中國的FDI,國內(nèi)投資與經(jīng)濟(jì)增長：一個(gè)時(shí)間序列分析[文獻(xiàn)翻譯]

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, 2008.10,1467-9701. 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 AnalysisSumei Tang, E. A. Selvanathan and S. Selvanathan1. 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 inter-firm linkages with domestic firms or have sub-national or sub-regional clusters of inter-related activities. Through formal and informal links and social contacts among employees, MNEs diffuse technology and management know-how to indigenous firms. Consequently, economic rents are created accruing to old technologies and traditional management styles. Also, FDI helps overcome capital shortage in host countries and complements domestic investment when FDI flows to high-risk areas or new industries where domestic investment is limited. When FDI occurs in resource industries, domestic investment in related industries may be stimulated. Moreover, FDI may result in an increased demand for exports from the host country, helping attract investment in the export industries. Empirical studies supporting these arguments include Sun (1998) and Shan (2002). Using the conventional regression model and panel data, Sun (1998) finds a high and significantly positive correlation between FDI and domestic investment in China. Shan (2002) uses a VAR model to examine the inter-relationships between FDI,industrial output growth and other variables in China. He concludes that FDI has a significantly beneficial impact on the Chinese economy when the ratio of FDI to industrial output rises. In contrast, opponents of FDI argue that FDI crowds out domestic investment, and has an adverse effect on growth . In particular, the industrial organisation theory stipulates that FDI is an aggressive global strategy by MNEs to advance monopoly power over and above indigenous firms of the host economy. The ownership-specific advantages of MNEs (e.g.advanced technologies, management know-how skills, transaction cost minimising and other intangible advantages)could be transformed into monopoly power. This monopoly power can be further reinforced by the other two advantages of MNEs: the market internalisation specific-advantage and the location-specific advantage (Dunning, 1981). In addition, FDI may disrupt backward linkages through substitution of imports for domestic commodities (Noorzoy, 1979).The present paper contributes to the existing literature by applying a multivariate VAR system with the error correction model (ECM) and time series techniques of co-integration and innovation accounting to explore the possible links between FDI, domestic investment and economic growth in China. Specifically, we use the impulse response function and variance decomposition plus the Granger causality testing procedures to investigate whether: (1) FDI has a complementary/substitution effect on domestic investment in China; (2) there exists any causal relationship between FDI, domestic investment and economic growth; (3) FDI has played an important role in Chinas economic growth; and (4) FDI contributes to growth more than domestic investment.This paper differs from earlier studies in a number of respects. Firstly, it represents the first attempt to directly test the