Foreign Direct Investment and Industry Structural Upgrade

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Foreign Direct Investment and Industry Structural Upgrade
FU Lifen
School of Economics, Xiamen University, China, 361005
[email protected]
Abstract: The paper firstly explores the bundle of beneficiary effects of FDI on Chinese industry
structural evolution, next, calculates industry structural alteration from 1985 to 2008 in China, and
upgrade since the reform and opening-up, and then tests the long-run and causality relations between the
five impacts and FDI by cointegration test and Granger causality test, and makes general and detailed
analysis on the effect of FDI by impulse-response function. The results indicate: FDI can accelerate
China’s industrial evolving and optimizing directly and through a bundle of beneficiary effects, such as
the change of demand structure, capital accumulation, technological progress, institutional change and
export trade development.
Keywords: Foreign direct investment, Industry structure, Readjust and upgrade
1 Introduction
Since our reform and opening to the world, foreign direct investment keep coming into China, with the
flows climbing from 1.658 billion to 92.395 billion, which has been widely recognized as a crucial
factor of the development of China. According to the transformation model that was proposed by
H.Chenery, it is the period of the fast change of industry structure when per capita GDP is between
5680 and 10650. In 2008, China's per capita GDP is 2460, which means that for now and a fairly
long period of time to come, the industrial growth and structural transformation are still an important
factor to China's economic growth. In many empirical studies of FDI’s role only considered its direct
impact, neglecting that FDI might promote industry structural upgrade by the impacts of the change of
demand structure, capital accumulation, technological progress, institutional change and export trade
development. In view of this, the paper probes into the direct and indirect impact of FDI to industry
structural upgrade, and tries to put forward positive and instructive useful reference to the present
competitive and FDI policy.
This paper is based upon annual time series data over the period from 1979 to 2008 in China.
Cointegration test and Granger causality test are applied to analyze dynamic interrelationships between
FDI and makes general and detailed analysis on the effect of FDI by impulse-response function. The rest
of the paper is organized as follows. In the next section we will explore the five impacts of FDI on
Chinese industry structural evolution. Section 3 describes the evolution of China’s industrial structure,
and Section 4 presents the empirical methodology and data used in this study, discusses the estimation
results. Finally, Section 5 concludes.
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2 The Effect of FDI Affecting Industrial Structure
With regard to the cause of industrial development, S. Kuznets(1966,1971) has investigated deeply and
drew a conclusion that after the developed country entered into the contemporary age, the new change
of industrial structure would take place with the increasing of per capita GDP. And system affect the
industrial structure through the direct way, that means influence the market and the division of labor, and
indirect way, that means exert its role by influence the police of government. H.Chenery (1975, 1986)
put forward three hypotheses to explain the structural transformation. That is the Engel's law of demand
structural hypothesis; the change of comparative advantage of trading hypothesis; products substitute for
raw materials and the impact of difference of productivity growth of the technical hypothesis. The flying
geese theory of Akamatsu emphasizes that international trade and the industrial transfer between
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countries will also affect a country's industrial structure. Krugman (1995), Davis (1997) add that the
market size, resource endowment in terms of trade are also the cause of industry structural changes.
Based on the above analysis, FDI might affect industrial structure by the following aspects:
Firstly, the mechanism of FDI affects industrial structure is by the change of demand structure. In the
process of the developing host country using foreign capital and opening wider to the outside world, the
ideas and patterns of consumption are inevitably affected by the international form. Furthermore, FDI
create new demand Cardoso and Dornbusch, 1989 and lead to the drop of the Engel coefficient and the
more demand of investment goods and societal infrastructure for its economic growth effect.
Secondly, the mechanism of FDI affects industrial structure is by the accumulation of capital domestic
firms that respond to FDI inflows by increasing and updating their capital stock (De Mello, 1999). More
particularly, when foreign investment is in a sector where many domestic firms already exist, local firms
will increase investment in order to face competition. When foreign investment is in an undeveloped
sector of the host country, positive effects could arise by creating complementarities with the domestic
firms.
