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Improving Willingness to Pay Estimates for Quality Improvements through Joint Estimation with Quality Perceptions

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  • John C. Whitehead
Abstract
Willingness to pay for quality change may depend on heterogeneous perceived quality levels. In these instances, contingent valuation studies should include measures of quality perceptions as covariates in the willingness to pay model in order to avoid omitted variable bias. Variation in quality perceptions across respondents leads to a potential endogeneity of quality perceptions. We address the potential for endogeneity bias using an instrumental variables approach in which a measure of quality perceptions is included as a determinant of willingness to pay and is simultaneously determined by various exogenous factors. The willingness to pay model is estimated jointly with quality perceptions allowing for correlation of the error terms. Using data on willingness to pay for water quality improvements in the Neuse River in North Carolina we reject exogeneity of perceived quality. Correcting for endogeneity improves the measurement of willingness to pay by differentiating willingness to pay among respondents with heterogeneous quality perceptions.

Suggested Citation

  • John C. Whitehead, 2005. "Improving Willingness to Pay Estimates for Quality Improvements through Joint Estimation with Quality Perceptions," Working Papers 05-09, Department of Economics, Appalachian State University.
    • Handle: RePEc:apl:wpaper:05-09
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    File URL: http://econ.appstate.edu/RePEc/pdf/wp0509.pdf
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    References listed on IDEAS

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    1. repec:ags:joaaec:v:31:y:1999:i:1:p:177-84 is not listed on IDEAS
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    11. Mi-Jung Um & Seung-Jun Kwak & Tai-Yoo Kim, 2002. "Estimating Willingness to Pay for Improved Drinking Water Quality Using Averting Behavior Method with Perception Measure," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 21(3), pages 285-300, March.
    12. Seung-Hoon Yoo & Hee-Jong Yang, 2001. "Application of Sample Selection Model to Double-Bounded Dichotomous Choice Contingent Valuation Studies," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 20(2), pages 147-163, October.
    13. John C. Whitehead, 2002. "Incentive Incompatibility and Starting-Point Bias in Iterative Valuation Questions," Land Economics, University of Wisconsin Press, vol. 78(2), pages 285-297.
    14. John C. Whitehead & Timothy C. Haab & Ju‐Chin Huang, 1998. "Part‐Whole Bias in Contingent Valuation: Will Scope Effects Be Detected with Inexpensive Survey Methods?," Southern Economic Journal, John Wiley & Sons, vol. 65(1), pages 160-168, July.
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    Cited by:

    1. Christophe Bontemps & Céline Nauges, 2016. "The Impact of Perceptions in Averting-decision Models: An Application of the Special Regressor Method to Drinking Water Choices," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 98(1), pages 297-313.
    2. Tan-Soo, Jie-Sheng & Finkelstein, Eric & Qin, Ping & Jeuland, Marc & Pattanayak, Subhrendu & Zhang, Xiaobing, 2023. "Air quality valuation using online surveys in three Asian megacities," EfD Discussion Paper 23-8, Environment for Development, University of Gothenburg.

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    JEL classification:

    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects

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