Is Laos a ready member of a potential Renminbi zone under the Belt and Road Initiative?
Wei Sun et al.
What the paper says
Purpose This study aims to empirically assess whether Laos may be a suitable candidate for a potential Renminbi (RMB) zone under the Belt and Road Initiative (BRI) based on the optimum currency area (OCA) theory. Design/methodology/approach This paper develops a two-country structural vector autoregression model, identify structural shocks using both the Uhlig’s (2005) sign restrictions and the Bjørland and Leitemo’s (2009) combination of short-run and long-run zero restrictions, and analyze the impacts of China’s supply and demand shocks on Laos’ gross domestic product (GDP) and price level using data from 1984 to 2023. Findings This paper finds that the BRI has played a positive role in promoting the Laos−China economic integration: Over time, the effects of China’s macroeconomic shocks not only increased but also became the dominant force driving Laos’ economy during the BRI period of 1999–2023. Research limitations/implications This study is limited by data availability for Laos. Higher-frequency data, if available, would have revealed more nuances in the evolution of economic integration between the two countries. Practical implications The findings suggest that, according to the Eurozone standard in Chow and Kim (2003), joining a Renminbi zone may be feasible for Laos as the BRI continues to strengthen economic ties between the two countries. Originality/value To the best of the authors’ knowledge, this study is the first attempt to quantitatively assess economic integration between Laos and China, with a particular focus on the impact of the BRI. The findings may provide insights into important policy issues related to the BRI, the RMB’s role in the global economy, and Laos’ future exchange rate management.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.