relationship between FDI and domestic investment in China. Second, we use pure time-series data while previous studies use either cross-sectional or panel data, which are likely to suffer from problems of data comparability and heterogeneity. Third, earlier studies do not test for causality between FDI, domestic investment and economic growth. The failure to consider the possible two-way causality between the variables may lead to the simultaneity problem. Finally, our VAR model incorporates long-run dynamics or ECM. Neglecting these dynamics may produce various estimation biases.The organisation of the paper is as follows. Section 2 offers an overview of FDI inflows, domestic investment and economic growth in China. This is followed by econometric analysis in Section 3. The final section of the paper presents the conclusion and some policy implications.2. AN OVERVIEW OF FDI INFLOWS, DOMESTIC INVESTMENT AND ECONOMIC GROWTH IN CHINA: 19782003In the early 1980s, special economic zones were formed with preferential policies including tax concessions and special privileges for foreign investors. During the reform period, the Chinese government introduced various new legislative measures to improve investment conditions and the business environment in order to attract FDI.Table 1 presents the ratios of FDI to GDP, DI to GDP, and FDI to DI from 1978 to 2003. As can be seen, the proportions of FDI to GDP (column 2) were quite low and less than 1 per cent until 1990. It increased to a peak value of 6.2 per cent in 1994 and then steadily decreased to 3.8 per cent in 2003. The proportion of DI to GDP was 18.5 per cent in 1978 and increased steadily to 47.6 per cent in 2003. The proportion of FDI to DI increased dramatically from 0.1 per cent in 1978 to 1.7 per cent in 1984, and by 1994 it had reached an all-time high of 18.1 per cent. Since then, it gradually decreased to 8.0 per cent in 2003. 3. EMPIRICAL ANALYSIS AND FINDINGS a. Data and Unit Root TestQuarterly time series data for FDI, DI and GDP are available and all in current prices of the Chinese currency (yuan). They are compiled from China Monthly Statistics(1987:12004:3),Comprehensive Statistical Data and Materials for 50 Years of New Chinaand various issues of China Statistical Yearbook. GDP quarterly time series is constructed on the basis of the monthly gross industrial output (GIO) and the yearly GDP statistics due to lack of quarterly and monthly GDP statistics. It is found that the annual growth pattern of GDP is similar to that of GIO. q=1,.,4 t=1988,1989,.,2003To minimise the effect of seasonal fluctuations when conducting co-integration analysis and model estimation, a variable of centred (orthogonalised) seasonal dummies is incorporated. The standard 01 seasonal dummy variables will affect both the mean and the trend of the level series in a VAR system but the centred seasonal dummy variable only shifts the mean without contributing to the trend . In this paper, we employ the augmented DickeyFuller (ADF) test to test the stationarity of the three time series FDI, DI and GDP. As can be seen from Figures 4(ac), the three series appear to be non-stationary in level form. Therefore, we investigate the stationarity of the first difference of the three series by