Weekend reading: Addressing earnings inequality across the U.S. labor force edition

Posted on by Maria Monroe

This is a post we publish each Friday with links to articles that touch on economic inequality and growth. The first section is a round-up of what Equitable Growth published this week and the second is relevant and interesting articles we’re highlighting from elsewhere. We won’t be the first to share these articles, but we hope by taking a look back at the whole week, we can put them in context.

Equitable Growth round-up

This Women’s History Month marks 1 year since COVID-19 restrictions began in many U.S. cities and states, and thus the unofficial start of what many have dubbed the “shecession,” thanks to the disproportionate impact of the coronavirus recession on women workers. Delaney Crampton looks at recent research on women’s longstanding challenges in the U.S. economy due to employer monopsony power, the child care crisis, and pay equity. These issues affect women of color in particular, both historically and today. One year into the pandemic, women workers of color are still experiencing higher rates of unemployment and loss of earnings than other workers. Crampton summarizes a series of studies showing how women, and especially women of color, face significant hurdles in the labor market and why each of these crises—earnings inequality, lack of access to child care, and monopsony power—must be addressed.

This week also marked Asian American and Pacific Islander Women’s Equal Pay Day, the day in 2021 until which, on average, Asian American, Native Hawaiian, and Pacific Islander women have to work, from the start of 2020, to earn as much as White, non-Latino men earned in 2020 alone. Kate Bahn and Carmen Sanchez Cumming explain the data on this 15-cent wage gap, particularly amid the coronavirus recession, due to the over-representation of AANHPI men and women among front-line workers. Though the wage divide between White, non-Latino men and AANHPI women narrowed significantly over the past two decades, Bahn and Sanchez Cumming write, many Asian American women continue to face pay discrimination and other obstacles in the labor market. A challenge for economic researchers lies in the lack of data that are disaggregated among the many subgroups of workers and families within the AANHPI community—an issue that Bahn and Sanchez Cumming argue is necessary to address in order to ensure that policymakers can target programs and aid more effectively.

Earnings inequality is a big driver of economic inequality in the United States. Recent research shows, however, that it’s not only what you do but also where you work that matters. Increasing alignment of earnings in occupations and at workplaces is making inequality worse. Nathan Wilmers and Clem Aeppli detail the findings in their new working paper, which showcases the importance of studying earnings inequality at workplaces and in occupations together, as high-paying occupations are increasingly clustered at high-paying workplaces and low-paying jobs at low-paying workplaces. This means higher-paid workers are earning increasingly more, while low-paid workers earn even less—resulting in “worse earnings inequality than either between-occupation or between-workplace variation would create by themselves,” the co-authors conclude. They then explain the implications for policymaking to address these two types of earnings inequality together rather than in silos.

Workers in the United States who typically experience lower earnings than they should are gig workers. Kathryn Zickuhr details how ride-hail drivers, such as those who work for Uber Technologies Inc. and Lyft Inc., are often misclassified as independent contractors by their employers in order for those companies to avoid paying them a minimum wage or providing full-time worker benefits such as health insurance or paid sick leave. Zickuhr then looks at a recent study of New York City’s 2019 pay standard for gig workers, describing how it increased the average hourly earnings of ride-hail drivers to be more in line with the city’s $15 minimum hourly wage. But, she notes, misclassification deprives these workers of more than wages. While the pay standard did effectively boost pay, updating labor laws to prevent misclassification and ensure worker protections would better address the lack of economic security and benefits that gig workers experience.

Every month, the U.S. Bureau of Labor Statistics releases data on hiring, firing, and other labor market flows from the Job Openings and Labor Turnover Survey, better known as JOLTS. This week, the BLS released the latest data for January 2021. Bahn and Sanchez Cumming put together four graphics highlighting trends in the data.

Links from around the web

One way to address the vast racial wealth divide between Black and White Americans in the United States is reparations—and one Chicago suburb is set to become the first city to financially compensate its Black residents for centuries of wealth and opportunity gaps resulting from enslavement, systemic racism, and discrimination. NBC News’ Safia Samee Ali reports the latest news on a reparations program in Evanston, Illinois, a program approved in 2019 and funded via community donations and revenue from a 3 percent tax on recreational marijuana sales. Critics are debating the legislation from several sides, but proponents argue that it’s an historic model that could be used in cities across the United States—at least until a federal reparations program is enacted. The city council is expected to vote in the coming weeks on a plan to release the first $400,000 to address housing needs.

President Joe Biden this week signed the $1.9 trillion American Rescue Plan and with it, may have started the second War on Poverty, writes Vox’s Dylan Matthews. The COVID-19 relief bill includes some of the most far-reaching anti-poverty policies in decades, Matthews explains, harkening back to former President Lyndon B. Johnson’s collection of government programs to combat U.S. poverty in the 1960s. The parallels between the two presidents and their two anti-poverty plans are clear, and while the American Rescue Plan may not be as impactful, it is estimated that poverty will fall by one-third overall, with child poverty cut in half, as a result of the bill’s enactment. Matthews runs through the various policies included in President Biden’s plan and the effects they’ll likely have on poverty, then turns to policies the president can push for in future legislation to continue waging this war on poverty now that the American Rescue Plan has been signed.

The passage of the American Rescue Plan also signals a shift in lawmakers’ willingness to use their authority to set the U.S. economy on the path to recovery, writes The New York Times’ Neil Irwin in The Upshot. The coronavirus recession shows that leaders from both parties are willing to borrow and spend money to “extract the nation from economic crises … [a power] they ceded for much of the last four decades.” This change stands in direct contrast to the response to the Great Recession of 2007–2009, Irwin argues, which was largely dealt with by the Federal Reserve—an entity with much more limited tools to address recessions. And, if successful, the American Rescue Plan could be a blueprint for how the U.S. government responds to future crises.

While the American Rescue Plan, on its face, is a coronavirus relief package, it also will have an impact on U.S. climate policy, writes The Atlantic’s Robinson Meyer. Of course, it isn’t a sweeping, climate change-specific bill, but by reviving many institutions that are central to addressing climate change that have been battered by the pandemic, it is part and parcel of the Biden administration’s overall climate agenda. Meyer briefly examines the various programs in the bill that will impact U.S. climate policy, from boosting public transit agencies to supporting state and local governments, and shows how this legislation has begun to shift political perspectives in such a way that opens the door for fighting climate change directly.

