic options for workers and leads to better matches between workers’ skills and interests and their jobs. The boost to small business creation and self-employment would be particularly useful, as the United States is a laggard in both relative to advanced economy peers.

Substantial evidence indicates that our current system of employer-sponsored insurance (ESI) creates significant “job lock”—a condition in which workers who don’t want to lose their current ESI stay in their current jobs rather than make transitions that would better meet their needs. In a comprehensive review of this literature, Baker (2015) finds:

The likely range of a job-lock effect is a reduction in turnover—the rate at which people leave jobs—of 15–25 percent among workers with EPHI [employer-provided health insurance, or ESI]. With normal turnover for prime-age workers (people ages 25–54) in the range of 15–20 percent per year, this job-lock effect implies a reduction in annual turnover of around 4 percentage points among prime-age workers with [employer-provided health insurance, or ESI].

Making employment decisions based on access to ESI rather than on other criteria—such as work–life balance, cash wages, and commuting distance—can lead to employment “matches” that are less productive and that decrease overall worker welfare relative to job choices that are not constrained by the availability of health insurance.

More small-business formation

Despite policymakers’ frequent claims that they seek to support small businesses in the U.S. economy, the United States has a notably small share of small-business employment relative to our rich country peers. In 2018, for example, the U.S. was dead-last among the members of the Organisation for Economic Co-operation and Development (OECD) in its share of self-employment, at just 6.3% of employment. Countries that are frequently portrayed in U.S. business reporting as being choked by regulation—like Spain, France, and Germany—have far higher shares of self-employment, at 16.0%, 11.7%, and 9.9%, respectively (OECD 2020).

Besides a low share of self-employment, the U.S. also had significantly lower shares of overall employment in small businesses, across nearly all industrial sectors. The latest OECD data show that the U.S. share of employment in enterprises with fewer than 50 employees is lower than in any other country except for Russia (OECD 2018, Figure 7). In an earlier overview of trends in employment by firm size, Schmitt and Lane (2009) highlight how health care policy plays two key roles in potentially explaining cross-country trends. First, because health care is nearly universally provided in other rich countries, workers choosing to start their own businesses in those countries do not face a cost confronting would-be entrepreneurs in the U.S.: the loss of ESI. Second, small businesses in the U.S. are at a distinct disadvantage in recruiting employees because the cost of providing health care coverage is significantly higher for small companies.11

Employment effects of fundamental health reform: gains in health care, losses in insurance and billing—with likely economywide net job gains from rising economic demand

Like all positive productivity gains, Medicare for All would be more likely to increase the total number of jobs in the U.S. economy, even as health reform leads to the redeployment of workers from some sectors and into others.

Despite the many labor market benefits of fundamental health reform like M4A, many critics have claimed that such reform would lead to a loss of jobs. This claim is misleading. One small grain of truth to it is that the universal provision of health insurance would allow people who would strongly prefer not to work (or not to work full time), but who have remained in their current jobs in order to retain health insurance, to be free to quit. This type of voluntary reduction in labor supply following a health reform would be strongly welfare-improving. For example, the ACA was clearly associated with a large increase in parents with young children transitioning to part-time work (see Jørgensen and Baker 2014). To the degree this occurred because these parents no longer needed to work full time to obtain ESI, and they preferred spending more time with their children for reasons of work–life balance, it should be seen as a clear win for the policy.

Generally, people expressing concern about job loss stemming from a policy are concerned about involuntary job loss that leads to a higher level of unemployment in the economy. Unemployment is almost entirely a function of the level of aggregate demand: spending by households, businesses, and governments.12 The effect of fundamental health reform on the level of aggregate demand depends in turn on the balance of increased public spending and the means of financing this spending. All else equal, more public spending will boost aggregate demand and create jobs, while higher taxes will reduce aggregate demand and restrain job growth. Further, the progressivity of taxes used to finance fundamental health reform will also condition its effect on aggregate demand. The more progressive the taxes that finance health reform, the less they will drag on job growth. Increased public spending combined with progressive tax increases would almost certainly boost the level of aggregate demand and lead to lower unemployment, all else equal.

While the overall number of jobs and the level of unemployment in the economy is largely a macroeconomic issue determined by aggregate demand, claims that fundamental health reform like M4A will lead to job loss sometimes sound plausible because it is easy to envision the specific jobs that might be displaced: jobs in the health insurance and billing administration sectors. But these job displacements would be balanced by likely job gains in other sectors—most particularly in health care delivery. The health insurance coverage expansions of M4A will boost demand for health care goods and services, and workers will need to be hired to meet this demand.

Job losses in the health insurance and billing administration sectors

A recent analysis of the economic effects of M4A (Pollin et al. 2018) includes the projection that up to 1.8 million jobs in the health insurance and billing administration sector (the divisions of hospitals and doctors’ offices dedicated to administrative processing of bills and payments) could be made redundant. These potential 1.8 million lost jobs are frequently presented as if they constitute the net employment effect of M4A.13 This is a deeply flawed misrepresentation of Pollin and his colleagues’ work. In fact, their estimates are a gross (not net) measure of job displacement or “churn”—the regular process of workers starting and leaving jobs during the course of their work lives. Relative to the scale of other gross measures of job churn, the churn associated with M4A is not large.

