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Witch Hunts? Electoral Cycles and Corruption Lawsuits in Argentina

Published online by Cambridge University Press:  08 November 2023

Germán Feierherd
Affiliation:
Universidad de San Andrés, Buenos Aires, Argentina
Ezequiel Gonzalez-Ocantos
Affiliation:
University of Oxford, Oxford, United Kingdom
Guadalupe Tuñón*
Affiliation:
Princeton University, Princeton, New Jersey, United States
*
Corresponding author: Guadalupe Tuñón; Email: guadalupe.tunon@gmail.com
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Abstract

Courts prosecuting corruption serve a critical horizontal accountability function, but they can also play a role in moments of vertical accountability when voters can sanction corrupt candidates. This article documents the strategic use of corruption lawsuits, demonstrating the presence of an electoral cycle in filing new corruption accusations against politicians. Using an original dataset of daily corruption complaints filed in federal courts against members of Argentina's main political coalitions between 2013 and 2021, we document increased corruption accusations against and by politicians in the periods immediately preceding an election. A second dataset of daily media coverage of corruption accusations in two leading newspapers suggests that corruption is more salient before elections, offering politicians a temporal focal point to prepare and launch especially impactful lawsuits. Our findings shed new light on using courts for accountability and debates about the so-called ‘lawfare’ in Latin America.

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Type
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, provided the original article is properly cited.
Copyright
Copyright © The Author(s), 2023. Published by Cambridge University Press
Figure 0

Table 1. Distribution of cases against Kirchnerist and Macrist networks

Figure 1

Figure 1. Crimes under investigation.Note: cases may include none (Not specified) or multiple crimes under investigation. See Appendix B for the full table.

Figure 2

Table 2. Summary statistics by network, incumbency, and status

Figure 3

Figure 2. Difference in the number of days with a corruption lawsuit before and after the nearest election Panel (a) Panel (b).Note: Outcome variables are dummy variables for whether at least one case was filed on that day for each category. Point estimates come from separate regressions for varying windows, as described in Equation 1. The top x-axis indicates the number of observations for each regression. Bars represent robust 95 per cent confidence intervals. Panel (a) examines cases in which politicians are the defendants; panel (b) examines cases in which politicians are the accusers.

Figure 4

Table 3. Local-linear estimates

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Figure 3. Placebo tests.Note: estimates come from local-linear regressions. Bars represent ‘robust’ 95 per cent confidence intervals as developed by Calonico, Cattaneo, and Titiunik (2014).

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Figure 4. Corruption news coverage before and after elections (Clarín and Página 12).Note: Point estimates come from separate regressions for varying windows, as described in Equation 1. Bars represent robust 95 per cent confidence intervals.

Figure 7

Table 4. Local-linear estimates: corruption keywords

Supplementary material: File

Feierherd et al. supplementary material

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