Document Type

Article

Journal/Book Title/Conference

Economics Research Institute Study Paper

Volume

3

Publisher

Utah State University Department of Economics

Publication Date

2006

Rights

Copyright for this work is held by the author. Transmission or reproduction of materials protected by copyright beyond that allowed by fair use requires the written permission of the copyright owners. Works not in the public domain cannot be commercially exploited without permission of the copyright owner. Responsibility for any use rests exclusively with the user. For more information contact the Institutional Repository Librarian at digitalcommons@usu.edu.

First Page

1

Last Page

44

Abstract

Previous studies on life expectancy by U.S. county have found large differences among counties in life expectancy at birth for both males and females. Various determinants of these differences have been identified, including economic, education, demographic, social, geographic, climatic, and environmental factors. This study uses mortality data to identify the distribution of mortality (age at death) and mortality Gini coefficients byU.S. county for males and females for each year between 1985 and 1994. The study also takes a preliminary look at differences in county mortality Gini coefficients among states, regions, and over time. The counties with the smallest degree of relative inequality in mortality tend to be smaller population, more rural counties in the Midwest, the Mountain States and Texas, while those with the largest degree of relative mortality inequality tend also to be smaller, rural counties in Alaska, the Dakotas, and the Mountain States. The main distinguishing factor in this latter group of counties is the prevalence of Indian reservations and/or Native American peoples in the counties. Some preliminary regression analysis identifies state effects on county mortality inequality, with states in the Central Rockies and the Deep South tending to have counties with larger mortality Gini coefficients. There does not seem to be a clear trend in relative county mortality inequality over the period examined. Further research to be pursued includes an extension of the data to 20002 and an examination of the determinants of relative mortality inequality for men and for women by county. County-level independent variables that will be used to explain differences in the distribution of county mortality are identified, and include economic, education, demographic, social, geographic, climatic, and environmental variables.

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