446 B. P. Resosudarmo and M. Irhamni
Other encouraging aspects of this situation are these. First, on water use, although the total amount used by the manufacturing sector increased by
approximately 51 in the 1990s, or from around 370 million m
3
in 1990 to 560 million m
3
in 2006, water use intensity declined by as much as 21 during this period, meaning the industrial sector was able to increase its efficiency in
using water. Second, the percentage of MVA produced by most pollutant-intensive sub-sectors declined from 20 in 1990 to 15 in 2000, meaning that, since in-
dustry grew during this period, the growth of the industrial sector was mostly due to the growth of the less polluting sub-sectors.
The fact that industry has been able to be more efficient in using water reflects the level of its water pollution intensity, which, reflected by the BOD intensity,
has been reduced by as much as 23 from 1990 to 2001. However, it is important to note that total water pollution from the industrial sector has still increased by
as much as 52; i.e. from 163.7 billion tonnes in 1990 to 248.7 billion tonnes in 2001. The ideal situation is that total water pollution by industry could be
reduced; since most firms dump their pollution in surrounding rivers, most rivers in industrial areas have been heavily polluted.
In terms of air pollution, the story is rather discouraging. As mentioned above, industry has more or less maintained its energy intensity. However, its pollution
intensity, measured by tonnes of CO
2
per 10
6
US of MVA, increased by 20 in the 1990s; i.e. from 993 tonnes of CO
2
per 10
6
US of MVA in 1990 to 1181 tonnes of CO
2
per 10
6
US of MVA in 2002. It is also important to compare the amount of CO
2
emitted by industry and the total CO
2
caused by all types of hydrocarbon energy sources. The total amount of CO
2
emitted was 150 million metric tons in 1990 and 310 million metric tonnes in 2002, or in other words it increased by around 106 EIA 2005. Meanwhile, for
the same period, the amount of CO
2
emitted by industry increased by 157; i.e. emission by industry increased faster than the average of other sectors. However,
the CO
2
intensity for all sectors, measured in metric tons per 2000 US of GDP, increased by around 31 from 1990 to 2002; i.e. higher than the CO
2
intensity of industry. In this case, one can say that in terms of loss of effectiveness in
controlling air pollution emission, the situation in other sectors was worse, on average, than in the industrial sector.
6. Conclusion
This paper reviews the pattern of industrial policy broadly defined in Indonesia, offers assessment of how industrial policies have impacted on the environmen-
tal performance of industry, and describes how industrial policies, paralleled by industrial environmental policies, have been modified to lessen industries’ envi-
ronmental impact.
Since systematic monitoring of industrial pollution has been limited so far, in observing the impact of industrial policy on the environment in general, this paper
focused on observing 1 the composition of industrial activity; i.e. high or low
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Journal of the Asia Pacific Economy 447
polluting industries; 2 the scale of industrial activity; and 3 the demand for and supply of pollution abatement efforts.
During the 1975–81 period, the dominant industrial policy was one of im- port substitution. The government allowed extensive extraction of natural re-
sources and used the revenue thus obtained to support and protect the devel- opment of large state-owned enterprises in heavy basic metals and chemicals.
These policies were able to promote the development of the industrial sector, inducing a large share of the industrial sector in the economy. However, since
most of these industries were relatively large and high polluting, in the absence of environmental regulation, levels of industrial pollution intensities increased
significantly.
During the 1982–96 period, industrial policy was characterised by various efforts to liberalise the economy – although various protections at the micro
level in heavy and hi-tech industries did exist – to attract industrial FDI and stimulate development of the labour intensive, export-oriented and non-oil and
gas manufacturing sectors. At the same time, many companies in Taiwan, South Korea, Singapore, Hong Kong, Japan and some other developed countries looked
for new places to relocate their factories. One of several motivations to find new locations was tighter environmental regulations in their own countries.
8
Hence, although there was a relatively large amount of new FDI, much of it was in the
form of relatively high polluting industries. Furthermore, no significant industrial pollution policy was implemented. Hence, levels of industrial pollution intensity
during this period continued to increase.
Serious efforts to reduce the increase in the level of industrial pollutants were begun only in the early 1990s, even though the concern for environmen-
tal degradation began to develop in the late 1970s. Various industrial environ- ment policies were then enacted. Although many argued that the implementa-
tion of these environmental policies was effective, their scale was too small. Efforts to up-scale them were either not conducted or were not conducted
successfully.
The economic crisis hit the country in 1997–98, causing the government and private sector to focus on efforts to help industries survive the crisis and ignore
the need to control their pollution. Many argued that industrial pollution intensity might have increased significantly during the crisis. However, the crisis also slowed
down industrial activity, so that the levels of pollution intensity in the early 2000s were more or less the same as in the early 1990s.
Current industrial policy, at the macro level, is characterised by various reforms to liberalise the economy even further to attract new FDI. At the micro level,
industrial policy focuses on various efforts to improve the competitiveness of the country’s industrial activities. To avoid attracting new capital investments mostly
in the high polluting industries, as was the experience in the 1980s and 1990s, it is recommended that strict nationwide environmental regulations should be
implemented. Efforts were made to re-establish industrial environmental policies in the early 2000s but their scale has so far been relatively limited. The results of
Downloaded By: [University of TokyoTOKYO DAIGAKU] At: 08:51 27 November 2008
448 B. P. Resosudarmo and M. Irhamni
these policies need to be monitored carefully to maximise the chance of successful outcomes for both industrial development and protection of the environment.
Acknowledgements
The authors would like to thank the UNIDO for partly funding this research and Fajar B. Hirawan for contributions as a research assistant. Any mistakes in this paper are the authors’
responsibility.
Notes
1. Environmental policies discussed in this section are those that relate to industrial
pollution. Other environmental policies have been implemented, such as promotion of unleaded gasoline and restricted areas for cars in the case of urban air pollution, the
integrated pest management programme in the case of pesticide, no smoking policies in public buildings in the case of indoor air pollution, eco-labelling in forestry, etc.
2. The regulation was re-issued by the enactment of Government Regulation No 511993,
specifically to clarify which agencies should assess and approve the environmental impact assessment report of a particular project.
3. The number is still relatively very small compared with the total number of rivers in
Indonesia, or even to the number of rivers in Java. 4.
Note that BAPEDAL was abolished that year and all of its staff were moved to the Ministry of Environment.
5. In 2000, the new regional government taxes and charges Law No. 342000 was enacted,
which actually provides an opportunity for regional government to implement pollution taxes. However, regional governments do not seem to have used this opportunity yet.
6. Dispenda is a regional body responsible for collecting income from tax, etc for the
region. 7.
A surety bond is a contract agreement between at least three parties. The principal is the primary party who will carry out obligations specified by the contract. The obligee
is the recipient of the contract obligation. The surety is the party who guarantees the principal’s performance of the obligation.