Friday figure

Percent change in U.S. employment for workers 20-years-old and over by race, gender, and ethnicity, February 2020–February 2021

Figure is from Equitable Growth’s “Women’s History Month: Systemic gender discrimination continues to harm working women amid the coronavirus recession” by Delaney Crampton.

Women’s History Month: Systemic gender discrimination continues to harm working women amid the coronavirus recession

Posted on by Emilie Openchowski
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Women’s History Month is observed every March to celebrate the contributions of women politically, economically, and culturally throughout the history of the United States. It is an important month for commemorating the great contributions of women pioneers in economics such as the late Sadie Alexander, Joan Robinson, and Elinor Ostrom, and the current secretary of the U.S. Department of the Treasury, Janet Yellen.

But with the widely felt impacts brought on by the coronavirus recession, it is also a time for acknowledging the struggles women are facing in the U.S. economy when it comes to the labor market and monopsony power, the child care crisis, and pay equity. Recent research demonstrates that these are all areas that have plagued women in the workforce, particularly women of color, historically and right up to today, and need to be addressed specifically as women claw their way out of this recession.  

A recent “Expert Focus” from Equitable Growth highlighting scholars studying the well-being of workers during the coronavirus recession featured Michelle Holder, an assistant professor of economics at John Jay College of Criminal Justice at the City University of New York. Holder’s research discusses the disproportionate impact of the current crisis on Black women and notes that these harms are rooted in historical and persistent disparities that crowd Black women into low-wage work with high layoff rates during economic downturns.

One explanation of these historical harms is part and parcel of the stratification research by William Darity Jr. of Duke University, Darrick Hamilton of the New School, Mark Paul of New College of Florida, and Khaing Zaw of Facebook Inc. They examine the intersectional wage gap that Black women experience due to the larger proportion of them earning lower wages and thus achieving a lower level of economic well-being. This wage gap is “unexplained” by the human capital model of wages and is therefore interpreted to be the result of outright racialized gender discrimination. The four scholars find that Black women are more likely to face a reduction in work hours, higher rates of unemployment, and exposure to coronavirus while at work, exacerbating the hardships women of color already face on the job.

Another economic phenomenon that disproportionately affects women is monopsony, a market structure that occurs when workers have few suitable outside job options, so employers use their greater market power to take advantage of these labor market conditions by pushing down wages for workers. Kate Bahn, director of labor market policy at Equitable Growth, and Mark Stelzner of the University of Connecticut demonstrate how women may be more likely to face difficulties in finding a job due to disproportionate care burdens and lack of access to wealth, leading to lower pay levels.

Bahn also examines how older women, who may be caregivers for family members or have their own health needs, are affected by how they search for jobs and thus are more vulnerable to monopsonistic labor markets. Monopsony, Bahn finds, is also more prevalent in female-dominated occupations, including nursing and teaching—professions that face disproportionate challenges during the coronavirus recession.

Yet women’s disproportionate responsibility for caregiving remains a primary determinant of their inequitable economic opportunities and outcomes. Equitable Growth Policy Analyst Sam Abbott details the struggles the U.S. child care industry faced leading up to the pandemic shutdown in 2020, including razor-thin profit margins and low median wages that put child care workers—a large majority of whom are women of color—at particularly high risk when the recession began. This dynamic, in turn, reduces the supply of child care services for working mothers.

Many working mothers, of course, cannot afford child care. A new working paper from Ariel Kalil, Susan Mayer, and Rohen Shah, all from the University of Chicago, highlights the economic distress brought on by COVID-19 for low-income working mothers. Their research surveyed 572 low-income families with preschool-age children in Chicago to understand the economic and social restrictions brought on by the pandemic. In particular, their research finds that mothers’ time providing child care has increased in the wake of school closings and stay-at-home orders, and that these mothers face substantial increases in stress and anxiety both around their newfound child care responsibilities and their economic conditions.

With working mothers increasing their demand for child care services, a renewed focus on addressing the already-fragile child care industry is necessary for tackling the needs working mothers are facing. Taryn Morrisey, associate professor at American University, proposes, in an essay included in Equitable Growth’s Vision 2020: Evidence for a stronger economy, solutions to meet the need for affordable, quality early child care in the United States. Morrisey argues that accessible child care is a necessary component of the U.S. economic infrastructure and, if adequately provisioned, will narrow socioeconomic and racial inequities while promoting parental employment and family self-sufficiency. And Equitable Growth’s Abbot argues that bold, wartime thinking is required, similar to what was needed to meet child care needs during World War II.

Similarly, ensuring that women are compensated fairly and are ensured greater protections during periods of unemployment is necessary for a swifter economic recovery and a more equitable economy. The U.S. economy is only just beginning to recover from an economic recession that disproportionately harms women. But even as that recovery takes hold, the research highlighted in this column demonstrates that these obstacles in the U.S. labor market facing women, and especially women of color, are pertinent now more than ever.

Consider Equal Pay Day, the marker of how far into the new year a woman must work to earn what comparable men earned during the prior year alone. In 2021, that day falls on March 24. Yet the experiences of women differ greatly based on race and ethnicity. Black women earn 62 cents for every dollar full-time, year-round White men workers earn, meaning their Equal Pay Day will fall on August 3, 2021. Even further on the distribution, Latina workers are required to work nearly 23 months to earn what White men workers earn in just 12 months, making just 55 cents on the dollar, compared to their White male counterparts.

A recent column from Equitable Growth highlights how unemployment affects women workers amid the pandemic. Specifically, women workers are more likely to have lost their jobs than White men, with Black women and Latina workers facing the greatest risk of becoming unemployed at the onslaught of the coronavirus recession. Latina workers alone experienced a 22 percent drop in unemployment between January and April 2020. Indeed, since the onset of the coronavirus recession, Black women and Latina workers have faced disproportionate impacts to their employment, as seen in the figure below. (See Figure 1.)

Figure 1

As the United States celebrates Women’s History Month and the great achievements of women, policymakers must not forget working women who have experienced disproportionate economic harms brought on by the coronavirus recession. Structural racism and sexism, alongside historical disparities in care responsibilities borne by women, laid the groundwork for the unique crisis facing women today, leading to starker outcomes for women, and women of color in particular. Whether it be pay equity, monopsony power, or the ongoing child care crisis, the United States must work to address everyday barriers women face in the workforce in order to create a stronger economy rooted in gender equity.

