The influence of the market mechanism on moral decision making - Evidence from an online experiment

Last registered on August 02, 2018

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Pre-Trial

Trial Information

General Information

Title

The influence of the market mechanism on moral decision making - Evidence from an online experiment

RCT ID

AEARCTR-0002707

Initial registration date

July 31, 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

August 02, 2018, 2:17 AM EDT

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

Locations

Country

Switzerland

Region

Primary Investigator

Name

Ann-Kathrin Crede

Affiliation

University of Bern, Institute for Organization and Human Resources

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Nana Adrian

PI Affiliation

University of Bern, Institute for Economics

Contact Investigator

PI Name

Jonas Gehrlein

PI Affiliation

University of Bern, Institute for Organization and Human Resources

Contact Investigator

Additional Trial Information

Status

In development

Start date

2018-07-31

End date

2018-12-31

Keywords

Governance, Welfare

Additional Keywords

morality, markets, philosophy, deontology, consequentialism, moral trolley problem, online experiment, competition, double auction, lottery, oTree, MTurk

JEL code(s)

C88, C99, D44, D47, D61, D62, D63, D91, P10

Secondary IDs

Abstract

Economists debate whether markets have a tendency to erode moral values. While some studies show that subjects tend to decide less morally when being exposed to a market environment, other studies argue that the market mechanism can have the property to promote moral behavior. We add to this discussion by explicitly distinguishing between two moral concepts from philosophy: consequentialism and deontology. According to consequentialism, the morality of an action is evaluated by the consequences it causes. Following deontology, the morality of an action is evaluated by the action itself.
We plan to conduct an online experiment on Amazon Mechanical Turk (MTurk) using oTree to investigate the research question of how exactly the market mechanism influences moral decision making: Subjects in the control treatment (non-market) play a lottery game in the first stage and take a decision in a moral trolley problem in the second stage. Subjects in the experimental treatment (market) play a double auction game in the role of a seller or buyer in the first stage and take a decision in the same moral trolley problem in the second stage.
We then compare the share of consequentialist decisions in the moral trolley problem between the two treatments. We hypothesize that the market interaction promotes the concept of cost-benefit analysis and makes consequences more salient, leading to a higher share of consequentialist decisions in the market treatment.
An answer to the question whether markets lead to more consequentialism would yield an important contribution to the current debate on the influence of markets on morality.

External Link(s)

Registration Citation

Citation

Adrian, Nana, Ann-Kathrin Crede and Jonas Gehrlein. 2018. "The influence of the market mechanism on moral decision making - Evidence from an online experiment." AEA RCT Registry. August 02. https://doi.org/10.1257/rct.2707-1.0

Former Citation

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

Participants of the experiment are recruited via MTurk and run through three parts: In the first part, they play a monetarily incentivized economic game, which differs according to the treatment. In the second part, participants face the same moral trolley problem and are asked how they would decide. In the third part, participants face a questionnaire with a variety of questions.

Intervention Start Date

2018-07-31

Intervention End Date

2018-12-31

Primary Outcomes

Primary Outcomes (end points)

The key outcome variable is the decision in the moral trolley problem.

Primary Outcomes (explanation)

The key outcome variable yields the share of participants actively intervening ("consequentialist" decisions) and the share of participants staying passive ("deontological" decisions).

Secondary Outcomes

Secondary Outcomes (end points)

Other variables of interest are responses in the questionnaire that comes in the third part of the experiment.

Secondary Outcomes (explanation)

The questionnaire collects information on morality, general experiences with markets, Fair Market Ideology (FMI), risk aversion, trust, and socio-demographic variables.

Experimental Design

The experiment was programmed with oTree and consists of two treatments: The non-market treatment and the market treatment. It will be conducted on MTurk in a between-subject design. In the first part, participants play a monetarily incentivized game which differs according to the treatment. Both games yield the same expected payoff. In the second part, participants have to decide in a moral trolley problem ("Trap Door"): They either stay passive, leading to the death of 3 people. Or they actively intervene, sacrificing the life of one person to save the other 3 people. In the third part, participants are asked to fill in a questionnaire collecting information on morality, general experiences with markets, Fair Market Ideology (FMI), risk aversion, trust, and socio-demographic variables.

Details on games:
In the non-market treatment, participants play a lottery game over 10 rounds and work on a transcription task (to hold duration and cognitive depletion of the first part constant across treatments). In the market treatment, participants play a double auction market game in the role of a seller or buyer over 10 rounds.

Experimental Design Details

Randomization Method

Randomization is done by the experimental software (oTree).

Randomization Unit

Individual

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

700 individuals

Sample size: planned number of observations

Based on a power calculation (t-test, alpha=0.05, power=0.8), we plan to collect n=700 observations. To check our manipulation for robustness, we will collect 120 additional observations where subjects additionally participate in a word-completion task after the first stage. Our hypothesis is that subjects in the market treatment complete the word fragments with more market-related words than subjects in the non-market treatment.

Sample size (or number of clusters) by treatment arms

Based on a power calculation (t-test, alpha=0.05, power=0.8), we plan to collect n=350 observations per treatment.

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Supporting Documents and Materials

IRB