Disease dispersion as a spatial interaction: The case of Flavescence Doree
Affiliation auteurs | Affiliation ok |
Titre | Disease dispersion as a spatial interaction: The case of Flavescence Doree |
Type de publication | Journal Article |
Year of Publication | 2020 |
Auteurs | Ay J-S, Gozlan E |
Journal | NATURAL RESOURCE MODELING |
Volume | 33 |
Pagination | e12265 |
Date Published | AUG |
Type of Article | Article |
ISSN | 0890-8575 |
Mots-clés | compulsory treatment, cost-benefit analysis, environmental externality, pest management, Spatial Spillovers |
Résumé | Flavescence doree is a serious and incurable vine disease transmitted by an insect vector. Focusing on its spatial diffusion and on its control with pesticides, this paper investigates the private strategies of wine producers and their socially optimal counterparts. The socially optimal regulation has to address two externalities regarding private treatment decisions: (a) the insufficient consideration of collective benefits from controlling the vector populations; (b) the failure to take into account environmental damage related to pesticide application. The probability of infection is estimated on French data from a spatial econometric specification. Three alternative assumptions are examined regarding producers' anticipation of the impact of their own treatment: naive, myopic, or farseeing, in increasing order of sophistication. Because of the two dimensions of externalities, no type of anticipation leads to a systematically preferable situation and optimal policy intervention requires a tax for environmental externalities and a subvention for protection externalities. Recommendations for Resource Managers: Current policy of compulsory treatment is justified by the positive protection externalities. This policy is particularly appropriated if producers' anticipations are naive or myopic. Taking into account negative externalities decreases the case for compulsory treatment. With two externalities, sophisticated anticipations are not necessary closer to the optimum. |
DOI | 10.1111/nrm.12265 |