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The paper documents key patterns of community-level disparities in access to unemployment insurance (UI) during the pandemic. To operationalize the notion of access to UI, researchers rely on a comprehensive conceptual framework that allows them to track a jobless worker’s access to UI benefits across three discrete stages in the lifecycle of a potential UI claim. To document the degrees of disparities in access throughout the lifecycle of a UI claim, the analysis develops and compares measures for each stage of access both across states and at more local levels within California. Researchers then correlate these measures of access with state and county characteristics to measure differences in access across these attributes.

Unemployment Insurance (UI) benefits provided a lifeline to workers who lost their jobs during the pandemic. However, access to these benefits has been uneven across communities and states (Edwards, 2020). Identifying and documenting these disparities is an important step to addressing them and to rendering the UI system more equitable. In the paper, utilizing a conceptual framework of unemployment claims, the researchers developed three metrics to measure access to UI benefits across the claim lifecycle. They then analyzed these measures to provide insight into differential access to UI benefits across U.S. states and across counties within California. The first measure of access is the First Payment Rate and corresponds to the earliest part of the claim lifecycle. It measures the share of people who file their first claim and who subsequently receive a UI payment. After the First Payment Rate, the primary measure of access in the report is the Recipiency Rate. The recipiency rate measures the share of unemployed or underemployed workers who are actually receiving UI benefits. This is the traditional measure (Wittenberg et al., 1999) of UI access, and reflects access in the middle of the claim lifecycle. The final measure of access is the Exhaustion Rate, which corresponds to the final part of the claim lifecycle. It measures the share of claimants who have exhausted eligibility for both regular and extended UI benefits.

The researchers calculated these metrics in each state by using publicly available data from the U.S. Department of Labor reports and by county in California using tabulations based on individual-level claims data from the California Employment Development Department. The additional information available in the California claims data allows them to improve and further segment their measures of access, allowing them to identify new facts and patterns from the data. They generated these metrics for the year 2020 and focused their analysis from the beginning of the pandemic in March through December 2020, just prior to the initial rollout of COVID-19 vaccines. In addition, they compared these to the corresponding values in December 2019 as a pre-pandemic benchmark.

The researchers use these measures to analyze disparities in access to UI benefits during and before the pandemic and identify community attributes and policy choices that are associated with differential access. This analysis cannot identify causal relationships, however, across metrics, there is a pattern of correlations showing that workers in states with more generous labor and UI policies have greater access to benefits, potentially indicating the importance of policy choices in shaping UI access. The correlations also show a pattern by which less affluent areas and areas with a higher share of disadvantaged social groups are associated with lower access to UI benefits. Additional research is needed to identify the causal mechanisms between policies and UI access.

Citation

Bell, A., Hedin, T. J., Mannino, P., Moghadam, R., Schnorr, G., Von Wachter, T. (n.d.). Disparities in Access to Unemployment Insurance During the COVID-19 Pandemic: Lessons from U.S. and California Claims Data. Chief Evaluation Office, U.S. Department of Labor.

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This study was part of CEO’s Summer Data Challenge on Equity and Underserved Communities, and was produced outside of CEO’s standard research development process.