externalities of fdi: evidence by chan yuen tung a...
TRANSCRIPT
![Page 1: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/1.jpg)
EXTERNALITIES OF FDI: EVIDENCEFROM CHINA’S EASTERN COASTAL
AND CENTRAL PROVINCES
BY
CHAN YUEN TUNGSTUDENT NO. 12006866
ECONOMICS CONCENTRATION
A PROJECT SUBMITTED IN PARTIAL FULFILLMENT OFTHE REQUIREMENTS FOR THE DEGREE OF
BACHELOR OF SOCIAL SCIENCES (HONOURS) DEGREEIN CHINA STUDIES
HONG KONG BAPTIST UNIVERSITY
APRIL 2015
![Page 2: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/2.jpg)
Page of Acceptance
April 2015
We hereby recommend that the Project by Mr. CHAN Yuen Tung entitled
“Externalities of FDI: Evidence from China’s Eastern Coastal and Central Provinces.” be
accepted in partial fulfillment of the requirements for the Bachelor of Social Sciences
(Honours) Degree in China Studies in Economics.
____________________ ____________________
Dr. Erin SO Pik Ki ____________________
Project Supervisor Second Examiner
1
![Page 3: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/3.jpg)
Acknowledgement
I would like to thank my supervisor Dr. Erin SO Pik Ki for guiding and
enlightening me through out the entire study. Without her generous care and support, this
paper is hardly finished. Thanks are also due to Dr. CHAN Hing Lin for his teaching of the
econometric theories and applications and to Dr. LUK Sheung Kan for his pragmatic
comments on the regression models.
____________________
China Studies Degree Course
Economics Concentration
Hong Kong Baptist University
15.04.2015
2
![Page 4: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/4.jpg)
Table of Content
PAGE OF ACCEPTANCE 1
ACKNOWLEDGEMENT 2
ABSTRACT 4
1. INTRODUCTION 5
2. LITERATURE REVIEW 9
3. METHODOLOGY AND REGRESSION MODEL 14
4. DATA 21
5. REGRESSION RESULT AND INTERPRETATION 23
6. CONCLUSION AND POLICY IMPLICATION 37
REFERENCES 40
3
![Page 5: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/5.jpg)
Abstract
Using the panel data across 14 provinces in China’s Eastern coastal and Central
regions from 2002 to 2011, this paper finds that there are different levels of positive and
significant externalities spilled out from the labors hired by FDI and HKMT firms in
various sectors as well as the capital stocks invested by FDI firms. Moreover, export-led
growth does exist in China’s industry sector, but is limited to the domestic firms only. In
addition, the export shares of FDI and HKMT firms do not affect the domestic economic
growth. Lastly, an interesting finding is that increasing the capital inputs in construction
sector does not necessarily generate efficient GDP output growth.
4
![Page 6: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/6.jpg)
1. Introduction
To take the advantages of the foreign direct investment (FDI), it is not uncommon
to see that the less developed countries’ governments are competing with each other to
offer different preferential policies, such as rental discounts, tax holidays and some special
subsides, to attract the overseas investors. Doubtlessly, China is a case in point. For
instance, in some sectors, the FDI firms can enjoy a 2-year tax holiday starting from the
first year that they can make profit and after these 2 years, they can still have a 50%
discount of the tax for the following 3 years. The major reason for doing so is that Chinese
government realizes that there will be externalities brought from the FDI inflows, which
will finally benefit the domestic economy. Thus, in the 1990s, with the government’s
efforts, China has become the largest recipient of the FDI among all other developing
countries.
Back to the late 1970s, China government has already set attracting the overseas
capital as one of the economic reform strategies. Since the Law on Sino-Foreign Equity
Joint Ventures1 published in 1979, the annual inflow of FDI has stepped up steadily. In
early 1992, China’s top leader Deng promised to further open up the country and to
accelerate the economic reform in his tour to the Southern provinces. Right after his speech,
the annual FDI inflows of 1992 and 1993 have increased for more than the double and
reached a peak of U.S. 44.2 billion in 1997. After China entered the World Trade
Organization (WTO) in 2001, according to Figure I below, the inflows of FDI kept
expending explosively until 2008, which was the year of global financial tsunami, to a level
1 It is a legal framework for FDI, which allows foreign investors to have equity joint ventures together with partners from China.
5
![Page 7: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/7.jpg)
of U.S. 186.8 billion. Starting from 2009, the figure recovered and rebounded rapidly from
U.S. 167.1 billion to another peak of U.S. 331.6 billion in 2011.
Figure I – China’s FDI inflows (1990 - 2011). Source: The World Bank.
Although there are many FDI inflows in China, not every province can get the same
amount of benefits. As Figure II below illustrates, the regional distribution of FDI is not
even. The majority part, up to 85%, went to the Eastern coastal region; this is because in the
beginning of the open door policies, the Eastern area acted as a ‘white mouse’, especially
Guangdong province, as it is near Hong Kong and close to the coastal line, it has a better
linkage with the overseas investors. As a result, Guangdong alone shared 25.3% of the total
FDI inflows from 1990 to 2011. While the central region accounted for 10% during this
period. Although the West regions shared only 5% of the total FDI from 1990 to 2011, this
percentage indeed has already been increasing slowly from 3% in 1979 to 1998.
0
50
100
150
200
250
300
350
Bill
ion
(U.S
.)
FDI inflows in China (1990 to 2011)
6
![Page 8: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/8.jpg)
Figure II – Regional Distribution of FDI Inflows in China (2002 - 2009). Source: China Trade and External Economic Statistical Yearbook. Eastern coastal region: Hebei, Liaoning, Jiangsu, Zhejiang, Fujian, Shandong,
Guangdong and Hainan. Central Region: Shanxi, Anhui, Jiangxi, Henan, Hubei and Hunan. West Region: Shaanxi, Sichuan, Guizhou, Yunnan, Tibet, Gansu, Qinghai, Ningxia and Xinjiang.
Besides the uneven geographic distribution, the sectorial distribution of FDI inflows
is also uneven. As the production costs in China are relatively cheap; therefore, according
to the Figure III below, the secondary sector, especially the industry, benefited the most and
accumulated for more than half of the FDI inflows; only industry alone got 56% of the total
FDI inflows from 2002 to 2009.
As above data shows, the FDI inflows after China entered WTO in 2001 have been
increasing rapidly and majorly concentrates on the 2nd sector, especially the industry sector,
and in the Eastern coastal and the central regions. Therefore, this paper collects a panel data
crossing 14 provinces, namely: Hebei, Liaoning, Jiangsu, Zhejiang, Fujian, Shandong,
Guangdong, Hainan, Shanxi, Anhui, Jiangxi, Henan, Hubei and Hunan, from 2002 to 2011
to analyze the externalities brought by these investments to different levels of the domestic
economic growths and will put more attentions on the industry sector. The current study
Eastern Coastal Region 85%
Central Region 10%
West Region 5%
Regional Distribution of FDI in China (2002 to 2009)
7
![Page 9: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/9.jpg)
will also analyze and compare the effects brought from 2 different origins of the FDI,
which are the investments from the foreign and HKMT investors.
