G. Rosas, Y. Shomer, S. Haptonstahl, “No News is News: Non-Ignorable Non-Response in Roll-Call Data Analysis”, American Journal of Political Science, 59(2), 2015.
Roll-call votes are widely employed to infer the ideological proclivities of legislators. However, many roll-call matrices are characterized by high levels of non-response. Under many circumstances, non-response cannot be assumed to be ignorable. We examine the consequences of violating the ignorability assumption that underlies current methods of roll-call analysis. We present a basic estimation framework to model non-response and vote choice concurrently, build a model that captures the logic of competing principals that underlies accounts of non-response in many legislatures, and illustrate the payoff of addressing non-ignorable non-response through both simulated and real data. We conclude that modeling presumed patterns of non-ignorable non-response can yield important inferential payoffs over current models that assume random missingness, but we also emphasize that the decision to model non-response should be based on theoretical grounds since one cannot rely on measures of goodness of fit for the purpose of model comparison.