Social Influence and Mitigation

Last registered on January 23, 2023
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Pre-Trial

Trial Information

General Information

Title
Social Influence and Mitigation
RCT ID
AEARCTR-0010768
Initial registration date
January 13, 2023

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
January 23, 2023, 8:05 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

Name
Friederike Mengel
Affiliation
Uni Essex
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Other Primary Investigator(s)

Additional Trial Information

Status
In development
Start date
2023-01-13
End date
2023-11-16
Keywords
Behavior, Environment & Energy
Additional Keywords
Climate Action; Social Influence
JEL code(s)
C92, D91, Q0
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Many people feel powerless to do reduce climate change as the individual choices they can make are likely to only have negligible impact. If their choices were to influence many others, however, then collectively the impact would become more important. We will study how people’s decision to mitigate their climate impact depends on the possibility to have social influence. In a baseline treatment participants decide by how much to mitigate their climate impact by donating to a tree planting scheme. Additional treatments then allow for their decision to be observed by a number of others either before or after they make their choice. When others observe a decision before they make their choice this creates the possibility of social influence in the experiment.
External Link(s)

Registration Citation

Citation
Mengel, Friederike. 2023. "Social Influence and Mitigation." AEA RCT Registry. January 23. https://doi.org/10.1257/rct.10768-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2023-01-13
Intervention End Date
2023-04-13

Primary Outcomes

Primary Outcomes (end points)
Willingness to Mitigate (WTM)
Primary Outcomes (explanation)
We measure the willingness to mitigate by the amount of money participants are willing to give up to offset their carbon footprint.

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We will study how people’s decision to mitigate their climate impact depends on the possibility to have social influence. In a baseline treatment participants decide by how much to mitigate their climate impact by donating to a tree planting scheme. Additional treatments then allow for their decision to be observed by a number of others either before or after they make their choice. When others observe a decision before they make their choice this creates the possibility of social influence in the experiment.
Experimental Design Details
Not available
Randomization Method
online platform
Randomization Unit
individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
n/a
Sample size: planned number of observations
1860 participants in Wave 1 and 3384 participants in Wave 2
Sample size (or number of clusters) by treatment arms
In Wave 1 we plan to have 240 participants per treatment except for the conditions where each individual is uniquely observed by twenty others in Wave 2. For those conditions we plan on 60 participants in Wave 1. The reason is that otherwise Wave 2 sample sizes would become extremely large. (240 Wave 1 participants in this condition would correspond to 4800 Wave 2 participants for this condition alone). We will have 300 participants (240+60) in the baseline treatment (without influence/observability).

In sum we will have the following sample sizes for our Wave 1 treatments:

Baseline: 300; Influence 1-1: 240; Influence 1-20: 60; Influence 20-1: 240; Influence 20-20: 240
Observability 1-1: 240; Observability 1-20: 60; Observability 20-1: 240; Observability 20-20: 240, where Influence x-y denotes an influence treatment where each Wave 1 participant is observed by x others who each observe y others in total.

Sample sizes in Wave 2 then directly follow from these.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Power analysis based on t-tests comparing two independent means shows that these sample sizes allow us to detect an effect in terms of a treatment difference between WTM between baseline and Influence 1-1 or Influence 1-1 and Observability 1-1 of about 0.24-0.25 GBP at the 5% level with 80% power.
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
University of Essex Social Sciences Ethics Subcommittee
IRB Approval Date
2022-12-13
IRB Approval Number
ETH2223-0583
Analysis Plan