HUMAN CAPITAL AND INCLUSIVE GROWTH:
EVIDENCE FROM SELECTED DEVELOPING COUNTRIES
by
KAMRAN KHAN
(Regd. No. 2003-GBAB-757)
Session: 2012-14
Kashmir Institute of Economics
Faculty of Arts
University of Azad Jammu & Kashmir
Muzaffarabad, Pakistan
1
ABSTRACT
The call for inclusive growth has been unanimously declared by the
researchers policymakers across the world to deal with the problems of massive
unemployment and income inequality, in particular. Inclusive growth is
characterized by robust economic growth, poverty elimination, employment
generation and reduction in income inequality. This study examines the impact of
human capital on inclusive growth by using penal data from the 19 selected
developing countries for the period 2000 to 2014. The Generalized Method of
Movements (GMM) is used for the estimation of our empirical model. The results
show that the human capital development through education and health is a
foundation for achieving inclusive growth. Physical capital, trade openness and
foreign direct investment foster greater inclusiveness, while population growth
negatively affects the inclusive growth.
2
Chapter 1
INTRODUCTION
1.1 INTRODUCTION AND BACKGROUND OF THE STUDY
Economic growth tells us whether an economy is growing or declining. In
the last four decades of the twentieth century, economic growth has gained a lot of
attention from well-known economists, policymakers and the researchers as well. It
has been at the heart of discipline in the late sixties. A lot of research work has
done on this subject especially on the models of long run growth determination in
both 1980s and 1990s (Barro and Sala-i-Martin, 2003).
While talking about the importance of economic growth, it is one of the key
indicators of development. It is, almost the only factor that directly affects the
individual's income level (Sala-i-Martin, 2003 a). The long run aggregate economic
growth expands the per capita GDP, raises the living standard of the world
population and integrates the world economies through trade. It calls for the
continuous improvements in the technology and the accumulation of human capital
through investment in health, education and research and development. This
increases the output level of the economies and hence the income level of the
individuals.
As, Solow (1957) predicts that the growth process must slowdown in the
absence of continuous improvements in the technology. Lucas (1988) concludes
that the investment in human capital and knowledge is necessary to enhance the
growth process as human capital is an important determinant of the long run
economic growth. Similarly, Romer (1986) indicates that the investment in people
3
through health, education and R&D raise the stock of human capital and hence the
productivity as well.
Moreover, the historical data set shows that the economic growth has not
only raised the aggregate GDP and income level of the individuals, it has also
reduced the poverty level and even the income inequalities to some extent. For
instance, Sala-i-Martin (2003a) finds that the income level of the individuals from
all over the world has increased during the period 1970-2000. He has also observed
an expansion in most of the economies as well as a positive evolution of incomes
around the globe. Sala-i-Martin (2003b) concludes that a number of people below
the poverty line have substantially declined, especially in the regions such as
Europe and United States experiencing larger growth rates. The result is almost
same for both the developed and the developing regions like United States, East
Asia and South Asia, respectively. Lastly, the income inequalities are declined
slightly in last two decades of the previous century (Sala-i-Martin, 2003a).
In conclusion, the importance of economic growth is obvious. As discussed
earlier, it raises the individual's incomes, expands the level of output and the GDP
per capita. It calls for improvements in the technical knowledge, accumulation of
both physical and human capital stock to uplift the long run living standards.
Despite the importance of GDP, the economists have observed some serious
economic problems that are often associated to the economic growth, of which the
income inequality is the most important. Moreover, it may not wipe out poverty
and unemployment from the developing world, in particular. The existence of
poverty and unemployment is still a challenge for the countries. It is seen that the
economic growth is often accompanied by income inequality especially in the
4
developing countries (Fosu, 2010). Similarly, income inequality, poverty and
unemployment remain high in Africa, in spite of rapid economic growth in the
recent years (Anyanwu, 2013).
