Abstract

Based on the classification of HS (Harmonized Commodity Description and Coding System), and according to the method of Lall (2000) [1], Sino-US trade products are divided into five categories, namely primary products, resource-intensive products, low technology products, medium technical products and high-tech products. Based on the data from the first quarter of 2005 to the fourth quarter of 2017, the influence of bilateral real exchange rate on the structure of Sino-US export trade was studied by using VAR model in this paper. The empirical results show that there is a strong granger causality between Sino-US bilateral real exchange rate and Sino-US export trade product structure, the former being the latter’s granger reason; in the short term, the appreciation (devaluation) of the real exchange rate between China and the US is conducive (inconducive) to an improvement in the trade structure, which has long been detrimental (beneficial) to the improvement of the trade structure. In general, the appreciation of RMB is unfavorable to the improvement of the technical structure of Sino-US export trade. Variance decomposition shows that Sino-US bilateral real exchange rate has a great contribution to the technical structure of Sino-US export trade.

Highlights

  • Based on the standard International Trade Classification (SITC), Xiao Quanxi and Liao Wenxiu (2012) [11], Yu Juanjuan and Linling (2013) [12], studied the exchange rate elasticity of the export amounts of large categories of encoded goods, the results show that the negative impact of RMB revaluation on capital-intensive products is less than the negative impact on the export of labor and resource-intensive products, which is conducive to the improvement of export structure

  • This paper studies the relationship between the real exchange rate of RMB against the United States dollar and China’s export trade product structure on the basis of HS classification

  • Based on the quarterly data of Sino-US bilateral real exchange rate fluctuation and Sino-US export trade technology product structure since 2005, the effect of bilateral real exchange rate fluctuation on the structure of Sino-US bilateral export trade is analyzed by using the vector autoregressive model, and the following main conclusions are obtained: Firstly, the Granger causality test of endogenous variables in VAR model shows that the real exchange rate between China and America is the Granger reason of China-US export trade technology product structure

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Summary

Introduction

Under the background of economic globalization and the gradual opening of international market, the sustained and steady development of foreign trade of a country is the key factor to achieve economic growth and external equilibrium. Since 1994, China has implemented “a single, managed floating exchange rate system based on market supply and demand”, which has been the combination of official quotations and adjustment prices for the RMB exchange rate, and the US dollar against the renminbi has been lowered to 8.70, according to the People’s Bank of China, and begins to appreciate slowly. Despite the slow rise in 2005 and the sharp appreciation after the exchange change, China’s export trade with the United States is not in line with expectations. Under the historical background of RMB internationalization, supply side reform and trade structure optimization, the United States, as the largest trading country of China, studies about the relationship between exchange rate fluctuation and the technical structure of Sino-US export trade products, has certain practical significance and instructive significance. The study can demonstrate the trade situation and exchange rate fluctuation, helping China to reflect on the effect of the exchange rate on different industries and products, which may be helpful for the making and implementation of some relevant policy

Literature Review
Selection of Variables and Data
ADF Test
Selection of the Lagging Order
Conclusion
Stability Test
Granger Causality Test
The Analysis of Impulse Response
The Analysis of Variance Decomposition
Findings
Conclusions
Full Text
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