The Dragon Is Flying West:
Micro-level Evidence of Chinese
Outward Direct Investment
∗
WENJIE CHEN AND HEIWAI TANG
Outward direct investment (ODI) from the People’s Republic of China (PRC) es
surging. A common perception is that it was driven by the country’s resource-
seeking and technology-seeking motives. Using a new, unique, and comprehen-
sive dataset that covers close to 10,000 Chinese ODI deals from 1998 a 2009,
we find that in contrast to the common perception, over half of the ODI deals
are in service sectors, with many of them appearing to be export-related. En
addition to documenting the pattern and trend of the PRC’s ODI, we empirically
examine both the determinants and effects of ODI at the firm level. encontramos que
ex ante larger, more productive, and more export-intensive firms are more likely
to start investing abroad. Using matching estimation techniques, we find that
ODI is associated with better firm performance, including higher total factor
productivity, employment, and export intensity, and greater product innovation.
To assess the relative contributions of technology transfer, export promotion, y
resource seeking to the positive effects of ODI, we use ODI data merged with
customs transaction-level trade data. We find that firms’ ODI participation is
associated with significantly better trade performance, measured by export and
import volumes, export and import unit values, and number of export destina-
ciones. Contrary to perceived technology-seeking and resource-seeking motives,
we find no evidence that ODI firms import more capital or intermediate inputs
compared to non-ODI firms.
Palabras clave: foreign direct investment, trade facilitation, resource seeking, Peo-
ple’s Republic of China
JEL codes: F1, F2
I. Introducción
The People’s Republic of China (PRC) is the world’s fifth largest source of
foreign direct investment in 2010 (in terms of flow), after the US, Francia, Alemania,
∗Wenjie Chen (chenw@gwu.edu): Assistant Professor, Universidad George Washington, School of Business and Elliott
School of International Affairs. Heiwai Tang (hwtang@jhu.edu): Assistant Professor, Universidad Johns Hopkins,
School of Advanced International Studies and CESIfo. The authors thank the editor, two anonymous referees, y
all participants at the Asian Development Bank Conference for valuable comments. Chen would like to thank the
Institute for International Economic Policy for financial support. Shan Li provided excellent research assistance.
Asian Development Review, volumen. 31, No. 2, páginas. 109–140
C(cid:3) 2014 Asian Development Bank
and Asian Development Bank Institute
yo
D
oh
w
norte
oh
a
d
mi
d
F
r
oh
metro
h
t
t
pag
:
/
/
d
i
r
mi
C
t
.
metro
i
t
.
/
mi
d
tu
a
d
mi
v
/
a
r
t
i
C
mi
–
pag
d
yo
F
/
/
/
/
3
1
2
1
0
9
1
6
4
2
0
2
7
a
d
mi
v
_
a
_
0
0
0
3
2
pag
d
.
/
F
b
y
gramo
tu
mi
s
t
t
oh
norte
0
7
S
mi
pag
mi
metro
b
mi
r
2
0
2
3
110 ASIAN DEVELOPMENT REVIEW
and Japan.1 He et al. (2012) predict that the PRC’s cumulative outward direct
investment (ODI) would probably exceed $5 trillion in 2020, increasing from a mere $3 billion in 2010. Given the PRC’s sheer size, the volume of its ODI may
be expected; but considering its relatively early stage of economic development, es
recent surge in ODI is surprising to many. While it is still a fairly new phenomenon,
reports about Chinese ODI often hit news headlines, such as Lenovo’s acquisition
of IBM PC units, CNOOC’s rejected acquisition of Unocal, Huawei’s investment
in 3Leaf System, and Dalian Wanda Group’s acquisition of AMC Theaters. El
target sectors are widespread, and even as mundane a product as pork has attracted
tremendous media attention recently due to Shuanghui’s acquisition of Smithfield.
Tensions in developed countries towards Chinese ODI are rising, similar to the 1980s
when Japanese firms were making high-profile acquisitions.
Despite the rising concerns, existing studies about Chinese ODI are either
descriptive in nature or based on aggregate data. Among the recent studies that
use micro data, the focus has been on understanding the motives of ODI, con el
primary goal to verify the media hype about the PRC’s attempt to control natural
resources and technology around the world.2 Little research has been done about
which firms are engaged in ODI and how ODI may enhance their performance.
This paper has two goals. It first documents several stylized facts about
Chinese ODI. A point of departure from all existing studies is that we document
our facts based on the most comprehensive micro-level data on Chinese ODI. El
conjunto de datos, which was made available by the PRC’s Ministry of Commerce, covers close
a 10,000 ODI deals of over 7,000 firms in all sectors over the period of 1998–2009.
Consistent with the existing literature, we find that the motives of Chinese ODI can
be broadly categorized into three types—resource seeking, technology seeking, y
market seeking (export promotion). In contrast with the common perception, ambos
the aggregate statistics and our micro data lend no support for the popular speculation
that the recent rise of Chinese ODI is driven by resource seeking. En cambio, we find
that business services and wholesale/retail trade have accounted for a large and
increasing share of Chinese ODI in terms of the number of deals as well as the
volume of flows. The presence of private firms in Chinese ODI is also increasing.
Half of the top 20 destinations of its ODI are in Asia.
The second goal of the paper is to analyze the firm-level determinants and
effects of ODI, which have implications for other emerging countries. To obtain a
long list of firm performance measures, we rely on manufacturing firms’ survey data
from the PRC’s National Bureau of Statistics, which we merge with the ODI firm list.3
1UNCTAD (http://unctadstat.unctad.org/ReportFolders/reportFolders.aspx). The PRC’s ODI flow rank is 17th
en 2006, 12th in 2008, 5th in 2009, and 11th in 2011.
2Ver, Por ejemplo, Cheng and Ma (2007) and Huang and Wang (2013).
3Given that a large fraction of the ODI firms in the PRC are non-manufacturing, the drawback of using
manufacturing survey is that all ODI firms in the service sectors are dropped in our analysis. Notice that a firm can be
yo
D
oh
w
norte
oh
a
d
mi
d
F
r
oh
metro
h
t
t
pag
:
/
/
d
i
r
mi
C
t
.
metro
i
t
.
/
mi
d
tu
a
d
mi
v
/
a
r
t
i
C
mi
–
pag
d
yo
F
/
/
/
/
3
1
2
1
0
9
1
6
4
2
0
2
7
a
d
mi
v
_
a
_
0
0
0
3
2
pag
d
/
.
F
b
y
gramo
tu
mi
s
t
t
oh
norte
0
7
S
mi
pag
mi
metro
b
mi
r
2
0
2
3
THE DRAGON IS FLYING WEST 111
By estimating a probit model of ODI participation, we find that more productive
(measured by total factor productivity), más grande (measured by employment), y
more export-intensive firms are more likely to invest abroad. These findings lend
support to the studies that typically assume higher fixed costs of horizontal foreign
direct investment (FDI) compared to that of exporting. We also find that relative
to domestic private firms, state-owned enterprises (SOEs) are more likely to invest
abroad, consistent with the conventional view that the PRC’s government is behind a
lot of the country’s ODI flows. A diferencia de, foreign firms are less likely to undertake
ODI.
We then apply the propensity-score matching techniques commonly used in
the program evaluation literature to assess the average treatment effects of ODI on
the treated firms’ performance. We find that ODI has a positive effect on a wide range
of firms’ performance measures including value added, employment, productivity,
export intensity, R&D intensity, and the propensity to innovate new products.
Since the positive effects of ODI on firm performance can be due to tech-
nology transfer, resource seeking, or export promotion, we use customs transaction-
level trade data merged with our ODI list to shed light on the relative contributions
of the three channels. By employing propensity-score matching techniques again
to establish causality, we find that firms’ ODI participation is associated with a
significant improvement in their trade performance, measured by export and im-
port volumes, export and import unit values, and number of export destinations.
To the extent that unit value proxies for the quality of goods, these results imply
that ODI induces quality upgrading of both imports and exports. En otras palabras,
these results show that horizontal FDI from the PRC complements rather than
substitutes firms’ trade. These findings are consistent with the idea that export-
ing entails high fixed costs, such as marketing and information signaling, cual
can be reduced by ODI. Finalmente, we find no evidence based on the composition
of firms’ imports and exports that ODI is associated with technology or resource
seeking.
En resumen, our paper shows that export-promoting ODI from emerging
countries can potentially raise and sustain the benefits of exporting, which in turn
contribute to the countries’ structural transformation from low-skill manufactur-
ing to high-skill manufacturing, and eventually from manufacturing to high-skill
services. Our findings have important policy implications for countries beyond the
PRC, which have been experiencing rising labor costs after years of FDI and export-
promotion policies.
The paper proceeds as follows. Section II reviews the related literature.
Section III describes our three data sources. Section IV uses the new ODI data
classified as a service firm in the ODI list but can still be merged with the NBS data, as long as it has some businesses
in manufacturing.
yo
D
oh
w
norte
oh
a
d
mi
d
F
r
oh
metro
h
t
t
pag
:
/
/
d
i
r
mi
C
t
.
metro
i
t
.
/
mi
d
tu
a
d
mi
v
/
a
r
t
i
C
mi
–
pag
d
yo
F
/
/
/
/
3
1
2
1
0
9
1
6
4
2
0
2
7
a
d
mi
v
_
a
_
0
0
0
3
2
pag
d
/
.
F
b
y
gramo
tu
mi
s
t
t
oh
norte
0
7
S
mi
pag
mi
metro
b
mi
r
2
0
2
3
112 ASIAN DEVELOPMENT REVIEW
to describe overall patterns of ODI firms. Section V presents the characteristics of
ODI from the PRC. Section VI examines the determinants and the effects of ODI
at the firm level. Section VII focuses on the export-facilitation motive and exam-
ines how ODI is related to firms’ trade patterns and performance. The final section
concludes with some policy discussions.
II. Literature Review
Our paper is related to various strands of literature. Primero, it relates to the
classical theory of multinational enterprises (MNEs) about how firms use their
capabilities and resources to generate competitive advantage over indigenous firms
in host countries (Caves 1971, Hymer 1976, Kindleberger 1969 y 1970). Más
recent studies show that in addition to facilitating foreign sales, firms undertake ODI
to acquire resources, assets and technology to develop their competitive advantage
(Child and Rodrigues 2005, Makino et al. 2002, Mathews 2006).4
Segundo, our paper contributes to the growing literature on Chinese ODI.
Most of the earlier studies were descriptive in nature, sometimes relying on case
estudios (p.ej., Deng 2003 y 2004, Wu and Chen 2001). Cai (1999) proposes that
Chinese firms invest overseas mainly to seek markets, natural resources, tecnología,
managerial skills, and financial capital.5 More recent studies focus on the empirical
examination of the determinants of Chinese ODI (p.ej., Buckley et al. 2007), but most
of these studies rely on aggregate data for analysis. There are a few notable exceptions
that use micro-level data. Por ejemplo, Luo et al. (2011) show empirically that ODI
by private Chinese firms had been prompted to exploit firm-specific advantages as
well as to tackle market imperfections due to the underdevelopment of the PRC’s
domestic institution. Other studies on Chinese overseas mergers and acquisitions
(METRO&Como) support the resource-seeking and technology-seeking motives (Antkiewicz
and Whalley 2007, Rui and Yip 2008). Using aggregate data, Cheng and Ma (2007)
and Cheung and Qian (2009) show that the PRC’s investment was motivated by
both market seeking and resource seeking. Sin embargo, they find no evidence that
its investment in Africa and other oil-producing countries account for the rise. En
addition, they find that the PRC’s international reserves and exports to developing
countries tended to complement ODI. Our findings based on firm-level data are
largely consistent with the macro patterns they document.
Based on detailed firm-level data from Zhejiang province, Huang and Wang
(2013) empirically identify export facilitation as the third motive, which is as im-
portant as the other two emphasized by earlier studies. Our paper finds supporting
4Aquí, technology is broadly defined to include production technology, management skills, and brand names.
5Deng (2004) identified two additional motives: strategic assets (p.ej., brands, marketing networks) y
diversification. The focus of our paper focuses on the nonfinancial type of ODI. Claramente, because the PRC was itself
a low-cost production base, cost minimization was not a major motivation of Chinese ODI.
yo
D
oh
w
norte
oh
a
d
mi
d
F
r
oh
metro
h
t
t
pag
:
/
/
d
i
r
mi
C
t
.
metro
i
t
.
