Income inequality and mortality: time series evidence from Canada.

In this paper, we apply the standard model used in the income strand of the socio-economic status (SES)-population health literature to explain the relationship between mortality and income to pooled cross-section time-series data for Canada. The use of time-series data increases the available degrees of freedom and allows for the possibility that the effects of inequality take time to translate into poorer health outcomes. In light of recent criticisms of aggregate level studies, we do not attempt to differentiate between the absolute and relative inequality hypotheses, but test for the existence of a relationship between mortality and a measure of income inequality. We find that whether an exogenous trend is incorporated or an auto-regressive distributed lag form is used, the coefficients on mean income and the Gini are not significantly different from zero, which contradicts the findings in other parts of the literature, but which is consistent with earlier cross-section evidence for Canada. The results suggest that models that focus exclusively on income as a measure of the impact of SES on mortality are not complete and that health spending and unemployment may be even more important than income growth and dispersion.