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.
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. The exchange rate, as a relative price between countries and macro-policy variables, plays an important role in the internal and external equilibrium of a country’s economy and the stable development of its economy, which is the key factor influencing the development of foreign economy and trade.
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 then begins to appreciate slowly. Between 1994 and 2005, China’s exchange rate system gradually evolved into a single dollar exchange rate system, to maintain stability. From July 21, 2005, the renminbi was no longer only pegged to dollar, but instead “a more flexible floating exchange rate system based on market supply and demand, and was pegged to a basket of currencies”, and the renminbi against the dollar revalued by 2% percent to 8.11 yuan to $1 at one time.
The renminbi is appreciating against the dollar over the next three years, rising by about 6% a year. By September 2008, the exchange rate between the renminbi and the dollar had risen to 6.83 yuan against 1 dollar. Affected by the financial crisis, our country then suspended the reference to a basket of currencies exchange rate system, again pegged the renminbi exchange rate with the U.S. dollar, basically kept at 6.82 yuan to 1 dollars. Two years later, the world economy recovered slowly, and the People’s Bank of China officially announced on June 19, 2010 that it would continue to push for reform of the renminbi’s exchange rate regime in order to enhance its exchange rate flexibility and floating space. The appreciation of the renminbi increased in 2010-2012, on December 21, 2012, the renminbi’s median exchange rate was about 6.2285. By December 31, 2014, the renminbi’s floating range had widened to 2%, and the renminbi’s median exchange rate was 6.20. Between 2014 and 2015, the renminbi fluctuated against the dollar, but overall the renminbi tended to depreciate. In 2016, devaluation widened further, by December 30, the renminbi’s median exchange rate against the dollar was 6.9370, down about 6.39% compared with the rate on December 31, 2015. In 2017, the renminbi entered a period of slow appreciation, the average of median exchange rate of RMB lowered from 6.8918 in January 2017 to average of 6.5942 in December 2017, appreciating about 4.51%. (Note: the data of exchange rate all come from the People’s Bank of China.)
At the same time, 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. Since 21st century, China’s trade surplus with the United States has continued to rise. According to the Statistics of General Administration of Customs, P. R. China in 2006, China’s U.S. trade surplus against the United States is 1442.63 billion U.S. dollars, accounting for 81.27% of China’s total foreign trade surplus. According to the Statistics of General Administration of Customs, P. R. China in 2017, China-US trade surplus was as highly up to 2758.12 billion U.S. dollars, rose nearly twice. While the Sino-US trade surplus accounted for China’s total trade surplus has fallen to 65.44%, but still high. As to the Exports, China’s exports to the United States have been expanding from 2034.72 billion U.S. dollars in 2006 to 4297.55 billion U.S. dollars in 2017 of, increasing by more than twice. The proportion of exports to the US has fallen from 21.00% in 2006 to 18.99% in 2017, but still stubbornly high.
Under the background of the RMB appreciation, and the increasingly growing of Sino-US trade surplus and the amount of exports, what happened to the Sino-US export trade product structure. 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. Because the trading between countries is similar to some extent, the studies of the relationship between China and America, the largest trading country of China, can set guidelines for China to take some measures to deal with the trade relationship with other countries. Besides, the study can also demonstrate the trade situation and exchange rate fluctuation, thus 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.
In theoretical research, Barry J. Eichengreen (1983) [
In empirical research, based on Japan’s data from 1978 to 1996, Janice Boucher Breuer and Leianne A. clements (2003) [
Under the background of RMB appreciation, domestic scholars have done a lot of research on the relationship between RMB exchange rate fluctuation and export trade structure, mainly focusing on the empirical research. Conclusions can be divided into three categories:
Most scholars’ empirical research results support the view that RMB appreciation is beneficial to the improvement of China’s export trade structure. Zengzheng and Zhang Yabin (2007) [
However, some scholars have found that the appreciation of RMB has no significant effect on China’s export trade structure. Madan and Xu Shaoqiang (2005) [
Another part of scholars’ research shows that the appreciation of RMB will inhibit the improvement of China’s export trade structure. Li Hongbin and Ma Hong, Xiong Yanyan and Xuyuan (2011) [
Overall, domestic and foreign studies have verified the relativity between exchange rate and trade structure both theoretically and empirically, and research about the influence of exchange rate on China’s export trade structure was mainly from country angle. The relationship between exchange rate and Sino-US trade was mainly focused on the study of exchange rate and Sino-US trading volume, with few studies on correlation of exchange rate and the Sino-US export trade structure. Although the US is not China’s biggest exporter, it is China’s largest export country. Therefore, studying the impact of exchange rate changes on the structure of Sino-US exports will not only provide a more convincing play on the relevance of exchange rates and trade structures, but also is possible to explore the difference between bilateral exchange rate changes in the Chinese and American export trade product structure.
