How personal exposure affects the support for carbon pricing

Last registered on March 07, 2024
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Pre-Trial

Trial Information

General Information

Title
How personal exposure affects the support for carbon pricing
RCT ID
AEARCTR-0012808
Initial registration date
January 10, 2024

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 12, 2024, 3:34 PM EST

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

Last updated
March 07, 2024, 11:29 AM EST

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

Locations

Country
Germany
Region

Primary Investigator

Name
Maike Korsinnek
Affiliation
Macroeconomic Policy Institute
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Other Primary Investigator(s)

PI Name
Jan Behringer
PI Affiliation
Macroeconomic Policy Institute
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PI Name
Lukas Endres
PI Affiliation
Macroeconomic Policy Institute
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Additional Trial Information

Status
Completed
Start date
2024-01-15
End date
2024-02-07
Keywords
Environment & Energy
Additional Keywords
carbon pricing, policy acceptance, perception, survey experiment
JEL code(s)
D83, H23, Q58
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
In 2021, a carbon price was implemented in Germany, targeting emissions in the building and transport sectors to encourage the adoption of low-carbon alternatives. The German government announced using revenues to compensate households via a climate rebate. Previous research suggests that knowledge about financial implications from and acceptance of carbon pricing and rebate schemes remain limited among the general public. In this project, we investigate whether policy acceptance can be improved by providing personalized information regarding costs or rebate amounts.

We conduct a survey experiment with a representative sample of the German population. We randomly assign participants to variants of our experiment that provide them with personalized information either regarding their households’ costs from carbon pricing or rebate amounts.
In the first experiment, we start by eliciting participants’ acceptance of carbon pricing. Next, we ask participants to state their household's additional annual costs for a given carbon price as well as their uncertainty regarding their estimation. A randomly selected treatment group receives quantitative information on their household’s actual costs from carbon pricing, calculated based on previously stated vehicle and energy usage. The remaining participants act as a control group with no further information. The experiment concludes by eliciting all participants’ posterior acceptance of carbon pricing.

Our second experiment starts by providing participants with the personalized cost information when inquiring about their prior acceptance of carbon pricing. Next, we suggest a lump-sum climate rebate of total revenues from carbon pricing, asking participants to state the expected annual payout to their household and their level of uncertainty regarding this estimation. Afterward, participants are randomly selected to receive information on the actual rebate amount for their household given this policy design. The control group receives no additional information. Again, we conclude by eliciting all participants' posterior acceptance of carbon pricing.

We conduct both experiments for the current price of 45€/t CO2 and a projected price of 200€/t CO2 in 2027. Our experiment is followed by additional questions on participants' trust in the government's climate policy decisions and their preferences regarding revenue use of the carbon price.

Our experimental design allows us to identify the causal effect of personalized information provision regarding costs and rebate amounts on policy acceptance of carbon pricing and to investigate how respondents differentially incorporate quantitative information based on their initial misperceptions and uncertainty.
External Link(s)

Registration Citation

Citation
Behringer, Jan, Lukas Endres and Maike Korsinnek. 2024. "How personal exposure affects the support for carbon pricing." AEA RCT Registry. March 07. https://doi.org/10.1257/rct.12808-1.3
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2024-01-15
Intervention End Date
2024-02-07

Primary Outcomes

Primary Outcomes (end points)
policy acceptance
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
trust in government, revenue use
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We conduct a survey experiment among approximately 9600 participants representative of the German population. Prior to our experiment, we ask all participants on a four-point Likert scale how well informed they feel about carbon pricing in Germany and measure their carbon price literacy based on three questions on the policy instrument. We collect additional information about participants’ household size, homeowner status, the size of their dwelling, energy consumption for heating purposes, their household’s vehicle fleet and annual vehicle usage.

We randomly assign participants to variants of our experiment which provide them with personalized information about either their household’s costs from carbon pricing or dividends received from a climate rebate program that pays out carbon pricing revenues on a per capita basis. Both variants are conducted for the current price of 45 €/t of CO2 and a projected price of 200 €/t of CO2 in 2027. Consequently, we have four segments, each including a treatment and a control group of 1200 participants.

The first experiment begins by briefly informing participants about carbon pricing in the building and transport sectors in Germany and eliciting their prior acceptance of carbon pricing on a five-point Likert scale. Next, we ask participants to estimate their household’s additional annual costs from carbon pricing at a given price level and to express their uncertainty regarding their estimation on a five-point Likert scale. 50% of participants are then randomly assigned to receive quantitative information on their household’s actual costs from carbon pricing. Additional heating costs are calculated using the previously collected information on household's annual energy consumption. Additional transportation expenses are inferred from the household's distance traveled and the average fuel consumption of their vehicle fleet. The remaining 50% of participants act as a control group and receive no further information. The experiment concludes by eliciting all participants’ posterior acceptance of carbon pricing on a five-point Likert scale.

The second experiment begins by providing participants with brief information about carbon pricing in the building and transport sectors and personalized information on their household’s additional costs from carbon pricing at a given price level, before eliciting their acceptance of carbon pricing on a five-point Likert scale. Next, we ask them to estimate the dividend received by their household, granted by a lump-sum climate rebate program that pays out all carbon pricing revenues on a per capita basis. We also ask participants to indicate their level of uncertainty regarding this estimation on a five-point Likert scale. 50% of participants are then randomly selected to receive quantitative information on their households’ actual rebate amount. Per capita dividends are calculated based on the latest wave of the German sample survey of income and expenditure which contains information regarding private households’ total consumption of fossil fuels in the building and transport sectors. We redistribute total revenues from carbon pricing on a per capita basis to derive rebate amounts, which are then multiplied with our respondents’ household size. The control group receives no additional information. As in the first experiment, we conclude by eliciting all participants’ posterior acceptance of carbon pricing on a five-point Likert scale.

Both experiments are succeeded by a question about participants’ trust in the government's climate policy on a five-point Likert scale. We also elicit participants’ preferences regarding the use of the carbon pricing revenues by asking them to allocate total revenues from carbon pricing to different categories, including transfers to households, public spending, or tax reductions.
Experimental Design Details
Randomization Method
Randomization was done by the survey institute.
Randomization Unit
individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
9600 individuals
Sample size: planned number of observations
9600 individuals
Sample size (or number of clusters) by treatment arms
Approximately 9600 individuals in total, with around 1200 individuals in each treatment and control group.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan

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