Determinants of Elderly Health: The Role of Place-Based Factors

Massachusetts Institute Of Technology, Cambridge MA

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Abstract

Heterogeneity in Damages from A Pandemic∗ Amy Finkelstein, MIT and NBER Geoffrey Kocks, MIT Maria Polyakova, Stanford University and NBER Victoria Udalova, U.S. Census Bureau June 10, 2024 Abstract We use linked survey and administrative data to document differences across multi- ple socio-economic and demographic groups in the extent of adverse economic and health impacts of the first two years of the COVID-19 pandemic in the United States. Across a wide set of characteristics—including race/ethnicity, education, industry, and occupation—the impacts of the pandemic on all-cause mortality and on employment were disproportionately concentrated in the same groups in the population. As the pan- demic progressed, disparities in the pandemic’s mortality impacts narrowed substan- tially between Black and White Americans and between Hispanic and White Ameri- cans, but persisted along the educational divide. For economic damages, only Hispanic- White disparities narrowed; Black-White and educational disparities persisted for the first two years of the pandemic. We also document greater mortality impacts for lower income individuals, with this negative income-excess mortality gradient becom- ing steeper in the pandemic’s second year. Together our findings—using a consistent set of methods and measures on nationally representative data with a wide set of mea- sures of socio-economic status—paint a detailed picture of the heterogeneous impacts of the first two years of the COVID-19 pandemic on health and economic well-being. ∗ This manuscript is intended to inform interested parties of ongoing research and to encourage discussion. Any views expressed are those of the authors and not those of the U.S. Census Bureau. We acknowledge funding from the National Institute on Aging under grant R01-AG032449 (Finkelstein), grant T32-AG000186 (Kocks), grant U01-AG076557 (Polyakova), National Science Foundation Graduate Research Fellowship under grant 2141064 (Kocks) and National Institute for Health Care Management Foundation (Polyakova). We are grateful to Miray Omurtak for excellent research assistance, to the NBER Racial and Ethnic Health Disparities Conference and the NBER Longer-Term Health and Economic Effects of COVID-19 Conference, and to Ben Handel (the editor) and six anonymous referees for helpful comments. The U.S. Census Bureau reviewed this data product for unauthorized disclosure of confidential information and approved the disclosure avoidance practices applied to this release under authorization numbers CBDRB-FY22-POP001-0104, CBDRB-FY22-POP001-0117, CBDRB-FY23-POP001- 0001. This research project was conducted as part of the Census Bureau’s Enhancing Health Data (EHealth) program under DMS project 7515435 (Social Determinants of Health). 1 1 Introduction The United States has long exhibited striking variation in health and economic well-being across demographic groups, including education, income, race, and ethnicity.1 The COVID- 19 pandemic – which was both a health and an economic crisis – was no exception. To characterize its heterogeneous impacts, we assemble rich, nation-wide, representative data on both economic and health damages from the pandemic. We document how the economic and health impacts of the pandemic varied across a wide set of pre-pandemic socio-economic characteristics, as well as how these disparities evolved over the course of the first two full years of the pandemic in the U.S. – from March 2020 through February 2022. We define the pandemic’s health damages by the increase in all-cause annual mortality relative to what was expected based on the historical linear trend. We define the pandemic’s economic damages by the average monthly decline in the employment-to-population ratio, again relative to the historical linear trend. We present estimates of average impacts over the first two years of the pandemic, and also show how these impacts evolved during this time period. We leverage linked administrative and survey data for the mortality analysis. Specifically, we use the U.S. Census Bureau’s version of the Social Security Administration’s Numerical Identification database (Census Numident), which provides individual-level data on the date of death (if applicable) for the near universe of the U.S. population. We link these admin- istrative all-cause mortality records to a record of race/ethnicity from the 2010 Decennial Census, and to a rich set of additional, pre-pandemic socio-economic covariates—including 1There is a vast literature documenting these disparities and investigating causal origins. Examples of the literature on health variation include Fuchs (1974), Case et al. (2002), Deaton (2002), Williams and Jackson (2005), Meara et al. (2008), Currie (2009), 2011, Boustan and Margo (2015), Case and Deaton (2015), Chetty et al. (2016), Weinstein et al. (2017), Lleras-Muney (2022), Polyakova and Hua (2019), Chetty et al. (2020), Bailey et al. (2021), Finkelstein et al. (2021), Schwandt et al. (2021), and Novosad et al. (2022). Examples of the literature on variation in economic well-being include Hoynes et al. (2012), Bayer and Charles (2018), and Derenoncourt et al. (2022). 2