Accounting for uncertainty in willingness to pay for environmental benefits

Arbeitspapier

Previous literature on the distribution of willingness to pay has focused on its heterogeneity distribution without addressing exact interval estimation. In this paper we derive and analyze Bayesian confidence sets for quantifying uncertainty in the determination of willingness to pay for carbon dioxide abatement. We use two empirical case studies: household decisions of energy-efficient heating versus insulation, and purchase decisions of ultralow-emission vehicles. We first show that deriving credible sets using the posterior distribution of the willingness to pay is straightforward in the case of deterministic consumer heterogeneity. However, when using individual estimates, which is the case for the random parameters of the mixed logit model, it is complex to define the distribution of interest for the interval estimation problem. This latter problem is actually more involved than determining the moments of the heterogeneity distribution of the willingness to pay using frequentist econometrics. A solution that we propose is to derive and then summarize the distribution of point estimates of the individual willingness to pay under different loss functions.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: ZEW Discussion Papers ; No. 13-059

Classification and Topics

• Classification: Wirtschaft ; Single Equation Models; Single Variables: Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities ; Consumer Economics: Empirical Analysis ; Valuation of Environmental Effects
• Subject: Discrete Choice Models ; Willingness to Pay ; Credible Sets

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Daziano, Ricardo A. ; Achtnicht, Martin
• Event: Veröffentlichung
• (who): Zentrum für Europäische Wirtschaftsforschung (ZEW)
• (where): Mannheim
• (when): 2013

Further information

• Handle: http://hdl.handle.net/10419/80722
• URN: urn:nbn:de:bsz:180-madoc-346152
• Last update: 10.03.2025, 11:44 AM CET