Distribution of Income

Australia's Recent Performance

The collection of data to analyse Australia’s recent performance in regards to this goal is sporadic, and as such it is challenging to establish emerging trends. However, we can certainly get some idea of the situation in this country from the data which has been published.

The following table lists the Gini co-efficient for two types of income at various stages for a period of10 years. The years that have been left blank are years in which that survey was not completed, and data has not yet been published for the years after 2006.

If we were able to see the Gini co-efficient for factor income, we would see that the number is even closer to 1 than the figure for gross income. In other words, as we move from factor income to gross income, the distribution becomes more equitable. Then as we move to disposable income the distribution becomes more equitable again. This would tend to suggest that the policies put in place by the federal government to redistribute income to help reduce the degree of income inequality in Australia are at least partly successful.

The clearest trend emerges from the progression in the Gini co-efficient for disposable income. In 1996/97 we can see that this figure was calculated to be 0.292. In the years to 2000/01, the figure slowly increased to 0.311. This indicates that the degree of income inequality in regards to disposable income in Australia was increasing during this period.

However, many people (including most economists) were surprised to discover that after the introduction of the GST in 2000, the distribution of income actually became more equitable. At first this seems counter-intuitive; the GST is a regressive tax, and so those on lower incomes would expect to be more affected. In interpreting these statistics, it is vital that you remember the definitions of the different types of income. The GST is an indirect tax. Therefore the impact of the GST is not seen in the Gini co-efficient for disposable income. In this sense, the statistic can not be used as a measure of living standards.

Despite this, the lower figure for the Gini co-efficient during this period must be explained. With an ongoing skills shortage, and strong demand for labour, we have seen the combined effects of increasing wages and falling unemployment. With more people receiving factor income, and a smaller percentage of the population collecting welfare payments, it is not surprising that the distribution of income is now more equitable.

It is also possible to assess the performance of the Australian economy based on “which group gets what”. To create the Lorenz curve, we must first break the population down into discrete groups – this allows for comparison. If we break the population down into ten groups, we call each a decile. On the other hand, when it is broken down into five groups, each fifth of the population is referred to as a quintile.

In this table we can see that in 1999/2000 the poorest 20% of the population received only 3.8% of the total income pool. At the same time, the richest 20% received 48.5% of the total income available. We already know that this situation resulted in a Gini co-efficient of 0.451 for gross income.

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