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In pace with the incressing trend of globalization, foreign direct investment (FDI) as an important element attracts more and more attention. A lot of experts states that foreign direct investment plays an impressively role in rapid economic growth. Owing to the fact that FDI as a colligation investment is considered as a combination of capital, technology, know-how, raw materials, intermediate components, labour, marketing,and mamagement (Ta-Shun and Hsin-Yu, 2010). Various countries regard foreign capital introduction as an important element in their strategy department, naturally including China.
Foreign direct investment (FDI) has played a major role in China’s rapid development over the past 3 decades. Mainland China since its economic reform has become the one of biggest recipients of world’s foreign direct investment¼ˆFDI¼‰in the world, which brought significant influence on China¡’s economic development. However, the foreign investment has a highly unbalanced distribution in China, with the eastern area absorbing more than eighty per cent of the total amount of FDI. The uneven distribution exacerbated the development disparity among different regions. In an effort to address the regional development gap and ameliorate inland economic development, central government in China put forward the Western Development Program in 2000, but it seems that the imbalance still exists.
It is widely acknowledge that the uneven distribution of inward FDI in China is an important reason for the country’s unblananced regional economic development. There are also a number of studies have confirmed the linkage between FDI regional disparity in China and the country’s growing provincial economic inequality (Wen 2003, Wanetal, 2006) 1.What is more, the rising disparity of regional economic development and growth can cause a range of problems including social and political instability. Eventually, it will hinder high-level and sustainable development of China. Therefore, it is essential to understand distribution condition of FDI among different regions as well as the determinants which may affect the location choices of FDI.
The main purpose of this paper is to analyze the key determinants that influence the location choice of foreign direct investment at regional level in current China. The examination makes it possible to give some explaination on the FDI regional disparity in China. To identify those key determinants, this paper will give a general picture of the evolution process of FDI in China which can be seperated into four stages in the first place. In the following part, this paper will mainly focus on the gigantic gap of foreign direct investment inflows between easten China, central and westen China including recent status and some determinants of the foreign direct investment at the regional level in China. Then a regression model will be applied to test whether those determinants are significant to FDI distribution.
During the Mao period (1949 to 1976), China implemented relatively closed economic policy, all the foreign investment was rejected outside the gate and all foreign loans (mostly to the Soviet Union) was paid back by 1965. China’s GDP per capita was only 381 yuan in 1978, closed economic environment tremendously restrained social progress and economic development of China. Then in 1978, China has started to carry out the reform and opening-up policy of liberalization, pragmatization, marketization and corporatization (Perkins 1988, 1994). As a result, FDI began to enter into Chinese capital market gradually from the late 1970s and has got a great development over last 3 decades. In fact, FDI in China has gone through four phases, preliminary and exploratory stage (1979 – 1991), unprecedented development stage(1992 – 1997), metamorphosis stage (1998 -2001) and the Stage of Stable Growth (2002 – )..
The first stage is from 1979 to 1991. As a result of lacking experience, Shengzhng, Zhuhai, Shantou and Xiamen as four Special Economic Zones (SEZs) were set up to absorb direct investment at first. In 1984, another 14 coastal cities were opened up. at that time the amount of foreign direct investment flowed into China slightly increased per annum. Particularly, the cumulative foreign direct investment and foreign borrowing by 1984 only amounted to US$ 4.4 and US$ 13.041 billion respectively. This two numbers increased to US$ 20.954 and US$ 39.52 billion at the end of 1991. It is obvious from the above data that China attracted foreign capital mainly through borrowing from abroad, FDI taked up a very small proportion in actually utilized value in that period. However, by the end of 1991, the 8 Eastern and Coastal provinces of Guangdong, Beijing, Fujian, Shanghai, Liaoning, Jiangsu, Shandong, and Hainan accounted for about 87% of the cumulative inward FDI. (Whalley and Xin, 2007).
