2010-E-2
Globalization, Education and Development:
A Comparison between Successes and Failures in the Asia-PacificPramila Neupane
PhD Candidate, Graduate School of Asia-Pacific Studies
Waseda University
February 2011

E-mail: neupane.pramila@gmail.com

Abstract
Link between globalization, education and development is one of the major subjects ofinterest in the contemporary discourse on international development. This paper compares theeducation, globalization, income and health indicators of successful and unsuccessful countries
in the Asia-Pacific region in terms of their GDP per capita growth over the period of 1970 to2006. The study finds that countries with high levels of education have achieved continuous highgrowth in GDP per capita along with rapid globalization over time. In contrast, countries withlow levels of education have found it more difficult to achieve progress. They have experienced
very slow growth in per capita income and have not been able to effectively integrate themselveswith the global economy and society. In addition, using panel data of 26 countries from theregion and applying fixed-effect regression model, it finds that globalization and education havehigh and positive impact on GDP per capita. However, in spite of high performance on
education and globalization, the Philippines has surprisingly low growth in GDP per capita overthe period, and poverty and income inequalities are also still high in the country. Thus, further
research is proposed to explore the reasons behind this unusual outcome.

1

Globalization, defined as increasing global interdependence in economic, political andcultural spheres and reducing barriers to international trade, investment and migration, has
accelerated in recent decades, affecting many aspects of development (while) bringing
opportunities and threats to all nations (Dreher et al. 2008). In this process education can play animportant role in optimizing the gain from globalization and ultimately achieving development
goals, particularly in less developed countries (Green et al 2007). As the latest champions ofglobalization for their national development mainly come from the Asia-Pacific region, it isworthwhile to see the triangular relationship between globalization, development and educationin these countries. It is also relevant because of the fact that Asia-Pacific region also has anumber of countries that are lagging behind in tapping globalization for national development,
both economic and social. On the basis of recent trends of globalization and development, as wellas educational attainments, this paper examines the role of education for successful globalization
and broad-base development in the Asia-Pacific region, particularly in East Asia and the Pacificand South Asia.
The definition of globalization is complex and there is rich and growing literature on thecauses and consequences of it. This paper adopts a rather comprehensive definition of
globalization that covers the rapid acceleration of cross-border movements of capital, people,
goods, knowledge, information and ideas. Globalization generally covers most of the dimensionsof society including economic, political and social aspects. Accepting this fact, Axel Dreher
introduced a new comprehensive indicator of globalization in 2002, which is called “KOF index
of globalization.” 1 The index was fully developed in 2006. The data for 153 countries from 1970
are being updated annually. Thus, this paper uses the KOF index of globalization as a working
definition and measurement of globalization. Like globalization, “development” also is a vague
term. Development refers to a range of aspects, from purely economic terms to human rights andsocial justice, from the physical quality of life to happiness and human satisfaction. To simplify
the research, however, this paper uses growth rate of GDP per capita as the development
indicator. Based on the average GDP per capita over the period of 1970 to 2006, five high1

The KOF index of globalization was introduced in 2002 by Axel Dreher. According to Dreher (2006), overall
index covers the economic, social and political dimensions of globalization. It defines globalization as a process ofcreating networks of connections among actors at multi-continental distances, mediated through a variety of flows
including people, information and ideas, capital and goods. Also available at http://globalization.kof.ethz.ch/ (accessed
March 15, 2010).

2

growth and five low growth countries are selected, and defines these countries as successes andfailures respectively for the comparison. After selecting the countries to be examined, the paper
accounts the equity or distributional aspect of economic gains and health aspect of population.
Finally, education seems a rather simple term. However, when we try to measure the quantityand quality of education, it proves not so simple. Although this study intends to comprehensively
cover all aspects of education, gross enrollment rate (in primary and secondary education) andadult literacy rate are used to measure education level.
The remaining part of this paper is organized as follows. Section 2 presents trends andrelationships between globalization and development. Based on the average growth of GDP per
capita over 1970-2006, five successes and five failures are identified from the Asia-Pacificregion to compare trends of globalization, poverty and inequality indicators across countries.
Section 3 analyzes educational status and achievement of successes and failures that demonstrate
the critical importance of education to leverage the benefits of globalization for overall
development. Section 4 empirically shows the significant positive impact of globalization andeducation on GDP per capita in the region. Finally, to conclude, Section 5 offers some policy
recommendations and explores further research areas.
Globalization and Development: Trends and Linkages
Globalization can simply be defined as the rapid acceleration of cross-border movementsof capital, labour, goods, knowledge and ideas (Green et al 2007). Martin Carnoy (1999, 13)
defines global economy as the main component of globalization. He writes, “A global economy
is one whose strategic, core activities, including innovation, finance and corporate management,function on a planetary scale in real time.” Many scholars claim the current wave of globalization
started in the 1970s (Green 2002, Wolf 2004). According to them, the current web of
globalization has resulted mainly from the expansion of faster and more efficient transport andcommunication sectors made possible by rapid advances in science and technology. At the sametime political factors have led to trade liberalisation and more open markets since the early 1970s.
When global flows of goods and services and factors of production increase, naturally, culturalinteractions also increase at the global level, leading to social globalization. Thus, as the KOF
index of globalization comprehensively incorporates economic, political and social aspects of3

