Back to History Current Version

Interactive versus non-interactive implementations of "Dictator Games"

Last registered on July 05, 2018

Pre-Trial

Trial Information

General Information

Title
Interactive versus non-interactive implementations of "Dictator Games"
RCT ID
AEARCTR-0003121
Initial registration date
July 02, 2018

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
July 05, 2018, 2:55 PM EDT

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

Locations

Region

Primary Investigator

Affiliation
ETH Zurich

Other Primary Investigator(s)

PI Affiliation
ETH Zurich

Additional Trial Information

Status
Completed
Start date
2017-11-20
End date
2017-11-23
Secondary IDs
https://osf.io/fsg52/
Abstract
This is a re-registry (after data collection and analysis) to accompany our study, which was pre-regiistered at the OSF in November 2017.

Situations where one gives up own material payoff in order to increase someone else's material payoff are ubiquitous. In experimental economics, they are modeled as ‘dictator games’ and have been analyzed in great depth. What has gone unnoticed is that there are many games that are being studied under the label 'dictator game' in the laboratory, and that these game differ critically with respect to whether the underlying context is such that one player only gives and another player only receives, or whether players give and take at the same time. These two protocols come with crucially different (Nash) equilibrium predictions, even if players are allowed to have substantially pro-social preferences. Across the experimental literature, there has been a shift from the former –‘non-interactive’– dictator game implementation to the latter –‘interactive’– dictator game implementation. In this study, we will therefore implement dictator games using both protocols to improve our understanding of how these different protocols affect giving decisions.

Registration Citation

Citation
Grech, Philip and Heinrich Nax. 2018. "Interactive versus non-interactive implementations of "Dictator Games"." AEA RCT Registry. July 05. https://doi.org/10.1257/rct.3121-1.1
Former Citation
Grech, Philip and Heinrich Nax. 2018. "Interactive versus non-interactive implementations of "Dictator Games"." AEA RCT Registry. July 05. https://www.socialscienceregistry.org/trials/3121/history/201854
Sponsors & Partners

There is information in this trial unavailable to the public. Use the button below to request access.

Request Information
Experimental Details

Interventions

Intervention(s)
The main hypotheses concern fundamental differences in giving decisions between the two protocols: The non-interactive protocol predicts intermediate payments if a subject has some distributional and altruistic concern for the recipient's material well-being. By contrast, Nash equilibria of the games induced by the interactive protocol are characterized by extremal payments (either full or null payments), and in particular by increased levels of zero-giving for low prices of redistribution.

Additional hypotheses can be tested by varying the 'price of redistribution' p, that is, the factor by which each unit of material payoff that is given up is multiplied and sent to the recipient: in the interactive protocol, the Nash equilibrium prediction is that the peak at null (full) decreases (increases) in p.

We do a standard economic experiment conducted online. Recruitment will be done through a pre-registered subject pool from Amazon's Mechanical Turk, as used by the Decision Science Laboratory of ETH Zurich. Earnings will include a fixed show-up fee, and a variable bonus that depends on decisions of the subjects. We will not exclude any specific set of subjects except for ones that took part in dictator game experiments in the last three months, and we will pay subjects based on the decisions they take during the experiment according to online experiments standards. We aim to run the study before January 2018.

We plan to run 5 sessions of two-times-both treatments involving 20 active decision-making participants per session per treatment = 200 active subjects per treatment, which leads to a total of 600 subjects (of which 200 are inactive "recipients" in one of the treatments).
Intervention (Hidden)
Intervention Start Date
2017-11-21
Intervention End Date
2017-11-22

Primary Outcomes

Primary Outcomes (end points)
The above mentioned 20 dictator games will be played under the two treatments/protocols described above. In each treatment, one randomly selected game will be chosen for payment. In each treatment, each dictator plays 20 dictator games. The games vary with respect to p, the price of redistribution of the amount given: given any p, the recipient receives p-times what was given. We chose all prices of redistribution from 0.1 to 2.0, and dictators will face them in random order.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We will compare the resulting two giving distributions using various standard statistics including the arithmetic mean, median, variance, as well as higher moments of the distribution and other distributional measures such as bimodality, etc. In addition, we will define dummy variables for extremal (zero and full) giving decisions.
Experimental Design Details
To test distributional differences between the two treatments we will use the following non-parametric tests:

• distributional differences using Kolmogorov-Smirnov

• differences in mode using Mann-Whitney-Wilcoxon if KS test shows no significant distributional differences