The following unprecedented development stage went through 1992 to 1997. Since 1992, the policy began favorig Western and central provinces. To attract more FDI fund and promote FDI flow to inland area, Chinese government set up new open economic zones among inland provinces since 1992. Therefore, more local governmnts began to jion in the competition of attracting FDI fund by provided preferential FDI policies and opening up various development zones (Kang Yu, Xiangyong Tan, and Xian Xin, 2007). 1 Consequently, the foreign capitals actually utilized increased from $4.4 billion in 1991 to $45.3 billion in 1997 and became the dominant form of utilizing of foreign capitals. In 1993, this increasing tendency reached its peak at approximately US$111.4 billion; China has received 1/4 to 1/3 of total FDI inflow to developing countries and became the biggest recipient among developing countries (Harry G. Broadman, Xiaolun Sun, 1997).
In the year 1998 China’s inbound FDI began launching into the metamorphosis stage which lasted for 3 years. In 1997, inward FDI of China faced an unexpected downturn and hesitation due to the sudden eruption of Asian financial crisis. Specifically, in 1999 and 2000, annual FDI inflow decreased from its peak which accounted for more than US$ 45 billion in 1997 and 1998. However, the amount of inward FDI in China did not experience a sharp decreasee, it still maintained at more than US$ 40 bollion per year( K.C. Fung, Hitomi Iizaka, Sarah Tong,2002). In addition, the central government decisided to implement the great western development strategy which contained various measures related to inward FDI commencing in the year 1999 (Kang Yu, Xiangyong Tan, and Xian Xin, 2007).
Since 2002, the progress of China’s inward FDI has stepped into the stable growth phase. China is always devoting to create a stable, transparent and reputable environment for being more attractive. China’s accession to World Trade Organization (WTO) in 2001 has promoted the continuing improvement of investment environment for FDI in various respects, for instance, the expanding investment fields; the increasing liberalization for choosing investment targets; the development of the construction of infrastructure; and the improvement governmental administrative system. (Chen-Min Hsu, Wei-Guo Zhang, Leslie Lok, 2007). As a consequence, China has became the second largest clustering area of FDI in the world after the US in 2004 (UNCTAD,2006)
China has got great achievements in attracting and using FDI to benefic the economic development, but there still exist some challenges. Among those problems, the unbalanced geographical distribition is one of the most serious issue. In the present paper, several determinants are thought to be correlated with disparity regional distribution of FDI in China and these determinants will be tested through a regression model to see whether it is statistically significant. The following literature reviews aim to demonstrate and support the whole article including the examination.
Accroding to Alan M. Rugman and Simin Collinson (2008), there are several reasons for investors to carry out FDI: increase sales and profits; enter rapidly growing market; reduce costs; gain a foothold in economic unions; protect domestic markets; protect foreign markets; acquire technological and managerial know-how.
It is obvious that FDI inflows promote the development of Chinese economy and many studies identified this relationship. Xiaowen Tian, Shuang Lin (2004) conducted panel data analysis to measure data from China’s 30 provinces during 1985 to 2000. He found that inward FDI is an important element of China’s flourishing economy, provinces with higher amount of inward FDI achieve relatively faster technology upgrading and economic growth.Shaxiong Cheng (2006) analyzed the data from 1983 to 2002 to certificate that the amount of FDI has an obvious impact on GDP, quantity of employment. Consequently, foreign direct investment is indeed conducivel to Chinese economic growth, labour enployment and the upgrade of industrial structure.
While lots of person underlined the positive effects of FDI to China’s devdelopment, Yasheng Huang focus more on the other side. Form his point of view, it is an admitted fact that foreign direct investment in China stimulates the economic growth, promote employment, technology transfer, foreign trade and other aspects, but these benefits should not paper over the existing problems of China’s FDI inflow. He claimed that China is overly dependent upon foreign direct investmen and there are mainly two problems of FDI in China, including uneven geographical distribution of FDI and lack of proportion to technology distribution(Yasheng Huang). In terms of the dispreportion regional distribution which is relevant to this paper, the majority amount of inward foreign direct inversment concentrates on eastern area of China. Excepting for some cities along Yangtze river, the majority of inland cities are not incorporated into China’s “millwork plant”, these cities are merely the supplier of raw material and migrant labour force and attract much less foreign direct investment.
