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

Published online by Cambridge University Press:  26 January 2015

John B. Loomis  and
Julie M. Mueller
John B. Loomis
Affiliation:
Department of Agricultural and Resource Economics, Colorado State University, Fort Collins, Colorado
Julie M. Mueller
Affiliation:
The W.A. Franke College of Business, Northern Arizona University, Flagstaff, Arizona
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We 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 population WTP 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.

Keywords

Bayesian estimationcontingent valuationspatial probitwillingness to payC11Q51
Type
Research Article
Information
Journal of Agricultural and Applied Economics , Volume 45 , Issue 1 , February 2013 , pp. 53 - 63
Copyright
Copyright © Southern Agricultural Economics Association 2013

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