Simulation: Wealth Table
How much greater initial wealth does an agent need to accumulate almost all the wealth after many wealth transfers? All agents begin with equal wealth but you can change the initial wealth of any agent before running the simulation to observe the effect of inheritance. The simulation shows the agent wealth after every timestep.
Simulation: Time Evolution Bias
This simulation plots the wealth of N agents after every timestep. Every agent begins with one wealth unit which corresponds to \$100,000.  Notice that the wealth of each agent initially appears to be a random walk around the initial wealth.  Sometimes an agent gains and sometimes he or she looses.  But over time the their wealth begins to diverge.  This divergence is caused by a subtle time-reversal asymmetry in the trading model.
Simulation: Pareto's Principle
Pareto's principle (or law) is a rule of thumb that states that roughly 80% of the effects come from 20% of the causes. This principle is named after the Italian economist Vilfredo Pareto, who observed in 1906 that 80% of the land in Italy was owned by 20% of the population and that 20% of the pea pods in his garden contained 80% of the peas. This simulation explores if our simulating reproduces Pareto's principle.
Simulation: Power Law Wealth Distribution
Does our model predict the distribution of wealth observed in actual societies? Vilfredo Pareto claimed that the probability P of a person having an income greater than x follows a power law and he believed that the power law coefficient ? has a value of 2.5.  This simulation tests the applicability of both power law and exponential distribution functions to our simple model.