A classic example is in his highly cited paper, with the same title as this post. Make some simple assumptions: Money is a conserved quantity, and the rates of transactions don't depend on the financial direction of the transactions. Take those assumptions, start with everyone having the same amount of money, and allow randomized transactions between pairs of people. The long-time result is an exponential (Boltzmann-like) distribution of wealth - the probability of having a certain amount of money \(m\) is proportional to \(\exp(-m/\langle m \rangle)\), where \(\langle m \rangle \) is the average wealth, a monetary "temperature". The take-away: complete equality is unstable just because of entropy, the number of possible transactions.

Apparently similar arguments can be applied to

*income*, because it would appear that you can describe the distribution of incomes in many countries as an exponential distribution (more than 90% of the population). Basically, for a big part of the population, it seems like income distribution is dominated by these transactional dynamics, while the income distribution for the top 3-ish% of the population follows a power-law distribution, likely because that income comes from returns on investments rather than wages. The universality is quite striking, largely independent of governmental policies on managing the economy.
Yakovenko would be the first to say not to over-interpret these results, but the power of statistical arguments familiar from physics is impressive. Now all we have to do is figure out the statistical mechanics of people....