In this paper, a vector autoregressive (VAR) model is selected for econometric analysis, in 1980, Christopher Sims based on statistical characteristics of data and proposed VAR model, which constructs the model by using each endogenous variable as a function of the hysteresis value of all endogenous variables in the system. Then the autoregressive model of single variable is extended to the “vector” autoregressive model composed of multivariate time series variables. At the same time, exogenous variables can be introduced into the model, and the general equation expressions of the var model with delay P-order are as follows:
y t = c + M 1 y t − 1 + M 2 y t − 2 + ⋯ + M p y t − p + H x t + ∂ t , t = 1 , 2 , 3 , ⋯ , T
In the model, yt is a column vector of m-dimensional endogenous variables, the xt is an n-dimensional exogenous variable column vector, and p is the delay order of the variables, and T is the number of samples. m * m dimensional matrix M 1 , ⋯ , M p and the m * n dimensional matrix H is the coefficient matrix to be estimated, c is the m-dimensional constant sequence vector, an ∂ t is m-dimensional perturbed column vector. VAR model is a kind of unstructured multiple equation model without prior constraints, but the form is flexible and the parameters are easy to estimate. The model can be used to estimate the general time series data, and then reveal the interaction between endogenous variables in the model. Therefore, this paper uses this model to analyze the relationships between real exchange rate fluctuation of RMB against the dollar and the Sino-US export trade products’ structure.
In this paper, we use RE and ES as endogenous variables, GDPG, FTG and FAG as exogenous variables to set the VAR model, the matrix expressions are as follows:
( E S i , t R E t ) = ( c 0 c 0 ) + ( a 11 1 a 12 1 a 21 1 a 22 1 ) ( E S i , t − 1 R E t − 1 ) + ⋅ ⋅ ⋅ + ( a 11 p a 12 p a 21 p a 22 p ) ( E S i , t − p R E t − p ) + ( b 11 b 12 b 13 b 21 b 22 b 23 ) ( G D P G t F T G t F A G t ) + ( ∂ 1 ∂ 2 )
Note: the explanation of the endogenous variables and exogenous variables are shown in the following context “3.2 Selection of Variables and Data”.
This part will empirically analyze the relationship between China’s export product structure and the real exchange rate of RMB against US dollar. Considering that the RMB exchange rate is more market-oriented after 2005, and for the rationality and accuracy of the thesis research, this paper selects the data from the first quarter of 2006 to the fourth quarter of 2017 for analysis and research, all the data are from the relevant statistical website (detailed below) and after the X12 seasonal adjustment. The following is a detailed description of the variables and data selected in the paper:
The theory shows that the pseudo regression is easy to be generated when the Non-stationary time series data is returned directly by the row least square method (OLS), so we need to test the data smoothly. This paper uses ADF to test the unit root of all variables, and the estimated results obtained by Eviews 7.2 Software are shown in
The stationary test results for all variables can be seen from
In the analysis of VAR model, it is very important to choose the delay order of the variables and the difference of the lagging order leads to the great differences of the estimation results. Large lagging order can better reflect the dynamic relationship between variables, it will reduce the degree of freedom in the system and not conducive to analysis if the order is too large. Therefore, it is necessary to analyze the relationship accurately between the variables in the model without losing its own degree by choosing the appropriate lagging order. The results of the test by Eviews 7.2 based on the preliminary VAR model are shown in
According to
Variables | Value of ADF test | Form of test (c, t, k) | Critical value | Conclusion |
---|---|---|---|---|
RE | −3.05239 | (c, 0, 1) | −2.926622 | Stationary |
ES | −3.28066 | (c, 0, 0) | −2.925169 | Stationary |
GDPG | −4.41518 | (c, 0, 0) | −2.925169 | Stationary |
FTG | −3.49674 | (0, 0, 4) | −1.948686 | Stationary |
FAG | −5.35903 | (c, t, 0) | −3.508508 | Stationary |
Endogenous variables | Meaning and explanation | Data source and processing |
---|---|---|
RE | RErepresents the real exchange rate of RMB against the United States dollar, because nominal exchange rate does not eliminate the price factor between the two countries and can’t reflect the truerelationship between exchange rate and trade structure, this paper uses the Chinese and American Consumer Price index to calculate the bilateral real exchange rate to eliminate the impact of inflation on the exchange rate. | The Sino-US bilateral nominal exchange rate data comes from the People’s Bank of China website, through the monthly final exchange rate data to get the quarterly nominal exchange rate. U.S. monthly CPI data comes from the U.S. Labor Department’s monthly month-on-month CPI, after the X12 seasonal adjustment and then take the monthly average of the U.S. quarterly CPI. China’s monthly month-on-month CPI data comes from the National Bureau of Statistics, processed by the same approach as the United States. Based on the first quarter of 2006, the CPI benchmark index of the United States and China are calculated, and finally calculate the Sino-US bilateral real exchange rate, which is expressed in RE. |