globalization, this paper uses the KOF index to observe the trend of globalization in the region.
Details of the index appear in Appendix 1.
Globalization affects the development process in many ways. Generally, it increases theimportance of international trade and also changes the terms of comparative economic advantage
while increasing labor, materials, capital, technology and know-how. Thus, globalization reduces
inefficiencies and increases factor productivity (Green et al. 2007). However, globalization
increases competition and non-competitive countries can be sidelined in the process. Since theopenness of a country means that its resources are accessible to other countries, non-competitive
countries may lose their unused resources. Hence, it is very much important to know how
countries are successfully globalizing to achieve national development.
The concept of development mostly depends on how we understand the concept ofglobalization. In fact, there is no consensus among scholars regarding the benefits ofglobalization. Whether globalization is “a good thing” for all nations or a phenomenon whichfurther enriches the elites in the developed world is a topic of heated debate among policymakers
and academics alike. Optimists, who believe globalization is a good thing, point to East Asian
countries in general and China in particular as examples of what less developed countries cangain from globalization. On the other hand, pessimists remind us of the stories of countries in
Latin America, South Asia and Africa who have gained very little and even suffered relative
declines as a consequence of globalization. Still others present a more balanced view. For
instance, Joseph Stiglitz (2002, 20) argues that globalization is inherently neither good nor bad
since it depends on how it is managed. He states, “Globalization itself is neither good nor bad. It
has the power to do enormous good. But in much of the world it has not brought comparable
benefits.”
In this context, what do empirical data from Asia-Pacific countries reveal about
globalization and development? Assessment of the actual situation can not only explain thevalidity of theoretical arguments but also offer a reliable solution to the existing debates. This
study takes GDP per capita of all the East Asia and Pacific and South Asian countries fromWorld Development Indicator (WDI) online database of the World Bank to define countries as
successes or failures. Average GDP per capita growth of each country from 1970 to 1990 and1991 to 2006 is calculated and defined successes for high growth countries and vice versa. Year
1990 is used to separate the two periods because the Cold War ended then and globalization4

process became more rapid (Sapkota 2010). Relevant data for other development indicators andglobalization are presented in Table 1.
Table 1 clearly contrasts two groups of countries in the Asia Pacific in terms of their GDP
per capita growth, globalization trends and level of poverty and income inequality. As definedearlier, successes achieved quite high per capita GDP growth rates ranging from 3.13% inIndonesia to 9.26% in China during the period of 1970 to 2006. On the other hand, failures areindicated by low rates of growth ranging from the average growth of -0.7% of Papua New
Guinea in 1970 to 1990 to 3.02% of Bangladesh in 1991 to 2006. Although the average annual
growth rate of Bangladesh in the later period indicates notable progress, it was as low as 0.09%
before 1990.
TABLE 1
GDP PER CAPITA GROWTH RATE AND OTHER DEVELOPMENT INDICATORSOF SUCCESSES AND FAILURESCountry

GDP per capita
growth rate (%)

KOF Index of
Globalization (0-100)

1970-90 1991-06 1970 1990
Successes (In terms of GDP per capita growth):

Infant mortality rate
(per 1,000 live births)

2006

1970

1990

2006

Poverty
Gini Index*
rate*

China

6.55

9.26

15.67

34.76

59.85

83

37

20

16

42

S. Korea

6.43

4.83

27.23

42.74

65.87

41

8

5

2

32

Malaysia

4.21

3.96

45.19

58.62

76.24

41

16

7

2

38

Thailand

5.54

3.79

28.31

39.62

66.49

71

26

14

2

42

Indonesia

4.96

3.13

23.99

35.25

57.66

103

56

33

21

39

Failures (In terms of GDP per capita growth):
Bangladesh

0.09

3.02

13.29

20.17

39.78

160

103

48

50

31

Nepal

1.1

2.02

13.87

24.47

39.65

158

99

46

55

47

Pakistan

2.77

1.93

26.69

33.29

53.32

136

101

75

23

31

Philippines
Papua New
Guinea

1.2

1.47

31

42.78

60.63

59

42

26

22

44

-0.07

0.79

27.96

41.08

44.57

107

67

54

36

51

SOURCES.– 1. KOF index of globalization: (Dreher 2006), also available at http://www.kof.ethz.ch/globalisation,(accessed March 15, 2010). 2. Other remaining variables: The World Bank, WDI online database (accessed on
various dates).
NOTE.–* Latest data available from 1995 and 2005.

