Effects of fairness principles on willingness to pay for climate change mitigation
Despite the shift from multilateral negotiations on legally binding mitigation commitments to the decentralized nonbinding Intended Nationally Determined Contributions (INDCs) approach in global climate policy, governments and other stakeholders continue to insist that fairness principles guide the overall effort. Key recurring principles in this debate are capacity and historical responsibility. To keep global warming within the internationally agreed 2 °C limit, many countries will have to engage in more ambitious climate policies relative to current INDCs. Public support will be crucial in this respect. We thus explore the implications of different fairness principles for citizens’ preferences concerning burden sharing in climate policy. To this end, we implemented an online experiment in which participants (N = 414) played an ultimatum game. Participants were tasked with sharing the costs of climate change mitigation. The aim was to examine how participants’ willingness to pay for mitigation was influenced by capacity and historical responsibility considerations. The results show that fairness principles do have a strong effect and that participants applied fairness principles differently depending on their position at the outset. It turns out that participants paid more attention to other players’ capacity and historical responsibility when proposing a particular cost allocation and more attention to their own capacity and responsibility when responding to proposals by others. These and other findings suggest that framing climate policy in terms of internationally coordinated unilateral measures is likely to garner more public support than framing climate policy in terms of a global bargaining effort over the mitigation burden.
KeywordsClimate Policy Ultimatum Game Historical Responsibility Mitigation Cost Burden Sharing
The research for this article was funded by the ERC Advanced Grant ‘Sources of Legitimacy in Global Environmental Governance’ (Grant 295456) and supported by ETH Zürich. We are grateful to Robert Gampfer, Mike Hudecheck, Vally Koubi, Liam McGrath, Lionel Miserez, Irina Shaymerdenova, and Florian Schmidt.
- Andreoni J, Miller J (2002) Giving According to GARP: An Experimental Test of the Consistency of Preferences for Altruism. Econometrica 70(2):737–753Google Scholar
- Balietti, S (2016). nodeGame: real-time, synchronous, online experiments in the browser. Behav Res Methods: 1–20Google Scholar
- Barrett S (2003) Environment and statecraft: the strategy of environmental treaty-making. Oxford University PressGoogle Scholar
- Bolton GE, Ockenfels A (2000) ERC: A theory of equity, reciprocity, and competition. Am Econ Rev 90:166–193Google Scholar
- Buchan NR, Grimalda G, Wilson R, Brewer M, Fatas E, Foddy M (2009) Globalization and human cooperation. Proc Natl Acad Sci 106(11):4138–4142Google Scholar
- Fehr E, Schmidt KM (1999) A Theory of Fairness, Competition, and Cooperation. The Quarterly J of Econ 114(3):817–868Google Scholar
- Fuglestvedt JS, Kallbekken S (2016) Climate responsibility: fair shares? Nat Clim Chang 6:19–20Google Scholar
- Gintis H, Bowles S, Boyd R, Fehr E (2003) Explaining altruistic behavior in humans. Evol Hum Behav 24(3):153–172Google Scholar
- Huff C, Tingley D (2015) Who are these people? Evaluating the demographic characteristics and political preferences of MTurk survey respondents. Res & Polit 2:1–12Google Scholar
- Paolacci G, Chandler J, Ipeirotis PG (2010) Running experiments on Amazon Mechanical Turk. Judgm Decis Mak 5:411–419Google Scholar
- Ramsay, K. W., & Signorino, C. S. (2009). A statistical model of the ultimatum game. University of RochesterGoogle Scholar