ES | ESrepresentsChina’s export Trade product technology structure, Referring to the classification method of Lall (2000), based on HS classification criteria, this paper divides the export products of the United States into primary products, resource-intensive products, low technology products, medium and high technology products according to the technical value added. The technical structure of China’s exports to the United States is represented by the medium and high technology products’ amount of China’s total amount of exports to the United States, which is expressed in ES. | The HS classified export data are from the People’s Republic of China General Administration website. |
Exogenous variables | Meaning and explanation. | Data source and processing. |
GDPG | GDPGrepresentsUS real GDP growth rate, the real GDP growth rate in the United States is to explain its changes to the export structure from the perspective of American demand for China’s export trade products. The real GDP growth rate of US represents the change rate of foreign income, and the change of foreign income will affect the change of American demand for China’s export products. While the foreign consumers have different income elasticity to the demand of China’s export trade products. Therefore, the change of income will cause the change of demand. The export scale of China’s export products has different degrees of impact on the export of our products structure, but the impact of the change of export structure and exchange ratechange on foreign GDP growth rate is small, so in this paper , the real GDP growth rate is an exogenous variable. | The data of America’s quarterly real GDP come from the U.S. Bureau of Economic, which was seasonally adjusted by X12 to calculate the real GDP growth rate for the quarter, expressed in GDPG. |
FTG | FTGrepresentsthe proportion of the FDI to GDP, the proportion of the FDI to GDP is to explain its changes to the structure of export trade from the point of supply of export trade, because China’s FDI enterprises have a very important role in China’s export. The movement of international capital is often accompanied by the movement of technology, management experience and so on, and the advanced technology will bring the change of product technology content, and finally promote the change of export trade structure. the proportion of the FDI to GDP represents the role of foreign capital in China’s economy, to explain the impact of source of factors on export structure. The existing literatures regarded it as an endogenous variable when using VAR model to deal with the research, but in this paper we argue that FDI is a policy variable to a large extent, which is influenced by the factors of national policy. The impact of export structure on FDI is smaller, so the proportion of FDI to GDP is analyzed as exogenous variable. | China’s GDP data are from the National Bureau of Statistics, and FDI are the actual amount of foreign investment, coming from the Ministry of Commerce. |
FAG | FAGrepresentsGrowth rate of fixed asset investment completion, the growth rate of fixed assets investment is to measure the change of domestic investment level, the change of domestic investment level will have some influence on China’s foreign export trade structure, this paper analyzes it as exogenous variable in the model. | The quarterly data of the fixed assets investment completion and the quarterly data of the real estate development investment are all from the National Bureau of Statistics. Considering that the investment in real estate development will not enter into the trade products industry, the real estate development investment completion amount is deducted from the completion amount of the fixed assets investment as the fixed assets investment. Using the quarterly fixed asset Investment price index (from the National Bureau of Statistics) to eliminate price factors to obtain the quarterly data of actual fixed asset investment completion, and then adjusts seasonally with X12 method, finally get the growth rate of real fixed assets investment in the quarter. |
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Lag | Log L | LR | FPE | AIC | SC | HQ |
---|---|---|---|---|---|---|
0 | 132.4119 | NA | 1.20E−05 | −5.655086 | −5.330688 | −5.534784 |
1 | 209.8682 | 133.7881 | 4.27E−07 | −8.994009 | −8.507411 | −8.813555 |
2 | 217.8636 | 13.08346* | 3.58e−07* | −9.175620* | −8.526824* | −8.935015* |
3 | 219.1863 | 2.044145 | 4.07E−07 | −9.053924 | −8.242928 | −8.753167 |
4 | 222.0738 | 4.199969 | 4.34E−07 | −9.003354 | −8.03016 | −8.642447 |
Note: *Represents the lagging order of the selected from each column criterion.
Although the optimal lag order of the model has been determined, it does not ensure that the relevant estimation results are effective. It requires that the model is stable, and the condition of the model stability is the reciprocal of the modulus of all the roots are in the unit circle. If the reciprocal of four roots exists outside the unit circle, then the model may not be stable, and the model’s impulse response and variance decomposition analysis may be ineffective. The unit root diagram of the model is shown in
According to
The causal relationship tested by Granger causality test is not a general cause and result, and its essence is whether a variable’s hysteresis can be introduced into the equation of another variable for interpretation and analysis. If the lag term of a variable has an effect on another variable, it is said that there is a causal relationship between them. In this paper, we did the Granger causality test in the 2-order VAR model, and the results are shown in
According to
technical product structure, while the Sino-US export trade technology product structure is not the Granger reason of Sino-US bilateral real exchange rate. This demonstrates that the change of real exchange rate can explain the change of China’s export Trade product technology structure to America.
