Pareto-optimality in linear public goods games

Abstract

We derive a generalized method for calculating the total number of Paretooptimal allocations (NOPA) in typical linear public goods games. Among other things, the method allows researchers to develop new experimental designs for testing the relevance of Pareto-optimality in experimental settings, for investigating alternative causes of the decline of voluntary contributions, or for analyzing the contribution behavior of the rich and poor in heterogeneous income settings. Further findings include that the NOPA is related to the marginal per capita return (MPCR) of a contribution to the public good and that the maximum number of free-riders tolerated by the Paretooptimality concept is independent from the group size and income distribution. Finally, we apply our findings to a number of published linear public goods games, suggest an agenda for future research and provide a MATLAB code.