| Title |
Modelling Lithuanian family farms' participation in agri-environmental subsidy schemes: a Neural Network Approach |
| ID_Doc |
63775 |
| Authors |
Geseviciene, K; Besuspariene, E |
| Title |
Modelling Lithuanian family farms' participation in agri-environmental subsidy schemes: a Neural Network Approach |
| Year |
2023 |
| Published |
Economia Agraria Y Recursos Naturales, 23, 2 |
| DOI |
10.7201/earn.2023.02.05 |
| Abstract |
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. |
| Author Keywords |
Agri-environmental Subsidy; Agricultural Practices; Common Agricultural Policy; Neural Network; Multilayer Perceptron |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Emerging Sources Citation Index (ESCI) |
| EID |
WOS:001133008600001 |
| WoS Category |
Economics |
| Research Area |
Business & Economics |
| PDF |
https://polipapers.upv.es/index.php/EARN/article/download/19156/16306
|