/
mi
d
tu
a
d
mi
v
/
a
r
t
i
C
mi
–
pag
d
yo
F
/
/
/
/
3
1
2
1
0
9
1
6
4
2
0
2
7
a
d
mi
v
_
a
_
0
0
0
3
2
pag
d
.
/
F
b
y
gramo
tu
mi
s
t
t
oh
norte
0
7
S
mi
pag
mi
metro
b
mi
r
2
0
2
3
THE DRAGON IS FLYING WEST 113
evidence but is unique in two respects. We use a much more comprehensive micro
dataset from the PRC, which covers all industries and provinces. We merge our ODI
data with customs transaction-level data and manufacturing survey data so that we
can assess the effects of ODI on firm performance. En particular, we examine how
exporters and importers benefit from ODI.
Tercero, our paper contributes to the large literature on the relation between
FDI and trade. Besides the early theoretical literature (Krugman 1980, Helpman
1984), there is an extensive empirical literature on the relation between FDI and
comercio. Por un lado, there are studies showing substitution between FDI and
exports (Brainard 1997; Markusen and Venables 2000; and Helpman, Melitz, y
Yeaple 2004). The key idea is the proximity concentration trade-off (es decir., a trade-
off between transportation costs and firm level returns to scale). These models are
explicitly designed for horizontal FDI. Por otro lado, some studies show that
FDI and exports can be complements (Lipsey and Weiss 1981 y 1984; Yamawaki
1991, Clausing 2000). By using Japanese product-level data on foreign production
in the US and exports to the US, Blonigen (2001) finds both substitution and
complementarity effects of FDI on exports. Substitution is likely to be found for
final goods exports, while complementarity is likely to be found for intermediate
inputs and finished products. A more recent strand of literature studies the complex
interactions between ODI and exports by highlighting the export-platform type of
exports by multinational firms (Antr`as 2003; Grossman, Helpman, and Szeidl 2006;
Ekholm, Forslid, and Markusen 2007; Yeaple 2003; Conconi et al. 2013).6 Our paper
finds that FDI and trade are complements in the PRC.
III. Datos
We use data on ODI’s by Chinese companies provided by the Chinese Min-
istry of Commerce (MOFCOM). The dataset covers all ODI transactions that were
approved by the MOFCOM between January 1, 1998 and December 31, 2009. Para
each ODI deal, the dataset reports the name of the investing firm, the firm’s sec-
tor of business, the province of origin, and the recipient country of the ODI flow.
There is, sin embargo, no information on the amount of the deal or the name of the
target for M&Como. There are altogether 9,744 deals from 7,202 unique firms for the
12-year period (1998–2009) included in the dataset. Since all Chinese firms need to
be approved by MOFCOM for each cross-border deal, this data source is the most
official and comprehensive among all other firm-level sources that have been used.
To verify the representativeness of our data, we compare the number of deals in our
6By considering a dynamic model with uncertainty and learning, Conconi et al. (2013) show that ODI and
export are substitutes in the short run but can be complements in the long run.
yo
D
oh
w
norte
oh
a
d
mi
d
F
r
oh
metro
h
t
t
pag
:
/
/
d
i
r
mi
C
t
.
metro
i
t
.
/
mi
d
tu
a
d
mi
v
/
a
r
t
i
C
mi
–
pag
d
yo
F
/
/
/
/
3
1
2
1
0
9
1
6
4
2
0
2
7
a
d
mi
v
_
a
_
0
0
0
3
2
pag
d
.
/
F
b
y
gramo
tu
mi
s
t
t
oh
norte
0
7
S
mi
pag
mi
metro
b
mi
r
2
0
2
3
114 ASIAN DEVELOPMENT REVIEW
data with those studied by Huang and Wang (2013). Our dataset covers 90% del
deals from Zhejiang, the province they focus on over the same sample period.7
The second data source is the Annual Survey of Industrial Enterprises,
conducted by the PRC’s National Bureau of Statistics (NBS) over the period of
1998–2009. The survey includes all industrial firms that are either state owned or
non-state owned with sales above CNY5 million (alrededor $600,000 during the sam-
ple period). The survey covers all manufacturing, mining, and utilities sectors. El
number of firms covered in this data set ranges from around 150,000 en 1998 a
431,000 en 2007. The dataset contains information on ownership structure, tangible
assets, number of employees, research and development (R&D), advertising, valor
added, sales, new product sales, and exports. Readers are referred to Ma et al. (2014)
for a more detailed description.
The third data source is the transaction-level trade data from the PRC’s cus-
toms over the period of 2000–2006. This dataset contains information on values
(in US dollars), quantities, and prices of all import and export transactions between
the PRC and over 200 destination countries at the HS 6-digit level (encima 5,000
products).8 This level of disaggregation is the finest for empirical studies in inter-
national trade—i.e., transactions at the firm-product-country-month level. For each
trading firm, the dataset also provides information on ownership type (estado, privado,
foreign) and customs regime (processing and non-processing).9 Mainly based on
firm names, we merge the ODI data with the firm-level manufacturing data and the
transaction-level trade data, respectivamente. More details will be described below.
IV. Overall Patterns of ODI Firms
Before analyzing the three micro-level datasets, let us highlight an overlooked
pattern simply based on aggregate data. Using sector-level data on Chinese ODI
reported by MOFCOM for the period of 2006–2010, Cifra 1 reveals that the
“mining” sector used to account for about 40% of total Chinese ODI flows in 2006,
followed by “leasing and business services” which contributed about 21% del
total. Since then, the share of “mining” in ODI flows declined gradually, while that
of “leasing and business services” increased continuously until it became the most
7Liao and Tsui (2012) compare the aggregate ODI data from the PRC’s Ministry of Commerce (MOFCOM)
and the transaction-level data put together by the Heritage Foundation and show that the former dataset systematically
underreports the PRC’s ODI in mining. Their main explanation for the discrepancy is that MOFCOM did not track the
final destination of ODI that went through tax havens (p.ej., Hong Kong, Porcelana; Virgin Islands, etc.). While we verify
that the overall patterns and the regression results remain robust to the exclusion of tax havens—in particular Hong
kong, China—two more remarks are in order. Primero, their datasets begin in 2005, which make the comparison between
ours and theirs difficult. Segundo, it is not clear why the Heritage Foundation dataset provides a more comprehensive
coverage of the PRC’s ODI transactions compared to MOFCOM data. Selection could be an issue in the Heritage
Foundation data as well.
8Example of a product: 611241 – Women’s or girls’ swimwear of synthetic fiber, knitted, or crocheted.
9Readers are referred to Fernandes and Tang (2013) for details of this dataset.
yo
D
oh
w
norte
oh
a
d
mi
d
F
r
oh
metro
h
t
t
pag
:
/
/
d
i
r
mi
C
t
.
metro
i
t
.
/
mi
d
tu
a
d
mi
v
/
a
r
t
i
C
mi
–
pag
d
yo
F
/
/
/
/
3
1
2
1
0
9
1
6
4
2
0
2
7
a
d
mi
v
_
a
_
0
0
0
3
2
pag
d
.
/
F
b
y
gramo
tu
mi
s
t
t
oh
norte
0
7
S
mi
pag
mi
metro
b
mi
r
2
0
2
3
THE DRAGON IS FLYING WEST 115
Cifra 1. Share of ODI Flows (2006–2010)
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
Transport
Manufacturing
Minería
Leasing and
business services
Banking
Wholesale and
retail trade
yo
D
oh
w
norte
oh
a
d
mi
d
F
r
oh
metro
h
t
t
pag
:
/
/
d
i
r
mi
C
t
.
metro
i
t
.
/
mi
d
tu
a
d
mi
v
/
a
r
t
i
C
mi
–
pag
d
yo
F
/
/
/
/
3
1
2
1
0
9
1
6
4
2
0
2
7
a
d
mi
v
_
a
_
0
0
0
3
2
pag
d
/
.
F
b
y
gramo
tu
mi
s
t
t
oh
norte
0
7
S
mi
pag
mi
metro
b
mi
r
2
0
2
3
2006
2007
2008
2009
2010
Fuente: The PRC’s Ministry of Commerce.
prevalent sector in terms of Chinese ODI flows (44% of the total). Together with
“wholesale and retail trade,” these two broad sectors accounted for over half of the
aggregate volume of the PRC’s ODI in 2010, compared to 27% en 2006. Minería
and banking, por otro lado, accounted for only 8% y 13% of the PRC’s total
ODI flows in 2010, respectivamente. These findings, based on official statistics, do not
support the common perception that the rising ODI from the PRC is due to rising
financial outflows or resource seeking.10 Instead, these aggregate patterns and trends
suggest that the recent rise in Chinese ODI could be related to its continuous growth
in exports. Motivated by these aggregate patterns, we will verify how firms’ ODI
are related to their overall and export performance.
The aggregate patterns outlined above say nothing about which firms are
engaged in ODI, where they invest, and how ODI may enhance their performance.
In the rest of the paper, we will use our firm-level ODI data along with official
micro-level balance sheet and trade data to analyze the determinants and effects of
ODI. Our dataset contains 9,744 deals conducted by 7,202 unique companies that
were approved by the PRC’s MOFCOM between 1998 y 2009. Mesa 1 reports
10There are concerns that the MOFCOM dataset is not representative. We will discuss the quality of the data
and other related research in Section 3.
116 ASIAN DEVELOPMENT REVIEW
Mesa 1. ODI Deals Breakdown, by Year
Año
Frecuencia
Percent
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
Total
ODI = outward direct investment.
Fuente: The PRC’s Ministry of Commerce.
19
9
20
21
66
79
244
1,091
1,412
1,632
2,091
3,060
9,744
0.19
0.09
0.21
0.22
0.68
0.81
2.50
11.20
14.49
16.75
21.46
31.40
100.00
the distribution of the deals per year during our sample period of 1998–2009.11 As
esperado, the number of ODI deals increased significantly from 19 deals in 1998 a
3,060 deals in 2009. The increase is particularly sharp in 2005, when the number of
deals increased from 244 a 1,091 (over a 300% increase). Table A2 in the appendix
shows that most of the increase is due to the massive liberalization of ODI by
domestic private firms.12
Mesa 2 tabulates the distribution of Chinese ODI deals by host country in our
datos. Between 1998 y 2009, Hong Kong, China appears as the major recipient of
ODI from the PRC, accounting for close to 20% of total deals. One may argue that
it may not be the final destination of Chinese ODI, as there can be a lot of transit
or round-trip FDI. Primero, firms in the PRC may take advantage of the low tax regime
and more developed legal and financial institutions in Hong Kong, China to raise
funds. Segundo, many firms in the PRC may choose to set up subsidiaries and even
headquarters to channel capital to a third country or even back to the PRC. Ambos
transit and round-trip FDI through Hong Kong, China are well-known. A drawback
of our dataset is that we have no information to separate both types of ODI from
genuine ODI to Hong Kong, Porcelana. We will check the robustness of our main results
by excluding Hong Kong, China as the host country of ODI.
After Hong Kong, Porcelana, the US comes as the second most important recipient
of ODI, accounting for 9.4% of the total number of deals. Following the US are
11Cheng and Ma (2007) pointed out that the gap between official statistics and figures found in news reports
appears to be big. We therefore focus mostly on the distribution of ODI across sectors and countries, and their
associated impact, rather than the actual amount of ODI when reporting our summary statistics.
12According to Cheng and Ma (2007), the Ministry of Commerce along with the All-China Federation of
Industry and Commerce started a discussion on policy reforms that encourage private firms to go overseas. A draft
document surfaced in 2006, which called for stronger support for domestic private and foreign firms in the areas of
taxation, finance, insurance, and foreign exchange.
yo
D
oh
w
norte
oh
a
d
mi
d
F
r
oh
metro
h
t
t
pag
:
/
/
d
i
r
mi
C
t
.
metro
i
t
.
/
mi
d
tu
a
d
mi
v
/
a
r
t
i
C
mi
–
pag
d
yo
F
/
/
/
/
3
1
2
1
0
9
1
6
4
2
0
2
7
a
d
mi
v
_
a
_
0
0
0
3
2
pag
d
/
.
F
b
y
gramo
tu
mi
s
t
t
oh
norte
0
7
S
mi
pag
mi
metro
b
mi
r
2
0
2
3
THE DRAGON IS FLYING WEST 117
Mesa 2. Top 20 Destinations of the PRC’s ODI
Country
Frecuencia
Percent
Hong Kong, Porcelana
United States
Russian Federation
Viet Nam
United Arab Emirates
Japón
Korea, Rep.