Thirdly, the mechanism of FDI affects industrial structure is by the progress of technology. The benefit
of technology transfer through inward FDI for the host country is two fold. First, there is a direct effect
as the MNE may introduce new technology in the host country. Second, the MNE’s use of new
technology in the host country may affect productivity indirectly, as the technology becomes more
accessible to domestically owned firms when diffusion costs associate with geographic distance decline
(Baldwin et al. 1999).
Fourthly, the mechanism of FDI affects industrial structure is by the change of Institution. With the
inflow of FDI, the international formulate and regulation will transmit to the host country and influence
the ideas and concepts of its decision-makers. AS a carrier of institutional innovation, FDI can even
introduce market-oriented ideas, concepts and institutional framework, shake off the fetters of the
traditional planned economy system and expediting the establishment of a market Economy.
Fifthly, the mechanism of FDI affects industrial structure is by the increase of exports. In a short time,
FDI can bring the related industries of host country into the multinational network of vertical and
horizontal division of labor, optimize the export structure. In the long term, it can accelerate the industry
transfer from the base country to the host countries, advance international competitive power and better
international standing
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3 The Evolution of China’s Industrial Structure
In order to examine in detail the inflow of FDI on the evolution of industrial structure in China, We need
to analyze the change and upgrading of the industrial structure after the opening up and reform.
Based on the calculating method, we adopt hereinafter index:
∆s =
1
2
∑
s i2 − s 1i × 1 0 0 %
(1 )
i
s1
、s
2
i is phase 1 and phase 2’s
Where ∆s is the structure alteration between phase 1 and phase 2, i
production value share in gross industry value correspondingly.
From the figure1, we can see the index fluctuates and appear two peaks in 1987 and1986 and two
troughs in 1988 and 1998. From the perspective of industrial sector, labor-intensive industries was the
leading one in the 80~90s, the change of capital and technology-intensive industries accelerated and
gradually held a leading post. On the whole, the industry structure of China experienced drastic changes
before the year 2000.
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Figure1:The change of industrial structure in China
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
85 987 989 991 993 995 997 999 001 003 005
1
1
1
1
1
1
1
2
2
2
19
labor-intensive industries
technology-intensive industries
capital-intensive industries
all industrial sectors
The change of industrial structure refers to the change of the ratio of each department to total industries.
The upgrade of industrial structure means this change move to certain direction, including three trends:
the first one is heavy and chemical industrialization, that is, the proportion of national income created by
heavy and chemical industries is rising and has a substantially bigger share; the second on is high
processing degree, that is the leading factor shifting from the raw material industries to processing and
assembly industries and beltline elongates; the third one is factors of production Intensification, that is
the changes in the proportion of input factors which are caused by technological advances.
From the perspective of light-heavy industry, in order to reverse the structure deviation “heavy is heavy,
light is too light”, the result of the strategy prior to the development of heavy industry, we adopt the
policies of support light industry and cut capital construction from 1978 to 1981. This lead to the share
of heavy industry in total industrial output value decreased rapidly from 56.9 percent to 48.5 percent and
the share of light industry increased from 43.1 percent to 51.5 percent. The durable consumer goods
sector represented by electrical household appliances was developing with a high speed from 1982 to
1987, and light and heavy industry have embarked on a track of steady development. Although the
growth of light industry is faster than that of heavy industry, they are about in a synchronous
development. The change of structure of industrial sector represented mainly that the trend of heavy and
chemical industrialization, which the share of heavy industry in total industrial output value increased
from 50.7 percent to 70.5 percent, was up 19.8 percent in the nine years and the average growth was 2.2
percent.
From the perspective of high processing degree, the coefficient of high processing degree increased
from 2.63 in 1985 to 4.02 in 2007. Such as costume processing industry and textile industry, the ratio of
total industrial output value between them increased from 0.15 to 0.18, but after 1990, the ratio sharply
increased from 0.18 to 0.41 in 2007. Another case is the ratio of total industrial output value between
machinery equipment manufacturing and primary metal industries changed little in the 1980s, increased
from 2.07 in 1980 to 2.15 in 1990, but since 1990s it has an upward trend, that the ration is 2.39 in 2007.
