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Economics Research Institute Study Paper




Utah State University Department of Economics

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Over the last five decades, life expectancy at birth in the United States and in the Mountain States has been increasing steadily for both males and females. Previous studies of mortality or life expectancy have looked at relatively small cohorts of people over time, or have looked at mortality or life expectancy at the national or state level. The larger-scale studies have usually concentrated on only one or a few of the determinants of life expectancy. The Harvard Center for Population and Development Studies recently published life expectancy tables for all U.S. counties for both males and females. Life expectancy varies greatly across counties in the eight Mountain States. This study examines the impact of demographic, economic, educational, social, and geographic factors on life expectancy by Mountain States county for males and females born in 1990. The models tested here can explain between 62 and 84 percent of the total county-level variability in life expectancy for men and for women. In general, we conclude that educational attainment is positively associated with life expectancy for both sexes; and that the percentage of the county population age five and older speaking a language other than English at home is positively associated with average female life expectancy; while the percentage of the county population foreign-born is positively associated with average male life expectancy. The percentage of the county whose primary ancestry is Northern European has a generally positive affect on both female and male life expectancies. The percentage of the population black and the percentage American Indian, Eskimo, and Aleut decreases meat county life expectancies for both men and women, ceteris paribus, but the effect is more significant in the statistical sense for female life expectancy. Violent crime rates are negatively associated with life expectancies for men and women, but population density seems to have a negative effect primarily on mean male life expectancy. The percentages of the county population classified as urban and as rural farm, the percentage of households married, and household size all have a positive effect on mean county life expectancies for both sexes. The only economic variables that seem to matter in determining life expectancy are income and income squared, which have the expected pattern of signs that give rise to a U-shaped relationship between income and life expectancy, but only for men. Latitude and elevation seem to be negatively associated with life expectancy, especially for women. Other things equal, life expectancy is greater than expected for both men and women in Colorado, Idaho, New Mexico, and Utah; while life expectancy is less than expected for both men and women in Nevada and Wyoming. In Montana, men live longer than the rest of the model predicts, while women have a shorter life expectancy.