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Explaining party ideological stances

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Abstract

We apply the iterative algorithm by Merrill and Adams (Political Analysis 9:347–361, 2001) to compute the optimal positions of vote-maximizing parties along a one-dimensional space for a large number of elections. This allows us to systematically evaluate factors that push parties toward more centrifugal locations in equilibrium. Our findings largely corroborate expectations suggested by the theoretical literature, albeit with one notable exception: the relative size of a partisan constituency reduces, rather than enhances, the likelihood of a party having an extreme optimal position. We then compare derived equilibrium positions with actual party positions, with the aim of understanding the nature of electoral incentives and offering insights about party-system competition. In particular, we show that the age of a party, the party family to which it belongs, post-election expectations, and internal rules for candidate and leader selection, are all factors that increase the probability of a party approaching the position predicted by pure vote-maximizing considerations.

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Notes

  1. A third approach to investigating party positioning determines the most promising strategy that a party can adopt to improve its vote-share across elections (Budge 1994; Laver and Sergenti 2012).

  2. Assuming that electors employ a proximity criterion when choosing among parties is not the only way to represent electors’ choices in a spatial framework. Possible alternatives include assuming that voters discount parties’ policy positions (Kedar 2002; Merrill and Grofman 1999), that they vote in a directional way (Rabinowitz and Macdonald 1989) and that they anticipate the impact of electoral rules (Calvo and Hellwig 2011).

  3. Parties should converge toward the mean of the distribution of voters assuming a stochastic model, as in our case (Lin et al. 1999).

  4. This assumes no abstention. If abstention is permitted, parties may seek extreme positions to induce extreme, alienated citizens to vote if they are likely to vote for the party (e.g., Chapter 8 in Adams et al. 2005).

  5. Data and documentation can be downloaded from http://www.cses.org.

  6. CL has been criticized for imposing the independence of irrelevant alternatives (IIA) property on voter choice (Alvarez and Nagler 1998). Dow and Endersby (2004) show that for most applications, the IIA assumption is not as restrictive as it might appear at first. We also estimated a generalized extreme value model for each country that relaxes the IIA assumption. Our findings are not affected by this choice.

  7. The Merrill-Adams algorithm always converges to a unique equilibrium for each election survey in the CSES dataset that we analyze. This result is not surprising given that a unique equilibrium typically exists for versions of the voting model depicted in (1) that include a party identification term. See Adams et al. (2005, Appendix 4.1) for a proof of the conditions that guarantee the existence and uniqueness of Nash equilibria for each party k.

  8. Replicating our analysis while employing a multilevel model that explicitly considers the hierarchical structure of our data does not alter any of our findings. The results are available upon request.

  9. The correlation between PARTISAN SHARE and the actual vote share of a party is 0.88. Therefore, larger parties also have larger values of PARTISAN SHARE.

  10. This is no longer true if we assume policy-seeking parties, that is, parties that seek office to implement their desired policies rather than proposing policies to maximize their vote shares. In this case, parties will offer more radical policies as their valence images improve (as long as those parties have non-centrist preferences) because their superior valence images give such parties the electoral leeway to announce policies that reflect their sincere beliefs (Adams and Merrill 2007; Adams et al. 2013).

  11. Interestingly, this value is surprisingly close to the ones observed in Adams et al.’s (2005) simulation analysis.

  12. Indeed, in our dataset, approximately 91 % of the observations have an actual position that is more centrifugal than the corresponding optimal position. This is a common finding in the literature (Adams et al. 2005).

  13. Following Curini and Hino (2012), the variable CABINET HABITS also takes a value of 1 when a minority government was in place in any of the four legislatures preceding the CSES survey.

  14. In Model 6, the socialist party family is used as the omitted category because no data are available regarding the selection procedure of the parties that belong to the communist party family.

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Acknowledgments

An earlier version of this article was presented at the EPSA 2013 Annual General Conference, Barcelona, June 2013. The author acknowledges helpful comments from the seminar’s participants as well from Samuel Merrill III, Stefano M. Iacus, Andrea Ceron, and two anonymous referees. All data to replicate this study are available online at: http://www.socpol.unimi.it/docenti/curini/. This study was supported by the Japan Society for the Promotion of Science Grant S-12123 and the Italian Ministry for Research and Higher Education, Prin 2009–prot. 2009 TPW4NL_002.

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Correspondence to Luigi Curini.

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Curini, L. Explaining party ideological stances. Public Choice 162, 79–96 (2015). https://doi.org/10.1007/s11127-014-0199-6

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