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The Distribution Of Life Expectancy Within U.S. States, Anne J. Israelsen, L. Dwight Israelsen
The Distribution Of Life Expectancy Within U.S. States, Anne J. Israelsen, L. Dwight Israelsen
Economic Research Institute Study Papers
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 preliminary study uses life expectancy by county to calculate the relative inequality in life expectancy within states. Gini coefficients for life expectancy are calculated for each state, and separate Gini coefficients are calculated for men and for women. The Gini coefficients are obtained from county average life expectancies by weighting each county life expectancy by county population, …
The Distribution Of Mortality In U.S. Counties, L. Dwight Israelsen, Ryan D. Israelsen, William J. Israelsen
The Distribution Of Mortality In U.S. Counties, L. Dwight Israelsen, Ryan D. Israelsen, William J. Israelsen
Economic Research Institute Study Papers
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 …
Distribution-Augmented Human Development Index: A Principal Component Analysis, Sanjib Sarker, Basudeb Biswas, Peter J. Saunders
Distribution-Augmented Human Development Index: A Principal Component Analysis, Sanjib Sarker, Basudeb Biswas, Peter J. Saunders
Economic Research Institute Study Papers
No abstract provided.
The Determinants Of The Distribution Of Mortality In Mountain States Counties, Anne Whyte, L. Dwight Israelsen, Ryan D. Israelsen
The Determinants Of The Distribution Of Mortality In Mountain States Counties, Anne Whyte, L. Dwight Israelsen, Ryan D. Israelsen
Economic Research Institute Study Papers
This study identifies the significant factors that affect the distribution of mortality by county in the Mountain States by using mortality data from the Multiple Cause of Death File of the National Center for Health Statistics. From this data, mortality (age at death) Gini coefficients are calculated for males and females for each county in the Mountain States (Arizona, Colorado, Idaho, Montana, Nevada, New Mexico, Utah, and Wyoming). These data are available for all counties only through 1989. Hence, the model of determinants of the distribution of mortality is tested using data from 1989-1990. Previous studies of the determinants of …
The Determinants Of The Distribution Of Mortality In United States Counties, L. Dwight Israelsen, Ryan D. Israelsen, Anne Whyte
The Determinants Of The Distribution Of Mortality In United States Counties, L. Dwight Israelsen, Ryan D. Israelsen, Anne Whyte
Economic Research Institute Study Papers
The purpose of this study is to determine the significant factors that affect the distribution of mortality by county in the United States, by using mortality data from the Multiple Cause of Death File of the National Center for Health Statistics from 1985 to 1994. These data are used to calculate distributions of mortality for men and women in each county by year. Gin coefficients are determined and used in a multiple regression model to ascertain the determinants of the distribution of mortality within counties. State and year effects are identified for the entire period, but the availability of data …
Globalization And Income Distribution Inequality Within Countries, Lei Zhou, Basudeb Biswas, Tyler J. Bowles
Globalization And Income Distribution Inequality Within Countries, Lei Zhou, Basudeb Biswas, Tyler J. Bowles
Economic Research Institute Study Papers
The issue studied in this paper is whether globalization affects income inequality within countries. Using the newly created Kearney (2002, 2003, 2004) data and the principal component analysis (PCA), we create two globalization indices. The Gini coefficient of a country is regressed on the indices respectively. One of the globalization indices is the equally weighted index. The other is derived from PCA. Sixty countries were involved in this study, including both developed and developing countries. The main conclusions obtained from the analysis can be summarized as follows: there is a negative relationship between the globalization index and the Gini coefficient …
Cattle Cycles, Expectations, And The Age Distribution Of Capital, David Aadland
Cattle Cycles, Expectations, And The Age Distribution Of Capital, David Aadland
Economic Research Institute Study Papers
This paper builds a dynamic forward-looking model describing the approximate ten-year cattle cycle. The theoretical model improves on existing models by (1) allowing cow-calf operators to make investment decisions on both the cow and calf margins, (2) formally recognizing the age distribution of the capital stock, and (3) considering a mixed scheme of rational and naive expectations. The model.is then calibrated and used to simulate artificial data that endogenously generates ten-year cycles in the total stock of cattle.
Measurement Error And The Distribution Of Income, L. Dwight Israelsen, James B. Mcdonald
Measurement Error And The Distribution Of Income, L. Dwight Israelsen, James B. Mcdonald
Economic Research Institute Study Papers
A model for measurement error is developed, based on the assumption that measurement error is random, multiplicative, and independent of the level of actual income. Thus, measured income is defined as the product of actual income and measurement error. Flexible parametric forms are utilized to model the distributions of actual income (generalized gamma) and measurement error (inverse generalized gamma). The probability density of measured income is then derived as a generalized beta of the second kind (GB2). Estimation of the parameters of the GB2 (measured income), then allows an estimate to be made of the pdf of actual income, from …