Inter-state Variation in Disability Applications during the Pandemic
The COVID-19 pandemic and its associated health and economic burdens have unfolded quite differently across states in the US. These differences are due to a variety of factors, including population density, socioeconomic status, health, and state policies. Variation across states in the timing and magnitude of the pandemic as well as in state characteristics and policies may have affected the dynamics of federal disability applications during this period.
In Inter-State Variation in Disability Applications During the COVID-19 Pandemic (NBER RDRC Working Paper 22-02), researchers Pinka Chatterji, Yiran Han, Kajal Lahiri, Jinman Pang, and Yimeng Yin examine inter-state differences in the monthly dynamics of disability applications after the onset of the pandemic.
The authors first create a spatial forecasting model of disability applications and use it to predict the number of applications in each state and month that would have occurred in the absence of the pandemic, after controlling for possible disruptions in the seasonal patterns due to the pandemic. They then calculate the difference between predicted and actual applications during the pandemic, which they term “state-level forecasting errors.” In a final step, they explore the association between these forecasting errors and state-level COVID cases and pandemic policies. The analysis uses State Agency Monthly Workload Data from the Social Security Administration merged with information on state characteristics, COVID cases, and policies.
The authors have several key findings. First, at the national level, there was a large drop in disability applications during the pandemic. Total applications were 84 percent of their 2017–19 level in May 2020 and 89 percent of that level in April 2022. The drop in disability applications was driven by falling Supplemental Security Income (SSI) applications, which remained at only 77 percent of their 2017–19 level in April 2022.
Second, the timing of the pandemic and its impact on Social Security Disability Insurance (SSDI) and SSI application rates varied considerably across states. For example, applications in Florida largely followed the national average during the first year of the pandemic but were far above this level during the second year, reaching 20 to 40 percent above expected levels in many months. By contrast, California experienced a steeper drop in applications than did the nation as a whole during the first two years of the pandemic, while New York experienced great volatility in applications during the pandemic’s first year.
Finally, the authors examine correlates of state-level forecasting errors during the pandemic years. They find that the unemployment rate, state of emergency declarations, and school closures all influenced whether a state experienced a smaller or larger decline in disability applications than the national average. A higher cumulative COVID death rate was associated with steeper declines in applications, suggesting that a higher burden of disease may have affected individuals’ ability to apply. There was a steeper decline in SSI applications in states that expanded Medicaid under the Affordable Care Act, possibly because individuals in expansion states were better able to obtain Medicaid without applying for disability.
The authors conclude, “Understanding how the pandemic has affected state-level disability applications since March 2020 is critical for policymakers to grapple with the fiscal impact of COVID-19, as well as to anticipate demands on the SSA front-line staff who process applications. In addition, it may shed light on long-term effects on disability applications in the aftermath of COVID-19.”
The research reported herein was performed pursuant to grant RDR18000003 from the US Social Security Administration (SSA) funded as part of the Retirement and Disability Research Consortium. The opinions and conclusions expressed are solely those of the author(s) and do not represent the opinions or policy of SSA, any agency of the federal government, or NBER. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of the contents of this report. Reference herein to any specific commercial product, process or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply endorsement, recommendation or favoring by the United States Government or any agency thereof. This project was also supported by grant number T32HS026128 from the Agency for Healthcare Research and Quality. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Agency for Healthcare Research and Quality. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.