The investors select the FDI location very cautious as choosing the right location is immensely important to a successful investment and the future benefits. In a article by Hymer (1960) 4, Multinational Corporations (MNC’s) as the biggest source of world’s foreign direct investment, there are a lot in common when they make the location decisions of foreign direct investment. Firstly, multinational corporations would like to put FDI into differentiated markets where there is an competitive edge for them. Secondly, companies that have the ability to expand their opeartion on a world wide scale all have certain advantages, such as economies of scale, differentiated products, special skills, and low-cost production. These companies will make investments in regions that do not have these advantages. Thirdly, apart from foreign direct investment, MNCs can invest overseas through many other ways such as exporting, and licensing. Foreign direct investment are more often selected by the companies without local partners. In the last place, the countries or regions with more advanced financial systems and capital markets are more attractive to foreign direct investment. According to Dunning (1977) 4, the certain location advantages held by a particular region which do not exist in other places is a major contributor to attract FDI. He also put forward some factors which may affect the FDI location, such as natural and humanal resources, fundamental facilities, economic system and political strategy and so on. In conclusion, the position choice of foreign direct investment are affected by various factors. On the behalf of investors, their ultimate objective is to increase the wealth and benefit themselves, as a consequence, the investors would let their funds move into the place where will finally have conferred the greatest profit on them.
A lot of previous studies are in regarded to the determinants and effcets of the foreign direct investment both on country level and regional level and the main determinants of FDI location were disclosed in these studies. Wheeler and Mody (1992) pointed out that agglomeration, infrastructure,labour cost and market capacity are significant determinants. In 1996 Braunerhjelm and Svensson identified that exports and R&D expenditures also have effect on FDI. Afterwards, Friedman et al (1996) and Fan and Dickie (2000) enumerated a series of determinants such as ladour costs, labour quality,market size, infrastructure situation, government’s policy, country risk, macroeconomic conditions and so on. In 2004 Akinlo added education as a another factor. These factors may explain what makes China become a leading host for FDI in the world . China’s attraction for FDI is owing to the source of China’s low labour costs, a massive domestic market with huge market potential, preferential polices of Chinese government, stable economic envirinment, increasing improvement of infrastructure and education career etc. Moreover, these determinants can not only apply to the country level but is also adequate to regional level.
Currently, with the inprovement of China’s status in attracting FDI and global economy, the study of FDI in China has been growing. At the same time, there are a vast number of surveys paid attetion to the regional imbalance distribution of foreign direct investment in China with some investigation on the determinants of inward FDI. In 1983, a survey was taken by Bhagwati and Srinivasan to compare the investment environment among each provinces of China. They identified a set of variables including education, extent of industrialization, level of scientific research, living environment, market size, age and infrastructure which consists of transport facilities and communication facilities. Wang and Swain (1995) investigated the manufacturing sector and found that there is a siginificant positive correlation between FDI in this sector and China’s GDP, GDP growth, wage as well as rade barriers. On the contrary, the correlation between FDI in manufacturing sector and interest rate, exchange rate is negative. According to Chen’s (1996) research, wage does not affect distribution of FDI while market size is likely to be the most important determinant to the investors in making location decision of FDI. Chen and Kwan (2000) examine the determinants of FDI in 29 provinces of China from the year of 1985 to 1995, findind that the preferential policy provided either by central or local government plays a crucial role in attracting FDI. In the same year, several extra factors was added by Lu Minghong. For instance, Infrastructure factor which is represented by energy consumption; labour quality which is represented by the literacy percentage; and the a system factor which is represented by honest government and the degree of openness. In 2002, Sun et al. found that agglomeration, country risk, degree of openness, labour cost, labour quality, level of significant research, market demand and market size influenced the inward FDI of China. Luo Cheng (2006) took FDI and other related data of Fujian Province during 1981 and 2004 as a study sample and examed six variables. Through the analysis, the inward FDI of Fujian Province is positively related to annual trade volume, infrastructure, industrial structure, agglomeration level of foreign direct investment, policy variable. Zhou Yuping and Cui Xiuli (2006) analyzed the infulence of technological factors on FDI distribution and found that the amount of patent granted, expenditures on scientific and technological activities, the expenditures on R&D (Research and Development) are all significant determinants to FDI in China.