5

Notably, three of the successes are from East Asia and the rest two are from South East
Asia, which experienced very rapid and sustained growth and poverty reduction. Although there
are some problems with the development paths followed by these countries - including politically
repressive governments, adverse environmental effects and poor labor conditions - theirdevelopment must be regarded as successful. From many perspectives, including real
improvement in human conditions as indicated by a sharp fall in infant mortality rate andreduction in poverty, their development success is impressive. This is why East Asiandevelopment trend is regarded as “East Asian miracle” in development discourse (World Bank
1993).
The successes’ globalization trends are rapidly growing as expected. For instance, while
the KOF index of globalization of China, Malaysia and Thailand was 15.67, 45.19 and 39.62
respectively in 1970; by 2006 the index had reached 59.85, 76.24 and 66.49 respectively. The
other two successes (South Korea and Indonesia) also showed very good progress on
globalization. Interestingly, even among the successes, those with higher GDP per capita growth
rates had faster increases in the globalization index in general. Such progress on economic
growth also led to improved health condition of the population and hence reduced poverty. This
fact can be interpreted from the data on infant mortality and poverty rates. The infant mortality
rate is defined as “the number of infants dying before reaching one year of age, per 1,000 live
births in a given year” and poverty rate, also called poverty headcount ratio, is “the percentage ofthe population living on less than $1.25 a day at 2005 international prices (World Bank 2010).”Between 1970 and 2006 the infant mortality rate of China, Malaysia and Thailand dropped from84, 46 and 73.9 to 18.7, 9.8 and 6.96, respectively.
On the other hand, many other countries operating in the same global economy performed
far worse. The five failures in Table 1 experienced minimal GDP per capita growth rates andhigh infant mortality and poverty rates. One of the countries, Papua New Guinea, evenexperienced a negative growth rate of GDP per capita from 1970 to 1990. Despite some
improvements, infant mortality rates remained unacceptably high in the failures. For instance, thepoverty head count rate was 50, 55, 23, 22 and 36 respectively for Bangladesh, Nepal, Pakistan,
the Philippines and Papua New Guinea. Another indicator of development, infant mortality rate,
was quite high in these countries, ranging from 73.1 in Pakistan to 23.56 in the Philippines in2006. Interestingly, if we compare the GDP per capita among these countries, there was not a big
6difference between the two groups of countries at the beginning. Figure 1 shows the trend of
GDP per capita at purchasing power parity (PPP) at current price. It shows there were no big
differences in terms of GDP per capita in 1970. Thus, we can observe that these successes andfailures operated not only in the same global and regional environment but also nearly at thesame level of development at the beginning of this study period. However, successes achievedvery high GDP per capita growth over the period of time under investigation.
FIGURE 1

GDP PER CAPITA (CURRENT US$) BETWEEN SUCCESSES AND FAILURE

SOURCE.– Author’s calculations based on data from the World Bank, WDI online database.
NOTE.– Dark lines for successes and gray lines for failures.

Along with development indicators, globalization trends are also found to be slower inthe failures. Interestingly, globalization level was lower in some of the successes than that of
failures at the beginning. However, successes globalized rapidly and reached far higher level
than that of the failures. These trends are presented in Figure 2. For instance, Malaysia hadsignificantly higher level of globalization already in 1970 but other successes had no big
differences with the failures. However, successes’ level of globalization grew faster together
with their development and in 2006 they all reached much higher point than failures except for7the Philippines. Notably, like in GDP per capita, progress in globalization is recorded very fast
for South Korea.
FIGURE 2

GLOBALIZATION TREND (KOF INDEX OF GLOBALIZATION)

SOURCE.– Author’s calculations based on data from http://globalization.kof.ethz.ch/query/.
NOTE.–Dark lines for successes and gray lines for failures.

Noticeably, the Philippines has very low GDP per capita growth rates in spite ofrelatively high levels of globalization index and other social indicators than rest of the countries
in the same category. There might be some other reasons behind the low growth performance,such as corruption, political instability, outward migration of skilled manpower, etc. Thus, thecase of the Philippines needs further research.
It has been argued that globalization increases inequality within and among countries as
many believe that the gains from globalization go more to richer countries and richer segments ofnational populations. Scholars agree that income inequality within most states has increased overthe past decade, as has the gap in average incomes between the world’s richest and poorest
countries (Wolf 2004). Since Kuznets, development economists tend to predict that inequality

8within a country increases at least until it reaches a certain development level.2 However, theinequality measure in Table 1, represented by Gini Index, reveals no significant differences
between successes and failures.3 For example, the Gini Index for successes ranges from 42.45 in
Thailand to 31.59 in South Korea, whereas for the failures, it ranges from 31.02 for Bangladesh
to 50.88 for Papua New Guinea. It appears that rapid economic growth and globalization do notnecessarily worsen the income inequality within a country.
If we compare between two sub-regions within the Asia-Pacific, there are three failures inSouth Asia: Bangladesh, Pakistan and Nepal. These countries have often experienced social
conflicts and political volatility. Among the other failures, Papua New Guinea belongs to the
Pacific and the Philippines belongs to Southeast Asia. On the other hand, China and South Korea,
both in the group of successes, belong to East Asia and the rest of the successes are fromSoutheast Asia. There are no success stories in South Asia, although India is performing well in
recent years as globalization has quickened pace in recent decades.
In this context, an obvious question to be asked is: why are some countries successful inutilizing globalization for their development and why others are failing? Although, there aremany differences between the two groups of countries (and within each group), their initialconditions (in per capita income or natural resource base, for example) were not very different
and all the countries face the same global economy and the same regional geo-politicalenvironment. So, what factors explain the different development performance between the
successes and failures? Are differences in human resources base a factor? The following section
examines this aspect.
Educational Status and Trends and its Role in Development and Globalization
Globalization has substantially changed the role of education in development processes.
Knowledge and skills become more important in the global era of competition. Many “rate of
return to education” studies have emphasized the importance of education in economic and social
2

Kuznets (1955) argued that a country’s income distribution worsens during the early industrialization process
and later stages at some critical point it starts to decrease over time. His argument was based on the inverted U shaped
curve that he drew from the measures of increased economic development on the horizontal axis and measures of income
inequality on the vertical axis.
3
Gini index is a widely used measure of inequality in development literature and ranges between 0 and 100. Here,0 means perfect equality in which everybody has the same amount of income, whereas 100 means perfect inequality, thatis, that all the income goes to one person and the remaining population shares no income.

