Modern Economy, 2011, 2, 447-454
doi:10.4236/me.2011.24050 Published Online September 2011 (http://www.SciRP.org/journal/me)
Trade Intensity Spillover Effects on East Asian Sustainable
Economic Growth
Elsadig Musa Ahmed
Economics Unit, Faculty of Business and Law, Multimedia University, Melaka, Malaysia
Received January 26, 2011; revised March 15 , 20 1 1; accepted April 2, 2011
Abstract
This paper has included the exports and imports per unit of labour (trade intensity) in the intensive growth
model beside the traditional factors of production such as capital deepening to find out the contribution of
total factor productivity per unit of labour (TFP intensity) to the economic growth of the most significant
East Asian countries [China, Indonesia, Japan, South Korea (Republic of Korea), Malaysia, Philippines,
Singapore and Thailand]. This paper finds out that the impact of trade intensity is positive with little contri-
bution to TFP intensity growth with light contribution of labour productivity to these countries economic
growth. These findings showed that most of East Asian productivity is input driven without technological
progress to display the spillover effects of the interaction of foreign technology and human capital that
should be translated into technology transfer to local firms and advanced skills, with the exception of Japan
and South Korea.
Keywords: Trade Intensity, Sustainable TFP Growth, Spillover Effects, East Asian Economies
1. Introduction
East Asian region considered to be one of the most
growing regions in the world and open economies for
exports and imports activities around the globe. Thanks
to foreign direct investment (FDI) inflows that helped
these countries to grow faster than industrialised coun-
tries. However, this growth is considered to be input
driven rather than productivity driven growth based on
huge inputs that is used to produce outputs without pro-
gressing technologically and based on foreign multina-
tional national corpo rations (MNCs) investment form the
hyper markets to electronics products. Meanwhile, Japan
and South Korea had showed technical progress through
their MNCs that were competed internationally through
high quality products that had been accepted worldwide.
This means that the spillover effects of interaction be-
tween foreign technology and local human capital and
firms has taken place in Japan and South Korea, in this
regard, their productivity considered to be productivity
driven.
Moreover, Juthathip [1] explains that economic
growth in East and Southeast Asia since the early 1980s
has been underpinned by rapid expansion in manufac-
turing exports. The surge in exports of manufactured
goods during this period has been accompanied by a shift
in commodity composition. While the speed of adjust-
ment has varied, the countries in the region tended to
start with a focus on tech nologically simple labou r inten-
sive goods such as apparel and footwear, and then moved
to a range of more capital-intensive, technology courte-
ous items, especially electrical and non-electrical ma-
chinery. In addition, Juthathip [1] affirms trade liberali-
zation and investment policy reforms in developing
countries have significantly shortened barriers to trade
and investment, thus, further encouraging expansion and
dispersion of outward direct investment of multinational
enterprises (MNEs). The author points out that these
emerging patterns could have implications for the factors
that influence export performance. Then, reviewed the
work of Jones and Kierzkowski [2] and Arndt and Hue-
mer [3] have argued that a surge in intermediate goods
trade could dilute real exchange rate impacts as interme-
diate exports involve a high proportion of imported parts
and components and high fixed costs in establishing the
“service links.” However, Obstfeld [4] and Rauch and
Trindade [5] have argued that the increasing importance
of product fragmentation and of trade in parts and com-
ponents could induce stronger substitution responses as
the presence of production facilit ies in different co untries

