Incentives and Bayesian Updating

Last registered on April 26, 2021

Pre-Trial

Trial Information

General Information

Title
Incentives and Bayesian Updating
RCT ID
AEARCTR-0006876
Initial registration date
December 13, 2020
Last updated
April 26, 2021, 5:39 AM EDT

Locations

Primary Investigator

Affiliation
University of Zurich

Other Primary Investigator(s)

PI Affiliation
University of Zurich
PI Affiliation
University of Zurich
PI Affiliation
University of Zurich

Additional Trial Information

Status
Completed
Start date
2020-12-19
End date
2021-03-31
Secondary IDs
Abstract
This preregistration describes an online experiment investigating reinforcement in a belief-updating task with various incentive levels. We describe the experimental design, the variables of interest, the hypotheses, and sample size. The experiment is conducted online via Prolific (recruiting) and Qualtrics (study).
External Link(s)

Registration Citation

Citation
Alós-Ferrer, Carlos et al. 2021. "Incentives and Bayesian Updating." AEA RCT Registry. April 26. https://doi.org/10.1257/rct.6876-1.1
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2020-12-19
Intervention End Date
2020-12-24

Primary Outcomes

Primary Outcomes (end points)
Error Rates in Conflict
Error Rates in Alignment
Primary Outcomes (explanation)
Error Rates in Conflict: Individual relative frequency of errors in the second draw (choosing the urn prescribed by reinforcement) in conflict situations.
Error Rates in Alignment: Individual relative frequency of errors in the second draw in alignment situations (used as exclusion criteria).

Secondary Outcomes

Secondary Outcomes (end points)
Response Times
Secondary Outcomes (explanation)
Individual average response times of errors and correct decisions in the second draw in conflict situations and individual average response times of correct decisions in the second draw in alignment situations.

Experimental Design

Experimental Design
This preregistration describes an online experiment investigating reinforcement in a belief-updating task with various incentive levels. We describe the experimental design, the variables of interest, the hypotheses, and sample size. The experiment is conducted online via Prolific (recruiting) and Qualtrics (study).
Experimental Design Details
See attached PDF.
Randomization Method
Randomization done by computer (Qualtrics).
Randomization Unit
Incentives randomized across individuals between 1 and 25 pence for a correct draw (integer values).
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
600 subjects
Sample size: planned number of observations
600 subjects
Sample size (or number of clusters) by treatment arms
approximately 24 observations for 25 different incentive levels.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials

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IRB

Institutional Review Boards (IRBs)

IRB Name
Human Subjects Committee of the Faculty of Economics, Business Administration, and Information Technology, University of Zurich
IRB Approval Date
2020-12-09
IRB Approval Number
OEC IRB # 2020-096

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials