Tag: impact evaluation

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.

Assessing the sensitivity of matching algorithms: The case of a natural resource management programme in Honduras

A fundamental challenge in impact evaluations that rely on a quasi-experimental design is to define a control group that accurately refl ects the counterfactual situation. Our aim is to evaluate empirically the performance of a range of approaches that are widely used in economic research. In particular, we compared three diff erent types of matching algorithms (optimal, greedy and nonparametric). These techniques were applied in the evaluation of the impact of the MARENA programme (Manejo de Recursos Naturales en Cuencas Prioritarias), a natural resource management programme implemented in Honduras between 2004 and 2008. The key findings are: (a) optimal matching did not produce better-balanced matches than greedy matching; and (b) programme impact calculated from nonparametric matching regressions, such as kernel or local linear regressions, yielded more consistent outcomes. Our impact results are similar to those previously reported in the literature, and we can conclude that the MARENA programme had a significant, positive impact on beneficiaries.

Agricultural science research impact in the Eastern European Union Member States

Improving agricultural research impact is an important goal for the European Union (EU). The EU Framework 7 project Impresa studied the process of research impact across Europe, and this article selects and discusses results drawn from the 11 Eastern EU Member States. The major methods used were a survey of the levels and trends of research expenditures by the public and private sectors, case studies identifying impact pathways of individual science-based innovations, and quantitative analyses of the relationship between research investments and their final impacts. The conclusions drawn are that, despite the potentially high payback from public investments in agricultural science, insufficient resources are being invested by the post-2004 EU accession countries, and improvements in innovation capacity and networking should enhance the efficiency of research impact.

The effects of a participatory approach on the adoption of agricultural technology: Focusing on the social network structure in rural Ethiopia

This study empirically examined the effects of the participatory approach on the adoption of new crop varieties and agricultural practices. Particularly, we focused on the social network structure and examined how the introduced technologies diffused through networks in rural Ethiopia. Our empirical results indicate that if farmers knew and trusted fellow participants, the probability of adopting a new maize variety increased by 25 percentage points. However, this network had no statistical impact on the diffusion of new agricultural practices. We conclude that the participatory approach has great potential in the adoption of new crop varieties through the social networks of farmers in Ethiopia.

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  • Scopus SJR (2022): 0.27
  • 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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