testing for unit roots. The ADF tests are performed on both the level and first differenced observations by estimating the following three models: No constant and no trend model: （1） Constant and no trend model: （2） Constant and trend model: （3） The results of the ADF test are shown in Table 2. They show that the null hypothesis of a unit root is: (a) accepted for the level series of FDI in all three models; (b) rejected for the level series of DI in model (3), and (c) rejected for the level series of GDP in model (1). 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 Co-integration of Variables Now, the co-integration test is performed to investigate any long-term 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 co-integration rank test is summarised in Table 3, which indicates the presence of two co-integrating vectors at 1 per cent and 5 per cent levels of significance, respectively (i.e. The null hypotheses of no co-integration is rejected for the rank of zero and less than or equal to 2). This means that there exists a long-term relationship among the three variables. c. The Error Correction ModelTo 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 decomposition and impulse response function) technique can be utilised to examine the relationships among economic variables . Using this technique, Kim and Seo (2003) explored the complementary 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 decomposition allows us to make inferences about the proportion of movements in a time series due to its own shocks 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 Chinas economic growth but its influences are less than that of domestic investment (5.7 per cent versus 17.6 per cent). GDP shows stronger influences on Chinas domestic investment than FDI does (40.8 per cent versus 3.5 per cent). The influences of DI and GDP on FDI are relatively low (2.4 per cent and 1.9 per cent, respectively). But the relationship between GDP and DI is strong, with a 40.8 per cent influence from GDP to DI and 17.6 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; (ii) the effects of FDI and GDP on DI are statistically significant; (iii)the effects of FDI and DI on GDP are statistically significant. Thus, FDI affects DI and GDP but not the reverse, whereas the causal links between GDP and DI are bi-directional. These findings confirm the results of the variance decomposition analysis.We now use the impulse response function to reveal the dynamic causal relationships between FDI, domestic investment and economic growth. e. Empirical Findings Using a VAR system with ECM, we have found the following: 1. FDI plays an important role in complementing domestic investment in China, the larger the FDI the greater the domestic investment. Further, FDI has a significant effect on Chinas economic growth. 2. Chinas domestic investment and economic growth are positively correlated; great economic growth spurs large domestic investment, and vice versa. 3. Chinas domestic investment and GDP do not have much impact on FDI inflows in the long run. The causal link between GDP and DI is bi-directional, but there is only a one-way directional causality from FDI to DI and FDI to GDP. 4. Chinas domestic investment has a greater impact on growth than FDI does. These lend some support to the theoretical view that FDI has complementaryeffects on domestic investment, and that long-term economic growth is positively associated with FDI.