Trying to develop a simple math model for the most recent events in western democracies I took some findings in neurosciences (e.g. psychology of moral) as a set of statistical links between variables. Specifically, there is a book “The Righteous Mind: Why Good People are Divided by Politics and Religion” (2012) written by J. Haidt, which stresses the importance of fairness for both conservative and liberal minds (in sense of moral prejudice). All people have own understanding of fairness, having some core values, however. It was also found that people cooperate much better when unfairness in cooperation is punished. When free-riders pay for the absence of fair behavior for other participants (it is not the absence of fairness for the free riders but rather fair-not-ness for the others). The whole ensemble of current fairness/unfairness judgements in the entire population defines net morality in the society. Majority is always around the net value. However, extreme deviations from this net value can be large and such people are most interested in shifting the equilibrium to their side (e.g., preachers, hippie, priests, criminals, etc.). They all proved to be able to influence individuals and groups shifting moral norms, including the understanding of personal and universal fairness. These are examples of inherent moral influence because such preachers do believe in their versions of fairness.
Another category of people trying to change the net value of moral judgements at large and using the outcome of such shifting is politicians. One can look at the map of the most recent elections in Austria or in the USA, or any other western country, and observe the distribution of moral predominance in big cities and the rest. It looks like that the whole territory is covered by the same color. And this is usually not the color of the winning party (except the USA). This is great division between conservative and liberal moral, both are intrinsic to people (at least, it is my interpretation of the Haidt’s book). For us, the most important is that this division is dynamic and subject to influence of propaganda (in Bernays terms). We suggest that such influence and dynamics are not random and can be described by simple mathematical model based on laws stationary evolution of an ensemble under endogenous and exogenous forces.
Now, we get back to free riders. One part of population considers another part as free riders on average in terms that they obtain more than deserved in a not fair way. The outcome is simple – the absence of cooperation with the other part and cooperation enhancement within the same moral norms group. The division has been growing with time together with the growth in economic (and likely social) inequality. Trump got it (as well as right-wing politicians in Europe) first and sent to the conservative part of population a message that unfairness will be punished (make the US great again!) This is direct message which actually make two major effects – increasing cooperation in both liberal and conservative cores of population and increasing deviations of the average conservative and liberal understanding of fairness from the net value.
We develop a math model of moral evolution, which includes the intrinsic (basic) and current distribution of fairness understanding, the dynamic development under endogenous (and likely exogenous in satellite countries of Western Europe) forces depending on the evolution of economic (income) inequality observed during the past 30 to 50 years. The latter is described by the evolution of Gini ratio, the share of labor in GDP (GDI) and the mean personal income. The sensitivity of a person to external influence is also distributed over the population and depends on the intensity of external influence. In other words, increasing economic inequality made many people to feel unfairness and become more sensitive to external propaganda which, in turn, makes people more sensitive on average.