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THE ROLE OF HUMAN CAPITAL IN MALAYSIA’S ECONOMIC DEVELOPMENT
Gopi Krishnan, Santha Chenayah Ramu and Rajah Rasiah (Crude Draft)
Faculty of Economics and Administration
University of Malaya
Abstract: This paper examines the impact of human capital on economic development using
Malaysia as an example. The evidence shows that Malaysia’s economic growth among the upper
middle income countries has been driven considerably by resource exports. The country has not
demonstrated strong human capital and innovation capabilities relative to countries classified among
the upper middle income countries. Malaysia’s share of R&D scientists and engineers per million
persons fell significantly short of South Korea, Taiwan, Singapore and China, which to a large extent
explains why it has not followed the growth trajectory of the latter countries to become developed.
The evidence suggests that efforts must be taken to raise the quality of human capital produced in
the country, and to attract more vigorously Malaysians carrying tacit knowledge to lead critical
human capital producing organizations.
Keywords: Human capital, education, economic development, structural change, Malaysia
1. Introduction
For a number of decades Malaysia was heralded as a model of economic development for other
countries to emulate (World Bank, 1993). Since the late 1990s, however, the onset of premature
deindustrialization has cast a different light on the Malaysian experience. While some economists
have focused on a rapidly cooling manufacturing sector others have pointed to the lack of human
capital as the prime reason over the slowdown.
The aggressive promotion of export processing zones since 1972 assisted industrialization to
stimulate structural change in Malaysia with manufacturing overtaking agriculture in terms of sectoral
contribution to become Malaysia’s leading sectoral contributor to GDP since 1984 and since 1988
(Malaysia, 2000). Foreign direct investment (FDI) helped make Malaysia a major exporter of the light
manufactured goods of electronics and clothing since the 1980s. Domestic firms became the prime
driver of processed vegetable oils and fats exports from the 1980s.
Massive inflows of FDI into the manufacturing sector also caused serious tightening of the labor
market by the mid-1990s (Mohamad Ariff, 1991; Rasiah, 1995). The focus of industrial policy shifted
towards industrial deepening as the government attempted to take advantage of low unemployment
levels (which reached 2.7 percent in 1995) to stimulate structural change into high value added
activities. Following the introduction of the Way Forward initiative by the government in 1991 targeted
at making Malaysia a developed economy by 2020, a series of instruments were introduced to
promote industrial deepening, alongside the Action Plan for Industrial Technology Development
(APITD) of 1990 (Malaysia, 1991).
Unfortunately, institutional weaknesses restricted the Malaysia’s capacity to stimulate structural
change from low to high value added activities. The most fundamental shortcoming was the inability
of the government to produce quality human capital from the expansion in tertiary education, as well
as, to make its brain programme successful in attracting its diaspora embodied with tacit knowledge
from abroad. The growing shortage of human capital since 1990 forced firms to import foreign labour.
Unfortunately, the prime target of firms to sustain their operations was low skilled labour, which
aggravated the situation by reducing the pressure to upgrade (Rasiah, 1995; Henderson and Phillips,
2007). Hence, while South Korea, Taiwan and Singapore have successfully evolved a critical mass of
human capital to spearhead sustain structural change from low to high value added activities,
Malaysia has remained entrenched among the upper middle income countries.
Therefore, this paper seeks to examine the contribution of human capital to Malaysia’s economic
development. The rest of the paper is organized as follows. The next section discusses the main
theoretical arguments on human capital and economic growth. Section three discusses the
methodology and data used in the paper. The subsequent section examines the relationship between
human capital and economic growth of Malaysia relative to other upper middle income countries.
Section 6 analyzes the relationship between scientific output and economic development. Section 7
discusses the impact of changes in tertiary education on economic growth. The final section finishes
with conclusions and policy implications.
2. Literature Review
The role of human capital in economic development has been discussed by a wide range of theories.
The dominant mainstream approach has its roots in Solow’s (1956) neoclassical production function
model. This approach assumed greater significance following Romer (1986) and Lucas (1988)
attempt to differentiate capital and labour so as to endogenize the influence of technology on
economic growth. Whereas in the original Solow model the residue term included both productivity
and technology, the Solow-Romer model is considered to have reduced the residue to total factor
productivity as human capital and machinery and equipment is introduced as a factor of production.