Rapid economic growth has put a significantly smaller impact on poverty in
many regions like Eastern Europe, Central Asia, Middle East, North Africa and in
India, particularly (IMF, 2013). According to Sala-i-Martin (2003a), poverty has
risen sharply in both Eastern Europe and Central Asia during 1970-2000. He also
concludes that both the income of the poorest ones and the number of people below
the poverty line do not decline significantly. Matilda (2013) argues that the
economic growth alone is not a sufficient tool to wipe out poverty. Fosu (2010) has
observed that the rapid economic growth is combined by the slow pace of poverty
reduction in many economies. Despite rapid economic growth in many regions,
poverty remains a real threat for a number of workers in the developing world.
Moreover, it is seen that a huge bulk of adults is unable to earn more than two US
dollars per day in most of the developing countries (ILO, 2011).
Similarly, the income inequality is another most important problem that is
often associated to the aggregate economic growth. As rapid economic growth is
usually accompanied by higher income disparities in many regions (Klasen, 2010).
Similarly, Ravallion (2007) argues that the income inequality is the by-product of
economic growth and almost unavoidable. In the last two decades, the income
inequality has risen in many regions (IMF, 2013). Despite rapid economic growth,
the income inequality has raised in most of the OECD countries over last three
decades (OECD, 2012). The long run economic growth has raised the income
inequality in many developing economies (Todaro and Smith, 2005). It has been
5
observed that the spells of rapid economic growth has risen the income inequality
in South Asia. Moreover, it has pushed the income inequality and poverty in
opposite directions (Osmani, 2008; Lee et al., 2013).
While talking about the problem of unemployment which is the most
undesirable consequence of the recent economic crisis, it has been observed that
two hundred million people are unemployed in 2010 (ILO, 2011). There exists an
inverse relationship between economic growth and unemployment as predicted by
Okun (1962), however the transformation rate of economic growth into
unemployment reduction remains slow in a number of developing countries (Fosu,
2010). Economic growth has failed to reduce the structural unemployment that
arises due to the mismatch between the available jobs and the qualification of the
workers (Kerishan, 2011). The growth of employment remains low in a number of
economies, which reflects the poor performance of economic growth regarding
employment (Kapsos, 2005). Furthermore, the US economy has observed the
highest ever unemployment rate, that is eight percent in 2012, in spite of
resumption of output growth since 2009 (Levine, 2013). It means that the economic
growth itself is not sufficient to generate employment to absorb the majority of
workers.
In short, the contribution of economic growth in the world economic
development is significant. However, the existence of poverty, unemployment and
the rising income inequalities particularly, after the global financial crisis are still a
challenge for most of the economies and demands for an alternative growth
process. For instance, the economies need such type of a growth process that
creates more jobs and reduces poverty (IMF, 2013). Moreover, rapid economic
6
growth alone is not a sufficient tool to eliminate higher levels of poverty and
income inequality (Matilda, 2013).
1.2 Significance of Inclusive Growth
Inclusive growth is considered as the most suitable pathway to distribute the
fruits of economic growth among masses. It also ensures the participation of the
majority of workers and especially the lower segments of the population in the
growth process. As the rapid economic growth is often accompanied by rising
income inequality in many regions, therefore, many international donors and
agencies are emphasizing on the promotion of inclusive growth in order to reduce
both poverty and income inequality (Alexander, 2015). The recent emphasis on
inclusive growth has originated from the fact that economic growth alone does not
reduce income inequality and unemployment while the inclusive growth ensures
both the pace and the pattern of economic growth (World Bank, 2009).
After global financial crisis, high unemployment and rising income
inequalities have drawn the attention of policy makers, governments and the
international agencies to adopt the goal of inclusive growth (Bordo and Meissner,
2012). For instance, inclusive growth should be reflected in the UN post-2015
agenda and considered as the prerequisite for sustainable development (ILO, 2011).
African development bank has endorsed inclusive growth as an agenda for
economic development in Africa (AfDB, 2013). Furthermore, the Asian
development bank, in its strategy 2020 has declared inclusive growth as one of
three strategic pillars along with regional integration and environmental
sustainability (ADB, 2010).
