Quantitative Dynamics Effects of Belt and Road Economies Trade Using Structural Gravity and Neural Networks

Bibliographic Data

ID3305050
AuthorsKoffi Dumor (0000-0002-1764-7025, University of Electronic Science and Technology of China, corresponding author), Yao Li (0000-0002-1093-3301, University of Electronic Science and Technology of China), Li Yao (0000-0002-7283-7462), Jean-Paul Ainam (0000-0001-8081-6867, Rensselaer Polytechnic Institute), Edem Koffi Amouzou (0000-0002-7725-0767, University of Electronic Science and Technology of China), Williams Ayivi (University of Electronic Science and Technology of China)
Year2021
Volume11
Issue3
Publication date2021-07-01
Open AccessYes
TypeARTICLE
VenueSAGE Open (JOURNAL)
Journal identifiersISSN: 2158-2440 • E-ISSN: 2158-2440
PublisherSAGE Publications Inc (PUBLISHER)
DOI10.1177/21582440211032662
OpenAlexW3183364846
LanguageEN
Citations received2
References cited47

Recent research suggests that China's Belt and Road Initiative (BRI) would improve the bilateral trade between China and its partners. This article uses detailed bilateral export data from 1990 to 2017 to investigate the impact of China's BRI on its trade partners using neural network analysis techniques and structural gravity model estimations. Our main findings suggest that the BRI countries would raise exports by a modest 5.053%. This indicates that export and network upgrades should be considered from economic and policy perspectives. The results also show that neural networks is more robust compared with structural gravity framework

Artificial neural network · Bilateral trade · Business · China · Economics · Geography · Gravity model of trade · International economics · International trade · Computer Science · Fiscal Policy and Economic Growth · Global Trade and Competitiveness · Global trade and economics · Artificial Intelligence

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