Using the neoclassical framework Barro found in a sample of 100 countries over the period 1965-95
human capital to have influenced positively economic growth. Engelbrecht (2003) found the same
results on a sample of the Organization of Economic Cooperation and Development (OECD)
countries. Meanwhile, Jorgenson and Fraumeni (1992) found 61% of the growth. Jorgenson and
Fraumeni (1992) observed that 61% of economic growth of US from 1948 to1986 was accounted by
human capital. Using 98 countries and 1985 data, Mankiw et. al. (1992) found human capital to
explain 49% of economic growth of these countries. However, Hall and Jones (1999) only found 22%
of the economic growth of 127 countries in 1988 accounted for by human capital.
The development of the neoclassical framework for estimating the contribution of labour (including
human capital), capital and total productivity to economic growth has been a significant contribution to
our understanding of growth dynamics. However, this framework does not take account of phases in
economic development, and in that sense is not consistent with the incremental capital output ratio
(ICOR) advanced by Harrod and Domar. The latter considers higher ICORs as essential for the less
developed
economies
compared
underemployment of resources.
to
the
more
developed
economies
as
they face
the
The neoclassical framework also does not take account of the quality of the human capital involved.
By focusing on markets the approach discourages active state intervention by claiming that markets
would adjust supply responses to ensure demand-supply equilibriums. While the market clearing
argument helps reduce the probably of shortfalls between supply and demand because human capital
is easily prone to market failure – long gestation period involved and poor ability to judge potential ex
ante employment and the fact that humans can also consciously seek to underperform if better
options arise elsewhere. Hence, economies, such as, Japan, Korea and Taiwan launched deliberate
human capital development policies to spearhead structural transformation and economic growth in
these countries.
Vogel (1991) discussed at length policies introduced by the governments of Japan, Korea and Taiwan
to expand the supply of upper secondary and tertiary educated and technical qualified personnel with
a strong focus on science and technology disciplines. Saxenian (2006) advanced this further with the
efforts of these governments to attract back from the developed countries citizens embodied with tacit
knowledge. Several others have documented evidence of how the return of the diaspora helped
support technological catch up in key high technology industries (****).
Hence, instead of choosing a panel country study of to estimate the influence of human capital on
economic development, we choose the middle income country of Malaysia to examine on the one
hand its influence on the country’s economic growth, and two, to examine changes in the composition
of the different education levels, and three, to assess quality issues in education.
3. Methodology & Data
The paper uses descriptive statistics and scatter plots to study the role of human capital in explaining
the economic development in Malaysia. While the focus of the study is on the Malaysian case, we
used aggregated data which are differentiated based on income level as a comparison against the
position of Malaysia’s Human Capital development. The data was compiled from World Development
Indicators provided by the World Bank. The time series cover from 1996 to 2011. Income
classification is based on the World Bank Atlas Method.
4. Human Capital and Innovation
The role of human capital in developing innovation capabilities is well documented in the past (refers
to litireature review). For this study, we use R&D personnel and tertiary enrolment as a proxy to
explain human capital. Table 1 shows that mean of R&D personal and tertiary enrolment is higher in
the High-Income economy than in the upper middle income countries. While Malaysia is classified as
Upper-Middle Income nation, the mean of R&D personal and tertiary enrolment is lower than its
peers. As a result, innovation output (i.e. Scientific journal articles, trademark and patent application)
are lower than the mean of the Upper-Middle income countries.
Interestingly, Malaysia spent more resources on R&D activities than its peers. Nevertheless, the
effectiveness of R&D spending remains uncertain. The data suggest that weakness in human capital
development may explain the ineffectiveness of R&D spending. This was in line with other studies
performed in Malaysia in the past. Quality of human capital remains the major obstacle for investment
climate in Malaysia (World Bank, 2010). Moreover, Rasiah (2011) found a lack of connection between
firms and organisations that entrusted for knowledge creation affecting the firm’s performance
negatively.
Hence, spending on R&D activities, doesn’t guarantee higher innovation output, especially when the
economy is lacking of human capital to drive the innovation activities.
