EU-wide survey to investigate the impact of lacking international cooperation and individual moralisation on climate policy attitudes

Collectively shared belief distortions or misperceptions and their implications have gained increasing attention by economists throughout the last decade. In this work we analyse the consequences of policy-related belief distortions for the case of climate change, a collective action problem of global scale where policy narratives are pervasive. We do so by surveying 2,000 households in each of the largest 24 EU member states (48,000 households in total). As part of this survey we conduct two experiments: (1) a choice experiment with randomized information treatment to analyse the effect of a climate policy narrative related belief distortions and updates, and (b) an incentivized choice experiment with 50% of the sample to elicit willingness to pay for climate action and how moralisation of attitudes related to the environment and paternalism correspond with actual behaviour.

External Link(s)

Registration Citation

Citation

Ockenfels, Axel et al. 2023. "EU-wide survey to investigate the impact of lacking international cooperation and individual moralisation on climate policy attitudes." AEA RCT Registry. September 04. https://doi.org/10.1257/rct.12031-1.0

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

Intervention Start Date

2023-08-04

Intervention End Date

2023-09-08

Primary Outcomes

Primary Outcomes (end points)

- attitudes and their moralisation related to normative statements about environmentalism, paternalism, and use-of-markets for climate policy
- willingness to pay for compensation of GHG emissions, willingness to impose respective constraints on the choice of others
- change of climate policy attitudes when learning about lack of international cooperation to address climate change
- support of global carbon markets / the EU Emission Trading System (EU ETS) in the frame of capacity to facilitate international cooperation

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

Secondary Outcomes (explanation)

Experimental Design

See Pre-Analysis Plan

Experimental Design Details

Randomization Method

Randomization done in office by a computer

Randomization Unit

individual

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

48,000 individuals

Sample size: planned number of observations

48,000 individuals

Sample size (or number of clusters) by treatment arms

24,000 individuals

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

We are not aware of similar studies that analyse the effect of sobering information on a continuous outcome variable, so we rely on relatable previous work by one of the co-authors (Andor et al., 2018). It surveys German households about the share the government should assign to a range of federal tasks, including environmental issues. The mean share of the budget for environmental purposes amounts to 16.5%, and the standard deviation (σ_y) is 6.74. To assess the minimum effect (MDE, δ) we can detect, we follow Djimeu & Houndolo (2016). We use a standard significance level of α=0.05 and a power of β=0.8, resulting in t_1=1.96 and t_2=0.84. As we randomly split the sample into two groups, P=0.5. The overall sample size is n=48,000. The resulting MDE for the entire sample is δ=0.172 percentage points. As we are also interested in the MDE per country, we repeat the calculation with n=2,000 (assuming that σ_y is identical across the countries), which results in δ=0.844 percentage points.

Supporting Documents and Materials

IRB