一、 CONCLUSIONS AND POLICY IMPLICATIONS Based on the empirical analysis and findings, we conclude that rather than crowding out domestic investment, FDI has a complementary relationship with domestic investment. FDI has not only assisted in overcoming shortages of capital, it has also stimulated economic growth through complementing domestic investment in China. The findings of this study do have some important implications for policy makers in China and elsewhere. Since FDI complements domestic investment, less developed countries ought to encourage and promote FDI inflows, for which appropriate FDI policies and regulations are required. 譯 文：中國的FDI,國內(nèi)投資與經(jīng)濟(jì)增長：一個(gè)時(shí)間序列分析二、 引言盡管FDI對投資影響的大量研究，F(xiàn)DI在經(jīng)濟(jì)增長中扮演的角色也受到廣泛的爭議。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(dòng)經(jīng)濟(jì)增長。尤其是跨國公司在東道國與國內(nèi)企業(yè)間有垂直關(guān)系或與其他國家的子公司或區(qū)域部門內(nèi)部有垂直聯(lián)系。FDI流入高危領(lǐng)域或新興產(chǎn)業(yè)還克服了東道國資金短缺問題。當(dāng)FDI進(jìn)入資源密集型產(chǎn)業(yè)時(shí)，相關(guān)產(chǎn)業(yè)的國內(nèi)投資也會(huì)受到刺激。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。支持這一說法的實(shí)證要求包括Sun（1998）和Shan（2002）運(yùn)用傳統(tǒng)的回歸模型和面板數(shù)據(jù)，Sun發(fā)現(xiàn)中國的FDI與國內(nèi)投資對中國的經(jīng)濟(jì)增長存在高度積極關(guān)系。Shan運(yùn)用一個(gè)VAR模型去檢驗(yàn)中國的FDI，產(chǎn)業(yè)產(chǎn)出增長和其他變量間的內(nèi)部聯(lián)系。他得出當(dāng)FDI在產(chǎn)業(yè)產(chǎn)出的比率上升時(shí)，F(xiàn)DI對中國經(jīng)濟(jì)有極大的收益性影響。相反，反對FDI促進(jìn)增長論者認(rèn)為FDI擠出國內(nèi)投資，并對經(jīng)濟(jì)增長有負(fù)面影響。特別是，工業(yè)組織理論認(rèn)為FDI是跨國公司為了在東道國超過本土企業(yè)，提升其壟斷力量的極具侵略性的全球戰(zhàn)略?？鐕镜乃袡?quán)優(yōu)勢（例如先進(jìn)的技術(shù)，管理經(jīng)驗(yàn)技巧，最小交易成本及其他無形優(yōu)勢）會(huì)轉(zhuǎn)為壟斷力。這種壟斷力量會(huì)進(jìn)一步地提升跨國公司其他兩方面的優(yōu)勢：市場內(nèi)部一體優(yōu)勢和市場定位優(yōu)勢（鄧寧）。此外，F(xiàn)DI也可能通過國內(nèi)商品的替代進(jìn)口破壞經(jīng)濟(jì)的后部聯(lián)系。本文對現(xiàn)有文獻(xiàn)的貢獻(xiàn)主要是通過建立多變量的誤差修正模型和時(shí)間序列協(xié)整檢驗(yàn)和創(chuàng)新技術(shù)會(huì)計(jì)去研究中國的FDI，國內(nèi)投資和經(jīng)濟(jì)增長間可能的因果聯(lián)系。具體地說,我們使用了脈沖響應(yīng)函數(shù)和方差分解等方法,再加上格蘭杰因果關(guān)系測試過程,去分析下面的關(guān)系：1.FDI對中國國內(nèi)投資有互補(bǔ)或替代效應(yīng)；(2)FDI，國內(nèi)投資和經(jīng)濟(jì)增長三者間存在相互因果關(guān)系；(3)FDI對中國的經(jīng)濟(jì)增長起到了重要的作用；(4)FDI對經(jīng)濟(jì)增長的貢獻(xiàn)超過國內(nèi)投資。本文在許多方面和前期的一些研究存在不同。第一，這是現(xiàn)有的研究中第一次直接去檢驗(yàn)中國的FDI和國內(nèi)投資間的聯(lián)系。第二，本文采用的是純時(shí)間序列數(shù)據(jù)，與先前研究中使用可能引起數(shù)據(jù)可比性及不均勻性問題的橫向或面板數(shù)據(jù)不同。第三，早期的研究沒有檢驗(yàn)FDI,跟國內(nèi)投資和經(jīng)濟(jì)增長間的因果關(guān)系。沒有考慮到變量間可能的雙向因果關(guān)系會(huì)引發(fā)并發(fā)性問題。最后，我們的變量模型包括長期動(dòng)態(tài)因素、企業(yè)內(nèi)容管理。忽略這些動(dòng)態(tài)因素可能導(dǎo)致各種估計(jì)偏差。 本文的框架如下：第二部分講述中國的FDI流入，國內(nèi)投資和經(jīng)濟(jì)增長的概述；接下來的第三部分對此進(jìn)行分析；最后一部分得出結(jié)論并提出相關(guān)政策。二、1978-2003中國的FDI流入，國內(nèi)投資和經(jīng)濟(jì)增長概述在20世紀(jì)80年代初期，向外國投資者提供稅收減免和經(jīng)濟(jì)特權(quán)的優(yōu)惠政策經(jīng)濟(jì)特區(qū)成立。在改革開放期間, 為了吸引外商直接投資中國政府出臺(tái)了許多新的改善投資和經(jīng)營環(huán)境立法措施。表1表示1978年-2003年的FDI/GDP,DI/GDP和FDI/DI的比率變化。從表中可以看出，F(xiàn)DI/GDP的比率到1992年為止都低于1%，在1994年達(dá)到高峰6.2%，然后又逐漸下降至2003年的3.8%。DI/GDP的比率從1978年的18.5%已快速增長到2003年的47.6%。FDI/DI的比率從1978年0.1%急劇增加到1984年的1.7%，到1994年已達(dá)到了18.1%的空前的高峰。然后,它逐漸下降到2003年的8%。三、實(shí)證研究及結(jié)論（一）數(shù)據(jù)和單位根檢驗(yàn)本文采用的數(shù)據(jù)是用當(dāng)年人民幣價(jià)格計(jì)算的FDI, DI 和 GDP季度時(shí)間序列數(shù)據(jù)。