Table 1: Descriptive Statistics (1996-2010)
Mean
Median
Maximum
Minimum
Std. Dev.
Innovation Input
RDP
TERTIARY
RDEX
793.2
34.4
0.6
737.3
31.1
0.5
2131.1
67.6
1.8
71.7
5.1
0.1
521.3
15.5
0.3
Mean
Median
Maximum
Minimum
Std. Dev.
3516.2
3154.3
8003.5
1144.6
1609.5
62.9
61.7
101.8
20.1
15.3
1.9
1.8
4.1
0.5
0.9
Mean
Median
Maximum
Minimum
Std. Dev.
706.0
499.5
1642.7
152.8
548.3
30.7
30.0
37.1
21.8
5.3
0.7
0.7
1.1
0.4
0.3
Upper Middle Income
Innovation Output
SCJ
TM
PAT
6092.3
81921.5
12761.2
1544.9
19790.0
682.0
89894.4
1388399.0
415829.0
33.9
2873.0
2.0
14738.6
198238.4
51650.1
High-Income OECD
18377.8
40774.7
29844.6
5133.1
17754.0
1972.0
209898.0
304129.0
384201.0
142.6
2095.0
18.0
35695.5
52732.3
79829.2
Malaysia
961.5
22247.1
681.4
724.1
24049.0
531.0
2092.2
28833.0
1234.0
387.1
14876.0
193.0
596.4
4787.9
421.8
Economic Progress
GNI
4699.2
3993.4
10806.4
834.1
2417.1
27729.6
25310.0
86850.0
3760.0
15492.1
5367.4
5587.7
6364.1
4175.8
791.6
Note: RDP - Researchers in R&D (per million people); Tertiary – Tertiary school enrolment (% gross); RDEX Research and development expenditure (% of GDP); SCI - Scientific and technical journal articles; TM – Total
trademarks; PAT – patent applications by residents; GNI – GNI per capita (current US$) (change this to
constant)
Source: Data Compiled from World Bank
5. Human Capital and Economic Development
The role between human capital and economic development is well established by both neo-classical
and evolutionary scholars. Economy with stronger human capital development tends to enjoy benefits
of higher income growth. Figure 1 and 2 shows this relationship where the regression line is positive
for both, Upper-Middle income countries and High-income OECD countries. However, the differences
between these two Figures are the slopes, and distance between data and the regression trend line.
The role of R&D personal in explaining GNI growth is weaker in the Upper-Middle Income countries
compared to the High-income countries. This is reflected from an almost flat regression line in Upper-
Middle income countries compared to positive relationship with the High-income countries. Hence,
income growth in Upper Middle Income countries could present despite the weaker human capital
position, but conversely, human capital development is essential for income growth in the Highincome economy.
This could explain why Malaysia still have enjoyed higher GNI per Capita mean compared to UpperMiddle income average despite having a weaker human capital and innovation performance (see
Table 1). We therefore suggest the income growth could be driven by non-innovative economic
activities, e.g. mining and quarrying and traditional agricultural activities as global commodity prices
strengthen. Nonetheless, further in-depth study is recommended to confirm this relationship.
Figure 1: Upper Middle Income: Relationship between R&D Personal and GNI Per capita
9.5
9.0
LNGNI
8.5
8.0
7.5
7.0
6.5
3
4
5
6
7
8
LNRDP
ln= natural log
Figure 2: High-Income OECD: Relationship between R&D Personal and GNI Per capita
11.5
11.0
LNGNI
10.5
10.0
9.5
9.0
8.5
8.0
6.8
7.2
7.6
8.0
8.4
8.8
9.2
LNRDP
ln= natural log
6. Scientific Output and Economic Development
Scientific output expressed the effectiveness of human capital development and other formed of
innovation inputs. A larger number of innovation inputs do not necessarily translated into higher
innovation output, especially when the quality of inputs is lower and the resource allocation to develop
innovation capabilities may not be targeted correctly due to policy failure.
Hence, income growth is not only a function of innovation input (human capital) but also the role of
innovation output (Scientific Output). Countries with a balance of both tend to enjoy greater economic
benefits. Figure 3 shows that High-income economies tend to have both equal development between
human capital and scientific output.
