Selection of the distributional rule as an alternative tool to foster cooperation in a Public Good Game

Abstract

This paper presents an investigation about cooperation in a Public Good Game using an Agent Based Model calibrated on experimental data. Starting from the experiment proposed in Colasante and Russo (2016), we analyze the dynamic of cooperation in a Public Good Game where agents receive an heterogeneous income and choose both the level of contribution and the distribution rule. The starting point is the calibration and the output validation of the model using the experimental results. Once tested the goodness of fit of the Agent Based Model, we run some policy experiment in order to verify how each distribution rule, i.e. equidistribution, proportional to contribution and progressive, affects the level of contribution in the simulated model. We find out that the share of cooperators decreases over time if we exogenously set the equidistribution rule. On the contrary, the share of cooperators converges to 100% if we impose the progressive rule. Finally, the most interesting result refers to the effect of the progressive rule. We observe that, in the case of high inequality, this rule is not able to reduce the heterogeneity of income.

Behavioral Heterogeneity Affects Individual Performances in Experimental and Computational Lowest Unique Integer Games

“…The necessity of combining two approaches have been argued and the methodology has been proposed for the last decade (e.g., [8][9][10][11]). There are a few researches which indeed employ the combined approach to computationally test the validity of experimental findings in the laboratory, implement an intensive computational experiment, and extend the experimental design by using the laboratory data [12][13][14].…”