Electoral Fraud, Voter Turnout, and Perceived Legitimacy

Last registered on October 28, 2024
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Pre-Trial

Trial Information

General Information

Title
Electoral Fraud, Voter Turnout, and Perceived Legitimacy
RCT ID
AEARCTR-0013916
Initial registration date
October 25, 2024

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
October 28, 2024, 1:19 PM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

Country
Russian Federation
Region

Primary Investigator

Name
Anastasiia Arbuzova
Affiliation
Boston University
Contact Primary Investigator

Other Primary Investigator(s)

Additional Trial Information

Status
Completed
Start date
2024-06-30
End date
2024-09-30
Keywords
Electoral
Additional Keywords
autocracy, legitimacy, electoral fraud, voter turnout
JEL code(s)
C93, D72, P00
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
The use of electoral fraud as a tool for securing victory in elections is well-documented. However, its use for purposes that go beyond winning an election remains relatively understudied. Particularly puzzling is its prevalence in the context of elections in non-democracies, where electoral results are often manipulated despite the incumbent's guaranteed success. Why do autocratic leaders engage in fraud when victory is assured? In this project, I study improving perceived legitimacy as one of the reasons for engaging in fraud. I examine the following mechanism: if turnout influences the population's perception of the autocrat's legitimacy, then he might want to employ fraud to achieve a desired turnout value. I will call this the legitimacy hypothesis. First, by leveraging data from the 2016-2021 Russian parliamentary elections, I confirm the presence of electoral fraud. I focus on manipulations of turnout values and perform several statistical tests to detect those, including last digit distribution and the excess integer values test. After gathering suggestive evidence of the use of fraud to influence turnout, I proceed with testing whether knowledge of turnout actually affects perceived legitimacy. To answer this question, I propose undertaking a survey with a representative sample of the Russian voter population. The key component of the survey will involve a randomized information intervention where treated respondents receive information about outcomes of a hypothetical election. Subsequently, their evaluation of legitimacy will be measured.
External Link(s)

Registration Citation

Citation
Arbuzova, Anastasiia. 2024. "Electoral Fraud, Voter Turnout, and Perceived Legitimacy." AEA RCT Registry. October 28. https://doi.org/10.1257/rct.13916-1.0
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Experimental Details

Interventions

Intervention(s)
Each respondent will be randomly assigned to one of five treatment arms: Control (C), Turnout Low (TL), Turnout High (TH), Turnout Low + Result (RL), and Turnout High + Result (RH). Respondents in the Control group (C) will not be provided with any information about elections. Respondents in the Turnout groups (TL, TH) will be provided with information about the turnout, either Low or High. Respondents in the Turnout + Result groups (RL, RH) will be provided with information about the turnout, either Low or High, and leading party vote share.
Intervention (Hidden)
Intervention Start Date
2024-07-02
Intervention End Date
2024-07-16

Primary Outcomes

Primary Outcomes (end points)
Trust in government, approval and willingness to abide by hypothetical laws respondents do not personally approve of.
Primary Outcomes (explanation)
To understand, which components comprise government's legitimate mandate, means to find answer to the question what gives the governor the right to govern. Several aspects have been highlighted in the literature: acceptance of authority, perception of the government's representation of their interests, and policy approval. If people do not perceive the government as legitimate, they are less likely to obey laws or decisions and may protest. Conversely, if people trust that the government is doing a good job, they are less likely to oppose even personally disliked reforms.

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
1,600 participants will be enrolled to ensure a representative sample of Russian voters. Participants must satisfy two inclusion criteria: (1) adults (over 18 years old); (2) Russian citizens with voting rights. In addition, quotas on federal district, city size, gender, and age cohort, will be implemented to insure that the sample is nationally representative.
The survey questionnaire consisted of three sections and should take approximately 10 minutes to complete. The first section will address socio-demographic characteristics. The second section will include questions on various forms of political participation, such as signing petitions and voting. At the end of this section, respondents will be asked about their participation in the 2021 Federal Duma elections and whether they recalled the results at both the national (proportional system) and constituency (majoritarian system) levels. To elicit actual political preferences, respondents will be presented with a scenario in which elections were scheduled to occur the following day and asked about their willingness to participate and, if yes, which party would they vote for. Subsequently, respondents will exposed to a hypothetical outcome of these election results and their perceptions of government elected with these results will be measured.
Experimental Design Details
Randomization Method
Randomization in software
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
-
Sample size: planned number of observations
1600 individuals
Sample size (or number of clusters) by treatment arms
320 Control (C), 320 Turnout Low (TL), 320 Turnout High (TH), 320 Turnout Low + Result (RL), 320 Turnout High + Result (RL)
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
I require a minimum of 230 respondents per group to achieve 90% statistical power to detect a 15 percentage point difference with alpha = 0.05 in responses to the binary response questions such as approval of a second wave of conscription.
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Charles River Campus Institutional Review Board
IRB Approval Date
2024-01-16
IRB Approval Number
7271X
Analysis Plan

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
Yes
Intervention Completion Date
July 16, 2024, 12:00 +00:00
Data Collection Complete
Yes
Data Collection Completion Date
July 16, 2024, 12:00 +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
-
Was attrition correlated with treatment status?
No
Final Sample Size: Total Number of Observations
1603
Final Sample Size (or Number of Clusters) by Treatment Arms
321 Control (C), 321 Turnout Low (TL), 320 Turnout High (TH), 321 Turnout Low + Result (RL), 320 Turnout High + Result (RL)
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
No
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials