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  5. New Research on Paid Leave Policies
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New Research on Paid Leave Policies

Paper Session

Friday, Jan. 6, 2023 2:30 PM - 4:30 PM (CST)

Hilton Riverside, Chart C
Hosted By: American Economic Association
  • Chair: Laura Dague, Texas A&M University

Access To Paid Leave Among Those With Caregiving Needs

Priyanka Anand
,
George Mason University
Laura Dague
,
Texas A&M University
Kathryn Wagner
,
Marquette University
Janusz Wojtusiak
,
George Mason University

Abstract

Our paper explores the long-term characteristics of people who have access to paid leave, with a particular focus on whether people who are most in need of paid leave are the ones who have access to it. Because there are no datasets that have information on both the availability of and need for paid leave, we use the American Time Use Survey to develop a machine learning-based classification model to determine the likelihood of having access to paid caregiving leave based on individual, employer and job characteristics. We use this model to categorize individuals in Survey of Income and Program Participation (SIPP) into three groups: those who are highly likely to have access to paid leave, those who are highly unlikely to have access to paid leave, and those with no clear prediction. We then examine characteristics such as the employment status, financial security, and public program use of those who have a need for paid leave (that is, those who experience a health shock or those who have family members who experience a health shock) and either do and do not have access through the state or their employer. Our findings have important policy implications for current efforts to expand access to paid leave to those who are most in need.

Impact of State-Level Changes in Paid Family Leave Policies: Evidence from New Jersey and New York

Rachel M.B. Atkins
,
New York University
Tracy Freiburg
,
St. John’s University
Kier Hanratty
,
Pace University

Abstract

In this paper, we examine the impact of paid family and medical leave policies (PFML) on entrepreneurship and employment outcomes. Our analysis exploits the variation in the timing of when the bordering states of New Jersey and New York implemented their PFML policies. We employ a difference-in-differences research design using census tract level data from the American Communities Survey (ACS), to evaluate whether these policies impacted employment and entrepreneurship (measured using self-employment levels). We also investigate whether the effects of the PFML programs varied by subgroups including race and gender. Additionally, we explore whether there were differential effects on business owners and workers operating in low-income versus high-income neighborhoods or in high-margin industries versus low-margin industries. Overall, we seek to evaluate whether marginalized communities experienced positive or negative effects from PMFL programs.

COVID-19 and Paid Leave: Assessing the Impact of the FFCRA

Tanya Byker
,
Middlebury College
Kristin Smith
,
Dartmouth College
Elena Patel
,
University of Utah

Abstract

Using monthly Current Population Survey data, this study will examine leave-taking behavior during the first few months of the coronavirus pandemic in the United States. Specifically, the authors will investigate whether and how leave-taking was influenced by the passage of the Families First Coronavirus Response Act. The researchers will analyze the impact of FFCRA on several employment and leave-taking outcomes such as employment status, usual hours worked, and reasons for work absence (including child-care problems or one’s own illness). They will use these variables to measure leave-taking behavior, including total leave-taking and reasons for leave taking. These data allow them to explore how workers trade off the alternatives to leave-taking, including working while sick or separation from the labor force. Using a difference-in-difference empirical estimation strategy, the authors will compare leave taking in states that do or do not have state-based paid family and medical leave programs.

The Impact of Paid Family Leave on Families With Health Shocks

Maya Rossin-Slater
,
Stanford University
Courtney Coile
,
Wellesley College
Amanda Su
,
Stanford University

Abstract

This paper analyzes the impact of paid family leave (PFL) policies in California, New Jersey, and New York on the labor market and mental health outcomes of individuals whose spouses or children experience health shocks. We use data from the 1996-2019 restricted-use version of the Medical Expenditure Panel Survey (MEPS), which provides state of residence and the precise timing of hospitalizations and surgeries, our health shock measures. We use difference-in-difference and event-study models to compare the differences in post-health-shock labor market and mental health outcomes between spouses and parents before and after PFL implementation relative to analogous differences in states with no change in PFL access. We find that (healthy) wives of individuals with medical conditions or limitations who experience a hospitalization or surgery are 7.0 percentage points less likely to report ''leaving a job to care for home or family'' in post-health-shock rounds of the data when they have PFL access. Impacts of PFL access on women’s mental health outcomes and on men whose spouses have health shocks are more mixed, and we find no effects on parents of children with health shocks. Lastly, we show that improvements in job continuity are concentrated among caregivers with 12 or fewer years of education, suggesting that government-provided PFL might reduce disparities in leave access.

Discussant(s)
Kanika Arora
,
University of Iowa
Linh Tô
,
Boston University
JEL Classifications
  • I3 - Welfare, Well-Being, and Poverty
  • J3 - Wages, Compensation, and Labor Costs