It is true that one source of cost savings from the introduction of M4A is the reduced demand for insurance and billing administration. In turn, this reduced demand would shift employment out of these sectors. This could certainly cause challenges and economic distress for the workers within these sectors who are directly affected. But for some perspective, it is worth noting that 21.5 million workers were laid off in 2018 (BLS 2020b). If the 1.8 million workers that Pollin et al. (2018) identify as potentially being displaced by M4A were forced to transition over the four-year phase-in commonly identified with M4A plans, this would increase the national rate of layoffs by about 2%. It is also worth noting that even within just the finance and insurance sectors, there have been 1.7 million layoffs in the past four years (BLS 2020b). And yet it’s safe to say that very few people even in the business press have made any note of this. This is not a shock: Our economy generates a huge amount of job churn every year. This churn is the hallmark of growth in productivity—getting more economic output with fewer inputs. While productivity growth can indeed put downward pressure on jobs in the sector experiencing it directly, Autor and Salomons (2018) demonstrate that productivity gains within a given sector strongly boost job growth in other sectors, as the savings to households and businesses stemming from enhanced productivity increase purchasing power that supports demand for these other sectors’ outputs.

If workers in the insurance or billing administration sectors were particularly hard-pressed for reemployment prospects because of geographic isolation or low average levels of educational credentials, their displacement might pose particular concern to policymakers. But employment in the health insurance and billing administration sectors is not particularly geographically concentrated,14 and Pollin et al. (2018) show that 56.5% of workers in these sectors have a four-year college degree or more education, a far greater share than the overall labor force (in 2018, 37.6% of workers had a four-year degree or more education, according to EPI 2020b).

Substantial likely job gains in the health care sector

While it may seem counterintuitive, fundamental health reform like M4A is almost guaranteed to substantially expand employment in the health care sector overall, even taking reduced billing administration employment into account. Often people hear that fundamental reform is aimed at cost containment and then imagine that part of this cost containment will take the form of fewer jobs providing health care, but this is not necessarily the case. As noted before, the U.S. is an outlier in terms of how much it spends on health care, but its health care workforce as a share of the total workforce is not out of line with shares in other countries. For example, in 2017 the health care workforce in the U.S. was equal to 13.4% of the overall workforce, while the share averaged 12.9% in the 20 other richest OECD countries.15 Additionally, seven of these other countries had health care workforce shares equal to or higher than the U.S.’s 13.4%.16

Pollin et al. (2018) estimate that expanded access to health care could increase demand for health services by up to $300 billion annually. Given the current level of health spending and employment, this would translate into increased demand for 2.3 million full-time-equivalent workers in providing healthcare.17 Obviously all of the workers displaced from the health insurance and billing administration sectors could not necessarily transition into these jobs seamlessly, but well over 10% of workers in the health insurance sector, for example, are actually in health care occupations (e.g., they are doctors or nurses).18

Further, several M4A plans have provisions to pay for long-term care services. Reinhard et al. (2019) have estimated that in 2018, Americans provided roughly 34 billion hours in unpaid long-term care. If this care was divided up among full-time paid workers, it would require 17 million new positions. Of course, not all of this currently unpaid care would be converted into paid positions in the job market. But if even 10% of unpaid care translated into new jobs, it would create enough new demand for workers to essentially offset the displacement of workers in the health insurance and billing administration sectors.

The upshot: M4A creates a small amount of manageable churn but increases the overall demand for labor and boosts job quality

The job challenge relating to a fundamental health reform is managing a relatively small increase in job churn during an initial phase-in period. Most Medicare for All plans explicitly recognize and account for the costs of providing these workers the elements of a just transition. As noted previously, this sort of just transition is far easier when health care is universally provided.

Besides this challenge, the effect of fundamental reform like M4A on the labor market would be nearly uniformly positive. The effect of a fundamental reform like M4A on aggregate demand is almost certainly positive and will therefore boost the demand for labor. The number of jobs spurred by increased demand for new health care spending (including long-term care) will certainly be larger than the number displaced by realizing efficiencies in the health insurance and billing administration sectors.

Finally, the introduction of fundamental health reform like M4A—particularly reform that substantially delinks health care provision from specific jobs—would greatly aid how the labor market functions for typical working Americans. Take-home cash pay would increase, job quality would improve, labor market transitions could be eased for employers and made less damaging to workers, and a greater range of job opportunities could be considered by workers. The increased flexibility to leave jobs should lead to more productive “matches” between workers and employers, and small businesses and self-employment could increase.

Fundamental health reform would benefit typical American families in all sorts of ways. Importantly, contrary to claims that such reform might be bad for jobs, this reform could substantially improve how labor markets function for these families.

About the author

Josh Bivens joined the Economic Policy Institute in 2002 and is currently EPI’s director of research. His primary areas of research include mac­roeconomics, social insurance, and globalization. He has authored or co-authored three books (including The State of Working America, 12th Edition) while working at EPI, has edited another, and has written numerous research papers, including many for academic journals. He appears often in media outlets to offer eco­nomic commentary and has testified several times before the U.S. Congress. He earned his Ph.D. from The New School for Social Research.

Endnotes

1. Underinsurance includes coverage gaps throughout a year.

2. “Excess costs” typically refers to health care costs that are rising faster than other economic benchmarks, such as overall gross domestic product. The Congressional Budget Office, for example, defines excess costs as the percentage change in health care costs per beneficiary minus the percentage change in per capita gross domestic product (Banthin 2017).

3. Author’s analysis of data from BLS 2020a.

4. Author’s analysis of data from BEA 2020, Table 2.4.5U, line 120.

5. Data from BEA NIPA Table 7.8, line 17, divided by data from BEA NIPA Table 2.1, line 2 (BEA 2020).

6. If the share of total compensation directed toward premiums had grown by just 3.65 percentage points rather than the actual increase of 7.3 percentage points between 1960 and 2018, and the difference had all been directed toward increased wages and salaries, then wages and salaries in 2018 would have been higher by an amount equal to 3.65% of total compensation of employees in that year ($10.93 trillion), or $399 billion (BEA 2020).

