Estimating Nursing Home Quality with Selection
44 Pages Posted: 21 Apr 2022 Last revised: 5 Aug 2023
Date Written: March 10, 2022
We use variational inference (VI), a technique from the machine learning literature, to estimate a mortality-based Bayesian model of nursing home quality accounting for selection. We demonstrate how one can use VI to quickly and flexibly estimate a high dimensional economic model with large datasets. Using our facility quality estimates, we examine the correlates of quality and find that public report cards have near-zero correlation. We then show that in contrast to prior literature, higher quality nursing homes fared better during the pandemic: a one standard deviation increase in quality corresponds to 2.5% fewer Covid-19 cases.
Funding Information: Olenski gratefully acknowledges support from the National Science Foundation Graduate Research Fellowship.
Declaration of Interests: None to declare.
Keywords: snf, nursing homes, covid, medicaid, variational inference
JEL Classification: I11, I18, L15
Suggested Citation: Suggested Citation