7
In spite of significant attention paid to the promotion of inclusive growth,
there is no unanimous definition of this concept. Inclusive growth is still an elusive
concept (Ramos et al., 2013). It is a broad concept that includes large part of the
labor force of a country and reduces the poverty as well (WB, 2009). Inclusive
growth is different from pro-poor and broad based growth. For instance, pro-poor
growth focuses only on economic growth and the poverty measures (WB, 2009). It
reduces the poverty level and raises the income level of the poor people only
(Ravallion and Chen, 2003). Similarly, the broad based growth is concerned with
the involvement of all the sectors of an economy whereas the shared growth
focuses only on the distribution of income. While the inclusive growth is more
comprehensive, it concentrates on both the economic output and the distribution of
income at the same time (Alexander, 2015). More specifically, the inclusive growth
ensures high per capita growth, eradicates poverty and lowers the income
inequality (Rauniyar and Kanbur, 2009). It is the growth process that reduces
poverty and enables the individuals to participate in the growth process to share
benefits (Elena and Sushana, 2010). In summary, it is a growth episode that allows
the participation of all the members of a society especially the poor that is the
disadvantaged groups in the growth process and reduces the income inequality
through education, health and nutrition (Klasen, 2010).
It is evident from literature that the measurement of inclusive growth is still
a challenge due to the absence of a commonly agreed definition (Klasen, 2010).
However, Anand et al. (2013) captures the inclusive growth by using only two
indicators that are income growth and the distribution of income. Ramos et al.
(2013) measures the inclusive growth by using three indicators that are poverty,
8
income inequality and employment to population ratio. While, the key
determinants of inclusive growth are human capital, trade openness and foreign
direct investment (Anand et al., 2013). Similarly, Alexander (2015) finds high per
capita growth, productive employment and investment in human capital as the
important determinants of inclusive growth. Despite high per capita growth and
trade openness, investment in health and education, progressive taxes and strong
institutions are the key factors that contribute to inclusive growth (CAFOD, 2014).
Keeping in view the significance of inclusive growth, this study analyzes
the impact of human capital development on inclusive growth. For this purpose, I
have disaggregated the human capital development into education human capital
and health human capital. Furthermore, a relatively broader index of inclusive
growth has been used by combining all four indicators proposed by Anand et al.
(2013) and Ramos et al. (2013) which are economic growth, poverty, income
inequality and employment.
1.3 Human Capital and Inclusive Growth
It is obvious from literature that the human capital is an important
determinant of economic growth for both developed and the developing countries.
The contribution of the human capital accumulation to economic growth has been
remarkable and has increased over the last two decades (Fernandez and Mauro,
2000). The human capital accumulation is an important source of economic growth
in advanced economies (Abbas, 2000). Investment in human capital is an important
factor that contributes to economic growth (Romer, 1986; Lucas, 1988).
9
Human capital refers to knowledge, skills and the competencies that are
embodied in the individuals (OECD, 2001). The idea of human capital is used for
education, skills and health of the workers that enhances their productivity and
efficiency (Todaro and Smith, 2005). In literature, different proxies are used to
capture the human capital such as expenditures on education, health expenditure,
primary and secondary school enrolment etc. Barro (1991) has used both primary
and secondary school enrolment to measure the human capital. While, Bloom et al.
(2004) uses health as a proxy for human capital and finds the positive impact of
health on economic growth.
In this study, we will examine the impact of human capital on inclusive
growth. The human capital affects the inclusive growth through different channels.
Human capital development through education enhance both the learning and
absorption capacities and capabilities of the workers. It also enables the individuals
to better understand, adopt and even produce the sophisticated production
techniques. Indeed, the productivity of workers rises, they earn more wage which
in turn enhance the economic growth and reduces the income inequality to increase
the degree of inclusiveness (ADB, 2011). Moreover, education raises the quality of
workers and enables them to create productive employment that reduces the
poverty and promotes the inclusive growth (Balakrishnan, 2013; Anand et al.,
2014).
Human capital development through health is another way to achieve the
inclusive growth. Firstly the good health, which is necessary for a good brain,
enables the workers to better understand and execute the production techniques.
Furthermore, the healthier workers are always more efficient and productive. They
10
work for more hours, avail less sick leaves and serve for a good number of years.
