Studies.hu
Studies.hu
Studies.hu

Tag: machine learning

Do Agriculture Subsidies Make Farmers Better-off? A Case Study from an EU Candidate Country

Studies on the impact assessment of subsidy schemes on farm performance indicators show contradictory results. Some studies indicate improvements in farm efficiency, while others highlight distortions and negative externalities. This paper analyses the impact of budgetary support provided to dairy farms in Albania based on a structured farm survey. The impact is assessed using causal forest, an adaptation of Breiman’s random forest algorithm for treatment effect estimation. Results suggest that subsidies positively impact the number of milking cows, output (quantity of milk sold), and revenues but have no impact on employment, yields, investment, or future investment plans. The study suggests that public support to dairy farmers should be conditioned on technology improvement measures and CAP-like cross-compliance obligations.

Journal Metrics

Scimago Journal & Country Rank

 

 

 

 

  • Scopus SJR (2023): 0.29
  • Scopus CiteScore (2022): 2.0
  • WoS Journal Impact Factor (2023): 0.9
  • WoS Journal Citation Indicator (2023): 0.33
  • ISSN (electronic): 2063-0476
  • ISSN-L 1418-2106

 

Impressum

Publisher Name: Institute of Agricultural Economics Nonprofit Kft. (AKI)

Publisher Headquarters: Zsil utca 3-5, 1093-Budapest, Hungary

Name of Responsible Person for Publishing:        Dr. Pal Goda

Name of Responsible Person for Editing:             Dr. Attila Jambor

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

The publication cost of the journal is supported by the Hungarian Academy of Sciences.

Most viewed