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Agriculture is a major source of greenhouse gas emissions but has largely been exempt from stringent climate change mitigation policies, often due to concerns about resistance from the sector. With Denmark introducing the world’s first CO 2 -equivalent (CO 2 e) tax on agricultural emissions, this paper provides representative evidence of farmers’ beliefs about its impacts and examines whether providing expert-predicted impacts can causally influence these beliefs and acceptance of the tax. Using a randomized survey experiment with 981 Danish farmers, we find a widespread overestimation of the tax’s impacts on production, employment, and land value, with 94–97 % of farmers expecting the impacts to be up to three times larger than expert-predicted estimates. Providing an expert-predicted impact reduces these perception gaps, with effects varying according to the tax’s stringency, size of belief gaps, and farm characteristics such as size and type. However, our results also indicate that, in some cases, belief updating may be muted or even contrary to the information provided, consistent with behavioral theories beyond the Bayesian framework. We also find that the belief revisions can translate into greater acceptance of the tax, although these effects vary with tax stringency, initial belief gaps, and farm characteristics. Our findings suggest that designing acceptable climate policies for agriculture may require not only expert information but also targeted communication and complementary measures that account for farmers’ diverse characteristics and perceptions.
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Zemo et al. (2026) studied this question.
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