Figure III – Sectorial Distribution of FDI Inflows in China (2002 to 2009). Source: China Trade and External Economic Statistical Yearbook.
The rest of this paper is organized as follows. The previous literatures of the related
topics are summarized in section 2. The regression models are shown in section 3. Section
4 describes the data and the processing procedures. The econometric results and the related
interpretations are contained in section 5. The concluding remarks and some policy
implications are in the final section 6.
1st Sector 1%
2nd Sector - Industry 56%
2nd Sector - Construction
1%
3rd Sector 42%
Sectorial Distribution of FDI in China (2002 to 2009)
8
![Page 10: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/10.jpg)
2. Literature Review
According to Qi and Li (2008), there are 3 main ways to increase the technology,
innovation and creativity level, which are:
I. Creating knowledge independently by research and development (R&D);
II. Purchasing advanced technology and know-how from international trade;
III. Spilling over the knowledge from FDI enterprises to the host countries;
and hence, they will increase the productivity of the society and the economic growth as
well.
Unlike the former two ways, the externalities in form of knowledge spillover
generated by FDI are relatively indirect and there are 5 major channels for it to carry out.
First and foremost, the local partners can learn the production processes and technology
directly from the investors. Labor mobility effect can be the second channel. The turnover
of the trained and skilled labor from the FDI firms to the domestic related counterparts will
also bring the technological know-how to their ‘new’ domestic firms. Demonstration effect,
in which the products and the inventions of the FDI companies can stimulate and enlighten
the local R&D activities, can be another channel (Jianhong Qi & Hong Li, 2008). The
fourth channel is the competitive effect. Last but not least, there will be the vertically
knowledge spillover through the forward and backward linages of supply chains. For
example, according to Smarzynska (2002), the local suppliers in Lithuania will have higher
productivities when there is a greater presence of the FDI companies.
9
![Page 11: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/11.jpg)
Economists generally agree that FDI does insert an externality - the positive
knowledge spillover effect and as a result, the production technology, efficiency and thus
the economies will grow in the host countries, which are usually the Lesser-Developed
Countries (LDCs), can be enhanced. For instance, Findlay (1978) suggests that the speed of
technical progress in the host country can be increased infectiously by the more advanced
know-how and management methods used in the FDI corporations. Walz (1997) claims that
the multinational companies in LDCs will spill their knowledge over to the domestic R&D
sectors and causing the economic growths in the host countries happen eventually.
Although most of the related theoretical literatures show the positive relations
between the levels of presence of the FDI firms, the technical progresses and the
productivities of the host countries, interestingly, the results of empirical studies are
somehow mixed and diverse. Major views from the empirical literatures are summarized as
follow:
FDI has a positive effect on the technology progresses and productivities in the host
countries.
Many scholars find out that the domestic firms are likely to absorb the
knowledge spillover by the FDI and learn from them to increase their own
productivities and competitiveness in the market.
Rhee and Belot (1989) discover that the creations as well as the growth of
the local-owned textile firms in Bangladesh and Mauritius are stimulated by the
entry of a few foreign-owned firms. Hanel (2000) assumes that there are relations
between the shares of sales of the foreign subsidiaries in 19 industries of Canada
10
![Page 12: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/12.jpg)
and those subsidiaries’ related knowledge stocks; then calculates how R&D in those
subsidiaries affect the growth of the domestic factor productivity; and draws the
conclusion that the knowledge creation and the productivity growth can be
contributed by those non-local knowledge stocks. Branstetter (2000) figures out that
FDI is an important way for knowledge spillovers between both the indigenous
companies in US and the investing companies from Japan using the data of patent
citations.
More recently, Lee (2006) summarizes that the global knowledge spillover
via FDI is obvious after analyzing the data of 16 Organization for Economic
Cooperation and Development (OECD) countries from 1981 to 2000. Wang et al.
(2006) find that the inflows of FDI are one big incentive for the domestic companies
in China to lift their R&D inputs in order to maintain their competitiveness under
the international and globalization pressures.
FDI does not have a positive effect on the technology progresses and productivities
in the host countries.
Some scholars think that the spillover effect from the FDI is not strong and
robust enough, whereas some may even deem that the effect does not exist at all. As
a result, the domestic parties do not learn or adopt the more advanced technology,
know-how or managements used by the FDI firms to increase their productivities.
A case in point is that the orders about assembly of electronic devices
received by the local firms from the foreign investors do not help the former to learn
any new or advanced technology besides the simple and low-value-added assembly
work. Another case in point is that, according to Xian and Yan (2005), in order for
11
![Page 13: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/13.jpg)
the spillover effects from FDI to occur, the local firms have to achieve certain basic
technology levels; yet, the provinces in the middle and west part of China have not
pass through the ‘doorsill’ and thus, no robust spillover effects can be observed.
Chen (2007) argues that the influences from FDI to China’s regional innovation
capabilities are feeble and furthermore, the FDI inflows may even crowd out the
domestic R&D activities.
The spillover effect of FDI on the technology progresses and productivities in the
host countries is unclear.
Besides the R&D stocks, economists generally understand and accept that
the capital stocks of the FDI firms can also spill over and enhance the productivities
of the local companies. However, Todo (2006) refutes that, basing on the data of
Japanese manufacturing industries from 1995 to 2002, there is a positive effect of
R&D stocks, but not capital stocks, on the knowledge and productivity growths of
the host countries, and that result can be interpreted as the daily production practices
of the FDI firms do not generate spillover effects, but only the R&D activities do.
This uncertain spillover effect is somewhat similar in China in the eyes of
Jiang and Xia (2005); using the data of China’s hi-tech industries, they claim that
FDI does provide some positive effects towards the domestic counterparts, yet, their
own R&D inputs and the numbers of the scientific and technical researchers, staff
employed are the more important factors contributing the knowledge creations of
the domestic firms; in addition, they find that the competitive effect does not only
bring goods to the firms, while the local firms may also lose their markets as well as
their own strategic R&D resources due to the intensive competition pressures.
12
![Page 14: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/14.jpg)
As mentioned above, the empirical studies towards this issue come with different
and diverse opinions. And the related studies towards China’s regional situations after 2001,
which is the entry year of WTO, comparing the direct investments from different origins
are relatively rare. Hence, this current paper tries to analyze the externality, which can drive
the economic growth, brought by the FDI from the foreign investors and HKMT investors
in the Eastern coastal and the central regions of China.