Therefore they have been highly learned and experienced enough to earn more
which reduces the income inequality, improves the distribution and creates decent
employment that reduces poverty and promotes the degree of inclusiveness (Bloom
et al., 2004; Adedeji, 2013; ADB, 2011). While poor health condition of the
workers badly affects the participation of the labor force in the economic activities.
Consequently, they earn lower wages and sometimes they are fired from their jobs
(Strauss, 1986). This leads to an increase in the income inequality and
unemployment that are opposite to the growth inclusiveness.
As good health and better education enables the lower segments of
population to participate in the growth process to share the benefits (CAFOD,
2014). Due to this reason most of the studies propose human capital as an
important policy measure to achieve the goal of inclusive growth. Human capital
development is one of the important determinants of inclusive growth (Alexander,
2015). Government spending on health and education significantly affects the
inclusive growth particularly in developing countries (Hur, 2014). In spite of
sustained economic growth and good governance higher spending on health and
education is an important factor that enhances the degree of inclusiveness (Ali and
Zhuang, 2007). Better educated workforce will help the countries to achieve
inclusive growth through poverty and income inequality reduction (Anand et al.,
2014). Investment in health and education is among the key sectors that contribute
to inclusive growth (AfDB, 2013).
Lastly, our study is dissimilar from the above studies in three different
ways. It contributes in literature in three folds. Firstly, we will disaggregate the
11
human capital development into education and health. Moreover, we will measure
education by secondary school enrollment and health by using life expectancy
which is the most appropriate way to capture the human capital development as
compared to the public expenditures on health and education, especially in the
developing countries. Because public expenditure on health and education do not
reflect the expenditures by the private sector which makes a significant
contribution towards the development of human capital. Secondly, we will use a
relatively broader index for inclusive growth by combining the all four indicators
e.g. economic growth, poverty, income inequality and employment to population
ratio that are indicated by both Anand et al. (2013) and Ramos et al. (2013).
Finally, we emphasize only on human capital to measure its impact on inclusive
growth for selected developing countries over the period 2000-2014.
1.4 OBJECTIVES OF THE STUDY
The objectives of this study are:
i.
To highlight the need for inclusive growth.
ii.
To analyze the impact of education and health human capital on inclusive
growth.
1.5 HYPOTHESIS
H0: Human capital development does not affect inclusive growth.
H1: Human capital development affects inclusive growth.
1.6 ORGANIZATION OF THE STUDY
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The study is organized as follows; chapter 2 presents the review of
literature. The third chapter explains the material and methods. Chapter 4 discusses
the empirical findings. While the last chapter presents the conclusions and
recommendations.
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Chapter 2
REVIEW OF LITERATURE
2.1 INTRODUCTION
After global financial crisis, rising income inequalities and higher levels of
unemployment in the developing and even some of the advance economies has
drawn the attention of numerous governments and policy makers to adopt the goal
of inclusive growth. Recently, a number of international agencies and donors are
emphasizing on the promotion inclusive growth to tackle with the problems of
unemployment and the income inequality (Bordo and Meissner, 2012). For
instance, India has been switching towards high, sustained and more inclusive
growth in order to achieve the goal of development (Planning Commission of
India, 2006). Similarly, China has prioritized inclusive growth in its 11th five year
plan (State Council of China, 2006). The G20 leaders, in 2013 have committed to
address the inclusive growth as an agenda for development. Moreover, the Asian
Development Bank in its strategy 2020 has declared inclusive growth as one of the
three strategic pillars along with regional integration and environmental
sustainability (ADB, 2010).
Despite the sluggish and uneven global recovery in the last five years,
China has achieved more sustained growth by reducing both poverty and income
inequality. This shows that China is moving towards more inclusive growth
(OECD, 2014). Moreover in some regions, the rapid economic growth is followed
by the higher levels of unemployment and characterized as futureless and jobless
growth. That is the reason, the inclusive growth has become a new mantra of
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development (Tilak, 2007). In spite of significant attention from eminent researcher
and policy makers, there is no commonly agreed definition of this concept.