9

development. This is because education not only affects labor productivity and countries’ ability
to compete in international markets, but it is also necessary to attract international capital andhence affects the accumulation of capital that is essential for investment.
It is difficult to study empirically the relationship between education and economic
growth. The relationship is very complex because of many other intervening variables thatinteract in many ways (Lewin 1993). Thus, available research findings are not consistent.
However, most scholars argue that human capital and technological know-how are vitally
important to growth (Barro 1991). For example, analyzing 98 countries between 1960 and 1985,
Robert J. Barro (1991, 409) concluded, “the growth rate of real per capita income is positively
related to initial human capital and negatively related to initial level of real per capita GDP.”
Indeed, education helps to enrich human lives, to empower people and to raise humanwellbeing (Stewart 1996). Education and skills determine the degree to which knowledge andtechnologies can be transferred and absorbed, which means the capacity of the state to build up
its indigenous industries and to compete in world markets with their goods and services (Amaden1981). Investment is a very important phenomenon in the development process and Educationand skills become more important to attract Foreign Direct Investment (FDI), which is one of the
primary engines of development for many countries (Wolf 2004; Carnoy 1999). Various
researches have showed that education and skills were one of the important factors for attracting
and benefiting from FDI in East Asia. Similar trends were observed recently in South Africa as
well (Willem and Xenogiani 2007). Generally, FDI tends to be involved in high skill activities.
This creates employment opportunities for well-qualified population that ultimately raises
enrollments in secondary and higher education (ODI 2005). The importance of education has
also been supported by many “rate of return to education” analyses (Becker 1993;
Psacharopoulos 1994). For instance, George Psacharopoulos and Maureen Woodhall (1985, 55)
found that “the rate of return to investment in education is higher than the average rate of returnto physical capital in developing countries, though not necessarily in developed countries.”
Furthermore, education not only contributes to the sectors that need high-skilled humanresources but also enhances the productivity of the primary sector. Scholars agree on the positive
relationship between education and agricultural productivity. For example, eighteen researchstudies on agricultural productivity revealed that four years of primary education increased farm
productivity by an average 8.6% (Lockheed et al. 1980). The same studies also found that10

agricultural productivity was more influenced by education in modernizing environments than in
traditional environments. Similarly, a positive and significant effect of education, particularly inmodernizing environments, was found in studies on education and agricultural productivity in
Korea, Malaysia, Thailand and Nepal (Haddad et al. 1991). J. Knight and R.H. Sabot (1990)
showed significant labor market returns to cognitive achievement through their study that
included about 2,000 employee samples in Kenya and Tanzania.
Educational development research used to be focused on economic aspects ofdevelopment in the past. Its recent focus, however, is increasingly on social benefits of education.
The role of education in promoting equity with growth has become more important. Therefore
we can find lots of recent evidence on the benefits of education to health, population control,
crime, equality and social cohesion. For example, for East Asian countries, Walter McMahon(1999) showed that education could have a substantial downward effect on income inequality,
even after controlling for population growth. However, increasing aggregate levels of education
may not always help to achieve greater income equality. For instance, the World Bank (2002)
pointed out that liberalization in Eastern Europe led to increased returns to higher education thatmight in turn result in greater income inequality. According to human capital theory, in general,
income inequality increases when demand for skills is not matched by increases in supply
because returns to higher qualifications will increase in such a situation. A similar situation holds
even if the supply of lower level skills increases faster than demand for them.
Moreover, McMahon (1999) found strong correlation between educational enrollment
and other socio-political indicators such as human rights, political stability and democratization.
He also showed significant positive correlation in primary and secondary enrollment withpoverty reduction. In addition, generalization of primary education and extension of secondary
education to rural areas is associated to development with stable or declining income inequality.
In light of these findings, what can be revealed from the data on the Asia-Pacificcountries examined here? Table 2 shows the human resource level, represented by gross primaryand secondary enrollment ratio, of successes and failures. The data source is World Bank, WDI
online database. As defined by United Nations Educational, Scientific and Cultural Organization(UNESCO 2009, 9), “Gross Enrollment Ratio (GER) is total enrollment in a specific level of
education, regardless of age, expressed as a percentage of the eligible official school-age
population corresponding to the same level of education in a given school year.”11

We can observe a clear linkage between GDP per capita, which is shown in Table 1, andenrollment rate in Table 2. Countries which have achieved high GDP per capita growth, referred
to as successes, also have high enrollment rates in both primary and secondary education. For
instance, the primary enrollment rate in China was 121.9 and 111.3 in 1976 and 2006,
respectively, whereas its secondary enrollment rate was 39.4 in 1970 and 75.5 in 2006, which is avery impressive improvement. China’s human resources, in this study, measured by grossenrollment rate, are remarkable from the beginning of our study period. Therefore, it is argued
that China had a big investment in human resources that critically contributed to its economic aswell as social development. The other countries in this group also have a good human resource
base.
TABLE 2SCHOOL ENROLLMENTS IN SUCCESSES AND FAILURES
Primary enrollment (%)
1970
2006
Total Female Male Total Female Male

