Willingness-to-pay estimates using the double-bounded dichotomous-choice contingent valuation format: A test for validity and precision in a Bayesian framework

The Double-Bounded Dichotomous-Choice (DB-DC) Contingent Valuation format is thought to yield more precise welfare estimates. Questions remain about its validity. The initial bid may represent information with which respondents update their willingness to pay. A Bayesian model of respondent decision making is estimated for two data sets. The results indicate updating or shifts in respondent willingness to pay between iterated valuations. Nonparametric resting of the welfare estimates reveals that the model incorporating updating yields different values fram the standard model The expected increases in the precision of the DB-DC welfare estimates are lost when updating occurs. (JEL Q26).