Abstract
This paper discusses the post-war trends in life expectancy worldwide. Even though applying the specification test to a sample of 125 countries suggests that some life expectancy clubs exist, their number and borderlines are not properly distinguished by mechanical splits of the sample. Hence, the clubs are discovered by regression tree analysis. The potential threshold variables are initial per capita income, literacy, fertility change, and the HIV prevalence rate in 2005. Four clubs appear, characterized as High Literacy, Low Literacy, Medium Literacy, and High AIDS, between which considerable life expectancy differentials appear.Excluding the HIV prevalence rate from the threshold candidates re-allocates a considerable number of the members of the High AIDS club, indicating that incomes, literacy, and fertility are unable to predict AIDS completely. The similarity of economic and demographic conditions in the Low Literacy and High AIDS clubs, however, raises concerns about life expectancy convergence in the future.
Highlights
Since World War II, many countries have experienced enormous gains in life expectancy and, in the most spectacular cases, have nearly doubled it
The specification test suggests that some life expectancy clubs exist in a sample of 125 countries, and their number and boundaries are revealed by regression tree analysis
The fastest growth was seen in the Low Literacy club, in which life expectancy increased by almost twenty years from 1960 to 2001
Summary
Since World War II, many countries have experienced enormous gains in life expectancy and, in the most spectacular cases, have nearly doubled it. Growth has typically been greater the lower was the initial life expectancy, leading to considerable convergence across countries. This convergence, has not been equivocal, as some countries seem to be caught up in a low-life expectancy trap and, in the most unfortunate cases, life expectancy has even decreased.. The optimists claim that, in spite of some exceptional cases, the trend is unique and most low-life expectancy countries will catch the high-life expectancy ones. The reason for this is the widespread diffusion of health technologies, driven by market forces and promoted by international health programs. The optimists maintain that the basic health technology is quite easy to adopt and implement, and will lead to a rapid decrease in infections and infant mortality in developing countries, whereas gains are less available in more developed countries, where life expectancy gains mostly come through the decrease in cardiovascular diseases (Omran 1971; Deaton 2003; Vallin and Meslè 2004; Edwards and Tuljapurkar 2005; Cutler et al 2006)
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