Modeling Area-Level Health Rankings

Charles Courtemanche, Samir Soneji () and Rusty Tchernis
Additional contact information
Samir Soneji: Geisel School of Medicine at Dartmouth College

No 7631, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: We propose a Bayesian factor analysis model to rank the health of localities. Mortality and morbidity variables empirically contribute to the resulting rank, and population and spatial correlation are incorporated into a measure of uncertainty. We use county-level data from Texas and Wisconsin to compare our approach to conventional rankings that assign deterministic factor weights and ignore uncertainty. Greater discrepancies in rankings emerge for Texas than Wisconsin since the differences between the empirically-derived and deterministic weights are more substantial. Uncertainty is evident in both states but becomes especially large in Texas after incorporating noise from imputing its considerable missing data.

Keywords: factor analysis; health; rank; county; Bayesian (search for similar items in EconPapers)
JEL-codes: C11 I14 (search for similar items in EconPapers)
Pages: 40 pages
Date: 2013-09
New Economics Papers: this item is included in nep-dem, nep-geo and nep-hea
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Published - published in: HSR Health Services Research, 2015, 50 (5), 1413-1431

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Related works:
Working Paper: Modeling Area-Level Health Rankings (2013)
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