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Accounting for Respondent Uncertainty to Improve Willingness-to-Pay Estimates


  • Rebecca Moore
  • Richard C. Bishop
  • Bill Provencher
  • Patricia A. Champ


"In this paper, we develop an econometric model of willingness to pay (WTP) that integrates data on respondent uncertainty regarding their own WTP. The integration is utility consistent, there is no recoding of variables, and no need to calibrate the contingent responses to actual payment data, so the approach can "stand alone." In an application to a valuation study related to whooping crane restoration, we find that this model generates a statistically lower expected WTP than the standard contingent valuation (CV) model. Moreover, the WTP function estimated with this model is not statistically different from that estimated using actual payment data suggesting that, when properly analyzed using data on respondent uncertainty, CV decisions can simulate actual payment decisions. This method allows for more reliable estimates of WTP that incorporate respondent uncertainty without the need for collecting comparable actual payment data." Copyright (c) 2010 Canadian Agricultural Economics Society.

Suggested Citation

  • Rebecca Moore & Richard C. Bishop & Bill Provencher & Patricia A. Champ, 2010. "Accounting for Respondent Uncertainty to Improve Willingness-to-Pay Estimates," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 58(3), pages 381-401, September.
  • Handle: RePEc:bla:canjag:v:58:y:2010:i:3:p:381-401

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    References listed on IDEAS

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    5. Banerjee, Anindya & Lumsdaine, Robin L & Stock, James H, 1992. "Recursive and Sequential Tests of the Unit-Root and Trend-Break Hypotheses: Theory and International Evidence," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(3), pages 271-287, July.
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    7. Johansen, Søren & Juselius, Katarina, 1992. "Testing structural hypotheses in a multivariate cointegration analysis of the PPP and the UIP for UK," Journal of Econometrics, Elsevier, vol. 53(1-3), pages 211-244.
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    Cited by:

    1. Fifer, Simon & Rose, John & Greaves, Stephen, 2014. "Hypothetical bias in Stated Choice Experiments: Is it a problem? And if so, how do we deal with it?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 61(C), pages 164-177.
    2. Provencher, Bill & Lewis, David J. & Anderson, Kathryn, 2012. "Disentangling preferences and expectations in stated preference analysis with respondent uncertainty: The case of invasive species prevention," Journal of Environmental Economics and Management, Elsevier, vol. 64(2), pages 169-182.
    3. Fifer, Simon & Rose, John M., 2016. "Can you ever be certain? Reducing hypothetical bias in stated choice experiments via respondent reported choice certaintyAuthor-Name: Beck, Matthew J," Transportation Research Part B: Methodological, Elsevier, vol. 89(C), pages 149-167.
    4. Ewa Zawojska & Pierre-Alexandre Mahieu & Romain Crastes & Jordan Louviere, 2016. "On a way to overcome strategic overbidding in open-ended stated preference surveys: A recoding approach," Working Papers 2016-34, Faculty of Economic Sciences, University of Warsaw.
    5. Subade, Rodelio F. & Francisco, Herminia A., 2014. "Do non-users value coral reefs?: Economic valuation of conserving Tubbataha Reefs, Philippines," Ecological Economics, Elsevier, vol. 102(C), pages 24-32.
    6. Loomis, John B., 2014. "2013WAEA Keynote Address: Strategies for Overcoming Hypothetical Bias in Stated Preference Surveys," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 39(1), April.

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