For the past three decades after 1978, China's rapid economic growth has been incredible. Along with many contributing factors to the growth of China is Foreign Direct Investment (FDI), which plays an increasingly significant but rather positive effect on its economic growth. China has become one of the world's most attractive FDI destinations due to its enormous labour supply and low labour cost, stable political and economic environment, and pro-FDI policies It is said to be the largest FDI recipient among the developing countries. The aim of this research is to examine and assess China's economic growth with respect to FDI during the period 1980-2008, while considering the spillover effect of FDI. Although, previous research on this study shows positive relationship between the two, still I find it necessary to modify the model so as to achieve even more persuasive results.
The world would agree that China has made such a tremendous progress during the past three decades after the reforms of the late 1970s in being one of the fastest growing economies today. The promotion of Foreign Direct Investment (FDI) inflow is an important part of the economic reform process. After more than 30 years of economic reform, China has become one of the most important destinations for FDI. China's increasing openness to foreign direct investment has contributed importantly to its exceptional growth performance. Despite the fact that it is still a developing country, China's external trade and Gross Domestic Product (GDP) grew on average about 15% and 9% per annum respectively from 1979 to 1997 8.7% in 2009 and most recently the real GDP according to the World Bank grew at an annual average rate of 10% over a twenty five year period. Research also show that the stock of FDI in China as at 1990 was less than $19 billion and it rose to over $300 billion in 1999.
Though, not all countries have been able to achieve high levels of economic growth, China has become the second largest FDI recipient in the world after the United States as its economic growth pays tributes to many factors of which include agriculture, investment in human capital particularly education, but most importantly its openness to foreign trade and investment. China's ability to attract foreign investors is far more competitive than other developing countries and most probably the rest of the world. FDI flows into China increased from $3.5 billion in 1990 to $69 billion in 2006, which in turn made a significant contribution to the rapid economic development of China.
It is also the largest producer of coal, roughly one third of the world's total production. As with coal, China has enough electric power supply. Other major natural resources such as land, iron and other minerals are economically available (Arindam Banerjee 2006).
The purpose of this research is two-fold: first to asses FDI and its impact on economic growth, secondly to analyse its effect on technology spillover.
Various studies and research have proved that the effect of FDI on economic growth in mostly positive and if left at this stage would produce results that are generic and have been previously studied. Therefore further discussion considering the spillover effect on FDI gives a clearer picture on how it affects economic growth in total.
The rest of the paper is organised hereafter as follows; in section 3, which is the literature review, theoretical evidence regarding the relationship between FDI and economic growth will be examined in addition to the spillover effect caused by FDI. This chapter also aims to review existing literature.
Section 4 focuses on a macro-economic model which will be used to explain the impact of FDI on economic growth. In this research, the augmented Solow-Swan model by Mankiw et al (1980) would be used.
Additionally, empirical analysis with data to back up literary content is carried out at a later part of the research (Section 5). The data used are collected from World Development Indicators, Global Market Information Database and International Historical Statistics. A certain level of econometrics is vital and running regressions using Ordinary Least Square methods will be carried out.
Graphs will be used to view the trends of each variable but focused particularly on the Foreign Direct Investment variable, which is dependent on GDP. To round up, limitations and conclusions will be drawn on observation from data.
This part of the research will focus on the theoretical evidence as well as the empirical evidence (studies) regarding the postulated relationship between FDI and economic growth of which evidence maybe general or specific.
The relationship between FDI and economic growth has been widely studied. Robert Solow and Trevor Swan in 1950 came about the augmented Solow growth model which started with the traditional neoclassical growth theory. In this model, he explains how output of an economy grows with respect to physical capital which includes labour and capital inputs. Economies under this model obey the laws of diminishing return to scale.
Athukorala and Chand (2000) and Balasubramanyam et al (1996) confirm that countries that have open trade policies and good trade regimes, tend to have a growth enhancing effect of export which makes FDI significant and strong.
Zhang (2001) explains that economies undergoing rapid growth not only create more room for FDI, but also make available better opportunities (income wise) for foreign investors and by so doing draw a greater dimension of FDI.
Alternatively, Zhang further explains how FDI inflows on host country can promote economic growth through direct effects and spillover effects. He concludes that both FDI and economic growth are positively mutually supporting and could lead to a two-way causality.
Yao and Wei (2007) argue that FDI affects economic growth positively in two ways; as a mover of production efficiency and a shifter of production frontier. Nevertheless, they regarded FDI as an important tool for economic growth especially in China. They also predicted that the less-developed regions of China, like the inland provinces might be able to catch up with the rich coastal regions as more FDI is expected.
