The restaurant industry is one of the largest private sector employers but is also the lowest paying, largely due to the subminimum wage for tipped workers. A direct legacy of slavery, the subminimum wage is still just $2.13 an hour at the federal level and below $5 an hour in 43 states. The subminimum wage has created large wage gaps between white workers and workers of color due to the segregation of workers of color into lower-tipping, more casual restaurants, and due to customer bias in tipping.  

This project will evaluate the two-tiered wage policy and its impact on racial equity, by comparing the racial wage gap and related health impacts, especially during COVID, on service workers between the seven states that require all workers to be paid a full minimum wage with tips on top and the 43 states that allow a subminimum wage. This research will help to inform discussions around policy being considered in 7 states and at the federal level to eliminate the subminimum wage for tipped workers. 

Starting January 1, 2018, New York State’s Paid Family Leave Act—a new state law mandating that employers provide paid family leave benefits through an employee-paid insurance policy—will be effective. This study will evaluate the impact of this law, focusing on three questions:

1. How does the law affect New York employers' provision of leave, employees' eligibility and utilization of leave, and disparities in these outcomes?
2. How do New York employers view the costs and benefits of paid family leave?
3. What are the early effects of New York’s Paid Family Leave Act on maternal and infant health outcomes and health equity?  

The study will use a number of data sources with multiple years of data (pre- and post-implementation of the law), including state administrative data on employer enrollment and employee utilization of paid family leave benefits, a large survey of New York employers, New York Birth Certificate data and Immunization Registry data, and a survey of new mothers who gave birth in a New York hospital, excluding those living in New York City.

The research will help fill gaps in our knowledge about how well state policies can lead to more equitable access, availability and use of paid family leave, and to improvements in maternal and infant health outcomes. It will also provide information on the reported impact on the business community.

The U.S. is one of three industrialized countries without universal access to paid sick leave. Thirty-five percent of all full-time employees lack this coverage. Among low-income and part-time employees, uninsurance rates exceed 80 percent. In addition to concerns about inequality, worker well-being, and productivity, a lack of paid sick leave also contributes to the spread of disease, when ill workers are forced to choose between their health and their job.

This study will evaluate the impact of state-level sick pay mandates on coverage rates, other non-mandated fringe benefits, and the spread of infectious diseases. Researchers will focus on Connecticut, California, Massachusetts, Oregon, and Vermont—the only states that have mandated paid sick leave, all within the last five years.

Using data from the National Compensation Survey (NCS), Google Flu data, and state-provided data on rates of influenza-like illness (ILI), the researchers will be able to estimate the causal effects of the mandates on coverage rates, non-mandated fringe benefits, and the spread of disease. Because little to nothing is known about the impact of these recently implemented state-level mandates, this project will provide important insights for academics, policymakers and the public.

Income is considered one of the key underlying social determinants of health. However, there has been relatively limited research on the health effects of policies designed to increase income for vulnerable families.

Using unpublished vital statistics data from the National Center for Health Statistics, this study will examine the effect of minimum wage variation over the last three decades on infant mortality, birth weight, and prenatal care. The researchers will also investigate how minimum wage policy influences health outcomes for low-wage workers using the Behavioral Risk Factor Surveillance System data, focusing on body mass index and chronic health conditions.

The effects of minimum wage-related policies on health will become even more pertinent as more states and localities consider increasing minimum wages. California, New York State and Washington D.C. are phasing in $15 minimum wages over the next six years; New Jersey is very likely to follow in 2018, and five other states (Arizona, Colorado, Maine, Oregon and Washington) have enacted minimum wages that will climb to $12 or higher. Establishing a link between wage policy and health outcomes would expand the growing evidence-base on the population effects of increased minimum wages, and may help inform state policymakers and employers who are considering a change in wage policy. 

Since 2004, California’s state disability insurance program has provided six weeks of parental leave at 55 percent pay (in addition to typically 6-8 weeks of postpartum disability leave for biological mothers, also at 55 percent pay). However, many parents—especially those of lower-income—cannot afford to take this bonding leave at only partial pay. San Francisco’s new Paid Parental Leave Ordinance (PPLO) addresses this issue by requiring San Francisco employers to supplement up to 100% pay for six weeks of parental bonding leave.