Secondary enrollment (%)
1970
2006
Total Female Male Total Female Male

121.9

114.2

129.1

111.3

110.9

111.5

39.4

32.1

46.3

75.5

75.8

75.2

S. Korea**

103.4

102.9

103.9

105

103.3

106.6

41.6

32.5

50.2

97.5

94.5

100.3

Malaysia

88.7

83.4

93.9

100.5

100.3

100.7

34.2

27.9

40.7

69.1

72.3

66.0

Thailand***

79.5

75.4

83.5

107.9

107.9

107.8

17.4

14.6

20.2

78.1

81.5

74.8

Indonesia

79.2

73.5

84.8

114.1

112.1

116.1

16.9

11.8

21.9

65.7

65.8

65.5

Failures
Bangladesh****

51.2

33.9

67.5

92.9

95.9

90.1

15.5

8.5

21.9

42.7

44.1

43.1

Nepal

24.5

7.5

40.4

126.1

123

129

8.7

2.6

14.5

43.2

40.5

45.7

Pakistan******

43.1

23.4

61.5

84.1

73.5

94.2

15.2

6.3

23.4

30.0

26.2

33.7

Philippines

113.8

109.5

108.7

110.3

48.5

47.2

49.8

83.1

87.6

78.8

Papua New
Guinea

47.0

55.2

50.3

59.7

6.9

3.7

10.1

Country
Successes
China*--34.858.8---

SOURCE.– The World Bank, WDI online database.
NOTE.– *China’s Primary enrollment is for 1976; **South Korea’s primary enrollment is for 1971;***Thailand’s primary enrollment is for 1971; ****Bangladesh’s secondary enrollment is for 1972;*****Pakistan’s primary enrollment is for 1971.
--- = data not available.

12However, there is a considerable gender gap in education in Indonesia, especially at the
beginning which resulted to relatively low progress in development among successes. In 1970,
the nation’s primary education enrollment rate was 73.5 for females and 84.8 for males and thesecondary enrollment rate was 11.8 and 21.9, respectively. The gap lessened to 112.1 and 116.1
in the primary level and 65.8 and 65.5 in the secondary level in 2006. Here, the gap between
female and male enrollment considerably shrunk in the later period.
The second part of Table 2 is educational status of failures in the region. All the countries
in this category had significantly low levels of human resources, especially at the beginning. For
instance, Nepal’s primary enrollment rate in 1970 was 24.5, whereas secondary enrollment was
8.7. Rest of the countries in this group, except the Philippines, also have quite low level ofhuman resource.
Adult literacy rate is another widely used educational indicator that captures the overalllevel of educational development of a country. This indicator is used widely in development
research and practice, and there are high concerns and commitments to increase the literacy levelparticularly in developing countries in the light of Education for All (EFA) targets. Adult literacy
rate is one of the aspects to measure “knowledge” in calculating Human Development Index(HDI) including enrollment ratio. As defined by UNESCO (2009, 3), “adult literacy rate is thepercentage of people ages 15 and above who can, with understanding, read and write a short,
simple statement on their everyday life.” Let us compare the successes and failures on the basisof adult literacy.
Figure 3 presents the total adult literacy rates for both successes and failures in two
periods, 1980-1982 and 2005-2008. It shows a clear link between a country’s level ofdevelopment and its educational attainment. All the countries, both successes and failures, areincluded in Figure 3, except for South Korea and Papua New Guinea because of lack of data. The
first four countries are successes and the other four countries are failures.
The data reveal that successes already had adult literacy rates above 65% in 1980-1982.
Interestingly, these successes did not have big gaps between them, whereas the failures’ literacy
rates varied widely from country to country. Notably, three South Asian countries had adultliteracy rates lower than 30% in 1980-1982. From the first to the second period, successes
achieved progress and reached higher than 90% in 2005-2008, but failures could not even reach13

60% except the Philippines. The adult literacy rate in the Philippines was exceptionally highamong the failures and compared favorably with the rates in the successes in both periods.
FIGURE 3
COMPARISON OF TOTAL ADULT LITERACY RATES OF SUCCESSES AND FAILURES(1980-1982 AND 2005-2008)

SOURCE.– Author’s calculations based on data from the World Bank, WDI online database.
NOTE.– The earliest period is between 1980 and 1982 and the recent period is between 2005 and 2008 depending
on countries and their data availability. The exact year and data are presented in Appendix 1.
CHN: China; MAL: Malaysia; THL: Thailand; IND: Indonesia; BLD: Bangladesh; NEP: Nepal; PAK: Pakistan;and PHL: the Philippines.