The FDI patterns in China show a great disparity among regions. In the early years of reform, foreign investments were mostly concentrated in the southeast provinces of Guangdong and Fujian. Between 1983 and 2000, nearly 88 % of all FDI were received by coastal regions. On the other hand, 20 inland provinces, whose population makes up almost two third of national total, accounts only for about 12%. Among all regions, Guangdong province has received the most. The main reason is for its close proximity for Hong Kong. One more thing is that Guangdong was among the first province open to foreign investment. Three of the four SEZs were in Guangdong (Song, Shunfeng and Kevin Honglin Zhang 2002).
After the government opened 14 coastal cities in 1984, foreign investments began to move towards north, and to other parts of the east coastal region. The establishment of Pudong district of Shanghai as a new development zone also contributed to the shift. Shanghai as well as its two neighbour provinces, Jiangsu and Zhejiang gains importance. In recent years, government is working to attract more FDI to the inland provinces, especially the western provinces, by offering preferential treatment.
FDI inflow benefits China's economical growth by inducing higher GDP growth. Nation has achieved economic growth at an impressive speed. External trade is now becoming very important element of nation's economy which is the direct impact of economic reform. Expansion of its trade with the rest of the world is the direct outcome of reform. Gradual reforms of over three decades have transformed China's economy from a centrally planned economy dominated by the state sector to a market-oriented economy consisted of firms with various ownership form. Government has encouraged technology transfer through various forms of foreign investment in the economy.
Li, Liu and Parker (2001) confirm that there is a technology spillover effect although differences in regional development policies exist
FDI reached a record US$ 92.4 billion in 2008, excluding financial investment. FDI flows fell steadily in the first half of 2009 due to global slowdown. But have now started to recover. From 1979 to 1999, for 20 years nearly US$ 306 billion had been invested in China from foreign companies, which was equivalent to 10 % of direct investment worldwide and about 30 % of the investment amount for all the developing countries put together. In December 2001, China became a member of the World Trade Organization (WTO), and the accession provides incentives for more export-oriented FDI (Chinability 2010).
The question addressed here is whether FDI fuels technological progress and how. Almost all countries are seeking to attract FDI, because of the various amounts of benefits that it brings; which include income generation from capital inflows, advanced technology, management skills and market know-how. FDI encourages local firms to improve their technological competence by generating knowledge or technological spillovers that increase factor productivity.
In recent years, foreign-invested firms have become a very important part of the Chinese economy. According to experts (Fung, Lau and Lee 2002), foreign capital has played a largely positive role in China's economic development during the reform. It can generate more benefits than just helps solve the capital shortage problem. FDI may provide better access to technologies for the local economy
It can also lead to indirect productivity gains through spillovers. For instance, with the entry of multinational companies (MNCs), competition increases in the local market which will force existing inefficient firms to invest more in physical or human capital. Usually MNCs provide training for labour and management which makes them become available to the economy in general.
In China, previous studies on FDI and spillovers have confirmed existence of a positive relationship. However, the empirical findings on spillover are mixed.
While some have proven a positive existence (Hejazi and Safarian, 1999; Javorcik, 2004; Keller, 2002; Liu, Siler, Wang, and Wei, 2000), others have confirmed quite the opposite (Aitken and Harrison, 1999; Konings, 2001) or found spillover effects to be confined to other multinationals (Feinberg and Majumdar, 2001)
The studies of Hermes and Lensink (2003), Lensink and Morrissey (2001), Gorg and Strobl, (2001) respectively show that knowledge spillovers take place through four likely channels which include: imitation, competition, linkages and/or training. Gorg and Hijzen (2004) also explains the positive effects that foreign firms have over local firms in export markets.
Foreign firms are mostly always technologically advanced and well organised compared to domestic firms. Domestic firms may find it cheaper to copy foreign firms by upgrading their technology for example, rather than generating new ideas or ways of doing things, therefore this process leads to domestic firms becoming more productive.
Since the effect on domestic firms is positive, it is imperative to understand that FDI brings about a positive technological spillover through the channel of imitation.
It is important to stress however that spillovers, whether technology or knowledge based occur through the channel of linkages whereby domestic firms deliver raw materials and/or intermediate goods to foreign firms. Accolley Delali (2003) confirms the existence of this linkage may force foreign firms to provide technical aid to domestic firms. Domestic firms become efficient because they driven by foreign firms to advance their technology and also train their staff, which increases productivity.<
Another question arises, of how spillover is measured. Technology spillover for this research will be measured using Research & Development (R&D). The reason for this is that technological process is an important factor of economic growth and R&D influences economic growth.
Evidence from Branstetter (2001) and Todo (2006) who examine technology spillover effects by using R&D data show that the industry R&D of foreign firms has a positive impact on the productivity level of local firms.