7. A quick example may help make the point. If health insurance premiums rose by 7% per year, they would double in 10 years. If growth of other forms of compensation remained flat, this would lead to the share of health insurance premiums in total compensation doubling in 10 years. If premiums started from 1% of total compensation in the base year (as in 1960), this doubling would only “crowd out” 1% of total compensation that could be taken in the form of cash wages and salaries. If instead premiums started from a base of 8.4% of total compensation (as in 2018), this doubling would “crowd out” 8.4% of total compensation that could be taken in the form of cash wages and salaries.

8. The wage floor Schmitt and Jones specify for a good job is the median wage of men in 1979, adjusted for inflation. When adjusted for inflation into 2019 dollars using the CPI-U-RS, the 1979 men’s median hourly wage is $21.07 (EPI 2020a).

9. Specifically, in Table 1 Schmitt and Jones report that the share of good jobs would rise from 24.1% to 28.8% with the introduction of universal health coverage. Dividing this 4.7-percentage-point increase by 24.1% yields a 20% increase.

10. See Schmitt and Jones 2013, Table 2.

11. For evidence on the cost of providing health insurance by employer size, see Hertel-Fernandez, Gould, and Bivens 2009, Figure C.

12. For an explanation of how aggregate demand determines the level of unemployment, see Bivens 2018a.

13. See Pradhan 2019 for an example of these numbers being presented as the overall effect of M4A on jobs.

14. For example, if one sums the share of employment in health insurance, hospitals, and medical offices for each U.S. state, this share is essentially perfectly predicted by the state’s population share (correlation coefficient of 1.0). This is notably not true, for example, if one does the same exercise for manufacturing employment and state population shares (correlation coefficient of 0.8). Author’s analysis of data from BLS 2020c.

15. Data are from the OECD Health Statistics program (OECD 2019). The 20 OECD countries compared with the U.S. are Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Iceland, Ireland, Italy, Japan, Luxembourg, the Netherlands, New Zealand, Norway, Spain, Sweden, Switzerland, and the United Kingdom. Data for Canada and Japan are from earlier years (2016 and 2015, respectively) because data for 2017 are unavailable. Without Italy and Spain (both of which have very low health care workforce shares, below 8%), the U.S. would be very slightly below the OECD average for its share of the health care workforce.

16. The seven countries are Denmark, Finland, France, Netherlands, Norway, Sweden, and Switzerland.

17. In 2018, spending on health care services was $2.35 trillion (data from BEA 2020, NIPA Table 2.3.5), while full-time-equivalent employment was 18.25 million (BEA 2020, NIPA Table 6.5D). This translates into $129,000 in health spending per full-time-equivalent job. Dividing $300 billion by $129,000 yields the 2.3 million new full-time-equivalent workers needed to satisfy this new demand.

18. Author’s analysis of BLS 2019.

References

Autor, David, and Anna Salomons. 2018. “Is Automation Labor-Displacing? Productivity Growth, Employment, and the Labor Share.” Brookings Papers on Economic Activity Conference Drafts, March 2018.

Baker, Dean. 2015. Job Lock and Employer-Provided Health Insurance: Evidence from the Literature. AARP Public Policy Institute, March 2015.

Banthin, Jessica. 2017. “Health Care Spending Today and in the Future: Impacts on Federal Deficits and Debt.” Congressional Budget Office briefing, presented to a conference organized by the Center for Sustainable Health Spending, Washington, D.C.

Bivens, Josh. 2018a. Recommendations for Creating Jobs and Economic Security in the U.S.: Making Sense of Debates About Full Employment, Public Investment, and Public Job Creation. Economic Policy Institute, March 2018.

Bivens, Josh. 2018b. The Unfinished Business of Health Reform: Reining in Market Power to Restrain Costs Without Sacrificing Quality or Access. Economic Policy Institute, October 2018.

Bureau of Economic Analysis (BEA). 2020. National Income and Product Accounts, NIPA Tables (online database), Tables 2.1, 2.3.5, 2.4.5U, 6.5D, and 7.8. Accessed February 2020.

Bureau of Labor Statistics (BLS). 2019. “National Industry-Specific Occupational Employment and Wage Estimates.” NAICS 524114 – Direct Health and Medical Insurance Carriers. Last modified April 2, 2019.

Bureau of Labor Statistics (BLS). 2020a. Consumer Price Index program, “Databases, Tables & Calculators by Subject” (interactive data retrieval portal), Series ID CUUR0000SEME. Accessed February 2020.

Bureau of Labor Statistics (BLS). 2020b. Job Openings and Labor Turnover Survey (JOLTS), “Databases, Tables & Calculators by Subject” (interactive data retrieval portal), Series ID JTU00000000LDL and JTU52000000LDL. Accessed February 2020.

Bureau of Labor Statistics (BLS). 2020c. Quarterly Census of Employment and Wages Data (interactive data retrieval portal).

Collins, Sara R., Herman K. Bhupal, and Michelle M. Doty. 2019. Health Insurance Coverage Eight Years After the ACA: Fewer Uninsured Americans and Shorter Coverage Gaps, but More Underinsured. The Commonwealth Fund, February 2019.

Economic Policy Institute (EPI). 2017. State of Working America Data Library, “Health Insurance Coverage.” Last updated February 13, 2017.

Economic Policy Institute (EPI). 2020a. State of Working America Data Library, “Median/Average Hourly Wages.” Last updated February 20, 2020.

Economic Policy Institute (EPI). 2020b. State of Working America Data Library, “Wages by Education.” Last updated February 20, 2020.

