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

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  • Loomis, John B.
  • Mueller, Julie M.

Abstract

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 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.

Suggested Citation

  • Loomis, John B. & Mueller, Julie M., 2013. "A Spatial Probit Modeling Approach to Account for Spatial Spillover Effects in Dicotomous Choice Contingent Valuation Surveys," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 45(01), February.
  • Handle: RePEc:ags:joaaec:143663
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    References listed on IDEAS

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    1. Gregory L. Poe & Kelly L. Giraud & John B. Loomis, 2005. "Computational Methods for Measuring the Difference of Empirical Distributions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(2), pages 353-365.
    2. Holloway, Garth & Shankar, Bhavani & Rahman, Sanzidur, 2002. "Bayesian spatial probit estimation: a primer and an application to HYV rice adoption," Agricultural Economics, Blackwell, vol. 27(3), pages 383-402, November.
    3. J. Barkley Rosser, 2009. "Introduction," Chapters,in: Handbook of Research on Complexity, chapter 1 Edward Elgar Publishing.
    4. Mueller, Julie M. & Loomis, John B., 2010. "Bayesians in Space: Using Bayesian Methods to Inform Choice of Spatial Weights Matrix in Hedonic Property Analyses," The Review of Regional Studies, Southern Regional Science Association, vol. 40(3), pages 245-255.
    5. Richardson, Leslie & Loomis, John, 2009. "The total economic value of threatened, endangered and rare species: An updated meta-analysis," Ecological Economics, Elsevier, vol. 68(5), pages 1535-1548, March.
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    Cited by:

    1. repec:eee:wdevel:v:95:y:2017:i:c:p:231-253 is not listed on IDEAS
    2. Adjognon, Serge & Liverpool-Tasie, Lenis, 2015. "Spatial Neighborhood Effects in Agricultural Technology Adoption: Evidence from Nigeria," 2015 Conference, August 9-14, 2015, Milan, Italy 210934, International Association of Agricultural Economists.
    3. Adjognon, Serge & Liverpool-Tasie, Lenis Saweda O., 2014. "Spatial Dependence in the Adoption of the Urea Deep Placement for Rice Production in Niger State, Nigeria: A Bayesian Spatial Autoregressive Probit Estimation Approach," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170515, Agricultural and Applied Economics Association.

    More about this item

    Keywords

    Bayesian estimation; contingent valuation; spatial probit; willingness to pay; Environmental Economics and Policy; C11; Q51;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects

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