We contribute to the long-running debate over aggregate turnout's effect on the representation of socially marginalized groups, examining the particular case of descriptive representation of racial minorities on city councils. We replicate and reanalyze Hajnal and Trounstine (2005), introducing an expanded data set on city council representation and a new statistical model designed to address serious problems that appear when estimating how groups partition seats in legislative bodies, especially when one or more groups fail to win seats. With a more appropriate statistical procedure and more accurate turnout data, the measurable effect of turnout has no substantive significance. The methods we propose should be of use in a broad range of applications, but particularly in the study of groups competing for seats in legislative bodies.
Deadlines are ubiquitous institutions in government decision making, constraining both agencies and courts. Yet these institutions are almost entirely ignored in formal models in instituional political science. We analyze deadlines as exogenously imposed instiutions upon a government decision maker, in a model of repeated optimal stopping of a complex stochastic process. Analysis of the model shows that deadlines almost always reduce expected decision-making times but can also increase the variability of decision times under plausible circumstances. Further, imposition of deadlines can generate decision error, such that a government agent will wrongly make an irreversible decision more often in the presence of a deadline, and the deadline induced error may be extremely hard to predict ahead of time. The error induced by deadlines is similar to that induced by (false) optimism. Our dynamic stochastic model incorporates a broader and richer information environment than does previous work, and it helps to explain several observed empirical phenomenon in government decision making and regulation.