How about the gender difference in adult literacy? In the case of developing countries,
gender differences in education receive due attention by policymakers and development scholars.
Because the gender gap in education is quite high in developing countries, it is hindering thedevelopment process. To assess the gender aspect of education in our sample of successes andfailures, Figure 4 is presented. It shows male and female adult literacy rates for both the earliest
years and the recent years.
As expected, gender gap in adult literacy is less pronounced in successes than in failures
ones. Among the four successes, China had the lowest women literacy in the earliest period.
However, China achieved a big progress, reaching almost 90%, in recent years and caught up
with other countries in the same category. On the other hand, Nepal had the lowest literacy rate
14

for both males and females during the earliest period. Its female adult literacy rate was less than
10% whereas the male literacy rate was nearly 40%. The other two failures (from South Asia),
Bangladesh and Pakistan, also had very low levels of female adult literacy, at less than 20%. The
rate for males was below 40% and gender gap was quite wide, about 20% difference. Male adultliteracy rates for failures in recent years ranged from 40% to 70% but female adult literacy
ranged from 40% to 50%. These data show the importance of gender equity in education fordevelopment. The Philippines was the exceptional case here as well as it has both higher rate ofadult literacy and lower level of gender gap. Recent data even shows slightly higher adult literacy
rate for female than for male.
FIGURE 4
GENDER-WISE COMPARISON OF ADULT LITERACY RATES OF SUCCESSES AND FAILURES(1980-1982 AND 2005-2008)

SOURCE.– Author’s own calculations based on the data from the World Bank, WDI online database.
NOTE.– The earliest period is between 1980 and 1982 and the recent period is between 2005 and 2008 depending
on countries and their data availability. The exact year and data are presented in Appendix 1.
CHN: China; MAL: Malaysia; THL: Thailand; IND: Indonesia; BLD: Bangladesh; NEP: Nepal; PAK: Pakistan;and PHL: the Philippines.

Analysis of the data in Table 2 and Figures 3 and 4 reveals direct linkages between
average GDP per capita growth rate, level of globalization (measured by the KOF Index of15

Globalization), other aspects of human development (measured by infant mortality rate, poverty
rate and inequality rate) and human resources (gross primary and secondary enrollment rate andadult literacy rate) in all the countries in our sample. Although the linkages are not consistent for
the Philippines, generally it is argued that educated human resources are an essential condition
for successful globalization and economic and other aspects of development.
This argument is supported by many studies which have demonstrated strong and positive
correlations between education and various aspects of development. For example, Edward F.
Dennison (1967) found positive correlations between education and growth in the United States
between 1930 and 1973. Later in 1979, he also found that direct effects of education were
responsible for 20% of growth and indirect effects for 11%. However, results were considerably
different when they were applied to other countries. In the study by Psacharopoulos andWoodhall (1985), the results varied from 2% to 25% for developed countries and from 1% to 6%
for developing countries. Hicks (1980:17-20) found that twelve developing countries with thefastest growth rates had literacy levels above the average (68% compared to 38% in 1960). Other
studies also found strong positive correlations between education and economic growth but theresults were different from country to country (Harbison and Mayers 1964). What does the datafrom the Asia-Pacific countries? Following section presents the statistical relationships between
these key variables.
Development, Globalization and Education: What are the Relationships?
The impacts of globalization and educational on GDP per capita are further analyzed
statistically through regression analysis. To do so, a panel data set is used taking data from 1980
to 2006 for 26 countries in East Asia and the Pacific and South Asia.4 The list of the selected
countries is presented in Appendix 3. All the data is obtained from the World Bank’s World
Development Indicators (WDI) online database except KOF index of globalization, which issourced from Dreher (2006). The summary statistics of the data are presented in Appendix 4 andcorrelation matrix is shown in Appendix 5. The panel is not fully balanced because of theinsufficient data of secondary school enrollment rate which is available only in certain year gap.

4

This study intends to cover all the countries from the region, however only 26 countries have sufficient data forregression analysis.

16

The fixed effect (FE) estimation model is used to analyze the data. As explained by Kohler
and Kreuter (2005, 245), the rationale for using the FE model is that; “The fixed-effects model
controls for all time-invariant differences between the individuals, so the estimated coefficientsofthe

fixed-effects

modelscannotbebiasedbecauseofomittedtime-invariant

characteristics…(like culture, religion, gender, race, etc.).” Thus, as each country have theirunique characteristics which are time-invariant, such country-fixed effects need to be controlled.
The FE model controls the country-fixed effects. The FE estimation model is described asfollows.
log (GDPpcp)it = β0 + β1 log(PGrowth)it + β2 log(Gbn)it + β3 log(Edu)it (ui +∈it)
Here, GDPpcp is the vector of dependent variables (i.e. GDP per capita at constant US$ 2005).
PGrowth is annual population growth rate as control variables. Population growth rate is taken as
control variable, because it is one of the major factors that affect GDP per capita, particularly indeveloping countries. And, it is expected to affect negatively to the GDP per capita. Gbn is thevector of explanatory variables (i.e. the KOF indexes of globalization).

Edu is anotherexplanatory variable which is secondary school enrollment rate. β is the coefficient of eachexplanatory variable that explain the magnitude and direction of impact on dependent variable,
i.e. GDP per capita. In addition, i represents the group identifier (i.e. 26 countries), and t
represents the time identifier (i.e. 27 years from 1980 to 2006). Similarly, ui +∈it is the composite
error term, where ui is the unobservable country effect fixed over time. To neutralize the different
units of the variables used, all the variables are logged before running the regression. Timedummies are also included in the regression and it is found that time and country fixed effects arejointly significant. But, the results are excluded from the result table. As “the robust variancematrix estimator is valid in the presence of any heteroskedasticity or serial correlation”(Wooldridge, 2002:275), robust estimators are used to correct the problem of heteroskedasticity
and serial correlations.