Alemania
Lao PDR
Australia
Indonesia
Canada
Singapur
Tailandia
Nigeria
Reino Unido
India
Mongolia
Kazakhstan
Malasia
ODI = outward direct investment.
Fuente: The PRC’s Ministry of Commerce.
1,946
918
551
464
370
360
299
270
267
236
180
167
167
143
137
134
128
102
101
95
19.97
9.42
5.65
4.76
3.80
3.69
3.07
2.77
2.74
2.42
1.85
1.71
1.71
1.47
1.41
1.38
1.31
1.05
1.04
0.97
the Russian Federation and Viet Nam, respectivamente. Curiosamente, the United Arab
Emirates (UAE) is the fifth important recipient country. To the extent that UAE is
a major oil exporter, the high ranking of UAE as a major recipient of the PRC’s
ODI provides some support for the resource-seeking hypothesis (Antkiewicz and
Whalley 2007, Rui and Yip 2008). It is worth noting that out of the top 20 Chino
ODI destinations (in terms of the number of deals), 12 are in Asia. The prevalence
of Asian countries among the top hosts is consistent with the sectoral pattern that
horizontal ODI (leasing and business services, along with wholesale and retail trade)
accounts for the majority of ODI flows in recent years, rather than technology-
seeking or resource-seeking ODI as commonly speculated.
Mesa 3 shows the numbers of deals by regions (p.ej, Asian versus non-Asian,
OECD versus non-OECD, etcétera) in our sample. The average fraction of Chinese
firms investing in OECD countries across all years (1998–2009) es solo 30% (last
row). Among the non-OECD countries, Asian countries accounted for about 80%
(55.75/69.83). Después 2004, Asian countries consistently accounted for over 60% de
Chinese ODI deals, while OECD countries never accounted for more than 40%
de nuevo. Sub-Saharan Africa rarely accounted for more than 10% of the total Chinese
ODI deals over the sample period. Just by considering the number of deals across
host countries, the relatively small fractions of ODI to OECD countries and the
concentration of ODI in Asia lend little support to the hypothesis that technology
seeking or resource seeking are the main drivers of the recent rise of ODI from the
yo
D
oh
w
norte
oh
a
d
mi
d
F
r
oh
metro
h
t
t
pag
:
/
/
d
i
r
mi
C
t
.
metro
i
t
.
/
mi
d
tu
a
d
mi
v
/
a
r
t
i
C
mi
–
pag
d
yo
F
/
/
/
/
3
1
2
1
0
9
1
6
4
2
0
2
7
a
d
mi
v
_
a
_
0
0
0
3
2
pag
d
.
/
F
b
y
gramo
tu
mi
s
t
t
oh
norte
0
7
S
mi
pag
mi
metro
b
mi
r
2
0
2
3
118 ASIAN DEVELOPMENT REVIEW
Mesa 3. Fraction of ODI Deals, by Region and Year
Año
Non-OECD
OECD
Non-Asia
Asia
Non-SSA
SSA
Total (No.)
5
44
25
29
30
42
31
31
36
31
28
30
30.17
95
56
75
71
70
58
69
69
64
69
72
70
69.83
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
Average
ODI = outward direct investment, OECD = Organisation for Economic Co-operation and Development, SSA =
Sub-Saharan Africa.
Nota: Numbers are in % in the first eight columns, while they are in whole numbers in the last column.
Fuente: The PRC’s Ministry of Commerce ODI data (1998–2009).
19
9
20
21
66
79
244
1,091
1,411
1,632
2,091
3,058
9,741
95
78
85
100
88
91
90
93
94
91
92
91
90.69
79
11
55
71
42
39
59
62
63
62
65
61
55.75
21
89
45
29
58
61
41
38
37
38
35
39
44.25
5
22
15
0
12
9
10
7
6
9
8
9
9.31
PRC. We are aware of the fact that some of the resource-seeking deals, Por ejemplo
those in Sub-Saharan Africa, are much larger in monetary value than the export-
related deals in Asia. Sin embargo, the trends in shares shown in Figure 1 imply that the
relatively large resource-seeking deals are unlikely to overturn the conclusion based
on the number of deals.
Próximo, we turn to analyzing the distribution of ODI deals across industries.
Consistent with Figure 1 that shows shares in total flows, Mesa 4 shows that a
majority of the PRC’s ODI deals belong to the service sectors. En particular, based
on a sample pool of observations from all years, “business services” and “wholesale
trade” stand out as the top two sectors in which most ODI deals are found. Juntos,
they account for 5,235 deals and thus, over half of the country’s total. The third largest
ODI sector in terms of the number of deals is “building and civil engineering,” but
it accounts for only 3% of the total. The sectors that are often suspected as the main
drivers of the rise in the PRC’s ODI—“nonferrous metals mining and dressing,"
“nonmetal mineral products,” and “geologic prospecting”—together account for
less than 6% of the total, consistent with the continuous decline in the share of
mining in the country’s aggregate ODI flow depicted in Figure 1. One can argue that
some of the firms in the mining sector can invest in other industries abroad. Además,
mining-related ODI could induce other types of ODI, such as “waterway transport.”
Sin embargo, given that the “business services” and “wholesale trade” account for the
bulk of ODI deals, the required complementary effects of ODI from mining to other
sectors will need to be very large to support the hypothesis that the PRC’s ODI is
ultimately driven by resource seeking but not export promotion. En suma, over half
of the PRC’s ODI deals are in the service sectors. ODI in manufacturing, mining,
and high-tech sectors have not been rising as has been postulated by many.
yo
D
oh
w
norte
oh
a
d
mi
d
F
r
oh
metro
h
t
t
pag
:
/
/
d
i
r
mi
C
t
.
metro
i
t
.
/
mi
d
tu
a
d
mi
v
/
a
r
t
i
C
mi
–
pag
d
yo
F
/
/
/
/
3
1
2
1
0
9
1
6
4
2
0
2
7
a
d
mi
v
_
a
_
0
0
0
3
2
pag
d
/
.
F
b
y
gramo
tu
mi
s
t
t
oh
norte
0
7
S
mi
pag
mi
metro
b
mi
r
2
0
2
3
THE DRAGON IS FLYING WEST 119
Mesa 4. Industry Breakdown of ODI (Top 20 Solo)
Industria
Frecuencia
Business services
Wholesale trade
Building and civil engineering
Nonferrous metals mining and dressing
Nonmetal mineral products
Garments, shoes, and caps manufacturing
Forestry
Real estate
Electric equipment and machinery
R&D
Geologic prospecting
Other financial activities
Metal products
Retail trade
Transport equipment
Food production
Water way transport
Agriculture
Ordinary machinery
Software
ODI = outward direct investment.
Nota: Industry classification is based on ODI firms’ description of the main business scope.
Fuente: The PRC’s Ministry of Commerce OFDI data (1998–2009).
2,816
2,419
285
212
202
189
181
169
162
159
157
143
135
122
118
106
101
86
86
84
Percent
28.94
24.86
2.93
2.18
2.08
1.94
1.86
1.74
1.66
1.63
1.61
1.47
1.39
1.25
1.21
1.09
1.04
0.88
0.88
0.86
In Table A2 in the appendix, we also show the distribution of the origin of
ODI across provinces in the PRC. The origins tend to be concentrated in coastal
provinces (p.ej., Zhejiang, Jiangsu, Shandong, Guangdong, and Shanghai). Estos
findings are consistent with the common perception that the PRC’s engagement in
globalization started in coastal provinces and is still largely concentrated there.
V. Characteristics of ODI Firms
The ODI dataset does not contain balance sheet information. To study the
relationship between the causes and effects of ODI at the firm level, we merge
the ODI data with the PRC’s NBS manufacturing firm survey data. Since there is
no common firm identifier in the two datasets, the merging is done based on firm
names. The statistics of the merging is reported in Table A5 in the appendix. El
NBS data are available for the period of 1998–2009. De término medio, acerca de 35% del
ODI deals can be merged to a firm in the NBS data, with the success rate ranging
de 11% (en 1999) a 55% (en 2002).13 We present the list of challenges we face
when merging the two datasets in online appendixes.14 Besides the imperfect match,
13These success rates are in the same order of magnitude of merging the PRC’s customs data with NBS data
done by other scholars (p.ej., Mamá, Espiga, and Zhang 2014; Manova and Yu 2013).
14Appendixes A and B, available at http://www.hwtang.com/adb_appendix.html.
yo
D
oh
w
norte
oh
a
d
mi
d
F
r
oh
metro
h
t
t
pag
:
/
/
d
i
r
mi
C
t
.
metro
i
t
.
/
mi
d
tu
a
d
mi
v
/
a
r
t
i
C
mi
–
pag
d
yo
F
/
/
/
/
3
1
2
1
0
9
1
6
4
2
0
2
7
a
d
mi
v
_
a
_
0
0
0
3
2
pag
d
.
/
F
b
y
gramo
tu
mi
s
t
t
oh
norte
0
7
S
mi
pag
mi
metro
b
mi
r
2
0
2
3
120 ASIAN DEVELOPMENT REVIEW
Mesa 5. The t-test of Key Characteristics between ODI and non-ODI
ODI
non-ODI
Diff
Size
ln(Sales)
No. or s.e.
ln(Value Added)
No. or s.e.
ln(Employment)
No. or s.e.
Ownership Type
Foreign
No. or s.e.
HKG; TAP; and Macau, China invested firms
No. or s.e.
SOE
No. or s.e.
12.32
7464
11.081
3,323
6.339
7,561
0.119
10,418
0.112
7,566
0.04
7,566
10.006
2,345,223
8.587
1,705,234
4.726
2,711,011
0.034
7,696,402
0.099
2,744,253
0.12
2,744,253
2.314∗∗∗
(0.017)
2.494∗∗∗
(0.026)
1.613∗∗∗
(0.014)
0.085∗∗∗
(0.002)
0.013∗∗∗
(0.003)
–0.08∗∗∗
(0.004)
General Performance Measures
ln(Labor Productivity)
No. or s.e.
Export/Sales
No. or s.e.
Value Added/Sales
No. or s.e.
R&D/Sales (multiplied by 1,000)
No. or s.e.
Raw materials/Sales
No. or s.e.
∗∗∗ = p < 0.001, HKG = Hong Kong, China, ODI = outward direct investment, TAP = Taipei,China.
Note: Data on value added are only available from 1998–2007. Data on R&D are only available from 2002–2007.
Standard errors in parentheses.
Source: Authors’ computations using manufacturing survey data (1998–2009).
4.39
2,524,320
0.144
2,345,223
0.295
1,548,148
0.00501
899,075
0.616
1,171,453
1.035∗∗∗
(0.017)
0.249∗∗∗
(0.004)
–0.009∗∗∗
(0.002)
0.000∗∗∗
(0.00)
0.002
(0.003)
5.425
7,539
0.393
7,464
0.286
3,299
0.0211
3,241
0.618
3,384
l
D
o
w
n
o
a
d
e
d
f
r
o
m
h
t
t
p
:
/
/
d
i
r
e
c
t
.
m
i
t
.
/
e
d
u
a
d
e
v
/
a
r
t
i
c
e
-
p
d
l
f
/
/
/
/
3
1
2
1
0
9
1
6
4
2
0
2
7
a
d
e
v
_
a
_
0
0
0
3
2
p
d
.
/
another drawback of using the merged dataset is that all “services” firms will be
excluded from our sample.
Before dealing with selection and endogeneity issues, let us simply compare
the means of several key variables between firms that conduct ODI (after they
got at least one deal approved) and those that do not. Table 5 reports the results.
Compared to non-ODI firms, ODI firms are significantly larger (in terms of sales,
value added, or employment). Specifically, the log difference in sales, value added,
and employment between ODI and non-ODI firms are 2.3, 2.5, and 1.6, respectively.
Interestingly, proportionately more ODI firms are foreign firms, including
those that have investors from Hong Kong, China; Macau, China; and Taipei,China.