Estevez-Abe, Margarita, Torben Iversen, and David Soskice. 2001. “Social Protection and the Formation of Skills: A New Interpretation of the Welfare State.” In Varieties of Capitalism: The Institutional Foundations of Comparative Advantage, edited by Peter A. Hall and David Soskice. New York: Oxford Univ. Press. For a publicly available earlier version of the paper, see the 1999 paper prepared for presentation at the 95th American Political Association Meeting in Atlanta, Georgia: http://www.people.fas.harvard.edu/~iversen/PDFfiles/apsa992.pdf.

Hacker, Jacob. 2002. The Divided Welfare State: The Battle over Public and Private Social Benefits in the United States. Cambridge Univ. Press.

Hertel-Fernandez, Alexander, Elise Gould, and Josh Bivens. 2009. Health Care Reform—Big Benefits for Small Businesses. Economic Policy Institute, July 2009.

Jørgensen, Helene, and Dean Baker. 2014. The Affordable Care Act: A Family-Friendly Policy. Center for Economic and Policy Research, September 2014.

Organisation for Economic Co-operation and Development (OECD). 2018. Entrepreneurship at a Glance: 2018 Highlights. October 2018.

Organisation for Economic Co-operation and Development (OECD). 2019. OECD Health Statistics 2019 (online database). Last updated November 15, 2019 (accessed February 2020).

Organisation for Economic Co-operation and Development (OECD). 2020. “Self-Employment Rate” (interactive online data table). Accessed February 2020.

Pollin, Robert, James Heintz, Peter Arno, Jeannette Wicks-Lim, and Michael Ash. 2018. Economic Analysis of Medicare for All. Political Economy Research Institute, November 2018.

Pradhan, Rachana. 2019. “Medicare for All’s Jobs Problem.” Politico, November 25, 2019.

Reinhard, Susan, Lynn Friss Feinberg, Ari Houser, Rita Choula, and Molly Evans. 2019. Valuing the Invaluable 2019 Update: Charting a Path Forward. AARP Public Policy Institute, November 2019.

Schmitt, John, and Janelle Jones. 2013. Making Jobs Good. Center for Economic and Policy Research, April 2013.

Schmitt, John, and Nathan Lane. 2009. An International Comparison of Small Business Employment. Center for Economic and Policy Research, August 2009.

Figure A shows in green the states with minimum wage increases that occurred through legislation or referendum in 2019, while states in blue had automatic increases resulting from indexing the minimum wage to inflation. Workers in states that increased their minimum wage between 2018 and 2019 account for about 55% of the U.S. workforce. The nominal minimum wage increases ranged from $0.05 (0.5%) in Alaska to $1.00 (9.1%−10.0%) in California, Massachusetts, and Maine.

Figure A

Figure B compares 10^th-percentile wage growth in states with minimum wage increases compared to those without increases. Growth at the 10th percentile in states without minimum wage increases was much slower (0.9%) than in states with any kind of minimum wage increase (4.1%). This result holds true for both men and women. The 10th-percentile men’s wage grew 3.6% in states with minimum wage increases, compared with 0.7% growth in states without any minimum wage increases, while women’s 10th-percentile wages grew 2.8% in states with minimum wage increases and 1.4% in states without.

Figure B

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Past decisions that have weakened our economic policy infrastructure will hamper our response to COVID-19; this is already baked into the cake. But there are some short-run ameliorative actions we can take that might help, and there are long-run policy changes that will aid our response to future epidemics.

In technical economic terms, COVID-19 combines potential supply shocks with sector-specific demand shocks. Basically, supply shocks hamper our ability to produce goods and services, and demand shocks are sharp cutbacks in spending from households, businesses, or governments. I provide a list for policymakers of what could/should be considered to deal with some of these below.

The supply shocks come from disrupted global value chains, as, for example, Chinese production of inputs used by U.S. manufacturing and construction firms are not delivered on time because Chinese factories have temporarily closed. In countries where schools are shut down for long periods of time, a shock to labor supply can occur as working parents have to stay home to care for kids.

The potential sector-specific demand shock is to businesses where consumption is largely social—done with other people around. Think bars, restaurants, grocery stores, and malls. As people avoid social contact to minimize disease transmission, this leads to less activity in these sectors.

These effects mean it will be hard indeed for policymakers to spare the economy any pain from this.

There’s very little that can be done about the supply-side shocks—particularly in the short run. Demand-side shocks are generally easier to address with policy (in theory—policymakers still often fumble the ball in this regard), but the specific nature of the demand shocks associated with COVID-19 make them slightly harder to address. Simply giving households more money won’t boost consumption much in the sectors likely to be affected—the pullback in consumption is not driven by income constraints, but due to concerns over catching the illness.Read more

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In her testimony, Lee discussed the history of U.S. trade policy toward China, problems with Trump’s “phase one” deal with China, and fundamental flaws in the U.S.–China economic relationship. According to new EPI research, the growing U.S.–China trade deficit was responsible for the loss of 3.7 million U.S. jobs between 2001 and 2018. These job losses are spread across all 50 states and the District of Columbia—and every congressional district in America.

Watch her testimony:

Given the stark rise in inequality over the past four decades (Bivens and Mishel 2015), it makes sense that the first tranche of revenues to pay for these current and possible future commitments to public spending should come from those at the top. In this report, we provide detailed 10-year estimates for options to raise revenue in a progressive manner, as well as brief explanations of the various proposals.

Unless otherwise noted, revenue estimates are largely taken from Tax Policy Center (TPC) scores of our Budget for Shared Prosperity, put together for the Peter G. Peterson Foundation’s “Solutions Initiative” (Blair 2019a, 2019b; Peter G. Peterson Foundation 2019). A capsule description and score for each can be found in Table 1 at the end of this report.

Individual income taxes

Construct fairer income rates and brackets

Largely sparked by a 60 Minutes interview in which Rep. Alexandria Ocasio-Cortez (D-N.Y.) suggested a top marginal tax rate of 70% (Picchi 2019), policy discussions in Washington are finally taking much higher top marginal tax rates seriously.