13
![Page 15: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/15.jpg)
3. Methodology and Regression Model
The Gross Domestic Product (GDP), measures the total gross values added by all
the residents participated in productions, which also is the aggregate production level of a
country. It is commonly used to measure to the economic performances of the countries as
well as various sectors’ contributions.
In this current study, instead of Nominal GDP (NGDP), Real GDP (RGDP) is used
as it separates the effects of inflation or deflation from NGDP and therefore, it can better
indicate the economic performances. In order to observe the real economic growth caused
by the externalities, taking the natural logarithm of the RGDP is an essential step to change
it into the growth rate. Thus, lnGDP, which is the natural logarithm of the deflated NGDP,
will act as the dependent variables in following 9 regression models.
The basic components and regression model to measure the externalities, according
to Chen (2011) in his book2, are as follow:
lnGDP = Constant + αlnL + βlnK + γ (Other independent variable) + ε
where α, β and γ are the coefficients that capture the impacts from the growth of L (labor),
the growth of K (fixed capital stock) and the other independent variable related to the
externalities. ε represents the random error term of the model.3 And lnL and lnK are the
growth rates of labor number and capital stock respectively. While other independent
2 Indeed, the model originally comes from the production function: Y = ALαKβ.
3 The mean of this term should be zero.
14
![Page 16: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/16.jpg)
variable can be any variable that can insert an impact on the dependent variable, such as the
FDI inflows growth.
This current paper mainly focuses on the labor and the export side; since, comparing
with the spillover effect brought by the capital stock, these two factors’ effects are
relatively less studied and indirect in the sense that the knowledge or know-how basically
has to spill through learning and adapting but not directly to acquire through purchasing.
Basing on the above production function, 9 gradually established regression models
are shown below (see Table I for definitions of the subscripts); to avoid the multi-collinear
problem, expect model (7) and (8), independent variables of the domestic firms are not
placed into the models.
InGDPp,t = C + β1InLp,t + β2InKp,t + β3In(LF,p,t / Lp,t)
+ β4In(LHKMT,p,t / Lp,t) + ε (1)
Subscript Definition p Pinvince t Time Period (Year) t-1 The Last Time Period (Lagged 1 Year) F Foreign Direct Investment Firms HKMT Hong Kong, Macau and Taiwan Investment Firms D Domestic Firms 1st Sector The First Economic Sector 2nd Sector The Second Economic Sector 3rd Sector NON 2nd Sector Industry Construction TEV TPV
The Third Economic Sector The First and the Third Economic Sectors Industry Sector Construction Sector Total Export Value Total Production Value
Table I – Definitions of the Subscripts.
15
![Page 17: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/17.jpg)
where In(LF,p,t / Lp,t) and In(LHKMT,p,t / Lp,t) are the growth rates of the ratios of labors
employed by FDI firms as well as HKMT investment firms among the total employed
labors respectively; while the coefficient β3 and β4 measure the magnitudes of the impacts
from the growths of the FDI and HKMT investment firms’ labors to the total employment
ratio severally. This model is set to study whether changes of the portions of labors hired by
the FDI and HKMT investment firms will affect the GDP growth.
Model (2) is somehow similar with model (1), except it is set to study whether
changes of the portions of capital stocks, instead of the employed labors, invested by the
FDI and HKMT investment firms will affect the GDP growth.
InGDPp,t = C + β1InLp,t + β2InKp,t + β3In(KF,p,t / Kp,t)
+ β4In(KHKMT,p,t / Kp,t) + ε (2)
where In(KF,p,t / Kp,t) and In(KHKMT,p,t / Kp,t) are the changes of the ratios of fixed capital
stocks invested by FDI firms as well as HKMT investment firms among the total fixed
capital stock respectively; while the coefficient β3 and β4 indicate the degrees of the
impacts from the growths of the FDI and HKMT investment firms’ fixed capital stocks to
the total fixed capital stock ratio severally.
In order to further study the spillover effects through the employed labors in
different economic sectors, model (3) and (4) are gradually developed from model (1)
above.
InGDP2nd Sector,p,t = C + β1InL2nd Sector,p,t + β2InK2nd Sector,p,t
+ β3In(L2nd Sector,F,p,t / L2nd Sector,p,t) + β4In(L2nd Sector,HKMT,p,t / L2nd Sector,p,t) + ε (3)
16
![Page 18: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/18.jpg)
InGDPNON 2nd Sector,p,t = C + β1InLNON 2nd Sector,p,t + β2InKNON 2nd Sector,p,t
+ β3In(LNON 2nd Sector,F,p,t / LNON 2nd Sector,p,t) + β4In(LNON 2nd Sector,HKMT,p,t / LNON 2nd Sector,p,t)
+ ε (4)
Unlike model (1), model (3) and (4) above are set to test whether the growths of the ratios
of L employed by the FDI firms, HKMT investments firms in the secondary and non-
secondary sector to the total employment in these 2 sectors will affect the growths of GDP
in these sectors respectively.
If model (3) shows significant and robust coefficient β3 or β4, then by using model
(5) and (6), it is possible to predict whether the spillover effects mainly occur in the
industry or the construction sector.
InGDPIndustry,p,t = C + β1InLIndustry,p,t + β2InKIndustry,p,t
+ β3In(LIndustry,F,p,t / LIndustry,p,t) + β4In(LIndustry,HKMT,p,t / LIndustry,p,t) + ε (5)
InGDPConstruction,p,t = C + β1InLConstruction,p,t + β2InKConstruction,p,t
+ β3In(LConstruction,F,p,t / LConstruction,p,t) + β4In(LConstruction,HKMT,p,t / LConstruction,p,t) + ε (6)
The coefficient β3 and β4 in model (5) are set to capture the impacts from the growths of the
labors working in industry sector, which are hired by FDI firms as well as HKMT
investment firms respectively, over the total industrial employment to the industry’s GDP
growth; while β3 and β4 in model (6) are not far-off but targeted at the construction sector.
Besides studying L and K, the export of industry sector is also worthwhile to pay
attention as the export sector, which is mainly composed by the industrial export sector in
17
![Page 19: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/19.jpg)
China, can cause the export-led growth in many developing countries.4 Therefore, model (7)
below is established to test the relation between the GDP growth of the industry sector and
the changes of the ratio of total export value to total production value.
InGDPIndustry,p,t = C + β1InLIndustry,p,t + β2InKIndustry,p,t
+ β3In(TEVIndustry,p,t / TPVIndustry,p,t) + ε (7)
If β3 in model (7) is significant and robust, then, by using model (8), whether the
GDP change of the industry sector, which is driven by the export, is mainly from the
growths of the export portions of the FDI firms, HKMT investment firms or domestic firms
to their own production values can possibly be identified.
