A BAYESIAN-APPROACH TO DOUBLE BOUNDED CONTINGENT VALUATION

In this paper we propose a Bayesian approach to model double bounded c ontingent valuation data. The double bounded elicitation method is int erpreted as a two tier iterated process in which the subject is allowe d to have a second thought about his/her valuation for the environment al good. Prior information is modelled from the answers to the first d ichotomous choice question. The model is Quasi-Bayesian (Q-B) in that the prior distribution refers to mean willingness to pay while the lik elihood function refers to the proportions of a multinomial distributi on. This model is applied to empirical data from a contingent valuatio n survey involving the valuation expressed by European tourists for ac cess to natural areas in the Canary Islands. Results show that point e stimate of consumer surplus computed with the Q-B model does not diffe r substantially from single bounded model estimation. In addition, dou ble bounded seems to be quite robust to the choice of the prior model of willingness to pay responses. Comparison with open ended suggests t hat the Q-B model might be useful to control for strategic response an d starting point biases.