Using Monte Carlo Methods to Extend Network Exchange Theory and Research.

Monte Carlo simulations can be an efficient way to obtain accurate answers for computationally expensive problems. In the field of network exchange theory, finding the probability that an actor is included in an economic exchange is one such problem. An exchange occurs when two connected actors reach agreement to exchange valued goods. The negotiations determine how much each should profit. Research has shown that there is a positive correlation between an actor?s probability of being included and that actor?s profits from exchange. Since the probability of inclusion is a function of the actions of all actors in the network, precise methods to compute a rate of inclusion are computationally expensive for large numbers of connected actors. In this paper, we address this issue by constructing Monte Carlo methods for two existing methods of computing inclusion rates in exchange networks. [ABSTRACT FROM AUTHOR]