In the case of Malaysia, the ratio of scientific output over R&D personal is very low. In fact the ratio
resembles the countries in lower middle income compared to its current position as an upper middle
income nation. Besides, Malaysia envisaged becoming a high-income nation by 2020. The present
condition of its human capital and scientific output is not encouraging. Hence, Malaysia’s policy
makers have to revisit human capital and innovation policy to ensure the country’s progression
become a high-income nation by 2020 is a reality.
Figure 3: Scientific Outputs/R&D Personal Ratio and GNI per Capita, 2010
20
$4,085
18
$12,616
BRA
High Income OECD
Scientific Journal Articles/R&D Personal
16
ITA
14
Upper Middle
Income
12
DEU
GBR
10
JPN
TUR
FRA
8
CAN
Low
Middle
Income
6
4
KOR
2
LKA
Malaysia
BOL
0
0
5000
10000
15000
20000
25000
30000
35000
40000
45000
50000
GNI (US$)
7. Changes in Tertiary Education and Economic Growth
Education is often perceived as one of the most important determinants of growth; education is
expected to increase economic growth. However, recent evidence reveals that the relationship
between education and growth is negative. It appears in many well-known studies, including the
seminal paper on growth empirics by Mankiw et al. (1992). A negative relationship between education
and growth also appears in Pritchet (2001) and Benhabib and Spiegel (1994). The negative result
might be due to data issues and schooling variables as Fuente and Domenech (2000) argue:
“weak data was likely to be one of the main reasons for the discouraging results obtained in the recent empirical
literature on human capital and growth.”
The choice of data might influence conclusions, especially when the study involves a time dimension.
Different types of data lead to contradictory conclusions (Atkinson and Brandolini, 2001) and policy
recommendations. The results of tertiary education enrolment are presented in Table 2.
Table 2: Education and Growth Relationship (Tertiary School)
Dependent variable: Economic Growth
Malaysian Educational
Statistics
WDI
Barro and Lee
(2010)
(1)
(2)
(3)
Population
-2.690
(-0.85)
-5.320
(-1.23)
-2.221
(-1.29)
Capital
0.182***
(2.39)
0.232***
(3.13)
0.193***
(4.59)
Tertiary
-0.384
(-0.48)
-0.157
(-1.18)
-1.142**
(-1.99)
Constant
5.829
(0.73)
12.172***
(1.10)
6.703*
(1.70)
Observations
35
31
49
Adj. R2-squared
0.106
0.273
0.194
Notes: Robust t-statistics in parentheses. *** p<0.01, ** p<0.05, * p<0.1
Data for Population and Capital was obtained from WDI Online, 2010
Source: Abdullah, Abdul Jabbar (2013).
The results show in all specifications or models that capital makes a significant contribution to
economic growth in Malaysia, consistent with the predictions of the Solow model for all datasets. The
coefficients of capital are positive and significant while the coefficients for population are negative.
The above results mean that capital formation is an important factor for growth in Malaysia.
To implement its education policy, Malaysia has been impressive in its public spending on education
(Cheong et al., 2011). As can be seen in Table 3, Malaysia’s expenditure significantly focuses on
tertiary education. Between two development plans (Seventh and Eight Malaysia Plan), expenditure
for tertiary education grew over one and a half times.
Between 8MP and 9MP, Malaysia’s spending on tertiary education was 81% of per capita GDP
compared to other Asian countries, including Singapore and South Korea (Cheong et al., 2011).
Table 3: Development Expenditure for education: Seventh and Eight Malaysia Plans, 1996 – 2005
(RM million)
Level
Seventh Plan
Eight Plan
Ninth Plan
Percentage Change
1996 - 2000
2001 - -2005
2006 – 2010c
7P – 8P
8P – 9P
Primarya
2,739
5,585
5,645
+103.9
+1.1
Secondary
5,318
8,748
6,793
+64.5
-22.4
Tertiary
5,005
13,404
16,069
+167.8
+19.9
Otherb
4,480
10,185
11,849
+127.3
+16.3
Total
17,542
37,922
40,356
+116.2
+6.4
Source: Adapted from Cheong, K.C., Viswanathan, S., and Goh, K. L. (2011)
a
includes preschool
consists of teacher education and other education support programmes
c allocation only
b
8. Quality Issues in Education
Over the past decade, Malaysia has invested heavily in post-secondary and higher education. In
2009, higher education institutions across the nation produced more than 181,000 graduates,
including more than 81,000 graduates from private higher education institutions. Similarly, in 2009,
skills training institutes produced more than 120,000 graduates, including more than 30,000
graduating from private skills training institutes (Malaysia, 2010).