8. For the East Asian NICs, the main push factors were the rising wages in, and the sharp
appreciation of, the currencies of these countries Thee 1991.
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Is foreign direct investment good for growth? Evidence from sectoral analysis of China and Vietnam
Tam Bang Vu
a
; Byron Gangnes
b
; Ilan Noy
b a
College of Business and Economics, University of Hawaii-Hilo, Hilo, Hawaii, USA
b
Department of Economics, University of Hawaii-Manoa, Honolulu, Hawaii, USA
Online Publication Date: 01 November 2008
To cite this Article Vu, Tam Bang, Gangnes, Byron and Noy, Ilan2008Is foreign direct investment good for growth? Evidence from
sectoral analysis of China and Vietnam,Journal of the Asia Pacific Economy,13:4,542 — 562 To link to this Article: DOI:
10.108013547860802364976 URL:
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Journal of the Asia Pacific Economy Vol. 13, No. 4, November 2008, 542–562
Is foreign direct investment good for growth? Evidence from sectoral analysis of China and Vietnam
Tam Bang Vu
a∗
, Byron Gangnes
b
and Ilan Noy
b
a
College of Business and Economics, University of Hawaii-Hilo, Hilo, Hawaii, USA;
b
Department of Economics, University of Hawaii-Manoa, Honolulu, Hawaii, USA We estimate the impact of FDI on growth using sectoral data for FDI inflows
to China and Vietnam. Previous empirical studies, using either cross-country growth regressions or firm-level micro-econometric analysis, fail to reach a
consensus. Our paper is the first to use sectoral FDI inflow data to evalu- ate the sector-specific impact of FDI on growth. Our results show that, for
the two developing-transition economies we examine, FDI has a statistically- significant positive effect on economic growth operating directly and through
its interaction with labor. Intriguingly, we find the effects seem to be very different across economic sectors, with most of the beneficial impact con-
centrated in the secondary industries. Other sectors appear to see much less growth benefit from sector-specific FDI.
Keywords: foreign direct investment; growth; China; Vietnam. JEL Classifications: F21; F23
Introduction
During the past two decades, foreign direct investment FDI has become increas- ingly important in the developing world, with a growing number of developing
countries succeeding in attracting substantial and rising amounts of inward FDI. The theoretical literature in economics identifies a number of channels through
which FDI inflows may be beneficial to the receiving economy. Yet the empirical literature has lagged behind and has had more trouble identifying these advantages
in practice. Most prominently, a large number of applied papers have looked at the FDI-growth nexus, but their results have been far from conclusive.
1
Notwithstand- ing the absence of any robust conclusions, most countries continue vigorously to
pursue policies aimed at encouraging more FDI inflows.
2
Table 1 presents recent trends in FDI inflows both as a percentage of output and as a percentage of fixed capital formation. The worldwide trend increase in
∗
Corresponding author. Email: tamvhawaii.edu
ISSN: 1354-7860 print 1469-9648 online
C
2008 Taylor Francis DOI: 10.108013547860802364976
http:www.tandf.co.ukjournals Downloaded By: [University of TokyoTOKYO DAIGAKU] At: 03:22 8 December 2008
Journal of the Asia Pacific Economy 543
Table 1. World distribution of FDI. FDI net inflows
FDI net inflows of GDP
of Fixed Capital Formation 1980–
1990– 1995–
2000– 1980–
1990– 1995–
2000– 1989
1994 1999
2003 1989
1994 1999
2003 World
1.12 2.00
3.97 5.05
4.60 8.86
15.33 24.72
East Asia 2.61
4.60 6.10
5.26 10.28
19.05 22.66
20.84 South-East Asia
2.70 4.19
5.51 3.27
7.88 16.35
21.22 12.75
China .
58 3.48
4.70 3.83
1.60 8.67
12.11 9.71
Vietnam 0.02
6.09 7.53
4.04 0.15
30.22 26.87
13.09
Source: World Bank’s World Development Indicators 2004: BX.KLT.DINV.DT.GD.ZS and BX.KLT.DINV.DT.GI.ZS.
the importance of FDI using both measures is apparent, with FDI inflows during the past decade increasing to 4–5 times the level experienced during the 1980s.
While there was a doubling of foreign investment into East Asia during this time period, the Asian FDI inflow period peaked in 1995–1999 and current levels are
still below that peak.
3
A closer look at these measures for China including Hong Kong and Vietnam reveals a similar trend, with both experiencing almost no inflows during the 1980s
and a very dramatic increase throughout the 1990s. Relative to the size of their economies, FDI flows into Vietnam are almost twice as large as those flowing into
China. Neither country’s experience appears unique in the region; their FDI inflows show the same relative magnitudes and temporal dynamics as other countries in
East Asia.
FDI inflows are not uniformly distributed across production sectors, nor is their sectoral composition Tables 2 and 3 the same for the two countries. For
China, the dominant sector, industry – defined as a combination of mining and quarrying, manufacturing, and utilities electricity, gas, and water – accounts for
82.9 of total inflows out of five sectors for which data are available. For Vietnam, the industrial sector accounts for less than 46 of total inflows out of eight sectors
for which data are available.
It may be possible to gain insight into the FDI-growth nexus by examining FDI impacts at the sectoral level. And the dramatic but uneven opening of these
two economies provides a promising environment in which to look for industry- differences.
The opening up of China and Vietnam to foreign investments began in 1979 and 1987, respectively. Since then, the legal regimes governing foreign invest-
ments have been progressively liberalized with important modifications to the laws governing such investments made in recent years.
4
At the same time, liberalization is far from complete in both countries, and cus- tomary rules may often be in conflict with the formal legal code. These customary
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544 T.B. Vu et al.
Table 2. FDI in Vietnam by sector in millions of 1994 US dollars. 1990–2004
Sector 1990–1994
1995–1999 2000–2004
of total flows Industry
293.5 3775.9
9014.3 24.07
Heavy Industry 133.2
1943.4 5286.8
19.18 Processing zones
13.1 356.2
412.7 2.04
Light Industry 98.4
1476.3 3314.8
1.27 Oil and Gas
410.2 2532.8
4643.6 19.76
Food 48.8
684.3 1476.4
5.75 Construction
28.5 945.2
2375.9 8.72
Transportation 72.3
675.6 1892.7
6.88 Real Estate
171.5 1857.3
3924.3 15.50
Hotel Tourism 127.0
1123.6 2201.2
8.99 Other Real Estates
44.5 741.4
1784.9 6.69
Agriculture 46.6
557.2 1876.1
6.45 Other Services
8.6 214.6
873.8 2.85
Total 1080
16883.8 17410.4
100
Source: IMF country report and Vietnam Statistical Yearbooks. Note: Actual disbursed amounts converted to constant 1994 US dollars using the US GDP implicit
price deflator.
