How excuse-driven risk behavior affects cooperation: Evidence from dictator games and public good games

Last registered on October 23, 2025

Pre-Trial

Trial Information

General Information

Title
How excuse-driven risk behavior affects cooperation: Evidence from dictator games and public good games
RCT ID
AEARCTR-0017001
Initial registration date
October 17, 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
October 23, 2025, 6:49 AM EDT

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
Renmin University of China

Other Primary Investigator(s)

PI Affiliation
Aix-Marseille School of Economics
PI Affiliation
Renmin University of China

Additional Trial Information

Status
In development
Start date
2025-10-22
End date
2026-06-30
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This study aims to test whether individuals who exhibit excuse-driven risk behavior in the dictator games reduce their cooperation in public goods games, and how their predictions of others’ behavior affect their decision-making in strategic games. Building upon the work of Cardenas et al. (2024) and Dong and Zheng (2025), we conduct a within-subject laboratory experiment in which participants make some decisions in dictator games and public goods games. The dictator games and public goods games are presented in random order at the individual level. The dictator games consist of two tasks: a decision task and a prediction task. The decision task aims to elicit participants’ excuse-driven risk behavior, while the prediction task focuses on their predictions of others' behavior under the same risk scenarios. The public good games, framed as an irrigation provision problem, contain five different modified games. Participants choose between keeping one token with some private returns or investing it in a group fund with some collective returns. Except for the baseline scenario (G0), the rest of the four games present varying degrees of risk to private and collective returns. Specifically, we also conduct a between-subjects design with two treatments: a control group without partial insurance and a treatment group with partial insurance to investigate the impact of expression on the robustness of the results.
External Link(s)

Registration Citation

Citation
DONG, Wanxin, Yazhen Gong and Jiakun Zheng. 2025. "How excuse-driven risk behavior affects cooperation: Evidence from dictator games and public good games." AEA RCT Registry. October 23. https://doi.org/10.1257/rct.17001-1.0
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2025-10-22
Intervention End Date
2026-06-30

Primary Outcomes

Primary Outcomes (end points)
Excuse-driven risk behavior of each participant;
Participants' predictions of others’ excuse-driven risk behavior;
The cooperation rate;
Identification variable: “excuse” for 1 and “no excuse” for 0;
Identification variable: “can predict” for 1 and “fail to predict” for 0;
Identification variable: “contribute” for 1 and “keep” for 0.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The experiment is a within-subject design with two games: dictator games and public goods games. The dictator games and public goods games are presented in random order at the individual level.
The dictator games consist of two tasks: a decision task and a prediction task. The decision task will elicit subjects' excuse-driven risk behavior, while the prediction task will evaluate their predictions of others' excuse-driven behavior under the same risk scenarios. To control for possible ordering effects, we will randomize the order of the decision and prediction tasks at the individual level. In each task, subjects are presented with the same five sets of multiple price lists, comprising a normalization price list and four valuation price lists. Except for the normalization price list, the rest of four price lists will be presented in a random order for each subject.
The public good games, framed as an irrigation provision problem, contain five different games. Subjects in the same experimental session participate in all five games. The experiment always begins with the baseline scenario (G0) in which each subject must choose between keeping one token with some private returns or investing it in a group fund with some collective returns to each participant for each token invested by the group. The rest of four games present varying degrees of risk to private and collective returns. Here, we conduct a between-subjects design with two treatments: a control group without partial insurance and a treatment group with partial insurance. In the control group, subjects face private investment alone (G1), private investment with a reduced risk (G3), public investment alone (G2), and public investment with a reduced risk (G4). In the treatment group, the private-risk game (G1) and the collective-risk game (G2) are the same as those in the control group. Instead, games of G3 and G4 are changed to private investment alongside a partial insurance option (G3’) and public investment alongside a partial insurance option (G4’). To control for possible ordering effects, we randomize the order of the five different games. With the purpose of reducing subjects’ cognitive load and subsequent noisy responses and maintaining task consistency, the experiment always starts with G0, then G1 or G2, and then G3 or G4 (G3’ or G4’).
Experimental Design Details
Not available
Randomization Method
Randomization done by a computer.
Randomization Unit
Individual. The computer will generate a random order of experimental parts and a random order of decisions within each part for all subjects independently.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
240 full-time students from Renmin University of China
Sample size: planned number of observations
240 full-time students from Renmin University of China
Sample size (or number of clusters) by treatment arms
120 full-time students for the control group and 120 full-time students for the treatment group.
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
Lab of National Governance and Development, Renmin University of China
IRB Approval Date
2025-10-13
IRB Approval Number
RUCecon-202510-1