Inclusive growth makes sure high per capita growth, eradicates poverty and lowers
the income inequality (Rauniyar and Kanbur, 2009). The inclusive growth is more
comprehensive, it concentrates on both the economic output and the distribution of
income at the same time (Alexander, 2015). The important determinants of
inclusive growth are investment in health and education, school enrollment,
literacy rate, infrastructure development, industrial employment, good governance,
financial sector development, institutional soundness, public investments and trade
openness (Krishnan et al., 2013; Anand et al., 2014; Ali and Zhuang, 2007).
In conclusion, the inclusive growth is relatively a new idea and has a very
short history of hardly a decade or little more. Furthermore, we find only a few
studies in this area. The rest of the research work on this concept is comprised of
policy documents and research reports. However, it has been receiving a significant
attention from the policy makers of both developing and advance economies to
achieve the goal of development (Ramos et al., 2013).
2.2 HUMAN CAPITAL AND INCLUSIVE GROWTH
Human capital is considered as an important determinant of long run
economic growth. It refers to knowledge, skills and the competencies that are
embodied in the individuals (OECD, 2001). Moreover, the notion of human capital
is usually used for health and education of the workers that enhances their
productivity and efficiency (Todaro and Smith, 2005). The followers of Lucas
(1988) view the human capital as an important input factor that refers to the skills
15
of the workforce. While the followers of Romer (1990) see the human capital as a
factor that facilitates the process of research and development (Leeuwan, 2006). In
literature, different proxies have been used to capture the human capital like
spending on education, health expenditure, primary and secondary school
enrolment and tertiary education. For instance, Barro (1991) has used both primary
and secondary school enrolment to measure the human capital. Similarly, IMF
(2013) has used both school enrollment and spending on education as proxies to
capture the human capital. African Development Bank (2013) measures human
capital through tertiary education. While Bloom et al. (2004) uses health as a proxy
to capture the human capital.
Krishnan et al. (2013) argues that the education is one of the most
important determinants of inclusive growth, in spite of industrial employment and
financial reforms. The impact of education measured by the years of schooling and
industrial employment is relatively stronger than health expenditures and financial
development. Similarly healthcare, trade openness and labor share of income also
positively affect the inclusive growth. Furthermore, they suggest a number of
policies like higher spending on health and education, increase in pension and a
wide-ranging financial system in order to enhance the degree of inclusiveness. Hur
(2014) has examined the relationship between fiscal policy and inclusive growth by
using the cross country panel data. He has used the panel vector auto regression
PVAR for sake of estimations. The results show that the gross fixed capital
formation has a strong positive impact on economic growth. While government
spending on health and education significantly affects the inclusive growth
especially in the developing countries. Moreover he recommends higher spending
16
on health, public investment and social subsidies in order to enhance the degree of
inclusiveness. Adedeji (2013) proclaims that the education and health are the
important contributing factors to the inclusive growth. Secondary school
enrollment and good health increase the productivity of the workers and improve
the distribution of income. Regardless of better access to health and education, the
targeted subsides and promotion of employment are the important policy measures
to achieve more inclusive growth. Similarly, Haan (2013) indicates that the strong
economic growth, human capital development and good governance are the
important contributors to the inclusive growth. Human capital development along
with robust economic growth significantly affects the inclusive growth.
Inclusive growth is usually characterized by equal opportunities to all. It
enables the individuals to participate in the growth process on the equal basis.