Against the common perception that a lot of the ODI deals are initiated by the
state, we find proportionately fewer ODI firms that are SOEs. It is possible that the
government does not need to invest in the ODI firms directly in order to influence
it. What they need to do is provide capital and other types of support to firms that
invest abroad.
f
b
y
g
u
e
s
t
t
o
n
0
7
S
e
p
e
m
b
e
r
2
0
2
3
THE DRAGON IS FLYING WEST 121
ODI firms are also on average more productive (in terms of labor productivity)
and more export-intensive. Specifically, the average export-to-sales ratio of ODI
firms is 0.25 higher than that of non-ODI firms. These findings are consistent
with the export-promotion motive of ODI firms, which we will further confirm
using transaction-level trade data below. ODI firms are also on average more R&D-
intensive (measured by the ratio of R&D expenses to total sales) and have a slightly
lower value-added/sales ratio. This finding is consistent with the theory of horizontal
FDI that firms may offshore the most downstream part of global supply chains (e.g.,
marketing) to foreign affiliates.
As Table 4 already showed, ODI deals are unevenly distributed across sectors.
Other unobserved factors may shape the revealed differences in observables between
ODI and non-ODI firms. Besides the simultaneity bias, there could be selection
bias behind the observed differences in the means reported in Table 5. Suppose
more productive firms choose to undertake ODI overseas, which would be the case
based on Helpman, Melitz, and Yeaple (2004) who emphasize higher fixed cost for
horizontal FDI than that for exporting, the observed superior performance among
ODI firms could be driven by selection. Without a feasible instrument in the dataset,
we will rely on matching techniques (i.e., Heckman et al. 1997 and subsequent
studies) to identify the effects of ODI on firm performance, relative to the control
group that shares similar ex ante characteristics.
Before introducing the matching estimation results, we estimate the following
linear specification, which fully controls for firm-specific, time-invariant determi-
nants of post-ODI performance:
Yit = [ fi + ft ] + β O D Iit + εit ,
(1)
where fi and ft stand for firm and year fixed effects, and εit is the regression
residual. Yit is the measure of firm performance, including (log) sales, (log) value
added, (log) employment, (log) total factor productivity (TFP), export to sales ratio,
value added to sales ratio, R&D to sales ratio, new output sales to total sales ratio,
and new product dummy, and material to sales ratio. Notice that any sector-level and
province-level effects are already absorbed by firm fixed effects.15 The ODI dummy
equals 1 in and after the year the firm reported positive ODI, 0 otherwise. By
including firm fixed effects, we are identifying the within-firm relationship between
ODI and firm performance. In addition to all non-ODI firms, in the control group, we
also include observations of ODI firms before their engagement in ODI. Thus, the
coefficients on the ODI dummy should be interpreted as the difference-in-difference
in the average outcomes between ODI and non-ODI firms.16
15In unreported results, we verify that a majority of firms in the sample are single-plant firms.
16The first difference is the difference from firms’ means (across the sample periods). The second difference
is the difference from the non-ODI firms’ demeaned average within each year.
l
D
o
w
n
o
a
d
e
d
f
r
o
m
h
t
t
p
:
/
/
d
i
r
e
c
t
.
m
i
t
.
/
e
d
u
a
d
e
v
/
a
r
t
i
c
e
-
p
d
l
f
/
/
/
/
3
1
2
1
0
9
1
6
4
2
0
2
7
a
d
e
v
_
a
_
0
0
0
3
2
p
d
/
.
f
b
y
g
u
e
s
t
t
o
n
0
7
S
e
p
e
m
b
e
r
2
0
2
3
122 ASIAN DEVELOPMENT REVIEW
Table 6. ODI Effects on Firm Performance (FE Regressions)
Dependent
Variable:
ODI
Firm FE
Year FE
R-squared
No. of obs.
Dependent
Variable:
ODI
ln(Sales)
0.047∗
(0.022)
Yes
Yes
0.883
2,419,825
ln(Value
Added)
0.071
(0.037)
Yes
Yes
0.851
1,719,528
VA/Sales
R&D/Sales
–0.005
(0.005)
Yes
Yes
0.628
1,706,349
0.001
(0.001)
Yes
Yes
0.702
857,519
ln(Emp)
0.118∗∗∗
(0.016)
Yes
Yes
0.904
2,400,966
ln(TFP)
–0.001
(0.033)
Yes
Yes
0.787
1,713,660
New Product
Sales Share
0.013∗
(0.006)
Yes
Yes
0.598
1,845,020
New Product
Dummy
0.034∗∗∗
(0.007)
Yes
Yes
0.484
2,445,197
Exp/Sales
0.019
(0.012)
Yes
Yes
0.8639
2,445,197
Materials/Sales
0.003
(0.005)
Yes
Yes
0.609
1,640,541
Firm FE
Year FE
R-squared
No. of obs.
∗ = p < 0.05, ∗∗ = p < 0.01, ∗∗∗ = p < 0.001, ODI = outward direct investment, FE = fixed effects.
Note: ODI = 1 for all firm-years when and after a firm reported overseas investment, 0 otherwise. The number
of observations fluctuates because data for some variables are not available in all years (e.g., R&D only for
2003–2005). Standard errors, clustered at the industry level (2-digit), are in brackets.
Source: Authors’ computations.
Table 6 reports the results. Standard errors are clustered at the 2-digit industry
level. Controlling for firm and year fixed effects, we find that engaging in ODI
increases firms’ employment and propensity to innovate new products. The effects
on sales and exports are also positive, but only marginally significant. We cannot find
supporting evidence for a positive effect on R&D activities or productivity. This is
inconsistent with the idea that ODI from emerging markets transfers technology from
their affiliates in advanced economies. Although we are still far from establishing any
causal relationship or tackling the selection bias, the regression results provide some
preliminary evidence that whenever a significant effect of ODI on firm performance
is identified, it is positive.
The next step is to implement the propensity-score matching methods to deal
with the selection bias, which potentially drives the results reported so far. To this
end, we will need to estimate propensity scores for each firm so that we can match
ODI with similar non-ODI firms. We estimate a probit model, using a dummy for
the firm’s first year of ODI as the dependent variable. Specifically, we estimate the
following specification:
Pr(ODIit ) = [ fs + f p] + Xit−1α + εit ,
(2)
where i, s, p, and t stand for the firm, industry (2-digit, 29 categories), province (30),
fs, and province
and year (12), respectively. Sector fixed effects (29 categories),
fixed effects (30 categories), f p, are always included to capture all regional (e.g.,
l
D
o
w
n
o
a
d
e
d
f
r
o
m
h
t
t
p
:
/
/
d
i
r
e
c
t
.
m
i
t
.
/
e
d
u
a
d
e
v
/
a
r
t
i
c
e
-
p
d
l
f
/
/
/
/
3
1
2
1
0
9
1
6
4
2
0
2
7
a
d
e
v
_
a
_
0
0
0
3
2
p
d
/
.
f
b
y
g
u
e
s
t
t
o
n
0
7
S
e
p
e
m
b
e
r
2
0
2
3
THE DRAGON IS FLYING WEST 123
ODI promotion policies) and sectoral unobserved determinants (e.g., comparative
advantage) of ODI participation.
O D Iit equals 1 if a firm starts engaging in ODI in year t, 0 otherwise. Notice
that an ODI firm will only appear once in the sample, and firms that never report
any ODI can appear multiple times in the sample. Xit−1 is a vector of (lagged) firm
characteristics that are suspected to affect a firm’s participation in ODI. Based on
previous models on FDI and exports (e.g., Helpman, Melitz, and Yeaple 2004), we
include firm TFP and employment as regressors.17 To capture the idea that exporters
may have stronger incentive to invest overseas to facilitate trade, we include the
ratio of exports to total sales. Specific to the institutional background of the PRC,
where foreign firms and SOEs have better financial access (e.g., Zhu 2012) and
even preferential policy treatments (Huang and Tang 2012), we include three firm
ownership type dummies to indicate SOEs, foreign-owned (both wholly-owned and
joint ventures) firms, and firms owned by investors from Hong Kong, China; Macau,
China; and Taipei,China (i.e., domestic private firms are the excluded firm group).
Moreover, to account for ODI that is driven by resource or technology seeking, we
include firm-level measures of material and capital intensities, respectively.
Table 7 reports the probit estimation results. Similar to our explanations for
the t-test and the regression results, we find that ex ante (lagged by one year) more
productive (measured by TFP) and larger (measured by employment) firms are more
likely to start investing in foreign markets. More export-intensive firms are also more
likely to undertake ODI.
We also find that compared to domestic private firms, SOEs are more likely
to undertake ODI, consistent with the conventional view that the PRC’s ODI has a
strong government backing. The first finding implies that the t-test results reported in
Table 5 are pure correlation and cannot be inferred as a rejection that SOEs are less
likely to invest abroad.18 Foreign firms and firms with major investors from Hong
Kong, China; Macau, China; and Taipei,China are less likely to invest in a third
market. These findings are consistent with the idea that foreign firms (e.g., Foxconn
which assembles all products for Apple) tend to outsource assembly and processing
tasks to the PRC and import the finished products back to the headquarters or export
them directly to a third market. If these are their incentives to conduct ODI, they
tend to initiate the investment directly from the headquarters, rather than doing
it through their processing plants in the PRC. Column 2 shows that the results
remain robust to using the same set of regressors lagged by two years instead of one
year.
17Since data on firms’ value added and thus TFP are only available for 1998–2007, the last two years of the
sample 2008–2009 are automatically dropped.
18During the sample period, the PRC’s central government embarked on an active privatization program (Zhu
2012). The fraction of SOEs in the total number of enterprises dropped significantly, which may explain the seemingly
contrasting results about SOEs’ likelihood to invest abroad between Tables 5 and 7.
l
D
o
w
n
o
a
d
e
d
f
r
o
m
h
t
t
p
:
/
/
d
i
r
e
c
t
.
m
i
t
.
/
e
d
u
a
d
e
v
/
a
r
t
i
c
e
-
p
d
l
f
/
/
/
/
3
1
2
1
0
9
1
6
4
2
0
2
7
a
d
e
v
_
a
_
0
0
0
3
2
p
d
.
/
f
b
y
g
u
e
s
t
t
o
n
0
7
S
e
p
e
m
b
e
r
2
0
2
3
124 ASIAN DEVELOPMENT REVIEW
Table 7. Participation in ODI Based on Manufacturing Firm
Characteristics (Probit)
Dependent Variable
ODI Dummy
Sample
ln(TFP)
ln(Employment)
Export intensity
Capital intensity
Material intensity
SOE
HKG; TAP; and Macau, China invested firms
Foreign
Industry FE
Province FE
1 year before ODI 2 years before ODI
0.270∗∗∗
(0.014)
0.114∗∗∗
(0.011)
0.424∗∗∗
(0.028)
0.409∗∗∗
(0.052)
0.691∗∗∗
(0.093)
0.0744∗∗
(0.027)
–0.0868∗∗
(0.033)
–0.105∗∗∗
(0.031)
Yes
Yes
0.255∗∗∗
(0.014)
0.106∗∗∗
(0.011)
0.368∗∗∗
(0.027)
0.354∗∗∗
(0.050)
0.616∗∗∗
(0.088)
0.0837∗∗
(0.026)
–0.0385
(0.032)
–0.0513
(0.030)
Yes
Yes
l
D
o
w
n
o
a
d
e
d
f
r
o
m
h
t
t
p
:
/
/
d
i
r
e
c
t
.
m
i
t
.
/
e
d
u
a
d
e
v
/
a
r
t
i
c
e
-
p
d
l
f
/
877,378
1,075,673
No. of obs.
∗ = p < 0.05, ∗∗ = p < 0.01, ∗∗∗ = p < 0.001, FE = fixed effects, HKG = Hong Kong,
China, ODI = outward direct
investment, TAP = Taipei,China, TFP = total factor
productivity, SOE = state-owned enterprises.
Note: The ODI dummy is equal to 1 for a firm in the year when it reports positive ODI, 0
for the same firm otherwise. ODI is equal to 0 for all observations of firms that never conducted
any ODI during the sample period. All independent variables are lagged by one year in
column 1, and by two years in column 2. Standard errors in parentheses.
Source: Authors’ computations, based on Manufacturing Firm Survey from the PRC’s
National Bureau of Statistics (NBS).
/
/
/
3
1
2
1
0
9
1
6
4
2
0
2
7
a
d
e
v
_
a
_
0
0
0
3
2
p
d
.
/
f
b
y
g
u
e
s
t
t
o
n
0
7
S
e
p
e
m
b
e
r
2
0
2
3
Before moving to the next section about the effects of ODI on firm and export
performance, a final remark is in order. All results from Tables 5 to 7 are robust to the
exclusion of firms that had ODI in Hong Kong, China. This eliminates the concern
that some of the documented patterns are an artifact of investment intermediation in
Hong Kong, China. In other words, our claim that a majority of ODI projects belong
to the service sectors is robust to excluding the main tax haven for the PRC’s ODI.