Hermes and Lensink (2003) confirmed the findings of Borensztein et al (1998) using 67 Least Developed Countries (LDCs). Borensztein et al (1998) tested the impact of FDI on growth with respect to technology spillover which was labour augmented and found a positive impact between the two and concluded that the spillover effect centres on the presence of a threshold level of educated labour force.
Further theoretical and qualitative insights can be drawn for this research but it is important to stress however that empirical analysis are also crucial in understanding the relationship between FDI and economic growth and also the spillover effect caused by FDI. For this research, the model used focuses on the augmented Solow growth model of the 1980s.
Assuming a Cobb-Douglas technology, output (Y) is essentially determined by two physical inputs, labour (L) and capital (K) as shown in Equation
Yt=ALtαKβee ……………………. (1)
where A is constant and e is a disturbance term normally distributed with mean zero and a constant standard error σ. Equation 1 implies that the growth of Y will depend on the growth of L and K given the sizes of the input elasticises α and β respectively
A is technology which is the total factor productivity level. Previous literature on economic growth has viewed technological progress in many ways, as a by-product of other economic activities, as a free good and because of research and development (R&D). So it is only fair that spillover effect of FDI in China is measured in terms of R&D.
L is total labour force in other words the economically active population.
K is stock of physical capital (fixed capital formation)
Y=A LtαKβeeZt ………..………….. (2)
Z represents other factors that can influence Y and for this research, they include;
FDI is Foreign Direct Investment which is measured in inflows
H is Human capital in terms of education (secondary school to be precise). The reason for using human capital as a variable is that, economic growth in a country will be influenced by a lot of factors and human capital especially education is one of them, so we use secondary school because education is optional after this period.
Taking logs of equation (2), the relation for growth can be expressed as:
lnYt= α0 + θFDIt + εt ………………………(3.1)
lnYt= α0 + α1 + lnA + αln Lt + βln Kt + θFDIt + ψln Ht + εt …….……..…… (3.2)
Dueto data constraints, we substitute variables with ones that closely define them. In the equation (2) for example, physical capital is required to estimate the growth model, but previous literature have used gross fixed capital as a substitute for this variable. Human capital has also been proxied by school enrolment and for this study, secondary school enrolment is used.
For this research, data used are collected from a wide variety, they include; the World Bank World Development Indicator, Global Market Information Database, International Historical Statistics (Africa, Asia & Oceania) 1750-2005. These sources are well known sources of statistics for China and the results are more or less accurate. Real Gross Domestic Product (GDP) is valued at constant price of local currency code: (NY. GDP. MKTP. KN) and the data are collected from the World Bank World Development Indicator. Foreign Direct Investment is also valued at constant 2009 prices, code: RMB mn, it is collected from the Global Market Information Database. Finally, human capital proxied by secondary school enrolment is measured by number of secondary school pupils. Labour force is measured by the number of economically active population and physical capital proxied by gross fixed capital formation valued at constant 2009 prices code: RMB nm. These data are also collected from the Global Market Information Database. The reason for choosing the data at constant prices is due to inflation rates, as constant prices reflect that the data will be adjusted taking inflation into account.
The impact of R&D expenditures on China's economic growth has not been systematically investigated. The data available went only as far back as 1996-2006 from the World Bank Development Indicator and other sources. It is inadequate to use as 10years is insufficient and can affect other variables therefore the R&D variable would not be accounted for in the empirical analysis.
Ordinary Least square (OLS) method for regression is used for the statistical analysis. The reason for regression analysis is to analyze relationships among variables and the software used to run these regressions is Eviews.
Previous study and research on FDI and growth have used data from a wide range of sources. In this section, the significance of FDI on economic growth is examined based on a general framework of time series regression. GDP is regressed on the level of FDI and other variable such as labour force, physical capital, and human capital. This section uses the annual data for China collected from the year 1980 to 2008 and the Ordinary Least Square (OLS) regression is performed.
An important step in the analysis of this study is the graphs. Each variable is accounted for by plotting graphs to show the trend within the years 1980-2008 as seen in Figure 1 of the appendix. The correlation matrix shows the existence of a positive linear association/relationship between the explanatory variables.
From Figure 1, there is a notable increase in FDI from 1980 to1986. This is due to the fact that China made a new foreign investment law in 1984 which was implemented to facilitate the growth of FDI in the economy.
In 1985, annual FDI inflow was less than $2 billion. We can also notice a sharp increase from about 1992/1993. This also happened because China re-affirmed its openness policies and market-oriented reforms which were introduced earlier in 1984. This re-affirmation provided evidence of success, hence the increase in FDI. After China joined the WTO in 2001, its annual growth rate of FDI inflows increased by more than 10% and in 2005 its FDI inflows rose to $63 billion. According to Wally and Xin (2006) China's economic growth during 2003 and 2004 pays tribute to the FDI enterprises which may have contributed more than 40% to its growth. Figure 2 shows a positive relationship between FDI and GDP.
