【正文】 The result of the Johansen cointegration rank test is summarised in Table 3, which indicates the presence of two cointegrating vectors at 1 per cent and 5 per cent levels of significance, respectively (. The null hypotheses of no cointegration is rejected for the rank of zero and less than or equal to 2). This means that there exists a longterm relationship among the three variables. c. The Error Correction Model To analyse the causal relationship between the three variables FDI, DI and GDP, we use an error correction model (ECM) of the following VAR system: When applied to the Chinese data, the VAR system performs quite well. As reported none of the diagnostic statistics are significant at the 95 per cent critical value. Therefore, there is nothing to suggest that the system model is incorrectly specified. Based on the Schwarzz (1978) and Akaike (1974) information criteria, the number of lags is chosen as six. d. Innovation Accounting and theGranger Causality Test The innovation accounting (variance deposition and impulse response function) technique can be utilised to examine the relationships among economic variables . Using this technique, Kim and Seo (2021) explored the plementary or substitution relationship between FDI and domestic investment, and analysed the impact of FDI on economic growth in South Korea. On the other hand, the forecast error variance deposition allows us to make inferences about the proportion of movements in a time series due to its own shocks 7 versus shocks to other variables in the system (Enders, 1995, p. 311). These results suggest that the strength of the relationships between FDI, domestic investment and economic growth are different. FDI plays an important role in China’s economic growth but its influences are less than that of domestic investment ( per cent versus per cent). GDP shows stronger influences on China’s domestic investment than FDI does ( per cent versus per cent). The influences of DI and GDP on FDI are relatively low ( per cent and per cent, respectively). But the relationship between GDP and DI is strong, with a per cent influence from GDP to DI and per cent in reverse. It is noted that each of the three variables explains the preponderance of its own past values (forecast error variances). This means that the current/past FDI, DI and GDP have strong influences on their own future/current trends. The Granger causality test results for the three variables. The results show that: (i) the effects of DI and GDP on FDI are not statistically significant。 (3) FDI has played an important role in China’s economic growth。 1 中文 3078 字 本科畢業(yè)論文外文翻譯 外 文 題 目 ： Foreign Direct Investment, Domestic Investment and Economic Growth in China: A Time Series Analysis 出 處： The World Economy, ,14679701. 作 者： Sumei Tang, E. A. Selvanathan and S. Selvanathan. 外文原稿 Foreign Direct Investment, Domestic Investment and Economic Growth in China: A Time Series Analysis Sumei Tang, E. A. Selvanathan and S. Selvanathan 1. Introduction Despite a large amount of literature on the subject, the role of FDI in economic growth remains highly controversial. The proponents of FDI argue that it helps promote economic growth through technology diffusion and human capital development. This is particularly the case when MNEs in a host economy have vertical interfirm linka