VI. The Effects of ODI on Firm Performance
We use the concept of the average treatment effect on the treated (ATET) to
gauge the effects of ODI on firm performance. To this end, we use the propensity-
score matching methods, proposed by Rosenbaum and Rubin (1983) and applied
by Heckman, Ichimura, and Todd (1997) in the program evaluation literature, to
THE DRAGON IS FLYING WEST 125
compare the post-ODI average outcomes of ODI firms with ex ante similar non-
ODI firms.19
We first obtain the propensity score from each firm by estimating the probit
model as specified in eq. (2). We then compute the average effect of ODI based on
Rosenbaum and Rubin (1983), in which the authors propose reweighting estimators
using propensity scores. Specifically, the estimator for the ATET is
ˆ(cid:4)ATE T = 1
n
n(cid:2)
i=1
⎡
⎣yi Fi −
(cid:5)
ˆP(Xi )
1− ˆP(Xi )
n
j=1
ˆP(X j )
1− ˆP( j)
⎤
yi (1 − Fi )
⎦ .
(3)
The first term is just the mean of the outcomes for the ODI firms (i.e., when F = 1).
The second term is the weighted average of the outcomes of the control units, i.e.,
firms that do not conduct ODI, where the weights have been normalized by dividing
each of them by the sum of all individual weights, so that they add up to one. A firm
that is more likely to conduct ODI receives a larger weight by virtue of reweighting
the propensity score with the probability of being a control unit. For instance, for a
firm with zero probability of treatment, the control unit gets a weight of 0 (before
normalization) because it is always observed as a control unit. In contrast, a control
unit with a probability of treatment of 0.9, for instance, gets its outcome divided
by 0.1 (before normalization) to reflect the fact that we observe only 1 in 10 of
such units as control units. Thus, control units with higher probabilities of treatment
receive more weight since they resemble the treated units more. Propensity score
reweighting has the advantage of avoiding the bandwidth selection problem, as well
as the need to decide what type of kernel to use or how many neighbors to select.
As with many two-step estimation procedures, using the simple formula for
the variance of the estimator is incorrect. We adjust the standard errors in the
second step by bootstrapping to account for measurement errors from the first stage
estimation.20 Table A7 in the appendix shows the balancing test results for the
matching. It clearly shows significant reductions in the differences in the average ex
ante characteristics between ODI and non-ODI firms after matching.
Table 8 reports the ATET estimation results, using the same set of dependent
variables from Table 6. In general, we find statistically more significant effects of
ODI on firm performance. For a firm that invests abroad (including the year of
investment), we find positive ATET of ODI on the firm’s value added (0.29 log
points), employment (0.42 log points), and TFP (0.16 log points). All these results
are statistically significant at the 0.1% level. Compared to the matched non-ODI
19Previous studies that have used the matching approach to search for causal effects of exporting on produc-
tivity include Girma, Greenaway, and Kneller (2003), Konings and Vandenbussche (2005), and De Loeker (2007),
among others.
20The implementation of the propensity score reweighting is closely based on the inverse probability regression
as proposed in Brunell and DiNardo (2004). We use the Stata routine treatrew following Cerulli (2012).
l
D
o
w
n
o
a
d
e
d
f
r
o
m
h
t
t
p
:
/
/
d
i
r
e
c
t
.
m
i
t
.
/
e
d
u
a
d
e
v
/
a
r
t
i
c
e
-
p
d
l
f
/
/
/
/
3
1
2
1
0
9
1
6
4
2
0
2
7
a
d
e
v
_
a
_
0
0
0
3
2
p
d
/
.
f
b
y
g
u
e
s
t
t
o
n
0
7
S
e
p
e
m
b
e
r
2
0
2
3
Dependent
Variable:
ATET
No. of obs.
Dependent
Variable:
ATET
126 ASIAN DEVELOPMENT REVIEW
Table 8. ODI Effects on Firm Performance (Based on Propensity-score Matching 1 Year
before ODI)
ln(Sales)
0.288∗∗∗
(0.026)
1,145,251
ln(Value
Added)
0.257∗∗∗
(0.036)
934,158
ln(Emp)
0.067∗∗∗
(0.016)
1,140,946
ln(TFP)
0.163∗∗∗
(0.027)
934,689
Export/Sales
0.021∗∗∗
(0.005)
1,148,377
VA/Sales
–0.008∗
(0.004)
929,661
R&D/Sales
0.002∗
(0.001)
553,322
New Output
Share
0.018∗∗
(0.007)
864,991
New Output
Dummy
0.028∗∗
(0.009)
1,148,377
Materials/Sales
0.005
(0.004)
899,973
No. of obs.
∗ = p < 0.05, ∗∗ = p < 0.01, ∗∗∗ = p < 0.001, ODI = outward direct investment, TFP = total factor productivity,
VA = value added, ATET = average treatment effect on the treated.
Note: ODI = 1 for all firm-years when and after a firm reported overseas investment. The number of observations
fluctuates because data for some variables are not available in all years (e.g., R&D only for 2003–2005).
Bootstrapped standard errors are in brackets.
Source: Authors’ computations.
firms, ODI firms derive on average a slightly larger share of their sales from exports
(a 0.02 log-point increase; significant at the 1% level). They also spend slightly
more on R&D (a 0.2% higher share in total sales; significant at the 5% level), create
new products, and derive a larger portion of sales from new products (significant
at the 1% level). All results remain robust to the exclusion of Hong Kong, China
as the host economy of ODI. These results are consistent with the hypotheses that
ODI transfers technology or complements sales abroad by decreasing fixed cost of
exporting. We will provide more evidence to disentangle these two channels in the
following section.
VII. The Effects of ODI on Firms’ Trade Performance
The positive effects of ODI on firm performance documented in the previous
section can be due to technology transfer or market expansion. For instance, the
finding that a firm tends to create more products after ODI can be induced by
new ideas or market expansion, which makes innovative activities profitable. In
this section, we focus on the market-seeking (export-promotion) motive of ODI
and examine how ODI affects a firm’s export performance, and through the export
channel enhances firm performance as documented above. Since the ODI dataset has
no information on exports and imports, we merge the ODI data with the customs
transaction-level trade data by firm names. Table A5 in the appendix shows the
fractions of firms in the ODI data that can be merged to the customs data. Notice
that the customs transaction-level data are only available for the year 2000–2006
(7 years).
l
D
o
w
n
o
a
d
e
d
f
r
o
m
h
t
t
p
:
/
/
d
i
r
e
c
t
.
m
i
t
.
/
e
d
u
a
d
e
v
/
a
r
t
i
c
e
-
p
d
l
f
/
/
/
/
3
1
2
1
0
9
1
6
4
2
0
2
7
a
d
e
v
_
a
_
0
0
0
3
2
p
d
.
/
f
b
y
g
u
e
s
t
t
o
n
0
7
S
e
p
e
m
b
e
r
2
0
2
3
THE DRAGON IS FLYING WEST 127
The match success rate is fairly high for the last two years of the customs
sample (2005–2006). Around 40% of the deals in our ODI dataset can be matched
with an observation in the customs trade dataset. Table A4.2 in the appendix shows
the distribution of the successfully matched observations across industries. The
industrial distribution of deals in the matched sample is very close to the ones in
the original ODI sample, providing some support that the matched observations are
systematically unbiased across sectors. The challenges that arise for this merging
are very similar to those encountered when we merge the ODI data with the customs
data.21
Similar to the analysis of the ODI effects on firms’ overall performance, we
apply the matching techniques outlined in Section 5 again to assess the ATET of
ODI on firms’ export performance. To implement the matching estimation exercise,
we need to first obtain the propensity score for each exporter (or importer), which
requires an estimation of the ODI participation equation using probit again. While
we try to include regressors as close as possible to those from manufacturing survey
data, customs trade data only include information related to firms’ trade and we are
restricted to use proxies. To proxy for TFP and firm size, we use the exporter’s total
export value (to the rest of the world). To proxy for material intensity (or reliance
on imported inputs), we include the exporter’s ratio of imports to exports. Similar to
Table 7, we include a set of ownership type dummies, with private firms being the
excluded group with no dummy included.
Consistent with Table 7, we find that larger (or more productive) exporting
firms are more likely to start investing abroad. Similarly, compared to domestic
private exporters, foreign exporters are less likely to undertake ODI. SOEs are also
less likely to conduct ODI, compared to domestic private exporters. This result
should not be taken as a rejection of the earlier finding that SOEs are more likely
to invest abroad, as here we focus on a subset of firms—only those that export.
Finally, in column 2, we show that the results remain robust to using the same set of
regressors lagged by two years instead of one year.
Next we use the propensity scores estimated from Table 9 to assess the ATET
of ODI on firms export performance. The dependent variables include ODI firm’s
export volume, export unit value, number of products (HS6) exported, and number
of foreign countries served. All these variables are in log. We also conduct the same
regression analysis by using the same four measures but for imports. By matching
ODI exporters with non-ODI exporters based on ex ante characteristics, we aim to
tackle the bias due to firms’ selection into ODI.
Table 10 reports the matching estimation results. We find evidence that after
investing overseas, existing exporters’ total export volume (in US dollars), export
unit value, and number of destinations all increase. In particular, ODI exporters on
average export about 0.6 log points more than non-ODI. Their unit value of the
21See (online) Appendix A (http://www.hwtang.com/adb_appendix.html).
l
D
o
w
n
o
a
d
e
d
f
r
o
m
h
t
t
p
:
/
/
d
i
r
e
c
t
.
m
i
t
.
/
e
d
u
a
d
e
v
/
a
r
t
i
c
e
-
p
d
l
f
/
/
/
/
3
1
2
1
0
9
1
6
4
2
0
2
7
a
d
e
v
_
a
_
0
0
0
3
2
p
d
.
/
f
b
y
g
u
e
s
t
t
o
n
0
7
S
e
p
e
m
b
e
r
2
0
2
3
128 ASIAN DEVELOPMENT REVIEW
Table 9. Participation in ODI for Customs (Probit)
Dependent Variable
ODI Dummy
Sample
Export
SOE
Foreign
Collective
Import/Export
Industry FE
Province FE
1 year before ODI
0.114∗∗∗
(0.007)
–0.0801∗∗
(0.036)
–0.565∗∗∗
(0.035)
0.085∗
(0.047)
–0.075
(0.052)
Yes
Yes
2 years before ODI
0.121∗∗∗
(0.007)
–0.090∗∗
(0.040)
–0.574∗∗∗
(0.039)
0.123∗∗
(0.050)
–0.0764058
(0.057)
Yes
Yes
No. of obs.
366,566
∗ = p < 0.05, ∗∗ = p < 0.01, ∗∗∗ = p < 0.001, ODI = outward direct investment, SOE =
state-owned enterprises, FE = fixed effects.
Note: The ODI dummy is equal to 1 for a firm in the year when it reports positive ODI, 0
for the same firm otherwise. ODI is equal to 0 for all observations of firms that never
conducted any ODI during the sample period. Industry is an HS2 category. Domestic
private firms are the excluded ownership type. Standard errors in parentheses.
Source: Authors’ computations, based on the PRC’s customs transaction-level trade data.
289,344
Table 10. Export Performance (Based on Propensity-score Matching 1 Year before ODI)
Sample
All firms (ODI = 0 for non-ODI firms and observations before ODI)
Dependent Variable:
ATET
No. of obs.
Dependent Variable:
ATET
Exp Value
0.586∗∗∗
(0.058)
314,240
Exp Unit Val
0.396∗∗∗
(0.075)
314,240
No. of HS6 Exp
0.031
(0.051)
316,011
No. of Exp Countries
0.239∗∗∗
(0.047)
316,011
Imp Value
0.363∗∗∗
(0.084)
307,119
Imp Unit Val
0.286∗∗∗
(0.010)
307,119
No. of HS6 Imp
–0.070
(0.052)
307,119
No. of Exp Countries
0.057
(0.040)
310,766
No. of obs.
∗ = p < 0.05, ∗∗ = p < 0.01, ∗∗∗ = p < 0.001, ODI = outward direct investment, ATET = average treatment effect
on the treated.
Note: The ODI dummy is equal to 1 for a firm in the year when it reports positive ODI, 0 for the same firm
otherwise. ODI is equal to 0 for all observations of firms that never conducted any ODI during the sample
period. Bootstrapped standard errors reported in brackets.
