Decomposing Belief Updating: Likelihoods and Posteriors

Last registered on February 04, 2026
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Pre-Trial

Trial Information

General Information

Title
Decomposing Belief Updating: Likelihoods and Posteriors
RCT ID
AEARCTR-0017734
Initial registration date
January 22, 2026

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
February 04, 2026, 9:37 AM EST

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

Locations

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Primary Investigator

Name
Tashfeen Saeed
Affiliation
Cornell University
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Other Primary Investigator(s)

Additional Trial Information

Status
In development
Start date
2026-01-26
End date
2026-04-30
Keywords
Behavior, Lab
Additional Keywords
Beliefs, Belief updating, Bayesian updating, Likelihood judgments, Posterior beliefs, Information processing, Probabilistic reasoning, Laboratory experiment
JEL code(s)
D83, C91
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This study proposes an experiment that elicits both likelihood judgments and posterior beliefs in a belief-updating task with a rich information structure. By directly measuring each phase of Bayesian updating, the experiment identifies whether deviations from Bayesian benchmarks arise from errors in likelihood assessment, Bayesian integration, or both. The study examines two questions: (i) whether eliciting or providing likelihoods improves posterior accuracy, and (ii) whether eliciting posterior beliefs affects the accuracy of likelihood judgments.
External Link(s)

Registration Citation

Citation
Saeed, Tashfeen. 2026. "Decomposing Belief Updating: Likelihoods and Posteriors." AEA RCT Registry. February 04. https://doi.org/10.1257/rct.17734-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Participants are randomly assigned to one of four experimental conditions in a belief-updating task. Across conditions, the study varies whether participants are asked to report likelihoods, are provided with likelihood information, and/or are asked to report posterior beliefs. All participants complete repeated rounds of a probabilistic inference task, where the information structure varies across rounds.

The Baseline (BL) group serves as the control condition, in which participants report posterior beliefs only. The three treatment groups (CU, PU, CO) vary in whether likelihoods are elicited or provided, and whether posterior beliefs are also elicited.
Intervention Start Date
2026-01-26
Intervention End Date
2026-04-30

Primary Outcomes

Primary Outcomes (end points)
The primary outcomes are participants’ reported posterior probabilities that a bag generated a given sample, and their reported likelihood probabilities of drawing the sample from each bag.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The study uses a belief-updating task based on a standard bookbag-and-poker-chip paradigm. Participants complete multiple independent rounds in which there are two bags containing different proportions of colored balls. In each round, one bag is selected at random, a small sample of balls is drawn with replacement, and participants report probabilities based on the observed sample.

Participants are randomly assigned to one of four treatment conditions that vary in whether they report likelihoods, posterior beliefs, or both, and whether likelihood information is provided or must be computed by the participant. In some conditions, participants report the probability of observing the sample from each bag. In other conditions, participants report the probability that each bag generated the sample. In one condition, participants are shown the correct likelihoods before reporting posterior beliefs.

Across rounds, the number of draws and the composition of the bags vary, generating exogenous variation in the Bayesian likelihoods and posteriors. All questions are framed hypothetically, with probabilities fully determined by the stated bag compositions and samples.

Additional details on procedures, analysis, and exclusions are provided in the uploaded Pre-Analysis Plan.
Experimental Design Details
Not available
Randomization Method
Participants are randomly assigned to one of four treatment conditions using Qualtrics’ built-in randomization features.
Randomization Unit
Individual participants
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
800 participants
Sample size: planned number of observations
800 participants
Sample size (or number of clusters) by treatment arms
200 participants in each of four treatment groups
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Cornell University Office of Research Integrity and Assurance
IRB Approval Date
2025-10-23
IRB Approval Number
IRB0150154
Analysis Plan

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