Through these extensive literature researches and studies, it can be concluded that, the factors that influence the location of FDI on the regional level of China is similar to those factors mentioned in the country level. In summary, although there is not a certain single set of determinants that consistently significantly influence the spatial distribution of FDI, market size, labour quality, labour cost, infrastructure, the degree of openness and government support are often considered as having a significant correlation between FDI and the location choice. Therefore, analyzing these factors can give the direction to why eastern area of China become a stronger appeal to foreign direct investment than central and western China.
The distribution of FDI in the fourth stage
China are often divided into three regions: eastern area, central area and western area. For the purpose of further understanding the current condition of the distribution of FDI among three regions in China, Table 1 exhibits the realized amount and the share of each region’s FDI during 2002 and 2008. The uneven distribution of FDI flows among the three regions can be seen clearly from Table 1. The twelve eastern procinces kept accounting for between 77 percent and 87 percent of total FDI inflows to China during the 2002 to 2008 period. Among the eastern area, Fujian, Shanghai, Jiangsu, Guangdong, Shangdong and zhejiang have all been hosts to significant amounts of FDI which accounted for 71.4 percent of the total FDI in 2002 and the proportion still remained at 55.2 percent in 2008. Additionally, it is worth noting that Jiangsu has surpassed of Guangdong to become the largest recipient of FDI in China since 2005. By contrast, the remaining 19 provinces and municipalities among central and western China only shared about 20 percent of FDI. On the contrary, the data suggest that although the majority of FDI inflows still take place in the eastern area, the picture has been changing. In specific terms, the regional disparity in inward FDI between the eastern, central, and western region is on a declining curve. For instance, FDI inflows to central area and western area in 2008 was has been increased about 4.6 and 6 times respectively as against 2002, comparing 2.4 times in eastern area.
Table 1 The Geographical Distribution Of Realization FDI¼ˆMillion USD¼‰
Table 1 The Geographical Distribution Of Realization FDI¼ˆMillion USD¼‰continued
Figure 2 is a trend graph which shows the variation of realized inward FDI for the Whole of China, eastern China, central China and western China from 2002-2008. From this figure, it is clearly that from 2002 to 2008, FDI in China is showing a tendency of rising in all of the three regions. This implies that China gets success and a bright prospectc of introducing FDI. In addition, the figure indicated that geographical distribution of FDI among three regions has obviously appeared the regional disparity with the increment of inward FDI. The unbalance is very sharp as the spatial distribution of realized FDI is amazingly concentrated in eastern area. But n the past few years, the amount of FDI in central and western region has increased rapidly. As far as the present situation is conserned, the overall level of introducing foreign direct investment is still low comparing to the eastern region but the great discrepancy is declining step by step. This is likely to attribute to the further expansion of opening up and reform of China and the adoption of a serial favorable polocies and measures such as “The Plan of Great Development of Western Area and strength the construction of infrastructure in central and western area”.
This paper focus on the spatial distribution of FDI in China and to identify the significant determinants of foreign direct investment at the regional level in China. A multiple regression model will be set up to measure these determinants.
In the firest place, based on the abundant researches and studies on the spatial distribution of FDI in both inter-country and intra-country context, five determinants are employed and supposed to be significant influential on the destination choice of FDI among China in this regression model. These five elements together represent each province’s level of economic development as well as its overall investment environment for FDI. In specific terms, the five determinants are market size (GDP), infrastructure (INFR), human capital (SHCN), labour cost (WAGE) and the level of openness and reform process (SHARE). In other words, for the amount of FDI in a certail region, it can be summarized by the following equation :
Y =( GDP, INFR, SHCN, WAGE, SHARE)
The regression model of FDI :
For the multiple regression model to measure the determinants of FDI by region in China, it is given below:.
