Modelling Lithuanian family farms’ participation in agri-environmental subsidy schemes: a Neural Network Approach

Kristina Gesevičienė and Erika Besusparienė

Economia Agraria y Recursos Naturales, 2023, vol. 23, issue 02

Abstract: [EN] Properly targeted agri-environmental subsidies (AES) can ensure the implementation of the European Green Deal goals. Hence, it is important to know what factors encourage family farms to participate in the AES schemes in order to select appropriate political tools and properly use the allocated subsidies. We propose a Multilayer Perceptron neural network to examine 34 Lithuanian crop family farms and identify the factors affecting their participation in the AES. The results indicate that the decision by the Lithuanian family farms regarding the participation mainly depends on a few factors, including the agricultural production output of the farm and farmers’ education, while other factors, such as farmer age and farm size, were less important. [ES] Los subsidios agroambientales (AES) adecuadamente dirigidos pueden garantizar la implementación de los objetivos del Pacto Verde Europeo. Por lo tanto, es importante saber qué factores alientan a las explotaciones familiares a participar en los esquemas de AES para seleccionar las herramientas políticas adecuadas y utilizar adecuadamente los subsidios asignados. Proponemos la red neuronal Multilayer Perceptron para examinar 34 granjas familiares de cultivos lituanos e identificar los factores que afectan su participación en AES. Los resultados indican que la decisión de participación de las granjas familiares lituanas depende principalmente de algunos factores: la producción agrícola de la granja y la educación de los agricultores, otros factores, como la edad del agricultor y el tamaño de la granja, no fueron tan importantes.

Keywords: Agricultural; and; Food; Policy (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:ags:earnsa:339124

DOI: 10.22004/ag.econ.339124

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