Poverty Is Low Consumption and Low Wealth, Not Just Low Income

Abstract

The purpose of this paper is to suggest an improved measure of financial poverty, based on household consumption and wealth as well as income. Data come from the Household, Income and Labour Dynamics Australia (HILDA) Survey, which appears to be the first national socio-economic panel survey to provide longitudinal data on all three measures of household economic well-being. National measures of poverty in Australia and other Western countries are usually based only on low income. But this is conceptually incorrect; the measures lack validity. To be poor is to have a low material standard of living—involuntarily. So measures of poverty should also take account of household consumption and wealth. If a household has an adequate current level of consumption, it should not be classified as poor right now, even if its current income is low. Similarly, if it has substantial wealth (net worth), it should not be viewed as poor because it could draw down on wealth to boost current consumption. The invalidity of income-based measures has long been recognised in principle (Ringen 1987, The possibility of politics. Oxford: Clarendon Press). In practical terms, the problem is to combine measures of wealth and income, and especially consumption, in the same survey. In the 2005 HILDA Survey a battery of household expenditure items was included which, benchmarked against the Australian Bureau of Statistics’ Household Expenditure Survey for 2003–04, appeared to provide valid measurement of 53.4% of total household expenditure. These well measured items correlated 0.76 with total expenditure and, in combination with standard demographic variables, accounted for 78.3% of the variance in the total. This paper uses 2005–06 HILDA data to construct revised measures of financial poverty. The value of these measures for public policy and research purposes is illustrated. In particular, the new measures give much lower estimates of poverty than income-based measures. They can also be used to predict which households are at risk of future poverty.