The basic inequality that plagues economies the world over may have a simple explanation—at least, according to physicists who’ve turned to economics.
Simple explanation aye, this sounds dodgy. Let’s assume that they are talking solely about income inequality, as it looks like the article doesn’t understand the importance of the difference. Let’s see what the “simple explanation” is.
Pick a country, they claim, and you’ll find multitudes of people who earn next to nothing, a few who rake in plenty, and a distribution between the extremes that falls exponentially as income increases (see figure). That distribution applies to all but the very rich, they say, and it arises from an analogy to the concept of entropy, a measure of disorder in a physical system such as a gas. Just as a gas evolves to a state of maximum entropy, they argue, random churning in the economy ensures that the income distribution naturally tends to this inequitable form.
The reasoning is “not very close to the thinking of economists, but it’s pretty persuasive,” says Thomas Lux, an economist at the University of Kiel in Germany. But Frank Cowell of the London School of Economics and Political Science says “I’m extremely skeptical” that the argument provides any insight into the economy.
Two things that make me furious with Thomas Lux here are:
- This isn’t an explanation as there is no mechanism involving the people involved – it is a description. These have value, but the two are very different, and descriptions are not policy relevant until we have a mechanism. Update: Good comment by Kiwi poll guy here regarding my first point being wrong – if described as inequality occurring due to luck it is an explanation. However, it is A explanation not THE explanation.
- FFS READ THE LITERATURE. Especially if you are going to say economists haven’t thought of this.
On the second point, the original (read first half of the 20th century) view of looking at income distributions was through a power law (Pareto distribution) and a log-normal distribution. When it came to looking at inequality indices, one of the key indices used was the generalised entropy family, specifically the Theil index and log mean deviation. The later two were the only distributions that met all the “axioms” economists put together for rating a distribution.
In modern times parametric forms have been studied to death, but with data increasingly bimodal (and these forms unimodal) there has been a strong push towards non-parametric analysis (without functional form, just using the microdata). Teasing these things out is difficult, and any introductory book would have given these points – hell even read Cowell’s notes on measuring inequality here. If you read Italian, just go back and read the Pareto and Gini papers from the late 19th and early 20th century and you will see a discipline that knows the points that are being raised (about the distribution being exponential, entropy measures came in the 1960s 😉 ) and was trying to tackled with “value judgments” and “mechanisms”.
The “natural tendency” that can exist for the dispersion of income is something that is a centerpiece of economic analysis – instead of saying the dispersion happens though, we try to work out, and test, different mechanisms. Hence this post by Shaz and Piketty’s text both talking about “natural” movements in income – pro-tip, what this “natural” is due to is an important element of whether leaning against it, or with it, is a good thing, and whether it is policy relevant.
If anyone thinks this is just “nit picking” and doesn’t indicate that the article is practically useless, then you don’t understand the basics of economics and policy making – that sounds strong, but it is so far away from being useful for policy or adding to knowledge that I’m comfortable saying it. Note that I know practically nothing about physics.
That is cool, the article should be informing you of those things – but as it is written by someone with no understanding of these basic points they can’t inform you. The article says virtually nothing and insults economists (directly) showing a complete lack of engagement with the literature that economists get to read in an undergraduate policy economics course.
If you want to look at economic data and say things, that is cool, do so physicists – I actually hold hope that you dudes and dudettes will add heaps to our understanding. But before saying “look at this 100 level result, economists haven’t thought of it and are morons” actually read what economists have f’ing said in the past. Arrogant sons of guns – I am utterly furious, and this was defacto published by the AAAS as it is their mag. FFS!