In the past decade, the mantle of higher marginal tax rates for those at the top was taken up by Rep. Jan Schakowsky (D-Ill.), whose Fairness in Taxation Act includes significantly higher tax rates for millionaires and billionaires (Schakowsky 2011).

In our Budget for Shared Prosperity, we make our own proposal for higher marginal tax rates, particularly at the top end. Our proposal combines rates and brackets from before both the Bush and Trump administration’s tax cuts, along with Rep. Schakwosky’s Fairness in Taxation Act. Specific rates and brackets for single filers (doubled for married filers) in our plan are detailed in Blair 2019a.

TPC has estimated that our particular proposal would raise about $2.7 trillion over 10 years. The more important point, however, is simply the recognition that there is room for raising the top marginal rate on ordinary income to raise revenue progressively (Fieldhouse 2013).

Assess a surtax on annual income of the rich

The rates and brackets listed above constitute a full rewrite of the income tax system. Failing that sort of broad reform, a subset of this would be the addition of a surtax on the incomes of the very rich. One such proposal is to assess a 10-percentage-point surtax on adjusted gross income (AGI) in excess of $1 million for single filers (and $2 million for joint filers). Importantly, such a surtax would apply to both income from work and income from wealth. The Tax Policy Center has estimated this surtax would raise about $634 billion in additional revenues over 10 years (ATF 2019b) and there are reasons to believe this amount could be substantially increased with some basic reforms to how capital income is taxed (see below).

Tax capital income using a mark-to-market approach

Every year, workers pay income taxes on what they earn from their labor, while high-income households that make their money from capital income can defer taxes until they “realize” these gains. Drawing on details from reports by Kamin (2016) and Toder and Viard (2016), we propose applying the capital gains tax on unrealized capital gains, not just realized gains. This proposal would ensure that high-income households are paying the taxes they owe on their increase in wealth annually. The proposal is estimated to raise $1.8 trillion over 10 years.

Tax all income equally

By far the largest, and most politically ambitious, proposal in our Budget for Shared Prosperity is doing away with every single deduction, exemption, and credit in the individual income tax system except for the Earned Income Tax Credit (EITC). These deductions, exemptions, and credits are often referred to as tax expenditures, because they operate as “spending through the tax code” that is ostensibly meant to encourage socially desirable actions like saving for retirement or investing in productive plants and equipment. But tax expenditures are regressive, largely benefiting the top 20%, and the social benefits they are meant to provide could be provided more equitably and efficiently through direct government spending (Blair 2019b).

While it would be politically difficult to close these loopholes, the revenue potential of doing so is immense—on the order of paying for Medicare for All (Blair 2019b). Our proposal to tax all income equally would raise $15.4 trillion over 10 years.

Tax wealth like work

If abolishing each and every tax expenditure is unrealistic (especially in the short run), we can prioritize those tax expenditures that are most regressive and would therefore be most beneficial to close for distributional reasons. A particularly regressive tax expenditure is the preferential tax rate applied to income from capital gains and dividends. There is no convincing economic case to be made for taxing capital income at a lower rate than income earned from work (Blair 2019b). And the preferential rate on capital income is extraordinarily regressive, with the top 1% getting 75% of the benefits (TPC 2018a).

Closing this loophole requires other reforms of the capital taxation system to ensure that rich taxpayers don’t dodge the taxes they owe, but the Institute on Taxation and Economic Policy (ITEP) estimates that doing so would raise $2.4 trillion over 10 years (ATF 2019a).

Repeal the 20% deduction for certain business income

The Tax Cuts and Jobs Act (TCJA) created a new loophole that is purportedly for “small businesses” via its deduction for pass-through business income. Despite the claim that it’s meant to help small businesses, 55% of the deduction goes to the top 1% (TPC 2018b). Not only do the benefits flow to high-income households, but this new loophole rewards tax avoidance that these business owners are already engaging in, typically through convoluted ownership structures (Cooper et al. 2015). High-income owners of pass-through income drive much of the “tax gap”—the difference between total taxes owed and taxes paid on time (Jacoby 2019). The loophole has no economic rationale, and its detrimental effects have already been seen in Kansas (Blair 2016). Getting rid of this loophole would raise $387 billion over 10 years (ATF 2019a).

Expand the EITC to all working adults

In 2018, the EITC pulled 5.6 million people out of poverty (CBPP 2019). But one group that does not benefit due to the current structure of the EITC is low-income childless adults, who receive far smaller EITCs (Marr and Huang 2019). Expanding the EITC to give this group larger benefits would fight poverty and would also make the EITC a more effective complement to state-level minimum wage increases spreading throughout the country (Rothstein and Zipperer 2020). Our proposal to increase the EITC for childless adults and noncustodial parents would cost just $43 billion over 10 years.

Close wealth loopholes to strengthen Medicare

Some rich owners of pass-through business are able to avoid the Net Investment Income Tax, an additional tax on high-income households created by the Affordable Care Act. Closing this loophole would raise $209 billion over 10 years.

Social insurance taxes

Shield Social Security from rising inequality

Currently only earnings up to a maximum of $137,700 are taxed by Social Security payroll taxes (SSA 2020). This taxable maximum rises each year by the amount that average wages rise. But because the earnings of those above the cap have tended to rise much faster than average earnings in recent decades (a sign of rising inequality), the share of total earnings subject to the Social Security tax has fallen. Following the last major reform to Social Security, 90% of taxable earnings were covered in 1983 (CBO 2018a). But the rise in income inequality since then has meant that as of 2016 only 83% of earnings were covered. Reversing this trend by setting the cap to capture 90% of earnings in each year would raise $1.2 trillion in revenue over 10 years, according to TPC estimates.

