论文标题
部分可观测时空混沌系统的无模型预测
The impact of CAP subsidies on the productivity of cereal farms in six European countries
论文作者
论文摘要
总要素生产率（TFP）是农场发展的关键决定因素，该部门获得了大量的公共支持。今天的问题非常重视，乌克兰的冲突导致谷物市场的影响。本文研究了不同补贴对谷物农场生产率的影响，该农场根据TFP的水平有所不同。我们依靠三步估计策略：i）生产功能的估计，ii）TFP的评估； iii）评估CAP补贴与TFP之间的关系。为了克服多重内生性问题，采用了系统GMM估计器。该调查使用2008年至2018年的FADN样本在法国，德国，意大利，波兰，西班牙和英国都包含农场。除了先前的分析外，我们比较了不同国家的结果，并调查了三个TFP水平不同的农场子集的结果。结果证实了CAP如何对农场TFP产生负面影响，但是根据具有不同生产力群体不同的农场，根据补贴，六个国家以及其中的补贴类型而有所不同。因此，为了促进谷物农场的生产力，还有一些政策改进的空间。
Total factor productivity (TFP) is a key determinant of farm development, a sector that receives substantial public support. The issue has taken on great importance today, where the conflict in Ukraine has led to repercussions on the cereal markets. This paper investigates the effects of different subsidies on the productivity of cereal farms, accounting that farms differ according to the level of TFP. We relied on a three-step estimation strategy: i) estimation of production functions, ii) evaluation of TFP, and iii) assessment of the relationship between CAP subsidies and TFP. To overcome multiple endogeneity problems, the System-GMM estimator is adopted. The investigation embraces farms in France, Germany, Italy, Poland, Spain and the United Kingdom using the FADN samples from 2008 to 2018. Adding to previous analyses, we compare results from different countries and investigate three subsets of farms with varying levels of TFP. The outcomes confirm how CAP negatively impacts farm TFP, but the extent differs according to the type of subsidies, the six countries and, within these, among farms with different productivity groups. Therefore there is room for policy improvements in order to foster the productivity of cereal farms.
