A Spatial Probit Modeling Approach to Account for Spatial Spillover Effects in Dicotomous Choice Contingent Valuation Surveys

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dc.creatorLoomis, John B.
dc.creatorMueller, Julie M.
dc.date2017-04-01T19:41:21Z
dc.date.accessioned2026-07-09T06:49:56Z
dc.descriptionWe present a demonstration of a Bayesian spatial probit model for a dichotomous choice contingent valuation method willingness-to-pay (WTP) questions. If voting behavior is spatially correlated, spatial interdependence exists within the data, and standard probit models will result in biased and inconsistent estimated nonbid coefficients. Adjusting sample WTP to population WTP requires unbiased estimates of the nonbid coefficients, and we find a $17 difference in populationWTP per household in a standard vs. spatial model. We conclude that failure to correctly model spatial dependence can lead to differences in WTP estimates with potentially important policy ramifications.
dc.identifierdoi:10.22004/ag.econ.143663
dc.identifierhttps://ageconsearch.umn.edu/record/143663/files/jaae624.pdf
dc.identifierhttp://ageconsearch.umn.edu/record/143663
dc.identifier.urihttp://hdl.handle.net/123456789/581349
dc.languageeng
dc.publisher
dc.sourcehttp://ageconsearch.umn.edu/record/143663
dc.titleA Spatial Probit Modeling Approach to Account for Spatial Spillover Effects in Dicotomous Choice Contingent Valuation Surveys
dc.typeText

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