From the perspective of factor intensity of the sector, the industrial sector is divided into
technology-intensive one, capital-intensive one and labor-intensive one. We can see the share of
capital(technology)-intensive industries grew strongly, and the share of capital-intensive industries rise
from 9.36 percent in 1985 to 20.7 percent in 2007, the share of technology-intensive industries rise from
2.89 percent in 1985 to 9.68percent in 2007. At the same time, there is a noticeable decline in the share
of labor-intensive industries, dropping from 39.03 percent in 1985 to27.8 percent in 2007, a decrease of
11.23 percentage points.
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4 Specification, Data and Estimation
Basing on the measure of China’s industrial change and upgrade, the paper makes an econometric
examination of the relationship between FDI and the industrial upgrade of China. Regression analysis
based on time series data implicitly assumes that the underlying time series are stationary. However, in
practice most economic time series variables are nonstationary. Regression of one time series variable
on one or more time series variables often can give nonsensical or spurious results, which shows a
significant relationship between variables, but in fact, this kind of relationship does not exist. So we
begin with stationary test, then use cointegration analysis research approach to find out whether there is
a long-run, or equilibrium relationship between two or more time series. Further more, impulse response
function analysis is applied to explore the effect of FDI’s impulse on other variables and how structural
upgrade responds to different variables and to find whether FDI may serve as a significant role in the
process of structural upgrade. Data are obtained from China Statistics Database and cover the period
1979 to 2008.
4.1 Function and dataset
According to the analysis of the first part of this paper, FDI might promote the industry structural
optimization in a multitude of ways, both directly and indirectly, so we take structural transformation of
domestic demand, domestic capital formation, technological progress, institutional change and the
increase in exports as a function of foreign direct investment and industry structural optimization is the
result of these factors. The explanation of variable is as follows:
IN (the Industrial Upgrade) is measured using Hoffman coefficient (the ratio of net value of consumer
goods to capital goods). While some economists have pointed out the limitations of the indicator, the
analysis of change of light and heavy industry in the secondary industry is beneficial to better
understanding the process of a country's industrialization.
EG (the Engel coefficient) represents the structural transformation of domestic demand. This is
measured a weighted average of the Engel coefficient of urban and rural areas, with the weight is their
respective population.
GCF (the gross fixed capital formation) includes finance budget and host private investment.
TFP (total factor productivity) is often used to measure the technological progress (Egger, Pfaffermary,
2001).
IC (institutional change) denotes the depth and breadth of resources allocation. Since China’ system
transition from a planed economy to a market economy is the most important part, we use the ratio of
the value-added of non-state-owned enterprises to the total industries.
EI export increase is measured by the number of exports of industrial manufactured article.
FDI (foreign direct investment) is the amount of actual use of foreign direct investment over the years.
Exports and foreign direct investment in the official statistical data is in U.S. dollars. Because in the
analysis of regression all variables are transformed to logarithmic, but other variables in the model is
measured in RMB, it is appropriate to measured in RMB. The data are deflated using the index of
producer price of industrial products and consumer price index at 1978 constant prices, then are
multiplied by the annual exchange rate of RMB to U.S. dollar. At the same time, in order to decrease the
data deviations, we transform the time series variable to logarithmic.
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4.2 Empirical results
Prior to testing for a long-run relationship between the time series using Johansen’s procedure, it
requires that all the series are integrated of the same order (Mohsen and Rhee 1997; Narayan 2003).So
we begin with
stationary test by the approach of Augmented Dickey-Fuller (1979). The test results for unit root with
the levels and first differences of the variables are shown in Table 1, indicate that all variables are
integrated to the first order, that is, they are I(1).
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IN
EG
Table1. Unit root tests
GCF
TFP
IC
EI
FDI
Levels of the variables
τT
-0.01
-0.41
-2.26
-1.28
-1.60
-2.51
0.51
-3.08**
-5.27*** -4.67*** -5.97*** -2.70***
First differences of the variables
τT
Note:
-6.84***
τT
-3.48***
denotes the Augmented Dickey-Fuller statistics with trend and intercept.
Notation‘**’ denotes significant at the 5% levels, ‘ ***’ denotes significant at the 1% levels.
