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Climatic Change

, Volume 109, Issue 3–4, pp 417–436 | Cite as

Household perceptions of climate change and preferences for mitigation action: the case of the Carbon Pollution Reduction Scheme in Australia

  • Sonia AkterEmail author
  • Jeff Bennett
Open Access
Article

Abstract

The study aims to reveal Australian households’ perceptions of climate change and their preferences for mitigation action. A web-based survey was conducted in November 2008 in which over 600 households from the state of New South Wales were asked for their willingness to bear extra household expenditure to support the ‘Carbon Pollution Reduction Scheme’, an emissions trading scheme proposed by the Australian government. The results of the study can be summarized in four key findings. First, respondents’ willingness to pay for climate change mitigation is significantly influenced by their beliefs of future temperature rise. Support for the policy increased at a decreasing rate as the perceived temperature change rose. Second, perceptions of policy failure have a significant negative impact on respondents’ support for the proposed mitigation measure. The higher the perceived likelihood that the measure would not deliver any outcome, the lower was the likelihood that respondents would support the policy. Third, respondent preferences for the proposed policy are influenced by the possibility of reaching a global agreement on emissions reduction. Sample respondents stated significantly higher values for the policy when the biggest polluting countries implement a similar scheme. Finally, respondents’ willingness to take action against climate change, both at the national and household level, is found to be influenced by their level of mass-media exposure. Particularly, those respondents who watched ‘An Inconvenient Truth’ were significantly more likely to act for climate change mitigation than others.

Keywords

Contingent Valuation Climate Change Mitigation Contingent Valuation Study Propose Mitigation Measure Unmitigated Climate Change 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© The Author(s) 2011

Authors and Affiliations

  1. 1.Crawford School of Economics and Government (Building 132)The Australian National UniversityCanberraAustralia

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