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• W2034156019 abstract "Julian Simon in 1989 observed that two-variable correlations between the rate of population growth and the rate of growth of per capita income usually show no significant relationship. This anti- Malthusian result has been obtained in both cross-sectional and time-series analyses. Such two-variable analyses however may be too primitive to justify the conclusion that changes in population growth rates have no effect upon economic growth. Simon agrees that the absence of correlation between two variables is usually a strong indication that neither variable is influencing the other thus that slower population growth does not cause faster economic development but argues that including one or more variables which have been otherwise left out of the analysis will lead to a negative partial relationship between population growth and economic development. These variables must however be named by any critic and be reasonable. Barlow accepts this challenge and names lagged fertility as a potentially omitted variable producing the result described by Simon. It is reasonable to add this variable to the current rate of population growth as a predictor of current per capita income growth because it enables one to disentangle short-run and long-run effects of population growth. It is argued that an increase in fertility over the short run tends to negatively affect economic growth but its partial effects over the long term tend to be positive. Since current fertility is highly correlated with past fertility current population growth rates capture both the short-run negative and long-run positive effects. Therefore in a two-variable correlation current population growth appears to have no effect upon current per capita income growth even when it does. This position is illustrated with a data set related to 86 countries at all levels of per capita income over the periods 1968-74 and 1977-83." @default.
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• W2034156019 date "1994-03-01" @default.
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• W2034156019 title "Population Growth and Economic Growth: Some More Correlations" @default.
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