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The Gini Inequality Flaw

By Craig Wright | 12 Aug 2019 | Economics

I have the Gini index touted as a constant error in the statements that I make that the US is not an unfair society. It is better to aim for a society where people eat than to strive for one where all individuals are equally poor and destitute.

The Gini index is one of the most flawed statistical lies used in the pursuit of socialism as a goal. It makes so many false assumptions — it is not funny. It does not class people by age and gender, and does not account for differences in the distribution of age over time.

It does not measure actual wealth, and confuses income and wealth.

It compares what it calls a measure of wealth (falsely) in different classes of populations.

To expound further, the Gini index is not as you tout a measure of inequality, but one of income distribution without regard to age and other factors. It fails as a measure of inequality for many reasons, mainly as it does not measure wealth. Inequality is a measure of having more wealth at a point in one’s life than another over a generalised population.

A person the age of 20 cannot be compared directly with another the age of 50. The same person at the age of 20 does not have the wealth and resources of the other at the age of 50 as one tends to accumulate wealth as one ages (being that one starts with little and it accumulates over time).

The wealth distributions of males — being that the decision to exit the workforce or not is in itself a determining factor for wealth, and also many Third World countries do not have large working populations of females with independent incomes — at the age of 45 would be a far superior measure of inequality than the Gini coefficient as it is used, yet which, of course, also has its problems (though there are far fewer issues here than with the Gini coefficient).

The age distributions in Third World and socialist countries (commonly the same, though not always) are far flatter than in the Western “capitalist” (nominally) countries. In other words, a worker in, say, Kenya will see little increment in her earned income from the age of 20 to the age of 50. The distribution of her income over her lifetime remains relatively static.

In contrast, the income and earning capacity of a worker in the US, even an unskilled one, will change significantly during her career.

A worker in the US earns little when being a student. The rate increases as she gains in experience and increases in productivity. The earning capacity generally peaks around the age of 45–55, and then starts to decline, until it finally returns to a low amount for most people in retirement when savings are used to supplement their income. A worker in the US commonly earns 4–5 times the starting wage at some point in her career.

Many socialist societies have no age-based income differentials, and the earning capacity is based more on class, rank, and party affiliations/positions — a truly unequal system.

As the Gini coefficient does not account for age- and sex-based differences in its calculation, it fails even as a true measure of income variance. That is, it fails without even looking at the fact that income inequality is not a measure of inequality in itself in any event.

We start in Western countries earning less, moving into higher-wage brackets, before falling to near nothing again. If you take a measure of the “inequality” rank to age and sex classifications, you find an R² of over 0.90 or a correlation to age and NOT inequality using the Gini coefficient.

Now, taking into account that First World countries generally have people living longer than ones in Third World countries, we start to see that there is an inherent bias in the Gini index, in addition to the afore-noted errors. In countries where people have a longer period of retirement, the Gini presents a situation where a country is classed as “unequal” for simply having people who live on their accumulated wealth.

Then, the socialist ideal here is not to actually analyse data, but to blindly accept the dogma as blinded sheep.