E. M. AHMED 448
would allow firms to respond more quickly to interna-
tional price changes by shifting activities across bord ers.
Literature Review
In the issu e of trad e and techn ology tra nsfer, Bla lock and
Veloso [6] affirm that the internation al economics litera-
ture has had a lasting interest in the relationship between
trade and technology transfer (Keller, [7]; Saggi, [8];
Werner, [9]). It should be recalled, that early studies us-
ing aggregate country-level data suggest trade is an im-
portant driver of economic growth and these findings
have prompted a stream of research on firm-level mecha-
nisms that support these aggregate findings. The existing
research has mostly focused on two mechanisms: exports
by local firms and FDI by multinational firms.
Meanwhile, the majority of studies associate both
mechanisms with increases in productivity, although the
direction of the causality is still under scrutiny. None-
theless, much less effort has been devoted to the export
counterpart, imports, which are th e fo cus of this paper. In
particular, few studies have used firm-level data to ex-
amine imports as a mechanism for technology transfer
(Amiti and Konings, [10]; Fernandes, [11]; Keller and
Yeaple, [12]; MacGarvie, [13]; Muendler, [14]), and the
results so far have been mixed. Blalock and Veloso [6]
ask whether imports can improve firm technological ca-
pabilities, as measured by productivity gains. Using a
rich panel dataset on Indonesian manufacturers from
1988 to 1996, they examine factory productivity growth
and its relation to imports in downstream industries. Be-
sides, control for the potential endogeneity between im-
ports and productivity by conditioning on static industrial
sector and firm-level attributes and by considering only
import activity largely exogenous to the focal firm. Bla-
lock and Veloso [6] find strong evidence that firms sell-
ing to sectors that rely more on imports have greater
productivity growth than other firms. This finding is
consistent with the hypothesis that vertical supply rela-
tionships are an important mechanism through which
import-driven technology transfer occurs. Identifying
imports as a source of international technology transfer
adds a critical third component, along with exports and
FDI, to the argument that trade promotes economic
growth. In the case, of most of East Asian countries trade
hasn’t show the spillover effects of technology interac-
tions with local human capital and firms to transfer the
technology and skills to the host countries of FDI in-
vestment.
Total factor productivity (TFP) growth in place of the
centre of spillover effects of this interaction has long
been identified as one of the important sources of eco-
nomic growth in the western countries (Solow [15,16],
Abromovitz [17], Denison [18], Kim and Lau [19]. In a
study on sources of growth in nine western countries,
Denison [20] found that advanced knowledge, improved
allocation of resources and economies of scale accounted
for almost 60 to 90 percent of the growth in income per
capita, with factor inputs (labour, capital and land) ex-
plaining a relatively small percentage of the overall eco-
nomic growth. This implies that the growth of the West-
ern countries has been mainly driven by TFP growth
rather than the growth in factor inputs, or by what so
called productivity driven. This finding is supported by
another recent study conducted by Kim and Lau [19],
who find that almost 45 to 70 percent of the economic
growth in five of the Organization for Economic Coop-
eration and Development (OECD) countries was con-
tributed by productivity growth. This growth phenome-
non is somewhat different from the growth pattern ob-
served in the East Asia Newly Industrialized Countries.
Studies indicated that the growth of these countries has
been mainly input-driven through massive factor accu-
mulation rather th an productivity driven (Young [21,22],
Krugman [23], Kim and Lau [19], Young [21], for ex-
ample, finds that over the period of 1966-1990 produc-
tivity growth in the aggregate non-agriculture economy
ranges from as low as 0.2 percent in Singapore to a high
of only 2.3 percent in Hong Kong, whereas in manufac-
turing productivity ranges from a low of 1.0 percent in
Singapore to a high of only 3.0 percent in South Korea
(Elsadig [24]).
[1] In conclusion of this section, the sustainability of
economic growth will be highly dependent on the inter-
action of technology and human capital that is will ap-
peared in the form of TFP or technical progress. That is
measuring the relationship between output and its total
inputs (a weighted sum of all inputs), which represent the
residual output changes not accounted by total factor
input changes. Being a residual, changes in TFP are not
influenced by changes in the various factors which affect
technological progress such as the quality of factors of
production, flexibility of resource use, capacity utilisa-
tion, quality of management, economies of scale, and the
like (Rao and Preston, [25]). In addition, it has been
documented in empirical work on economic growth by
Solow [15,16], that after accounting for physical and
human capital accumulation, “something else” accounts
for the bulk of output growth in most countries. Both
physical and human capital accumulations are certainly
critical for economic growth. This is should be the com-
bined contribution of inputs used in the production ac-
tivities.
Additionally, the process becomes more complicated
with the role of knowledge in the economic growth
process. Knowledge obviously accounts for a part of the
growth that is not accounted for by the other factors of
production; namely capital a nd labour. In growth theory,
the Solow residual is an unexplained residual of labour

