State Support for Agriculture in the Context of Ukraine’s Economic Security: Identification of Key Measures in the EU, Canada, the USA, and New Zealand’s Conceptual Models
Notice bibliographique
Résumé
State support for agriculture, as a strategically important sector of Ukraine’s national economy, is the government’s response to adverse conditions, crises, and temporary shocks to ensure the continuity of farming production, which experiences economic instability and significant destructive losses caused by a full-scale invasion. Based on the diversity of existing state support types and the presence of controversial statements regarding the effectiveness of its mechanisms, the paper aims to identify measures approved in countries with a highly developed agricultural sector that will contribute to strengthening economic security if implemented in the strategy of Ukraine’s agricultural policy. For this objective, linear multiple regression models are used, which allow the identify the dominant types of state support in funding volumes in the EU, Canada, New Zealand, the USA, and Ukraine in 2010–2022, which have a statistically significant impact on the value of agricultural products. It was found that only some types of state support have an empirically confirmed effect on the dependent variable, namely financing payments based on the resources used (New Zealand), payments based on both current (Canada) and non-current (USA) area planted, animal numbers and incomes that require or do not require production, support of agricultural knowledge and innovation (EU, Canada), inspections and control (New Zealand, Ukraine), consumer subsidies (USA, Canada). Supplementing existing inspection and control measures in Ukraine, implemented by New Zealand, will minimize the risk of losses due to diseases, pests, or biological threats and increase the international competitiveness of agricultural products, which is crucial for strengthening the country’s foreign economic security. Separate measures of the Canadian model for direct producer support are justified since their adaptation could facilitate the forced relocation of the breeding stock during a full-scale invasion, which positively influences industrial and food security, or expand the diversity of basic food products, reducing import dependence on them. The provision of tax breaks for bioethanol and biofuel production, which demonstrates statistical significance in the USA, if adopted by Ukraine, increases its energy security level, reducing dependence on imported energy sources through renewable energy development. However, when improving support tools, the limited financial resources that are necessary for their implementation should be borne in mind. Therefore, Ukraine should avoid subsidies tied to non-current production indicators and not require production (USA), as they create an additional burden on the state budget, weakening the level of both budgetary and debt security. In addition, the financing of measures to promote Ukrainian agricultural products (in particular, advertising campaigns and participation in international fairs) did not lead to a growth in its value due to extra demand, new sales markets, or increased consumer awareness of the world market, which is likely evidence of the ineffectiveness of implemented actions in 2010–2022. Using results based on successful international practices adapted to real challenges, Ukraine can improve its state agricultural policy, focusing on strengthening industrial, food, social, energy security, and environmental sustainability, depending on priorities.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».