Download The Regional Agglomeration of Foreign Direct Investment in China

The Regional Agglomeration of Foreign Direct Investment in China*
CHENG Huifang, QIU Jin yue, ZENG Zhangji
Zhejiang University of Technology, China (310032)
Abstract
This paper tries to analyze the location of FDI inflow in China and explain the
determinants of FDI regional agglomeration. Using the database of the location of FDI inflow in 30
provinces/municipalities in China in the period of 1994 to 2003, a regression model of FDI location
determinants is built to analyze the factors that driving FDI to be agglomeration in China. The results
Show that market size, lower wage, number of enterprises in region, opening level and close to the coast
location are the main factors that promote FDI to be regional agglomeration in China.
Key words FDI; Location, Regional agglomeration; regional economy; China.
1 Introduction
Foreign direct investment (FDI) has been an increasingly important factor of economic integration
and regional economic development during the last few decades in the world. However, the distribution
of FDI has become highly uneven among countries and regions within a country. Foreign direct
investment in the world has been mainly concentrated in the developed countries. FDI in developing
countries has been concentrated in the developed regional area. For example, the eastern coastal region
has attracted over eighty five percent of total FDI inflow in China .The remaining about ten percent has
been in the Middle and Western regions of China. The regional agglomeration of FDI in China has been
a very important phenomenon since Chinese open economic development. However, People pay little
attention on the determinants of regional agglomeration of FDI in China although some scholars have
made some progress on the research of FDI location in the world and in China.
This paper tries to analyze the location characteristics of FDI inflow in China and explain the
determinants of FDI regional agglomeration. Using FDI database of 30 provinces/municipalities in
1994-2004 in China, a regression model is built to analyze the factors of regional agglomeration of FDI
in China. The results indicate that market size, lower wage, number of enterprises in region, opening
level and close to the coast location are the main factors that promote FDI to regional agglomeration in
China.
2 Literature Survey
The literatures on the determinants of FDI location mainly focused on developed countries during
the 1970s and 1980s. With the development of FDI in developing counties in the 1990s, some
economists have played
attention the location of FDI in developing countries .The determinants of
FDI location are explained by cost-related strategy, the investment environment, exchange
rate ,regulatory restrictions, tariffs, quotas, infrastructure quality and economic policy and political
stability. The development and location of FDI inflow in China has been studied since China has been
the second largest foreign capital recipient in the world in past six years. The existing studies of
determinants of FDI inflow in China can be divided into three categories: the first category investigated
FDI determinants in individual province or partial provinces in China. Cheng and Kwan(2000) found
that wage, market size, transaction cost, and level of infrastructure development were important factors
of regional location of FDI in China. The second category focused on the aspect of investors from
--------------------------------*This paper is part of research Project of Nation Natural Science Foundation of China in The
Location Agglomeration of Foreign Direct Investment and the Inequality of Regional Economic
development in China .Any opinion expressed are those of the authors and not those of Nation Natural
Science Foundation of China.
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various countries. These studies found that Hong Kong, the United States, Japan and Europe are
different to major business centre, geo-cultural factors, and tax and economic incentives . Qu and Green
(1997) found that city size, consumption level and infrastructure are the most important location factors
for American, Japanese and European investments, while cultural and geographical distance play a
prominent role in Hong Kong investment. Singaporean investors mainly value the favourable treatment
granted to foreign investors. Zhao and Zhu (2000) do further studies on the country of origin effects in
FDI locations. According to the research result, Hong Kong and Taiwan investors actively seek location
with large market demands, large export potentials and high profits ratios, while Japanese investors are
favour to resource seeking. The American and European investors generally prefer to locate in the
regions with higher labour productivity and better overall economic fundamentals (Canfei He 2000).The
last category is concerned with the determinants of FDI at the industrial level in Chinese economy(Ho,
2004).The empirical analysis in his study is based on the pooled data of 13 sectors for China and 9
sectors for Guangdong province over the period from 1997 to 2002.The findings indicate that market
size, wage rate, degree of economic reform and innovation activities are important determinants of
industrial FDI in China.
3 The Model
Many studies have identified numerous factors that affect the location of FDI inflow in a country or
a region. We argue that the regional agglomeration of FDI in China is related with labor cost , local
GDP( market size), costal location, and the numbers of industrial enterprises centralized in specific
regions as well as opening level. We try to set up the model of the regional agglomeration of FDI and to
analyze the factors that affect the regional agglomeration of FDI in China.
We give following hypotheses:
H1: There is a negative correlation between labor cost and the FDI inflow in specific regions. The
higher the labor cost, the less of FDI inflow is. The cost here means productive cost, including labour
cost and transportation cost.
H2: There exists a positive relationship between the number of industrial enterprises and FDI intensity
in a region. In this regression model, we used the number of enterprises divide the acreage to evaluate
the agglomeration factor in all provinces in China.
H3: The bigger local market size in a region, the more of FDI inflow in region; It is a positive
relationship between local market size and the inflow of FDI. We use local GDP to indicate a region’s
market size.
H4: Foreign investors are favor to invest in the costal provinces and regions. the Open Door Policy and
the establishment of Special Economic Zones continue a long process where government policy has
favored foreign direct investment along the coast.
H5: There is a positive relationship between the opening level and inflowing FDI in a specific region.
Opening level is indicated the ratio of export & import to GDP. The better export & import
performance of a region, The more FDI inflow to the region. It is fact that a lot of foreign companies
take FDI as export base in the oversea, and there are over 50% of total export in China from foreign
companies.
We put these five variables to the model of FDI regional agglomeration in China and try to analyze the
factors that affect the regional agglomeration of FDI in China. The ordinary least square (OLS) is
employed to evaluate the factors that affect FDI location. Both the dependent and independent variables
have been transformed to natural logarithm. The purpose of the transformation is to reduce the curvature
of the data when plotted on natural scales, also can reduce the abnormal distribution level of residual.
The model takes the following form:
Ln( FDI ) = α 0 + α 1 Ln(Wage) + α 2 Ln( NumEnt ) + α 3 Ln(GDP) + α 4 Ln(Opening ) +
α 5 (Coastal ) + Ε i
(1)
Where, FDI is annual value of FDI inflow in China, Wage indicates Average annual wage of staff and
workers in every province, NumEnt indicates Number of industrial enterprises per 10000 km2 in region ,
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the local GDP in province indicates market size , the ratio of Import & Export to GDP indicates opening
level , Coastal indicates coastal regions, in this case, coastal regions is equal to 1,inland region is equal
to zero. Ei is a random disturbance that is attributable to errors associated with inadequate assessment.
Table 1: Illuminate the variables which we used in the regression model
Illustration
Variables
Investment
Agglomeration
Market size
Cost
Opening
Geography
Period and number of region
Index
Unit
Annual value of FDI
Number of industrial
enterprises
10 thousand $
GDP
Number per 10 sq.km.
1994 to 1996, 29 regions,
GDP: 100 millian yuan;
Consumptiom: yuan
Average wage of total
worker
degree of opening (ratio
of import and export to
GDP
Dummy, coastal or
inland
yuan
1996 to 2003
30 regions
Opening: %
1 or 0
4 The analysis of empirical results
We set up a database about location of FDI inflow in China to run the model . We use the database
of the location of FDI inflow in 30 provinces/municipalities in China in the period of 1994 to 2003 to
run the model (1), and we get following as result:
Ln( FDI ) = 13.840 − 1.543Ln(Wage) + 0.321Ln( NumEnt) + 0.913Ln(GDP) +
(2)
0.569Ln(Opening) + 0.689(Coastal) + Ε i
Regression results show that the model is credible. The value of F is 62.103, and the significant level is
0.0001, this is a very high credible. The adjusted R square is 0.913; it indicated that this model can
explain 91.3% of FDI in spatial distribution. Also, we could find that all the explanatory variables are
significant, the sequence of significant level of the FDI location determinants are gross domestic product
(GDP) (0.913) significant level at 0.000, the number of enterprises (NunEnt) (0.321) significant level at
0.004, degree of opening (Opening) (0.569) significant level at 0.016, average wage of staff and workers
(Wage) (-1.543) significant level at 0.032, and the dummy variable (Coastal) (0.689) significant level at
0.053. This result indicated the GDP and the number of existing enterprises are the most important
determinants.
Table 2: Descriptive Statistics of Regression Model
N
Mean
Std.
Deviation
FDI
10.7793
1.71102
30
WAGE
9.0128
.24284
30
GDP
7.6595
.90317
30
COASTAL
.4000
.49827
30
NUMENT 6.2559
1.57372
30
OPENING 2.7608
1.03072
30
913
Table 3 : Regression Result
Unstandardized Coefficients
Standardized Coefficients
B
Beta
(Constant)
13.840* *
0.000
(2.366)
WAGE
-1.543* *
-0.219* *
(-2.277)
GDP
0.913* * *
0.482* * *
(6.575)
COASTAL
0.689*
0.201*
(2.040)
NUMENT
0.321* * *
0.295* * *
(3.226)
OPENING
0.569* *
0.343* *
(2.582)
R2=0.928, Adjusted R2=0.913,
F=62.103, significant level at 0.0001
Durbin-Watson=1.352
Note: * * * significant level at 0.01; * * significant level at 0.05; * significant level at 0.10
The number in the bracket is the value of t
5 Conclusion
Foreign direct investment (FDI) has been an increasingly important factor of economic integration
and regional economic development during the last decade in China. However, the regional distribution
of FDI has become highly uneven between regions. FDI highly agglomerated in the eastern developed
regions but just a very small proportion is in the western regions in China. This paper tries to analyze the
location of FDI inflow in China and explain the determinants of FDI regional agglomeration. Using the
database of the location of FDI in 30 provinces/municipalities in China in the period 1994 to 2003 , a
regression model of FDI location determinants is built to analyze the factors that driving FDI to be
regional agglomeration in China. The results show that local GDP(local market size), lower wage,
number of enterprises in region , opening level and close to the coast location are the main factors that
promote FDI to be agglomeration in China. Future research should investigate the different motivations
of FDI inflow in China and preferences of different investors from different countries-of-origin over
different periods.
Reference
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