All most all the public universities are governed by the Universities and Universities Colleges Act 1971
and technical education is provided by the Education Act 1996 and funded by the government. The
private higher education institutions (PHEIs) are not funded or maintained by the government
generally although they have been given some tax incentives (LAN, 2006).
Prior to 1996, the concerned with the higher educational programmes relates to matters such as
approval of new programmes, funding, and recognition of qualifications for employment and licensing
of professionals by the professional bodies. Realisation for the need for a quality assurance body was
due to global, regional and local forces which led to the establishment of LAN. The quality regime
began with the establishment of the Lembaga Akreditasi Negara (National Accreditation Board) in
July 1997 for the purpose of ensuring quality of education provided by the PHEIs.
In 2002 the government decided that public universities must also be subjected to quality assurance
and ordered the establishment the Quality Assurance Division (QAD) within the Ministry of Education
(now referred to as Ministry of Higher Education).
There was also increased concerned on quality of graduates of professional courses by professional
bodies as a consequence many new programmes and impact of international developments in
various professions.
Malaysia has unilaterally open its doors to foreign programmes and commercial presence of
institutions and benefited from such arrangements for a long time. Major international providers are
universities from UK and Australia from offering a full degree programme or undertake to accept
student under a twinning agreement, an articulation agreement for advanced standing or credit
transfers. It is found that the transnational education has succeeded to assist in nurturing private
education, increased access and affordable education for students whilst a wide options from across
the world. In addition to this quality assurance system has been put in place by the government.
All courses approved and conducted by the PHEIs are subjected to quality audit by LAN and the
regulations by the Ministry. There are generally clear evidence of capacity building and quality
improvement in the delivery of other programmes. The private sector and their cross-borders partners
provided wide access to higher education, reduce outflow of revenue and build local competency. It
also raises negative impact.
The negative impact of the transnational providers in some cases are provision of poor quality
programmes, insufficient commitment and monitoring of the delivery by partner institutions, different
quality standards, indifference or general ignorance to national criteria, local needs and policies,
issues comparability of quality of education, faculty staff, lack of clear information, cultural differences
and had issues relating to recognition of qualification. Other new challenges faced by authorities
come with the technology mediated provision of higher education, fraudulent qualifications and
practices, diploma and accreditation mills. Within the higher education sector, other challenges
includes ensuring that the students get good education, equality of access, funding, strengthening
internationalization initiatives and dealing effectively with issues of recognition, consolidation the
quality assurance system and the higher education structures with the establishment of the Malaysian
Qualifications Agency.
Malaysia’s current workforce with tertiary education stands at 23%, whereas the average for
Organisation of Economic Co-operation and Development (OECD) countries is nearly 28% studies
(Malaysia, 2010). Furthermore, of the graduating students who were employed, 29% in 2006 and 33%
in 2009 earned less than RM1,500 per month. Employers and industry associations state that lack of
soft skills, such as positive work ethics, communications, teamwork, decision making and leadership
skills, is the primary factor with some, like Singapore and Finland, as high as 35%. For students
graduating from local higher education institutions in 2009, 27% remained unemployed six months
after completion of their hampering employability of many Malaysian graduates. As there is still a
sizeable gap between the competency levels of graduates and comparable international standards,
the issue of graduate competency needs to be addressed to ensure that Malaysia has a skilled, wellrounded and employable graduate pool to enter the workforce.
Similarly, there are an estimated 100,000 or 22% of Malaysian students in 2009 who enter the
workforce directly upon completion of only 11 years of schooling, after achieving a SPM. This group of
students may be more technically inclined and therefore offers significant opportunity to improve their
skills in the technical fields.
