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B1340
Title: Studying the impact of agricultural subsidies across Europe using a Bayesian spatiotemporal clustering model Authors:  Gregor Kastner - University of Klagenfurt (Austria)
Alexander Mozdzen - University of Klagenfurt (Austria) [presenting]
Tamas Krisztin - International Institute for Applied Systems Analysis (Austria)
Abstract: The global climate crisis has conceived the need for impactful policies reducing greenhouse gas emissions across all sources, including emissions stemming from agricultural expansion. In order to study the effectiveness of mitigation policies, statistical methods need to take into account complex biophysical and socio-economic processes. A Bayesian spatiotemporal model is proposed for exploring the impact of agricultural subsidies on land usage while simultaneously controlling for other relevant drivers. Recent developments in the literature are combined on land use models with a Bayesian nonparametric prior to cluster areas that exhibit similar results of the policy in question. Individual impacts of essential spatial processes and explicitly model spillovers are controlled between regions. Additionally, a suitable Markov chain Monte Carlo (MCMC) algorithm is developed, and the model is tested in an extensive simulation study. Using European regional data, the effectiveness of mitigation policies is investigated concerning agricultural expansion across Europe and the diversity of the problem is revealed.