In the analysis of VAR model, we usually do not analyze the influence of the change of one variable to other variables, but the influence of the endogenous variable on the other endogenous variables in the system, which is the analysis method of impulse response. In this part, the impulse response function is analyzed based on the VAR model set before, the specific pulse response diagram is shown in
According to
second phase has the biggest negative response, for −0.004019. The negative response showed a gradual downward trend, and at the fifth phase shifted to a positive response of 0.000181. Subsequently, the response gradually expanded, at the 10th phase, it reached the maximum, 0.001792. Finally, this positive response tends to be 0. In terms of impulse response, a positive impact on the real exchange rate of RMB against the dollar will have a negative effect on China-US export trade technology product structure, but the long-term effect is positive and the overall response is positive. This shows that the real appreciation of the dollar (real exchange rate depreciation), in the short term, will inhibit the improvement of China-US export trade technology product structure (the increase of the export ratio of medium and high technology products), and promote the improvement of the structure of China-US export trade technology products in the later period. Therefore, from the current background of RMB appreciation, the appreciation of RMB real exchange rate will promote the improvement of China-US export trade technology product structure (the ratio of medium and high technology export products) in the short term, which is the largest in the second phase, then the improvement effect is gradually reduced and the latter is negative. In the long run, the appreciation of RMB real exchange rate is unfavorable to the improvement of China-US export trade technology product structure (ratio of medium and high technology export products).
It can be seen from
The impulse response analysis reveals the influence of an endogenous variable in an economic system on other endogenous variables and its influence path after suffering from an external shock. Instead, the variance decomposition method is to analyze the contribution of each structural impact to the variation of internal variables (generally measured by variance), and then to evaluate the importance of structural impact in the model. Therefore, the variance decomposition of the variables produced in the system can be decomposed by variance, we can analyze the relative importance of each random perturbation which affects the variables in the model. The detailed variance decomposition diagram is shown in
From the variance decomposition diagram
From the variance decomposition diagram
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. Combining theory with practice, and 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. The Chinese and American Export trade technology product structure is not the Granger reason of Sino-US bilateral real exchange rate. It shows that the real exchange rate between China and America will have an impact on the structure of China-US export trade technology products.
Secondly, the analysis of impulse response function based on VAR model shows the effect of bilateral real effective exchange rate on the structure of China-US export trade technology products. The real effective exchange rate between China and America can be divided into two parts in the process of export trade technology product structure. The first part is the negative impact of one to four periods, the Sino-US bilateral real exchange rate, after suffering from a positive impact (the devaluation of the renminbi) in the first phase, will have a negative effect on Sino-US Export trade technology product structure, and this negative effect reaches to the largest in the second phase, and then continues to reduce. In the fifth phase, the positive effect of the second part begins to occur, and becomes the largest in the tenth phase, then gradually reduces to zero, but the overall effect is positive. Therefore, in the short term, the depreciation of the real exchange rate (appreciation) of the renminbi is not conducive (conducive) to the improvement of China-US bilateral export trade product structure. However, in the long run, the depreciation of RMB real exchange rate (revaluation) is beneficial (unbeneficial) to the improvement of China-US bilateral export trade product structure, but this influence of improvement reduces gradually. Overall, the appreciation of Sino-US bilateral real exchange rate is in favor of promoting the optimization of China-US export trade technology product structure.
Finally, from the variance decomposition of VAR model, the Sino-US bilateral real exchange rate has contributed greatly to the change of China-US export trade technology product structure, which has a tendency of increasing with time.
Although China’s exports of High-tech products to the United States are numerous, one big reason is that developed countries outsource the final assembly of High-technology products to low-wage developing countries, and these High-technology products are “statistical hallucinations” for these developing countries. Therefore, the technical structure of Sino-US export trade containing the processing trade cannot truly reflect the technical structure of China’s exports to the US. And the calculated technical structure of Sino-US export trade may be exaggerated, which cannot precisely reflect the changes in the technical structure of trade products, thus the relationship between the exchange rate and the technical structure of Sino-US export may not be true. Therefore, for the future research, the general trade products and processing trade products in the technical structure of Sino-US trade products may be studied precisely.
Lu, Y.L. (2018) The Influence of RMB Real Exchange Rate on the Technical Structure of Sino-US Export Trade Products. American Journal of Industrial and Business Management, 8, 1261-1276. https://doi.org/10.4236/ajibm.2018.85086