0000000000621275

AUTHOR

Jean-sauveur Ay

showing 2 related works from this author

Disease dispersion as a spatial interaction: The case of Flavescence Dorée

2020

International audience; Flavescence dorée 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 alternat…

cost‐benefit analysisMandatory treatmentJEL: Q - Agricultural and Natural Resource Economics • Environmental and Ecological Economics/Q.Q1 - Agriculture/Q.Q1.Q12 - Micro Analysis of Farm Firms Farm Households and Farm Input MarketsCompulsory treatmentEnvironmental Science (miscellaneous)environmental externalityAnalyse cout-benefice0502 economics and businessEconometricsStatistical dispersion050207 economicsExternalité environnementaleMathematicsGestion des nuisibles2. Zero hungercompulsory treatmentJEL: H - Public Economics/H.H2 - Taxation Subsidies and Revenue/H.H2.H21 - Efficiency • Optimal Taxation[QFIN]Quantitative Finance [q-fin]Spatial interactioncost-benefit analysis05 social sciencesTraitement obliatoire[SHS.ECO]Humanities and Social Sciences/Economics and Financespatial spilloverspest management13. Climate actionModeling and SimulationFlavescence doréeJEL: Q - Agricultural and Natural Resource Economics • Environmental and Ecological Economics/Q.Q5 - Environmental Economics/Q.Q5.Q51 - Valuation of Environmental Effects050202 agricultural economics & policy
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Nonlinear impact estimation in spatial autoregressive models

2018

International audience; This paper extends the literature on the calculation and interpretation of impacts for spatial autoregressive models. Using a Bayesian framework, we show how the individual direct and indirect impacts associated with an exogenous variable introduced in a nonlinear way in such models can be computed, theoretically and empirically. Rather than averaging the individual impacts, we suggest to graphically analyze them along with their confidence intervals calculated from Markov chain Monte Carlo (MCMC). We also explicitly derive the form of the gap between individual impacts in the spatial autoregressive model and the corresponding model without a spatial lag and show, in…

Economics and Econometrics[SDV]Life Sciences [q-bio]Lag0507 social and economic geographysymbols.namesake0502 economics and businessEconometricsMarginal impacts050207 economicsSpatial econometricsMathematics05 social sciencesMarkov chain Monte Carlo[SHS.ECO]Humanities and Social Sciences/Economics and FinanceSplineConfidence intervalMarkov chain Monte CarloSpline (mathematics)Nonlinear systemAutoregressive model13. Climate actionsymbolsBayesian frameworkSpatial econometrics050703 geographyFinanceEconomics Letters
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