Posted in Uncategorized

JOLTS Day Graphs: January 2021 Edition

Posted on by Carmen Sanchezcumming

Every month the U.S. Bureau of Labor Statistics releases data on hiring, firing, and other labor market flows from the Job Openings and Labor Turnover Survey, better known as JOLTS. Today, the BLS released the latest data for January 2021. This report doesn’t get as much attention as the monthly Employment Situation Report, but it contains useful information about the state of the U.S. labor market. Below are a few key graphs using data from the report.

The quits rate declined slightly to 2.3 percent in January, but remains at pre-pandemic levels following the sharp recovery that began in the summer.

Quits as a percent of total U.S. employment, 2001–2021

The job opening rate increased slightly while the hire rate decreased slightly in January, leading to a decrease in the vacancy yield for openings-to-hires.

U.S. total nonfarm hires per total nonfarm job openings, 2001–2021

As unemployment declined and job openings increased, the ratio of unemployed-workers-to-job-opening went down slightly.

U.S. unemployed workers per total nonfarm job opening, 2001–2020

After being stalled for three months, the Beveridge Curve moved closer to typical territory as job openings recovered to their levels one year prior and the unemployment rate decreased partially from its pandemic high.

The relationship between the U.S. unemployment rate and the job opening rate, 2001–2021

New evidence on the success of gig-worker pay standards for ride-hail drivers

Posted on by Emilie Openchowski
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The misclassification of work performed by ride-hailing drivers is rampant in the online platform-based gig economy. Companies such as Uber Technologies Inc. and Lyft Inc. claim their drivers are independent contractors, despite Uber and Lyft setting prices and exercising an extreme degree of influence and control over their drivers’ actions. These gig workers can exercise some degree of flexibility over the hours that they work, but they must still bear the risks of fluctuating passenger demand and the unpaid time between rides—without minimum wage protections, unemployment benefits, overtime pay, protection from discrimination, or paid sick or family leave.

As Equitable Growth’s Corey Husak explains, true independent contractors are self-employed, freelance workers with significant control over the work they do and how they do it. Because of this high degree of autonomy, independent contractors are not entitled to basic employee protections or benefits, or the right to form a union or bargain collectively for better pay and working conditions. Yet many companies choose to misclassify large swaths of their workforce as independent contractors in order to move costs to the workers while maintaining significant control over the work process.

One argument against classifying ride-hail drivers and similar gig workers as employees is because drivers are able to choose when to work, and because they may accept rides via multiple companies during their time on the road, it is not possible for companies to pay drivers a minimum wage. But new evidence from New York City’s 2019 gig-driver pay standard shows that flexible hours are not incompatible with a wage threshold, even for on-demand ride-hailing services. This column reviews research findings on the outcomes of New York City’s pay standard and examines several ways in which ride-hailing companies misclassify their drivers and the consequences of those actions on these workers’ pay and overall economic well-being.

On-demand ride-hail services are not incompatible with a minimum earnings standard

App-based drivers often wait for long periods of time between trips—on average, around 40 percent of their time in New York City, according to the report—either waiting for trip requests or driving to pick up a passenger. These wait times are both difficult to predict and uncompensated, even though drivers are essentially “on call” for the company when they are signed into an app and are penalized for not accepting the rides the company assigns them—which, as the Economic Policy Institute describes, shows that they are “engaged to wait” by the company.

Absent a pay standard or minimum wage protections, online ride-hailing companies such as Uber and Lyft are incentivized to encourage a surplus of drivers so that more of them are available for new ride requests, which translates into shorter wait times for passengers. This also means that drivers need to keep multiple apps open during quiet times to find what work is available, which allows each individual company to claim that they are not responsible for the driver’s waiting time.

In February 2019, a new pay standard for “high-volume for-hire services” such as Uber, Lyft, and Via Transportation Inc. went into effect in New York City. While not a minimum wage, the pay standard’s purpose is to deliver to drivers a minimum level of pay per trip, equivalent to $15 per hour after expenses, by taking into account time spent on the road, distance traveled, and the extent to which drivers are utilized and spend time with passengers. The pay standard is designed so that drivers receive gross earnings of $27.86 per hour, equivalent to a net income of $17.22 per hour after expenses, which would cover the $15 per hour received by a regular employee after deducting payroll taxes and the average compensation value of paid time off.

A recent report published by the Center for New York Affairs at the New School suggests that ride-hail drivers’ pay did increase after the implementation of the pay standard. The report, titled “New York City’s Gig Driver Pay Standard: Effects on Drivers, Passengers, and the Companies,” is by Dmitri Koustas of the Harris School of Public Policy at the University of Chicago, James Parrot of the Center for New York City Affairs at the New School, and Equitable Growth grantee Michael Reich of the Center on Wage and Employment Dynamics at the University of California, Berkeley. Their preliminary findings point to the positive potential effects of New York City’s pay standard for app-based drivers on drivers’ pay, as well as other outcomes related to trips, fares, and passenger demand.

Parrott and Reich also are involved with the design of the pay standard, having conducted a prospective economic impact analysis of the pay standard for the New York City Taxi and Limousine Commission and later providing updated cost estimates that informed the adopted rules. The most recent report’s descriptive findings show that New York City drivers’ average gross hourly pay rose by 8.8 percent, from approximately $28 per hour to more than $30 per hour, between June 2018 and June 2019. Drivers’ average earnings per trip rose from $14.87 per hour to $16.20 per hour after the pay standard was implemented, increasing the most for trips during weekday off-peak hours, although the median earnings per trip remained lower, rising from $10.91 to $11.29 per hour. 

While the report shows that drivers’ gross hourly pay climbed after the implementation of the pay standard, its authors note that the pay standard went into effect along with other changes that affected the ride-hail market. New York City also limits the number of app-based vehicles that can be on the road at any point and launched a congestion charge at the same time as the driver pay standard in 2019. Therefore, the paper reports only the descriptive changes in take-home pay before and after the bundled changes, although the authors plan to examine the causal effects of the pay standard alone in a working paper later this year.