E. M. AHMED449
and capital and it is attributable to the growth of TFP.
The notion of TFP is interpreted as an “ind ex of all those
factors other than labour and capital not explicitly ac-
counted for but which contribute to the generation of
output.” TFP refers to the additional output generated
through enh ancements in the efficiency accounted for by
such things as advancement in human capital, skills and
expertise, acquisition of efficient management tech-
niques and know-how, improvements in an organisation,
gains from specialisation, introduction of new technol-
ogy, innovation or upgrading of present technology and
enhancement in Information and Communication Tech-
nology (ICT), (Elsadig [24], [26] and [27]). The TFP is
the indictor of technological progress expresses through
the interaction between physical and digital technologies
with human capital to make the differences between the
countries and firms development based on the quality of
human capital that is called the spillover effects which
transfer the technology, the process and skills.
Moreover, Madsen [28] states that from the time when
the influential paper of Solow [15], it has been known
that technological change has been an important factor
behind the increasing labour productivity that has been
experienced over the past century; see also Prescott [29]
and Hall and Jones [30]. However, very little is known
about the importance of ideas for growth in TFP, the
international diffusion of ideas, the origin and the direc-
tion of the flow of ideas since the second industrial
revolution, and whether the spillover of ideas has de-
terred or contributed to TFP convergence among the in-
dustrialized countries. In the Solow [15] model techno-
logical progress is exogenous and, as such, technological
knowledge is a free good, i.e., it is free of charge and
accessible to everybody. Solow did not discuss the im-
plications of this for international knowledge spillovers;
however, subsequent research in the neoclassical tradi-
tion has suggested that technological knowledge is freely
available internation ally; for a discussion of these issues,
see Fagerberg [31].
It should be mentioned, that none of the exiting re-
viewed studies has used labour productivity approach
(intensive growth theory) to address the impact of trade
on productivity growth. Economists are more interested
in intensive growth, which is expressed as growth in
output per worker (labour productivity). Moreover, an
economy’s standard of living is not determined by its
total output but by the amount of output available per
person (Dollar and Sokoloff [32], Elsadig [24,26,27]).
This study aims to investigate the role of decomposition
of labour productivity growth into contributions of capi-
tal deepening, increased usage of trade intensity, and the
simultaneous contribution of the quality of these factors.
This has expressed as the contribution of TFP intensity
growth in accomplishing productivity driven growth in
these economies and showing the spillover effects of the
technology interaction with human capital.
This paper gives details as follows. Section 2 contains
descriptions on the estimation methods employed in this
paper, Section 3 demonstrates details of the data. Results
of the empirical analysis are explained in Section 4. Fi-
nally, Section 5 presents the concluding remarks and
recommendations.
2. Methods and Estimation
In this paper, an attempt is made to apply the conven-
tional growth accounting framework developed. These
include results achieved by Solow [15,16], which finally
brought to fruition by Kendrick [33,34] and further re-
fined by Denison [19], Denison and Edward [35],
Griliches and Jorgenson [36], Jorg enson et al. [37], Dol-
lar and Sokoloff [32] and Elsadig [24,27].
The production function for economies can be repre-
sented as follows:


,,,,,,,,,GDPtiFKt i Lt i EXPt i IMPt iTt i,, (1)
where fo r Country 1,2,, 8i

 in Year 1965-2006,
the output is annual real GDP, and the inputs are; real
fixed physical capital K, number of persons employed
(human capital) L, Exports EXP, Imports IMP and time T,
that proxies for total factor productivity (TFP) as a tech-
nological progress of the countries and an indicator of
spillover effects.
t
The Divisia Index basically decomposes the aggregate
output growth into the contribution of changes in inputs
(such as aggregate capital, labour, exports and imports
growth), and TFP growth. This calculates the productiv-
ity indicators to show the reliability of the results gener-
ated without considering statistical analysis (Mahadevan
[38]).
The paper attempts to fill this gap by developing the
model below into a parametric model and providing its
statistical analysis in the first step as follows;
ln,.ln,.ln ,.ln,
.ln, ,
GDPt iaKt iLt iEXPt i
IMPt it i





 , (2)
(t

1965-2006)
where

is the output elasticity with respect to cap ital,

is the output elasticity with respect to labo ur,

is the output elasticity with respect to expo rts,

is the output elasticity with respect to imports
a is the intercept or constant of the model1,

is the residual term2,
1The intercept term, as usual, gives the mean or average effect on de-
p
endent variable of all the variables excluded from the model.
2The residual term proxies for the total factor productivity growth that
accounts for the technological progress of the economy through the
quality of input terms.

E. M. AHMED 450
ln is the logarithm to transform the variables.
Following Dollar and Sokoloff, [32], Wong [39],
Felipe [40] and Elsadig [24,27]; when constant returns
(1 )

  to scale is imposed, Equation (2)
becomes;
ln,. ln,.ln,.ln,
(1).l n,,
GDPti aKtiEXPItiIMPti
Lt it i


 
 
 
(1965-2006) (3)
t
For the purposes of this paper, Equation (3) is trans-
formed by dividing each term by L (labour input) and
then the output elasticity is calculated with respect to
capital deepening, exports and imports intensities, i.e.,

,

and

, respectively becomes;
 


ln/,. ln/,
.ln/ ,
ln/ ,,
GDPLt ibKLt i
EXPL ti
I
MPLt it i






 
(4)
Then, it follows that

ln/ ,GDPLt i

is the contribution of labour pro-
ductivity (outpu t per worker),

ln/, ,
K
Lti   is the contribution of Capital deep-
ening,

ln/ ,EXPL t i   is the contribution of the exports
intensity,

ln/ ,
I
MPL t i   is the contribution of imports in-
tensity
,ti

is the residual term that prox-
ies for TFP intensity growth,

ln/ ,TFPLt i
 is the difference operator denoting proportionate
change rate.
To calculate the average annual contribution growth
rate of the TFP intensity and labour productivity as well
as the contribution of the capital deepening, exports in-
tensity and imports intensity, as the intercept (b) has no
position in the calculation of the productivity growth rate
Equation (4) becomes
 
 
ln/,ln/,.ln / ,
.ln/,ln/,
TFPLti GDPLtiKLti
EXP LtiIMP Lti



 