Table 3. FDI in China by sector in millions of 1994 US dollars. 1990–2004
Sector 1990–1994
1995–1999 2000–2004
of total flows Farming, forestry, and
fishery 1150.0
2621.6 4092.0
1.65 Mining and quarrying
3185.7 2980.2
4090.3 1.29
Manufacturing 24068.6
138864.9 313817.6
59.99 Electric, gas, and water
6460.5 16155.6
14724.4 4.69
Construction 3885.5
8041.3 6920.8
2.53 Transport, post, and
telecommunication 4958.6
8828.8 9434.6
3.15 Wholesale, retail trade
and catering services 3020.0
6457.7 8310.6
2.36 Real estate
25229.2 31242.1
27850.6 10.61
Social services 9711.9
13652.2 21367.5
5.63 Health care, sport, and
social welfare 761.1
801.2 1499.2
0.39 Education, culture and arts
4005.2 3695.2
26013.8 3.37
Others 6194.0
6710.4 16908.2
3.75 Total
90068.9 238470.8
466459.5 100
Source: China Statistical Yearbooks. Note: Actual disbursed amounts converted to constant 1994 US using the US GDP implicit price
deflator.
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Journal of the Asia Pacific Economy 545
rules require an individual to obey local rules drafted by community leaders over and above the government’s laws. Any effort by the central government to contact
the individual directly may be met with ‘bamboo fences’ in a system that values community benefits above private ones. These customary rules create a patron-
age system that invites corruption among government officials at the intermediate levels.
5
In a 2006 ranking of property rights from the Heritage Foundation, both China and Vietnam rank very low, with China ranking a 4 and Vietnam a 5 for an
index 1–5 with low scores implying better property rights protection.
6
All these characteristics make China’s and Vietnam’s governance exceptionally weak and
inconsistent and make it more difficult to maintain an environment friendly to for- eign investors. These barriers are likely to be more important in some sectors than
in others, potentially affecting the growth effects deriving from FDI in particular sectors.
In this paper, we use an augmented production function to estimate the impact of FDI on growth using sectoral data for Vietnam and China including Hong
Kong. We let FDI affect GDP growth directly and also indirectly through its interaction with labor. This approach creates heteroskedasticity, and so feasible
generalized least squares FGLS is employed. The results show that FDI in both countries has a positive and statistically significant effect on economic growth
operating directly and indirectly through interaction with labor. Interestingly, the effect is not equally distributed across economic sectors. FDI only has a consis-
tently positive effect on growth in the manufacturing sector; its effect on other sectors is usually statistically insignificant, in some cases even negative.
A number of hypotheses have been offered regarding the interaction of foreign investment and growth. Singer 1950 argued that FDI will ‘crowd out’ domestic
investment since foreign firms often have greater access, at better terms, to in- ternational capital markets and will use the cheaper credit to drive out otherwise
productive firms. This makes the foreign firms superior to the domestic ones in financing large projects and in taking advantage of changes in comparative costs,
consumers’ tastes, and market conditions. Findlay 1978 models this channel explicitly using an augmented Solow model. Assuming that domestic technology
is an increasing function of FDI, he finds that the growth effect of FDI is am- biguous; an increase in the technology level might be offset by an increase in the
dependency on foreign capital.
7
Romer 2001 looks at technology as a non-rival input and at foreign direct investment as a source of technological advance. In this case, the FDI effect is
unequivocally positive. Bhagwati 1978, 1985 on the other hand, suggests that the growth effects of FDI might be positive for export promoting EP countries but
negative for import substituting IS ones; the reduction of foreign import goods in the domestic market reduces competition and efforts to improve efficiency among
the domestic firms.
Reis 2001 uses an endogenous growth model to evaluate the growth effects of FDI when the investing firm’s profits may be repatriated. She finds that, in
equilibrium, foreign firms replace all domestic firms in the RD sector. In this
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546 T.B. Vu et al.
model, FDI only adds a positive effect to growth if the world interest rate is lower than the home interest rate. These hypotheses guide, to a large extent, all
the empirical research that is described in the following section. The next section provides a brief survey on the state of current empirical work on the growth effects
of FDI. The section after presents our model and the data we use. The fourth section analyzes the empirical results, and the fifth section concludes.
Existing empirical literature
In light of the conflicting results in the theoretical literature, the FDI-growth problem remains largely an empirical one. In this section, we describe the current
state of empirical research on the FDI-growth nexus through cross-country studies, intra-regional comparisons, and specific case studies.
Cross-country studies
The early empirical work on the FDI-growth nexus modified the growth account- ing method introduced by Solow 1957. This approach defined an augmented
Solow model with technology, capital, labor, inward FDI, and a vector of ancillary variables such as imports, exports, etc. Taking the logs and time derivatives of
the explanatory variables yields an equation in growth rates for all variables with a ‘Solow residual’ measuring total factor productivity TFP growth. Using this
method and annual panel data for 46 developing countries, Balasubramanyam et al. 1996 find support for Bhagwati’s hypothesis that the growth effect of FDI is pos-
itive for export-promoting countries and might be negative for import-substituting ones.
Influenced by Mankiw et al. 1992, most empirical models add education to the augmented equation as a proxy for human capital. Blomstrom et al. 1994
and Coe et al. 1995 find that for FDI to have positive impacts on growth, the host country must have attained a level of development that helps it reap the benefits
of higher productivity. In contrast, De Mello 1996 finds that the correlation between FDI and domestic investment is negative in developed countries. Li and
Liu 2005 find that FDI not only affects growth directly but also indirectly through its interaction with human capital.
Using a larger sample, Borensztein et al. 1998 find that inward FDI has pos- itive effects on growth with the strongest impact through the interaction between
FDI and human capital. De Mello 1999 finds positive effects in both developing and developed countries. He finds that long-term growth in host countries is deter-
mined by the spillovers of technology and knowledge from the investing countries to host countries. In more recent work, Carkovic and Levine 2005 argue that the
positive results described above are due to a biased estimation methodology. When employing a different estimation technique Arellano-Bond GMM they find no
robust relationship between FDI inflows and domestic growth.
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Journal of the Asia Pacific Economy 547
Alfaro et al. 2004 and Durham 2004 focus on the ways in which the FDI effect depends on the strength of the domestic financial markets of the host
country. They find that only countries with well-developed banking and financial institutions gain from FDI. Durham 2004 finds similar results; FDI only has a
positive effect on growth in countries with strong financial systems. Additionally, he finds that only countries with high quality governance, as evidenced by strong
institutional development and investor-friendly legal environment, enjoy positive effects of FDI on growth. In addition, using data on developing countries, Hsiao
and Shen 2003 find that institutional strength and high levels of urbanization are conditions for positive effects of FDI on growth.
