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Semi-nonparametric distribution-free dichotomous choice contingent valuation

Michael Creel, John Loomis

Research output: Contribution to journalArticleResearchpeer-review

Abstract

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
Volume32
DOIs
Publication statusPublished - 1 Jan 1997

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being
  2. SDG 12 - Responsible Consumption and Production
    SDG 12 Responsible Consumption and Production

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