 
(5)
Thus, Equation (5) expresses the decomposition of la-
bour productivity g rowth into the contributions of capital
deepening, increasing usage of exports and imports per
unit of labour (trade intensity), and the simultaneous
contribution of the quality of these factors. This is ex-
pressed as the TFP intensity growth.
3. Data Sources
The data for this paper were collected from various sec-
ondary sources. Real GDP, real aggregate fixed capital,
number of employment, exports and imports were col-
lected from Asian Development Bank: Key indicators of
developing Asia and Pacific countries, Statistical and
Data Systems Division, and international financial statis-
tics of International Monetary Fund, online database. As
well as from the individual countries databases, World
Development indictors of the World Bank and the Inter-
national Labour Organization for the period of 1965-
2006. Due to lack of data on man-hours of work, the la-
bour input index is constructed based on the number of
persons employed which is considered to be very sig-
nificant proxy of human capital when spillover effects is
addressed. Moreover, following Mahadevan [41] GDP is
adjusted to exclude the components of trade, both ex-
ports and imports shares are found to have an out-
standing influence on GDP growth. These feedback links
are further strengthened by two-way relationship be-
tween the growth of imports and exports. It has been
documented in literature (Mahadevan, [41]), that a high
level of intra-industry trade is associated with imports
and exports moving together (Bernard and Jensen, [42]).
4. Results and Discussion
In this paper, autoregressive estimator has been applied
to Equation (4) of the modified model that is generated
from Cobb-Douglas production function to measure the
shift in the production functions of ASEAN 5 plus 3. An
annual time series data over the period of 1965-2006 for
GDP, aggregate physical capital, number of employment,
exports and imports have been employed for the indi-
vidual countries.
Meanwhile, analysis of the data using Equation (4) has
shown that most estimated coefficients of the explana-
tory variables of the model mainly are significant at 5%
and 10% levels. According to Durbin-H values the model
has no problem of autocorrelation Table 1. In addition,
the adjusted and t-values do not indicate multicol-
linearity in the model Table 1. Meanwhile, the model
used in this paper has been specified in first differences
and the calculated growth rates and contribution of the
productivity indicators were used in the discussions of
results and findings of the study, the model is found to be
stationary. This found to be consistent with the statement
of Engle and Granger [43] of noble prize honour, that if
economic relationships are specified in first differences
instead of levels, the statistical difficulties due to non-
stationary variables can be avoided because the differ-
enced variables are usually stationary even if the original
variables are not.
2
R
Empirical Analysis
In this paper, empirical analysis was carried out to com-
pare the productivity indicators between 8th East Asian

E. M. AHMED 451
economies for the entire period of 1965-2006. In order to
study the effect of governments’ policies in improving the
productivity growth, the study period was divided into two
phases. These phases, which corresponded to the major
policy changes, were 1965-1987; 1988-2006. The period
of the 1960s; and 1970s witnessed the labour driven poli-
cies in these countries and the birth of new era of ex-
port-oriented economies. The decades of 1980s, 1990s and
2000s saw a further diversification of the economies of
these countries into more advanced industries through
investment driven policies and trade liberalisation that had
attracted foreign direct investment (FDI) which brought to
these countries through Transnational Corporations
(TNCs), investment. As a result of these polices the range
of economic activities and sources of growth had become
more diversified. Furthermore, during these decades, the
economic structural transformation took place in most
economies of these countries. The manufacturing sector
became the engine of growth in these countries in the
structural transformation periods. Finally, it includes the
period of 1988-2006, i.e., was the period of pre and post
the Asian financial crisis of 1997. Meanwhile, the service
sector has taken the role of manufacturing as an engine of
growth recently in most of these countries and has con-
tributed significantly to these economies.
Accordingly, the contribution of TFP per worker (in-
tensity) growth (as indicator of spillover effects of the
interaction of technology brought by FDI and trade with
human capital) to the economies of these countries in
terms of average annual productivity growth was little
Table 2. The highest contribution of labour productivity
by including trade intensity in the model to the produc-
tivity growth of the selected 8th East Asian countries was
the contribution of the sub period of 1988-2006 in most
countries under study Table 2. In addition to the contri-
bution of labour productivity to the productivity growth
of the economies of these countries was high also during
the sub-period of 1965-1987 Table 2. The sub-period of
1965-1987 was found to be a combined period of labour
and investment driven policies. On the other hand, the
sub period of 1988-2006 was the perceived period of
investment driven. As a result the performance of the
economies of these countries was rapid compared with
the period before the transformation of these economies
into investment driven that supported by FDI as the
source of exports, imports and direct ph ysical and digital
capital investment in most of these countries. The TFP
intensity growth contributed very little and the labour
productivity was not the uppermost to contribute to these
economies productivity growth. The reasons behind that
were the economic recession of 1973, 1985 and the fi-
nancial crisis of 1997 and the quality of human capital
and the technology involved in the production of the
majority of these economies. Consequently, the spillover
effect of inter action of technology and hu man capital has
played insignificant role in transferring the technology to
the local firms and upgrading the skills of human capital.
Besides, the highest contribution of capital deepening
to labour productivity in terms of average annual produc-
tivity growth of the ASEAN 5 plus 3 was during the
sub-period of 1988-2006 for most of the countries under
study. Similarly, the contribution of trade intensity (ex-
ports and imports per unit worker) to labour productivity
in terms of average annual productivity growth of these
countries was light during all the periods of the study
Table 2.
Table 1. Estimated Coefficients of ASEAN 5 + 3, 1965-2006
Country Intercept Capit a l D eepeningExport IntensityImport IntensityAdjustedR2 D-H
1. China 0.05
(1.57) 0.68 (7.88)** 0.12 (2.69)** 0.20 (1.30) 0.92 0.39
2. Indonesia 0.12
2.77)** 0.40 (1.86)* 0.32 (1.52) 0.28 (1.83)* 0.93 –0.92
3. Japan 0.07
(2.84)** 0.46 (13.7)** 0.34 (6.05)** 0.20 (4.42)** 0.91 0.42
4. Korea 0.17
(3.98)** 0.63 (2.76)** 0.20 (1.7) 0.17 (1.65) 0.94 0.98
5. Malaysia 0.13
(1.60) 0.57 (1.60) 0.23 (3.77)** 0.20 (1.61) 0.92 0.87
6. Philippines 0.20
(7.82)** 0.59 (11.7)** 0.22 (2.82)** 0.19 (2.31)** 0.96 0.30
7. Singapore 0.55
(0.65) 0.45 (4.76)** 0.28 (1.61) 0.27 (1.14) 0.93 0.17
8. Thailand 0.15
(3.08)** 0.55 (3.42)** 0.26 (3.63)** 0.19 (–0.80) 0.95 0.45
Notes: Figures in parentheses are t-values; ** Significant at 5% level; * Significa nt at 10% level; Figures in Table 1 were estimated using Equation (4)