Blonigen and Wang 2005 argue that mixing wealthy and poor countries is inappropriate in empirical FDI studies. Organizing the aggregate data for
developed countries into six groups and developing ones into nine, they note three results. First, the factors that affect FDI inflows are different across
the groups. Second, the growth impact of FDI is only supported for devel- oping countries in the aggregate data, not developed ones. Third, the crowd-
ing out effect of FDI on domestic investment is only significant for developed countries.
Regional and country-specific empirical studies
Mortimore 1995 finds that there is a positive correlation between FDI and capital accumulation for Latin American countries. Bengoa and Sanchez-Robles 2003
use data for 18 Latin American countries from 1970 to 1999 and find that only countries with a higher level of economic freedom enjoy a positive growth effect
from FDI. Bende-Nabende 2001 conducts a cross-country study on Asian coun- tries, using annual data for 1970–1996 for the ASEAN-5. Results show that FDI
has a positive effect on GDP growth in Indonesia, Malaysia, and Philippines, but a negative impact in Singapore and Thailand.
Using Thai annual macroeconomic data for the 1970–1999 period and adding export openness, Kohpaiboon 2003 shows that FDI is positively correlated with
GDP growth in Thailand. Similarly, Marwah and Tavakoli 2004 examine Indone- sia, Malaysia, Philippines, and Thailand separately. Their results show that FDI has
a positive impact on GDP growth for all four countries. In contrast, Chakraborty and Basu 2002 find that GDP growth in India is not influenced by FDI. Instead,
the causality they find is from GDP growth to FDI, with trade liberalization weakly increasing the flows of inward FDI.
Several papers examine the growth effect of FDI in China. Chen et al. 1995 use data for selected cities and provinces during the 1979–1991 period. They
regress the log of GNP on FDI and find a positive growth effect. Zhang 2001 uses data from 1984 to 1998 for 28 provinces and finds that, generally, FDI
has a positive effect on economic growth in China through its interaction with human capital. Yao and Wei 2006 find similar results for more recent data
Downloaded By: [University of TokyoTOKYO DAIGAKU] At: 03:22 8 December 2008
548 T.B. Vu et al.
for 29 Chinese provinces and distinguish between two different benefits of FDI: extending the production frontier, and pushing production towards its frontier.
Wen 2007 shows that FDI only has positive effects on economic growth in China’s coastal provinces, which have more open policies toward foreign investors
than the inland provinces. By separating the Chinese economy into an FDI and a non-FDI sector, Whalley and Xin 2006 conclude that the contribution of FDI
to Chinese growth is quite substantial of the order of 3–4 percentage points per year. None of these papers distinguishes direct investment projects by sectors,
although Hale and Long 2007 examine productivity spillovers in Chinese FDI projects.
Regarding Vietnam, very little detailed analysis on growth effects of FDI has been conducted. Two papers by Kokko and Zejan 1996 and Kokko et al. 2003
discuss reasons for success or failure of specific FDI projects in Vietnam. Two other papers by Schaumburg-Muller 2003 and Ngoc and Ramstetter 2004 investigate
the performance of foreign multinationals versus local firms in Vietnam. Pham 2002 analyzes FDI and regional development using data on approval values
of FDI for 64 provinces in Vietnam. He finds that FDI contributes to regional development by increasing industrial output. However, Kokko et al. 2003 find
that the data set for approval values is only weakly correlated with the data set for actual implemented projects, which casts doubt on the robustness of the Pham
2002 results.
In summary, results on growth effects of FDI are hardly robust. Several authors argue that only developed countries with high-quality governance and robust
financial systems benefit from FDI. Others suggest that developing countries are more likely to enjoy a growth impetus from FDI and are less likely to suffer from
crowding out effects. Our data and methodology permit us to avoid some of the key problems that plague this literature.
We employ a case study single-country regression-based approach that en- ables us to disregard variables that measure the time-invariant institutional, legal
and cultural environment in which FDI projects are implemented. The difficulty measuring these institutional characteristics hinders easy identification in cross-
country approaches.
9
Second, to the best of our knowledge, our paper is the first to use data from different sectors to examine the sectoral differences in the impact of FDI on
economic growth. This is potentially important since much of the recent theoretical and empirical micro-econometric literature concludes that FDI spillovers, if they
exist, are found in intra-industry rather than in inter-industry settings.
10
This finding further justifies our attempt to ask whether the impact of FDI on growth
might be different for different sectors and to begin to investigate whether particular sectoral characteristics are conducive to a positive impact of FDI. Finally, by
implementing the same methodology for two different country-specific datasets and comparing these results, we are able to provide some evidence on the generality
of our conclusions.
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Journal of the Asia Pacific Economy 549
Methodology and data Methodology
We use the augmented Cobb–Douglas production function: Y
it
= AL
α
i
it
K
δ
i
it
F
γ
i
it n
j = 1
C
φ
ij
ij t
e
v
i
e
ε
it
1 where Y ,L,K and F are value added of each sector, labor, physical capital hence-
forth simply capital, and foreign direct investment respectively; C is a vector of control variables such as exports, imports, infrastructure, etc. The subscripts
are for sector i, variable j , and time t; α, δ, γ , and φ are parameters; v
i
is the sector-specific disturbance and ε
it
the general disturbance. Taking natural logarithms of equation 1 and time derivatives of each variable
yields the linear form in growth rates: ˙
Y Y
it
= α
i
˙ L
L
it
+ δ
i
˙ K
K
it
+ γ
i
˙ F
F
it
+
n j =
1
φ
ij
˙ C
C
ij t
+ η
it
2 where ˙
XX is the growth rate of X. During the high growth phase of economic
development, we expect that the productivity of labor and capital will evolve over time. Because a plausible channel for host-country growth effects of FDI is
through labor-augmenting technical transfers,
11
we write the coefficient of labor as a linear function of FDI.
α
it
= α
1
+ α
2
F
it
+ u
it
3 where u
it
is the idiosyncratic disturbance for sector iat time t.
12
We then follow the conventional literature on economic growth and write the capital coefficient
as a linear function of human capital:
13
δ
it
= δ
1
+ δ
2
H
t
+ e
it
4 where H
t
is human capital growth and e
it
is the idiosyncratic disturbance. Substi- tuting equations 3 and 4 into equation 2 yields:
˙ Y
Y
it
= α
1
˙ L
L
it
+ α
2
F
it
• ˙
L L
it
+ δ
1
˙ K
K
it
+ δ
2
H
t
• ˙
K K
it
+ γ
i
˙ F
F
it
+
n j =
1
φ
ij
˙ C
C
ij t
+ w
it
5
Downloaded By: [University of TokyoTOKYO DAIGAKU] At: 03:22 8 December 2008
550 T.B. Vu et al.
where w
it
= u
it
• ˙
LL
it
+ e
it
• ˙
KK
it
+ η
it
is a composite disturbance for sector i at time t.
