外文翻譯--中國的fdi國內(nèi)投資與經(jīng)濟增長：一個時間序列分析-wenkub
2023-05-19 08:13:59 本頁面
【正文】 經(jīng)濟變量之間的關(guān)系。 （三）誤差修正模型 為了分析 FDI, DI 和 GDP 這三個變量間的因果聯(lián)系，選用 VAR 系統(tǒng)下的誤差修正變量模型（ ECM）：本 文中的數(shù)據(jù)在這個變量系統(tǒng)中運用得非常好。在仔細的選擇和檢驗后，選折一個由滯后長度為 穩(wěn)定的、周期性虛擬變量組成的模型。它們表明單位根的 0 假設(shè)是： （ a） 接受 FDI 在三個模型中的水平序列； （ b） 拒絕 DI 在模型（ 3）中的水平序列； （ c） 拒絕 GDP 在模型（ 1）的水平序列。 11 從圖 4（ ac）可以看出 ,三個序列水平是不平穩(wěn)的。由于缺乏季度和月度本地 GDP 統(tǒng)計數(shù)據(jù)，本季的 GDP是在每月工業(yè)總產(chǎn)值 (GIO)和每年的國內(nèi)生產(chǎn)總值的統(tǒng)計數(shù)據(jù)的基礎(chǔ)上得到的。 FDI/DI 的比率從 1978 年 %急劇增加到 1984 年的 %，到 1994 年已達到了 %的空前的高峰。在改革開放期間 , 為了吸引外商直接投資中國政府出臺了許多新的改善投資和經(jīng)營環(huán)境立法措施。最后，我們的變量模型包括長期動態(tài)因素、企業(yè)內(nèi)容管理。第 一，這是現(xiàn)有的研究中第一次直接去檢驗中國的 FDI 和國內(nèi)投資間的聯(lián)系。此外， FDI也可能通 過國內(nèi)商品的替代進口破壞經(jīng)濟的后部聯(lián)系。 相反，反對 FDI 促進增長論者認為 FDI 擠出國內(nèi)投資，并對經(jīng)濟增長有負面影響。 FDI 還有可能導(dǎo)致東道國出口需求增加，從而為出口產(chǎn)業(yè)吸引更多的投資。 FDI 的支持者表示 FDI 可 以通過技術(shù)外溢與人力資本發(fā)展帶動經(jīng)濟增長。 (b) rejected for the level series of DI in model (3), and (c) rejected for the level series of GDP in model (1). 6 Based on the first differenced data, the results indicate that all three series are stationary. Therefore, we conclude that the three time series are all integrated of order 1, I(1). b. Testing for Cointegration of Variables Now, the cointegration test is performed to investigate any longterm equilibrium relationships among the three variables of FDI, DI and GDP. After a careful search and trial, a model with six lags, constant and centred seasonal dummy variable was chosen. 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 (2020) 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 G
畢業(yè)設(shè)計相關(guān)推薦
鄂ICP備17016276號-1