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Enregistrement W6950406812 · doi:10.5281/zenodo.7435246

AUGMENTED GRAVITY MODEL: AN EMPIRICAL INVESTIGATION INTO INDIA'S TRADE FLOWS DURING TWO EXIM POLICY PERIODS

2022· article· en· W6950406812 sur OpenAlexaboutno aff

Notice bibliographique

RevueZenodo (CERN European Organization for Nuclear Research) · 2022
Typearticle
Langueen
DomaineEconomics, Econometrics and Finance
ThématiqueIndian Economic and Social Development
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésRupeeDevaluationIncentiveValue (mathematics)TariffTerms of tradeLiberian dollarExport subsidyDumpingBalance of trade

Résumé

récupéré en direct d'OpenAlex

Indian exports slowed for a long time because the country relied heavily on agricultural products like tea, jute, and cotton. The inelastic demand for these products cannot be overstated, and India's exportable goods were not competitively priced. Following the devaluation of the rupee in 1966, the government entered into several treaties with socialist countries and began offering fiscal and monetary incentives to their citizens. In addition, several councils and agencies were established to boost exports. In the 1970s, exports proliferated for all these reasons. However, because most exportable commodities were primary goods, our import bill has always been greater than the export value. Due to rising domestic consumption, India exported only a small percentage of its surplus. It was concluded that tax incentives and similar programs to encourage exports were insufficient. Developed nations, such as the United States, raised tariff barriers to combat imports from less developed nations. It is worth noting that the unit value of exportable goods increased by a much larger margin than the quantum index of exports when most developed countries were experiencing economic recession. Due to rapid industrialization and the government's efforts to supplement domestic production and maintain a minimum level of buffer stock by regularly importing food grains from 1958-59 to 1972-73 under the PL 480 scheme, the value of India's imports rose above the value of its exports since 1951. Increasing imports and supplies of price-sensitive commodities like cement, edible oils, etc., had helped keep inflation in India under control. In the name of boosting exports, imports have been liberalized, allowing entry of both necessary and luxury items. Since 1973, when OPEC was formed, oil prices have been ramped up regularly. India's import costs have increased because of this. The new FTP (2009-14) includes several provisions designed to promote steady growth in international trade and reverse a last ten-month decline in exports. The measures include both financial and procedural leniencies. For 2010–11, exports were projected to reach $200 billion, representing a 15 percent increase for the forecast period. The FTP also plans for an annual growth rate of 25% in the medium term. Therefore, it was anticipated that improvements to export-related infrastructure, a decrease in transaction costs, and the provision of full refunds of all indirect taxes and levies would all contribute to meeting the targets. In the past, the Foreign Trade Policy 2009-14 included five separate schemes for incentivizing merchandise exports with duty scrips of varying types and conditions (sector-specific or actual user only) such as the Focus Product Scheme, the Market Linked Focus Product Scheme, the Focus Market Scheme, the Agricultural Infrastructure Incentive Scrip, and the VKGUY (Vishesh Krishi and Gram Udyog Yojana). The Foreign Trade Policy 2015-2020 (FTP 2015-20) has consolidated all of these programs into a single program called the Merchandise Export from India Scheme (MEIS), and the scrips issued under the program will no longer be subject to any conditions. The critical components of MEIS include information on the various product groups supported by MEIS. Under the Foreign Trade Policy 2015-2020, the MEIS plan applies to the following nation clusters: Category A: Traditional Markets (30) - European Union (28), USA, and Canada. The 139 nations in Category B, Emerging & Focus Markets, including those in Africa (55), Latin America and Mexico (45), the Commonwealth of Independent States (12), Turkey and West Asian countries (13), the Association of Southeast Asian Nations (10), Japan, South Korea, China, and Taiwan. Category C: All Other Markets (70). The following section of literature review followed by estimation of gravity model for EXIM policy 2010-15 and 2015-20.

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 distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesÉtudes des sciences et des technologies, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesCharge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,736
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0040,000
Communication savante0,0000,000
Science ouverte0,0010,001
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0050,001

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 Opus0,050
Tête enseignante GPT0,261
Écart entre enseignants0,211 · 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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeSans objet
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

Citations0
Publié2022
Routes d'admission1
Résumé présentoui

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