The variance of the composite disturbance can be written as: σ
2 w
it
= σ
2 u
it
• ˙
L L
2 it
+ σ
2 e
it
• ˙
K K
2 it
+ σ
2 η
it
6 This specific form of heteroskedasticity can be corrected using an appropriate fea-
sible generalized least squares FGLS estimator. Since foreign capital in the form of foreign aid is a significant source of capital for both countries we decompose
capital into domestic capital and foreign capital. Hence, the estimable form of equation 5 is:
V AL
it
= β
1
+ β
2
FDI
it
+ β
3
FDI
it
LAB
it
+ β
4
LAB
it
+ β
5
CAP
it
+ β
6
HUM
t
CAP
it
+ β
7
FOCAP
it
+ +
n j =
1
β
ij
CON
ij t
+ w
it
7 where X is the differenced logarithm approximately the growth rate of X; VAL,
FDI, LAB, CAP, FOCAP, HUM, and CON are value added, FDI, labor, capital, foreign capital, human capital, and control variables, respectively.
Data
Vietnamese data on value added are available from the Vietnam Statistical Year- book VSY published by the General Statistical Office of Vietnam GSOV.
Complete annual series are available for nine sectors for the period 1990–2004. The GSOV only provides FDI data for approved amounts. Data on actually utilized
FDI for 11 economic sectors and foreign aid from 1990 to 2004 are available from the International Monetary Fund’s appendices to its Annual Reports for Vietnam.
The data are originally provided by the Vietnamese authorities, and then adjusted by IMF staff. Data on value added in real estate are not available for 1990–1994,
so we have an unbalanced panel.
The VSY and the GSOV’s website provide data for the labor force in Vietnam from 1990 to 2004. We obtained data for investment INV – new increase in fixed
assets – for the 1990–2004 period from the VSY and GSOV’s website. As a proxy for domestic capital, we calculate the stock of accumulated investment.
The complete annual time series of Chinese value added data are available for 12 sectors for the 1990–2004 period. The China Statistical Yearbook CSY and
theGeneral Statistical Office of China GSOC both provide data for FDI. Data for 1992–1993 and 1997–2002 periods are for 12 sectors, from 2003 to 2004 are
for 19 sectors. Eleven sectors in the FDI data set match the sectors in the value added data. Data for 1990–1991 are ascribed to 21 governmental departments. We
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Journal of the Asia Pacific Economy 551
match these departments to the above 11 sectors. Data on sectoral FDI for 1994, 1995, and 1996 are missing, so we again have an unbalanced panel.
The CSY provides data on labor force in China for 16 sectors from 1990 to 2002, and we add up the separate data on urban and rural labor forces for 2003–
2004. For investment, the only series that is available for all sectors throughout the 1990–2004 period is investment in capital construction INV. We again calculate
accumulated investment to use as a proxy for capital. Data on foreign aid for China are obtained from the International Monetary Fund’s Balance of Payments
Statistics.
In calculating education as a proxy for human capital HUM, we sum up data from the Statistical Yearbooks for enrollments in secondary schools, technical
schools vocational schools in the case of China, worker training schools, and four-year colleges.
14
We then divide the data on education by population to obtain the school enrollment ratio for each country and label this variable as ‘human cap-
ital’. Data in domestic currency are converted to constant 1994 domestic currency using GDP price indices for China and 1994 constant prices for Vietnam. Data on
FDI and foreign capital are converted to constant 1994 US dollars using the US GDP implicit deflator DEFL.
15
For a list of variables that might explain economic growth, we consult Barro and Sala-i-Martin 2004 and Romer 2001. We obtain data on interest rate
INT from the IMF International Finance Statistics and calculate its growth rate GINT, data on exports EX and imports IM, the number of telephones
as a proxy for telecommunication capacity COM, and the volume of freight traffic as a proxy for transportation infrastructure TRANS are from the respective
statistical yearbooks of the two countries. Binary dummies are created to control for missing observations, and calculating the growth rates uses up one year, so
126 observations for Vietnam and 154 observations for China are available for estimation.
Results Specification tests
We carry out a downward piece-wise specification search in order to avoid omitted variable bias, starting with all available variables that may explain economic
growth: FDI, labor, capital, foreign capital, the real interest rate, human capital, exports, imports, telecommunication, and infrastructure. The model is initially
estimated without interaction terms, which create built-in multicollinearities and cause the multicollinearity tests to be invalid. We use the Variance Inflation Factors
VIF approach by Kennedy 2003, who recommends elimination of any variable with VIF greater than ten. However, we decide to keep exports growth EX,
which is an important variable for export-led growth countries like China and Vietnam, although the VIF for EX is slightly greater than ten. We then add the
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552 T.B. Vu et al.
interaction terms to obtain the following estimated equation: VAL
it
= β
1
LAB
it
+ β
2
FDI
it
+
it
β
3
FDI
it
LAB
it
+ β
4
CAP
it
+ β
5
HUM
t
CAP
it
+ β
6
FOCAP
it
+ β
7
INT
t
+ β
8
EX
it
+ w
it
8 There is the potential for endogeneity between several of the right-hand vari-
ables and real value added. We carry out endogeneity t-tests for each right-hand side variable, in each case including 14 time dummies to eliminate the autocor-
relation problem.
16
The estimation results, reported in the working paper of Vu et al. 2007, do not indicate significant endogeneity, and so a two-stage least
squares method is not suggested.
17
We therefore estimate equation 8 using FGLS to correct for the built-in heteroskedasticity shown in equation 6.
Growth effects of FDI
We begin by examining aggregate effects of FDI. The results of FGLS estimations are given in Table 4. Panel 4.a presents results for Vietnam. Column 4.a.1
presents estimation of the benchmark empirical model, including only the control variables. The signs of the coefficient estimates generally fit our priors. In column
4.a.2 we add the FDI measure described above. The term enters with a positive and significant effect at the 1 level. An interaction of FDI with labor 4.a.3 also
yields positive and significant FDI effects, working indirectly through interaction with labor. Including both the level of FDI and the interaction term 4.a.4 does
not markedly change the magnitudes of estimated coefficients.
Panel 4.b presents equivalent results for the China data set. The signs of the coefficient estimates also generally fit our priors. Qualitatively, the effects of
FDI are very similar to those for Vietnam. For China, the estimated direct and indirect effects of FDI on growth are positive but smaller than those for Vietnam.