Close the business payroll tax loophole

Currently, workers contribute to Social Security and Medicare through Federal Insurance Contributions Act (FICA) payroll taxes on their earnings. Similarly, sole proprietors contribute to Social Security and Medicare through Self-Employment Contributions Act (SECA) payroll taxes on their net business income. But some owners of different types of pass-through businesses are able to avoid some of the SECA taxes they should owe (CBO 2018b). Closing this loophole would raise $170 billion over 10 years, according to TPC estimates.

Corporate income taxes

Restore responsible corporate tax rates

The TCJA lowered the rate on corporate income from 35% to 21%. Evidence prior to the passing of the TCJA was overwhelming that the benefits of corporate rate cuts go to those at the top of the income distribution (Bivens and Blair 2017, 2018). And new data since the TCJA passed does nothing to change this view (Blair 2019c). Returning the corporate income tax rate to 35% would be extraordinarily progressive and is estimated to raise about $1.4 trillion over 10 years.

End offshore outsourcing

Prior to the TCJA, U.S. multinationals avoided taxes by booking trillions of dollars in profits offshore in tax havens (Clemente, Blair, and Trokel 2016). The pre-TCJA law allowed firms to defer taxes until the profits were repatriated to owners in the United States. The TCJA did little to fix this, and the TCJA may even incentivize the offshoring of jobs along with profits (Wamhoff 2018). Essentially, the TCJA moved the United States to a “territorial” tax system where most profits earned abroad are essentially untaxed by the U.S. government.

We propose moving to a worldwide system with a 35% tax rate on corporate income, but removing the option for firms to defer taxation. This option would require strong “anti-inversion” provisions to keep firms from trying to declare themselves no longer “American” companies subject to U.S. taxation, even as the bulk of their sales and workforces (and even managerial workforce) resides in the United States. This reform could be accomplished by following the parameters of Rep. Doggett (D-Texas) and Sen. Whitehouse’s (D-R.I.) No Tax Breaks for Outsourcing Act (Doggett 2018). TPC estimates this would raise $619 billion over 10 years.

Close corporate tax loopholes

The corporate tax code is littered with loopholes that allow highly profitable corporations to avoid paying the full taxes they owe (Clemente, Blair, and Trokel 2016). Our Budget for Shared Prosperity proposes getting rid of almost every single corporate tax expenditure. This proposal is estimated to raise $456 billion over 10 years.

Estate and gift and wealth taxes

Tax inherited wealth fairly and close estate tax loopholes

The estate tax has been drastically eroded by legislation passed since 2001, with only 0.1% of estates paying any estate tax today (CBPP 2018). And even when estates do owe taxes, large loopholes allow many wealthy estates to avoid them (Huang and Cho 2017). Our proposal would reinstitute estate tax exemptions and rates from the early 2000s and close the various loopholes that riddle the estate tax, using the parameters of Sen. Bernie Sanders’ (I-Vt.) Responsible Estate Tax Act (Senate Budget Committee 2015). Combined, these two actions would raise $689 billion over 10 years.

Replace estate and gift taxes with an inheritance tax

Another option for taxing inherited wealth is to better target large inheritances by replacing the current tax, based on large overall estates, with a tax based just on the amount inherited by the beneficiary. A proposal for this was put forth by Lily Batchelder of the Washington Center for Equitable Growth (Batchelder 2016). Implementation of Batchelder’s proposal could raise as much as $670 billion over 10 years (ATF 2019a).

Tax the richest’s wealth holdings

The Democratic presidential primary has put discussions of a wealth tax front and center in Washington policy discussions. Our proposal, for progressive rates on wealth that start at 0.1% on net worth above $10 million and cap out at 1% for net worth above $19 million, would raise about $1.4 trillion over 10 years.

Excise and other taxes

Institute a carbon tax and dividend to fight climate change

A carbon tax by itself would be regressive, as consumption is a higher share of income for nonrich households. Because of this, most proposals to impose a carbon tax include a measure to recycle the money raised—often in a progressive manner—to shield the living standards of low- and moderate-income households. These rebates mean that a carbon tax and refund tends to be revenue-neutral, but we still include this proposal among our progressive revenue options because the overall economic benefits of mitigating climate change are large and progressive.

Enact a Wall Street speculation tax

There is strong evidence that the marginal value of financial transactions in the U.S. economy are near-zero, or even negative (Bivens and Blair 2016). That is, today’s financial markets largely extract economic rents by overcharging users for financial intermediation. With much of this rent extraction stemming from excessive churn, a well-designed financial transactions tax (FTT) has the potential to dampen the rents that the financial sector siphons off from the rest of the economy by reducing speculative trading and encouraging more productive investment. TPC estimates that the FTT in our Budget for Shared Prosperity would raise about $1.1 trillion over 10 years, while we think there’s potential for a well-designed FTT to raise considerably more (Bivens and Blair 2016).

Tax too-big-to-fail banks

The global financial crisis of 2008 showed plainly the substantial risks associated with a financial sector heavily reliant on “systemically important financial institutions” (SIFIs), or banks that are “too big to fail.” A financial fee of 0.15% on certain liabilities of SIFIs would raise $99 billion over 10 years.

Table 1

References

Americans for Tax Fairness (ATF). 2019a. Fair Taxes Now: Revenue Options for a Fair Tax System. April 2019.

Americans for Tax Fairness (ATF). 2019b. Tax Policy Center Revenue Estimates for 10% Surtax. October 2019.

Batchelder, Lily. 2016. The “Silver Spoon” Tax: How to Strengthen Wealth Transfer Taxation. Washington Center for Equitable Growth, October 2016.

