Public Acceptability of Climate Change Mitigation Policies

Last registered on March 06, 2021


Trial Information

General Information

Public Acceptability of Climate Change Mitigation Policies
Initial registration date
March 04, 2021
Last updated
March 06, 2021, 5:49 PM EST


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Primary Investigator

Harvard University

Other Primary Investigator(s)

PI Affiliation
PI Affiliation
PI Affiliation
PI Affiliation
PI Affiliation
ETH Zürich
PI Affiliation
Harvard University

Additional Trial Information

On going
Start date
End date
Secondary IDs
The project aims to understand how people think about climate change, including what they think about mitigation policies that look to address it. In particular, it aims to study how attitudes on climate change mitigation policies differ between countries.
We want to understand how respondents set priorities to fight climate change; what they think governments can and should do to mitigate climate change; what people think is fair in terms of policies.
Finally, we will provide some information treatments to see to what extent perceptions can change after receiving new information and if such information treatments will have an effect on policy preferences. Thanks to the geographical variation of our data, we will analyze if living in areas more vulnerable to impacts from climate change affects perceptions and preferences for different policies, such as a carbon tax or a green infrastructure program.
External Link(s)

Registration Citation

Boone, Laurence et al. 2021. "Public Acceptability of Climate Change Mitigation Policies." AEA RCT Registry. March 06.
Experimental Details


We run online surveys in six countries. We recruit participants through professional survey companies to ensure that our sample is representative of each country's population along key dimensions - gender, income, and age. To be eligible, subjects must be adults (age 18+) and must be citizens of the country. The surveys will be performed online or on phone.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Support for and views on climate mitigation policies, real outcome (donation to charity), Knowledge of policies, Views on fairness, Cross-country differences
Primary Outcomes (explanation)
We will use a lot of the policy knowledge and perception questions as such, but we also construct various indexes that summarize the support for government intervention on climate issues, the beliefs and knowledge about climate change, the perception of the efficiency costs of climate policies, the fairness of climate policies, the preference for global interventions and so on. We will also construct measures of the misperceptions by subtracting respondents' answers to knowledge questions from the true answer, as well as variables indicating whether a respondent is particularly accurate or inaccurate. In the text analysis, we will construct measures of "topics" and "sentiment" using text analysis tools. Moreover, we will also analyze if those different variables vary a lot across countries.
Finally, we tell respondents that they have been automatically enrolled in a lottery to win a given amount of dollars (depending on the country in which the survey is run). Before they know whether they have won or not, they need to commit to donating none of it, part of it, or all of it to one charity (that fight climate change with projects to reduce the emissions of CO2). We use the amount respondents wish to donate as (real) measure of support for climate change.

Secondary Outcomes

Secondary Outcomes (end points)
In addition to the experimental variables, we are also interested in the heterogeneity of the background characteristics of respondents and will thus look at outcomes by sub-groups as defined by income, age, gender, political affiliation, education level and employment status.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We randomize the information provided to respondents, with some respondents being assigned to a treatment or a control group.
Experimental Design Details
Not available
Randomization Method
The randomization is done by the survey software (Qualtrics).
Randomization Unit
We randomize participants in control and treatment groups within each country.
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
6 countries
Sample size: planned number of observations
12,000 respondents
Sample size (or number of clusters) by treatment arms
Around 588 respondents for the control group in each country, around 496 respondent for each of the two videos only in each country, around 419 for the two videos in each country.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)

IRB Name
Harvard IRB
IRB Approval Date
IRB Approval Number