Additionally, between these periods 1980-1988, output of the economy grew however, it is evident that the trend for China has been growing at a continuous rate and is currently counted as one of the fastest developing nations. Figure 2, 3, 4 & 5 also show a positive relationship with GDP.
The next step is the regression analysis; it explains the movements of the dependent variable in this case real GDP in terms of a set of other variables (independent or explanatory variables) through the quantification of a single equation.
The correlation matrix (as seen in the appendix) shows a strong linear positive statistical association or relationship between the real GDP explanatory variables. The L in front the variables signifies that they are logged, as in LGDP, LFDI, LLF, LH, and LGCF. The reason variables are logged is simply because log variables are invariant to scale of the variables (see equation 3.1 and 3.2) and they give a direct estimate of elasticity.
The main focus of this study is to find the relationship between FDI and economic growth (GDP) hence, it is essential to focus on FDI and GDP first before considering others.
Initial estimation of the relationship between FDI and GDP reported in Table 1 revealed evidence of serial correlation (as shown in Table 2) given by the Breusch-Godfrey Serial Correlation LM Test. Similarly there was evidence of heteroskedasticity given by the White test (as shown in Table 3) however, Figure 6 shows that the errors are normally distributed.
Heteroskedasticity is the violation of the classical assumption model which has severe consequences for the OLS. It occurs when random variable have different variances therefore causing OLS to underestimate the variances and standard errors of the coefficients. The t-Statistic and F-statistic scores become higher than they should be. The white test is the most used test for heteroskedasticity. It is tested using the "F-statistic" to test the overall significance of the equation, if any of the coefficients is significantly different from zero. There is evidence of heteroskedastic patterns in the residuals. Accepting the null hypothesis (H0) implies that there is no evidence of heteroskedasticity.
To correct the heteroskedasticity and serial correlation we carry out a White Heteroskedasticity-Consistent standard Errors & Covariance white test as shown in Tables 4 & 5. (A.H. Studenmund, Using Econometrics, A Practical Guide, 5th Edition, Pearson International Edition)
The results in Tables 4 and 5 show that is the regression estimate of the relationship between FDI and GDP. The coefficient on FDI is significant at a 1% level and it shows that a 1% increase in FDI leads to a 0.35% increase in real GDP. The adjusted R2 is 0.848 which means that 84% of variation in real GDP around its mean is explained by FDI.
Finally, other variables i.e. human capital, labour force and gross fixed capital are included in the regression model and the results are reported in Table 6. Analysis of the residuals show that there is evidence of serial correlation (see Table 7) but no heteroskedasticity (see Table 8) also the residuals are normally distributed (see Figure 8).
To correct for serial correlation, we use Newey-West HAC Standard Errors & Covariance (lag truncation=3) again and the new results are reported in Table 9
and from it, we can deduce that the size of FDI is diminished from 0.35% to 0.01% meaning that when we account for other influences/variables, FDI does not have a statistical significance at 1%, 5% and 10% conventional levels and its impact on GDP is overstated.
Adjusted R2 is 0.99 goodness of fit. It takes account of loss of degrees of freedom. This means that about 99% of the variation in GDP around its mean is explained by the explanatory variable.
For many years, studies on the relationship between FDI and economic growth have been debated. Various economists and researchers have investigated this relationship using different data estimation like cross section data and time series data. This study uses time series data for the estimation of the role of FDI on economic growth in China.
One of the limitations of this research was the fact of not being able to access data on R&D which would have been used to evaluate the effect of spillover on FDI. Nevertheless The World Bank also explains that statistical systems in developing countries are quite weak and China being a developing country, suffers from this problem. Although none of the results counteracts the proposed literature, the effect of FDI on economic growth is less significant than expected.
China's policy aimed at promoting export-oriented FDI has met with remarkable success. It has led to the building of an internationalised manufacturing sector, highly competitive in world markets. FDI firms can be expected to continue to strengthen China's comparative advantages by increasing its specialisation in the exports of labour intensive products and technology intensive products.
China's entry into the WTO will have far-reaching consequences. It will put an end to the fragmentation of China's trade regime and allow a more equal access to foreign resources. FDI has allowed new entrants into China's industry and hence accelerated the diversification of ownership pattern, which has been part of the emergence of competitive structures.
Finally, this paper supports the empirical literature in general, such as Zhang (2001) and Yao and Wei (2007), but the empirical findings of Jai S. Mah (2010) show that FDI inflows have not caused real economic growth in China. The results above account for a positive relationship between FDI and economic growth in the analysis. However, when other variables are taken into account, the effect of FDI on economic growth in China is diminished meaning that other factors influence economic growth more than FDI.
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