Source: Authors’ computations, based on the PRC’s customs transaction-level trade data.
same product (a HS6 category) is 0.4 log points higher, while the number of export
destinations increases by 0.2 log points. To the extent that unit value proxies for
quality, we postulate that ODI can lead to quality upgrading, but higher unit values
can also arise from more effective marketing. In the presence of fixed exporting
costs, the increase in the number of export destinations after ODI suggests that
l
D
o
w
n
o
a
d
e
d
f
r
o
m
h
t
t
p
:
/
/
d
i
r
e
c
t
.
m
i
t
.
/
e
d
u
a
d
e
v
/
a
r
t
i
c
e
-
p
d
l
f
/
/
/
/
3
1
2
1
0
9
1
6
4
2
0
2
7
a
d
e
v
_
a
_
0
0
0
3
2
p
d
/
.
f
b
y
g
u
e
s
t
t
o
n
0
7
S
e
p
e
m
b
e
r
2
0
2
3
THE DRAGON IS FLYING WEST 129
ODI may be associated with an across-the-board reduction in those fixed costs.
Collectively, these results confirm our conjecture that ODI from the PRC has been
mostly related to export promotion. We find no effect in terms of the number of
exported products after ODI.
In the lower panel of Table 10, we repeat the same exercises but for importers.
We find that importers that invest abroad have higher import volumes and unit values
for a given product. These results show that ODI serves not only as a platform for
exports, but also for imports, an aspect of ODI that has not received its deserved
attention in the literature. However, there is no effect on import variety or the number
of source countries for imports.
While Table 10 shows very strong export promotion effects of ODI, we
still cannot rule out technology transfer or resource seeking as the source of the
positive effects. To this end, we rely on firms’ imports to provide indirect evidence.
If technology and resource seeking are important, we should expect ODI firms to
import more capital goods and intermediate inputs, compared to non-ODI firms.
To verify these speculations, we repeat the same estimation as in Table 10 but with
dependent variables replaced by the shares of capital goods and intermediate inputs
(materials) in firms’ exports and imports, respectively.
To classify a product (HS6) as capital good, raw material, and others, we
use the list from the United Nations Broad Economic Categories (UN BEC)
classification.22 If the increase in import volume documented in Table 10 is really
associated with technology transfer, we should observe an increase in the share of
capital goods in imports. The findings about the share of raw materials will then
inform us about whether the PRC’s ODI could be associated with resource seeking.
Table 11 reports the results. The first four columns report the results regarding
the share of capital and materials in firms’ imports, in terms of total value or the
total number of imported varieties. The last four columns report the results regarding
those shares in exports. We find no evidence for a higher import share or fraction
of capital goods in total imports by ODI firms. There is also no significant effect of
ODI on imports of material. Based on trade of tangible goods, we find no evidence
that Chinese ODI is technology seeking. However, it is worth noting that there can
still be transfer of intangible asset from foreign affiliates to the headquarters in the
PRC that are not observed in trade data, as pointed out by Atalay et al. (2014).
For completeness, we also examine the ODI effects on firms’ composition of
exports. Interestingly, as reported in the last four columns, we find a significantly
positive effect on firms’ capital export share, consistent with the export promotion
or quality upgrading effects reported in Table 10. However, there is no effect when
it is measured as a fraction of total export varieties. There is no evidence of an effect
on exports of materials.
22Available at http://unstats.un.org/unsd/cr/registry/regcst.asp?Cl=10. See also (online) Appendix B for de-
tails (http://www.hwtang.com/adb_appendix.html).
l
D
o
w
n
o
a
d
e
d
f
r
o
m
h
t
t
p
:
/
/
d
i
r
e
c
t
.
m
i
t
.
/
e
d
u
a
d
e
v
/
a
r
t
i
c
e
-
p
d
l
f
/
/
/
/
3
1
2
1
0
9
1
6
4
2
0
2
7
a
d
e
v
_
a
_
0
0
0
3
2
p
d
/
.
f
b
y
g
u
e
s
t
t
o
n
0
7
S
e
p
e
m
b
e
r
2
0
2
3
130 ASIAN DEVELOPMENT REVIEW
Table 11. Capital Goods and Raw Materials in Exports and Imports and ODI
Sample
Dep.
Variable
All Firms (ODI = 0 for non-ODI firms
and observations before ODI)
All Firms (ODI = 0 for non-ODI firms and
observations before ODI)
Share of
Capital Goods
Share of
Materials
Share of
Capital Goods
Share of
Materials
ATET
Firm
Import
Volume
0.014
(0.012)
301,043
Firm
Import
Volume
0.027
(0.015)
301,043
No. of
Imported
Goods
–0.004
(0.005)
301,043
No. of
No. of
Exported
Imported
Goods
Goods
0.001
–0.003
(0.003)
(0.005)
No. of obs.
309,817
301,043
∗ = p < 0.05, ∗∗ = p < 0.01, ∗∗∗ = p < 0.001, ODI = outward direct investment, ATET = average treatment effect
on the treated.
Note: The ODI dummy is equal to 1 for a firm in the year when it reports positive ODI, 0 for the same firm
otherwise. ODI is equal to 0 for all observations of firms that never conducted any ODI during the sample
period. Bootstrapped standard errors reported in brackets.
Source: Authors’ computations, based on the PRC’s customs transaction-level trade data.
Firm
Export
Volume
0.042∗∗∗
(0.013)
309,817
No. of
Exported
Goods
–0.003
(0.005)
309,817
Firm
Export
Volume
–0.009
(0.006)
309,817
l
D
o
w
n
o
a
d
e
d
f
r
o
m
h
t
t
p
:
/
/
d
i
r
e
c
t
.
m
i
t
.
/
e
d
u
a
d
e
v
/
a
r
t
i
c
e
-
p
d
l
f
/
/
/
/
3
1
2
1
0
9
1
6
4
2
0
2
7
a
d
e
v
_
a
_
0
0
0
3
2
p
d
.
/
f
b
y
g
u
e
s
t
t
o
n
0
7
S
e
p
e
m
b
e
r
2
0
2
3
VIII. Conclusion
Using a new panel dataset of Chinese multinational firms that covers close
to 10,000 deals from all provinces and industries from 1998 to 2009, we find that
over half of the ODI deals are in service sectors, with many of them appearing to be
related to export promotion. In addition to documenting the pattern and trend of the
PRC’s ODI firms, this paper empirically examines both the determinants and effects
of the PRC’s ODI at the firm level.
We find that ex ante larger, more productive, and more export-intensive firms
are more likely to start engaging in ODI. Using matching estimation techniques, we
find that ODI enhances firm performance in terms of TFP, export intensity, product
creation, and employment. To shed light on the relevant importance of technology
transfer and export promotion of ODI, we use customs transaction-level trade data
merged with the ODI firm list for analysis. We find that firms’ ODI participation is
associated with better performance in both exports (in terms of volume, unit value,
and number of destination countries) and imports (in terms of volume and unit
value). We find no evidence of technology upgrading and resource seeking based on
the pattern of imported products.
What lessons do we learn from the PRC about development strategies that are
applicable for other developing nations and emerging markets? One of the intriguing
findings in the literature about the PRC is its fast transition from processing exports,
which mostly originate from foreign-invested exporting firms, to non-processing
exports by indigenous Chinese firms. Our findings on the export promotion effects
of ODI in the PRC imply that ODI may have played an important role in driving this
transition.
THE DRAGON IS FLYING WEST 131
It has been shown that inward FDI into the PRC has transferred know-
how, technology, and management skills to the country. However, the benefits of
promoting exports and inward FDI are diminishing for the PRC, about 20 years
after the country’s economic integration with the rest of the world, initiated by
Deng’s famous southern trip in 1992. This phenomenon is not specific to the PRC
and has been or will be faced by many developing countries that lose comparative
advantage in labor-intensive sectors due to increasing labor costs. When the average
wage level of low-skilled workers continues to increase, a country will have to
transition to more skill-intensive and capital-intensive sectors. While this transition
can happen naturally (with some adjustment cost), there could be room for policies
to make the transition smoother. In Chen and Tang (2013), we find evidence of skills
upgrading and capital deepening through ODI, as revealed in the pattern of exported
products from the PRC’s exporters that engage in ODI. In summary, our paper shows
that export-promoting ODI can potentially raise and sustain the benefits of exporting,
which may in turn contribute to a country’s structural transformation from low-skill
manufacturing to high-skill manufacturing, and eventually from manufacturing to
high-skill services.
References
Antkiewicz, Agata and John Whalley. 2007. Recent Chinese Buyout Activity and the Implications
for Wider Global Investment Rules. Canadian Public Policy 33(2):207–26.
Antr`as, Pol. 2003. Firms, Contracts, and Trade Structure. Quarterly Journal of Economics 118
(4):1375–418.
Atalay, Enghin, Ali Hortac¸su, and Chad Syverson. 2014. Vertical Integration and Input Flows.
American Economic Review 104(4):1120–48.
Blonigen, Bruce. 2001. In Search of Substitution between Foreign Production and Exports. Journal
of International Economics 53(1):81–104.
Brainard, S. Lael. 1997. An Empirical Assessment of the Proximity-Concentration Trade-off
between Multinational Sales and Trade. American Economic Review 87(4): 520–44.
Brunell, Thomas, and John DiNardo. 2004. A Propensity Score Reweighting Approach to Esti-
mating the Partisan Effects of Full Turnout in American Presidential Elections. Political
Analysis 12(1):28–45.
Buckley, Peter, L. Jeremy Clegg, Adam Cross, Xin Liu, Hinrich Voss, and Ping Zheng. 2007.
The Determinants of Chinese Outward Foreign Direct Investment. Journal of International
Business Studies 38(4):499–518.
Cai, Kevin. 1999. Outward Foreign Direct Investment: A Novel Dimension of China’s Integration
into the Regional and Global Economy. China Quarterly 160: 856–80.
Caves, Richard. 1971. International Corporations: The Industrial Economics of Foreign Invest-
ment. Economica 38(149):1–27.
Cerulli, Giovanni. 2012. TREATREW: Stata Module to Estimate Average Treatment Effects by
Reweighting on Propensity Score. Boston College. Unpublished.
Chen, Wenjie, and Heiwai Tang. 2013. Export Promotion of ODI
from Emerging
Markets—Transaction-level Evidence from China. Johns Hopkins University. Unpublished.
l
D
o
w
n
o
a
d
e
d
f
r
o
m
h
t
t
p
:
/
/
d
i
r
e
c
t
.
m
i
t
.
/
e
d
u
a
d
e
v
/
a
r
t
i
c
e
-
p
d
l
f
/
/
/
/
3
1
2
1
0
9
1
6
4
2
0
2
7
a
d
e
v
_
a
_
0
0
0
3
2
p
d
.
/
f
b
y
g
u
e
s
t
t
o
n
0
7
S
e
p
e
m
b
e
r
2
0
2
3
132 ASIAN DEVELOPMENT REVIEW
Cheng, Leonard, and Zihui Ma. 2007. China’s Outward FDI: Past and Future. In China’s Growing
Role in World Trade, edited by Robert Feenstra and Shangjin Wei. Chicago: University of
Chicago Press.
Cheung, Yin-Wong, and Xinwang Qian. 2009. Empirics of China’s Outward Direct Investment.
Pacific Economic Review 14(3):312–41.
Child, John, and Suzana Rodrigues. 2005. The Internationalization of Chinese Firms: A Case for
Theoretical Extension? Management and Organization Review 1(3):381–410.
Clausing, Kimberly. 2000. Does Multinational Activity Displace Trade? Economic Inquiry
38(2):190–205.
Conconi, Paola, Andre Sapir, and Maurizio Zanardi. 2013. The Internationalization Process of
Firms: From Exports to FDI. CEPR Discussion Paper no. 9332. London, UK: Centre for
Economic Policy Research.
De Loecker, Jan. 2007. Do Exports Generate Higher Productivity? Evidence from Slovenia.
Journal of International Economics 73(1):69–98.
Deng, Ping. 2003. Foreign Direct Investment by Transnationals from Emerging Countries: The
Case of China. Journal of Leadership and Organizational Studies 10(2):113–24.
Deng, Ping. 2004. Outward Investment by Chinese MNCs: Motivations and Implications. Business
Horizons 47(3):8–16.