• Equality of variance tests: Levene’s Test (using mean), Brown–Forsythe test (using median) if KS test shows no significant distributional differences

In addition, we identify whether extremal payments are more likely to be made under interactive versus non-interactive and whether zero-giving occurs more frequently for low p's, and full giving more frequently for high p's. These tests will rely on

• Logit regression for dummy “giving was zero” and for dummy "giving was full". Interaction effects between treatment and level of p are included, controlling for subject fixed effects as each dictator decided for all values of p. Regressions are repeated adding variables related to beliefs (as collected via the exit survey); in particular the following variables are added: we ask subjects to specify how many tokens they expected a random other subject to give when in the role of the dictator. We would add this value as a control. Moreover, we ask whether they would have given more (less) if they knew more (less) was given, and we will add two dummies respectively specifying whether the answer to this question is yes or no.
Randomization Method
We run a standard two-group, between-subject experiment, with random allocation of roles (dictator vs recipient) in the non-interactive protocol. We will balance sessions by day and time.

In each session, half of the subjects per session are randomly matched into one of two treatments and into one of the two games played per treatment, each subject playing exactly one protocol. In addition, there will be random allocation of roles (dictator vs recipient) in the non-interactive protocol. Active players will face decision situations in random order. Payment is based on one randomly selected decision per dictator.
Randomization Unit
Since we are comparing the protocols between-subject, we implement the experiment in the interest of budget and reasonable statistical power to have at least n=200 active subjects per treatment.

A total of 600 participants is about as much as we can afford given our budget situation.

Recruiting fewer subjects is not desirable as previous experimental from dictator games (under either protocol) consistently shows that a proportion of subjects (up to 50% in total) always and independent of treatment give either nothing or half, thus reducing the variation of people that could be affected by treatment variations.
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
Since we are comparing the protocols between-subject, we implement the experiment in the interest of budget and reasonable statistical power to have at least n=200 active subjects per treatment.

A total of 600 participants is about as much as we can afford given our budget situation.

Recruiting fewer subjects is not desirable as previous experimental from dictator games (under either protocol) consistently shows that a proportion of subjects (up to 50% in total) always and independent of treatment give either nothing or half, thus reducing the variation of people that could be affected by treatment variations.
Sample size: planned number of observations
Since we are comparing the protocols between-subject, we implement the experiment in the interest of budget and reasonable statistical power to have at least n=200 active subjects per treatment. A total of 600 participants is about as much as we can afford given our budget situation. Recruiting fewer subjects is not desirable as previous experimental from dictator games (under either protocol) consistently shows that a proportion of subjects (up to 50% in total) always and independent of treatment give either nothing or half, thus reducing the variation of people that could be affected by treatment variations.
Sample size (or number of clusters) by treatment arms
Since we are comparing the protocols between-subject, we implement the experiment in the interest of budget and reasonable statistical power to have at least n=200 active subjects per treatment.

A total of 600 participants is about as much as we can afford given our budget situation.

Recruiting fewer subjects is not desirable as previous experimental from dictator games (under either protocol) consistently shows that a proportion of subjects (up to 50% in total) always and independent of treatment give either nothing or half, thus reducing the variation of people that could be affected by treatment variations.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
GfeW
IRB Approval Date
2017-11-15
IRB Approval Number
https://gfew.de/ethik/RJPwvcoT

Post-Trial

Post Trial Information

Study Withdrawal

There is information in this trial unavailable to the public. Use the button below to request access.

Request Information

Intervention

Is the intervention completed?
Yes
Intervention Completion Date
November 21, 2017, 12:00 +00:00
Data Collection Complete
Yes
Data Collection Completion Date
November 21, 2017, 12:00 +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
Was attrition correlated with treatment status?
Final Sample Size: Total Number of Observations
Final Sample Size (or Number of Clusters) by Treatment Arms
Data Publication

Data Publication

Is public data available?
Yes
Public Data URL

Program Files

Program Files
Yes
Program Files URL
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials

Description
GEB paper
Citation
Grech, Philip D., and Heinrich H. Nax. "Rational altruism? On preference estimation and dictator game experiments." Games and Economic Behavior 119 (2020): 309-338.
Description
Dictator games are widely used to measure social preferences. What has gone unnoticed is that laboratory implementations differ critically, by virtue of the experimental protocol, with respect to whether a given player either only gives or receives, or wh
Citation
Grech, Philip and Heinrich Nax. "Interactive vs. Non-Interactive Dictator Games," Proceedings of the 17th International Conference on Group Decision and Negotiation, pg. 309-313, August 14, 2017.