Experimental Design
We collected our data in December 2020 using the commercial survey company Respondi. This survey company maintains a panel of German respondents to whom it emailed our survey links based on certain socioeconomic characteristics. In addition to the link, the email contained information about the duration of the survey and the payment for fullparticipation. Those panelists who responded to the email were first directed to a welcome page before they needed to answer three screening questions that ensured our sample is representative in terms of age, gender, and income.
Our survey consists of five sections, three treatment groups and one control group.
First, we ask respondents several questions about basic socio-demographic characteristics, including their gender, age, household income, level of education, employment status, marital status, number of children, migration background, state of residence, and size of the place of residence. Moreover, we collect data on respondents’ political attitudes including their political affiliation, a self-assessment of
their political knowledge as well as their trust in the government.
Next, we give our respondents a brief introduction on what carbon pricing is and inform them about the introduction of the German carbon price. We then closely follow Ferrario & Stantcheva (2022) and gather respondents’ first-order considerations by asking about the first thoughts, the advantages, and the disadvantages that come to their minds when thinking about the introduction of the German carbon price. To avoid pushing respondents in any direction, we make use of open-end questions and encourage respondents to write as much as they like. Thereafter, we explicitly ask respondents whether they support the introduction of the German carbon price.
In the next part of the survey, we measure respondents’ climate change awareness by asking whether they agree that global warming
exists, that it is (among others) human-caused, that global warming has serious consequences and whether they agree that scientists exaggerate the dangers of climate change. We, furthermore, ask how worried they are about global warming.
Subsequently, we randomly assign respondents to a control group or one of three treatment groups. Each of the treatment groups receives information about a different aspect of carbon pricing in form of a written text and an accompanying graphical illustration. The control
group receives no information.
The Efficiency treatment first explains that carbon pricing makes emission-intensive behavior more expensive and thus creates a financial burden for both individuals and firms. It, however, also explains the negative external effects of carbon emissions and the idea of the polluter pays principle. Finally, it argues that carbon pricing creates financial incentives to reduce emission-intensive behavior and provides concrete examples
The Redistribution treatment informs respondents about the regressive nature of carbon pricing. It, however, also explains that carbon pricing leads to government revenues that can be used to reverse these disadvantageous distributional effects through, e.g., lump sums or other tax reductions. Moreover, the treatment informs about the federal government’s plans for the use of the revenues from the German carbon price.
The Comparison treatment provides a social information. Specifically, it informs respondents about per capita emission levels in Germany and compares it to other countries such as China, the United States of America, or other European member states. Moreover,
it provides information on the number of European member states that already have a national carbon price in addition to the European Emissions Trading Scheme at the time of the survey. In the final section of our survey, we explore how respondents think about carbon pricing. For this reason, we elicit their perceptions of the efficiency of carbon pricing (will individuals or firms change their behavior?), the distributional implications of carbon pricing (how much will low income households be affected?), and global emission levels and national carbon pricing initiatives (where does Germany rank?). Thus, the questions focus on the dimensions covered in the three information treatments.
Moreover, we ask our respondents again whether they support the introduction of the German carbon price, whether they consider it to be fair, or whether they think carbon pricing is a suitable policy measure to reduce climate change. We also include two "realstakes"
questions to receive alternative measures for respondents’ support. First, we inform the respondents that they take part in a lottery to win 10€. We then ask them how much of their win, they are willing to donate to an organization that promotes emission reductions if they win the lottery. Second, we use a variant of the incentivized coordination game by Krupka & Weber (2013) to elicit respondents’ views on other
people’s support for the German carbon price and thus their perceived social norm.