Economic vs. Generational inequality: A survey experiment of intra- and intergenerational cleavages in support for climate change mitigation policies

Last registered on December 14, 2022

Pre-Trial

Trial Information

General Information

Title
Economic vs. Generational inequality: A survey experiment of intra- and intergenerational cleavages in support for climate change mitigation policies
RCT ID
AEARCTR-0009745
Initial registration date
July 14, 2022

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 19, 2022, 4:30 PM EDT

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

Last updated
December 14, 2022, 9:46 AM EST

Last updated is the most recent time when changes to the trial's registration were published.

Locations

Region

Primary Investigator

Affiliation
Universität Konstanz

Other Primary Investigator(s)

PI Affiliation
Universität Konstanz
PI Affiliation
Universität Konstanz
PI Affiliation
Universität Konstanz

Additional Trial Information

Status
Completed
Start date
2022-11-10
End date
2022-12-05
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
We examine this trade-off between the immediate inequality
citizens face from climate mitigation policies (in terms of carbon trading) vs. the
long-term generational inequalities future generations will face. We assess this trade-
off using a between-subjects survey experiment, fielded among German citizens.
External Link(s)

Registration Citation

Citation
Bellani, Luna et al. 2022. "Economic vs. Generational inequality: A survey experiment of intra- and intergenerational cleavages in support for climate change mitigation policies." AEA RCT Registry. December 14. https://doi.org/10.1257/rct.9745-2.6
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Experimental Details

Interventions

Intervention(s)
Between-subjects survey experiment with vignettes, in which respondents are primed to consider economic vs. generational inequality concerns relating to climate change mitigation policies.
Intervention Start Date
2022-11-10
Intervention End Date
2022-12-05

Primary Outcomes

Primary Outcomes (end points)
After the survey experiment, respondents are first asked: ”Do you support such a carbon taxation
policy?”. This is on a Likert-scale from 1 (”Do not agree at all”) to 5 (”Fully agree”). In order
to check whether respondents’ disagreement with the policy might be due to it not aiding enough
in climate change mitigation, we additionally ask respondents: ”Do you think the suggested CO2
taxation is:” with the answer options ”Too high”, ”exactly right”, ”too low”, and lastly ”Don’t
know”
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We implemented a 2*4 between-subject experiment research design. Each
group of respondents was shown an information treatment consisting of three main parts: 1) an introduction text about a current climate change mitigation policy in Germany, 2) a randomisation into an elite-cue treatment group (vs. control group with no extra information), 3) a randomisation into one of 4 treatment groups (3 inequality treatment groups and one control group).
Experimental Design Details
Randomization Method
Randomisation by computer.
Randomization Unit
Randomization at the individual level.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
Estimated to be 6000 individuals.
Sample size: planned number of observations
6000 individuals.
Sample size (or number of clusters) by treatment arms
6000 individuals.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Power analyses based on results from quantitative pretest Hypothesis 1: Respondents are less likely to support the Co2 policy if they receive the economic treatment, as compared to the control group. Power analyses based on pretests of our study design show that we can detect a change of half a point on our answer scale between framing groups with a power of 100% at the conventional statistical significance level of 5% and 1%. Hypothesis 2: Respondents are more likely to support the Co2 policy if they receive the generational treatment, as compared to the control group. Power analyses for this hypothesis shows that we can detect a change of half a point on our answer scale between framing groups with a power of 20% at the conventional statistical significance level of 5%. Hypothesis 3: Respondents are less likely to support the Co2 policy if they receive the economic treatment, as compared to the generational treatment. Power analyses for H3 shows that we can detect a change of half a point on our answer scale between framing groups with a power of 99.8% (95.3%) at the conventional statistical significance level of 5% (and 1%). Order effect hypotheses: Hypothesis 4: Respondents are more likely to support the Co2 policy if they receive the generational treatment, as compared to the mixed treatment group. Power analyses for H4 shows that we can detect a change of half a point on our answer scale between framing groups with a power of 99.9% at the conventional statistical significance level of 5%. Hypothesis 5: Respondents are less likely to support the Co2 policy if they receive the economic treatment, as compared to the mixed treatment group. Power analyses for H5 shows that we can detect a change of half a point on our answer scale between framing groups with a power of 13.3% at the conventional statistical significance level of 5%. Hypothesis 6: There is an order effect in whether respondents see the economic or the generational treatment first. Power analyses for H5 shows that we can detect a change of half a point on our answer scale between framing groups with a power of 5.2% at the conventional statistical significance level of 5%. Court treatment hypothesis: Hypothesis 7: Respondents are less likely to support the Co2 policy if they receive the court treatment, as compared to the control group. Power analyses for H7 shows that we can detect a change of half a point on our answer scale between framing groups with a power of 100% at the conventional statistical significance level of 5% and 1%. See documentation for full information and results from the power analyses.
Supporting Documents and Materials

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IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
Yes
Intervention Completion Date
December 02, 2022, 12:00 +00:00
Data Collection Complete
Yes
Data Collection Completion Date
December 02, 2022, 12:00 +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
6,319
Was attrition correlated with treatment status?
No
Final Sample Size: Total Number of Observations
6,137
Final Sample Size (or Number of Clusters) by Treatment Arms
3,172 with Court treatment: 770 (Treatment 1) Generation; 824 (Treatment 2) Economic; 803 (Treatment 3) Generation + Economic (of the order effects groups are 420 Generation + Economic and 383 are Economic + Generation); 775 (control) No info. 3,147 without court treatment (control group): 810 (Treatment 1) Generation; 747 (Treatment 2) Economic; 781 (Treatment 3) Generation + Economic (of the order effects groups are 377 Generation + Economic and 404 are Economic + Generation); 809 (control) No info.
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
No
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials