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Impact of Spatial Differentiation of Nitrogen Taxes on French Farms' Compliance Costs

机译：氮税的空间差异对法国农场履约成本的影响

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The spatial differentiation of input-based pollution fees should in theory decrease compliance costs in the case of nitrate pollution of water bodies from agriculture because both the damage and the compliance costs vary over space. However, the empirical evidence in the literature does not agree on the extent of the potential savings from differentiation. We address this issue in the case of France, using a mathematical programming model of agricultural supply (AROPAj). The modeling approach used accounts for the spatial diversity of nitrate pollution and the heterogeneity of farming systems. Our results reveal the efficiency gains from differentiating pollution fees among polluters and water bodies. For instance, firm-specific and water body-specific taxes represent respectively 5.8 and 32.5 % of farmers' gross margin in terms of compliance costs, whereas a uniform policy at the river-basin district or national level leads to major economic losses and abandonment of the agricultural activity. These results stem from the lower tax rates faced by farmers in less polluted areas, for scenarios based on spatial differentiation. Our estimates suggest that realistic regulation via input-based pollution fees should be differentiated in order to significantly reduce the financial burden on farmers of conforming to predefined pollution levels. Some potential adverse effects related to input-based taxation and land use change call for additional fine-scale nitrogen pollution regulation (e.g. limitations on crop switching).
机译：从理论上讲，基于投入的污染费的空间差异在农业用水污染硝酸盐的情况下应降低履约成本，因为损害和履约成本随空间而变化。但是，文献中的经验证据在分化带来的潜在节省范围上并不一致。对于法国，我们使用农业供给的数学规划模型（AROPAj）解决了这个问题。使用的建模方法考虑了硝酸盐污染的空间多样性和耕作制度的异质性。我们的结果表明，通过区分污染者和水体的污染费用可以提高效率。例如，就合规成本而言，针对公司和针对水体的税收分别占农民毛利率的5.8％和32.5％，而在流域或国家一级实行统一政策会导致重大的经济损失和放弃。农业活动。这些结果是由于在基于空间差异的情况下，污染较少的地区农民面临的税率较低。我们的估计表明，应区分通过基于投入的污染费的实际监管，以显着减少符合预定污染水平的农民的经济负担。与基于投入的税收和土地使用变化相关的一些潜在不利影响要求对氮污染进行更精细的监管（例如，限制农作物转换）。

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