Examining spatially heterogeneous preferences for coastal ecosystem restoration with Bayesian spatial probit approaches

Kei Kabaya ()
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Kei Kabaya: Rikkyo University

Letters in Spatial and Resource Sciences, 2022, vol. 15, issue 1, No 6, 99-112

Abstract: Abstract Preferences for environmental goods often display spatial heterogeneity. Nevertheless, spatial discrete choice models have received minimal attention in the stated-preference literature to date. The present study examined three alternative Bayesian spatial probit models to investigate the various implications of space on respondents’ voting patterns. The case study was a dichotomous choice contingent valuation of coastal ecosystem restoration in Yokohama City, Japan. A non-spatial probit model first showed that spatial observable variables, such as distance and landscapes, failed to explain spatially motivated voting patterns. A spatial autoregressive probit model then revealed significantly negative spatial feedback effects on respondents’ votes and demonstrated insignificant but potentially policy-relevant difference in willingness-to-pay estimates. A spatial error probit model also unveiled significant spatial heterogeneity based on latent factors. Finally, a spatially structured effects probit model with a more flexible boundary setting enabled the researcher to identify some regional voting patterns. These results suggest that the application of spatial probit models to a contingent valuation study can provide additional insights on the spatial aspects of respondents’ preferences.

Keywords: Bayesian estimation; Contingent valuation; Spatial autoregressive probit model; Spatial error probit model; Spatially structured effect probit model; Willingness-to-pay (search for similar items in EconPapers)
JEL-codes: C21 C25 Q51 Q57 (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s12076-022-00301-z

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