International Journal of Humanities and Social Science

      ISSN 2220-8488 (Print), 2221-0989 (Online) 10.30845/ijhss

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      Life Expectancy and its Socioeconomic Determinants – A Discriminant Analysis of National Level Data
      Abu Jafar Mohammad Sufian

      Abstract
      Although studies in recent years have shown that life expectancy at birth (LEB) has been rising in almost all societies, significant differentials in mortality, and hence, in LEB, exist within, as well as, between societies. This disparity in LEB is believed to have its roots in differential socioeconomic backgrounds of different social groups. The underlying rationale is that the socioeconomic, and environmental factors do exert independent, as well as, interactive influence on the LEB level. The aim of this paper is to identify the effects of different socioeconomic factors on life expectancy at birth across a number of countries by analyzing national level data. The source of data in this analysis is the World Population Data Sheet, 2011. Data on LEB and all other nine variables used in this analysis are available only for 106 countries in the World Population Data Sheet, 2011. The values of LEB have been collapsed and the countries have been classified to yield three groups: group 1 - countries with low values of LEB; group 2 - countries with medium values of LEB; and group 3 - countries with high values of LEB. The technique called 'Canonical Discriminant Analysis' is employed to uncover variables that discriminate among the groups most. Standardized coefficients as well as structure coefficients have been examined to identify these variables. A number of measures such as Wilk's lambda, canonical correlation, plot of group centroids etc., have been used to assess the appropriateness of the technique, and efficiency of the variables to discriminate among the groups. The analysis shows that the infant mortality rate is the most influential variable in discriminating among the three groups, while poverty is the second most influential variable. The other important discriminators are also identified.

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