The United States’ Clothing Imports from Asian Countries along the Belt and Road: An Extended Gravity Trade Model with Application of Artificial Neural Network

Danny Chi Kuen Ho, Eve Man Hin Chan, Tsz Leung Yip and Chi-Wing Tsang
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Danny Chi Kuen Ho: Department of Supply Chain and Information Management, The Hang Seng University of Hong Kong, Hong Kong 999077, China
Eve Man Hin Chan: Faculty of Design and Environment, Technological and Higher Education Institute of Hong Kong (THEi), Hong Kong 999077, China
Tsz Leung Yip: Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Hong Kong 999077, China
Chi-Wing Tsang: Faculty of Science and Technology, Technological and Higher Education Institute of Hong Kong (THEi), Hong Kong 999077, China

Sustainability, 2020, vol. 12, issue 18, 1-15

Abstract: In 2013, China announced the Belt and Road Initiative (BRI), which aims to promote the connectivity of Asia, Europe, and Africa and deepen mutually beneficial economic cooperation among member countries. Past studies have reported a positive impact of the BRI on trade between China and its partner countries along the Belt and Road (B&R). However, less is known about its effect on the sectoral trade between the B&R countries and countries that show little support of the BRI. To address that gap, this study examines the changing patterns of clothing imports by the United States (US) from China and 14 B&R countries in Asia. An extended gravity model with a policy variable BRI is built to explain bilateral clothing trade flow. A panel regression model and artificial neural network (ANN) are developed based on the data collected from 1998 to 2018 and applied to predict the trade pattern of 2019. The results show a positive effect of the BRI on the clothing exports of some Asian developing countries along the B&R to the US and demonstrate the superior predictive power of the ANN. More research is needed to examine the balance between economic growth and the social and environmental sustainability of developing countries and to apply more advanced machine learning algorithms to examine global trade flow under the BRI.

Keywords: clothing trade; Belt and Road initiative; gravity trade model; panel data regression; artificial neural network (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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