Many political and socio-economic binary outcomes are the result of multi-actor interaction: states joining a given international institution (e.g., military alliance, economic block) and not its rivals, people entering the workforce as an employee of a specific firm and not of its competitors, etc. Yet, most empirical studies analyze multilateral phenomena as the (joint) binary choice of either a single or, at most, two decision-makers. This is due in part to a lack of empirical estimators that can efficiently deal with multi-actor interaction. Analyzing multilateral processes as a set of either monadic or dyadic events, though, introduces bias, and has important consequences for the estimates and ultimately the inferences that one would draw. In this paper, I develop a new empirical estimator that is specifically designed to analyze multiparty interactions. Specifically, the model can accommodate the input of multiple actors into a unified, overarching decision making process. Results from a Monte Carlo analysis and an application to real data on alliance formation demonstrate the superior performance of the new estimator relative to the standard approach
