Time Heals: A Trust Game Experiment of Anger

Last registered on August 25, 2022


Trial Information

General Information

Time Heals: A Trust Game Experiment of Anger
Initial registration date
August 22, 2022

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
August 25, 2022, 1:59 PM EDT

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


Primary Investigator

The Ohio State University

Other Primary Investigator(s)

PI Affiliation
Texas A&M University
PI Affiliation
Ohio State University

Additional Trial Information

In development
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Do people remain angry over time when treated unfairly in cases involving monetary stakes? To find out, we study the effect of delay on anger in economic decision making, using a game-theoretical framework and lab experiments. Low degrees of cooperation have been indicated to bring up anger. We study how reciprocity changes where subjects have to wait before making a decision, over multiple rounds. Also, to elicit the degree of anger resulting from lack of cooperation, we employ choice-process data measures of Galvanic Skin Response and Neural Network-based face-reading software. These measures are intended to examine how people react to different cooperations, and how those emotions dissipate during the delay period.
External Link(s)

Registration Citation

Kamyar, Kamyar, Ian Krajbich and Marco Palma. 2022. "Time Heals: A Trust Game Experiment of Anger." AEA RCT Registry. August 25. https://doi.org/10.1257/rct.9678-1.0
Experimental Details


Time: subjects will be randomly divided into 3 groups, with different waiting times before submitting their decisions. More specifically, we implement a trust game in which responders will have to wait before submitting their decision for the amount they will return to the senders.
Wait: Indicator variable for the waiting time of the subject.
A=8 minutes
B=4 minutes
C=10 seconds
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Offers: the amounts offered by subjects in the experiment. More specifically,
1. Amount returned by the responders
2. Since waiting times are common knowledge for both players we will also record the amount sent by proposers to evaluate if the knowledge about time delays results in strategic considerations for the proposers.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
PANAS self-report of emotions, face-reading of emotions, and Skin Conductance Response values
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We employ a repeated investment (trust) game to experiment Simple Anger and Anger from Blaming Behavior treatments from Battigalli et. al., 2019. The trust game, first introduced by Berg et. al., 1995, is a two-player strategic game in which subjects are anonymously matched with each other and are randomly assigned to the role of ”investor” or the ”trustee”. The investor receives an initial endowment and chooses how much of it, if any, to ”invest” (double the amount while transferring) to the trustee. Then, the trustee decides how much of the received amount, if any, to give back to the investor. We find the trust game suitable for this experiment's purposes because of its simplicity and dynamic characteristics, as well as the possibility of initiation and/or reinforcement of anger due to low cooperation among counterpart subjects. As we are interested in the evolution of anger over time and the dynamic aspects of anger in a controlled experimental setting, we employed a repeated version of the standard trust game. Following the literature, to avoid endgame effects (a player ”coaxing" for higher returns in the starting rounds, and taking everything in the finishing round), we also employed a random termination rule. For the ”Anger from Blaming Behavior" (first) section, subjects are randomly matched in groups of two, and play the trust game for 3 to 5 rounds. That is, after the third round a digital coin is flipped to determine whether the players will play a fourth round, and after that round another digital coin will be flipped to determine whether the players will play a fifth round. We expect that repetitive low degrees of cooperation arise feelings of anger. Any two players that are matched initially, will play with each other and remain in their roles (investor or trustee) until the end of the Anger from Blaming Behavior (first) section.
After the Anger from Blaming Behavior (first) section, each player is rematched with another counterpart, yet every player remains in the same role (trustee or investor) that they were initially assigned until the end. The Simple Anger (second) section consists of another 3 to 5 rounds of the trust game (same methodology as the first section) where participants are rematched with a different person. It's expected that anger resulting from low cooperation in the first section spills into the second section, therefore the second section represents Simple Anger (i.e., anger towards others generally).
To test the time-dependent theory of anger, we create three treatments in which trustees are exogenously assigned to a waiting before responding to an offer condition. In the baseline group, the mandatory waiting time is 10 seconds; Treatment 1 and Treatment two have waiting times of 4 and 8 minutes respectively. It's expected that reciprocity will increase as the waiting time increases (i.e., higher amounts returned to player 1 with longer waiting times), since a shorter time delay would produce less anger than the control, but more anger than the longer time delay to measure the cooling down of anger.
Subjects are unable to skip the waiting time in their randomly assigned condition, and they will only be able to enter the desired "send back" amount after the waiting time is up. During the waiting time, subjects are asked to do a Real Effort Task (RET): random numbers in green or red appear on the screen, and subjects are asked to press the '1' key if the number is in green, and not press anything if the number is red. The RET is incentivized with 1 token per every "correct" keystroke. Also, contrary to some previous studies (Grimm and Mengel, 2011), we made the waiting time mandatory. Unless the waiting time is made mandatory, the critique of selection bias may be raised as entering the cooling off treatment was optional (and not mandated by the experimenters). To make the cumulative waiting time equal among all subjects, subjects with shorter waiting groups have to perform the RET after finishing the trust games. Furthermore, to elicit the degree of anger resulted from lack of cooperation, we employ choice-process data measures of Galvanic Skin Response and face-reading software, as well as self-reported emotions on the negative schedule of the PANAS scale, both available at Human Behavior Lab, Texas A&M University.
Battigalli, P., Dufwenberg, M., & Smith, A. (2019). Frustration, aggression, and anger in leader-follower games. Games and Economic Behavior, 117, 15–39. https://doi.org/10.1016/j.geb.2019.06.001
Berg, J., Dickhaut, J., & McCabe, K. (1995). Trust, reciprocity, and social history. Games and Economic Behavior, 10 (1), 122–142
Grimm, V. & Mengel, F.. (2011). Let me sleep on it: Delay reduces rejection rates in Ultimatum Games. Economics Letters 111(017)

Experimental Design Details
Randomization Method
Specific dates and sessions will be assigned and allocated to each waiting times. Subjects will be randomly assigned to the sessions based on their availability,
Randomization Unit
Individual units of randomization; matching in randomly-assigned groups of 2 (twice per session)
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
3 treatments (different waiting times)
Sample size: planned number of observations
44 pairs of subjects (88 subjects) per treatment
Sample size (or number of clusters) by treatment arms
A medium effect size requires 44 pairs of subjects (88 subjects) per treatment, resulting in a total sample size of 264 subjects
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Previous studies (e.g., Neo et. al., 2013) find a small effect size (Cohen’s d=0.019). Using prior data, we have conducted power analysis and calculations and found a minimum sample size of 42 for an effect size of 0.5, a minimum sample size of 66 for an effect size of 0.4, and a minimum sample size of 168 for an effect size of 0.25. Study parameters: alpha = 0.0500 power = 0.8000 delta = 0.5120 m1 = 1.7600 m2 = 2.2720 diff = 0.5120 sd = 2.5600 Please refer to the uploaded word document for documentations on power analysis.
Supporting Documents and Materials


Document Name
Power Calculation
Document Type
Document Description
Power Calculation

MD5: 4bc73c7193a4b4a93bbd9513c284eb5d

SHA1: 7cb19e336ad092c0cb3486cb41f187a2c73406ef

Uploaded At: June 30, 2022


Institutional Review Boards (IRBs)

IRB Name
The Ohio State University IRB
IRB Approval Date
IRB Approval Number
IRB Name
Texas A&M University IRB
IRB Approval Date
IRB Approval Number


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