Detailed data are necessary to understand ride-hail platform dynamics and policy impacts

The New York City report also is of interest for its detailed data linking drivers and their pay across app platforms. Ride-hail companies such as Uber and Lyft generally resist sharing detailed data with governments or independent researchers. New York City, however, requires app-based ride-hail companies, taxis, and other for-hire vehicles to share this type of data, which is why this report was possible. The linked data are key to understanding drivers’ pay. Because of the potentially long wait times, drivers tend to keep apps for multiple ride-hail services open at a time. Since they are driving for—and potentially on-call for—many companies at once, drivers’ actual time with each company may not reflect their overall working time, and misclassification means that no single company is otherwise “responsible” for the drivers’ on-call time in between rides.

These comprehensive and linked data show that the median driver worked 32 hours per week and that drivers working 32 or more hours per week provided 70.7 percent of all trips in June 2019. When individual ride-hail companies publish data on driver earnings, however, they may only report time spent with accepted fares on their own platforms, which can understate drivers’ working hours and overstate drivers’ hourly pay. Analyses produced by or in collaboration with rideshare companies also find both less working time and higher wages, for instance, by excluding wait times in between fares or by reporting driver earnings before the company’s platform and booking fees. 

What’s more, many analyses of drivers’ pay also do not take into account basic expenses, including vehicle costs and operating expenses, which can be both considerable and difficult for drivers to calculate. A study by Alejandro Henao of the University of Colorado Denver and Wesley Marshall of the National Renewable Energy Laboratory examined driver economics in Denver and found that while a driver in Denver in 2016 might be able to expect gross, pretax earnings of $15.57 per hour on average (with a median hourly rate of $12.99), the driver’s net pretax earnings would likely be $8.15 per hour (with a median of $6.88) after accounting for expenses related to car ownership or leasing, as well as ongoing operating costs.

Focusing on net pretax earnings, the two authors report that 61 percent of the rides in the dataset showed net hourly earnings of less than the state’s minimum wage at the time of the study of $8.31 an hour. In addition, as the Economic Policy Institute notes, drivers classified as independent contractors must also bear costs such as health insurance or retirement benefits and pay more in taxes than drivers classified as employees, reducing their effective earnings further. 

Misclassification robs workers of more than wages

While the New York City study shows that ride-hail drivers’ hourly earnings did rise after the implementation of the gig-worker pay standard, ride-hail drivers in New York City and elsewhere are still denied the basic protections and benefits they deserve due to misclassification. By treating these drivers as independent workers, ride-hail companies ensure that individual drivers bear not only the costs of providing the service but also the risks of shifts in passenger demand and overall earnings volatility. The mechanics of providing transportation for hire are not incompatible with employee status, even when rides are dispatched through an app; workers can be properly classified as employees and still have flexible schedules, and minimum wage laws apply even when workers’ hours change or when workers are part time.

Misclassification not only robs app-based ride-hail drivers and other gig workers of pay, but it also denies them other benefits and protections tied to employment status. While ride-hail drivers in New York City are more likely to receive the equivalent of the city’s $15 minimum wage due to the new pay standard, with the economic equivalent of some paid time off, their independent contractor status means they do not receive the security of paid family leave, paid sick leave, and the possibility of being a union, in addition to regular mandatory benefits such as health insurance, overtime, or protection from discrimination.

Combating worker misclassification is necessary to provide ride-hail drivers and other gig workers with fair wages, economic security, and crucial benefits. Policymakers can make labor law more inclusive to apply employee labor protections, including minimum wage standards, to gig workers who have limited control over their work, and apply the “ABC test” to determine employment status. In addition, greater data transparency by these companies is necessary for meaningful oversight and would let policymakers and independent researchers understand the impact of the policies they are passing.

Posted in Uncategorized

The alignment of earnings in occupations and at U.S. workplaces increasingly exacerbates earnings inequality

Posted on by Maria Monroe
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A few common explanations dominate the discussion of rising earnings inequality in the United States. Automation and computerization, for example, have augmented many nonroutine white-collar jobs—meaning those jobs can pay more—while replacing more routine jobs. Tech pays off differently depending on your occupation. Another set of explanations of earnings inequality has to do with the types of employers, workplaces, or firms that make up the U.S. economy. Low-paying service-sector employers have multiplied, and manufacturers have deunionized, outsourced, or offshored, while a select few firms in finance, consulting, and tech pay disproportionately high wages. This last set of firms is made up of so-called superstar firms.

In short, where you work matters for earnings inequality, too—it’s not just what you do at work.

In a new paper, we argue that these two types of explanations miss something crucial. From 1999 to 2017, increasing earnings inequality occurred not mainly because of changing pay-offs to where you work or what you do at work. Instead, inequality is increasing through the increased alignment between occupations and workplaces. High-paying occupations are increasingly clustered at high-paying workplaces, and low-paying occupations are increasingly located at low-paying workplaces.

This alignment between earnings at workplaces and occupations exacerbates overall earnings inequality. But this has largely escaped public attention because we typically study either occupations or workplaces in isolation.

For our analysis, we used restricted-use Occupational Employment Statistics, or OES, survey data collected by the U.S. Department of Labor’s Bureau of Labor Statistics. Twice a year, the BLS surveys about one-sixth of establishments in the United States, asking them to list the occupations they employ, the number of workers in each occupation, and the wage distribution of each occupation. So, the OES data let us examine the role of both workplace and occupation in earnings inequality—something that other sources of U.S. data cannot do.

Using this survey’s data, we modeled workers’ earnings as the sum of both occupational premiums and workplace premiums. An occupation premium is what a certain occupation pays beyond the average, once you take into account the workplaces where it is employed. A workplace premium is what a workplace pays beyond average, once you take into account the occupations it employs.

Here’s an example. A software engineer working at the online vacation rental company Airbnb Inc. earns a lot, since software engineers in general are well-compensated and since Airbnb pays its employees above the rate they might earn elsewhere. A software engineer working at a nonprofit might earn less—even though that worker could still earn more than other employees at the nonprofit due to their occupation, the nonprofit as a whole pays less. So, software engineering has a high occupational premium, Airbnb has a high workplace premium, and the nonprofit has a lower workplace premium.

Using what’s called a two-way fixed-effects regression, we calculate these two sets of premiums for every occupation and for every workplace in the OES survey. This approach lets us separate inequality between occupation premiums (due to skill-biased technological change, for example) from inequality between workplace premiums (due to superstar firms, for example).

Surprisingly, we find that both between-workplace inequality and between-occupation inequality have stayed roughly level over the past 20 years, each explaining around the same amount of earnings variation. The big change has been in the covariance between occupation and workplace premiums, which has doubled in the past 20 years and which accounts for two-thirds of the total increase in wage inequality. (See Figure 1.)