Bivens, Josh, and Hunter Blair. 2016. A Financial Transactions Tax Would Help Ensure Wall Street Works for Main Street. Economic Policy Institute, July 2016.

Bivens, Josh, and Hunter Blair. 2017. “Competitive” Distractions: Cutting Corporate Tax Rates Will Not Create Jobs or Boost Incomes for the Vast Majority of American Families. Economic Policy Institute, May 2017.

Bivens, Josh, and Hunter Blair. 2018. “The Likely Economic Effects of the Tax Cuts and Jobs Act (TCJA): Higher Incomes for the Top, No Discernible Effect on Wage Growth for Typical American Workers.” Testimony submitted to the Tax Policy Subcommittee of the U.S. House of Representatives Ways and Means Committee, June 1, 2018.

Bivens, Josh, and Lawrence Mishel. 2015. Understanding the Historic Divergence Between Productivity and a Typical Worker’s Pay: Why It Matters and Why It’s Real. Economic Policy Institute, September 2015.

Blair, Hunter. 2016. “How Bad Are Trump’s Policy Instincts? He’s Taking Tax Advice from Kansas Governor Sam Brownback.” Working Economic Blog (Economic Policy Institute), April 26, 2016.

Blair, Hunter. 2019a. “Detailed Estimates for Policies in EPI’s ‘Budget for Shared Prosperity’.” Working Economics Blog (Economic Policy Institute), July 29, 2019.

Blair, Hunter. 2019b. EPI’s Model Federal Budget and Tax Plan: How We Can Raise the Revenue Needed to Provide Universal Health Care, Strengthen Safety Nets, and Shore Up Public Investment. Economic Policy Institute, July 2019.

Blair, Hunter. 2019c. “On Its Second Anniversary, the TCJA Has Cut Taxes for Corporations, but Nothing Has Trickled Down.” Working Economics Blog (Economic Policy Institute), December 2019.

Center on Budget and Policy Priorities (CBPP). 2018. Policy Basics: The Federal Estate Tax. November 2018.

Center on Budget and Policy Priorities (CBPP). 2019. Policy Basics: The Earned Income Tax Credit. December 2019.

Clemente, Frank, Hunter Blair, and Nick Trokel. 2016. Corporate Tax Chartbook: How Corporations Rig the Rules to Dodge the Taxes They Owe. Economic Policy Institute, December 2016, chart 1 updated June 2017.

Congressional Budget Office (CBO). 2018a. “Revenues—Option 20: Increase the Maximum Taxable Earnings for the Social Security Payroll Tax.” In Options for Reducing the Deficit: 2019 to 2028, December 2018.

Congressional Budget Office (CBO). 2018b. “Revenues—Option 22: Tax All Pass-Through Business Owners Under SECA and Impose a Material Participation Standard.” In Options for Reducing the Deficit: 2019 to 2028, December 2018.

Cooper, Michael, John McClelland, James Pearce, Richard Prisinzano, Joseph Sullivan, Danny Yagan, Owen Zidar, and Eric Zwick. 2015. “Business in the United States: Who Owns It and How Much Tax Do They Pay?” Working paper, October 2015.

Doggett, Lloyd. 2018. “Rep. Doggett, Sen. Whitehouse Introduce Bill to End Tax Breaks for Exporting Jobs, Profits” (press release). Office of U.S. Congressman Lloyd Doggett, February 27, 2018.

Fieldhouse, Andrew. 2013. How High Should Top Income Tax Rates Be? (Hint: Much Higher). Economic Policy Institute Commentary, April 2013.

Huang, Chye-Ching, and Chloe Cho. 2017. Ten Facts You Should Know About the Federal Estate Tax. Center on Budget and Policy Priorities. October 2017.

Jacoby, Samantha. 2019. “Policymakers Should Ensure Pass-Throughs Pay More of the Taxes They Owe.” Off the Charts (Center on Budget and Policy Priorities blog), November 22, 2019.

Kamin, David. 2016. Taxing Capital: Paths to a Fairer and Broader U.S. Tax System. Washington Center for Equitable Growth, August 2016.

Marr, Chuck, and Yixuan Huang. 2019. Childless Adults Are Lone Group Taxed into Poverty: EITC Expansion Could Address This Problem. Center on Budget and Policy Priorities, June 2019.

Peter G. Peterson Foundation. 2019. “Solutions Initiative 2019” (web page).

Picchi, Aimee. 2019. “Does Alexandria Ocasio-Cortez Want to ‘Soak the Rich’?” CBS News, January 7, 2019.

Rothstein, Jesse, and Ben Zipperer. 2020. The EITC and Minimum Wage Work Together to Reduce Poverty and Raise Incomes. Economic Policy Institute, January 2020.

Schakowsky, Jan. 2011. “Schakowsky Introduces Bill to Tax Millionaires and Billionaires” (press release). Office of U.S. Congresswoman Jan Schakowsky, March 16, 2011.

Senate Budget Committee. 2015. Fact Sheet: The Responsible Estate Tax Act. July 2015.

Social Security Administration (SSA). 2020. Fact Sheet: 2020 Social Security Changes.

Tax Policy Center (TPC). 2018a. “Model Estimates: T18-0183 – Tax Benefit of the Preferential Rates on Long-Term Capital Gains and Qualified Dividends, Baseline: Current Law, Distribution of Federal Tax Change by Expanded Cash Income Percentile, 2018” (data table). October 2018.

Tax Policy Center (TPC). 2018b. “Model Estimates: T18-0213 – Tax Benefit of the 20 Percent Deduction for Qualified Pass-Through Business Income, Baseline: Current Law, Distribution of Federal Tax Change by Expanded Cash Income Percentile, 2018” (data table). October 2018.

