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Testing for Hypothetical Bias in Contingent Valuation Using a Latent Choice Multinomial Logit Model

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Author Info
Steven B. Caudill
Peter A. Groothuis
John C. Whitehead

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Abstract

The most persistently troubling empirical result in the contingent valuation method literature is the tendency for hypothetical willingness to pay to overestimate real willingness to pay. We suggest a new approach to test and correct for hypothetical bias using a latent choice multinomial logit (LCMNL) model. To develop this model, we extend Dempster, Laird, and Rubin’s (1977) work on the EM algorithm to the estimation of a multinomial logit model with missing information on categorical membership. Using data on both the quality of water in the Catawba River in North Carolina and the preservation of Saginaw wetlands in Michigan, we find two types of “yes” responders in both data sets. We suggest that one set of yes responses are yea-sayers who suffer from hypothetical bias and answer yes to the hypothetical question but would not pay the bid amount if it were real. The second group does not suffer from hypothetical bias and would pay the bid amount if it were real.

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Paper provided by Department of Economics, Appalachian State University in its series Working Papers with number 06-09.

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Date of creation: 2006
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Handle: RePEc:apl:wpaper:06-09

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Keywords: C25; P230; Q51;

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  1. Christian A. Vossler & Robert G. Ethier & Gregory L. Poe & Michael P. Welsh, 2003. "Payment Certainty in Discrete Choice Contingent Valuation Responses: Results from a Field Validity Test," Southern Economic Journal, Southern Economic Association, vol. 69(4), pages 886-902, April.
  2. John C. Whitehead & Peter A. Groothuis & Rob Southwick & Pat Foster-Turley, 2006. "Economic Values of Saginaw Bay Coastal Marshes," Working Papers 06-10, Department of Economics, Appalachian State University. [Downloadable!]
  3. David Aadland & Arthur J. Caplan, 2003. "Willingness to Pay for Curbside Recycling with Detection and Mitigation of HypotheticalBias," American Journal of Agricultural Economics, American Agricultural Economics Association, vol. 85(2), pages 492-502, 05. [Downloadable!] (restricted)
  4. Steven Caudill & Peter Groothuis, 2004. "Modeling Hidden Alternatives in Random Utility Models: An Application to Don’t Know Responses in Contingent Valuation," Working Papers 04-07, Department of Economics, Appalachian State University.
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  5. Greene, William H. & Hensher, David A., 2003. "A latent class model for discrete choice analysis: contrasts with mixed logit," Transportation Research Part B: Methodological, Elsevier, vol. 37(8), pages 681-698, September. [Downloadable!] (restricted)
  6. Brown, Thomas C. & Ajzen, Icek & Hrubes, Daniel, 2003. "Further tests of entreaties to avoid hypothetical bias in referendum contingent valuation," Journal of Environmental Economics and Management, Elsevier, vol. 46(2), pages 353-361, September. [Downloadable!] (restricted)
  7. Karen Blumenschein & GlennC. Blomquist & Magnus Johannesson & Nancy Horn & Patricia Freeman, 2008. "Eliciting Willingness to Pay Without Bias: Evidence from a Field Experiment," Economic Journal, Royal Economic Society, vol. 118(525), pages 114-137, 01. [Downloadable!] (restricted)
  8. Gregory Poe & Jeremy Clark & Daniel Rondeau & William Schulze, 2002. "Provision Point Mechanisms and Field Validity Tests of Contingent Valuation," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 23(1), pages 105-131, September. [Downloadable!] (restricted)
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