17

TABLE 3
GDP PER CAPITA, GLOBALIZATION AND EDUCATION (1980-2006)
Dependent Variable: GDP Per Capita
Explanatory variables
Log of population growth
Log of KOF index of globalization
Log of secondary school enrollment
Constant
R-Square (within)
Number of observations

Coefficients– .04* (0.03).84** (0.32).25* (0.16)
3.91*** (1.25).78
276

NOTES.– Fixed effect (FE) estimations are reported. Robust standard errors adjusted for clusters in countries arein parentheses. Annual data from 1980 to 2006 in 26 countries in East Asia and the Pacific and South Asia are used.
KOF index of globalization are taken from Dreher (2006) and the remaining variables are taken from the WorldBank’s WDI online database. The names of the countries and summary statistics of the data are given in Appendix 3
and Appendix 4 respectively. And, * p< .10, **p< .05, ***p< .01.

The result of the regression analysis is presented in Table 3. While the coefficients show
the magnitude, sign of the coefficient indicates the direction of effect. The number/s of asterisk[*] indicates the level of significance of the effect. No asterisk means no significant effect. Oneasterisk [*] means the effect is significant at 10 percent. Two asterisk [**] means the effect issignificant at 5 percent, and three asterisks [***] means the effect is significant at 1 percent. For
instance, as all the dependent and independent variables are logged and as the coefficient of
globalization is 0.84, which means if globalization index increases by 1 percent, GDP per capita
will increase by 0.84 percent. This highly positive impact of globalization on GDP per capita issignificant at 5 percent level. This result is consistent with the previous findings of positive
association of globalization and GDP growth by Dennison (1967) and Green et al (2007).
Similarly, it is also found that secondary enrollment has positive and significant effect on
GDP per capita. As the coefficient is 0.25, it evident that if secondary school enrollment isincreased by 1 percent, GDP per capita will increase by 0.25. This positive effect is significant at
10 percent level. This result further reconfirm many existing studies (for example, Barro 1991;
Stewart 1996; Haddad 1991) as discussed in the previous section.
As expected, the control variable, population growth, is found to have negative effect on
GDP per capita. If there is population growth at 1 percent, GDP per capita will decrease by 0.04
percent, and the effect is significant at 10 percent level. This result is rationale, because
population growth is considered as one of the major obstacles for development in developing18

countries. Many scholars argue that higher population growth rates have negative correlations
with economic growth, health and educational indicators, particularly in developing countries(Kelly and Schmitd, 1995; Kelly 1994; Shaw, 1989).
In sum, the result shows globalization and education have significant positive impact on
GDP per capita, Thus, this study that focuses on the Asia-Pacific region generally support theexisting literature, which emphasizes the central role of education for development as well as in
the globalization process.
Conclusion

General comparison and empirical analysis between successes and failures from the AsiaPacific region revealed that education plays a key role in optimizing the gain from globalization
for development. Although, globalization is claimed to be positive for national development, lackof trained human resources limits countries’ ability to take advantage of the positive benefits ofthe globalization process. The importance of having skilled human resources that will attract
foreign investment has become much greater as the potential impact of trade and investment has
increased with globalization, vis-à-vis other important factors of development, such as physicalinfrastructure, law and order, etc. This can be seen from the experience of successes, which had
well educated human resources, to compete in the global market and benefited significantly fromthe process of globalization. Thus, in addition to opening their countries, governments should
invest more in educational development if they are to benefit from successful globalization andexpanded prosperity.
However, it has not been an easy task for the failures to invest in education. Because of
the fragility of the countries, their governments have other short-term priorities, such as, disease
control, infrastructure development, and conflict and crisis management. Such governments
should undertake two major policy actions to attract investment in education: firstly, opening up
the education services to the private sector, and secondly, attracting donor communities withwell-designed and targeted educational programs especially to rural areas and poor people. The
private sector’s involvement can provide quality education in city centers where there is demandand people can easily afford these quality services. Consequently, the government can saveresources from these urban centers and invest them in rural areas and for disadvantaged
populations. Donor communities are another major source, both financially and technically, that19

the government should look to. If the government has a reliable program to reach out to the poor
areas and people, donor communities should play a significant role in the development of an
education system. Moreover, donor communities also have due responsibility to support suchpoorer countries. They should proactively facilitate the weak governments who are preoccupied
with tackling many other urgent problems, such as poverty, hunger, epidemics, natural disasters,
political instability, and conflicts.
Although, this study shows that education is an important factor in obtaining “successful”
development gains from globalization, the Philippines appears to be an exception. In spite of its
high performance on education and even high level of globalization, the Philippines’s GDP per
capita growth was surprisingly slow over the period of 1970 to 2006, and its poverty rate wasstill high. Further research is recommended to find out why this was the case.
In conclusion, multiple conditions are associated with rapid economic development, andno single factor can be considered a sufficient cause. However, education has been central to thedevelopment process in every case. It is worth noting that all the countries in the world thatdeveloped most rapidly, including Japan and many other East Asian economies, had near
universal primary education enrollments and high levels of adult literacy at the beginning of theirhigh economic growth.
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Psacharopoulos, George. 1994. “Returns to Investment in Education: A Global Update,” World
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21

APPENDIX 1
KOF INDEX OF GLOBALIZATION
Indices and Variables

Weights

Economic Globalizationi) Actual Flows
Trade (percent of GDP)

