Agents of Change and the Approximation of Network Outcomes: a Simulation Study

This paper reports results of a simulation designed to evaluate the precision of Neumann approximations of outcomes of networked economic systems. We simulate systems with Erdös-Renyi, Watts-Strogatz, and Barabási-Albert networks. We discuss the conditions under which second-order approximations of economic outcomes generate small errors. We find that in certain economic systems data requirement is significantly reduced if the research goal is to predict economic outcomes of targeted agents (as opposed to outcomes of the entire system). Despite the systems’ complex network structure, our simulations indicate that sampling the targeted group, its connections, and the connections of its connections is sufficient to predict outcomes. As a result, economic policy that targets this specific group should focus on agents in the two-order of distance sample as opposed to the entire network. This sample of agents can be thought of as the group’s agents of change or opinion leaders.