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Recycling uncast votes as a means to increase voter turn out
Last registered on October 28, 2020

Pre-Trial

Trial Information
General Information
Title
Recycling uncast votes as a means to increase voter turn out
RCT ID
AEARCTR-0006679
Initial registration date
October 27, 2020
Last updated
October 28, 2020 9:14 AM EDT
Location(s)

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Primary Investigator
Affiliation
University of Neuchatel
Other Primary Investigator(s)
PI Affiliation
FSU Jena
Additional Trial Information
Status
In development
Start date
2020-10-29
End date
2021-10-31
Secondary IDs
Abstract
Sufficient voter turnout is a desirable property of a healthy democratic system. Unfortunately, historical data show that a sizable portion of the eligible electorate tends to abstain. This project aims to increase voter turnout by leveraging important insights from personal and social psychology and behavioral economics.
The main idea is to modify the current vote counting rule in the following manner: uncast votes are not ignored but rather, randomly allocated to the alternatives. We hypothesize that this intervention will prompt people to turn out to vote to avoid having their votes misused or misallocated by the random mechanism. The intervention does not restrict voters' freedom (as opposed to, e.g., obligatory voting) and would be easy to implement in real life. We test the effectiveness of the proposed intervention both in the field (U.S. presidential elections) and in the laboratory experiments in Switzerland and Germany.
External Link(s)
Registration Citation
Citation
Kandul, Serhiy and Olexandr Nikolaychuk. 2020. "Recycling uncast votes as a means to increase voter turn out." AEA RCT Registry. October 28. https://doi.org/10.1257/rct.6679-1.0.
Sponsors & Partners

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Experimental Details
Interventions
Intervention(s)
The intervention is centered around the idea of integrating uncast votes into the determination of the winner of the election.
Intervention Start Date
2020-10-29
Intervention End Date
2021-07-30
Primary Outcomes
Primary Outcomes (end points)
voter turnout, attitudes towards the intervention
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Voting preferences, i.e. the share of voters supporting a particular candidate
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
We study several variations of randomization mechanism and include treatments with pecuniary penalty for abstaining.

Experimental Design Details
Not available
Randomization Method
Randomized is done by a software (oTree)
Randomization Unit
individual
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
1800 for the US. survey;
200 for the experiment in Germany;
200 for the experiment in Switzerland.
Sample size: planned number of observations
1800 for the US. survey; 200 for the experiment in Germany; 200 for the experiment in Switzerland.
Sample size (or number of clusters) by treatment arms
600 per condition for the U.S. survey;
40 per conditions in lab experiments.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
German Association of Experimental Economics
IRB Approval Date
2020-10-27
IRB Approval Number
4HAMU7uB