In our study, a conjoint experiment, also known as stated preference choice experiment, consists of respondents choosing between one of two carbon taxation proposals with randomly assigned attribute values. Participants choose which of the pair of proposals they support and rate these proposals, on a scale of 1 (fully oppose) to 7 (fully support), five different times. By randomly manipulating the values of each attribute within a proposal, we are able to estimate a variety of quantities of interest. First, we can estimate the causal effect of attribute values upon the choice of proposal, known as the average marginal component effect (AMCE) (38), relative to some baseline. Second, as the conjoint design shares similarities to factorial designs, we can then measure the causal effect of attribute values upon the average level of support for a carbon tax policy.

For our conjoint experiment, participants were asked to choose between randomly assigned policy proposals whose characteristics differ along a set of attributes: cost, exemptions for domestic or foreign firms, and participation by other countries. Respondents were further randomly assigned whether or not to receive an additional attribute in their conjoint experiment about revenue usage. Study participants were then provided background information on each of the attributes, describing their relevance to the design of a carbon tax. The conjoint experiment then consisted of respondents being shown sets of two proposed carbon taxes, side by side, where the values on specific policy attributes are manipulated and randomly assigned. Participants then chose which policy they prefer and noted their level of support for each proposed carbon tax on a Likert scale of 1 to 7. They performed this task by choosing between and rating two randomly generated carbon taxes five times in total. The 3620 and 3640 participants in Germany and the United States, respectively, thus generate information on their support levels for a total of 36,200 and 36,400 hypothetical carbon taxes, respectively (five rounds times two proposals, times the number of study participants).

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