GHG emission abatement around the zero reference point

Last registered on October 07, 2026

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Pre-Trial

Trial Information

General Information

Title

GHG emission abatement around the zero reference point

RCT ID

AEARCTR-0019497

Initial registration date

October 06, 2026

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 07, 2026, 11:15 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

Name

Christian Friedrich

Affiliation

Universität Mannheim

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Other Primary Investigator(s)

PI Name

Christian Peters

PI Affiliation

University of Wisconsin - Madison

Contact Investigator

PI Name

Marco Meier

PI Affiliation

Independent

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Additional Trial Information

Status

In development

Start date

2026-10-05

End date

2026-10-30

Keywords

Behavior, Environment & Energy, Finance & Microfinance

Additional Keywords

JEL code(s)

Secondary IDs

Prior work

This trial is based on or builds upon one or more prior RCTs.

Abstract

Economies around the world are increasingly setting zero-threshold emissions targets. To achieve zero-threshold emissions, market mechanisms, such as emission trading systems, encourage emission reductions where they are the most cost-efficient. We investigate whether salient sustainability achievements around reference points, such as zero-threshold emissions, serve as heuristic cues for retail investors making investment decisions in such market environments. Based on theory on heuristic decision-making, we predict that retail investors are more likely to invest in a bond disclosing emissions achieving the zero-reference point, even when the emission abatement behind this achievement is more costly than the current market price for abatement. We aim to collect process evidence for reference points reducing decision-making effort by combining different reference points with a separate versus joint evaluation of investment alternatives. We use evidence from previous experiments to calibrate power calculations and exclude possibly confounding decision elements.

External Link(s)

Registration Citation

Citation

Friedrich, Christian, Marco Meier and Christian Peters. 2026. "GHG emission abatement around the zero reference point." AEA RCT Registry. October 07. https://doi.org/10.1257/rct.19497-1.0

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Experimental Details

Interventions

Intervention(s)

We use a full-factorial design and present participants with one of four experimental variants based on varying two manipulations:
Manipulation 1: Reference point: the reference point of the lower-emission bond can either be (i) zero-threshold or (ii) positive-residual emissions.
Manipulation 2: Evaluation type: We design the evaluation of information to be either a (i) separate or (ii) joint evaluation of the investment options.

Details can be found in the supporting document.

Intervention Start Date

2026-10-05

Intervention End Date

2026-10-30

Primary Outcomes

Primary Outcomes (end points)

Our key outcome variable is the investment decision participants make, which we measure as (i) the average reponse, on a scale from 0-100, to three items eliciting participants' willingness to invest in Bond A (see supporting document for the items) and (ii) money allocated to Bond A in an allocation task.

Details can be found in the supporting document.

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

(1) The average response, on a scale from 0-100, to three items eliciting participants' willingness to invest in Bond A MINUS the average response, on a scale from 0-100, to three items eliciting participants' willingness to invest in Bond B.
(2) A dummy variable for whether the participant allocated any money to Bond A.
(3) The average response, on a scale from 0-100, to three items eliciting participants' willingness to invest in removal offsets
(4) The money allocated to removal offsets in an allocation task
(5) The share of a participant's available return allocated to removal offsets in an allocation task
(6) A dummy variable for whether the participant allocated any money to removal offsets.
(7) issuer-channel abatement = 1.5 x (allocation to A / 10,000 GBP)
(8) market-based abatement = allocation to offset / 120 GBP
(9) financial opportunity cost for each abatement channel
(10) reference-point focality index calculated as the average of two reference-point items (see supporting document)
(11) integrated-comparison index calculated as the average of two comparison items (see supporting document)
(12) time spent on willingness to invest assessments
(13) time spent on allocation task
(14) allocation revisions
(15) human-coded (based on blinded coding by several human coders) of whether written justification for decisions mentioned
• net zero / the zero reference point
• the return difference
• explicit A vs. B comparison
• opportunity cost
• offsets / 120 GBP per ton
• using the extra return from B to offset emissions

Secondary Outcomes (explanation)

Experimental Design

We share a link to our online survey, which is fully presented in the supporting document, via Prolific. Participants are paid a flat participation fee according to Prolific policy of 2.5 GBP. Participants who click on the link are randomly assigned one of our treatments and fill in the survey on their personal device. We run the study, and randomization, on OTree.

Experimental Design Details

Not available

Randomization Method

Randomization is done by a computer through the OTree software.

Randomization Unit

Individual

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

600 individuals

Sample size: planned number of observations

600 individuals

Sample size (or number of clusters) by treatment arms

approximately 150 individuals

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

All minimum detectable effect sizes are based on a 5% significance level and an 80% power level. We plan to conduct full-factorial ANOVAs with numerator degrees of freedom of 1 for all tests (main effects and interactions) and four groups (2 x 2 full-factorial analysis). We also plan to run a planned contrast test, which we analyze as a one-way ANOVA with a two-level factor. We express minimum detectable effect sizes as Cohen's f. Based on calculations with G*Power 3.1.9.7, our minimum detectable effect size is 0.1146 for all mentioned analyses. We have some data from previous experiments to gauge expectations of effect sizes. The previous experiment explored a similar reference point manipulation, but may have introduced design features that exaggerated effect sizes, which is why we expect somewhat smaller realized effect sizes. The observed effect size was 0.1515 (F = 7.34, df1,2 = [1, 320]). Moreover, the experiment also had an accompanying manipulation for the planned contrast test, but we expect our manipulation to be more subtle, which is why we expect much smaller realized effect sizes. The observed effect size was 0.1686 (F = 9.15, df1,2 = [1, 322]).

Supporting Documents and Materials

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