InGDPIndustry,p,t = C + β1InLIndustry,p,t + β2InKIndustry,p,t
+ β3In(TEVIndustry,F,p,t / TPVIndustry,F,p,t) + β4In(TEVIndustry,HKMT,p,t / TPVIndustry,HKMT,p,t)
+ β5In(TEVIndustry,D,p,t / TPVIndustry,D,p,t) + ε (8)
Apart from the export to production ratio, the growths of the shares of exports from
FDI firms as well as from HKMT investment firms among the total export value may also
drive the GDP growth in industry sector, and thus, model (9) below is set to test the above
statement.
InGDPIndustry,p,t = C + β1InLIndustry,p,t + β2InKIndustry,p,t
+ β3In(TEVIndustry,F,p,t / TEVIndustry,p,t) + β4In(TEVIndustry,HKMT,p,t / TEVIndustry,p,t) + ε (9)
4 See Tiwari and Mutascu (2011).
18
![Page 20: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/20.jpg)
In order to prevent the problem of reverse causality, another 9 regression models are
also formulated with the subscript ‘t’ of all the independent variables in above 9 models
replaced by ‘t-1’ (lagged for 1 year) for robustness checking as follows:
InGDPp,t = C + β1InLp,t-1 + β2InKp,t-1 + β3In(LF,p,t-1 / Lp,t-1)
+ β4In(LHKMT,p,t-1 / Lp,t-1) + ε 1(t-1)
InGDPp,t = C + β1InLp,t-1 + β2InKp,t-1 + β3In(KF,p,t-1 / Kp,t-1)
+ β4In(KHKMT,p,t-1 / Kp,t-1) + ε 2(t-1)
InGDP2nd Sector,p,t = C + β1InL2nd Sector,p,t-1 + β2InK2nd Sector,p,t-1
+ β3In(L2nd Sector,F,p,t-1 / L2nd Sector,p,t-1)
+ β4In(L2nd Sector,HKMT,p,t-1 / L2nd Sector,p,t-1) + ε 3(t-1)
InGDPNON 2nd Sector,p,t = C + β1InLNON 2nd Sector,p,t-1 + β2InKNON 2nd Sector,p,t-1
+ β3In(LNON 2nd Sector,F,p,t-1 / LNON 2nd Sector,p,t-1)
+ β4In(LNON 2nd Sector,HKMT,p,t-1 / LNON 2nd Sector,p,t-1) + ε 4(t-1)
InGDPIndustry,p,t = C + β1InLIndustry,p,t-1 + β2InKIndustry,p,t-1
+ β3In(LIndustry,F,p,t-1 / LIndustry,p,t-1) + β4In(LIndustry,HKMT,p,t-1 / LIndustry,p,t-1) + ε 5(t-1)
19
![Page 21: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/21.jpg)
InGDPConstruction,p,t = C + β1InLConstruction,p,t-1 + β2InKConstruction,p,t-1
+ β3In(LConstruction,F,p,t-1 / LConstruction,p,t-1)
+ β4In(LConstruction,HKMT,p,t-1 / LConstruction,p,t-1) + ε 6(t-1)
InGDPIndustry,p,t = C + β1InLIndustry,p,t-1 + β2InKIndustry,p,t-1
+ β3In(TEVIndustry,p,t-1 / TPVIndustry,p,t-1) + ε 7(t-1)
InGDPIndustry,p,t = C + β1InLIndustry,p,t-1 + β2InKIndustry,p,t-1
+ β3In(TEVIndustry,F,p,t-1 / TPVIndustry,F,p,t-1)
+ β4In(TEVIndustry,HKMT,p,t-1 / TPVIndustry,HKMT,p,t-1)
+ β5In(TEVIndustry,D,p,t-1 / TPVIndustry,D,p,t-1) + ε 8(t-1)
InGDPIndustry,p,t = C + β1InLIndustry,p,t-1 + β2InKIndustry,p,t-1
+ β3In(TEVIndustry,F,p,t-1 / TEVIndustry,p,t-1)
+ β4In(TEVIndustry,HKMT,p,t-1 / TEVIndustry,p,t-1) + ε 9(t-1)
20
![Page 22: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/22.jpg)
4. Data
The econometric analyses in this paper are based on data of 14 provinces across the
Eastern coastal and central region of China from 2002 to 2011. The annual provincial data
is collected from various statistical reports: CHINA STATISTICAL YEARBOOK, CHINA
POPULATION & EMPLOYMENT STATISTICS YEARBOOK, CHINA LABOUR
STATISTICAL YEARBOOK, STATISTICAL YEARBOOK OF THE CHINESE
INVESTMENT IN FIXED ASSETS, CHINA INDUSTRY ECONOMY STATISTICAL
YEARBOOK, CHINA REAL ESTATE STATISTICS YEARBOOK, CHINA EXTERNAL
ECONOMIC STATISTICAL YEARBOOK and different provincial statistical yearbooks,
such as JIANGSU STATISTICAL YEARBOOK.
Since NGDP cannot reflect the actual economic performance, GDP used in this
paper is the NGDP deflated by the GDP deflator, which takes 1978 as the base year. Labor
is measured as the employed labor number at the end of the year. The export and
production value are counted in the provinces which product the final goods. For example,
if Guangxi produces a car and Guangdong acts as the exporter, the production value as well
as the export value will both count into the former’s account.
As Liu (2002) mentions, the capital stock measurement is a well-recognized
problem in the empirical studies; it does not only exist in the studies of China, but also
other countries. There are several approaches to estimate the total capital stock in a country;
unlike some fellows who will use the fixed capital investment figures directly as the capital
stock, this paper uses a scientific method used by Kim and Lau (1994) and Lei and Yao
(2009), which the initial capital stocks of China, Hong Kong and Macau, are assumed to be
21
![Page 23: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/23.jpg)
5 times of the real gross fixed capital formation in the same year and the real gross fixed
capital formation after the initial year can be used as a proxy for the change in the capital
stock each year. And China’s annual depreciation rate of the capital, as used by Perkins
(1988), Woo (1998), Meng and Wang (2000) and Wang and Yao (2003), is assumed to be
5%. Therefore, in the current study, the nominal fixed capital formation of the initial year
(2002) is firstly deflated by the investment in fixed assets price index, which takes 1978 as
the base year; then by multiplying the value 5 times, the initial capital stocks can be found.
And the capital stock of the year after 2002, i.e. 2003, is the sum of 95% of the capital
stock of 2002 plus the newly real fixed capital formation of 2003 (deflating the nominal
fixed capital formation by the investment in fixed assets price index of 2003).
