Abstract
This study introduces distribution-free methods to estimate interval-censored willingness-to-pay (WTP) models. The approaches proposed encompass the recovery of WTP values using an iterated conditional expectation procedure and subsequent estimation of the mean WTP using parametric and nonparametric models. Methods allow us to estimate the effects of covariates on the mean WTP and the underlying probability distribution. We employ Monte Carlo simulations to compare the performance of the estimators proposed against standard parametric and nonparametric estimators. We illustrate the estimation techniques by assessing producersÕ WTP for services provided by an e-marketing website that helps connect farmers with local consumers.
