This is the first of a series of posts on inequality, with a particular focus on South Australia. The series begins with income inequality between states, but will then consider inequalities within South Australia. Unless otherwise stated, the data is drawn from the Australian Bureau of Statistics’ Household Income and Wealth series, but the posts often use different categories and ask different questions to those presented in the ABS data.

The primary analytic used here is often the share of total income. It is an aggregate measure used because the more usual “average” figures (mean or median) tend to individualise social and structural issues. Further, the average figures do not account for the changes in numbers of people or households within a category. This is a parallel argument to one I made in relation to the gender wage gap, but in the case of the inequality highlighted in this post, the share of total income takes account of for both differences in household income and population changes. As will be seen, this makes a difference in the story told by the data.

The share of total income as a measure of inequality between states is also important in its own right because it highlights the relative resources available to different communities. A millionaire recluse living on their own island may have a high average income, but that is the only resource available to them. By contrast, a larger community may have much lower average incomes but far more resources which can be taxed and mobilised for the community.

Inequality between States: 2020 data

In 2020 South Australian households accounted for 6.3% of all household income in Australia, while constituting 6.9% of the population. This may appear to be a small difference, but is actually quite significant. This 0.6 percentage point difference is approximately 10% of the income share. It equates to around $130m per week or $6.7bn per year which would be in the South Australian economy if the state’s share of income matched its population share.

Putting the data in this form highlights the wicked dilemma of this inequality between states. South Australia (and other lower-income states) do not have the same income resources to drive the development which could see it catch up to the other higher-income states. If there are no other national financial redistributions, the inequality is perpetuated. This potential cycle is one reason why federal government support and the distribution of the GST pool in favour of the poorer states is crucially important.

As the graph below shows that SA is not alone in having a lower share of income than population. Queensland has the largest gap between income and population shares at 0.8 percentage points, but this is on a relatively large base (equating to just 4% of the income share). Tasmania’s income share is 0.3% below its population share, but this is particularly significant when the population share is only 2.3% of the whole in first place.

By contrast, WA has the highest gap with income share greater than their population share. Their 10.7% share of national household income is 0.5 percentage points above their population share. This equates to about 5% of their population share. Again, the percentage differences may appear small, but constitute significant amounts of money and represent significant inequalities between Australian states.

It is noteworthy that these figures do not simply reflect differences in household income. Average (gross mean) household income in South Australia was $1,989 per week, which was 85.4% of the national figure ($2,329). Tasmania’s average household income was 75% of the national average. But both SA and Tasmania also have smaller households on average, which pulls their income averages lower.

By contrast, the average gross household income in the Northern Territory was $2,711 – the second highest in the country and 16.4% above the national average. This would seem surprising, but the territory data excludes remote areas. The result is also a product of larger household sizes (average of 2.9 people per household in the Territory, as opposed to 2.6 nationally). The NT’s share of national income roughly reflects their population share.

Of course some of these demographic differences would be captured had I used the ABS equivalised income data sets (which are adjusted to take account of household size). However, using the data on shares of national income to measure inequality between states also provides important insights on changes over time.

Changes over Time: South Australia

While South Australia’s share of national household income is currently below its share of population, its income share has also declined over the last 20 years. As shown in the graph below, the state’s share of national household income reached a high in 2003-04 at 7.4%, but dropped below 7% in 2007-08 and has not recovered.

In all years the SA share of national household income was below its population share, while average household incomes were also consistently below the national average. However, (again) it was not simply about lower average household incomes. As the graph below shows, the South Australian average household income as a percent of the national average fluctuated over the period. It ranged from a high of 91.6% of the national average in 2003-04 to a low of 81.3% in 2013-14, before returning by 2019-20 to close to its 2000-01 value around 85%. In that sense, while changes in household income provide short term fluctuations, what is really evident in the graph below (which plots the three variable as indexes with the same starting point) is that the overall decline in South Australia’s share of income has been driven much more by the decline in population share.

Again, the fall of 0.7 percentage points in South Australia’s share of national household income over the period may seem minor, but it is actually a drop of around 10% of South Australia’s share of national income. It equates to well over $8bn annually in current dollars that would be in SA if income share had been maintained its share of national household income over the period.

While the COVID pandemic has changed some migration and population patterns, the longer-term trends remain to be seen and the wicked problem of maintaining income and population shares is likely to remain for a while yet.

Caveats

There are of course a number of caveats to the above data and analysis. In previous posts I have been critical of these household income figures: (here) for not taking account of capital gains and non-cash housing income, and (here) noting Piketty’s critique of the categorisation and data sources. The ABS does publish some data on non-cash income (imputed rents, and “social transfers in-kind” [i.e. provision of free services like health and education which do not appear in household budget]). This provides a fuller account of household income, but it is still without capital gains and is not published at the state level.

Without that state data on total income, the analysis is incomplete. It is likely that imputing rent for owner-occupied dwellings would reflect higher rental prices in eastern states and increase the differences between South Australia and some of those states. By contrast, the social transfers in-kind are likely to disproportionately benefit the lower-income states and reduce inequality. However, without the data I can’t be sure or estimate the extent of impact.

Conclusions and Implications

Even with these caveats though, the income share data does show significant geographic inequality between states. Alarmingly, it also shows the situation is getting worse for South Australia and points to a vicious cycle of falling relative incomes leading to shedding population which itself leads to lower incomes shares and a decreasing ability to generate the things that could build/maintain population and income shares.

It is also coincidental but noteworthy that the period studied here is the period since the GST was introduced. That is important because the formula for the distribution of the GST is explicitly designed with an equalisation objective to “provide states with the opportunity to provide their residents with comparable services” (Commonwealth Grants Commission). The formula is based on a complex range of metrics (not income shares) and the distribution has been controversial. Western Australia in particular in recent times has complained of not getting their fair share. However, the data in this post suggests not only an ongoing need to support a redistributive approach to states with weaker income and revenue, but indeed that more needs to be done (within and/or beyond the GST).

The alternative is greater inequality between states driven by some states capturing a greater and greater share of national income and population, leaving the weaker states in their wake.