Punishing a non-cooperator in collective action has consequences not only for the punisher, but also for others, and hence may commonly generate externalities. Individual selection theories have focused on the positive effects of punishment that benefit the punisher individually and propose that the adaptive function of punishment is to optimize relative individual fitness within group. On the other hand, group selection theorists argue that the benefitting effect of punishment on the group relative to other groups was more important for the ancestral punishers. For the past several decades, attempts at resolving the debate over the adaptive function and level of selection of punishment have floundered and we have not yet arrived at a consensus resolution.

The goal of this dissertation is to propose a solid and powerful paradigm for model selection that helps researchers decide between alternative evolutionary models. The evolutionary principal component approach (E-PCA) combines the statistical principal component approach with the multilevel selection perspective in order to evaluate alternative theories of how selection shaped evolved mechanisms. E-PCA transforms the abstract concept of strength of selection into a displacement of a mutation set over time (or temporal variance), something that can be potentially measured. Then, evolutionary psychology provides an inferential framework for estimating the temporal variance by conceptualizing it as the magnitude of design improvement with respect to the optimization problem.

I modified the public goods games (PGG) to test diverging predictions made by E-PCA for the two competing theories of punishment: group versus individual selection theories. The three chapters (chapters 3, 4, and 5) with their empirical projects demonstrate the power of E-PCA as well as provide unambiguous evidence of individual selection being the dominant force shaping the design of the human anti-free rider punishment system. Across all of the projects with PGG and surveys, the punishers' decisions show that the optimization criterion is the individual relative payoff, not the group payoff.

The punishers' decision-making was made in the service of solving the within-group second-order free riding issue, at the expense of group-level optimization and efficiency (chapters 4 and 5). Punishers cared about their relative spending, and tended to reduce their punishment effort compared to those of others; moreover, they were themselves willing to second-order free ride on others (chapters 3 and 5). Punishers also imposed an unnecessary cost on others to prevent them from benefitting from their own sacrifice -- a decision pattern that hurt group-level efficiency (chapter 4). Punishers sent dishonest signals to other members so that more punishment effort would be made by others while privately reducing their own punishment effort (chapter 5). In sum, the empirical evidence for individual selection theory was strong and consistent.