Exigent
L-max
0.892044
0.846508
0.675102
0.494454
0.451078
0.281618
0.212075
64.55494
54.34901
32.60312
19.78136
17.39417
9.591874
6.912233
Table2. Cointegration Tests
Critical Values
Trace
H0:r
L-max 90%
205.1867
0
49.58633
140.6318
1
43.41977
86.28276
2
37.16359
53.67964
3
30.81507
33.89828
4
24.25202
16.50411
5
17.14769
6.912233
6
3.841466
Trace 90%
139.2753
107.3466
79.34145
55.24578
35.01090
18.39771
3.841466
To test whether these variables have a stable relationship, the Johansen’s maximum-likelihood
procedure is used. The cointegration test results are found in Table2. Both the maximum eignvalue
(lambda-max) and trace tests reject the null hypothesis of no cointegration at the 5 percent level of
significance. This is also the case with the null of a single cointegration relation. Turning to the null of
two and three relations, we observe that they are rejected by the maximum eignvalue test but not by the
trace test.
While cointegration implies causality in at least one direction, cointegration tests do not determine the
direction in which causality flows. This would have to be ascertained from Granger causality tests.
Granger causality tests show FDI Granger causes five variables and there is a bidirectional relationship
between FDI and IN. This fully indicates that FDI promote the upgrade of industrial structure directly
and indirectly.
Lag length
2
2
1
1
1
5
Table3. Granger Causality Tests
Null Hypothesis
F-Values
FDI does not Granger Cause IN
4.08767
IN does not Granger Cause FDI
2.86790
FDI does not Granger Cause EG
1.76165
EG does not Granger Cause FDI
0.46415
FDI does not Granger Cause GCF
10.4087
GCFdoes not Granger Cause FDI
0.64780
FDI does not Granger Cause TFP
9.18128
TFP does not Granger Cause FDI
0.01564
FDI does not Granger Cause IC
2.04554
IC does not Granger Cause FDI
0.23830
FDI does not Granger Cause EI
2.97533
EI does not Granger Cause FDI
1.58454
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P-Values
0.0303
0.0773
0.1942
0.6344
0.0034
0.4282
0.0055
0.9014
0.1646
0.6295
0.0491
0.2281
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5 Conclusion
Through calculating the industry structural alteration and upgrade of China, we can find it has a
significantly upgrade, especially since the middle of 1980s. In line with more and more MNC
investment in China, the industrial development and upgrade are at a faster rate.
The long-term relationship between FDI and industry structural upgrade is confirmed by subsequent
tests. The results of Granger causality show FDI Granger causes six domestic variables and there is a
bidirectional causal relationship between FDI and IN. The entry of foreign capital make up for domestic
fund shortage, improve China’s efficiency of resources collocation, promote China’s exertion of
comparative advantage and induce the enhancement of total economic output, expedite institutional and
mechanism innovation. In a word, FDI does drive China’s industrial evolving and optimizing directly
and through a bundle of beneficiary effects, such as the change of demand structure, capital
accumulation, technological progress, institutional change and export trade development.
In addition, it deserves to be specially noted that although FDI play an important role in the upgrade of
industry, it does not mean China should introduce foreign investment on a large scale. On the premise of
an orderly growth of using foreign capital, The Government should guide more foreign investments to
those industries with high technology content, added value and associate degree. Furthermore, the
Government need to implement the policies that encourage foreign investment in the central and western
regions of China. Thus, we can make good use of the role of FDI in improving the performance of
whole economy on the one and in upgrading our industry structure on the other.
References
[1]. Agosin, M. R., Mayer, R.B. Foreign Investment in Developing Countries: Does it Crowd in
Domestic Investment?. Discussion Paper no. 146, United Nations Conference on Trade and
Development (UNCTAD), Palais des Nations, Geneva, Switzerland, 2000.
[2]. Baldwin, R. E., H. Braconier, and R. Forslid. Multinationals, Endogenous Growth and
Technological Spillover: Theory and Evidence. CEPR Dicussion Paper, (1999).
[3]. Borensztein E, De Gregorio J, Lee JW. How does foreign direct investment affect economic
growth?. Journal of International Economics, 1998(45):115~135.
[4]. Chenery,H.B. The Structural Approach to Development Policy. American Economic Review, 1981
(2): 310~316.
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