Furthermore, as Holz (2004) claims that China’s official statistics are of
questionable quality and inaccuracy, the inconsistency among the data used by this study is
relatively apparent. To cope with this problem, if there is inconsistency of a data point, the
data from a later time period will be given the first priority and the data from a higher
authority will be given the second priority in this study.5
5 This practice is in a belief that the data announced later may be amended and therefore they should be generally more consistent and competent; while the data published by a higher authority might be more accurate because the data may be processed more seriously.
22
![Page 24: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/24.jpg)
5. Regression Result and Interpretation
As there are various institutions and characteristics of each province after the de-
centralization, fixed-effects model should be used to process the panel data to separate the
differences and let each province has a different constant term. However, probably due to
the insufficient sample size as the time limitation, the results from 18 models are almost
statistically insignificant. Hence, pooled ordinary least squares (pooled OLS) is used to
carry out the regressions in the current paper. And the results are shown below.
From the results of 9 models as well as 9 (t-1) models, generally speaking, the
coefficients of lnL and lnK, which are β1 and β2, are positive and statistically significant at
the 1% level. And the means of the all coefficients of them are 0.5981 and 0.3871
respectively. Therefore, it implies that, on average, every 1% of labor increase will lead to a
0.60% growth of GDP, while every 1% increase of capital stock will lead to 0.39% growth
of GDP. And the results above are indeed within the expectation as L and K are two basic
elements that have positive relations with the output in the production function. Moreover,
it suggests that, from a macro view, putting 1% extra labor in economic activities will give
a higher output growth then putting 1% more of the capital stock. And it denotes that in
these regions, economic activities and growths are still relying more heavily on labor
instead of using capital such as machines and computers and it can also be interpreted as
the economy of China’s Eastern coastal and central areas is relatively labor-intensive.
However, one thing to be highlighted is that the coefficients of the InKConstruction in
model (6) and its (t-1) model, unlike all other coefficients of lnL and lnK in remaining
models, are not statistically significant. This suggests that the increase in fixed capital stock
23
![Page 25: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/25.jpg)
in the construction sector of those provinces does not push up the GDP growth of the
related field and this can also be interpreted as the capital investments in China’s
constriction sector are inefficient to generate positive outputs.
Table II – Estimation of GDP growth effect by the changes of (LF/L), (LHKMT/L), (KF/K) and (KHKMT/K).
a) Models with (t-1) mean that the independent variables are lagged for 1 year for robustness checking. b) The italic numbers in the table above are the p-values. c) *** stands for p-value < 0.01; ** stands for p-value between 0.01 & 0.05; * stands for p-value between 0.05 & 0.1.
According to Table II, the results of model (1) show that if the ratio of labors hired
by the FDI firms to the total employment of a province increase 1%, the GDP of that place
will have a 0.12% increase; while the labor hired by HKMT investment firms to the total
employment ratio of a province increase 1%, it will lead to a 0.06% rise in GDP of that
24
![Page 26: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/26.jpg)
province. And both findings above are significant at the 1% level and the results still hold
their significances and robustness in the (t-1) model. The empirical results reveal that the
increases of ratios of labors from FDI firms and HKMT firms can both have positive effects
on the GDP growth; but with the same 1% increase in the ratio, the labor hired by the FDI
firms will give a nearly 100% higher return then the labors hired by HKMT firms to the
GDP growth. It denotes that the spillover effects are stronger through the labors hired by
the FDI firms to the domestic GDP growth. It may due to different reasons and for example,
the worker training sections are better and/or the standards of production, such as the know-
hows, technical requirements in the working environment, are higher in the FDI firms,
comparing with HKMT ones; as there is a hypothesis that when the multinational firms
decided to enter a country, i.e. China, they will have ensured that the revenues brought by
their competitive advantages, such as high technologies, are big enough to cover the huge
costs. And when the labors in the FDI firms go to domestic firms, the local firms can enjoy
the relatively high-skilled labors. Hence, the general productivities and contributions to the
local GDP growth of the labors in FDI firms are higher than those in HKMT firms.
Model (2)’s results in Table II above show that when the percentage of the capital
stock owned by FDI firms among the total amount of the capital stock increases 1%, the
GDP will have a rise of 0.22% and this finding is robust and significant at the 1% level
both in Model (2) and its (t-1) model. Whereas the coefficients of the ratio of capital stock
owned by HKMT firms to the total amount of the capital stock are statistically insignificant
in Model (2) and also its (t-1) model, suggesting that there are no association between this
ratio and the GDP growth. By assuming that the more advanced capital stocks can generate
a higher output value and contribute more to the GDP, the above findings reveal that, 25
![Page 27: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/27.jpg)
comparing to the fixed asset capital stocks owned by HKMT firms, the ones owned by FDI
firms are more advanced and with higher productivities and this finding is also in line with
the hypothesis mentioned above. Therefore, if the ratio of the capital owned by the FDI
firms to the total capital stock amount in a province increases, there will be a positive
spillover effect to domestic sector as well as a positive growth of the GDP.
Table III – Estimation of GDP growth of 2nd sector and NON 2nd sector effects by the changes of (L2nd Sector,F /
L2nd Sector), (L2nd Sector,HKMT / L2nd Sector) as well as (LNON 2nd Sector,F / LNON 2nd Sector) and (LNON 2nd Sector,HKMT / LNON
2nd Sector).
a) Models with (t-1) mean that the independent variables are lagged for 1 year for robustness checking. b) The italic numbers in the table above are the p-values. c) *** stands for p-value < 0.01; ** stands for p-value between 0.01 & 0.05; * stands for p-value between 0.05 & 0.1.
26
![Page 28: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/28.jpg)
Model (3) and (4) in Table III are further developed from model (1) to see how
spillover effects occur through the labors employed by the FDI and HKMT firms in the
secondary and the non-secondary sector. Basing on the regression results of model (3) as
well as the related (t-1) model, the coefficients of the ratio of labors hired by the FDI firms
within the secondary sector to the total employment number of the secondary sector are
positive and statistically significant at the 1% level, showing that when there is a 1%
increase in this ratio, the GDP of the secondary sector will increase by 0.04%. On the other
hand, model (3) also shows that there are no statistical relation between the growth of GDP
in secondary sector and the change of the ratio of labors hired by HKMT firms within the
secondary sector to the total employment number of the secondary sector, since the
coefficients of this ratio are insignificant in both model (3) and its (t-1) model. The
empirical results above reveal that, within the secondary sector, the spillover effects to the
domestic economic growth will transmit through the labors hired by the FDI firms but not
through those who are hired by HKMT firms. And thus, it implies that the productivities of
the labors employed by the FDI firms in the 2nd sector are averagely higher; thence, when
more and more labors work in the FDI firms, with the total labor number of the 2nd sector
unchanged, more and more labors may have a better knowledge and productivity and
contribute more to the 2nd sector’s GDP growth. A reason behind may be the high standard
and technology productions of the FDI firms, but not HKMT ones, in the industry sector
that can spill the technical skills and the knowledge to the domestic labors and this reason is
further confirmed in model (5), which will be discussed later.
According to model (4) and its (t-1) model in Table III, there is a 99% confidence
level to claim that when the ratio of labors employed by HKMT firms within the non-2nd 27
![Page 29: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/29.jpg)
sector to the total employment number of the non-secondary sector goes up 1%, it will lead
to a 0.08% increase of the non-secondary GDP. However, in the non-2nd sector, as the
coefficients of the ratio of labors hired by the FDI firms to the total employment number
are insignificant in model (4) as well as the (t-1) model, there are no statistical relations
between this ratio and the GDP growth of the non-2nd sector. It discloses that, in the non-
secondary sector, which is mainly composed by 3rd sector6, the workers hired by HKMT
firms have a higher contribution to the GDP growth of the related sectors, comparing with
the ones hired by the FDI firms; and there are some possible reasons to explain. Closer
Economic Partnership Arrangement (CEPA) involving Hong Kong and Macau may be one
of the reasons as it liberates various high value-added 3rd sectors, such as banking sector,
insurance service sector and security markets, to the companies from Hong Kong and
Macau. The labors of HKMT firms can work in the higher economic output fields, which
also require higher human capitals, than the ones work in FDI firms by assuming that
higher value added sectors need higher human capitals, and consequently, the workers in
HKMT firms of non-2nd sector will conduct a stronger spillover effect to the domestic
economic growth. Culture may also be another reason to explain. Since the 3rd sector is
majorly composed by the service sector, unlike the industry and construction sector in 2nd
sector, it is much more ‘human’ and hence, with the same service quality, the culture of a
company is relatively important. By assuming that HKMT firms will have a more similar
cultural background with Chinese consumers; one can claim that HKMT firms will be more
6 The size and the economic output value from the 3rd sector are much bigger than the 1st sector. For instance, China 3rd sector’s GDP was around 4.6 times higher than the 1st sector one in 2013.
28
![Page 30: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/30.jpg)
popular than the FDI firms in the service sector7; in another words, the labors in these
HKMT firms can adapt to the Chinese service market environment better and thus, there
can be greater spillover effects regarding the knowledge and the skills, such as selling skills,
which can generate higher outputs. And when these workers go to domestic firms, the skills
they learnt could then spill to the domestic firms.8
Table IV – Estimation of GDP growth of industry sector and construction sector effects by changes of
(LIndustry,F / LIndustry), (LIndustry,HKMT / LIndustry) as well as (LConstruction,F / LConstruction) and (LConstruction,HKMT / LConstruction).
a) Models with (t-1) mean that the independent variables are lagged for 1 year for robustness checking. b) The italic numbers in the table above are the p-values. c) *** stands for p-value < 0.01; ** stands for p-value between 0.01 & 0.05; * stands for p-value between 0.05 & 0.1.
7 This assumes that the service qualities of the FDI firms and HKMT firms are the same.
8 This is because the service qualities of the FDI and HKMT firms are generally better than the local ones.
29
![Page 31: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/31.jpg)
Model (5) and (6) are built up from model (3) to see and compare the spillover
effects through the labors hired by the FDI firms and HKMT firms in 2 sectors of the 2nd
sector, namely the industry sector and the construction sector.
From the regression results of model (5) in Table IV above, the estimated
coefficient of the ratio of labors employed by FDI firms in the industry sector to the total
labor employment number in the industry sector is positive and significant at the 10% level,
which means that, in China’s Eastern coastal and central areas, every 1% increase of this
ratio, it will lead to a 0.08% growth of the industry’s GDP. Yet, this finding, indeed, is
relatively feeble comparing with other findings in this paper as the coefficient of above
ratio in its (t-1) function is insignificant statistically; more works have to be done to solidify
this finding. On the other hand, significant and robust relation does not exist in the labors
employed by HKMT firms according to the results above. In both model (5) and its (t-1)
model, the results shows that there are no relations found between the GDP growth of the
industry sector and the change of the ratio of the industrial labors hired by HKMT firms to
the total industrial employment number as both coefficients in these 2 models are
insignificant.
The aim of setting model (6) is to find out the relations between the GDP growth of
the construction sector and the ratios of the workers in construction sector employed by
FDI firms as well as HKMT firms to the total employment number of the construction
sector. However, as the coefficients of both ratios are statistical insignificant in model (6)
as well as in its (t-1) model. It denotes that no matter how the portion of workers in
construction sector employed by the FDI firms or by HKMT firms among the total
30
![Page 32: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/32.jpg)
construction sector employment changes, the GDP growth rate of the construction sector
will not be affected. This may be explained by construction sector’s situation. As in the
construction sector, it is common to see that the large infrastructure projects are indeed
launched by the state; therefore, the contracts are usually got by the domestic firms. As a
result, the numbers of labors hired by the FDI firms as well as HKMT firms are small, i.e.
the ratios of them to the total employment in construction sector are generally below 5%
from 2002 to 2011. Thus, even if there are spillover effects through these labors, the effects
might not be statistically significant.
As illustrated previously in model (3) of Table II, if there is a 1% increase of the
ratio of labors hired by the FDI firms in the 2nd sector to the total employment of the 2nd
sector, it will lead to a 0.04% increase of the GDP of 2nd sector. One possible reason behind
is that the FDI firms in industry sector are using relatively higher technologies and/or
having higher productivities and the labors working there should have absorbed the skills
and technical know-hows. As a result, when this kind of labors’ portion becomes relatively
bigger in the society, it will lead to a higher economic growth and their knowledge will also
spill to the domestic firms someday later. And this reason is now solidified by the results of
model (5) and (6). Increasing the number of labors employed by the FDI firms in the
industry sector with total employment number of the industry sector unchanged does have a
positive relation with the GDP growth of industry sector. As a major part of GDP growth of
the 2nd sector is in fact coming from the GDP growth of the industry sector9; therefore, one
9 From 2012 to 2013, 2011 to 2012 and 2010 to 2011, the increases of the GDP of the industry sector accounted for 76%, 76% and 84% of the GDP growth of the 2nd sector, while the rest of 24%, 24% and 16% of the GDP growths of the 2nd sector are contributed by the construction sector respectively.
