Carbon tax and traffic lights carbon labels to reduce consumers’ basket carbon footprint

In a web platform that reproduces a shop that sells food products, we investigate whether it is possible to induce consumers to reduce the carbon footprint of their basket by using monetary incentives (a carbon tax in our case) and/or non-monetary incentives (traffic lights carbon labels in our case).
The objective of our research is to investigate whether a carbon tax and a traffic lights mechanism implemented on food products are, first, efficient in encouraging consumers to reduce the carbon footprint of their basket of food and, second, whether these two types of incentives are complement (i.e., their joint effect is stronger compared to their effect when used separately) or substitutes (i.e., their joint effect is weaker compared to their effect when used separately).

External Link(s)

Registration Citation

Citation

Ambec, Stefan et al. 2021. "Carbon tax and traffic lights carbon labels to reduce consumers’ basket carbon footprint." AEA RCT Registry. December 14. https://doi.org/10.1257/rct.8676-1.0

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

Respondents are invited to connect on a web platform that reproduces an online shop and asked to select food products that they would choose in real life. Our first outcome of interest is therefore their choice of food products.
In addition to a control group, we will test the implementation of a carbon tax computed according to the carbon content of food products (with two levels of tax) and of the use of traffic lights labels (the colours indicate the carbon content of food products).
We will implement these instruments either separately or combined.

Intervention Start Date

2021-12-14

Intervention End Date

2022-02-28

Primary Outcomes

Primary Outcomes (end points)

We will pay specific attention to the basket carbon footprint of each respondent, as well as the type of food they have chosen.

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

We will also collect socio-economic information, information on food habits, knowledge on food carbon footprint, attitudes towards a carbon tax implemented on food, and environmental attitudes.

Secondary Outcomes (explanation)

Experimental Design

First, respondents will connect to a webplatform that reproduces an online shop that sells food products.
There will be 6 different groups:
i) a control group where subjects constitute their basket of food without any incentives (carbon tax or traffic lights) being implemented,
ii) a treatment where we implement traffic lights (use of colors depending on the product carbon footprint – green, orange, and red),
iii) a treatment in which we modify food products’ prices with a carbon tax set at €80/ton of CO2,
iv) a treatment where we implement both the carbon tax set at €80/ton of CO2 and traffic lights,
v) a treatment where we implement a carbon tax set at €250/ton of CO2, and
vi) a treatment where we implement both the carbon tax set at €250/ton of CO2 and traffic lights.
Respondents will be randomly allocated to one group (treatment) only.

When no tax is implemented, respondents will be endowed €40 for their expenditures.
When a carbon tax at €80/ton of CO2 is implemented, respondents will be endowed €43 for their expenditures to control for income effects (the computation is based on the results obtained in Aysegul Kanay's thesis).
When a carbon tax at €250/ton of CO2 is implemented, respondents will be endowed €48 for their expenditures to control for income effects (the computation is based on the results obtained in Aysegul Kanay's thesis).

Second, subjects answer a questionnaire to collect socio-economic information, information on food habits, knowledge on food carbon footprint, attitudes towards a carbon tax implemented on food, and environmental attitudes.

The experiment is incentivized and subjects know the procedure: for their participation, they all receive a €10 gift voucher. In addition, 1 out of 10 in each group will receive the basket of food he/she chose in the shop.

Subjects are recruited from the general population by the survey company ENOV.

Experimental Design Details

Randomization Method

Randomization made by the survey company ENOV who recruits the subjects

Randomization Unit

Individual

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

N.A.

Sample size: planned number of observations

We will recruit 100 subjects (minimum 18 years old) in each group. The experiment will therefore have a final sample of 600 subjects.

Sample size (or number of clusters) by treatment arms

100 subjects per treatment

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

Supporting Documents and Materials

IRB

Institutional Review Boards (IRBs)

IRB Name

TSE Research Ethics Committee for Experimental Research

IRB Approval Date

2021-12-10

IRB Approval Number

N/A

Analysis Plan

Post-Trial

Post Trial Information

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Intervention

Is the intervention completed?

Data Collection Complete

Data Publication

Is public data available?

Program Files

Reports, Papers & Other Materials

Carbon tax and traffic lights carbon labels to reduce consumers’ basket carbon footprint

Pre-Trial

General Information

Locations

Primary Investigator

Other Primary Investigator(s)

Additional Trial Information