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Political corruption and voting in Romanian municipal elections: Why perceptions of collective action matter

Published online by Cambridge University Press:  10 November 2025

Nicholas Charron*
Affiliation:
Dept. of Political Science and QoG Institute, University of Gothenburg, Gothenburg, Sweden
Andreas Bågenholm
Affiliation:
Dept. of Political Science and QoG Institute, University of Gothenburg, Gothenburg, Sweden
*
Corresponding author: Nicholas Charron; Email: nicholas.charron@pol.gu.se
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Abstract

In recent years, scholars have investigated the ‘corruption voting puzzle’, ie why, despite an overwhelming distaste for corruption, voters often collectively fail to ‘throw the rascals out’. While previous literature has largely investigated why voters support corrupt incumbents, our focus lies on nonvoters. Using an original two-wave panel data with Romanian voters just prior to and after the 2020 municipal elections, we test three hypotheses. First, that there is a discrepancy between voters’ intentions and their actual voting behavior (e.g. ‘norms versus actions’). Second, that those most pessimistic about other voters’ intentions to come out to the polls to vote out corrupt incumbents are most likely to abstain. Finally, building on the collective action literature, whether providing such pessimistic voters with information about the intentions of other voters will decrease abstention and increase opposition voting. Using original observational and experimental data, we demonstrate empirical support for our three hypotheses.

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 (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2025. Published by Cambridge University Press on behalf of European Consortium for Political Research
Figure 0

Table 1. Summary of data collection and design

Figure 1

Table 2. Treatment effects of corruption on vote choice from conjoint experiment

Figure 2

Table 3. Predicting incumbent voting in the 2020 election: logit estimates

Figure 3

Table 4. Comparing electoral outcomes in municipalities with and without an indicted mayor

Figure 4

Table 5. Attitudes of others’ behavior and abstention

Figure 5

Figure 1. Conditional treatment effects of information on others’ attitudes toward political corruption. Note: Treatment effects show by group – those who believe others will act (‘optimists’) and those who do not (‘pessimists’). Estimates from multinomial logit model. Control variables include gender, age, education, political interest, unemployment, awareness of corruption charges, political trust, economic satisfaction, urban municipality, and whether one’s municipality had a mayor charged with corruption. Survey weights used, and standard errors are clustered by municipality, with 95% confidence reported. Sample size is 2333. Full results are found in model 2, Table A5 in the Appendix.

Figure 6

Table 6. Comparison of treatment effects in both groups for non−incumbent support outcomes

Supplementary material: File

Charron and Bågenholm supplementary material

Charron and Bågenholm supplementary material
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