Moreover inclusive growth is a key to reduce the income inequality and to
eradicate poverty. The high and sustainable economic growth and social inclusion
are the two most important ingredients of inclusive growth that are obtained by
investing in health and education. Educated and healthy workforce enhances the
degree of inclusiveness by raising the worker's productivity and creating the
productive employment. In spite of education and healthcare, investment in
infrastructure and energy, financial sector development and good governance are
the important policy tools to achieve the target of inclusive growth (Ali and
Zhuang, 2007). Spending on education and high literacy rate along with robust
economic growth has a significant impact on inclusive growth. Education is a
precondition for inclusive growth. It raises the quality of workforce which in turns
enhance the economic growth and reduces the level of poverty, Moreover, public
17
investment is also an important contributor to inclusive growth (Anand et al.,
2014). Human capital development through substantial investment in both health
and education enables the majority of the workers to participate and hence
contribute in the growth process by creating more productive and decent
employment. As the result, a large number of workers have not only absorbed in
the growth process but also earn more income. This leads to more inclusive growth
(Tanaka, 2015). Higher spending on health and education significantly affects the
inclusive growth. Similarly, progressive taxes, higher pension expenditures,
increased labor shares in income and social securities are also the important factors
that enhance the degree of inclusiveness (Lee et al., 2013). In spite of good
governance and sound institutions, investment in health and education to enhance
the productivity of workers is an important factor that contributes to the inclusive
growth along with high and sustained growth that creates more jobs (Zhuang,
2010). Similarly, the empirics reveal the People’s Republic of China has achieved
more inclusive growth through increased government spending on health and also
by providing unemployment benefits to workers (OECD, 2015). Good and quality
education is necessary for inclusive growth. It is not only an instrument to achieve
the inclusive but a precondition as well (Tilak, 2004).
Similarly, a good number of research reports published by the different
international agencies and policy centers have proposed that the human capital is
an important policy measure to achieve the target of inclusive growth. For instance,
the governments have to invest in human capital in order to make the growth
process inclusive as expenditures on health and education reduce poverty and the
income inequality by ensuring the participation of poor people in the growth
18
process (CAFOD, 2014). To achieve the target of inclusive and pro-poor growth, it
is necessary to invest in human capital in spite of infrastructure development, social
protection and progressive taxation (Alexander, 2015). Economies have to invest in
basic infrastructure, heath services and on both secondary and higher education to
achieve the inclusive growth and development (Samans, 2015). Investment in
health and education is among the key sectors that contribute to inclusive growth
(AfDB, 2013). The developing countries have to focus on both basic and higher
education in spite of export diversification in the areas of comparative advantage
and innovation to achieve more inclusive growth (World Bank, 2007).
Lastly, our study is different from the above studies in a way that we will
disaggregate the human capital development into education and health. More
specifically, we will measure education by secondary school enrollment and health
by using life expectancy rather than public expenditure on health and education.
Because public expenditure on health and education does not reflect the
expenditures by the private sector as it is an important contributing sector to human
capital development especially in the developing countries. Secondly, we will use a
relatively comprehensive and broader index to capture the degree of inclusiveness
by combining the all four indicators i.e. economic growth, poverty, income
inequality and employment to population ratio that are indicated by both Anand et
al. (2013) and Ramos et al. (2013). Finally, we will emphasize on human capital
rather than finding out a number of determinants and the developing countries only
in order to make our analysis more specific.
As inclusive growth is the index of economic growth, poverty, income
inequality and employment to population ratio. Therefore, we will present the
19
literature review regarding human capital and above four indicators of inclusive
growth one by one to make our analysis more parsimonious.
2.2.1 Human Capital and Economic Growth
Economic growth is an important topic in economic literature. At a glance,
it tells us whether an economy is growing or declining. It is also an essential
ingredient of inclusive growth. Furthermore, economic growth is one of the key
indicators of development and almost the only factor that directly affects the
individual's income level (Sala-i-Martin, 2003 a). The long run aggregate economic
growth expands the per capita GDP, raises the living standard of the world
population and integrates the world economies through trade. It calls for the
continuous improvements in the technology and the accumulation of human capital
through investment in health education and research & development along with
physical capital accumulation and foreign direct investment.
Although, a good number of studies emphasize on the development of
human capital in order to achieve the sustained economic growth. However the
idea of human capital has been implicitly introduced by Arrow (1962) and
Sheshinski (1967) while explaining the mechanism of learning by doing.