Toder, Eric, and Alan Viard. 2016. A Proposal to Reform the Taxation of Corporate Income. Tax Policy Center, June 2016.

Wamhoff, Steve. 2018. The New International Corporate Tax Rules: Problems and Solutions. Institute for Taxation and Economic Policy, June 2018.

Unfortunately, preparing for the “significant disruption” will be economically unimaginable for one group of Americans—the millions of people in the United States who do not have access to paid sick days or have health insurance with a regular health care provider.

The CDC released very clear instructions to help prevent the spread of respiratory diseases, including staying home when you are sick. Not everyone has that option.

Overall, just under three-quarters (73%) of private sector workers in the United States have the ability to earn paid sick time at work. And, as shown in the figure below, access to paid sick days is vastly unequal. The highest wage workers are more than three times as likely to have access to paid sick leave as the lowest paid workers. Whereas 93% of the highest wage workers had access to paid sick days, only 30% of the lowest paid workers were able to earn sick days. In this way, access to paid sick days increases with wages among workers, disproportionately denying workers at the bottom this important security. And, low-wage workers are more likely to be found in occupations where they have contact with the public—think early care and education workers, home health aides, restaurant workers and food processors. When workers or their family members are sick, they shouldn’t have to decide between staying home from work to care for themselves or their dependents and paying rent or putting food on the table. But, that is the situation our policymakers have put workers in.Read more

The latest findings on wage growth as documented in EPI’s State of Working America Wages 2019 report indicate wages in general are slowly improving with the growing economy, but wage inequality has grown and wage gaps have persisted, and in some cases, worsened. In this post, I will highlight the worsening black-white wage gap and look at it from multiple dimensions. Since 2000, by any way it’s measured, the wage gap between black and white workers has grown significantly.

The figure below compares wages for black and white workers over the last 19 years, highlighting the gaps in wages in 2000, the last time the economy was closest to full employment, 2007, the last business cycle peak before the Great Recession, and 2019, the latest data available. Against these benchmarks, I illustrated the growth in the average gap, the gap for low-, middle-, and high-wage workers, the gap for workers with a high school diploma, a college degree, and an advanced degree, and a regression-adjusted wage gap (controlling for age, gender, education, and region).

Figure A

The black–white wage gap is smallest at the bottom of the wage distribution, where the minimum wage serves as a wage floor. The largest black–white wage gap as well as the one with the most growth since the Great Recession, is found at the top of the wage distribution, explained in part by the pulling away of top earners generally as well as continued occupational segregation, the disproportionate likelihood for white workers to occupy positions in the highest-wage professions.

It’s clear from the figure that education is not a panacea for closing these wage gaps. Again, this should not be shocking, as increased equality of educational access—as laudable a goal as it is—has been shown to have only small effects on class-based wage inequality, and racial wealth gaps have been almost entirely unmoved by a narrowing of the black–white college attainment gap, as demonstrated by William Darity Jr. and others.

Black workers can’t simply educate their way out of the gap. Across various levels of education, a significant black–white wage gap remains. Even black workers with an advanced degree experience a significant wage gap compared with their white counterparts. And after controlling for age, gender, education, and region, black workers are paid 14.9% less than white workers.

While the wage gaps differ depending on measure, what is obvious from the trends displayed is that the gaps widened in the full business cycle 2000–2007 and continued to grow in the Great Recession and its aftermath. Even though the black unemployment rate has fallen precipitously over the last several years, wage growth has remained particularly weak for black workers.

As always, it’s important to remember the historical and social contexts for differences in black and white labor market experiences and labor market outcomes (see Razza). Workers’ ability to claim higher wages rests on a host of social, political, and institutional factors outside of their control. The systematic social deprivation and economic disadvantage is maintained and reinforced by those with economic and political power. Furthermore, occupational segregation plays a significant role in these gaps, for both black men and black women. And, black women, in particularly, can face larger wages gaps with white men than the sum of their parts, meaning the black women face a double wage penalty for their race and gender. The trends in black–white wage gaps found here are supported by other important research that shows that black-white wage gaps expanded with rising inequality from 1979 to 2015.

Given a long history of excluding black Americans from social and political institutions that boost wage growth, the stubbornness of racial wage gaps is less surprising. However, the fact that they are getting worse is troubling. The good news is that policy can make a difference.

We see in the figure that the minimum wage keeps the lowest-wage black workers from even lower wages. In states that increased in the minimum wage between 2018 and 2019, low-wage workers saw stronger wage growth than in states that had no increase in their minimum wage in that period. Raising the federal minimum wage would disproportionately benefit black workers because they are overrepresented among low-wage workers and are less likely to live in states or localities that have passed a minimum wage that is higher than the current federal minimum.

Aside from strengthening and enforcing labor standards such as the minimum wage, making it easier for workers to form unions can narrow the black–white wage gap. Black workers are more likely to be in a union than white and get a bigger wage boost to being in a union than white. Therefore, unions can help shrink the black–white wage gap. Related, research has shown that the decline of unionization led to an expansion of the black–white wage gap.

Using all fiscal and monetary policy levers to achieve and maintain high-pressure labor markets can improve relative labor market outcomes for black workers, including participation in the labor force and work hours as well as wage growth. The U.S. certainly saw this stronger across the board growth in the tight labor market of the late 1990s.

In 2019, black wages exceeded their 2000 and 2007 levels across the wage distribution for the first time in this recovery. I’m hopeful that as the economy continues to move toward genuine full employment, black workers will see their wages rise. But it will take more than a couple of years of a full-employment economy to close racial wage gaps and compensate for years of lower wages, lower incomes, and lower wealth.

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

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

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

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

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).

Acknowledgments

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.

Endnotes

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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