Multidimensional scaling (or MDS) is a methodology for producing geometric models of proximities data. Multidimensional scaling has a long history in political science research. However, most applications of MDS are purely descriptive, with no attempt to assess stability or sampling variability in the scaling solution. In this article, we develop a bootstrap resampling strategy for constructing confidence regions in multidimensional scaling solutions. The methodology is illustrated by performing an inferential multidimensional scaling analysis on data from the 2004 American National Election Study (ANES). The bootstrap procedure is very simple, and it is adaptable to a wide variety of MDS models. Our approach enhances the utility of multidimensional scaling as a tool for testing substantive theories while still retaining the flexibility in assumptions, model details, and estimation procedures that make MDS so useful for exploring structure in data.

Segnalazione bibliografica. American Journal of Political Science, Volume 55, Number 4, 1 October 2011 , pp. 907-922(16) Autore: Till Weber Abstract Very few theories of democratic elections can claim to overarch the field. One of them that has not been given due regard, I suggest, is Albert Hirschman's Exit, Voice, and Loyalty. I aim to exploit the integrative capacity of this general framework in a model of typical “midterm“ effects occurring through the electoral cycle. The model unites such diverse phenomena as antigovernment swings, declining turnout, protest voting,...

Segnalazione bibliografica. Autori: Jane Green e Will Jennings British Journal of Political Science 42, 311-343 (April 2012) Abstract There is a discernable mood in macro-level public evaluations of party issue competence. This paper argues that voters use heuristics to transfer issue competence ratings of parties between issues, therefore issue competence ratings move in common. Events, economic shocks and the costs of governing reinforce these shared dynamics. These expectations are analysed using issue competence data in Britain 1950–2008, and using Stimson's dyad ratios algorithm to estimate ‘macro-competence’. Effects on macro-competence are found for events and economic shocks, time in government, leader ratings, economic evaluations and...

Segnalazione bibliografica. National Bureau of Economic Research (2009), working paper n. 15365 Autori: Alan S. Gerber, Gregory A. Huber, Ebonya Washington Abstract Political partisanship is strongly correlated with attitudes and behavior, but it is unclear from this pattern whether partisan identity has a causal effect on political behavior and attitudes. We report the results of a field experiment designed to investigate the causal effect of party identification. Prior to the February 2008 Connecticut presidential primary, researchers sent a mailing to a random sample of unaffiliated registered voters informing them of the need to register in order to participate in the upcoming primary. Comparing post-treatment survey...

Although many studies of clientelism focus exclusively on vote buying, political machines often employ diverse portfolios of strategies. We provide a theoretical framework and formal model to explain how and why machines mix four clientelist strategies during elections: vote buying, turnout buying, abstention buying, and double persuasion. Machines tailor their portfolios to the political preferences and voting costs of the electorate. They also adapt their mix to at least five contextual factors: compulsory voting, ballot secrecy, political salience, machine support, and political polarization. Our analysis yields numerous insights, such as why the introduction of compulsory voting may increase vote buying, and why enhanced ballot secrecy may increase turnout buying and abstention buying. Evidence from various countries is consistent with our predictions and suggests the need for empirical studies to pay closer attention to the ways in which machines combine clientelist strategies.