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The electoral personalization of Italian mayors. A study of 25 years of direct election

Published online by Cambridge University Press:  06 January 2020

Anna Carola Freschi
Affiliation:
Department of Social, Political and Cognitive Sciences, University of Siena, Siena, Italy
Vittorio Mete*
Affiliation:
Department of Political and Social Sciences, University of Florence, Florence, Italy
*
*Corresponding author. Email: vittorio.mete@unifi.it

Abstract

This paper presents an analysis of the personalization of the vote in Italian municipal elections in the period 1993–2017. Considering the ability of mayoral candidates to attract more votes than those of the lists that support them, the paper outlines the socio-demographic and political characteristics of the candidates who receive the most personalized votes. Contrary to what one might expect, the most personalized candidates are the losing candidates, not the winning ones. At the same time, the candidates who present themselves as outsiders are more personalized: women; candidates at the head of civic lists; those who lead coalitions positioned at the extremes of the left/right axis; candidates supported by one or two lists. Thus, the paper shows the propensity of the Italian electorate to use the split vote to reward those candidates who present themselves as challengers, rather than the established ones, also in the more pragmatic context of local government elections. Moreover, while it is true that personalization is increasingly more important in the political and electoral context, the ability to create lists of candidates for municipal elections capable of obtaining the broad support of voters seems to count as much, if not more.

Information

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
Copyright © Società Italiana di Scienza Politica 2020
Figure 0

Figure 1. Personalization indexed by gender and geopolitical area (N = 19,219).

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Figure 2. Personalization index of individuals who were elected and not elected over time (N = 19,219).

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Figure 3. Personalization index of individuals who were elected and not elected by geopolitical area (N = 19,219).

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Figure 4. Personalization index of incumbent and not incumbent mayors by geopolitical area (N = 3649).

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Figure 5. Personalization index by candidates' political colours (N = 19,219).

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Figure 6. Personalization index by number of lists supporting the candidate (N = 19,219).

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Table 1. Linear regression of the personalization index with respect to socio-demographic and political covariates

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Table A1. Descriptive statistics for categorical variables in the regression models

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Table A2. Descriptive statistics for continuous variables in the regression models

Supplementary material: Link

Freschi and Mete Dataset

Link