31
![Page 33: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/33.jpg)
of the sources for the spillover effects to carry out through the labors hired by FDI firms in
2nd sector to the domestic economic growth is probably from the spillover effects through
labors hired by the FDI firms in the industry sector but not in the construction sector; yet, to
further ensure this statement, new models as follow should be set and tested:
InGDP2nd Sector,p,t = C + β1InL2nd Sector,p,t + β2InK2nd Sector,p,t
+ β3In(LIndustry,F,p,t / LIndustry,p,t) + β4In(LIndustry,HKMT,p,t / LIndustry,p,t) + ε
and
InGDP2nd Sector,p,t = C + β1InL2nd Sector,p,t + β2InK2nd Sector,p,t
+ β3In(LConstruction,F,p,t / LConstruction,p,t) + β4In(LConstruction,HKMT,p,t / LConstruction,p,t) + ε
Table V – Estimation of GDP growth of industry sector effect by changes of (TEVIndustry / TPVIndustry),
(TEVIndustry,F / TPVIndustry,F), (TEVIndustry,HKMT / TPVIndustry,HKMT) and (TEVIndustry,D / TPVIndustry,D).
a) Models with (t-1) mean that the independent variables are lagged for 1 year for robustness checking. b) The italic numbers in the table above are the p-values. c) *** stands for p-value < 0.01; ** stands for p-value between 0.01 & 0.05; * stands for p-value between 0.05 & 0.1.
32
![Page 34: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/34.jpg)
Unlike previous models, model (7) aims at figuring out the relation between the
GDP growth of the industry sector and the ratio of the total industrial export value to the
total production value in order to see whether there will be export-led growth10 in China’s
Eastern coastal and central areas’ industry sectors. From the results of model (7) in Table V,
the estimated coefficient of the total industrial export value to the total industrial production
value is positive and significant at the 1% level. It reveals that when this ratio goes up by
1%, the GDP growth of the industry sector will increase 0.09% and this finding is also
robust in the (t-1) model. Besides L and K, the growth of export to production ratio of the
industry sector can also drive the GDP growth of the industry sector positively; it denotes
that with the total industrial production value unchanged, one can increase the economic
growth of the industry sector by increasing the export value of the industrial goods.
According to Grossman and Helpman (1991), trade can promote technology diffusion and
knowledge spillover and hence lead to a faster productivity growth. Therefore, as China
exports more with the total production level unchanged, there should be a bigger spillover
effect from the trade to the domestic economic sector.
10 Indeed, to see the export-led growth of the whole country should use the model below:
InGDPp,t = C + β1InLp,t + β2InKp,t + β3In(TEVp,t / TPVp,t) + ε
but not only limited to the industry sector. Yet, the export sector is only composed of primary goods and
manufactured goods in China and the export from the industry sector accounts the majority part of the export
sector; i.e. in 2013, 2012 and 2011, manufactured goods’ export values account for 95%, 95% and 94% of
China’s total export values. The relations between the export-led growth of the whole society and the change
of the ratio of the total export value (which is mainly from the industry sector) to the total production value
may not be obvious as the spillover effects have to be strong enough to spill to the non-industry sector in a
short period of time. Since the models set in this paper are only the present year and the lagged one year (t-1),
this paper focuses only on the industry sector’s export-led growth effect.
33
![Page 35: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/35.jpg)
Model (8) tries to find out whether the spillover effect found in model (7) is from
the FDI firms, HKMT investment firms or from the domestic firms. According to the
results in Table V, the coefficient of the ratio of industrial total export value of the domestic
firms to the industrial total production value of these local firms, unlike the ratios of the
FDI firms and HKMT firms, is the only robust finding and it is significant at the 1% level
in both model (8) and its (t-1) model. In fact, the findings above are not difficult to
understand. Comparing to the FDI and HKMT investment firms, domestic firms, without
doubt, are relatively less productive. As trade can increase the chances of technology
diffusions by letting the less advanced party to exposes to the more productive ones and to
learn from the latter, therefore, the spillover effect from the exports of industrial goods only
appears in the relatively backward Chinese domestic industrial firms according to the
regression results above.
34
![Page 36: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/36.jpg)
Table VI – Estimation of GDP growth of industry sector effect by changes of (TEVIndustry,F / TEVIndustry) and (TEVIndustry,HKMT / TEVIndustry).
a) Models with (t-1) mean that the independent variables are lagged for 1 year for robustness checking. b) The italic numbers in the table above are the p-values. c) *** stands for p-value < 0.01; ** stands for p-value between 0.01 & 0.05; * stands for p-value between 0.05 & 0.1.
Unlike Model (7) and (8), model (9) is used to see whether the shares of the
industrial total export value of the FDI firms as well as HKMT firms among the total
industrial export value will affect the growth rate of GDP of the industry sector. As the
estimated results indicate that the coefficients of both ratios of the FDI firms as well as
HKMT investment firms are statistical insignificant in both model (9) and the (t-1) model,
the changes of the export shares amount the FDI firms and HKMT investment firms do not
affect the industrial GDP growth rate. One of the reasons to explain the above findings is
35
![Page 37: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/37.jpg)
that there are basically no export quotas for many manufacturing goods in China after the
entering of WTO and thus, the export amount of the FDI firms and the export amount of
HKMT investment firms do not necessarily have relation and hence, the export amounts
solely depend on the firms’ decisions. As a result, only the changes of ratio of the export
value to the production value will matter and may affect the GDP growth, as model (7) and
(8) show, but not the relative export shares.
36
![Page 38: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/38.jpg)
6. Conclusion and Policy Implication
Using the panel data across China’s 14 provinces in the Eastern coastal and the
central regions from 2002 to 2011, this study tries to find out the evidences of the relations
between labors, capital stocks and the exports of the FDI firms as well as HKMT
investment firms and the domestic GDP growths in different sectors.
Basing on the pooled OLS regression results from above 9 models, it is obvious to
observe that the growth of the labor force and the growth of the fixed asset capital stock are
two important and essential factors to drive the positive growth of the GDP as they are two
basic components of the production function; therefore, it is not hard to understand that
basically all the coefficients of the lnL and lnK in above regression results are positive and
significant at the 1% level, except one of the InK in the construction sector. It indicates that
the growth of the fixed asset capital stock in that sector does not have statistical relation
with the growth of the GDP and in another words; the input increase of the capital will not
lead to output growth in the construction sector.
As for the spillover effects through the labors, the results indicate that, with the total
labor employment number unchanged, both increases of the labors hired by the FDI and
HKMT firms will lead to a positive growth of the GDP. Within the 2nd sector, only the
growth of the labors hired by the FDI firms to the total employment level will lead to a
positive rise of the 2nd sector’s GDP, but not the ones employed by HKMT firms. Whereas
the situation is totally different in the non-2nd sector, the results reveal that, instead of the
FDI firms, the portion of the labors hired by HKMT investment firms to the total
employment number in non-2nd sector has a positive relation with the GDP of that sector.
