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Factors Driving Openness in China Trade: Corruption, Exchange Rate Volatility, and Macro Determinants

Author

Listed:
  • Thong Trung Nguyen

    (School of Banking, University of Economics Ho Chi Minh City, Vietnam)

  • Toan Luu Duc Huynh

    (School of Banking, University of Economics Ho Chi Minh City, Vietnam)

  • Wing-Keung Wong

    (Department of Finance, Fintech & Blockchain Research Center, and Big Data Research Center Asia University, Taiwan3Department of Medical Research, China Medical University Hospital, Taiwan4Department of Economics and Finance, Hang Seng University of Hong Kong, Hong Kong)

Abstract

Trade openness plays a critical role in the growth of China and its partners. Using a system generalized method of moments (system GMM) estimator and quantile regression, a new viewpoint is presented on trade openness in China for institutional and economic factors over 15 years with 192 economies. The empirical findings provide two contrasting views. Intriguingly, China is seeking to broaden this strategy to countries with less control over corruption and low political stability. By categorizing countries as advanced, emerging, and developing, the study provides the evidence that exchange rate volatility has a negative effect on trade openness, while investment, labor force, and broad money share a positive impact. This study suggests that Chinese policymakers should further boost financial reform to promote trade development. Other countries desirous of greater trade openness with China should have more efficient management of macroscopic economic factors. Finally, the study also examines the two main groups of international offshore financial center from econometric convergence test and club clustering for trade openness in China from the worldwide perspective.

Suggested Citation

  • Thong Trung Nguyen & Toan Luu Duc Huynh & Wing-Keung Wong, 2021. "Factors Driving Openness in China Trade: Corruption, Exchange Rate Volatility, and Macro Determinants," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 24(02), pages 1-25, June.
    • Handle: RePEc:wsi:rpbfmp:v:24:y:2021:i:02:n:s0219091521500168
    DOI: 10.1142/S0219091521500168
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    Cited by:

    1. Kola Ijasan & Peterson Owusu Junior & George Tweneboah & Tunbosun Oyedokun & Anokye M. Adam, 2021. "Analysing the relationship between global REITs and exchange rates: Fresh evidence from frequency-based quantile regressions," Advances in Decision Sciences, Asia University, Taiwan, vol. 25(3), pages 58-91, September.

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