Figure 1

Disparities between workplaces and between occupations have stayed constant, while the association of workplace and occupation pay premiums has doubled since 1999

Figure 1 shows that pay premiums are increasingly aligned such that highly paid occupations are more likely to be located at high-paying establishments, and similarly for poorly paid occupations and low-paying establishments. Workers with the high-premium occupations at high-premium establishments enjoy very high wages, while those with low-premium occupations at low-premium establishments receive very low wages. We call this the consolidation of workplace and occupation inequalities.

But why does consolidation matter?

Consolidation exacerbates overall earnings inequality, with those in high-occupation-premium, high-establishment-premium jobs earning extra and those in low-occupation-premium, low-establishment-premium jobs earning even less. The result is worse earnings inequality than either between-occupation or between-workplace variation would create by themselves. And, though we cannot test it with our data, consolidation could affect other aspects of work, too. While a janitor hired by Eastman Kodak Co. some 40 years ago could work her way into other jobs at the firm, a janitor at Apple Inc. today is actually employed by a custodial services contractor and has little chance for promotion.

The consolidation we observe means that many conventional explanations for rising earnings inequality do not capture the full story. Explanations emphasizing divergence between occupations or educational levels or explanations focusing on the importance of where you work ignore the fact that the two are increasingly tied together.

This earnings-inequality dynamic also means that policymakers need to look at more than one dimension of earnings inequality—occupation or workplace—at a time. Policies such as the minimum wage cut across both workplace and occupation at once: It doesn’t matter whether it’s the occupation premium or the workplace premium that’s low. So, a higher minimum wage keeps low workplace premiums and low occupation premiums from compounding. Of course, the minimum wage alone isn’t enough—most of the rise in inequality over the past 20 years is due to a growing gap between median-earning and high-earning workers.

So, policymakers should also consider interventions in the sectors where the consolidation of earnings inequality is most rampant. First is the service sector, which is increasingly dominated by low-paying workplaces employing primarily poorly paid occupations on the one hand (think fast-food restaurants), and very high-paying workplaces employing mainly well-compensated occupations (think consulting firms). Together, this shift in industrial composition accounts for more than 20 percent of the total increase in consolidation.

Second is the bifurcation of social services. Some hospitals, nursing homes, and the like have cut costs in recent years by shifting to a workforce of primarily poorly compensated occupations. An underresourced community health center, for example, may reduce the number of physicians on staff, relying instead on a workforce of nurses and other employees with less-prestigious credentials. Perhaps constrained by budget cuts, the health center also may pay its employees less across the board than they might earn elsewhere.

Meanwhile, other establishments in social services have shifted up, employing more professional elites and paying them well, too. Think of a small psychiatric practice with a primarily wealthy clientele. These patterns of down-shifting and up-shifting account for about 12 percent and 11 percent, respectively, of the total increase in consolidation, according to our working paper.

While most dramatic in these two sectors, earnings consolidation has occurred throughout the U.S. economy. Regardless of industry, the alignment of workplace and occupation now exacerbates overall earnings inequality. It forms a new source of earnings inequality, one which defies conventional explanations and which requires attention from researchers and from policymakers alike.

Posted in Uncategorized

Four ways to understand the pay divide facing Asian American, Native Hawaiian, and Pacific Islander women

Posted on by Emilie Openchowski
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Tomorrow is Asian American and Pacific Islander Women’s Equal Pay Day.1 The day marks the point in 2021 until which, on average, Asian American, Native Hawaiian, and Pacific Islander women had to work—from the start of 2020 through March 9, 2021—to earn as much as White, non-Latino men earned in 2020 alone. Put differently, this group of women earns 85 cents for every dollar White men make.

Of course, there are big disparities between different subgroups among these women. For instance, Malaysian, Taiwanese, and Indian women’s median earnings surpass those of White men, while Nepalese women earn half as much as White men. Nonetheless, the coronavirus recession overall is hitting Asian American, Native Hawaiian, and Pacific Islander women workers hard.

Both AANHPI men and women workers are overrepresented among front-line workers. As the downturn hit, Asian American workers in the bottom of the earnings distribution suffered some of the largest reductions in wages. For Asian American, Native Hawaiian, and Pacific Islander women specifically, their overrepresentation in education, healthcare, and other service occupation, alongside the greater likelihood of living in multigenerational households in which both children and elderly persons might require care, translated into tough labor market outcomes.

Just one telling case in point: As of February 2021, 64 percent of unemployed Asian American women have been jobless for 27 weeks or more—a greater share than for any other group of workers. (See Figure 1.)

Figure 1

Share of unemployed workers who have been jobless for 15 weeks or more, by race, gender, and ethnicity, February 2021

Asian American, Native Hawaiian, and Pacific Islander women are making important strides toward pay parity but continue to face disadvantages in the labor market

The pay disparity between White, non-Latino men and Asian American women narrowed over the past two decades, from 31 cents per dollar in 2002 to 13 cents per dollar in 2019.2 Yet a stubborn gap remains over time. Going further back, when studying the evolution of earnings of Japanese, Chinese, and Filipino American women from 1960 to 1990, Donald Mar of San Francisco State University finds that the difference between their actual and simulated earnings—the pay they would receive if they were treated as White women—narrowed significantly in the 1970s.

These findings suggest that the pay penalty these groups of women workers experienced vis-à-vis their White counterparts as a result of discrimination might have become less pervasive in the second half of the 20th century. Still, Asian American, Native Hawaiian, and Pacific Islander women continue to face important barriers and challenges in the labor market.

Workplace discrimination and longstanding gender norms affect AANHPI women’s career trajectories and access to job opportunities. In addition, occupational segregation entrenches inequality both between women and men and between different subgroups of AANHPI women. For instance, according to our analysis of the U.S. Census Bureau’s American Community Survey data, the largest number of Asian American women are employed as registered nurses, whereas for Native Hawaiian and Pacific Islander women, the most common occupation is that of cashiers—which, with an average wage of $11.73 per hour, is one of the lowest-paying jobs in the U.S. economy.

