Tag: artifi cial neural networks

The economic effect of Russia imposing a food embargo on the European Union with Hungary as an example

In the summer of 2014, Russia imposed a food embargo on most agricultural products from countries that supported the anti-Russian sanctions. In this study we use vector autoregression and neural network modelling to assess the eff ect of the embargo on the bilateral trade relations between the European Union (EU) (using the example of Hungary as an EU Member State) and Russia. In particular, the changes in the dynamics of Hungary’s aggregate agricultural exports in response to the shock of the embargo, as well as to Russia’s imports of products banned under the embargo, are analysed. The work also looks at the eff ectiveness of the introduction of the embargo with the aim of implementing import substitution policies and supporting domestic producers. Our results show the ineff ectiveness of the Russian import substitution policy and the negative eff ects on both Russian and Hungarian parties.

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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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