(PFDI) = +(PGDP) +(INFR) +(SCHN)+(WAGE) +(SHARE) +
(i = 1, 2, â€¦â€¦, 31 and j = 1, 2, â€¦â€¦, 7)
Where i means a certain region i and j represent different years; is an error term.
The Dependent Variable (PFDI)
The dependent variable in this model is the annual amount of per capital utilization of direct foreign investments in each province during the period of 2002 to 2008.
The Explanatory Variables
Market size (GDP)
Market size is likely to be an important determinant for FDI distribution in China as the market size directly affects the return on foreign direct investment. In this model, GDP is used for estimating market demand and size effect. GDP is a sensitive indicator of local market demand and potential market growth as well as economic development of each province. As mentioned previously, the major goal for investors is to make profits thus increase their wealth and FDI is a way to achieve this purpose through expanding the market size and market share on a word wide scale. Therefore, it is likely that the certain province with larger market size and greater demand potential should attract more FDI when other things stay the same. To allow for population differences, the GDP of each province is presented in per capital.
Good infrastructure is the guarantee of smooth operation of business, it is quite reasonable to assume that the particular region can attract more FDI within better infrastructure. Infrastructure facilities covers a wide range of contents such as water conservancy, transportation intensity, telecommunication systems, institutional development and so on 2 P8. However, it is rather difficult to integrate all these various aspects into an single calculable variable. As a result, the total length of transportation routes in each provinces is regarded as the a statement about a province’s infrastructure situation. Furthermore, considering the provincial geographical size difference, the total length of transportation routes is divided by the provincial area. That is to say the infrastruacture variable is actually denoted by transportion route density which is calculated by adding the following three items together:
(1) the total length of railways in operation per unit of land mass;
(2) the total length of navigable inland waterways per unit of land mass; a
(3) the total length of highways including expressway,class I to IV highway and hignway below class IV per unit of land mass.
Human capital (SCHN)
Human capital is also considered to be an important determinant of the geographical distribution of FDI as it has direct impact on product quality, product innovation as well as technology content. In addition, quality staffs may also help companies to reduce the cost of production. In regard of this, quality workers and skilled labours play an important role in keeping companies’ market share and market position. On this basis, this paper set up a hypothesis that foreign investors prefer the region with highly skilled labour to other places given other things equal. In this model, the total number of higher education insititutions in each province normalized by provincial total population is used to sent back a mirror image of the province’s education level and further as a proxy for labour quality. The total number of schools includes the amount of undergraduate universities and colleges.
Labour cost (WAGE)
As mentioned previously, one major motivation for foreign investors to engage in foreign direct investment is to look for lower costs of production comparing to prooduce outputs in their home countries. Labour cost is one of the main essential productive factors, in this respect, the assumption should be that the cheaper the average wage of a particular province, the more FDI the province should receive.
However, owning to the remnant influence of China’s central planning which has tended to balance wage level, the average wage level of different provinces in China does not exhibit significant difference. As a result, once foreign investors select China as the FDI location, it is possible that intra-country labour cost does not make considerable difference to to FDI location choice among China. Furthermore, it is likely to be the case that labour cost has a positive relation with FDI location deciosion since MNCs may be willing to employ quality workers by paying them higher wage. This study uses annual average wage of staff and workers of each provinces divided by its retail price index to measuere the WAGE variable.
The level of openness and reform process (SHARE)
The last determinant to be estimated is the level of openness and reform process. Foreign investors my be more prefer to invest in the place with a more open economy as they know more about its local economy and they can get more liberalization in operation and competiotion. Moreover, the level of openness and reform process are also able to reflect the government’s attitude to foreign direct investment, the region with an more open economy may provided more favorble policies. However, there are also disadvantages for FDI to enter into an more open market. For instance, it will face more intensive competiotion.