37
![Page 39: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/39.jpg)
To dig deeper in the 2nd sector, within the industry sector, only the ratio of the labors hired
by FDI firms to the total industrial employment number will positively drive the industry
sector’s GDP, but not the workers employed by HKMT firms. In the construction sector, no
spillover effects are observed from the labors hired by the FDI as well as HKMT firms.
As for the externalities from the capital stocks, when more capital stocks are
invested by the FDI firms, but not HKMT firms, with the total amount of the stocks the
same, it will lead to a positive GDP growth.
Last but not least, this paper also finds that export-led growth does exist in China’s
industry sector as the total export to total production value goes up, the related GDP will
also be driven up positively. Moreover, this situation will only appear in the domestic firms
but not the FDI firms nor HKMT firms. In addition, no statistical relations has found
between the ratios of the industrial export values of FDI firms as well as HKMT firms to
the total export value and the GDP growth of the industry sector; and this indicates that
there will be no crowding out effects between which parties export more.
Basing on the empirical results of the current study, there are some policy directions
towards the government policies of the Eastern coastal and the central regions of China.
Generally speaking, the government should welcome the investments from overseas
and HKMT as they can generate positive externalities to the domestic economic growth.
Comparing both kinds of the investments, FDI ones will have stronger spillover effects
than HKMT ones. And thus, once there are crowding out effects, government should limit
HKMT investments before limiting the FDI.
38
![Page 40: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/40.jpg)
To capture the spillover effects through the labors as much as possible, the
government ought to encourage the FDI firms from the 2nd sector, especially the industry
sector, to hire more domestic workers; on the other hand, to encourage HKMT firms from
non-2nd sector to employ more local workers as well. For instance, giving tax rebates to the
companies hiring certain amounts of the domestic labors.
Encouraging the industry sector to export more is another way to enjoy the spillover
effects. Be that as it may, this can only apply on the domestic firms. Besides liberating the
export duties as the government does now, it, for example, can assist the domestic firms to
build up connections with overseas buyers by holding more expos and internationalize
RMB to facilitate the trading and so on. Although the government should stimulate the
industrial export of the domestic firms, there is not necessary to put a cap or heavy tariffs
on the exports of the FDI firms as well as HKMT firms’ goods.
39
![Page 41: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/41.jpg)
References
Branstetter, L. (2006). Is foreign direct investment a channel of knowledge spillovers?
Evidence from Japan’s FDI in the United States. Journal of International
Economics, 68, 325-344.
Chen, C. (2011). Foreign direct investment in China: Location determinants, investor
behaviour and economic impact. Cheltenham: Edward Elgar.
Chen, Y. (2007). Impact of foreign direct investment on regional innovation capability: a
case of China. Journal of Data Science, 5, 577-596.
Cheung, K.Y., & Lin, P. (2004). Spillover effects of FDI on innovation in China: Evidence
from the provincial data. China Economic Review, 15, 25-44.
Findlay, R. (1978). Relative Backwardness, Direct Foreign Investment, and the Transfer of
Technology: A Simple Dynamic Model. Q. J. Econ, 92, 1–16.
Grossman, G. M., & Helpman, E. (1991). Trade, Knowledge Spillovers, and Growth.
European Economic Review, 35, 517-526. doi:10.1016/0014-2921(91)90153-A
Hanel, P. (2000). R&D, Interindustry and International Technology Spillovers and the
Total Factor Productivity Growth of Manufacturing Industries in Canada, 1974-–
1989. Economic Systems Research, 12(3), 345-361.
Holz, C. A. (2004). China's Statistical System in Transition: Challenges, Data Problems,
and Institutional Innovations. Review of Income and Wealth, 50(3), 381-409.
doi:10.1111/j.0034-6586.2004.00131.x
Jiang, D., & Xia, L. (2005). The empirical study of the function of FDI on innovation in
China’s high-tech industries. World Economy, 8, 3-11.
40
![Page 42: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/42.jpg)
Jong-Il, K., & J, L. L. (1994). The Sources of Economic Growth of the East Asian Newly
Industrialized Countries. Journal of The Japanese and International Economies,
235-271. doi:10.1006/jjie.1994.1013
Lee, G. (2006). The effectiveness of international knowledge spillover channels.European
Economic Review, 50(8), 2075–2088.
Lei, C. K., & Yao, S. (2009). Economic convergence in greater China: Mainland China,
Hong Kong, Macau and Taiwan (p. 165). London: Routledge.
Liu, Z. (2002). Foreign Direct Investment and Technology Spillover: Evidence from
China. Journal of Comparative Economics. doi:10.1006/jcec.2002.1789
Meng, L., & Wang, X. L. (2000). Assessment of the Reliability of China’s Economic
Growth Statistics, monograph, National Economic Research Institute, Beijing.
Perkins, D. (1988). Reforming China’s Economic System. Journal of Economic
Literature, 26, 601-645.
Qi, J.H., & Li, H. (2008). Spillover effect of FDI on China's knowledge creation.Chinese
Management Studies, 2(2), 86-96.
Rhee, J. W., & Belot, T. (1989). Export Catalysts in Low-Income Countries. Working
Paper, World Bank.
Smarzynska, B. K. (2002). Spillovers from Foreign Direct Investment through Backward
Linkages: Does Technology Gap Matter? The World Bank working paper.
Tiwari, A. K., & Mutascu, M. (2011). Economic Growth and FDI in Asia: A Panel-Data
Approach. Economic Analysis and Policy, 41(2), 173–187.
Todo, Y. (2006). Knowledge spillovers from foreign direct investment in R&D: Evidence
from Japanese firm-level data. Journal of Asian Economics, 17, 996-1013.
41
![Page 43: EXTERNALITIES OF FDI: EVIDENCE BY CHAN YUEN TUNG A …lib-sca.hkbu.edu.hk/trsimage/hp/12006866.pdf · externalities of fdi: evidence from china’s eastern coastal and central provinces](https://reader034.vdocument.in/reader034/viewer/2022050716/5e166debfe649673e62fc3e0/html5/thumbnails/43.jpg)
Wang, H., Li, D., & Feng, J. (2006). Does FDI facilitate or dampen indigenous R&D?
Economic Study, 2, 44-55.
Wang, Y., & Yao, Y. (2001). Sources of China's economic growth, 1952-99 :
incorporating human capital accumulation. China Economic Review, 14, 32-52.
Woo, W. T. (1998). Chinese Economic Growth: Sources and Prospects. The Chinese
Economy, edited by M. Fouquin and F. Lemoine, Economica Ltd, Paris.
Xian, G., & Yan, B. (2005). The spillover effect of FDI on Cabhina’s innovation
capacity.World Economy, 10, 18-25.
42