[37%]
(50%)
(19%)

Foreign Direct Investment, flows (percent of GDP)
Foreign Direct Investment, stocks (percent of GDP)

(20%)
(24%)

Portfolio Investment (percent of GDP)
Income Payments to Foreign Nationals (percent of GDP)

(17%)
(20%)

ii) Restrictions
Hidden Import Barriers
Mean Tariff Rate
Taxes on International Trade (percent of current revenue)

(50%)
(22%)
(28%)
(27%)

Capital Account Restrictions(22%)

Social Globalizationi) Data on Personal Contact
Telephone Traffic
Transfers (percent of GDP)
International Tourism

[39%]
(33%)
(26%)
(3%)
(26%)

Foreign Population (percent of total population)
International letters (per capita)

(20%)
(25%)

ii) Data on Information Flows
Internet Users (per 1000 people)

(36%)
(36%)

Television (per 1000 people)
Trade in Newspapers (percent of GDP)

(36%)
(28%)

iii) Data on Cultural Proximity
Number of McDonald's Restaurants (per capita)

(31%)
(43%)

Number of Ikea (per capita)
Trade in books (percent of GDP)

(44%)
(12%)

Political Globalization
Embassies in Country
Membership in International Organizations

[25%]
(25%)
(28%)

Participation in U.N. Security Council Missions
International Treaties

(22%)
(25%)

SOURCE.– Dreher, Axel (2006), available at: http://globalization.kof.ethz.ch/static/pdf/variables_2010.pdf

22

APPENDIX 2
COMPARISON OF ADULT LITERACY RATES OF SUCCESSES AND FAILURES(Various years from 1980 to 2008, depending on availability of the data)
Earliest
Country

FemaleMale

Recent
Total

Female

Male

Total

Successes
China

51.14

79.19

65.51

90.50

96.70

93.70

S. Korea

---

---

---

---

---

---

Malaysia

61.25

78.15

69.52

89.80

94.30

92.10

Thailand

83.89

92.21

87.98

91.53

95.60

93.51

Indonesia

57.69

77.47

67.31

88.79

95.16

91.98

Bangladesh

17.97

39.73

29.23

49.80

60.00

55.00

Nepal

9.15

31.67

20.57

45.40

71.10

57.90

Pakistan

14.77

35.38

25.73

39.97

66.84

53.70

Philippines

82.76

83.89

83.32

93.90

93.30

93.60

Papua New Guinea

---

---

---

---

---

---

Failures

SOURCE.– The World Bank, WDI online database.
NOTE.– Earliest data are from 1982 to 1984 and the most recent data from 2005 to 2008 depending on countries
and their data availability.
CHN: China; MAL: Malaysia; THL: Thailand; IND: Indonesia; BLD: Bangladesh; NEP: Nepal; PAK: Pakistan;
PHL: the Philippines; and PNG: Papua New Guinea.
--- = data not available

APPENDIX 3
LIST OF COUNTRIES INCLUDED ON REGRESSION ANALYSIS
1.
2.
3.
4.
5.
6.
7.
8.
9.

Australia
Bangladesh
BhutanChina
FijiHong Kong
India
Indonesia
Japan

10. South Korea
11. Lao PDR
12. Malaysia
13. Magnolia
14. Nepal
15. New Zealand
16. Pakistan
17. Papua New Guinea
18. Philippines
23

19. Samoa
20. Singapore
21. Solomon Island
22. Sri Lanka
23. Thailand
24. Tonga
25. Vanuatu
26. Vietnam

APPENDIX 4
SUMMARY STATISTICS OF DATA USED IN REGRESSION ANALYSIS
Variable

Observation

GDP per capita, PPP(constant 2005 int’l $)Population growth
KOF index ofglobalization
School enrollment,
Secondary (% gross)

Mean

Std. Dev.

Minimum

Maximum

691

7296.75

9496.896

523.3145948.72

702

1.670028

0.95085

-2.36

4.81

675

43.03191

17.53921

16.54

88.95

294

64.14459

32.45704

6.01

161.66

SOURCE.– Dreher (2006) for the KOF index of globalization; the World Bank, WDI online database for allother variables.
NOTES.–Annual data from 1980 to 2006 for 26 countries in East Asia and the Pacific and South Asia areused. The names of the countries included in the analysis are given in Appendix 3.

APPENDIX 5
CORRELATION MATRIXGDP PCP

Population
growthGlobalization

GDP per capita, PPP(constant 2005 int’l $)1.0000Population growth-0.4140

1.0000

KOF index of globalization

0.7368-0.3892

1.0000School enrollment, Secondary(% gross)

0.7356-0.6273

0.7148Schoolenrollment

1.0000SOURCE.– Dreher (2006) for the KOF index of globalization; the World Bank, WDI online database for allother variables.
NOTES.– Annual data from 1980 to 2006 in 26 countries in East Asia and the Pacific and South Asia areused. The names of the countries included in the analysis are given in Appendix 3.

24

GIARI Working Paper Vol. 2010-E-2,

February 2011
Published by Waseda University Global COE Program
Global Institute for Asian Regional Integration (GIARI),
Waseda University, Nishiwaseda Bldg. 5F#507 1-21-1
Nishi-waseda, Shinjuku-ku, Tokyo 169-0051 Japan
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25