Epstein Secrets

rom top to bottom. But this still results in a distribution with a large bias giving most of the wealth to a minority of individuals. Going back to the Lotka-Volterra and GLV models discussed in section 1.2, it is better to abandon the predator-prey model of foxes killing rabbits, and instead think in terms of a '

he details of income and wealth distributions have rarely been studied in mainstream theoretical economics, a notable and important exception being Champernowne. Champernowne was a highly gifted mathematician who was diverted into economics, he was the first person to bring a statistical mechanical approach

this is a chaotic model, not a stochastic one. There is no stochasticity in this model. All fluctuations in the model are created endogenously from the Lotka-Volterra like differential equations in the model. Figure 4.3.4 shows the detail of couple of cycles. Figure 4.3.4 here These are real live Minskian / Aus

ater in economics, this area has attracted physicists and statistical mathematicians and engineers in significant numbers since at least the work of Champernowne. The reason is simple; to a statistical physicist, economics is obviously a multi-body phenomenon. It is messy. There are millions of agents in a t

al and ecological scientists have the right mathematical tools for creating a radical and effective new economics, both specifically in the form of the Lotka-Volterra and maximum entropy production models, and more generally in their understanding of complex inter-related evolving systems. Ultimately this maths f

lots of boundary conditions, may be simple enough to be tractable to a traditional statistical mechanical analysis on the lines of Dewar, or indeed Champernowne. Before moving into further discussion I would first like to follow the maths through a little more. I would like to do two things. Firstly I would