A new approach to age and risk taking behavior of agents

Abstract

In this thesis, we use evolutionary game theory techniques to analyze the relation between risk taking behavior of agents and their ages. We suppose that risk aversion is the stable pattern for the old agents and risk seeking is the stable pattern for the young agents as it is commonly assumed so in economics literature. First, we solve a benchmark model without heterogeneity in terms of age di§erentiations. In such a case, we observe that mutation either increases or decreases with respect to the payo§ levels, depending on the initial Ötness levels of the population groups. In the second step, we introduce heterogeneous population frontier. The anticipated level of the initial mutant proportion provides incentives to triger the evolution. Then, we analyze numerically the e§ects of the initial level of Ötness, initial risk averse and risk seeking proportions on the pattern of the evolution process. Finally, we studied the intertemporal e§ects of di§erent risk averse and risk seeking population proportions on mutation.