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0221U105886,
0120U104796
,
Assessing the consequences of quarantine measures related to the spread of COVID-19 pandemic for the agricultural sector and national food security and minimizing their negative impact
Khodakivska Olga V., Доктор економічних наук
07-09-2021
National Scientific Centre "Institute of Agrarian Economics"
Interim report of a scientific work: 375 pages, 139 graphs, 73 tables, 222 sources, 12 appendixes. The purpose of the study is to evaluate the impact of quarantine measures and the spread of the COVID-19 pandemic on the agricultural sector of the economy, agri-food markets and food security and to develop measures to minimize their negative impacts. Methods – abstract-logical, monographic, statistical-economic, expert assessments, comparative analysis. Results. A structural and logical scheme for assessing the impact of quarantine measures and the spread of COVID-19 on the development of the agricultural sector and ensuring food security has been developed. The importance of the criteria for the impact of quarantine measures and the spread of COVID-19 on the development of the agricultural sector and ensuring food security was determined. The results assessment of the degree of impact of restrictive measures and the spread of COVID-19 on the domestic agricultural sector and food security were obtained. Prepared a collective monograph; 5 articles in scientific journals included in international scientometric databases; 3 abstracts of reports of international scientific-practical conferences. Scientific novelty of the research results: in-depth scientific and methodological bases for assessing the consequences of quarantine measures and the spread of the COVID-19 pandemic for the agricultural sector of the economy, agri-food markets and food security of the state; a forecast scenario for 2021-2023, prepared on the basis of the PSIA methodology using the adaptive model of general equilibrium CGE and an alternative forecast developed using the mathematical model of the NSC "Institute of Agrarian Economics", built on neural networks. The use of this forecast scenario will optimally combine economic, organizational, legal, institutional, sectoral, investment and innovation, business and other measures of state influence on the development of the agricultural sector.
Gryschenko Olena Yu.
Krushelnytsky Mykola V.
Mohylnyi Oleksii M.
Patyka Nataliia I.
Pugachov Mykola I.
Tulush Leonid D.
Khodakivska Olga V.
Shpykuliak Oleksandr Hr.
2021-09-07
Updated: 2025-12-07
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