E. M. AHMED 452
Table 2. ASEAN 5 + 3 Productivity Indicators (in percentage)
Country Labour Produ c t iv i t y Capital DeepeningExport IntensityImport Intensity TFP
Intensity
1. China
1965-2006
1965-1987
1988-2006
5.53
4.68
6.52
4.64
3.73
5.70
7.88
6.93
8.99
7.85
6.93
8.93
0.56
0.63
0.48
2. Indonesia
1965-2006
1965-1987
1988-2006
5.25
8.80
5.47
9.32
8.21
10.6
8.9
7.28
10.8
8.88
7.31
10.6
1.23
1.32
1.13
3. Japan
1965-2006
1965-1987
1988-2006
6.95
6.68
7.26
6.26
6.03
6.53
5.74
5.48
6.03
5.66
5.41
5.94
0.74
0.70
0.77
4. Korea
1965-2006
1965-1987
1988-2006
6.63
6.71
7.10
11.8
11.8
11.8
11.7
11.6
11.9
11.9
11.9
11.8
1.56
1.94
1.12
5. Malaysia
1965-2006
1965-1987
1988-2006
4.79
5.84
6.02
10.2
12.2
12.3
18.7
23.0
13.7
18.5
22.8
13.5
1.16
2.01
1.90
6. Philippines
1965-2006
1965-1987
1988-2006
6.88
6.27
7.59
5.03
4.19
6.00
5.31
4.10
6.70
5.44
4.27
6.79
1.91
2.14
1.62
7. Singapore
1965-2006
1965-1987
1988-2006
6.54
6.21
6.62
13.2
12.5
14.0
15.1
14.2
16.1
15.3
14.6
16.1
0.48
0.52
0.43
8. Thailand
1965-2006
1965-1987
1988-2006
5.50
6.09
6.28
6.06
5.38
6.85
6.14
5.14
7.30
6.24
5.33
7.30
1.43
1.83
0.98
Note: Figures in Table 2 were calculated using E quation (5).
Ultimately, the contribution of the trade intensity was
the utmost among the input terms during all periods of
the study, apart fro m the entire period. By examining the
role of trade intensity to achieve productivity driven
economies through TFP per unit of labour growth, it was
found from the results that there was a positive contribu-
tion of trade intensity to TFP per unit of labour growth in
the 8th East Asian economies.
This reflects the role of comparative advantage in un-
skilled labour intensive that eventually helped to attract
FDI in the latter half of the 1980s that intensifies the
trade activities in these open economies. These countries
have accelerated trade liberalisation policies and drasti-
cally eased restrictions with respect to capital ownership
of foreign companies. That fostered the significant in-
crease of global capital. In addition, FDI in terms of ex-
ports and imports as the source of technology transfer to
these countries through TNCs investment. It should be
recalled, that the majority of these economies are highly
reliant on the exports and imports activities by TNCs.
Nonetheless, this contribution of productivity indicators
considered to be an input driven economic growth with-
out significant spillover effects by looking to the contri-
bution of TFP per unit of worker as an indicator of spill-
over effects.
5. Concluding Remarks and
Recommendations
This paper claims to fill in the gaps of previous studies
by developing applications of intensive growth theory
and including the exports and imports per unit of worker
(trade intensity) in this model to find out the effect of
TFP intensity (TFP per unit of labour) of these countries
in transferring the technology and upgrading the skills of
human capital what so called the spillover effects. In
addition, provides a statistical analysis in the first step of
the estimation to reach the coefficients of the explanatory
variables that have been used by econometric approach.
It can be restated here that in addition, a second step that
plugs the parameters of the variables into the model in
order to compute the contribution rates of productivity
indicators including the calculation of the residual of the
model (TFP intensity) and labour productivity contribu-
tions being used by growt h accountin g app ro ach.
The paper finds that the impact of trade intensity is
positive with little contribution to TFP intensity growth.
These findings are in line with Mahadevan [41], and

