A few observations on inequality

This blogpost started with a graph showing the way that incomes in the United States have become gradually less equitable since the 1980s, up until which time increases in productivity were matched by increases in real median family income. This graph is quite well-known and has been discussed in detail in some Wikipedia articles on inequality in the US.

The reason this graph and its message are so topical is because, of course, it’s outcomes like this that have fuelled the kind of middle-class discontent that led to the election of Donald Trump, who, we are assured, will take steps to further increase income inequality by cutting taxes for the rich.

Inequality is often measured internationally by what’s known as the Gini coefficient, which is an index that functions on a scale where 0 means that everybody has the same income and 1 means that all income is controlled by one individual. The US does quite badly in the OECD ranking using the Gini coefficient, as you can see in the following graph. The US is the country with the fourth-highest Gini coefficient, after Costa Rica, Mexico and Turkey. Australia is further down toward the middle of the pack.

The Gini coefficient for the US is demonstrably worse now than it was in the 1990s. I found figures comparing the US in the mid-1990s, when the Gini coefficient before taxes and transfers was 0.477, with the late-2000s, when it was 0.486. An even bigger difference can be seen if you look at the Gini coefficient after taxes and transfers (0.361 in the mid-1990s compared to 0.378 in the late-2000s). This second index represents income once redistribution has taken effect; “transfers” is used here to indicate things like welfare payments. So, in the US lower-income families are worse off now because they are getting less benefit from wealth redistribution. In other words, fewer taxes for the rich, such as Trump is recommending, is exactly what the US does not need.

Other things have been working to erode average incomes in the US as well, such as competition from workers in lower-wage countries, who cost less to employ.

In Australia, the Gini coefficient before taxes and transfers in the mid-1990s was 0.467, and by the late-2000s it was 0.468. So, it didn’t change much over that 25-year period. However, the Gini coefficient after taxes and transfers in the mid-1990s for Australia was 0.309, and by the late-2000s it was 0.336. This means that income inequality over that 25-year period has favoured the rich while the less-well-off have lost access to redistributed wealth.

Here’s another graph, this time from the Australian Bureau of Statistics (ABS), and it shows real median income over time. It shows that lower-income Australians have done worse than higher-income Australians over time. In this graph, the numbers go up to 2016.

The ABS numbers for wealth tell a similar story, as you can see from the following graph. In this graph, which includes numbers from the early-2000s and compares them to more recent numbers, the wealth of the middle of Australia has grown much less rapidly than the wealth of the wealthy. The wealth of those at the bottom of the chart has remained virtually unchanged over that 13-year period, while the numbers for the middle have increased only slightly.

In France, the Gini coefficient before taxes and transfers in the mid-1990s was 0.473 and by the late-2000s it was 0.483. But the Gini coefficients after taxes and transfers for the same time segments were 0.277 and 0.293, meaning that while lower-paid French people have also done worse over time, they still get a larger slice of the redistributed pie.

The following table shows the Gini coefficient figures used in this blogpost, all in one place. The table shows how redistribution works in a European country to even out inequality. Whereas in France inequality before taxes and transfers is the same, approximately, as it is and has been in the US, once redistribution takes effect there is far less inequality in the economy. It also shows that Australia is coming in at about half-way between the two extremes: between the US on the one hand and France on the other.