Can the Prediction Market Improve Predictions of COVID-19?
The goal of this study is to better understand how people predict the future risks of the novel Coronavirus (COVID-19).
Specifically, the investigators will ask the following research questions:
- How well do participants predict the future risks of COVID-19?
- Can the predictions be improved by using a prediction market mechanism?
- Does the prediction market reduce people's fear of COVID-19?
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
The proposed study is an online experiment. Students enrolled at National University of Singapore are recruited to participate in the study.
Participants will first complete a pre-experiment survey, which contains basic demographic questions. Then, participants will be randomly assigned to one of two conditions: "Survey" and "Prediction Market".
"SURVEY" CONDITION:
Participants in the "Survey" condition are asked 16 prediction questions in a survey format. The questions are of the following format:
"What do you think will be the total cumulative number of cases in Singapore on 8th of June, at 12pm?"
Each question has 5 answer options. Each answer option is a range of outcomes, e.g. "< 28,900", "between 28,900 and 33,899", "between 33,900 and 38,899", "between 38,900 and 43,899", and "> 43,899". Participants are required to enter their perceived likelihood of each answer option in %.
The 16 prediction questions come from the following variations: 4 countries (Mexico, Singapore, Turkey, USA) x 2 outcome measures (cases, deaths) x 2 time periods (8th of June, 6th of July).
Participants have 24 hours to submit their predictions.
After the 24-hour period, participants are requested to fill out a post-experiment survey, which includes questions about their subjective attitudes and fears towards COVID-19.
"PREDICTION MARKET" CONDITION:
For participants in the "Prediction Market" condition, the same 16 prediction questions are presented in the form of prediction markets. The prediction market is a well-established method of eliciting people's predictions. The method is briefly described below.
There are 16 prediction markets, one for each question. Participants are given 100 tokens per market, which can be used to buy "stocks" on possible outcomes. There are 5 possible outcomes per market (identical to the 5 answer options per question in the "Survey" condition).
Each stock (i.e., possible outcome) will have a price that is dynamically determined by the central marketplace, which is a function of real-time demand and supply of the option. If the option is popular, its price will become higher, and vice versa.
Participants can trade at any time, and as many times as they want, during a 24-hour period. Upon closure of the prediction market, participants will be rewarded proportional to the number of shares that they hold on options that later turn out to be true.
The final prices of stocks correspond to the group's predictions of COVID-19.
After the 24-hour period, participants are requested to fill out a post-experiment survey, which includes questions about their subjective attitudes and fears towards COVID-19.
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HYPOTHESES
The prediction market leads to better predictions about COVID-19. The investigators will compare the survey predictions and the prediction-market predictions with the actual realized outcome. The investigators hypothesize that the prediction-market predictions are more accurate than the survey predictions through information aggregation.
The prediction market reduces fear. Fear is measured by participants' responses to subjective attitude questions in the post-experiment survey.
Study Type
Study Type
Enrollment (Actual)
Enrollment
Phase
Phase
- Not Applicable
Contacts and Locations
Study Locations
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-
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Singapore, Singapore
- National University of Singapore
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-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Description
Inclusion Criteria:
- National University of Singapore students
Exclusion Criteria:
- N/A
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Other
- Allocation: Randomized
- Interventional Model: Parallel Assignment
- Masking: None (Open Label)
Number of Arms
Arms and Interventions
Participant Group / ArmParticipant Group / Arm |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
No Intervention: Control
Participants' COVID-19 predictions are elicited via a survey
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|
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Experimental: Treatment
Participants' COVID-19 predictions are elicited via a prediction market
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Participants "bet" on likely future outcomes using a prediction market
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What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Predictions of COVID-19 Cases and Deaths
Time Frame: 24 hours
|
Participants are asked 16 questions of the following format: "What do you think will be the total cumulative number of cases in Singapore on 8th of June, at 12pm?" Each question has 5 answer options. Each answer option is a range of possible outcomes. The primary outcome measure is participants' perceived likelihood of each answer option. The 16 questions come from the following variations: 4 countries (Mexico, Singapore, Turkey, USA) x 2 outcome measures (cases, deaths) x 2 time periods (8th of June, 6th of July). |
24 hours
|
Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Fear
Time Frame: 24 hours (participants are required to submit post-experiment survey within 24 hours of completion of the main experiment)
|
Fear is measured by participants' responses to subjective attitude questions in the post-experiment survey.
The questions are on a 5-point Likert scale.
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24 hours (participants are required to submit post-experiment survey within 24 hours of completion of the main experiment)
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Collaborators and Investigators
Sponsor
Sponsor
Investigators
Investigators
- Principal Investigator: Teck Ho, PhD, National University of Singapore
Publications and helpful links
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Actual)
Primary Completion
Study Completion (Actual)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Other Study ID Numbers
Other Study ID Numbers
- SG-COVID
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
IPD Plan Description
IPD Sharing Time Frame
IPD Sharing Access Criteria
IPD Sharing Supporting Information Type
- STUDY_PROTOCOL
- ICF
- ANALYTIC_CODE
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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