Context-dependent evaluation of climate change policies: competing policies, knowledge and emotions

Abstract

Climate change policies can compete with policies on other social and environmental problems for limited economic resources. This paper investigates the potential influence of alternative policies on citizens’ preferences for climate change policies. A contingent valuation study was implemented to estimate the impact of observable and unobservable contextual effects of competing polices on climate change valuation. Individuals are also investigated about their endowment of knowledge and emotional reactions to such problems. The results show that citizens’ valuation of climate change policies crucially depends on the context-dependent competing policies. The valuation rises as the number of competing policies increases. This increment becomes economically significant when the competing policies are related to specific problems such as forest fires and development. In addition, the valuation also rises with the amount of knowledge endowed by the individual about the climate change problem, and with the experience of negative emotions such as fear and sadness.

Keywords:

• contingent valuation
• climate change
• emotions
• knowledge
• joint evaluation
• willingness to pay

Disclosure statement

No potential conflict of interest was reported by the authors

Supplemental data

Supplemental data for this article can be accessed here.

Notes

1. Experts were selected colleague professors in environmental and social sciences. There was a high degree of agreement among experts. For a review of how to employ experts to recode verbal protocols or open ended questions see Chi (1997), Shkedi (2004), Berg, Lune, and Lune (2004), Hopkins and King (2010) and King, Hopkins, and Lu (2012).

2. A detailed discussion of the methods and different alternatives to measure informational levels quantifying qualitative data, and advantages and limitations of each alternative, can be found in Hoffman (1987), Cooke and McDonald (1987) and Evans (1988).

3. The full questionnaire is available from authors upon request.

4. Several vehicle payments were tested in the qualitative phase of the study. This pre-survey analysis showed that using taxes in this specific context significantly reduced the number of protest answers and did not affect the distribution of responses to the experiment for “non-protest” responses.

5. It should be noted that this design for the joint valuation decision frame, based on different payment vehicles for each of the policy issues, was not purported to estimate the relative values of all the policy issues discussed in the interviews, but to investigate how the value of a climate change policy might be affected by the consideration of alternative policy issues.

6. However, since this was not possible for the issue of terrorism we decided to utilize a general consumption good with similar market value to the other goods in the experiment.

7. The random design of the experiment and the use of a bayesian framework to analyze the data guaranteed sampling errors of 3%.

8. A more detailed technical explanation of the econometric model and estimation algorithm can be found in Appendix 2 (online supplemental data).

9. There were 30 protest responses identified in the sample. These are characterized as individuals who declined to pay for any policy because they did reject the valuation scenario for reasons different to low valuation of the policies. The most common responses in this group were related with the government being corrupt and believing that the money would go somewhere else. The question to identify protest responses (i.e., zero WTP motivation) was put to the individual after all valuation questions were answered in the joint valuation treatments.

10. A reviewer raised the question of whether these results can be partially explained by respondents considering that some policies are global rather than local. The qualitative analysis did not show any evidence of this behavior. However, since the experiment was not designed for this, the statistical power of any hypothesis testing on this matter would be very low. Further research focusing on the impact of local vs. global competing policies can be of interest.

11. A general description of GS and its application in Econometrics can be found in Greene (2003).

Additional information

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The authors received financial support for the research from the Spanish Government (Ministerio de Economía y Competitividad) under the research program ECO2011-30365.