For China, when FDI is added to the regression models, estimated coefficients on
CAP fall markedly, from 0.3164 to an average of 0.15, whereas coefficients on LAB remain almost the same. This might reflect a ‘crowding out’ effect of FDI
on domestic capital formation in China. For the case of Vietnam, the opposite is true, consistent with the notion that the labor effect on growth in Vietnam is
largely related to technical transfers and spillovers from foreign companies. The impact we identified for aggregate FDI was statistically significant and
positive. It is possible that the aggregate results mask important differences in the effect of FDI on economic performance across individual sectors. Hence, we
perform regressions with sectoral slope dummies in addition to all of the previously discussed variables. The manufacturing sector is our base sector. In Tables 5 and
6 we report FGLS estimation results for all sectors. To interpret the effect of FDI on a sector, its coefficient is added to that of the manufacturing sector, and a test
for the significance of their sum is performed.
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553
Table 4. Aggregate effects of FDI on growth. Dependent variable is the growth rate of value added. 4.a.1
4.a.2 4.a.3
4.a.4 Panel 4.a. Results for Vietnam
FDI 0.0625 0.0211
0.0256 0.0132 FDI LAB
2.98e-5 8.26e-6 2.45e-5 1.23e-5
LAB 0.7021 0.3512
0.7246 0.3612 0.3069 0.1562
0.2164 0.1201 CAP
0.3142 0.1104 0.2513 0.1242
0.2487 0.0628 0.2515 0.1260
HUM CAP 0.2254 0.1126
0.2192 0.1084 0.1793 0.0902
0.1842 0.0935 FOCAP
0.1394 0.0631 0.1398 0.0687
0.1403 0.0701 0.1387 0.0642
EX 0.1296 0.0675
0.1303 0.0654 0.1289 0.0641
0.1293 0.0634 INT
− 0.1022 0.3123
− 0.1018 0.2546
− 0.1186 0.3167
− 0.1248 0.6287
Observations 126
126 126
126 Adjusted R
2
0.7124 0.7616
0.7693 0.7285
Prob F 0.0006
0.0008 0.0005
0.0009 4.b.1
4.b.2 4.b.3
4.b.4 Panel 4.b. Results for China.
FDI 0.0336 0.0164
0.0165 0.0082 FDI LAB
1.32e-06 3.48e-07 1.57e-06 4.05e-07
LAB 0.7103 0.1638
0.7238 0.2186 0.6954 0.0996
0.6832 0.1734 CAP
0.3164 0.0845 0.1472 0.0763
0.1523 0.0796 0.1486 0.0732
HUM CAP −
0.1426 0.2681 −
0.2453 0.3875 −
0.2713 0.3032 −
0.2435 0.3284 FOCAP
0.2984 0.0856 0.2854 0.1589
0.2823 0.1396 0.2869 0.0974
EX 0.1418 0.0712
0.1405 0.0701 0.1397 0.0678
0.1416 0.0706 INT
0.1186 0.1692 0.1296 0.1375
0.1149 0.1696 0.1372 0.1483
Observations 154
154 154
154 Adjusted R
2
0.7976 0.7849
0.7692 0.7739
Prob F 0.0012
0.0024 0.0026
0.0015
Notes: Standard errors are in parentheses. Significance levels are 10, 5, and 1 level.
554
T. B
. Vu
et al.
Table 5. Sectoral effects of FDI on growth in Vietnam. Dependent variable is the growth rate of value added. Reference group is manufacturing.
GFDI × D
i
FDI × GLAB × D
i
5.1 Regression 5.2 Sums of
5.3 Regression 5.4 Sums of
coefficients coefficients
coefficients coefficients
Manufacturing 0.0376 0.0182
0.0376 0.0182 3.58e-5 1.76e-5
3.58e-5 1.76e-5 Oil and Gas
0.0082 0.0039 0.0458 [0.009]
1.34e-5 6.21e-6 4.92e-5 [.008]
Food 0.0037 0.0335
0.0413 [0.027] 2.13e-6 1.02e-5
5.71e-6 [0.046] Construction
0.0029 0.0412 0.0405 [0.021]
1.43e-6 1.85e-5 2.15e-6 [0.029]
Transportation −
0.0213 0.0102 0.0163 [0.007]
− 2.62e-5 1.30e-5
9.60e-6 [0.038] Hotel Tourism
− 0.0247 0.0128
0.0129 [0.042] −
3.02e-5 1.43e-5 5.60e-6 [0.010]
Other Real Estates −
0.0269 0.0184 0.0107 [0.049]
− 3.21e-5 1.60e-5
3.70e-6 [0.048] Agriculture
− 0.0232 0.0118
0.0144 [0.002] −
2.65e-5 1.31e-5 9.30e-6 [0.041]
Other Services −
0.0372 0.0184 0.0004 [0.342]
3.52e-5 1.71e-5 6.00e-7 [0.235]
Observations 126
126 Adjusted R
2
0.7523 0.7493
Prob F 0.0013
0.0032
Notes: Specification is given in equation 8 with eight sectoral dummies added. Manufacturing is the omitted sectoral dummy the base dummy. The coefficient reported for manufacturing is the slope coefficient on GFDI or FDI×GLAB. Standard errors
are in parentheses, and p-values for the tests of summed coefficients are in square brackets. Significance levels are 10, 5, and 1 level. In Columns 5.1 and 5.3, significance levels are for the null hypothesis that an industry’s effect is the
same as that of the base sector, manufacturing. In Columns 5.2 and 5.4, significance levels are for the null hypothesis that an industry’s effect is not significantly differently from zero.
Journal of
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sia P
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555
Table 6. Sectoral effects of FDI on growth in China. Dependent variable is the growth rate of value added. Reference group is manufacturing.
