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Bid Design Effects in Multiple Bounded Discrete Choice Contingent Valuation

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  • Christian Vossler
  • Gregory Poe
  • P. Welsh
  • Robert Ethier

Abstract

A potential concern in “multiple bounded discrete choice” contingent valuation surveys – where the respondent is asked to express voting certainty, rather than a simple yes or no, on a large number of payment amounts (bids) – is whether responses are influenced by the particular position of bids in the bid-voting panel rather than solely on the respondent’s willingness to pay (WTP). For instance, respondents may systematically state they would pay the first few bid amounts and not pay all subsequent bids – regardless of the actual dollar values. Such systematic bid design effects would suggest that this method does not provide a valid measure of WTP. Using a split-sample survey, we compare responses to three different bid arrays that have an identical minimum bid, maximum bid, and number of bids. Using nonparametric estimation techniques, we find that estimated WTP distributions and corresponding welfare measures are not statistically different across survey samples. Copyright Kluwer Academic Publishers 2004

Suggested Citation

  • Christian Vossler & Gregory Poe & P. Welsh & Robert Ethier, 2004. "Bid Design Effects in Multiple Bounded Discrete Choice Contingent Valuation," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 29(4), pages 401-418, December.
    • Handle: RePEc:kap:enreec:v:29:y:2004:i:4:p:401-418
    DOI: 10.1007/s10640-004-9457-2
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    References listed on IDEAS

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    1. Kahneman, Daniel & Ritov, Ilana & Schkade, David A, 1999. "Economic Preferences or Attitude Expressions?: An Analysis of Dollar Responses to Public Issues," Journal of Risk and Uncertainty, Springer, vol. 19(1-3), pages 203-235, December.
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    Cited by:

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    2. Eugene Frimpong & Jamie Kruse & Gregory Howard & Rachel Davidson & Joseph Trainor & Linda Nozick, 2019. "Measuring Heterogeneous Price Effects for Home Acquisition Programs in At‐Risk Regions," Southern Economic Journal, John Wiley & Sons, vol. 85(4), pages 1108-1131, April.
    3. Cooper, Bethany & Crase, Lin & Burton, Michael P., 2010. "Urban Water Restrictions: Attitudes and Avoidance," 2010 Conference (54th), February 10-12, 2010, Adelaide, Australia 58892, Australian Agricultural and Resource Economics Society.
    4. Simon Chege Kimenju & Hugo De Groote, 2008. "Consumer willingness to pay for genetically modified food in Kenya," Agricultural Economics, International Association of Agricultural Economists, vol. 38(1), pages 35-46, January.
    5. Ahtiainen, Heini & Pouta, Eija & Zawadzki, Wojciech & Tienhaara, Annika, 2023. "Cost vector effects in discrete choice experiments with positive status quo cost," Journal of choice modelling, Elsevier, vol. 47(C).
    6. Göran Bostedt & Göran Ericsson & Jonas Kindberg, 2008. "Contingent values as implicit contracts: estimating minimum legal willingness to pay for conservation of large carnivores in Sweden," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 39(2), pages 189-198, February.
    7. Ogutu, Francis, 2021. "Agro-dealer’s knowledge, perception, and willingness to stock a fungal based biopesticide (ICIPE 20) for management of Tuta absoluta in Kenya," 2021 Conference, August 17-31, 2021, Virtual 315896, International Association of Agricultural Economists.
    8. Broberg, Thomas & Brännlund, Runar, 2008. "An alternative interpretation of multiple bounded WTP data--Certainty dependent payment card intervals," Resource and Energy Economics, Elsevier, vol. 30(4), pages 555-567, December.
    9. Mikołaj Czajkowski & Nick Hanley & Jacob LaRiviere & William S. Neilson & Katherine Simpson, 2016. "Information and Learning in Stated-Preference Studies," Working Papers 2016-20, Faculty of Economic Sciences, University of Warsaw.

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