The study of international relations (IR), and political science more broadly, has derived great benefits from the recent growth of conceptualizing and modeling political phenomena within their broader network contexts. More than just a novel approach to evaluating old puzzles, network analysis provides a whole new way of theoretical thinking. Challenging the traditional dyad-driven approach to the study of IR, networks highlight actor interdependence that goes beyond dyads and emphasizes that many traditional IR variables, such as conflict, trade, alliances, or international organization memberships must be treated and studied as networks. Properties of these networks (e.g., polarization, density), and of actor positions within them (e.g., similarity, centrality), will then reveal important insights about international events. Network analysis, however, is not yet fully adapted to account for important methodological issues common to IR research, specifically the issue of endogeneity or possible nonindependence between actors’ position within international networks and the outcomes of interest: for example, alliance network may be nonindependent from the conflict or trade network. We adopt an instrumental variable approach to explore and address the issue of endogeneity in network context. We illustrate the issue and the advantages of our approach with Monte Carlo analysis, as well as with several empirical examples from IR literature.