GFDI × D
i
FDI × GLAB × D
i
6.1 Regression 6.2 Sums of
6.3 Regression 6.4 Sums of
coefficients coefficients
coefficients coefficients
Manufacturing 0.0673 0.0218
0.0673 0.0218 1.29e-5 6.52e-6
1.29e-5 6.52e-6 Mining and quarrying
− 0.0038 0.0018
0.0635 [0.031] 4.65e-7 6.34e-7
1.34e-5 [0.007] Electric, gas, and water
0.0043 0.0182 0.0716 [0.009]
4.12e-6 4.98e-6 1.33e-5 [0.043]
Construction 0.0082 0.0091
0.0755 [0.037] 3.98e-7 6.03e-7
1.33e-5 [0.039] Farming, forestry, and fishery
− 0.0398 0.0192
0.0275 [0.013] −
7.86e-6 3.60e-6 5.14e-6 [0.027]
Transport, post, and telecommunication −
0.0169 0.0082 0.0504 [0.024]
− 9.13e-7 4.52e-7
1.20e-5 [0.008] Wholesale, retail trade and catering
services −
0.0661 0.0312 0.0012 [0.462]
− 1.23e-5 1.54e-6
6.00e-7 [0.397] Real estates
− 0.0662 0.0063
0.0011 [0.237] −
1.24e-5 1.31e-6 5.20e-7 [0.325]
Social services −
0.0664 0.0340 0.0009 [0.145]
− 1.23e-5 6.12e-6
6.40e-7 [0.196] Health care, sport, and social welfare
− 0.0669 0.0334
0.0004 [0.328] −
1.27e-5 6.11e-6 2.30e-7 [0.243]
Education, culture and arts −
0.0548 0.0272 0.0125 [0.036]
− 7.65e-6 3.51e-6
4.60e-6 [0.045] Others
− 0.0672 0.0339
0.0001 [0.185] −
1.31e-5 1.64e-5 2.10e-7 [0.286]
Observations 154
154 Adjusted R
2
0.7843 0.7952
Prob F 0.0023
0.0014
Notes: Specification is given in equation 8 with ten sectoral dummies added. Manufacturing is the omitted sectoral dummy the base dummy. The coefficient reported for manufacturing is the slope coefficient on GFDI or FDI×GLAB. Standard errors are in parentheses, and p-values for the tests of
summed coefficients are in square brackets. Significance levels are 10 , 5 , and 1 level. In columns 6.1 and 6.3, significance levels are for the null hypothesis that an industry’s effect is the same as that of the base sector, manufacturing. In columns 6.2 and 6.4, significance levels are for the
null hypothesis that an industry’s effect is not significantly differently from zero.
556 T.B. Vu et al.
Columns 5.1 and 6.1 report the regression coefficients for the model without interaction terms, and columns 5.2 and 6.2 report the sums of these coefficients and
the manufacturing coefficient. Columns 5.3 and 6.3 present regression coefficients for the model with FDI-Labor interaction terms included, and columns 5.4 and 6.4
present the sums of these coefficients and the manufacturing coefficient. We find that the effect of FDI on growth is positive and significant for the manufacturing
sector in both China and Vietnam for both levels and interaction terms. The results also suggest that the effects of FDI on growth differ greatly across sectors.
For the primary industry agriculture for Vietnam, and farming-forestry- fishery for China, the effects are similar for the two countries: the effect is
still positive but the coefficients for these sectors are much lower than that of the manufacturing sector. For the secondary industries, the effects of FDI inflows on
growth are all positive for both countries. The coefficients are not significantly different from those of the base sector except in two cases: the coefficient for
the oil-gas sector in Vietnam is higher than that of the base sector, whereas the coefficient of the mining-quarrying sector including oil, gas, and coal in China
is significantly lower than that of the base sector.
For the tertiary industries, the results are mixed. For Vietnam, the effects on transportation and real estate including hotel-tourist sector and other real estate
sector are still positive but much lower than that of the base sector, and the effect on other services is not significantly different from zero. For China, the effect
on transportation is positive and only slightly lower than that of the base sector, whereas the effect on education-culture-art sector is still positive but much lower
than that of the base sector. The effects on real estates and all other service sectors are not significantly different from zero.
These results are not entirely surprising. First, we may expect capital-intensive sectors and ones in which technology plays a major role to exhibit a more positive
impact of FDI inflows on factor productivity. In addition, it may be much easier for firms in these externally-oriented sectors to overcome the peculiar institutional
rigidities that we discussed above and therefore benefit more from FDI inflows.
Conclusion
While most economists seem to agree that FDI is beneficial if perhaps still doubting the wisdom of government subsidies for investing multinationals, many
policymakers and, to a larger extent, NGOs appear much less sanguine. In this work, we have estimated the impact of FDI on growth in different economic sectors
using data from China and Vietnam. Using an augmented production function, we allow FDI to directly affect GDP growth and also to indirectly affect growth
through interaction with labor. The influence of FDI on labor is permitted to vary over time through an idiosyncratic disturbance, requiring a particular FGLS
estimation procedure. The results reveal that FDI has a significant and positive effect on economic growth in both countries. However, the effect is not equally
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Journal of the Asia Pacific Economy 557
distributed across sectors. In both countries, the secondary industries appear to benefit most from FDI inflows.
From a policy perspective, two observations appear to follow from these results. First, governments who want to subsidize FDI inflows may want to direct scarce
resources to secondary industries, and to manufacturing in particular. FDI into other sectors appears to yield much lower benefits and therefore its tax treatment
should potentially be less favorable. Besides tax policy, many other institutional arrangements assist or discourage the implementation of FDI projects. These
should also focus more on those industries for which we uncovered evidence in favor of FDI inflows.
Second, more resources should be directed toward understanding why the sectoral benefits that we identified appear and whether these patterns persist in
other geographical areas. Are these differences fundamental to industry types? To transition or post-Communist economies? Or is it a result of institutional barriers
to effective absorption of FDI in certain economic sectors? Are there government policies that might improve the ability of primary and tertiary industries to benefit
from FDI inflows?
The relatively small available data samples suggest caution in interpreting these results. More and better data and comparative work with sectoral data from
other countries are plainly needed. In addition, we have focused on the growth effect of FDI inflows. It would be useful to explore whether other types of capital
inflows – equity and foreign loans – also have differential growth effects across sectors, and whether they too show both direct and indirect impact on economic
growth.
Acknowledgments
The authors wish to thank audiences at the ACE conference in Hong Kong and the ASSA meeting in New Orleans and two anonymous referees for many insightful comments. All
remaining errors are ours.
Notes
1. With the availability of better data, the last few years have seen an especially large
number of empirical papers devoted to this question e.g., Alfaro et al. 2004, Bengoa and Sanchez-Robles 2003, Durham 2004, Hsiao and Shen 2003, and Li and Liu 2005.
2. For a critical look at these domestic taxsubsidy policies, see Hanson 2001 and Mooij
and Ederveen 2003. Gastanaga et al. 1998 analyze other host-country policies that aim to encourage FDI inflows.
3. The reasons for this are not entirely obvious. The ‘fire-sale’ FDI that followed the
large depreciations of 1997–98 was not sustained; the difficulties in the domestic financial systems of some of the target countries after 1998 and the worldwide slump
of 2001–2002 might all be possible explanations. 4.
Details for Vietnam can be found at http:www.vietnamlaws.comlegal updates.aspx. There are numerous sources for China. See, for example, http:www.chinatoday.com
lawa0.htm. 5.
See, for example, Tran 1997, and Do 1993.
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558 T.B. Vu et al.
6. Few countries received a 5. Examples for these are Zimbabwe, Turkmenistan, Sierra
Leone, Libya, and North Korea. For details see: http:www.heritage.orgresearch featuresindexdownloads.cfmscores.
7. A related channel is the ‘creative destruction’ hypothesis raised by Aghion and Howitt
1992. If the competition from the foreign investors results in the destruction of inefficient firms, the FDI effect will turn out to be positive.