E. M. AHMED453
Robert and David [44] findings; both find that TFP
growth has no significant effect on exports or imports
growth in some of these countries such as (Japan, Korea
and Malaysia). Though, their findings should be put in
the precise concept that trade intensity has no significant
contribution to the TFP intensity of these countries. TFP
is measuring the relationship between output and the
quality of its total inputs (a weighted sum of all inputs),
by this means giving the residual output changes not ac-
counted by total factor input changes. Being a residual,
changes in TFP are influenced by changes in the various
factors which affect technological progress such as the
quality of factors of production, flexibility of resource
use, capacity utilisation, quality of management, econo-
mies of scale through the quality of inputs not the quan-
tity of the inputs. In this regard, the spillover effects
which are viewing the interaction between technology
and human capital will take place through TFP intensity
contribution to display the technological progress of the
economy brought to the local firms and skills upgrading
of the local human capital.
These results also confirm that trade intensity had a
very significant role in achieving light labour productiv-
ity contribution that is produced by these economies
through using huge input to produce output. Apprecia-
tion to FDI that is helped the manufacturing sector to
become the engine of economic growth instead of agri-
cultural sector when economic structural transformation
took place at most of these economies and recently the
service sector has over taken the manufacturing sector
role to be the engine of growth in most of these countries.
Unlike other Eastern Asian nations Japan model that is
followed by South Korean model had constructed com-
panies such as Daewoo, Samsung and LG, those com-
peted globally side by side with their Japanese counter-
parts in the automobile and electronics and electrical
industries and products. This indicates the spillover ef-
fects that took place in Japan and South Korea through
technology transfer and human capital skills upgrading
that translated their products to high quality products and
their ability to compete and led the global markets. In
addition to their companies to led the foreign direct in-
vestment in East Asia and the rest of the world.
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