數(shù)據(jù)來源于由中國國家統(tǒng)計(jì)局出版的中國統(tǒng)計(jì)月報(bào)（1987:1-2004:3）及新中國50年的綜合和統(tǒng)計(jì)數(shù)據(jù)材料和中國各種統(tǒng)計(jì)年鑒。由于缺乏季度和月度本地GDP統(tǒng)計(jì)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(jì)數(shù)據(jù)的基礎(chǔ)上得到的。 q=1,.,4 t=1988,1989,.,2003為了在進(jìn)行協(xié)整分析和模型估計(jì)時(shí)減少季節(jié)性波動(dòng)，在模型中引入了周期性虛擬假設(shè)變量。標(biāo)準(zhǔn)的0-1周期虛擬變量將影響變量模型的均值和趨勢，但主要的周期虛擬變量只影響平均值不影響趨勢。在本文中運(yùn)用擴(kuò)展的ADF檢驗(yàn)來檢驗(yàn)FDI, DI 和 GDP這三個(gè)時(shí)間序列的平穩(wěn)性。從圖4（a-c）可以看出,三個(gè)序列水平是不平穩(wěn)的。因此,我們通過單位根檢驗(yàn)研究三個(gè)序列在一階差分下的平穩(wěn)性。ADF檢驗(yàn)是在同一水平和一階差分下對以下三個(gè)模型的估計(jì)觀察進(jìn)行。1. （1）2. （2）3. （3）ADF檢驗(yàn)結(jié)果見表2。它們表明單位根的0假設(shè)是：（a）接受FDI在三個(gè)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。結(jié)果表明，根據(jù)一階差分?jǐn)?shù)據(jù)，三個(gè)時(shí)間系列都是平穩(wěn)的。因此，我們得出結(jié)論這三個(gè)時(shí)間序列都成一階矩陣即I（1）。（二）變量的協(xié)整檢驗(yàn)現(xiàn)在進(jìn)行的協(xié)整檢驗(yàn)時(shí)檢驗(yàn)FDI, DI 和 GDP這三個(gè)變量在任何長期均衡關(guān)系的協(xié)整。在仔細(xì)的選擇和檢驗(yàn)后，選折一個(gè)由滯后長度為6、穩(wěn)定的、周期性虛擬變量組成的模型。Johansen的協(xié)整等級(jí)檢驗(yàn)結(jié)果如下表3。其表明存在兩個(gè)分別在1%和5%水平意義的協(xié)整向量（矩陣為零或其秩小于等于2而拒絕零假設(shè)：無協(xié)整）。這意味著三個(gè)變量FDI, DI 和 GDP之間存在長期的均衡關(guān)系。（三）誤差修正模型為了分析FDI, DI 和 GDP這三個(gè)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(gè)變量系統(tǒng)中運(yùn)用得非常好。由結(jié)果可知，沒有一個(gè)檢驗(yàn)統(tǒng)計(jì)量在95%的臨界水平下是有意義的。因此，沒有任何跡象證明該系統(tǒng)模型是不正確的。根據(jù)Schwarzz（1978）和Akaike（1974）的信息準(zhǔn)則，滯后的長度被選為6。（四）會(huì)計(jì)創(chuàng)新和格蘭杰因果檢驗(yàn)創(chuàng)新會(huì)計(jì)（方差分解和脈沖響應(yīng)功能）技術(shù)可以用來研究經(jīng)濟(jì)變量之間的關(guān)系。運(yùn)用這個(gè)檢驗(yàn)方法，Kim and Seo (2003)使用這種技術(shù)研究了韓國外商直接投資與國內(nèi)投資的互補(bǔ)或替代關(guān)系，并分析了外國直接投資對韓國經(jīng)濟(jì)增長的影響。另一方面，預(yù)測誤差方差分解使得我們作出有關(guān)時(shí)間序列的比例變動(dòng)，這個(gè)比例變動(dòng)是由于系統(tǒng)中變量的自身沖擊受到其他變量的沖擊(Enders, 1995, p. 311)。這結(jié)果表明，F(xiàn)DI，國內(nèi)投資和經(jīng)濟(jì)增長之間的關(guān)系強(qiáng)度是不同的。FDI 在中國的作用經(jīng)濟(jì)增長中起著重要，但國內(nèi)投資的作用較?。ǚ謩e為5.7%和17.6%）。GDP的增長對FDI的影響比對中國的國內(nèi)投資的影響要較強(qiáng)（分別為40.8%和3.5%）。國內(nèi)投資和GDP對FDI的影響較低（分別為2.4%和1.9%）。但DI與GDP之間的聯(lián)系是比較強(qiáng)勁的，DI/GDP為40.8%，GDP/DI 為17.6%。這表明，這三個(gè)變量解釋了各自過去的優(yōu)勢值（預(yù)測誤差方差）。這意味著，目前/過去的FDI, DI 和 GDP對其以后/當(dāng)前的趨勢有重要影響。Granger因果檢驗(yàn)的結(jié)果表明：（1）DI和GDP對FDI沒有顯著的統(tǒng)計(jì)性影響；（2）FDI和GDP對DI的影響是顯著的；（3） FDI和DI對GDP的影響是顯著的。因此，F(xiàn)DI影響DI和GDP，反向作用不明顯，GDP和DI間因果聯(lián)系是雙向的。這些研究結(jié)果證實(shí)了方差分解的結(jié)果分析。接著進(jìn)行脈沖響應(yīng)函數(shù)的動(dòng)態(tài)因果關(guān)系分析，揭示FDI, DI 和 GDP關(guān)系。（五）實(shí)證結(jié)果本文選用誤差修正模型，得出了以下結(jié)論：1外國直接投資在對國內(nèi)投資的補(bǔ)充作用明顯，外國直接投資越多，國內(nèi)投資越大。另外，F(xiàn)DI對中國的經(jīng)濟(jì)增長有重大影響。 2中國的國內(nèi)投資和經(jīng)濟(jì)增長呈積極正相關(guān)關(guān)系。巨大的經(jīng)濟(jì)增長刺激國內(nèi)投資的增長，反之亦然。3在長期，中國的國內(nèi)投資和國內(nèi)生產(chǎn)總值對外國直接投資的流入沒有太大影響。國內(nèi)生產(chǎn)總值和國內(nèi)投資之間存在雙向因果關(guān)系，同時(shí)外國直接投資對國內(nèi)投資和外國直接投資對國內(nèi)生產(chǎn)總值都只是單向因果關(guān)系。 4中國的國內(nèi)投資對經(jīng)濟(jì)增長的影響比對外國直接投資產(chǎn)生的影響更大。 這些結(jié)論這在某種程度上支持了外國直接投資對國內(nèi)投資有補(bǔ)充效用而長期的經(jīng)濟(jì)增長與外國直接投資呈積極正相關(guān)的理論。四、結(jié)論及相關(guān)政策在實(shí)證分析和調(diào)查結(jié)果的基礎(chǔ)上，我們得出這樣的結(jié)論，外國直接投資對國內(nèi)投資不具有排擠作用，反而補(bǔ)充帶動(dòng)國內(nèi)投資。外國直接投資不僅幫助克服資金短缺， 它還通過補(bǔ)充國內(nèi)投資刺激中國經(jīng)濟(jì)增長。這項(xiàng)研究的結(jié)果對中國和其他地方的政策制定者也有一些重要的政策含義。由于外國直接投資對國內(nèi)投資具有補(bǔ)充作用，那些欠發(fā)達(dá)的國家應(yīng)該通過適當(dāng)?shù)耐鈬苯油顿Y政策和法規(guī)鼓勵(lì)和促進(jìn)外國直接投資流入。13