Ekholm, Karolina, Rikard Forslid, and James Markusen. 2007. Export-Platform Foreign Direct
Investment. Journal of the European Economic Association 5(4):776–795.
Fernandes, Ana, and Heiwai Tang. 2013. Scale, Scope, and Trade Dynamics of Export Processing
Plants. Johns Hopkins University. Unpublished.
Girma, Sourafel, David Greenaway, and Richard Kneller. 2003. Export Markets Exit and
Performance Dynamics: A Causality Analysis of Matched Firms. Economics Letters
80(2):181–187.
Grossman, Gene, Elhanan Helpman, and Adam Szeidl. 2006. Optimal Integration Strategies for
the Multinational Firm. Journal of International Economics 70(1):216–38.
He, Dong, Lillian Cheung, Wenlang Zhang, and Tommy Wu. 2012. How Would Capital Account
Liberalization Affect China’s Capital Flows and the Renminbi Real Exchange Rates? China
& World Economy 20(6):29–54.
Heckman, James, Hidehiko Ichimura, and Petra Todd. 1997. Matching as an Econometric Evalua-
tion Estimator: Evidence from Evaluating a Job Training Programme. Review of Economic
Studies 64(4):605–54.
Helpman, Elhanan. 1984. A Simple Theory of International Trade with Multinational Corpora-
tions. Journal of Political Economy 92(3):451–71.
Helpman, Elhanan, Marc Melitz, and Stephen Yeaple. 2004. Exports versus FDI with Heteroge-
neous Firms. American Economic Review 94(1):300–16.
Huang, Yasheng, and Heiwai Tang. 2012. FDI Policies in China and India: Evidence from Firm
Surveys. World Economy 35(1):91–105.
Huang, Yiping, and Bijun Wang. 2013. Investing Overseas without Moving Factories Abroad:
The Case of Chinese Outward Direct Investment. Asian Development Review 30(1):85–
107.
Hymer, Stephen Herbert. 1976. The International Operations of National Firms: A Study of Direct
Foreign Investment. Cambridge, Mass.: MIT Press.
Kindleberger, Charles. 1969. American Business Abroad: Six Lectures on Direct Investment. New
Haven, Connecticut: Yale University Press.
Kindleberger, Charles, ed. 1970. The International Corporation: A Symposium. Cambridge, Mass.:
MIT Press.
l
D
o
w
n
o
a
d
e
d
f
r
o
m
h
t
t
p
:
/
/
d
i
r
e
c
t
.
m
i
t
.
/
e
d
u
a
d
e
v
/
a
r
t
i
c
e
-
p
d
l
f
/
/
/
/
3
1
2
1
0
9
1
6
4
2
0
2
7
a
d
e
v
_
a
_
0
0
0
3
2
p
d
.
/
f
b
y
g
u
e
s
t
t
o
n
0
7
S
e
p
e
m
b
e
r
2
0
2
3
THE DRAGON IS FLYING WEST 133
Konings, Jozef, and Hylke Vandenbussche. 2005. Heterogeneous Responses of Firms to Trade
Protection. Journal of International Economics 76(2):371–83.
Krugman, Paul. 1980. Scale Economies, Product Differentiation and the Pattern of Trade. Ameri-
can Economic Review 70(5):950–59.
Liao, Wei, and Kevin K. Tsui. 2012. China’s Outward Direct Investment: Evidence from a New
Micro Dataset. HKIMR Working Paper No. 17/2012. Hong Kong, China: Hong Kong
Institute for Monetary Research.
Lipsey, Robert, and Merle Weiss. 1981. Foreign Production and Exports in Manufacturing Indus-
tries. Review of Economics and Statistics 63(4):488–94.
———. 1984. Foreign Production and Exports of Individual Firms. Review of Economics and
Statistics 66(2):304–07.
Luo, Yadong, Hongxin Zhao, Yagang Wang, and Youmin Xi. 2011. Venturing Abroad by Emerging
Market Enterprises: A Test of Dual Strategic Intents. Management International Review
51(4):433–59.
Ma, Yue, Heiwai Tang, and Yifan Zhang. 2014. Factor Intensity, Product Switching, and Productiv-
ity: Evidence from Chinese Exporters. Journal of International Economics, 92(2):349–62.
Makino, Shige, Chung-Ming Lau, and Rhy-Song Yeh. 2002. Asset-exploitation versus Asset
Seeking: Implications for Location Choice of Foreign Direct Investment from Newly In-
dustrialized Economies. Journal of International Business Studies 33(3):403–21.
Manova, Kalina, and Zhihong Yu. 2013. Firms and Credit Constraints along the Global Value
Chain: Processing Trade in China. Stanford University mimeo.
Markusen, James, and Anthony Venables. 2000. The Theory of Endowment, Intra-industry and
Multi-national Trade. Journal of International Economics 52(2):209–34.
Mathews, John. 2006. Dragon Multinationals: New Players in 21st Century Globalization. Asia
Pacific Journal of Management 23(1):5–27.
Rui, Huaichuan, and George Yip. 2008. Foreign Acquisitions by Chinese Firms: A Strategic Intent
Perspective. Journal of World Business 43(2):213–27.
Rosenbaum, Paul, and B. Donald Rubin. 1983. The Central Role of the Propensity Score in
Observational Studies for Causal Effects. Biometrika 70(1):41–55.
UNCTADstat. http://unctadstat.unctad.org/ReportFolders/reportFolders.aspx.
Wu, Hsiu-Ling, and Chien-Hsun Chen. 2001. An Assessment of Outward Foreign Direct Invest-
ment from China’s Transitional Economy. Europe-Asia Studies 53(8):1235–54.
Yamawaki, Hideki. 1991. Exports and Foreign Distributional Activities: Evidence on Japanese
Firms in the United States. Review of Economics and Statistics 73(2):294–300.
Yeaple, Stephen Ross. 2003. The Complex Integration Strategies of Multinationals and Cross
Country Dependencies in the Structure of FDI. Journal of International Economics
60(2):293–314.
Zhu, Xiaodong. 2012. Understanding China’s Growth: Past, Present, and Future. Journal of
Economic Perspectives 26(4):103–24.
l
D
o
w
n
o
a
d
e
d
f
r
o
m
h
t
t
p
:
/
/
d
i
r
e
c
t
.
m
i
t
.
/
e
d
u
a
d
e
v
/
a
r
t
i
c
e
-
p
d
l
f
/
/
/
/
3
1
2
1
0
9
1
6
4
2
0
2
7
a
d
e
v
_
a
_
0
0
0
3
2
p
d
/
.
f
b
y
g
u
e
s
t
t
o
n
0
7
S
e
p
e
m
b
e
r
2
0
2
3
134 ASIAN DEVELOPMENT REVIEW
Appendix
Industry
Table A1. Industry Breakdown
Business services
Wholesale trade
Building and civil engineering
Nonferrous metals mining and dressing
Nonmetal mineral products
Garments, shoes, and caps manufacturing
Forestry
Real estate
Electric equipment and machinery
R&D
Geologic prospecting
Other financial activities
Metal products
Retail trade
Transport equipment
Food production
Waterway transport
Agriculture
Ordinary machinery
Software
Plastic products
Professional and technical services
Timber processing, bamboo, cane, palm fiber, and straw products
Food processing
Textile industry
Telecom and other information transmission
Securities
Leather, furs, down, and related products
Medical and pharmaceutical products
Raw chemical materials and chemical products
Telecom, computer, and other electronic equipment
Ferrous metals mining and dressing
Cultural, educational, and sports goods
Instruments, meters, cultural, and clerical machinery
Waste materials recycling and reprocessing
Catering
Smelting and pressing of ferrous metals
Computer services
Special purposes equipment
Smelting and pressing of nonferrous metals
Art and craft, and other manufacturing
Other services
Building installation
Science and technology exchange, and promotion services
Petroleum and natural gas extraction
Nonmetal minerals mining and dressing
Fishing
Furniture manufacturing
Freq.
2,816
2,419
285
212
202
189
181
169
162
159
157
143
135
122
118
106
101
86
86
84
82
82
82
77
75
67
61
58
57
57
57
55
53
48
48
47
44
42
42
41
34
34
33
33
32
29
28
26
Percent
0.289
0.248
0.029
0.022
0.021
0.019
0.019
0.017
0.017
0.016
0.016
0.015
0.014
0.013
0.012
0.011
0.010
0.009
0.009
0.009
0.008
0.008
0.008
0.008
0.008
0.007
0.006
0.006
0.006
0.006
0.006
0.006
0.005
0.005
0.005
0.005
0.005
0.004
0.004
0.004
0.003
0.003
0.003
0.003
0.003
0.003
0.003
0.003
Continued.
l
D
o
w
n
o
a
d
e
d
f
r
o
m
h
t
t
p
:
/
/
d
i
r
e
c
t
.
m
i
t
.
/
e
d
u
a
d
e
v
/
a
r
t
i
c
e
-
p
d
l
f
/
/
/
/
3
1
2
1
0
9
1
6
4
2
0
2
7
a
d
e
v
_
a
_
0
0
0
3
2
p
d
/
.
f
b
y
g
u
e
s
t
t
o
n
0
7
S
e
p
e
m
b
e
r
2
0
2
3
Industry
Freq.
Percent
Table A1. Continued.
THE DRAGON IS FLYING WEST 135
Rubber products
Air transport
Papermaking and paper products
Leasing
Railway transport
Chemical fiber
Building decoration
Loading and unloading, and carrying, and other transport
Animal husbandry
Beverage production
Hotels
Services to households
Storage
Culture and art
Highway transport
Production and supply of power, steam, and electricity
Services for agriculture, forestry, animal husbandry, and fishing
Urban public transport
Education
Other construction
Banking
Broadcasting, television, film, and audio
Health
News and publishing industry
Petroleum refining, coking, and nuclear energy
Printing and record medium reproduction
Tobacco processing and production
Post
Entertainment industry
Production and supply of water
Production and supply of gas
Coal mining and processing
Pipeline transport
Sports
Management of public facilities
Management of environment
Other
25
22
22
20
18
17
15
15
14
13
13
13
13
12
12
11
10
10
9
9
7
7
7
7
7
7
7
6
5
5
4
3
3
3
2
2
13
Total
9,744
Note: Industry classification is based on NBS 4-digit code.
Sources: PRC’s Ministry of Commerce, PRC National Bureau of Statistics, and authors’ own calculation.
0.003
0.002
0.002
0.002
0.002
0.002
0.002
0.002
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.000
0.000
0.000
0.000
0.000
0.000
0.001
1.000
l
D
o
w
n
o
a
d
e
d
f
r
o
m
h
t
t
p
:
/
/
d
i
r
e
c
t
.
m
i
t
.
/
e
d
u
a
d
e
v
/
a
r
t
i
c
e
-
p
d
l
f
/
/
/
/
3
1
2
1
0
9
1
6
4
2
0
2
7
a
d
e
v
_
a
_
0
0
0
3
2
p
d
.
/
f
b
y
g
u
e
s
t
t
o
n
0
7
S
e
p
e
m
b
e
r
2
0
2
3
136 ASIAN DEVELOPMENT REVIEW
Table A2. Distribution across Provinces
Province
Zhejiang
Shandong
Jiangsu
Guangdong
Central Enterprises
Shanghai
Beijing
Fujian
Liaoning
Heilongjiang
Hunan
Tianjin
Yunnan
Henan
Hebei
Jilin
Sichuan
Guangxi
Xinjiang
Anhui
Chongqing
Jiangxi
Hubei
Shaanxi
Shanxi
Gansu
Hainan
Ningxia
Guizhou
Qinghai
Xizang
Total
Freq.
1,993
996
938
920
568
508
489
410
341
302
295
253
201
171
170
164
159
139
123
103
95
89
73
73
72
35
28
13
12
9
2
9,744
Percent
20.45
10.22
9.63
9.44
5.83
5.21
5.02
4.21
3.50
3.10
3.03
2.60
2.06
1.75
1.74
1.68
1.63
1.43
1.26
1.06
0.97
0.91
0.75
0.75
0.74
0.36
0.29
0.13
0.12
0.09
0.02
100.00
Cum.
20.45
30.68
40.30
49.74
55.57
60.79
65.80
70.01
73.51
76.61
79.64
82.24
84.30
86.05
87.80
89.48
91.11
92.54
93.80
94.86
95.83
96.75
97.50
98.25
98.98
99.34
99.63
99.76
99.89
99.98
100.00
Sources: PRC’s Ministry of Commerce and authors’ own calculations.
