Methods for testing the income-health relative hypothesis that the distribution of income in a society affects the distribution of health.

Health and income relation analysis has been the subject of controversies on the absolute income hypothesis (the higher an individual's income, the better their health status) and the relative income hypothesis (individual health is affected by the distribution of income within society). In addition, the assumed relationship has been criticised as being a statistical artefact. To overcome these issues, we formulate the hypothesis that the distribution of health in a society is correlated with the distribution of income in that society and propose the analytical method framework. The method is focused on the calculation of Foster-Greer-Thorbecke (FGT) poverty indices using health and income outcomes. Econometric time series methods, particularly the autoregressive distributed lag (ARDL) cointegration bounds test and dynamic simulation, are complementary tools used to measure the relationship between the calculated indices. Applied to the sub-sample of countries below the poverty line, the method highlights the correlation between the gaps and inequalities in health outcomes and the gaps and inequalities in income outcomes, respectively. • The Foster-Greer-Thorbecke (FGT) poverty indices are applied to income and health outcomes. • Aggregate poverty indices are measured across states. • These indices are meaningful indicators for analysing the link between the distribution of health and the distribution of income in a society.