Given the rapid pace at which Malaysia will need to develop its human capital to achieve high-income
nation status, it is necessary to radically raise the skills of Malaysians to increase their employability
by focusing on the following:

Mainstreaming and broadening access to quality technical education and vocational training;
and

Enhancing the competencies of tertiary graduates to prepare them for entering the labour
market
Cheong et al. (2011) has clearly stated in their paper about the poor quality of the output of tertiary
institutions and mismatch between skills needed and those acquired from the tertiary education
system. Rasiah (2002, 2005) pointed that this mismatch is particularly problematic at a time when
Malaysia sets out to upgrade its technological capability. This mismatch is illustrated in table 4.
Malaysia has a low proportion of students enrolled in technical subjects and research scientists to
population ratio compared to countries moving towards high technology. At the same time, the
proportion on graduates in arts and humanities has been rising (Table 4).
Table 4: Enrolment in technical subjects and public expenditure on education: Selected countries
COUNTRY
Total enrolment
Percentage of
Public
Percentage of
in technical
total enrolment
expenditure/
education in total
subjects (‘000)
in technical
Tertiary student
public expenditure
subjects
2005a
2005
(1)
(2)
(3)
(4)
74.9
14
93.7
28.0
1000.4
33
9.3
15.0
Singapore
15.9
19
-
-
Taiwan, China
368.9
37
-
-
China
2580.4
21
90.1 (1998)
-
India
1913.0
19
68.6
10.7
Indonesia
585.6
19
13.3
9.7
Thailand
186.0
9
23.0
27.5
Malaysia
South Korea
a
expressed as percent of per capita GDP
Source: Adapted from Cheong, K.C., Viswanathan, S., and Goh, K. L. (2011)
Rankings of world universities show that Malaysian universities are not internationally competitive and
one of the main contributing factor in research weakness.
9. Conclusions
Malaysia has developed strongly enough to become an upper middle income country with
manufacturing becoming the prime exporter since the 1980s. However, natural resources, such as, oil
and gas and oil palm not only initiated the country’s growth till the early 1970s, they have become
important again in the country’s rapid growth since the late 1990s. Growth, however, has slowed
down in trend terms since the Asian financial crisis struck in 1997-98. Malaysia’s progress has since
fallen below the growth trajectory required for the country to achieve developed status by 2020.
Human capital has been identified as the key deficiency that has restricted Malaysia’s capacity to
sustain rapid growth and structural change to high value added activities (Malaysia, 2011).
Although Malaysia invested relatively strongly in education compared to other countries, the share of
enrolment in technical education fell below Korea, Taiwan, Singapore, China, India and Indonesia.
Similarly, Malaysia had a significantly lower ratio of R&D scientists and engineers per million
population than Korea, Singapore, Taiwan and China. Little wonder that Malaysia ranked low in
scientific output and patents taken in the United States when compared to Korea, Taiwan, China and
Singapore.
Malaysia enjoyed higher GNI per capita mean compared to the upper-middle income country average
despite having a weaker human capital, innovation and scientific publications performance suggesting
that the country’s income growth has been driven strongly by non-innovative economic activities, such
as, mining and quarrying and oil palm. These results suggest that serious efforts must be taken to
review Malaysia’s human resource policies. While investment is necessary the prime deficiency
appears to come from the quality of human capital produced in the country. Also, while the infusion of
quality is pertinent in the country’s educational establishments, more vigorous efforts must be taken to
attract Malaysians abroad with tacit knowledge to return and lead the organizations producing human
capital.
References
Abdullah, Abdul Jabbar (2013). Education and Economic Growth in Malaysia: The Issues of
Education Data, Procedia Economics and Finance 7 ( 2013 ) 65 – 72 ,Elsevier B.V.
Atkinson, A B., and Brandolini, A., (2001). Promise and Pitfalls in the Use of ‘Secondary’ Datasets:
Income Inequality in OECD Countries as a Case Study. Journal of Economic Literature 39(3), p. 77199.
Barro, R.J. (2001) "Human capital and growth." American Economic Review, 91(2) 12-17.
Benhabib, J. and Mark M. Spiegel., (1994). The Role of Human Capital in Economic Development
Evidence from Aggregate Cross-country Data. Journal of Monetary Economics 34 (2), p.143- 173.