Table A3. Number of ODI Firms by Ownership Type
Year
State-owned
Domestic Private
Foreign
0
0
0
2
0
4
2
20
21
23
12
26
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
ODI = outward direct investment.
Source: PRC’s Ministry of Commerce.
0
0
3
2
28
22
39
273
366
366
335
336
0
0
2
1
1
3
13
82
79
93
79
110
l
D
o
w
n
o
a
d
e
d
f
r
o
m
h
t
t
p
:
/
/
d
i
r
e
c
t
.
m
i
t
.
/
e
d
u
a
d
e
v
/
a
r
t
i
c
e
-
p
d
l
f
/
/
/
/
3
1
2
1
0
9
1
6
4
2
0
2
7
a
d
e
v
_
a
_
0
0
0
3
2
p
d
/
.
f
b
y
g
u
e
s
t
t
o
n
0
7
S
e
p
e
m
b
e
r
2
0
2
3
THE DRAGON IS FLYING WEST 137
Table A4.1. Breakdown of Industries by NBS Classifications
of NBS ODI Dataset
Sector
Freq.
Percent
Manufacturing
Mining
Power, gas, and water
NBS = National Bureau of Statistics, ODI = outward direct investment.
Sources: PRC’s Ministry of Commerce, PRC National Bureau of Statistics,
and authors’ own calculation.
2,544
19
13
98.76
0.74
0.50
Table A4.2. Breakdown of Industries by ODI Assigned Classifications of Customs ODI
Dataset
Industry
Freq.
Transport equipment
Leather, furs, down, and related products
Plastic products
Telecom and other information transmission
Cultural, educational, and sports goods
Forestry
Timber processing, bamboo, cane, palm fiber, and straw products
Business services
Building and civil engineering
R&D
Electric equipment and machinery
Retail trade
Food production
74
63 Wholesale trade
18 Garments, shoes, and caps manufacturing
47
31 Nonmetal mineral products
39
75
65
14
34 Metal products
19
37
30
60
24
2
20
35 Ordinary machinery
9
17
40
78 Geologic prospecting
Instruments, meters, cultural, and clerical machinery
41
13
Food processing
71 Other financial activities
1
36
26
27 Medical and pharmaceutical products
72
76
8
29 Waterway transport
32
54
62
22
Rubber products
Smelting and pressing of ferrous metals
Ferrous metals mining and dressing
Papermaking and paper products
Nonferrous metals mining and dressing
Textile industry
Telecom, computer, and other electronic equipment
Agriculture
Special purposes equipment
Raw chemical materials and chemical products
Real estate
Professional and technical services
Software
718
421
46
45
32
31
31
28
25
23
22
22
20
19
18
17
17
17
16
15
14
14
13
12
11
10
10
9
9
8
8
7
7
7
7
7
6
Percent
39.56
23.20
2.53
2.48
1.76
1.71
1.71
1.54
1.38
1.27
1.21
1.21
1.10
1.05
0.99
0.94
0.94
0.94
0.88
0.83
0.77
0.77
0.72
0.66
0.61
0.55
0.55
0.50
0.50
0.44
0.44
0.39
0.39
0.39
0.39
0.39
0.33
Cum.
39.56
62.75
65.29
67.77
69.53
71.24
72.95
74.49
75.87
77.13
78.35
79.56
80.66
81.71
82.70
83.64
84.57
85.51
86.39
87.22
87.99
88.76
89.48
90.14
90.74
91.29
91.85
92.34
92.84
93.28
93.72
94.10
94.49
94.88
95.26
95.65
95.98
Continued.
l
D
o
w
n
o
a
d
e
d
f
r
o
m
h
t
t
p
:
/
/
d
i
r
e
c
t
.
m
i
t
.
/
e
d
u
a
d
e
v
/
a
r
t
i
c
e
-
p
d
l
f
/
/
/
/
3
1
2
1
0
9
1
6
4
2
0
2
7
a
d
e
v
_
a
_
0
0
0
3
2
p
d
/
.
f
b
y
g
u
e
s
t
t
o
n
0
7
S
e
p
e
m
b
e
r
2
0
2
3
138 ASIAN DEVELOPMENT REVIEW
Industry
Freq.
Table A4.2. Continued.
33
43
69
83
4
42
61
82
7
21
28
48
58
67
77
10
16
52
5
15
55
57
59
73
90
Waste materials recycling and reprocessing
Smelting and pressing of nonferrous metals
Securities
Other services
Services to households
Fishing
Computer services
Art and craft, and other manufacturing
Building installation
Science and technology exchange, and promotion services
Furniture manufacturing
Catering
Chemical fiber
Storage
Petroleum and natural gas extraction
Highway transport
Nonmetal minerals mining and dressing
Tobacco processing and production
Loading and unloading, and carrying, and other transport
Air transport
Post
Leasing
Beverage production
Culture and art
Services for agriculture, forestry, animal husbandry, and fishing
6
6
6
5
4
4
4
4
3
3
3
3
3
3
3
2
2
2
1
1
1
1
1
1
1
Percent
0.33
0.33
0.33
0.28
0.22
0.22
0.22
0.22
0.17
0.17
0.17
0.17
0.17
0.17
0.17
0.11
0.11
0.11
0.06
0.06
0.06
0.06
0.06
0.06
0.06
Cum.
96.31
96.64
96.97
97.25
97.47
97.69
97.91
98.13
98.29
98.46
98.62
98.79
98.95
99.12
99.28
99.39
99.50
99.61
99.67
99.72
99.78
99.83
99.89
99.94
100.00
Total
ODI = outward direct investment.
Sources: PRC’s Ministry of Commerce, PRC National Bureau of Statistics, and authors’ own calculation.
1,815
100
Table A5. Success Rates of Matching between ODI and Customs
Data, and ODI and Manufacturing Survey Data
Year
NBS Matches
Customs
Matches Export
Customs
Matches Import
0.01
0.01
0.06
0.05
0.09
0.39
0.41
0.16
0.11
0.35
0.29
0.55
0.47
0.32
0.47
0.44
0.39
0.34
0.27
0.35
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
Average
NBS = National Bureau of Statistics, ODI = outward direct investment.
Sources: PRC’s Ministry of Commerce, PRC National Bureau of Statistics, PRC Customs,
and authors’ own calculation.
0.01
0.01
0.06
0.05
0.08
0.37
0.42
0.15
0.14
l
D
o
w
n
o
a
d
e
d
f
r
o
m
h
t
t
p
:
/
/
d
i
r
e
c
t
.
m
i
t
.
/
e
d
u
a
d
e
v
/
a
r
t
i
c
e
-
p
d
l
f
/
/
/
/
3
1
2
1
0
9
1
6
4
2
0
2
7
a
d
e
v
_
a
_
0
0
0
3
2
p
d
.
/
f
b
y
g
u
e
s
t
t
o
n
0
7
S
e
p
e
m
b
e
r
2
0
2
3
Table A6. ODI Effects on Export Performance (FE Regressions)
Sample
All Firms (ODI = 0 for non-ODI firms and observations before ODI)
THE DRAGON IS FLYING WEST 139
Dependent Var: Export Total Value Exp Unit Value
ODI
Firm FE
Year FE
R-squared
No. of obs.
Dependent Var:
0.017
(0.069)
Yes
Yes
0.727
717,355
0.103
(0.057)
Yes
Yes
0.806
717,355
Imp Unit Value
# of Exp HS6
0.079∗∗
(0.027)
Yes
Yes
0.839
751,589
Exp # of Country
0.067∗∗
(0.023)
Yes
Yes
0.838
751,588
Imp Total Value
0.630∗∗∗
(0.074)
Yes
Yes
0.826
659,392
Imp # of HS6 Value
0.301∗∗∗
(0.034)
Yes
Yes
0.835
659,392
ODI
0.047
(0.083)
Yes
Firm FE
Yes
Year FE
0.795
R-squared
No. of obs.
659,392
∗ = p < 0.05, ∗∗ = p < 0.01, ∗∗∗ = p < 0.001, FE = fixed effects, NBS = National Bureau of Statistics, ODI
= outward direct investment.
Note: ODI = 1 for all firm–years when and after a firm reported overseas investment. All dependent variables are in
log form. All custom firms and treated firms prior to ODI are included in the control group. Robust standard
errors reported in brackets.
Source: Authors’ computations.
Imp # of Country
0.064∗
(0.030)
Yes
Yes
0.716
677,740
Table A7. Balancing Test of Matching ODI and non-ODI (NBS Sample)
Variable
Sample
Treated
Control %Bias
Mean
%Reduction
Bias
t
p>t
TFP
Ln Employment
Export Intensity
Capital Intensity
Material Intensity
0.000
0.962
0.000
0.989
0.000
0.735
0.001
0.834
0.000
0.976
0.000
0.893
0.653
0.990
0.000
0.643
HKG = Hong Kong, Porcelana, NBS = National Bureau of Statistics, ODI = outward direct investment, TAP =
Taipéi,Porcelana, TFP = total factor productivity, SOE = state-owned enterprises.
Fuente: Authors’ computations.
21.89
99.1 −0.05
32.65
98.1 −0.01
2.78
0.34
3.20
0.21
26.02
0.03
6.64
0.13
0.45
74.3 −0.01
5.23
86.1 −0.46
Unmatched
Matched
Unmatched
Matched
Unmatched
Matched
Unmatched
Matched
Unmatched
Matched
Unmatched
Matched
Unmatched
Matched
Unmatched
Matched
0.441
0.441
5.722
5.716
0.217
0.217
−0.248
−0.248
6.258
6.254
0.252
0.251
0.133
0.133
0.169
0.169
0.202
0.443
4.703
5.736
0.204
0.213
−0.279
−0.262
5.477
6.298
0.176
0.244
0.128
0.134
0.119
0.176
62.1
−0.6
85.8
−1.7
8.5
2.9
11.4
5.1
72.3
−4.1
18.5
1.8
1.3
−0.3
14.4
−2.0
HKG; TAP; and Macau,
China invested firms
Foreign
SOE
65.4
90.0
94.4
55.0
yo
D
oh
w
norte
oh
a
d
mi
d
F
r
oh
metro
h
t
t
pag
:
/
/
d
i
r
mi
C
t
.
metro
i
t
.
/
mi
d
tu
a
d
mi
v
/
a
r
t
i
C
mi
–
pag
d
yo
F
/
/
/
/
3
1
2
1
0
9
1
6
4
2
0
2
7
a
d
mi
v
_
a
_
0
0
0
3
2
pag
d
/
.
F
b
y
gramo
tu
mi
s
t
t
oh
norte
0
7
S
mi
pag
mi
metro
b
mi
r
2
0
2
3
140 ASIAN DEVELOPMENT REVIEW
Table A8. Balancing Test of Matching ODI and non-ODI (Customs Sample)
Significar
%Reduction
Bias
SOE
Export
Sample
Treated
Control
Variable
Import Share
t
−10.36
−0.19
18.63
0.48
13.58
−0.07
18.13
0.63
−24.04
−0.61
ODI = outward direct investment, SOE = state-owned enterprises, POE = privately-owned enterprises.
Fuente: Authors’ computations.
Unmatched
Matched
Unmatched
Matched
Unmatched
Matched
Unmatched
Matched
Unmatched
Matched
%Bias
−41.6
−1.1
76.9
2.6
46.9
−0.5
63.6
4.2
−104.5
−3.5
0.404
0.283
13.467
15.261
0.136
0.331
0.166
0.427
0.687
0.241
0.280
0.280
15.324
15.324
0.329
0.329
0.445
0.445
0.226
0.226
Foreign
POE
99.0
96.6
97.4
96.7
93.5
p>t
0.000
0.850
0.000
0.629
0.000
0.946
0.000
0.532
0.000
0.541
yo
D
oh
w
norte
oh
a
d
mi
d
F
r
oh
metro
h
t
t
pag
:
/
/
d
i
r
mi
C
t
.
metro
i
t
.
/
mi
d
tu
a
d
mi
v
/
a
r
t
i
C
mi
–
pag
d
yo
F
/
/
/
/
3
1
2
1
0
9
1
6
4
2
0
2
7
a
d
mi
v
_
a
_
0
0
0
3
2
pag
d
/
.
F
b
y
gramo
tu
mi
s
t
t
oh
norte
0
7
S
mi
pag
mi
metro
b
mi
r
2
0
2
3
Descargar PDF