How Voting Rules Impact Legitimacy

Last registered on January 26, 2024


Trial Information

General Information

How Voting Rules Impact Legitimacy
Initial registration date
June 24, 2021

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
June 25, 2021, 1:41 PM EDT

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

Last updated
January 26, 2024, 8:16 AM EST

Last updated is the most recent time when changes to the trial's registration were published.



Primary Investigator

ETH Zurich

Other Primary Investigator(s)

PI Affiliation
University of Leeds
PI Affiliation
ETH Zurich
PI Affiliation
ETZ Zurich
PI Affiliation
Université Fribourg
PI Affiliation
ETH Zurich

Additional Trial Information

Start date
End date
Secondary IDs
EK 2021-N-28
Prior work
This trial does not extend or rely on any prior RCTs.
Collective action is essential for addressing the grand challenges of our time. However, for such action to be successful, decision-making processes must be perceived as legitimate. In this study, we investigate the legitimacy of different voting methods.

Using a pre-registered human subject experiment, 120 participants cast their votes using four voting methods: majority voting, combined approval voting, score voting and modified Borda count. These methods represent a range of preference elicitation designs, from low to high complexity and flexibility.
Furthermore, we developed a legitimacy scale upon which the participants rate the voting methods.
The experiment was conducted in a non-political setting (voting on colour preferences) and a political context (voting on COVID-19-related questions).

Our findings suggest that the perceived legitimacy of a voting method is context-dependent. Specifically, preferential voting methods are considered more legitimate than majority voting in political decision-making, but only for individuals with well-defined preferences.

Furthermore, preferential voting methods are more legitimate than majority voting in a highly polarized situation.
External Link(s)

Registration Citation

Hausladen, Carina Ines et al. 2024. "How Voting Rules Impact Legitimacy." AEA RCT Registry. January 26.
Sponsors & Partners


Experimental Details


The intervention follows a between-subjects design: Participants provide legitimacy ratings at three different stages of the experiment. The ratings vary w.r.t. context and whether they were provided after voting or examining outcomes of the vote.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
The main dependent variable is a participant's (self-reported) legitimacy rating.
Primary Outcomes (explanation)
Legitimacy is proxied by the concepts of fairness, trust, influence and acceptance. More precisely, participants are asked: "I would comply with the result and accept it as fair reflecting my and others' opinions."

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The experiment has three main stages. At each stage, participants provide legitimacy ratings, varying the context and action preceding the rating.
In stage I, participants vote upon a trivial, non-critical context (their favourite colour). Subsequently, they provide legitimacy ratings.
In stage II, participants vote upon a complex, critical context (COVID-19). Subsequently, they provide legitimacy ratings.
Finally, in stage III, participants observe the outcome of the vote and subsequently provide legitimacy ratings.
Experimental Design Details
Randomization Method
Randomization is done by a python-based algorithm.
Randomization Unit
As there is no treatment involved, no randomization of allocating participants to treatments is necessary. What is randomized is the order of the different questions and within questions their respective options, that participants vote upon.
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
200–300 participants
Sample size: planned number of observations
Each participant provides 16 votes (4 questions* 4 voting methods) and 24 legitimacy ratings (4 + 4 + 16).
Sample size (or number of clusters) by treatment arms
200–300 participants
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Two-sample t-test power calculation n = 30.4263 d = 0.8449776 sig.level = 0.05 power = 0.9 alternative = two.sided NOTE: n is number in *each* group
Supporting Documents and Materials


Document Name
Document Type
Document Description
This is the preprint of the paper.

MD5: d1e840c17c66e5c0f85da484ed4e06fd

SHA1: f09178e9e99c575d5750259670b0e5e8338f422e

Uploaded At: April 06, 2023

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Institutional Review Boards (IRBs)

IRB Name
ETH Ethics Commission
IRB Approval Date
IRB Approval Number


Post Trial Information

Study Withdrawal

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Is the intervention completed?
Intervention Completion Date
July 31, 2021, 12:00 +00:00
Data Collection Complete
Data Collection Completion Date
July 31, 2021, 12:00 +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
Was attrition correlated with treatment status?
Final Sample Size: Total Number of Observations
Final Sample Size (or Number of Clusters) by Treatment Arms
Data Publication

Data Publication

Is public data available?

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials