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An Experimental Study of Political Expertise and the Democratic Ideal
Last registered on November 05, 2019


Trial Information
General Information
An Experimental Study of Political Expertise and the Democratic Ideal
Initial registration date
November 04, 2019
Last updated
November 05, 2019 9:39 AM EST
Primary Investigator
Florida State University
Other Primary Investigator(s)
PI Affiliation
University of Rochester
Additional Trial Information
In development
Start date
End date
Secondary IDs
How does the level of political expertise among voters affect the quality of democratic choice? The answer to this question underlies one of the key hallmarks of representative democracy, namely, whether individuals with the best knowledge of political issues and policies are the ones who ultimately make political decisions. We propose experiments that will address this question by investigating the quality of democratic choice made by individual voters who have the same goals and studying how changes in the level of expertise among voters affect the quality of democratic choice and voters' willingness to participate in elections. Using a novel experimental design we will directly elicit voters' willingness to vote which will allow us to examine several distinct collective action issues that arise in democratic decision-making.
External Link(s)
Registration Citation
Ou, Kai and Scott Tyson. 2019. "An Experimental Study of Political Expertise and the Democratic Ideal." AEA RCT Registry. November 05. https://doi.org/10.1257/rct.4981-1.0.
Experimental Details
We will change the level of political expertise in the laboratory.
Intervention Start Date
Intervention End Date
Primary Outcomes
Primary Outcomes (end points)
Whether an individual voter decides to participate in voting and what the maximum cost they would like to take to make their vote count
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
We will conduct laboratory experiments and use undergraduate student subjects to investigate how the change of level of political expertise affects voting decisions and the quality of democratic choice.
Experimental Design Details
Our experiment will represent a common value election between two alternatives, A and B, where the best option for every voter (or experimental subject) will be the same, but where the alternative that best serves voters' interest will not be known to every voter. To determine voters' best alternative, an equally likely state of the world (also A or B) will be independently drawn. The electorate will be composed of 5 (human) subjects who must collectively choose an alternative, where the committee's decision will be made through a simple majority election, i.e. whichever color receives more votes will be the collective decision that is applied to everyone; ties will be broken by a fair coin toss. To represent the behavior of voters whose preferences are independent of the state of the world, we also consider two additional votes cast randomly by the computer, which we refer to as the partisan bias. The partisan bias will have three possible values that correspond to two votes for A, two votes for B, or one vote for each, A and B. Each of these events are equally likely. The partisan bias in our experiment will provide a hurdle that subjects must cross to achieve their best alternative. The state of the world and the level of the partisan bias will be randomly determined prior to subjects making voting decisions. Voters will not know the state of the world ex ante and will not be told what the correct decision is until after the collective decision has been made. Voters will have identical preferences that depend only on the group decision and the state of the world. If the collective decision matches the state of the world, then all participants will receive a high payoff of 110 experimental points, Otherwise, all participants will receive a low payoff of 10 experimental points. Before voting, some voters will be exogenously assigned as expert voters, and will be perfectly informed of the state of the world, which tells them which alternative best serves the common interest. In addition, an expert voter will also be told the value of the partisan bias. To determine whether a voter is assigned expertise, in each election the computer will generate a random INFORMATION NUMBER for each subject from a uniform distribution between 1 and 100 points. Subjects will become experts based on an exogenously assigned cutoff over INFORMATION NUMBERS that is symmetric, commonly known, and fixed in each treatment. If the computer randomly generates an INFORMATION NUMBER that is higher than the exogenously assigned threshold for each treatment, the subject will not be told the state of the world or the partisan bias (and is not charged the expertise fee). If the INFORMATION NUMBER is lower than the exogenously assigned threshold, then the state of the world and partisan bias is privately revealed. There is no cost for the information (political expertise). We administer expertise in this way because our method is relatively simple for subjects to understand and calculate the level of expertise. As a critical part of our design, expert voters do not know exactly about the number of how many voters are experts, but all the voters know the distribution of expert voters, and can form a posterior belief regarding the number of expert voters. After expertise has been administered, each subject will be asked to make a voting decision. We design a novel method to elicit an individual's willingness to vote that takes advantage of the Becker-Degroot-Marshak (BDM) mechanism. Once a subject reports her willingness to vote, the computer will independently generate a voting cost from a uniform distribution between 1 and 100. If a voter had reported a vote choice, and if her individual voting cost is lower than her reported willingness to vote, then the subject will pay the voting cost, and her vote is included in the collective decision. Instead, if a subject's individual voting cost is higher than her reported willingness to vote, then the subject's vote will not be counted toward the committee's decision and she will not be charged the cost of voting.
Randomization Method
We will use undergraduate student subjects in our laboratory experiments. 120 subjects will be randomly recruited from a subject pool in which there are more than 3000 registered subjects. The recruited subjects will be randomly assigned to treatments and sessions.
Randomization Unit
Was the treatment clustered?
Experiment Characteristics
Sample size: planned number of clusters
120 subjects
Sample size: planned number of observations
3600 observations will be generated from 120 subjects playing voting games for 30 rounds
Sample size (or number of clusters) by treatment arms
60 subjects for High Expertise Treatment
60 subjects for Low Expertise Treatment
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials

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IRB Name
Florida State University
IRB Approval Date
IRB Approval Number
Post Trial Information
Study Withdrawal
Is the intervention completed?
Is data collection complete?
Data Publication
Data Publication
Is public data available?
Program Files
Program Files
Reports, Papers & Other Materials
Relevant Paper(s)