CEO Library

In the issue brief, researchers report findings from testing and validating the Worker Paid Leave Usage Simulation (Worker PLUS) using data from the 2018 U.S. Department of Labor Family and Medical Leave Act Employee Survey; the 2014–2018 American Community Survey Public Use Microdata Sample; and benefit outlay data published by state paid leave programs in California, New Jersey, and Rhode Island. The brief also discusses the implication of the model testing results on choice of simulation methods, assessment of program take-up rates, and estimation of program benefit outlays.

The issue brief provides a step-by-step guide to using the Worker Paid Leave Usage Simulation (Worker PLUS) Model to perform an example policy simulation of the recently proposed parental leave program for federal workers. The model uses as its intakes the 2018 U.S. Department of Labor (DOL) Family and Medical Leave Act Employee Survey and the sample of civilian employees at the federal government from the 2014–2018 American Community Survey Public Use Microdata Sample and applies program parameters that best reflect the proposed leave program.

In the issue brief, researchers use simulation results from the Worker Paid Leave Usage Simulation (Worker PLUS) Model to analyze the impacts of moving from the unpaid leave system under the current Family and Medical Leave Act to a system that includes a paid leave program that adopts the program rules of the existing program in California. The population considered consists of individuals who work in the state of Maryland who meet the eligibility rules of the California program, and among them, the low-wage workers who earn no more than $30,000 annually.

The brief provides a step-by-step guide to performing example simulations using the Worker Paid Leave Usage Simulation (Worker PLUS) model. With this guide, users should be able to replicate the provided example of model running using either the Python or the R simulation engine, and to check how the simulation results compare against actual program data for existing state programs in California, New Jersey, and Rhode Island.

To help researchers, policy analysts, and interested members of the public gain better understanding of the Worker Paid Leave Usage Simulation (Worker PLUS) Model and its applications in policy analysis, researchers present an issue brief series to supplement the model documentation files.

The paper compares leave experiences of low-wage and non-low wage workers using data from the 2018 Family and Medical Leave Act (FMLA) Employee Survey. It finds that in some ways experiences are similar—both groups take needed leave at similar rates for similar reasons. In other ways experiences are very different and worse for low-wage workers—they less commonly have access to paid leave or are eligible for FMLA protections and more commonly face adverse financial and job consequences from taking leave.

Using data from the 2018 Family and Medical Leave Act (FMLA) Employee Survey, the paper explores patterns of needing and taking leave from work for a family or medical reason—either for one’s own health, or to care for someone else. The 2018 FMLA Employee Survey asks U.S. employees about their need for leave for a family or medical reason, whether they took leave, and their experiences while on leave—all for the twelve months prior to the survey. This paper begins by exploring patterns in needing and taking leave between women and men.

The brief uses data from the 2018 Family and Medical Leave Act (FMLA) Employee Survey and Worksite Survey to summarize findings on employee access to paid leave benefits, pay received while on leave for a family or medical reason, pay and unmet need for leave. It also describes variation in findings between states that do and do not offer paid family and medical leave.

The brief uses data from the 2018 Family and Medical Leave Act (FMLA) Employee Survey to summarize findings on employee leave-taking rates and characteristics of leaves taken. The survey asked about family and medical leave, both for qualifying FMLA reasons and for care of non-immediate family members with serious health conditions (which does not typically qualify). Other medical reasons that are not serious health conditions, such as a sick day for a cold, are not included.

The brief uses data from the 2018 Family and Medical Leave Act (FMLA) Employee Survey to summarize findings on employee eligibility rates, reasons for ineligibility, differences in eligibility by employee characteristics, and knowledge of their own eligibility.

The methodology report appendices to the 2018 Family and Medical Leave Act (FMLA) surveys that include employee survey materials, employer survey materials, revision matrices, nonresponse follow-up employee survey materials, and employer survey response option experiment (detailed findings).

The report for the 2018 Family and Medical Leave Act (FMLA) surveys that details the methods used to conduct the surveys.

The supplemental results from the 2018 Family and Medical Leave Act (FMLA) surveys that provide key definitions and detailed survey results, including both more detailed information underlying exhibits presented in the technical report and additional exhibits not displayed in the technical report.

The executive summary of the 2018 Family and Medical Leave Act (FMLA) surveys that summarizes the conduct of the 2018 surveys and major findings.

The report of the 2018 Family and Medical Leave Act (FMLA) surveys, presenting findings, including comparisons between worksites covered and not covered by FMLA, between employees eligible and ineligible for FMLA, and over time.

The U.S. Department of Labor’s (DOL) Employee Benefits Security Administration (EBSA), in conjunction with the Internal Revenue Service (IRS) and the Pension Benefit Guaranty Corporation (PBGC), publishes the Form 5500 Annual Return/Report of Employee Benefit Plan (Form 5500) and the Short Form Annual Return/Report of Small Employee Benefit Plan (Form 5500-SF).

In 2017, the Chief Evaluation Office (CEO) partnered with the Employee Benefits Security Administration (EBSA) and funded contractor Summit Consulting to conduct An Analysis of Benefit Plans Auditors under the Administrative Data Research and Analysis portfolio of studies. The statistical analysis aims to analyze trends in employee benefit plan audit quality, particularly when plan administrators change certified public accountant (CPA) firms.

The report presents findings from a trend analysis of benefit plan auditors using 5500 filing data and audit reviews conducted by Employee Benefits Security Administration (EBSA) between plan years 2011 and 2015. EBSA administers and enforces the reporting, disclosure, and fiduciary requirements of Title I of the Employee Retirement Income Security Act of 1974 (ERISA). EBSA’s Office of the Chief Accountant, Division of Accounting Services enforces annual audit requirements of employee benefit plans.

In 2018, the Chief Evaluation Office (CEO) partnered with the Office of Workers’ Compensation Programs (OWCP) and funded contractor Summit Consulting to conduct Return-to-Work Outcomes for Federal Employees in the Office of Workers’ Compensation Disability Management Program under the Administrative Data Research and Analysis portfolio of studies.

The report provides descriptive statistics and associations between case characteristics (injury, claim, and claimant characteristics) and the outcomes of interest (return-to-work and disability management duration). Process diagrams and survival models complement the descriptive statistics. This report also assesses the similarities and differences in return-to-work rates and duration in disability management across case characteristics and timing and sequence of disability management services.

In 2017, the Chief Evaluation Office (CEO) partnered with the Employment and Training Administration (ETA) and funded contractor Mathematica Policy Research to conduct Data on Earnings: A Review of Resources for Research and Comparing Job Training Impact Estimates Using Survey and Administrative Data under the Administrative Data Research and Analysis portfolio of studies. The descriptive analyses aim to review potential opportunities and implications of using different

The U.S. Department of Labor (DOL) Employee Benefits Security Administration (EBSA) administers and enforces the reporting, disclosure, and fiduciary requirements of Title I of the Employee Retirement Income Security Act of 1974 (ERISA). Multiple Employer Welfare Arrangements (MEWAs) and certain Entities Claiming Exception (ECEs) must file the Form M-1 report annually. Form 5500 is an annual report that employee benefit plans must file to satisfy reporting requirements under Title I and Title IV of ERISA and under the Internal Revenue Code.

Earnings are a key outcome in evaluating the impact of job training and other employment- oriented assistance programs. Adequate and sustained earnings provide a reliable measure of success for these interventions and contribute to other positive outcomes as well. Accordingly, high quality data on the income earned from employment—including self-employment—are an essential component of any analysis that seeks to understand the consequences of participating in an employment-assistance program.

The report presents a high-level look at the community engagement (CE) project approach and analysis, and presents options that the U.S. Department of Labor (DOL) Women’s Bureau (WB) may consider for future exploration. It is important to note that this project was not conducted as a rigorous assessment of the impact of the WB’s work overall or the work resulting from its CE approach. Rather, the focus was on understanding the CE activities the WB conducts at the regional level and developing potential options the WB could consider to strengthen its approach in the future.

The Family and Medical Leave Act (FMLA) enables employees to take up to 12 weeks of unpaid, job-protected leave. However, while FMLA has increased leave-taking among eligible workers, overall effects have been modest, perhaps because much of the workforce is ineligible for FMLA, and many who are eligible are unaware of the law’s benefits and eligibility requirements.