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 Political Science Review 01 August 2011 105: 586-603 Autori: Kemtaro Fukumoto; Yusaku Horiuchi Abstract Weak electoral registration requirements are commonly thought to encourage electoral participation, but may also promote electoral fraud. As one possibility, candidates and their supporters can more easily mobilize voters who do not reside within the district to register there fraudulently and vote for that district's candidates. We statistically detect this classic type of electoral fraud for the first time, by taking advantage of a natural experimental setting in Japanese municipal elections. We argue that whether or not a municipal election was held in April 2003 can...

The left/right semantic is used widely to describe the patterns of party competition in democratic countries. This article examines the patterns of party policy in Anglo-American and Western European countries on three dimensions of left/right disagreement: wealth redistribution, social morality and immigration. The central questions are whether, and why, parties with left-wing or right-wing positions on the economy systematically adopt left-wing or right-wing positions on immigration and social morality. The central argument is that left/right disagreement is asymmetrical: leftists and rightists derive from different sources, and thus structure in different ways, their opinions about policy. Drawing on evidence from Benoit and Laver’s (2006) survey of experts about the policy positions of political parties, the results of the empirical analysis indicate that party policy on the economic, social and immigration dimensions are bound together by parties on the left, but not by parties on the right. The article concludes with an outline of the potential implications of left/right asymmetry for unified theories of party competition.

The past few years have seen the advent and proliferation of Voting Advice (or Aid) Applications (VAAs), which offer voting advice on the basis of calculating the ideological congruence between citizens and political actors. Although VAA data have often been used to test many empirical questions regarding voting behaviour and political participation, we know little about the approaches used by VAAs to estimate the positions of political parties. This article presents the most common aspects of the VAA approach and examines some methodological issues regarding the phrasing of statements, the format of response scales, the reliability of coding statements into response scales and the reliability and validity of scaling items into dimensions. The article argues that VAAs have a lot of potential but there is also much space for methodological improvements, and therefore concludes with some recommendations for designing VAAs.