Environmental and Resource Economics

, Volume 38, Issue 1, pp 71–87

Does “No” mean “No”? A protest methodology

OriginalPaper

Abstract

In this paper, we propose a method of identifying and truncating protesters in Contingent Valuation surveys. We propose using a system of Willingness to Pay (WTP) questions that value multiple goods and that use both discrete choice and open-ended questions coupled with multiple questions about protest beliefs administered to the entire sample. Protesters can then be identified because they reject all bids, declare zero on all open-ended questions, and hold protest beliefs. The proposed procedure has been empirically tested on an air pollution data set from Poland, where 27 of the sample was identified as protesters. The adjustment for protesters increased the estimated WTP values by a factor of more than 3.

Keywords

Air quality Contingent Valuation Embedding Protest voters Sequencing 

Abbreviations

CV

Compensated variation

CVM

Contingent valuation methods

DC

Dichotomous choice

OE

Open-ended

WTP

Willingness to pay

References

  1. Arrow K et al (2002) Appendix I: report of the NOAA panel on contingent valuation. In: Cost-benefit analysis, 297–323, Elgar reference collection. International library of critical writings in economics, vol 152. Elgar, Cheltenham, U.K. and Northampton, Mass., distributed by American International Distribution Corporation, Williston, VtGoogle Scholar
  2. Boyle KJ, Welsh MP, Bishop RC (1993) The role of question order and respondent experience in contingent valuation studies. J Environ Econ Manage 25(1):S80–S99CrossRefGoogle Scholar
  3. Cameron TA, James MD (1987) Efficient estimation methods for close-ended contingent valuation surveys. Rev Econ Stat 69(2):269–276CrossRefGoogle Scholar
  4. Cameron TA (1988) A new paradigm for valuing non-market goods using referendum data: maximum likelihood estimation by censored logistic regression. J Environ Econ Manage 15(3):355–79CrossRefGoogle Scholar
  5. Carson, RT, Groves T, Machina MJ (2000) Incentive and information properties of preference questions. Department of Economics, University of California, San Diego, California (www.econ.ucsd.edu/%Ercarson/cgm,pdf)Google Scholar
  6. Council of the European Union (1999) Council Directive 1999/13/EC of 11 March 1999 on the limitation of emissions of volatile organic compounds due to the use of organic solvents in certain activities and installations. Official Journal 29:0001–0022Google Scholar
  7. Dziegielewska DA, Mendelsohn R (2005) Valuing air quality in Poland. Environ Resour Econ 30(2):131–163CrossRefGoogle Scholar
  8. Halstead JM, Luloff AE, ThomasStevens H (1992) Protest bidders in contingent valuation. Northeastern J Agric Resour Econ 21(2):160–169Google Scholar
  9. Hammitt JK, Zhou Y (2006) The economic value of air-pollution-related health risks in china: a contingent valuation study. Environ Resour Econ 33(3):399–423CrossRefGoogle Scholar
  10. Hanemann WM, (1984) Welfare Evaluation in Contingent Valuation Experiments with Discrete Responses. Am J Agric Econ 66(3):182–84CrossRefGoogle Scholar
  11. Hanemann WM, Loomis, J, Kanninen B (1991) Statistical efficiency of double-bounded dichotomous choice contingent valuation. Am J Agric Econ 73(4):1255–63CrossRefGoogle Scholar
  12. Hanemann WM, Kanninen B (1996) The statistical analysis of discrete-response. CV Data, Working paperGoogle Scholar
  13. Huang JC, Smith VK (1998) Monte Carlo benchmarks for discrete response valuation methods. Land Econ 74(2):186–202CrossRefGoogle Scholar
  14. Jorgensen BS, Syme GJ, Bishop BJ, and Nancarrow BE et al (1999) Protest responses in contingent valuation. Environ Resour Econ 14(1):131–50CrossRefGoogle Scholar
  15. Jorgensen BS, Syme GJ (1995) Market models, protest bids, and outliers in contingent valuation. J Water Resour: Plan Manage 121(5):400–402Google Scholar
  16. Jorgensen BS, Syme GJ (2000) Protest responses and willingness to pay: attitude toward paying for storm water pollution abatement. Ecol Econ 33(2):251–265CrossRefGoogle Scholar
  17. Lindsey G (1994) Market models, protest bids, and outliers in contingent valuation. J Water Resour: Plan Manage 120(1):121–129CrossRefGoogle Scholar
  18. McCollum DW, Boyle KJ (2005) The effect of respondent experience/knowledge in the elicitation of contingent values: an investigation of convergent validity, procedural invariance and reliability. Environ Resour Econ 30(1):23–33CrossRefGoogle Scholar
  19. McConnell K (1990) Models for referendum data: the structure of discrete choice models for contingent valuation. J Environ Econ Manage 18(1):19–34CrossRefGoogle Scholar
  20. McFadden D (1974) The Measurement of Urban Travel Demand. J Publ Econ 3(4):303–328CrossRefGoogle Scholar
  21. Markowska A, Zylicz T (1999) Costing an international public good: the case of the Baltic Sea. Ecol Econ 30(2):301–16CrossRefGoogle Scholar
  22. Sutherland RJ, Walsh RG (1985) Effects of distance on the preservation of water quality. Land Econ 61(3):281–291CrossRefGoogle Scholar
  23. Whittington D et al (1992) Giving Respondents Time to Think in Contingent Valuation Studies: A Developing Countries Application. J Environ Econ Manage 22(3):205–225CrossRefGoogle Scholar
  24. Zylicz T, Bateman I, Georgiou S, Markowska A, Dziegielewska D, Turner RK, Graham A, Langford I (1995) The Baltic drainage basin project: contingent valuation of eutrophication damage in the Baltic Sea region. CSERGE, Working PaperGoogle Scholar
  25. Zylicz, T (2000) Costing nature in a transition economy: case studies in Poland. Northampton Mass Edward Elgar Pub, Cheltenham UKGoogle Scholar

Copyright information

© Springer Science+Business Media, Inc. 2007

Authors and Affiliations

  • Dominika A. Dziegielewska
    • 1
    • 3
  • Robert Mendelsohn
    • 2
  1. 1.Center for Energy and Environmental StudiesBoston UniversityBostonUSA
  2. 2.Yale School of Forestry and Environmental StudiesNew HavenUSA
  3. 3.LouisvilleUSA

Personalised recommendations