Warm-Glow versus Cold-Prickle Revisited: First Evidence from the Field

Last registered on June 10, 2019

Pre-Trial

Trial Information

General Information

Title
Warm-Glow versus Cold-Prickle Revisited: First Evidence from the Field
RCT ID
AEARCTR-0004283
Initial registration date
June 06, 2019

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
June 10, 2019, 10:04 PM EDT

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

Locations

Region

Primary Investigator

Affiliation
RWI - Leibniz Institute for Economic Research

Other Primary Investigator(s)

PI Affiliation
RWI and Ruhr Graduate School in Economics
PI Affiliation
University of Alabama, NBER, RWI
PI Affiliation
University of Mannheim

Additional Trial Information

Status
In development
Start date
2019-06-07
End date
2020-07-01
Secondary IDs
Abstract
In his seminal paper, Andreoni (1995) has shown in a laboratory experiment that framing the contribution to a public good as a positive externality leads to larger contributions to the public good than framing non-contribution as a negative externality. He refers to the motivation to contribute under the positive externality frame as the “Warm-Glow from doing good”, while he refers to the motivation to contribute under the negative externality frame as the avoidance of the “Cold-Prickle from doing bad”. In this paper, we test the external validity of the Andreoni (1995) findings in the field.
External Link(s)

Registration Citation

Citation
Andor, Mark A. et al. 2019. "Warm-Glow versus Cold-Prickle Revisited: First Evidence from the Field ." AEA RCT Registry. June 10. https://doi.org/10.1257/rct.4283-1.0
Former Citation
Andor, Mark A. et al. 2019. "Warm-Glow versus Cold-Prickle Revisited: First Evidence from the Field ." AEA RCT Registry. June 10. https://www.socialscienceregistry.org/trials/4283/history/47860
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2019-06-07
Intervention End Date
2019-06-30

Primary Outcomes

Primary Outcomes (end points)
y_i: Amount of money donated to Atmosfair (in Euro)
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
See Pre Analysis Plan
Experimental Design Details
Randomization Method
randomization done in office by a computer
Randomization Unit
individuals
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
6000 individuals
Sample size: planned number of observations
6000 individuals
Sample size (or number of clusters) by treatment arms
1500 individuals
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
We base our power analysis on data from an experiment by Löschel et al. (2013). They find the standard deviation of voluntary purchases of carbon offsets amounts to 849 kg of CO2. We set the significance level to 0.05 and the power level to 0.8. As we split our sample of around 6,000 respondents into four treatment groups, there are 1,500 respondents in each treatment group. Given this parametrization, the minimum detectable treatment effect (in a two-sided test) amounts to the tenth of the standard deviation, which corresponds to some 85 kg of CO2 offsets or, in monetary terms, a contribution of about €2.
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan

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Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials