Climate Change Attitudes in Oil-Dependent Economies

Last registered on December 26, 2024

Pre-Trial

Trial Information

General Information

Title
Climate Change Attitudes in Oil-Dependent Economies
RCT ID
AEARCTR-0015049
Initial registration date
December 25, 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
December 26, 2024, 12:19 PM EST

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

Locations

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Primary Investigator

Affiliation
New Economic School

Other Primary Investigator(s)

Additional Trial Information

Status
In development
Start date
2024-12-30
End date
2025-03-26
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This paper examines attitudes toward climate change in Russia, a fossil fuel-dependent economy. We conduct a survey based on a modified version of Dechezleprêtre et al. (2022), which did not include Russia in its original scope. While retaining the core structure of the original survey, we introduce three novel components. First, we explore within-country variation in public knowledge, opinions, and support for climate policies, with a particular focus on differences between fossil fuel-rich and fossil fuel-poor regions. Second, we expand the original set of randomized treatments by incorporating informational videos on various aspects of the 2023 Presidential Decree, which outlines the government’s official stance on climate change. Third, we investigate public trust in experts, including economists. This study aims to provide insights into climate attitudes, policy preferences, and effective communication strategies in oil-dependent economies, which are often expected to resist a swift energy transition.

Dechezleprêtre, Antoine, Adrien Fabre, Tobias Kruse, Bluebery Planterose, Ana Sanchez Chico, and Stefanie Stancheva. “Fighting Climate Change: International Attitudes Toward Climate Policies,” NBER Working Paper 30265, 2022.

Registration Citation

Citation
Toews, Gerhard. 2024. "Climate Change Attitudes in Oil-Dependent Economies." AEA RCT Registry. December 26. https://doi.org/10.1257/rct.15049-1.0
Experimental Details

Interventions

Intervention(s)
Just as in Dechezleprêtre et al. (2022), we run an online survey. We recruit participants through a professional survey company ensuring that our sample is representative by gender, age and location, in fossil fuel rich and poor regions in Russia and random treat them with either pedagogical or public official endorsement videos. To be eligible, subjects must be adults (age 18+) and must be Russian citizens.
Intervention Start Date
2024-12-30
Intervention End Date
2025-03-26

Primary Outcomes

Primary Outcomes (end points)
We are interested in people's view on and understanding of climate change, as well as support for and views on climate mitigation policies, and their willingness to share the burden to address climate change.
Primary Outcomes (explanation)
Just as in Dechezleprêtre et al. (2022), we will use a lot the raw answers to the policy knowledge and perception questions in the analysis, but we will also construct various indexes that summarise the participants knowledge and views.

Secondary Outcomes

Secondary Outcomes (end points)
We are interested in the heterogeneity generated by whether individuals are located in fossil fuel poor or fossil fuel rich regions as well as people's response to the treatment videos.

We are also interested in trust towards scientific results.
Secondary Outcomes (explanation)
We have identified the top 10 regions in Russia to be rich in fossil fuels: Tyumen Oblast, Khanty-Mansi Autonomous Okrug, Yamalo-Nenets Autonomous Okrug, Kemerovo Oblast, Republic of Tatarstan, Irkutsk Oblast, Krasnoyarsk Krai, Sacha Republic, Sakhalin Oblast and Orenburg Oblast.

We are in particular interested in different scientific fields, differentiating between economists, geophysicist and climatologists.

Experimental Design

Experimental Design
We randomize the information provided to respondents, with 5 out of 6 respondents being assigned to one of the treatment videos, while 1 out of 6 individuals is assigned to the control group.
Experimental Design Details
Not available
Randomization Method
As mentioned above, the randomization is provided by random number generator algorithms by the surveying company.
Randomization Unit
Randomization is at the unit of individuals.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
0
Sample size: planned number of observations
Up to 2400 individuals
Sample size (or number of clusters) by treatment arms
Four hundred individuals will be in the control group, while each of the five different videos (5 different treatments) will be shown to a group of 400 individuals.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
NEW ECONOMIC SCHOOL COMMITTEE ON THE USE OF HUMAN SUBJECTS IN RESEARCH
IRB Approval Date
2024-12-14
IRB Approval Number
А1214-02
Analysis Plan

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