8. Lensink and Morrissey 2006 arrive at a similar negative conclusion by including
FDI volatility measures in both cross-country and panel specifications. 9.
See Mukand and Rodrik 2005 for insights into this problem that are relevant to the policy-applicability of estimation results.
10. For a recent survey of wage and productivity spillovers from FDI see Lipsey and
Sj¨oholm 2005. 11.
See, for example, International Labor Office 1984, pp. 71–74. 12.
In Vu 2008, the accumulated stock of FDI is used instead of the inflow of FDI. For a discussion of time-varying coefficient models, see Griffiths et al. 1993, pp. 412–413,
and Greene 2003, pp. 132–133. 13.
Packard and Thurman 1996 suggest interaction terms for capital with several other variables: human capital, infrastructure, and research and development RD. In-
frastructure and capital are highly correlated, and data on RD by sector is not available for either country. Packard and Thurman 1996 also suggest an interaction
term of labor with human capital, but this would cause high multicollinearity with the labor–FDI interaction term, and so we do not add this additional interaction term.
14. This is a more accurate expression of Vietnamese and Chinese educational systems
than just secondary school enrollments. The secondary schools have to follow nation- ally drafted curricula, which focus heavily on political doctrine and abstract sciences.
This leaves the vocational, technical schools or worker training schools the responsi- bility of providing technologically skilled labor.
15. Since exchange rates did not change much for Vietnam during 1991–2003 and for
China during 1985–2004, we do not convert FDI data to local currencies. 16.
The endogeneity t-test is a form of the Hausman 1978 specification test. A right-hand side variable is treated as the instrument in a first-stage regression, and the resulting
error is introduced as a regressor in the second-stage regression. If the coefficient on this error term is significantly different from zero, this is taken as evidence of the
existence of endogeneity.
17. We have also performed Granger causality tests as described in Geweke et al.
1983.We regress the FDILAB variable on its own lags, GDP lags, and other vari- ables, using the FGLS estimation, and then test the significance of GDP lags. The t
statistics for individual lagged GDPs and p values of the F-statistic for jointly lagged GDPs are all insignificant. We fail to reject the null hypothesis of no reverse causality.
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Journal of the Asia Pacific Economy 559
Appendix . Data Definitions and Sources
Code Definition of Variable
Source Vietnam
FDI Actual FDI inflows per sector in millions
of 1994 US IMF Annual Reports on Vietnam;
deflated using the US GDP implicit deflator.
VAL Value added for each sector, in
Vietnamese Dong VND Vietnam Government Statistical Office
website and Vietnam Statistical Yearbook
CAP Accumulated investment in fixed assets
INV per sector VND Calculated from investment in fixed
assets INV per sector taken from the Vietnam Government Statistical
Office website and Vietnam Statistical Yearbook
LAB Labor per sector thousand workers
IMF-Vietnam Statistical Yearbook INT
3-mts. household saving rate IMF-Vietnam Statistical Yearbook
HUM School enrollments thousand pupils
Vietnam Government Statistical Office website and Vietnam Statistical
Yearbook EXPIM Exports and imports VND
IMF-Tho et al. 2000 COM
Number of telephones pieces Vietnam Statistical Yearbook
TRANS Volume of freight traffic million
tonskm, i.e., total weight multiplied by total length of roads
Vietnam Statistical Year book FOCAP Foreign aid as a proxy for foreign capital
in millions of 1994 US. IMF Annual Reports on Vietnam;
deflated using the US GDP implicit deflator.
China FDI
Actual FDI inflows per sector, in million of 1994 US
China Statistical Yearbook; deflated using the US GDP implicit deflator.
VAL Value added for each sector, in Chinese
Renmenbi RMB China Statistical Yearbook
CAP Accumulated investment in capital
construction INV per sector RMB Calculated from investment in capital
construction INV per sector taken from the China Statistical Yearbook
LAB Labor per sector thousand workers
China Statistical Yearbook INT
3-mts. household saving rate International Financial Statistics
IFS-China Statistical Yearbook HUM
School enrollments thousand pupils China Statistical Yearbook
EXPIM Exports and imports million US Dollars China Statistical Yearbook COM
Number of telephone subscriptions households
China Statistical Yearbook TRANS
Volume of freight traffic million tons.km, i.e., total weight multiplied
by total length of the roads China Statistical Yearbook
FOCAP Foreign aid as a proxy for foreign capital in millions of 1994 US.
IMF Balance of Payments Statistics; deflated using the US GDP implicit
deflator.
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560 T.B. Vu et al.
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Mainstreaming fisheries in development and poverty reduction strategies in the Asia-Pacific region
Chris Reid
a
; Andy Thorpe
a
; Simon Funge Smith
b a
Department of Economics, University of Portsmouth, Hampshire, UK
b
Regional Office for Asia and the Pacific, Food and Agriculture Organization of the United Nations, Bangkok, Thailand
Online Publication Date: 01 November 2008
To cite this Article Reid, Chris, Thorpe, Andy and Smith, Simon Funge2008Mainstreaming fisheries in development and poverty
reduction strategies in the Asia-Pacific region,Journal of the Asia Pacific Economy,13:4,518 — 541 To link to this Article: DOI:
10.108013547860802364794 URL:
http:dx.doi.org10.108013547860802364794
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Journal of the Asia Pacific Economy Vol. 13, No. 4, November 2008, 518–541
Mainstreaming fisheries in development and poverty reduction strategies in the Asia-Pacific region
Chris Reid
a
, Andy Thorpe
a∗
and Simon Funge Smith
b
a
Department of Economics, University of Portsmouth, Hampshire, UK;
b
Regional Office for Asia and the Pacific, Food and Agriculture Organization of the United Nations,
Bangkok, Thailand This paper offers an assessment of the mainstreaming of fisheries in na-
tional development plans and Poverty Reduction Strategy Papers within the Asia-Pacific region. Fisheries and aquaculture in the region make a signif-
icant contribution to world fisheries production. Importantly, those directly involved in the sector are predominantly small-scale artisanal producers, a
group traditionally regarded as extremely vulnerable in poverty terms. There- fore, mainstreaming – integrating a sector into every stage of the national
policy process – may have important welfare implications for those drawing livelihoods from the industry. This paper examines the significance of fish-
eries and aquaculture to developing Asia-Pacific economies, and evaluates the extent to which the sector has been mainstreamed in national development and
poverty reduction strategies using a content analysis framework. We conclude that the representation of fisheries issues, the recognition of sectoral poverty,
policy responses, and stakeholder representation, is typically greater than in other fish producing regions, and there are many examples of best practice.
Keywords: fisheries; poverty; Asia-Pacific; PRSP JEL Classifications: I38; O20; O53; Q22
1. Introduction