Asian American, Native Hawaiian, and Pacific Islander women face barriers to accessing the highest-paying jobs

AANHPI women run up against a “bamboo ceiling” that holds back their career trajectories despite representing an important share of the workforce of high-wage sectors such as information, finance, and professional services. Studies on the tech and legal services industries, for example, show that Asian American and Pacific Islander workers in general, and Asian American and Pacific Islander women workers in particular, are greatly underrepresented in upper-management and executive-level positions. Other research, analyzing Equal Employment Opportunity Commission data disclosed by five large Silicon Valley companies, finds that Asian American women represented almost 14 percent of the professionals in the sample, but only 3 percent of executives.

This phenomenon is not exclusive to the tech and legal industries. Research by ChangHwan Kim and Yang Zhao of the University of Kansas finds that even when accounting for factors such as demographic characteristics, years of work experience, field of study, industry, and region of residence, Asian American women with a college degree supervise fewer workers than their White counterparts. This evidence shows that Asian American women’s underrepresentation in positions of authority cannot be fully accounted for by so-called human capital variables, suggesting that discrimination and harmful stereotypes continue to present an obstacle that prevents many from accessing upper-level management jobs.

Asian American, Native Hawaiian, and Pacific Islander women are overrepresented in both high- and low-wage jobs

Occupational segregation—that some workers are overrepresented in some jobs and underrepresented in others—explains a chunk of the pay disparities between groups of workers. For Asian American and Pacific Islander women, this kind of job sorting means that they make up a disproportionately large share of both the best- and worst-paid jobs in the U.S. economy. An analysis by the National Women’s Law Center finds that Asian American and Pacific Islander women are overrepresented in the 40 occupations with the highest wages, as well as in the 40 occupations with the lowest wages. As such, even though AANHPI women make up just more than 3 percent of the U.S. workforce, they represent 61 percent of all manicurists and pedicurists and 17 percent of tailors, dressmakers, and sewers. In 2019, these occupations paid an average hourly wage of $16.32 or less—well-below the average for all occupations of $25.72 an hour. (See Figure 2.)

Figure 2

Occupations with the greatest share of Asian American and Pacific Islander women workers, 2014–2019

Yet there is evidence that Asian American, Native Hawaiian, and Pacific Islander women are making important progress toward greater occupational integration. For instance, an analysis by the Institute for Women’s Policy Research finds that as gender occupational segregation became less pronounced between the early 1970s and the early 2000s, Asian American and Pacific Islander men and women gained the most ground toward occupational integration. As such, by 2011, this group of men and women were much more likely to do the same kind of work than the men and women of any other major racial or ethnic group.

The different labor market experiences and economic outcomes among Asian American, Native Hawaiian, and Pacific Islander women point to the importance of disaggregating data

The variety of economic outcomes among AANHPI women are often obscured by a lack of data. Insufficient information therefore masks serious economic inequities between subgroups of workers, families, and communities. An analysis by the Pew Research Center, for example, finds that income inequality between Asian Americans skyrocketed between the early 1970s and the mid-2010s. Whereas they had the most even distribution of income of any major racial or ethnic group in 1970, by 2016, Asian Americans in the top 10 percent of the income ladder were making 10.7 times more than Asian Americans in the bottom 10 percent—a larger divide than the one experienced between their Black, White, and Latinx counterparts.

Disaggregated data, therefore, is an essential tool for understanding differences within the Asian American, Native Hawaiian, and Pacific Islander communities, gaining a better grasp of what is driving disparities in economic outcomes, and informing a policymaking process capable of alleviating those inequities.

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Brad DeLong: Worthy reads on equitable growth, March 2-8, 2021

Posted on by Maria Monroe

Worthy reads from Equitable Growth:

1. My friends among the Biden plan doubters—who do not seem to have internalized exactly how devastating the slow recovery of the 2010s was—do not seem to recognize how great the uncertainty is about the economy’s likely trajectory today. Those factors militate very strongly in favor of taking steps to make sure that you do not repeat the mistakes made in the previous decade. On the other side, I see little in the way of argument save what I regard as an unwarranted suspicion that the Federal Reserve will not do its proper job—plus a fear that the financial system could not cope without a crisis with an even moderate revaluation of the asset price structure. Austin Clemens is right here, focusing attention where it should be focused. Read his “New Great Recession data suggest Congress should go big to spur a broad-based, sustained U.S. economic recovery,” in which he writes: “Joe Biden’s proposed $1.9 trillion American Rescue Plan, critics now argue that it will ‘overshoot’ [but] … Undershooting the policy response would be a far more dangerous prospect … The U.S. Department of Commerce’s Bureau of Economic Analysis’s Distribution of Personal Income … shows just how devastating this pattern was for most U.S. workers and their families … In the bottom 50 percent … disposable personal income incorporates transfers from the federal government to households, so losses in this group were partially compensated for by rising Unemployment Insurance payments, Supplemental Nutrition Assistance Program benefits, and other government benefits. But this group then became mired in years of stagnant, or even declining, income as these benefits ended amid a still-tepid economic recovery, and did not experience substantial income gains until 2015. By comparison, households in the top 10 percent of income recovered almost immediately after the end of the Great Recession and ended 2018 up 22 percent compared to 2007.”

2. David Mitchell has a very good list of things that Biden and his staff could do to start to turn that around. Read his “Executive action to-do list for achieving strong, stable, and broad-based U.S. economic growth,” in which he bullets a series of factsheets, including: “Executive action to coordinate federal countercyclical regulatory policy … Executive action to combat wage theft … Executive action to coordinate antitrust and competition policies … Executive action to reform the cost-benefit analysis of U.S. tax regulations … [and] Executive action to improve U.S. economic measurements.”

Worthy reads not from Equitable Growth:

1. Jason Furman and William Powell once more try to keep people from looking at the official unemployment rate and taking it as a reliable guide to any dimension of the economic situation. Please listen to them. Read their “US Unemployment remains worse than it seems as millions still out of the labor force,” in which they write: “Throughout the pandemic the official unemployment rate has been kept down by a misclassification error and the unusually large withdrawal of millions of people from the workforce. Our estimate of the realistic unemployment rate for February was 8.2 percent … Another concept, the fixed participation rate unemployment rate, cited by Federal Reserve Chair Jay Powell and Treasury Secretary Janet Yellen, was 9.5 percent; the comparable concept peaked at 11.8 percent in the financial crisis. The headline unemployment rate was 6.2 percent in February, down slightly from 6.3 percent in January. This concept works well in normal times but has had some deficiencies in the context of the pandemic.”

