Tag: propensity score matching

Do EIP-AGRI operational groups improve farmers’ performance? An analysis of treatment effects in intensive farming systems

The Operational Groups (OGs) of the European Innovation Partnership for Agricultural Productivity and Sustainability (EIPAGRI) were introduced by the 2014-2020 Common Agricultural Policy to foster competitive and sustainable farming and forestry. The objective of this paper is to assess the economic and environmental impacts of participating in the EIP-AGRI OGs located in the Italian region of Emilia-Romagna. Performance of participants in OGs is compared with that of non-participants, who are selected by applying propensity score matching techniques to an Italian farm accountancy data network sample of 3204 farmers observed in the period 2017-2020. Logistic regressions are used to measure both propensity scores and the average treatment effect on the treated, while one-to-many optimal matching without replacement is adopted to form the control group. The resulting sample is composed of 270 observations, of which 45 are treated subjects. Results indicate that the OGs analysed might have contributed to improving fertiliser management and profitability levels in participating farms, but they failed to preserve biodiversity and reduce the consumption of pesticides and other inputs such as water, energy, and fuels. To increase the effectiveness of OGs, policy makers are advised to condition projects on the actual experimentation and implementation of agricultural innovations and ...

Do coupled subsidies increase milk productivity, land use, herd size and income? Evidence from Kosovo

This study assesses the effectiveness of the Subsidy per Head Scheme (SPHS) in increasing milk productivity, land use, herd size and income in dairy farms across the seven regions of Kosovo. SPHS represents one of the largest coupled subsidy programs in the agricultural sector of Kosovo in terms of farmer participation and budget allocation. We use a Propensity Score Matching approach to assess the impact of this program by comparing a group of participants with a group of non-participants during the 2013–2014 farming seasons. We test the robustness of the impact results using four different matching algorithms. Results reveal SPHS was not effective in increasing land use, gross income and farm size (number of cows), although SPHS had a limited impact on improving milk productivity. In addition, the study highlights the need to reformulate coupled subsidies and develop new, complementary strategies that address farmers’ needs more efficiently.

The impact of government subsidies on the olive and vineyard sectors of Albanian agriculture

This study analyses the impact of government subsidy schemes on farm production capacity, technical efficiency and use of idle production factors (land and labour) in the olive and vineyard sectors of Albanian agriculture. The paper uses a quasi-experimental design by applying a propensity score matching method based on a structured survey conducted in 2013. The results show that the government subsidy scheme had a net positive impact on areas planted with olives and grapevines, and on part-time on-farm employment. On the other hand, no significant net impact was observed regarding farm size and crop yields. This is the first time that such an in-depth impact assessment of government subsidies in the agriculture sector has been carried out in Albania, thus the results will be useful both for scientists and policy makers in agriculture and rural development.

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  • Scopus SJR (2023): 0.29
  • Scopus CiteScore (2022): 2.0
  • WoS Journal Impact Factor (2022): 1.2
  • WoS Journal Citation Indicator (2022): 0.45
  • ISSN (electronic): 2063-0476
  • ISSN-L 1418-2106



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.

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