Because the goals of local and national representation are inherently incompatible, there is an uncertain relationship between aggregates of citizen votes and the national allocation of legislative seats in almost all democracies. In particular electoral systems, this uncertainty leads to diverse configurations of electoral responsiveness and partisian bias, two fundamental concepts in empirical democratic theory. This paper unifies virtually all existing multiyear seats-votes models as special cases of a new general model. It also permits the first formalization of, and reliable method for empirically estimating, electoral responsiveness and partisian bias in electoral systems with any number of political parties. I apply this model to data from nine democratic countries, revealing clear patterns in responsiveness and bias across different types of electoral rules.
In this paper we prove theoretically and demonstrate empirically that all existing measures of incumbency advantage in the congressional elections literature are biased or inconsistent. We then provide an unbiased estimator based on a very simple linear regression model. We apply this new method to congressional elections since 1900, providing the first evidence of a positive incumbency advantage in the first half of the century.
We analyze the effects of redistricting as revealed in the votes received by the Democratic and Republican candidates for state legislature. We develop measures of partisan bias and the responsiveness of the composition of the legislature to changes in statewide votes. Our statistical model incorporates a mixed hierarchical Bayesian and non-Bayesian estimation, requiring simulation along the lines of Tanner and Wong (1987). This model provides reliable estimates of partisan bias and responsiveness along with measures of their variabilities from only a single year of electoral data. This allows one to distinguish systematic changes in the underlying electoral system from typical election-to-election variability.
In this paper, we formalize existing normative criteria used to judge presidential selection contests by modeling the translation of citizen votes in primaries and caucuses into delegates to the national party conventions. We use a statistical model that enables us to separate the form of electoral responsiveness in presidential selection systems, as well as the degree of bias toward each of the candidates. We find that (1) the Republican nomination system is more responsive to changes in citizen votes than the Democratic system and (2) non-PR primaries are always more responsive than PR primaries and (3) surprisingly, caucuses are more proportional than even primaries held under PR rules and (4) significant bias in favor of a candidate was a good prediction of the winner of the nomination contest. We also (5) evaluate the claims of Ronald Reagan in 1976 and Jesse Jackson in 1988 that the selection systems were substantially biased against their candidates. We find no evidence to support Reagan’s claim, but substantial evidence that Jackson was correct.
The literature on cabinet duration is split between two apparently irreconcilable positions. The attributes theorists seek to explain cabinet duration as a fixed function of measured explanatory variables, while the events process theorists model cabinet durations as a product of purely stochastic processes. In this paper we build a unified statistical model that combines the insights of these previously distinct approaches. We also generalize this unified model, and all previous models, by including (1) a stochastic component that takes into account the censoring that occurs as a result of governments lasting to the vicinity of the maximum constitutional interelection period, (2) a systematic component that precludes the possibility of negative duration predictions, and (3) a much more objective and parsimonious list of explanatory variables, the explanatory power of which would not be improved by including a list of indicator variables for individual countries.