2. I want to highlight my attempt to understand what is really worrying my friends among the new inflation hawks. For reasons I do not understand, they let what I think are their real concerns stay submerged in subtext. They do not stress that they do not trust the Federal Reserve. They do not stress that they worry that the financial web is on the point of another crisis and would collapse in response to even moderate shifts in the asset price structure. Yet their worries and their focus make no sense to me, unless such considerations are in the very forefront of their minds. Please “What Are the New Inflation Hawks Thinking?,” in which I write: “These warnings … all reflect a fear that the Fed might have to hike the federal funds rate and return it to the range we used to consider normal. I say “might” because, as the aforementioned critics acknowledge, any inflationary pressures generated by the $1.9 trillion package remain merely a possibility, not a certainty. It is equally likely that the new spending will end up filling holes in aggregate demand. In any case, if the past 15 years of debates about “secular stagnation” and “global savings gluts” have taught us anything, it is that we should want to create the conditions in which a higher federal funds rate is warranted.”


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Weekend reading: Executive orders to ensure a strong economic recovery edition

Posted on by Maria Monroe

This is a post we publish each Friday with links to articles that touch on economic inequality and growth. The first section is a round-up of what Equitable Growth published this week and the second is relevant and interesting articles we’re highlighting from elsewhere. We won’t be the first to share these articles, but we hope by taking a look back at the whole week, we can put them in context.

Equitable Growth round-up

As President Joe Biden considers ways that he can improve the economy using executive authority, Equitable Growth released an Executive Action Agenda, a series of factsheets on economic policy proposals that can fight inequality and a ensure strong, broad-based economic recovery and sustained economic growth. David Mitchell summarizes each of the five factsheets released over the past few weeks and how they would advance widespread economic growth. We have written about the ideas in the factsheets before but repurpose the proposals in this series to provide specific steps the administration can take and list experts in each area with whom policymakers can consult for guidance.

Here are the five topics already covered, with more to come:

In addition to executive orders on the economy, President Biden is pushing for Congress to pass his $1.9 trillion American Rescue Plan. New data on personal incomes from the Great Recession of 2007–2009 and its sluggish recovery demonstrate that spending too little is a far more dangerous prospect than spending too much, writes Austin Clemens. He says Congress risks repeating the errors of the past, which, in the decade following the previous recession, led to a slow and uneven recovery and left millions of U.S. workers and their families struggling. Clemens unpacks the new data series produced by the U.S. Bureau of Economic Analysis, explaining why these data—which are broken out to show how people across the income distribution fared, rather than an aggregate growth number—provide a key look at why the recovery from the Great Recession was so anemic. These new data make clearer the necessity of a big stimulus bill, as well as the utility of distributional datasets, Clemens concludes, urging policymakers to learn their lessons and act accordingly.

Part of the American Rescue Plan is extended Unemployment Insurance benefits that run through August 2021. Equitable Growth research shows that automatic triggers for relief programs are better for economic recovery than arbitrary expiration dates, but there’s no doubt that unemployment benefits are an important support for struggling families. It’s also well-established that Black and Latinx workers are less likely to access these benefits than their White peers, which can have a major impact on the stabilizing effects of UI benefits on the broader U.S. economy, writes Alix Gould-Werth. New research shows that some demographic groups’ consumption and spending in their local economies is more sensitive to fluctuations in income: A $1 change in income means a 7-cent change in spending for White workers, a 15-cent change in spending for Latinx workers, and a 22-cent change in spending for Black workers. This means that when Black and Latinx workers lose income as a result of losing their jobs, they curtail their consumption more significantly, which leads to further unemployment. But it also means that when these workers gain income from UI benefits, they spend significantly more of it, boosting their local economies. This research, Gould-Werth concludes, highlights why extending Unemployment Insurance is a vital part of propelling the broader U.S. economy toward recovery—and why policymakers must also act to address the racial disparities in UI benefit receipt.

One year into the coronavirus recession, unemployment rates are still well-below what they were in February 2020. Kate Bahn and Carmen Sanchez Cumming analyze the latest data released from the U.S. Bureau of Labor Statistics on employment and the U.S. labor market in February. And check out their charticle presenting five key charts on the new unemployment data.

Links from around the web

The way the federal government and many economists and analysts currently measure economic health is not working, write Jhumpa Bhattacharya and Andrea Flynn in The Nation. Looking at aggregate Gross Domestic Product growth or how high the stock market is doesn’t accurately reflect the lived experience of most Americans, especially during the coronavirus recession, in which the rich have gotten richer and low- and middle-income families are struggling. Instead, Bhattacharya and Flynn explain, we should focus on improving the lives of the most marginalized in our society—without fearing the cost of doing so—because this will improve everyone’s standards of living. Insufficient action and aid from the government at this point would only serve to reinforce and exacerbate the stark racial and gender divides that predated this pandemic-induced recession but have only worsened over the past year. “The health of our economy is only as good as the economic health of the American people—all of them,” the co-authors conclude. Measuring the economy in new ways that showcase the lived experience of all people, and especially the most vulnerable, would guide policy in a way that ensures broad-based solutions and a strong recovery.

It is well-documented that the coronavirus pandemic and recession are disproportionately affecting people of color in the United States, but a lack of disaggregated data is preventing policymakers from targeting aid to both the communities that need it and the programs that would be most efficient in providing it. Yahoo!’s Brian Cheung reports on the importance of breaking out data by race and ethnicity to ensure disparities are addressed in relief efforts. Disaggregating data on access to the COVID relief programs passed by Congress in 2020, for instance, would show how different demographic groups utilized the aid and where bottlenecks occurred, which would allow policymakers to be more deliberate as they craft, debate, and pass the American Rescue Plan. Gathering these data, Cheung explains, is a vital part of ensuring equity in government programs and combatting broader economic inequality in wealth and income in the United States.

The coronavirus pandemic and recession has pushed millions of workers from the U.S. workforce, disproportionately affecting women and workers of color, so many of whom have lost the labor market gains they made in recent decades. A new survey from Indeed shows that the pandemic also widened the gender divide in requests for raises and promotions, with men being 8.6 percent and women 12.1 percent less comfortable asking for more money or a better job title from their employers. Indeed’s AnnElizabeth Konkel reviews the survey’s findings and its implications for gender parity in the U.S. labor force. The survey also finds that women are now more comfortable asking for flexible work schedules and conditions amid the pandemic, probably as a result of increased responsibilities at home, which fall heavily on women’s shoulders. Konkel explains that if employers become less accommodating after the pandemic eases, this could push even more women out of the labor force, further widening gender divides in the U.S. workforce.

