Global merchandise and agricultural trade developments during WTO regime: Commercial crops performance
Notice bibliographique
Résumé
Abstract Global trade has increased the growth proportionally over the last two centuries. Trade increases the prosperity of nation, fueling economic growth, rising employment opportunities, reducing poverty, and raising the living standards of the people. The study period is from 1990–1991 to 2018–2019. Compound annual growth rate (CAGR), coefficient of variation, moving average method, terms of trade, and elasticity of total merchandise, agricultural, and commercial crops exports and imports were used to achieve objectives. The study revealed that agricultural trade shared very less percentage out of total merchandise trade in the world, that is, 7.55%. South America and South Africa (poor continent) have shown the highest percentage of agricultural commodities traded out of total merchandise trade. Richest continents such as Europe, North America, and Asia shared very less percentage of agricultural commodities traded to total merchandise trade. Globally, China, USA, and Germany highly expanded their trade. China and Republic of Korea were the largest exporting and importing countries of total traded goods. Brazil, Spain, and China were shown the highest significant growth potential of agricultural exports, whereas China, Canada, and USA have shown the highest growth rate of agricultural imports in the world during the study period. America was exporting more quantity of cotton, tea, rubber, and opium while importing tobacco and coffee. Asia was exporting more quantity of sugar crops and coffee while importing cotton, jute, opium, rubber, tea, and tobacco. Africa was exporting more quantity of cotton, jute, tea, and rubber while importing sugar crops, cocoa, tobacco, and coffee. Europe was exporting more quantity of tea, rubber, opium, tobacco, and coffee while importing cocoa. More quantity of opium by America and Europe; coffee by Europe; and sugar crops by Asia was exported with the highest price in the world. Terms of trade was favored for sugar crops, jute, opium, and coffee in the Africa; cocoa, opium, rubber, tea, and coffee in the Europe; and rubber in the America. Export price elasticity of sugar crops, cotton, jute, opium, rubber, and coffee in the America; jute in the Asia; cotton, rubber, and tobacco in the Africa; and sugar crops, opium, rubber, tea, tobacco, and coffee in the Europe was marginally greater than their imports. Countries governments that are growing commercial crops must give prominence in framing price policies for the cash crops. Governments should take action against the unfair competition existing in the international markets of cash crops especially for opium and tobacco. The study found that even Neoliberal globalization modern period also, developing countries and continents such as Africa, Latin America and South America trade economies are more depend on agriculture and developed countries more on manufactured sector. Developing countries and continents must design strategies and policies to promote manufactured sectors keeping agriculture sector self‐sufficiency.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».