e propose a comprehensive statistical model for analyzing multiparty, district-level elections. This model, which provides a tool for comparative politics research analogous to that which regression analysis provides in the American two-party context, can be used to explain or predict how geographic distributions of electoral results depend upon economic conditions, neighborhood ethnic compositions, campaign spending, and other features of the election campaign or aggregate areas. We also provide new graphical representations for data exploration, model evaluation, and substantive interpretation. We illustrate the use of this model by attempting to resolve a controversy over the size of and trend in the electoral advantage of incumbency in Britain. Contraiy to previous analyses, all based on measures now known to be biased, we demonstrate that the advantage is small but meaningfkl, varies substantially across the parties, and is not growing. Finally, we show how to estimate the party from which each party's advantage is predominantly drawn. w e propose the first internally consistent statistical model for analyzing multiparty, districtlevel aggregate election data. Our model can

This paper develops an approach to studying how bias in favor of one party due to the pattern of electoral districting affects policy choice. We tie a commonly used measure of electoral bias to the theory of party competition and show how this affects party strategy in theory. The usefulness of the approach is illustrated using data on local government in England. The results suggest that reducing electoral bias leads parties to moderate their policies.

We examine whether and when voters in American states hold elected officials accountable for the results of fiscal policy decisions. Clear fiscal policy effects appear in both gubernatorial and legislative elections between 1968 and 1992, independent of the effects of incumbency, coattails, term limits, and macroeconomic conditions. The results show that voters expect Democrats to provide higher levels of taxes and spending relative to state economies. Net of these expectations, Republican gubernatorial candidates lose votes if their party is responsible for unanticipated increases in the size of the state budget, but Democrats do not, and indeed may be rewarded for small increases. Independent of this, the incumbent party is punished for failing to maintain fiscal balance, and accountability is generally stronger following a period of unified party control than under divided government. Taken together, these results show how electoral accountability for fiscal policy outcomes is strong but highly contingent on a complex configuration of party labels, partisan control, expectations, and institutions. Despite the attention given to "big government " and budget deficits during recent political campaigns, the connection between fiscal policy outcomes and election results in the American states

The rich array of institutional diversity makes the United States an excellent testing ground for studying the relationship between political institutions and public policy outcomes. This essay has three main aims. First, it reviews existing empirical evidence on the relationship between institutional rules, political representation and policy outcomes. It aims to place the literature into a broader context of theoretical and empirical work in the field of political economy.

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Randomized experiments have become increasingly important for political scientists and campaign professionals. With few exceptions, these experiments have addressed the overall causal effect of an intervention across the entire population, known as the average treatment effect (ATE). A much broader set of questions can often be addressed by allowing for heterogeneous treatment effects. We discuss methods for estimating such effects developed in other disciplines and introduce key concepts, especially the conditional average treatment effect (CATE), to the analysis of randomized experiments in political science. We expand on this literature by proposing an application of generalized additive models (GAMs) to estimate non-linear heterogeneous treatment effects. We demonstrate the practical importance of these techniques by re-analyzing a major experimental study on voter mobilization and social pressure and a recent randomized experiment on voter registration and text messaging from the 2008 US election. 1

Competition in U.S. House elections has been declining for more than 50 years and, based on both incumbent reelection rates and the percentage of close races, the 2002 and 2004 House elections were the least competitive of the postwar era. This article tests three hypotheses that attempt to explain declining competition in House elections: the redistricting hypothesis, the partisan polarization hypothesis, and the incumbency hypothesis. We find strong support for both the partisan polarization hypothesis and the incumbency hypothesis but no support for the redistricting hypothesis. Since the 1970s there has been a substantial increase in the number of House districts that are safe for one party and a substantial decrease in the number of marginal districts. However, this shift has not been caused by redistricting but by demographic change and ideological realignment within the electorate. Moreover, even in the remaining marginal districts most challengers lack the financial resources needed to wage competitive campaigns. The increasing correlation among district partisanship, incumbency, and campaign spending means that the effects of these three variables tend to reinforce each other to a greater extent than in the past. The result is a pattern of reinforcing advantages that leads to extraordinarily uncompetitive elections. The 2004 House elections may have been the least competitive in American history. They were certainly the least competitive of the

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The quality of government is often measured by the degree of congruence between policy choices and public opinion, but there is not an accepted method for calculating congruence. This paper offers a new approach to measuring policy-opinion congruence, and uses it to study 10 high-profile issues across the 50 states. For the issues examined, states chose the policy preferred by a majority of citizens (equivalent to the median voter outcome) 59 percent of the time — only 9 percent more than would have happened with random policymaking. Majoritarian/median outcomes were 18–19 percent more likely when direct democracy was available, and 11–13 percent more likely when judges were required to stand for reelection. The likelihood of a majoritarian/median outcome was not correlated with a variety of election laws, including campaign contribution limits, public funding of campaigns, and commission-based redistricting. In a democracy, citizen preferences are supposed to play an important role in public policy decisions. Indeed, as Erikson et al. (1993, p. 1) note, “we often gauge the quality of government by the responsiveness of public policymaking to the preferences of the mass public, ” and scholars and activists continue to search for institutions that will enhance responsiveness. The Downsian model (Downs, 1957) shows that competition between

We develop and analyze a model of strategic redistricting. Two parties choose optimal redistricting plans for their respective territory. Parties redistrict before aggregate uncer-tainty is resolved. We show that in the unique equilibrium, parties maximally segregate their opponent’s supporters but pool their own supporters into uniform districts. We show that the stronger a party gets, the more it segregates. Hence, of the two competing par-ties, ceteris paribus, the stronger party segregates more than the weaker one. Finally, we show that if the district level uncertainty is sufficiently small, the stronger party chooses polarizing policies while the weaker party accommodates the stronger party’s supporters. † We thank Thomas Eisenbach, Thomas Palfrey and Andrea Prat for helpful comments on earlier drafts of this paper. This research was supported by grants from the National Science Foundation. 1.