Friday figure

Probability of minimum wage violations measured against state unemployment rates

Figure is from Equitable Growth’s Executive Action Agenda factsheet “Executive action to combat wage theft against U.S. workers.”

Jobs report: a year into the coronavirus recession, employment losses have been greatest for Black women workers and Latinx workers

Posted on by Maria Monroe
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One year after the onset of the coronavirus recession, the U.S. labor market is still a long way from its February 2020 employment levels, but saw important job gains last month. According to the latest Employment Situation Summary by the U.S. Bureau of Labor Statistics, the U.S. economy in February added 379,000 nonfarm payroll jobs—the greatest month-over-month gain since October of last year.  

Today’s release also shows that between mid-January and mid-February the overall unemployment rate fell from 6.3 to 6.2  percent, with 50,000 workers re-entering the U.S. labor force. Across sectors, last month’s job gains were concentrated in leisure and hospitality, which added 355,000 jobs. Yet data on employment changes over the entire year show that the downturn remains especially hard for this sector and for service-providing industries in general. (See Figure 1.)

Figure 1

Percent change in employment by U.S. industry, February 2020–February 2021

The economic pain brought on by the downturn continues to fall heaviest on some groups. The jobless rate stands at 9.9 percent for Black workers, at  8.5percent for Latinx workers, at 5.1 percent for Asian American workers, and at 5.6 percent for White workers. Disaggregating the data further shows that over the past 12 months, net job losses have been greatest for Black and Hispanic women and men—groups for whom employment declined by  9.7 percent and 8.6 percent, respectively. (See Figure 2.)

Figure 2

Percent change in U.S. employment for workers 20-years-old and over by race, gender, and ethnicity, February 2020–February 2021

Hispanic men’s experience during the coronavirus recession

For Hispanic men, overall job losses are less severe than for women workers or Black men. Yet their experience during this recession also highlights important challenges they face in the labor market. For instance, Hispanic men are overrepresented in jobs that cannot be done from home. Despite accounting for about 8 percent of the U.S. workforce, these workers represent about a quarter of the construction workers and about 1 in 5 workers in the mining sector. In part as a result of their industry and occupational distribution, Hispanic men are facing risks associated with in-person work and have been more likely to experience joblessness than their White, non-Hispanic peers—a trend that risks entrenching longstanding inequities between the two groups of workers.

Consequently, as of the last quarter of 2020, Hispanic men were earning the lowest median weekly earnings of any other group of men, and just a bit higher than the weekly earnings than for Hispanic women.

Even though earnings disparities between Hispanic men and their White non-Hispanic peers are often attributed to differences in education, these pay disadvantages persist even among workers with the same level of education. A recent study shows that whereas 6 percent of White men with an advanced degree hold low-wage jobs, 13 percent of Hispanic men do. An analysis by the Economic Policy Institute shows that Hispanic men make about 15 percent less than White men who live in the same geographic region and have the same level of education and work experience. That gap, moreover, remains relatively unchanged since the early 1970s.

Researchers also find evidence that Hispanic men—and especially those who also are immigrants—are more likely to take low-wage and low-quality jobs, since they often lack the private networks and access to social insurance programs that would allow them to engage in longer job-search periods. Consistent with this evidence is that Latinx workers who are part of a labor union experience a particularly large pay boost. On average, workers covered by a union contract are paid 11 percent more than their nonunionized peers. Among Latinx workers, however, the wage premium associated with being represented by a union contract is more than 20 percent.

Yet research by Jake Rosenfeld of the University of Washington-St. Louis and Meredith Kleykamp at the University of Maryland, College Park also finds that Latinx immigrants are less likely to be part of a union than U.S.-born Latinx workers, suggesting that stronger networks and U.S. citizenship might protect workers against hostile responses to unionization efforts.

Conclusion

As the U.S. economy went into a pandemic-driven tailspin one year ago, almost 21 million workers lost their jobs between mid-March and mid-April alone. In February 2021, the U.S. labor market is short 9.5 million jobs relative to February 2020. These losses remain starkest for Black and Latina women, and other vulnerable groups of marginalized workers, highlighting the importance of policy in setting the groundwork for an equitable economic recovery.

Above all, policymakers should prioritize the enforcement of existing labor law. Even though this should be a priority for policymakers during booms as well as contractions, research shows that wage theft rises and falls with the business cycle—as recessions hit and the jobless rate rises, so does the share of workers who suffer a minimum wage violation.

Another way to tackle these U.S. labor market inequities is to lift the federal minimum wage, now frozen at $7.25 an hour for more than a decade. More than 40 percent of U.S. workers make less than $15 dollars per hour. In the food services industry, where Latinx workers make up more than a quarter of all workers, a whopping 78 percent of workers earn less than $15 dollars an hour. A large share of U.S. workers and an even larger share of women workers and workers of color would receive a much-needed pay boost should the federal minimum wage increase, helping drive a faster and more equitable economic recovery.

Equitable Growth’s Jobs Day Graphs: February 2021 Report Edition

Posted on by Carmen Sanchezcumming

On March 5th, the U.S. Bureau of Labor Statistics released new data on the U.S. labor market during the month of February. Below are five graphs compiled by Equitable Growth staff highlighting important trends in the data.

The prime-age employment rate increased slightly from 76.4 percent to 76.5 percent in February, remaining well below pre-crisis levels as the recession continues.

Share of 25-54 year olds who are employed, 2000–2021

The unemployment rate remains highest for Black and Hispanic workers, while declining for Asian workers and showing little change for White workers.

U.S. unemployment rate by race, 2000–2021

Public-sector employment remains significantly below pre-crisis levels, and has seen little change since the beginning of the year. 

U.S. public- and private-sector employment indexed to average employment in 2007

The proportion of unemployed U.S. workers facing long-term unemployment continued to rise in February, as 55.6 percent of unemployed workers have now been out of work for more than 15 weeks.

Percent of all unemployed U.S. workers by length of time unemployed

The number of part-time workers who would prefer full-time work remained high in February, with involuntary part-time employment currently at 6.1 million jobs.

Percent increase in part-time employment compared to January 2018