Belief updating from explicit, implicit, and silent signals across multiple settings

Last registered on December 09, 2025

Pre-Trial

Trial Information

General Information

Title
Belief updating from explicit, implicit, and silent signals across multiple settings
RCT ID
AEARCTR-0017408
Initial registration date
December 05, 2025

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
December 09, 2025, 7:50 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

Affiliation
Shanghai University of Finance and Economics

Other Primary Investigator(s)

PI Affiliation
Shanghai University of Finance and Economics
PI Affiliation
Shanghai University of Finance and Economics

Additional Trial Information

Status
On going
Start date
2025-12-01
End date
2026-12-31
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
We conduct a series of experiments to examine how people update their beliefs in response to non-explicit or silent signals/activities across multiple settings. Experiment 1 studies an individual belief-formation environment, testing whether participants can infer an underlying state optimally after receiving imperfect exogenous signals, which may be explicit, implicit, or silent. Experiment 2 studies a game-theoretic environment using a “colored hats” problem, examining whether individuals correctly update their beliefs about the state of the world by observing others’ actions, which again vary in how explicitly they convey information. Experiment 3 studies a matching environment with incomplete information, investigating whether people learn about the underlying state of the matching market from others’ matching behavior or outcomes. The information structure varies across conditions, with participants observing either only matching outcomes or all market activities, including individual proposals, acceptances, and rejections.
External Link(s)

Registration Citation

Citation
Gui, Shan, Simin He and Gaoji Hu. 2025. "Belief updating from explicit, implicit, and silent signals across multiple settings." AEA RCT Registry. December 09. https://doi.org/10.1257/rct.17408-1.0
Experimental Details

Interventions

Intervention(s)
Experiment 1 (individual belief-formation).
In an individual belief-formation setting, participants are asked to infer the underlying state by observing signals. The experiment involves two dimensions of intervention: First, whether one type of signals is explicitly presented or replaced by the absence of a signal, while maintaining theoretical equivalence. Second, in the case of no signal, whether participants are explicitly reminded that there is no signal.

Experiment 2 (game-theoretic: “colored hats” problem).
In a game-theoretic setting, represented by a colored hats problem, participants must guess the underlying state (the color of their hats) by observing the hat color and actions of others over multiple periods. The experimental intervention has two dimensions: First, whether others’ actions are explicit (guessing one specific color), or silent (no action taken). Second, whether the action space explicitly contains the option of “no action”.

Experiment 3 (matching with incomplete information).
In a matching market with incomplete information setting, participants must infer the state of the market to make optimal matching decisions based on observed market activities. The intervention involves two dimensions: First, whether others' matching behavior is active (e.g., moving from unmatched to matched, or dissolving an existing match) or silent (e.g., remaining unmatched). Second, whether detailed matching activities (including proposals, acceptances, and rejections) are made public, allowing participants to observe the actions behind silent matching behavior.
Intervention Start Date
2025-12-01
Intervention End Date
2026-12-31

Primary Outcomes

Primary Outcomes (end points)
Experiment 1. Whether the choices are Bayesian optimal.
Experiment 2. Whether the choices are correct/optimal given the information received.
Experiment 3. At individual level, whether the individual reaches the Bayesian correct matching.
Primary Outcomes (explanation)
Experiment 1. Whether the choices are Bayesian optimal: a choice is classified as Bayesian optimal if it is the optimal guess based on the signals received; otherwise, it is considered non-optimal.

Experiment 2. Whether the choices are correct/optimal: given the color of the other player’s hat as well as their choices made in previous periods, there is always a correct/optimal choice according to the theory.

Experiment 3. Whether individuals can reach the Bayesian correct matching: given the realized state of the matching market (and others’ observable matching behavior), there is always a correct matching choice.

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Experiment 1.
There are two possible states of the world: Blue or Red, each occurring with a known probability. Participants receive imperfect exogenous signals about the true state. In Treatment Explicit, signals are shown as either blue or red; and each signal is more likely to occur under the corresponding true state (i.e., a blue signal is more likely to be drawn if the state is Blue). In treatment Silent, the blue signal is replaced with the absence of a signal, meaning it is not displayed to participants, while the red signal remains explicit. In Treatment Implicit, the signal structure mirrors that of Silent, but participants are given explicit information about the probability of receiving no signal and are informed whenever the signal is absent. In our experimental design, we use a between-subject design for these three treatments.

Experiment 2.
We consider a “colored hats” problem with two players, each wearing a colored hat: either Red or Blue. Both players are informed that at least one of the two hats is Red (or Blue, depending on the realized state of hat colors), and each player observes the color of the other player’s hat. The game is played for multiple periods (open-ended), with the following rules: in each period, players first observe the other player’s action (if any) from the previous period, and then simultaneously decide whether to guess the color of their own hat. Once a player makes a guess, it becomes final and cannot be changed in later periods. The game ends when both players have made a guess, or when both choose to proceed to the next round. Correct guesses made in later periods receive a discounted payoff, ensuring that players with sufficient information have no incentive to delay their guess.
We employ a 2x2 design that varies along two dimensions: game type and action space.
The game type is determined by the true state and consists of two possibilities:
A. The two players wear different hat colors.
B. The two players wear the same hat color.
The action space also has two versions:
a. (“Red”, “Blue”, no action). No action means not making a choice between “Red” and “Blue”.
b. (“Red”, “Blue”, “Not Sure”).

We consider a two-game-type by two-action-space design. The two game types (different hat colors or same hat color) are implemented within participants, while the two action spaces (whether “Not Sure” is a displayed action) are assigned between participants.

Experiment 3.
We adopt a matching with incomplete information environment here (see pre-registration at https://www.socialscienceregistry.org/trials/16825/edit for background information).
We employ a 2x2 design that varies along two dimensions: game type and information structure.
Game types:
A. At the start of the market, all participants are unmatched. Participants can update their beliefs of the state by observing others either form a match or dissolve existing matches.
B. At the start of the markets, all participants are unmatched. Participants can update their beliefs of the state by observing others maintain the unmatched status quo.

Information structures:
a. Only dynamic matching outcomes are observable to everyone in the market.
b. Both dynamic matching outcomes and additional detailed activities, including individual proposals, acceptances, and rejections, are observable to everyone in the market.
We consider a two-game-type by two-market-information-structure design. The two game types (active matching behavior or maintaining the status quo) are implemented within participants, while the two market information structures (whether the proposing and responding activities are publicly displayed) are assigned between participants.
Experimental Design Details
Not available
Randomization Method
Experiment 1. Within each experiment session, multiple treatment orders are implemented by randomization; the randomization is pre-determined. Subjects who sign up for the experiment receive a seat number randomly before entering the laboratory; the seat number determines the treatment and the parameter order.
Randomization Unit
Individual-level randomization
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
Experiment 1. We aim to collect 40-50 subjects for each of the 3 treatments; within each treatment, they are roughly equally split among the two different parameter orders.
Sample size: planned number of observations
Experiment 1. About 120-150 individuals, recruited via the subject pool of the Economic Lab of the Shanghai University of Finance and Economics. We only recruit first-year undergraduate students for this experiment, as they haven’t taken a Probability Theory or Statistical course yet (during university).
Sample size (or number of clusters) by treatment arms
Experiment 1. 40-50 subjects per treatment order.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
NA
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number