Building on an existing analysis of the effects of PPLO on parental leave-related outcomes and the impact on local employers, the research team will use new survey data as well as administrative data from the California State Employment Development Department to investigate:

1. What types of employers are experiencing increased leave-taking?
2. To what extent is PPLO providing financial protection for the most vulnerable families, such as low-income families with premature infants hospitalized for extended stays in the neonatal intensive care unit?

Measuring leave-taking across individuals at different earnings levels, as well as across firm characteristics such as size and industry, provides a much more robust ability to test whether low-income workers are benefiting, as well as to test for ongoing barriers to leave-taking in certain types of employers. Additionally, the analysis will explore remaining unmet needs under a policy providing (only) six weeks of fully paid leave.

Many hourly workers, especially in the retail sector, contend with unstable and unpredictable work schedules in which the number of hours, the days of the week, and the times of day that they work vary substantially from week to week. This chronic instability is likely to negatively affect workers and could also have spillover effects for children.

This project draws from a unique database of approximately 9,500 parents (with children under age 10) working hourly retail jobs at the nation’s largest 100 employers. The research team will use Facebook’s highly sophisticated targeting capabilities to assemble a sampling frame of employees of specific retail companies and then recruit workers to an online survey that collects detailed data on schedules, household economic insecurity, and childcare arrangements.

 Two states are attempting to address this schedule instability by regulating work schedules. Oregon’s Fair Workweek law took effect in the summer of 2018, and now requires that workers receive extra pay if they are not given at least two weeks’ notice of their work schedule or when their schedules change on short notice. New York State requires pay for workers who show up for work but are not needed, and has proposed expanded regulations to discourage last-minute scheduling. Targeting these two states, the analysis will:

1. Estimate how exposure to unstable and unpredictable scheduling practices in retail is associated with the type of childcare used, the complexity of care arrangements, and parents’ difficulty in arranging for care.
2. Estimate how childcare arrangements change with regulations and ordinances that aim to improve the predictability and stability of work schedule.

While policymakers have already begun regulating scheduling practices, the evidence base remains quite thin, in large part because existing data sources lack the necessary information about work scheduling. This project’s innovative methods allow for an unprecedented view of the work scheduling experiences of parents at less than 200 percent of the federal poverty level, and can help inform plans to introduce these types of policies.

Principal Investigator: Daniel Schneider, University of California, Berkeley and Kristen Harknett, University of California, San Francisco

For more on this topic:

• Precarious Work Schedules And Population Health

The Institute for Women’s Policy Research’s (IWPR) simulation model estimates the costs and benefits of paid leave for six common leave types, using data largely derived from the U.S. Department of Labor’s 2012 Family and Medical Leave (FMLA) Survey. The types include 1) own serious medical condition; 2) maternity and childbirth; 3) new child care following birth, adoption, or foster placement; 4) care for spouse; 5) care for children; and 6) care for parents. IWPR plans to improve the financial estimates generated by the model and add health indicators for those who do and don’t take leave from the aspects of the retrospective reporting of worker leave spells in the FMLA data with prospective reporting from panel series such as the Survey of Income and Program Participation (SIPP) and the Medical Expenditure Panel Survey (MEPS).

The research team aims to improve the reliability of the estimates of policy decisions and offer the best-available estimates of the costs and benefits of these policies. Benefits may include reduced readmissions and usage of nursing homes for convalescence when family caregivers are available, infant vaccinations received on schedule when workers can take paid leave, and increased initiation and duration of breastfeeding.

For example, with these intended updates, the model can provide a bridge from current knowledge of improved pregnancy outcomes with paid maternity leave to economic savings that can be incorporated into a cost-benefit framework for evaluating future national or state proposals for paid family and medical leave programs.

Principal Investigators: Jeffrey Hayes and Heidi Hartmann, Institute for Women's Policy Research