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Enregistrement W2989776417 · doi:10.32702/2306-6814.2019.21.63

TRADE LIBERALIZATION: THEORY, PREDICTING THE CONSEQUENCES OF IMPLEMENTATION AND PRACTICAL REALITIES

2019· article· en· W2989776417 sur OpenAlexaboutno aff
Mark Hellyer

Notice bibliographique

RevueInvestytsiyi praktyka ta dosvid · 2019
Typearticle
Langueen
DomaineEconomics, Econometrics and Finance
ThématiqueEconomic Issues in Ukraine
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésFree tradeEconomicsOpenness to experienceTrade barrierInternational economicsLiberalizationInternational tradeInternational free trade agreementEconomic integrationSubsidyCommercial policyContext (archaeology)Market economy

Résumé

récupéré en direct d'OpenAlex

Background. The competitive positions of countries and their companies largely depend on the nature of participation in international economic interaction. It has been proven that countries with high levels of economic development are benefiting from foreign trade through liberalization. However, it remains debatable how much positive expectations identified in trade liberalization theory can be put into practice in economically peripheral countries. The fundamental scientific basis for studying the correlation of economic openness in the context of the impact on economic growth, including ambiguous and contradictory impact of trade liberalization, have been studied by various scholars. However, since antagonists of trade liberalization theory often do not fully understand all the positive effects of its application, research in this area is relevant. The goal of this study is to analyze the development and foundations of trade liberalization theory, as well as to compare projections of the effects of trade liberalization between Ukraine and the EU under the terms of the Deep and Comprehensive Free Trade Area (DCFTA) and the practical realities. The main results of the research. International trade theory provides explanations for the impact of international trade and the distribution of the gains from trade and particularly trade liberalisation through preferential trade agreements. Classical trade theory supports free trade and advocates against tariffs and restrictions. The assumptions behind the classical trade theory are the following: Completely free trade; no subsidies, tariffs, or commercial restrictions; Frictionless inter-sectoral transfer of labour. However these assumptions do not hold in the real world and gives rise to the debate on the conditions under which free trade provides Gains from Trade. In the Heckscher-Ohlin model of trade, each nation's comparative advantage is traced to its particular endowments of different factors of production: that is, basic inputs such as land, labour, and capital. Since the costs of these inputs in each country will depend on their availability, differences in factor endowments across countries will create differences in comparative advantage. Each country will tend to export items whose production requires intensive use of the factors with which it is abundantly endowed relative to other nations; conversely, each country will import goods whose production requires intensive use of factors that are relatively scarce. Therefore, countries well endowed with land, like Australia and Canada, and indeed Ukraine, are thus expected to export agricultural products (e.g., wheat and wool), while importing products that require the intensive use of labour (e.g., textiles and footwear). The article emphasized that Classical theory and Heckscher-Ohlin theory is further developed by the factor price equalization theory, by Paul A. Samuelson. Economic theory of equalization of factors and prices implies that free trade should lead to trends in the equalization of income, capital and labour in different countries. The example of graphical models illustrates what to expect in an economy that can move from protection to free trade. It has been shown that this will lead to a net increase in welfare. This made it possible to formulate a scientific understanding of why trade theory supports trade liberalization through preferential trade agreements, such as the DCFTA between the EU and Ukraine. The results of this agreement, as shown by the systematization of short— and long-term expectations, should be to increase trade, more effective allocation of resources, equalise wages and stimulate economic growth. According to forecasts, six sectors in Ukraine were expected to generate additional increases in Exports to the EU of over 20% net. However, we stressed that Ukrainian business entities will only gain access to the domestic market if European standards are established and technical regulations are complied with. At the same time, the cost of implementation of EU standards and retrofitting of production should be compensated by the flow of European investment which is going to stimulate restructuring and retrofitting of companies, facilitate new businesses and, as the result, increase the state' revenues. Our personal research has revealed that with 4 years of data since the effective application of DCFTA provisions on Ukraine's exports to the EU, it shows that Ukraine's exports have not significantly improved under the DCFTA. This runs contrary to both the EU and Ukrainian policy objective of the DCFTA as well as traditional economic theory. Conclusions. According to the traditional economic theory, trade liberalization brings not only traditional "static gains" from specialization, but also the adoption of new technologies and skills, leading to "dynamic gains" from trade — to higher productivity. But in the case of the practical implementation of the DCFTA on Ukraine's exports to the EU, the opposite consequences were found. It is noted that the results obtained during this study can be used for further research towards optimizing the processes of liberalization and upholding national economic interests in the context of the objective growth of world trade. Our data can also be used to find the real reasons that did not allow the country to benefit from the implementation of the DCFTA, as well as to develop measures to eliminate or minimize the negative effects.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,004
score de la tête « metaresearch » (Gemma)0,016
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: Théorique ou conceptuel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,009
Score d'incertitude au seuil0,031

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0040,016
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0020,003
Études des sciences et des technologies0,0010,008
Communication savante0,0040,005
Science ouverte0,0010,002
Intégrité de la recherche0,0020,002
Charge utile insuffisante (le modèle a refusé de juger)0,0090,001

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.

Tête enseignante Opus0,052
Tête enseignante GPT0,297
Écart entre enseignants0,244 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeThéorique ou conceptuel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2019
Routes d'admission1
Résumé présentoui

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