Current State and Prospects of Russia – China Trade Development in the BRICS Format
Notice bibliographique
Résumé
Motivation: The substantiation of the scientific problem and the practical value of the study are determined by the enhanced cooperation of the BRICS countries, in particular the growing weight of Russia and China on the world stage. The main objective of the study: is to analyze the problems of the development of bilateral trade between China and Russia and to provide a statistically proven forecast for this trade for 2019-2020, as well as to develop recommendations for the improvement of bilateral trade relations. Novelty: The author’s statistical model was developed and its testing was presented through confirming the 24-month forecast of bilateral trade between Russia and China. The model involves solving various problems of bilateral trade. Recommendations for improvement of bilateral trade relations are proposed through formation of an investment and innovation model of bilateral trade. Methodology and Methods: The work used the method of forecasting time series, which suggested the use of a model to predict future values based on previously observed values. To evaluate the modern prospects of the trade between the countries, the authors produced a forecast of the goods turnover trend for 2019-2020. The forecast was issued via the software tool Statgraphics Centurion 18. A reasonable model of the 24-month forecast based on the statistical model Random Walk is developed. The adequacy of the proposed forecast model was subjected to statistical tests. To verify the statistical adequacy of the model the relevant tests were done to determine the compliance of the model with the informational criteria ME (Mean Error), MSE (Mean Squared Error), МРЕ (Mean Absolute Error), МРРЕ (Mean Absolute Percentage Error), МРЕ (Mean Percentage Error). However, it should be noted that the forecast was issued in accordance with the trends which had been identified in the preceding periods. Data and empirical analysis: The factors influencing bilateral trade are analyzed, as well as examples of implemented projects of international cooperation between Russia and China are presented. The current dynamics of sales turnover between Russia and China for the period of 2010-2018 with the use of various statistical and analytical methods is studied, and a reasonable model of the 24-month forecast based on the statistical model Random Walk is developed. The adequacy of the proposed forecast model was subjected to statistical tests. The basic hypothesis is suggested for the upward trend based on reference time series. Policy considerations: It can be said with certainty that the level of technological development of BRICS countries will help Russia and China to start building their cooperation in many fields at a completely new level, taking into account their joint experience in overcoming global crises and Western sanctions. International cooperation between Russia and China in the innovation field will help them unite their efforts and achieve significant synergy. Coordination of countries on this issue will help to reduce production costs, cooperation of production, joint research and development, as well as increase bilateral trade turnover.
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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 | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| 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 ».