Social network analysis and interpersonal comparisons of utilities in behavioral games

In 1999, Fehr and Schmidt conducted an experimental study on how aversion towards inequity changes payoffs in a game through feelings of envy or guilt. In this study, an Inequity Aversion Utility Function is constructed to show how decision making behaviors of players are affected due to their economic environment and the heterogeneity of preferences. However, these studies are based on costly, time-consuming experiments with inconsistent players with noisy choice behaviors. Thus, I propose the usage of Social Network Analysis metrics to derive coefficients of envy and guilt for Inequity Aversion utility function as an alternative.Social Network Analysis is an alternative to experimental studies because the tool focuses on how the network structure of ties affects individuals' behavior and thus it is a good alternative for deriving preference parameters for studies using Interpersonal Comparison of Utilities. The two methods of Social Network Analysis and Interpersonal Comparison of Utilities are connected by a transformation function that takes a node's attributes in a Social Network and shows the individuals' relative decision making process within an institution. By acquiring proximity and saliency of the individuals from Social Network data and plugging it into a generalizable transformation function, Fehr and Schmidt's envy and guilt coefficients can be derived without conducting experimental studies. After fusing the theories of Interpersonal Comparisons of Utility and SNA, I choose a study on trade and conflict to evaluate my proposition the usage of SNA metrics to derive coefficients of envy and guilt for Inequity Aversion utility function is a valid alternative to experimental studies.The application of my postulated theoretical relationships to the analysis of trade and conflict shows that social network analysis can be a powerful explanatory method for characterizing institutional trading arrangements. This is evidenced by the seven-fold increase in explanatory power of the study of trade and conflict compared to excluding institutional variables. The transformation functions only increases the explanatory power of trade and conflict relationship analysis is also increased by five times demonstrating that it plays an important role.