Tag: DEA

Analysis of determinants of efficiency in grape farming – the case of Kosovo

This study analyses the performance of vineyards in Kosovo in terms of their technical, allocative, and economic efficiency. It uses two methods to measure efficiency: Data Envelopment Analysis (DEA) and Tobit regression. The data comes from a survey of 165 wine producers through face-to-face interviews in three regions of Kosovo – Rahovec, Suharake and Prizren – between the years 2016 and 2018, each yielding the average of inputs, outputs and prices for the three years. In order to determine the key variables for grape growing efficiency, it was necessary to consider the combined effects of the interactions between inputs, as this has an impact on overall final production. The results show great potential for improving the efficiency of viticulture. The average technical efficiency (TE) is 0.68, the average allocative efficiency (AE) is 0.77 and the average economic efficiency (EE) is 0.52. In general, TE, AE and EE were influenced by the selected variables, suggesting that the selected variables played quite an important role in enabling farmers not to use too many inputs in the production of grapes and instead to use them in appropriate proportions. It also shows how grape growers can improve their productive efficiency by adopting certain practices ...

Exploring efficiency reserves in Hungarian milk production

This paper aims to explore the efficiency of Hungarian dairy farms. Based on FADN data representing more than 950 dairy farms in Hungary, our sample contains more than 6800 data points which we analysed by applying different Data Envelopment Analysis models. Results suggest that the average technical efficiency of the Hungarian dairy sector during the examined 10 years was 77.6%, meaning that output could be increased by 22.4% without changing the level of input (efficiency reserve). Large and small farms are more efficient (79.2%) than medium sized farms (59.2%). Moreover, large farms keeping more than 501 dairy cows were found to be more efficient (92.5%) than the other two size categories (77.9% and 65%, respectively). Farms located in Northern Hungary had less efficiency reserves (23.6%) that the farms operating in the Great Hungarian Plain, Central Hungary (34.8%) or in the Transdanubian Region (27.6%). All this suggests high reserves for potential efficiency growth.

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  • 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



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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