Cheong, K.C., Viswanathan, S., and Goh, K. L. (2011). ‘Education and Human Capital Formation’ in
Rasiah, R. (ed), Malaysian Economy, Oxford University Press
Engelbrecht, H. J. (2003) “Human Capital and Economic Growth: Cross-Section Evidence for OECD
Countries”, Economic Record 79: 74–84.
de la Fuente, Angel and Rafael Domenech (2000) “Human Capital and Growth: How Much Difference
Does Data Quality Make?” Mimeo, Instituto de Análisis Económico (CSIC), Barcelona
Hall, R. and Jones, C. 1999. “Why Do Some Countries Produce So Much More Output Per Worker
Than Others?”, Quarterly Journal of Economics, 114(1): 83-116.
Jorgenson, D. W. and Fraumeni, B.(1992) "Investment in Education and U.S. Economic Growth",
Scandinavian Journal of Economics, 94: 51-70.
LAN (2006). Quality Assurance System In Higher Education, Lembaga Akreditasi Negara –Zita/06
http://siteresources.worldbank.org/EDUCATION/Resources/malaysia-qa-system.pdf (accessed on
23.6.2014)
Lucas, R. 1988. “On The Mechanics of Economic Development”, Journal of Monetary Economics,
22(1): 3-42.
Malaysia, (2010). Tenth Malaysia Plan, 2011-2015, Government of Malaysia, Kuala Lumpur.
Mankiw, N. G., Romer, D. and Weil, D. N. 1992. “A Contribution to the Empirics of Economic Growth”,
Quarterly Journal of Economics, 407-437.
Mincer
Pritchett, L., (2001). Where Has All the Education Gone? World Bank Economic Review 15 (3), p.
367-91.
Rasiah, R. (2002). Systematic Coordination and the Knowledge Economy: Human Capital
Development in Malaysia’s MNC Driven Electronics Clusters, Transnational Corporations, 11(3), 89129
Rasiah, R. (2005). Clusters and Regional Industrial Synergies: The Electronics Industry in Penang
and Jalisco’ in Scot, A. J., and Garofoli, G. (eds), Developments on the Ground: Clusters, Networks
and Regions in the emerging Economies, London: Routledge
Rasiah, R. (2011). The Role of Institutions and Linkages in Learning and Innovation. International
Journal of Institutions and Economies, 3(2), 165-172.
Romer, P. (1986) “Increasing Returns and Long-run Growth”, Journal of Political Economy, 94: 10021037.
Saxenian, (2006)
Solow, R. (1956)
Vogel, (1991)
World Bank. (2010). Malaysia Economic Monitor : Inclusive Growth.
Appendix
Country Name
Bolivia
Sri Lanka
Brazil
China
Malaysia
Turkey
Belgium
Canada
France
Germany
Italy
Japan
Korea, Rep.
United
Kingdom
Country
Code
BOL
LKA
BRA
CHN
MYS
TUR
BEL
CAN
FRA
DEU
ITA
JPN
KOR
GBR
Figure 3: R&D Personal (per million people) and GNI per capita, Atlas Method (current US$)
(2000-2010)
6000
High-Income Economies
KOR, 2010
5000
Researchers in R&D (per Million)
BOL
LKA
4000
BRA
CHN
MYS
3000
CAN
FRA
KOR, 2000
DEU
ITA
2000
JPN
MYS, 2010
KOR
GBR
1000
MYS, 2000
0
0
5000
10000
$12,616
15000
20000
25000
30000
GNI per capita (Atlas Method)
35000
40000
45000
50000
90000
80000
CHN
Scientific & Technical Journal Articles
BOL
70000
LKA
Low Middle
Income
BRA
60000
CHN
50000
DEU
MYS
JPN
GBR
TUR
40000
Upper
Middle
Income
CAN
FRA
30000
ITA
FRA
CAN
DEU
KOR
20000
ITA
JPN
BRA
10000
KOR
TUR
0
0
GBR
Malaysia
LKA
1000
2000
3000
4000
R&D Personal (per million people)
5000
6000
High
Income
OECD