Semi-nonparametric distribution-free dichotomous choice contingent valuation

Michael Creel, John Loomis

Research output: Contribution to journalArticleResearchpeer-review

48 Citations (Scopus)


We apply a semi-nonparametric distribution-free estimator for binary discrete response data to the estimation of a dichotomous choice contingent valuation model. Using this estimator, mean and median compensating and equivalent variation can be consistently estimated without making nontheoretically motivated assumptions on consumer' preferences. The approach is illustrated using a contingent valuation survey of willingness to pay for reduction of risk of premature death due to exposure to hazardous waste. We find that a conventional parametric estimator and the proposed estimator give similar estimates of unconditional WTP, but that conditional on explanatory variables the estimates are quite different.
Original languageEnglish
Pages (from-to)341-358
JournalJournal of Environmental Economics and Management
Publication statusPublished - 1 Jan 1997


Dive into the research topics of 'Semi-nonparametric distribution-free dichotomous choice contingent valuation'. Together they form a unique fingerprint.

Cite this