This article aims at investigating the impact of financial supports from agricultural policy on farm-size dynamics. Since not all farms may behave alike, a non-stationary mixed-Markov chain modelling (M-MCM) approach is applied to capture unobserved heterogeneity in the movements of farms across economic size (ES) classes. A multinomial logit specification is used for transition probabilities and the parameters are estimated by the maximum likelihood method and the Expectation-Maximisation (EM) algorithm. An empirical application to an unbalanced panel from 2000 to 2018 shows that French farming consists of ‘almost stayers’, with a high probability of remaining in the same ES class over time, and ‘likely movers’, which present a higher probability of a change in size. The results also show that the impact of subsidies and other economic factors depends greatly on the type that a farm belongs to. These findings confirm that individual characteristics of farmers may be relevant for policy efficiency and more attention should thus be paid to unobserved farm heterogeneity in both policy design and the assessment of their impacts on farm-size dynamics.

中文翻译：

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农业政策补贴的异质农场规模动态和影响：来自法国的证据

本文旨在调查农业政策的财政支持对农场规模动态的影响。由于并非所有农场的行为都可能相似，因此应用了非平稳混合马尔可夫链建模 (M-MCM) 方法来捕捉不同经济规模 (ES) 类别的农场移动中未观察到的异质性。多项式 logit 规范用于转移概率，参数通过最大似然法和期望最大化 (EM) 算法进行估计。从 2000 年到 2018 年对不平衡面板的实证应用表明，法国农业由“几乎停留者”组成，随着时间的推移很有可能保持在同一 ES 类别中，而“可能的推动者”则呈现出更高的变化概率在尺寸方面。结果还表明，补贴和其他经济因素的影响在很大程度上取决于农场所属的类型。这些发现证实，农民的个体特征可能与政策效率相关，因此在政策设计和评估其对农场规模动态的影响时，应更多地关注未观察到的农场异质性。