This paper regards the proportion of gross industrial output value of state owned and state-holding idustrial enterprises (SOE’s) to the total region gross industrial output value as a reflection of the level of openness and reform process
About Data And Test
For the data and the test progress, there are some additional information need to be illustrated. Firstly, the data used in this study are derived from China’s Statistical Yearbook and the China Statistical Yearbook of individual region over the year of 2003 to 2009 and a region is either a province, centrally administered municipality, or an autonomous region. Secondly, total amount of foreign investment actually utilized are used for this regression model and the whole study. Thirdly, all real variables such as the amount of FDI and GDP as well as average wage in different regions are measured in current price. In addition, since FDI is measured by USD, GDP and average wage are denominated in RMB, the unit of FDI is converted into RMB by using the average yearly exchange rate.
Moreover, there is no doubt that the influencing factors of inward FDI in different regions are far more than the above five such as tax structure, the amount of tourists and the hometown relation between overseas Chinese investors and FDI etc. However, it is more difficult to collect such data on a regional or provincial level in China.
Finally, owning to the data exhibits heteroskedasticity in inspection, this study use GLS (General least square) as the testing method to estimate the model parameters during the process of test.
Summary of Results
The folliwing three tables (Table 2 ,Table 3) lists the estimation results of the five determinants based on different time period or different area (Table 4).
Table 2 summarized the regression results of the whole period from 2002 to 2008. The results indicate that all the five variables in the model are significantly related to the amount of inwad FDI in the 31 different provinces, centrally administered municipalities, or autonomous regions among China. Among them, variables of GDP, INFR and SCHN show the positive relations to regional inward FDI and the other two is negative related to FDI inflows.
From table 2, it can be seen that market size and market demand (GDP) as the first determinant in the model are strongly positive related to inward FDI in different regions. The cofficent of GDP is 1.804 indicates that a one percent increase in per capital GDP causes per capital inward FDI to rise by over 1.8 percent. Fuethermore, with the coefficeient of 1.804 which is the larggest number among the five coefficents, the market size and market demand becoms the most important factors to be considered by foreign investors when making FDI location decisions. This is consistent with previous assumption, FDI tends to move into the region with higher market size, market growth potential as well as faster speed of ecomonic development.
Owing to the level of significance of INFR, the local infrastructure condition also shows a positive impact on FDI inflows in a certain region. The coefficiet of this variable suggests that a one percent increase in the regional transpotation density which represents the region’s infrastructure level (INFR) brings about 0.177 percent point more inward FDI into this place. Therefore, this study has proved that good infrastructure condition of a place have a positive effect on FDI location. However, this factor relatively has a small effect on the regional inward FDI comparing to other determinants.
The results also indentify a significant positive relation between regional FDI inflows and labour quality. As same as the previous expectation, the region with more qiality workers and skilled labours are more attractive to foreign investors. In addition, the outcome also shows that a one percent increase in labour quality (SCHN), as proxied by the number of higher education insititutions leads to a 0.658 percent increase in regional inward FDI.
The remainning two variables,WAGE and SHARE both have a negative coefficient. To the fourth variable, the results implies that the higher the level of average wage in a region, the weaker the appeal to the FDI inflows. Since the estimated coefficient of WAGE is -1.031, a one percent increase in regional average wage brings about 1.031 percentage point decrease in the amount of inward FDI. This outcome identifies the initial hypothesis that the wage level still has an negative relation with geographical distribution of FDI at regional level in China.
The final variable SHARE is used to estimate the influence of the degree of openness and progress of reform on regional inward FDI. In other words, this model takes the share of regional gross industrial output value of SOE’s in the total region gross industrial output value as a proxy for a region’s level of openness. The less ownership the local SOE’s have in total gross industrial output value in a particular region, the more open the region is. Consequently, the negative coefficient of the final variable SHARE means that foreign direct investment is positively related to the degree of a region’s reformation and the extent of its opening to the outside world as well as the favorable policies provided by local governments. The Z-Value of this variable certificates the above connection between the level of openness and reform process and FDI inflows. The results also displays that a one percent decrease in the share of SOE’s in industrial output is associated with a 0.851 percent increase in regional inward FDI.
Table2 GLS regression results of determinants of regional FDI from 2002-2008
Notes: Constant coefficient = -4.291
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