Saliency theory is among the most influential accounts of party competition, not least in providing the theoretical framework for the Comparative Manifesto Project – one of the most widely used data collections in comparative politics. Despite its prominence, not all empirical implications of the saliency theory of party competition have yet been systematically tested. This article addresses five predictions of saliency theory, the central claim of which is that parties compete by selective issue emphasis rather than by direct confrontation. Since a fair test of the theory's assumptions needs to rely on data that measures party issue saliency and party positions independently, this article draws on new manifesto data from the Austrian National Election Study (AUTNES). Analysing all manifestos issued for the 2002, 2006 and 2008 general elections, it shows that saliency theory correctly identifies some features of party competition. For instance, parties disproportionally emphasise issues they ‘own’. Yet, the core assumption of saliency theory that parties compete via selective issue emphasis rather than direct confrontation over the same issues fails to materialise in the majority of cases.

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.

CHIARAMONTE, A. C. A. (2012). Recensione del volume: D. Giannetti & B. Grofman (eds), A natural experiment on electoral law reform. Evaluating the long-run consequences of 1990’s electoral reform in Italy and in Japan, New York, Springer, 2011. R...

This article analyses the impact of party systems on human well-being and argues that multiparty systems are associated with better welfare outcomes for two primary reasons: first, multiparty systems provide representation to multiple issue-dimensions in society, thereby indicating a more inclusive system, which ensures that diverse societal interests are taken into account during formulation of welfare policies. Second, multiparty systems also indicate a competitive party system, which provides incentives for parties to perform effectively while in office and propels parties to appeal to multiple segments of society by providing broader welfare services. The impact of party systems on human well-being is tested on a global sample of 68 democratic countries from 1975–2000. The findings show support for the hypothesized relationship between party systems and human well-being.