title: Spatial Dependence and Determinants of Dairy Farmers' Adoption of Best Management Practices for Water Protection in New Zealand.
abstract: This paper analyses spatial dependence and determinants of the New Zealand dairy farmers' adoption of best management practices to protect water quality. A Bayesian spatial durbin probit model is used to survey data collected from farmers in the Waikato region of New Zealand. The results show that farmers located near each other exhibit similar choice behaviour, indicating the importance of farmer interactions in adoption decisions. The results also address that information acquisition is the most important determinant of farmers' adoption of best management practices. Financial problems are considered a significant barrier to adopting best management practices. Overall, the existence of distance decay effect and spatial dependence in farmers' adoption decisions highlights the importance of accounting for spatial effects in farmers' decision-making, which emerges as crucial to the formulation of sustainable agriculture policy.
authors.affiliation: Department of Economics, Business School, the University of Auckland, Owen G Glen Building, 12 Grafton Road, Auckland, New Zealand. ywei841@aucklanduni.ac.nz.
authors.forename: Wei
authors.identifier: 0000-0003-1046-2703
authors.initials: W
authors.lastname: Yang
authors.affiliation: Department of Economics, Business School, the University of Auckland, Owen G Glen Building, 12 Grafton Road, Auckland, New Zealand.
authors.forename: Basil
authors.initials: B
authors.lastname: Sharp
mesh_terms: D001499:Bayes Theorem; D003247:Conservation of Natural Resources / Q000379:methods*; D003612:Dairying / Q000191:economics / Q000458:organization & administration*; D003657:Decision Making; D000067565:Farmers; D006801:Humans; D009520:New Zealand; D062206:Spatial Analysis; D011795:Surveys and Questionnaires; D014876:Water Pollution / Q000517:prevention & control*
keywords: Bayesian spatial Durbin probit model; Best management practices; Dairy farmers; Spatial dependence