Furthermore, human capital has been recognized as an important contributing
factor of economic growth in the famous work of Romer (1987, 1990) and Aghion
and Howitt (1992) regarding the long determination of economic growth (Barro
and Sala-i-Martin, 2004). Human capital enables the individuals to create and
absorb the contemporary knowledge and ideas. As the result, the economies with
more human capital have a tendency to grow faster by easily grasping the
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contemporary technological methods skills (Nelson and Phelps, 1966). Human
capital is essential for lashing the process of economic growth (Uzawa, 1965;
Rosen, 1976). Human capital is basically a factor of production. The development
of human capital should positively contribute to the long run economic growth
(Lucas, 1988). There exists a significant relationship between human capital
accumulation and economic growth. Investment in human capital is essential in
order to grow at a faster pace. The economies with greater human capital stock like
Japan, Taiwan and Korea have achieved more growth as compared to those with
lower human capital stock (Becker, 1995). Human capital is an important
component and a spur of the research and development sector. It enables the
individuals to create new thoughts and to develop the sophisticated methods of
productions. As a consequence, it boosts the growth of technology and hence the
economic growth as well (Romer, 1990). Human capital is important while
explaining the long run growth process. It strengthens the capabilities of the worker
so as to produce the higher levels of output (Mankew et al., 1992). Investment in
the human capital is an important factor that contributes the long run growth
process. Human capital also attracts the physical investment that also a key to
enhance the pace of growth. Furthermore, it has also been observed that a number
of poor countries fail to attract the physical capital from abroad just because of
insufficient human capital endowments (Romer, 1986; Lucas, 1990).
A number of studies measure the human capital by using general school
enrollment as a proxy. Education enrollment has a significant impact on long run
economic growth. Education enhances the productivity of the workers to earn more
wages. Furthermore, gross fixed capital positively affects the economic growth
21
while poverty is negatively associated to economic growth. So a plenty of funds
should be allocated to develop the skilled human capital through better education
and training (Ali et al., 2012). It is seen that there exist a strong positive
relationship between school enrollment and the long run economic growth, in
particular. Similarly, physical capital is found to have a positive association with
economic growth while inflation retards the long run growth process (Afzal et al.,
2010). Human capital development through both primary and secondary school
enrolment has a significant impact on economic growth in developing countries.
Moreover, human capital development is positively associated to physical capital
and enables the developing countries to attract the physical capital from abroad. So
the developing economies have to invest more in education in order to achieve the
higher levels of economic growth (Abbas, 2000). Educated workers have the ability
to accumulate more capital. They better understand the modern technology as
compared to the less educated workers. So that they are more productive. That is
why, an economy with more educated labor force growth at relatively a faster pace
(Fernandez and Mauro, 2000). Higher rate of school enrollment is a key to pull off
faster growth rate in long run. Furthermore, education moves up the productivity of
workers to earn more and to maintain the higher standard of living (Bils and
Klenow, 2000). Better education is a key to enhance the long run growth process. It
also improves the productivity of the workers (Bosworth and Collins, 2003).
Quality education and health care along with physical capital accumulation put a
strong positive impact on the economic growth (Amjad, 2005).
Similarly, a good number of studies lay emphasis on investment in both
health and education to achieve sustained economic growth. For instance, public
22
spending on health and education leads to human capital accumulation. It raises the
productivity of the workers in order to enhance the pace of economic growth. So it
is essential to invest more in health and education to drive the long run economic
growth (Imran et al., 2012). Health is also an important component of human
capital. It improves the productivity of the workers. So, it necessary to invest more
in health human capital in to enhance the growth process in both short run and long
run (Akram, 2008). Investment in human capital accompanied by physical capital
accumulation is a key to sustain the long run economic growth (Ashton et al.,
2002). Good health is an important aspect of human capital and critical for faster
economic growth. The healthier workers are very much energetic. They are always
productive enough to earn relatively higher wages. Because they work for a long
period of time and have higher levels of experience. As a result, an economy with
healthier work force and higher life expectancy has a tendency to grow faster
(Bloom et al., 2004). Spending on education fastens the national economic growth
process by raising the productivity of the workers. It allows the labor force to earn
more and hence raises their standard of living. In conclusion, the overall impact of
spending on education and training of the workers have been significant in advance
economies. So, it is essential to invest in education and training of the workers to
achieve sustained economic growth (Wilson and Briscoe, 2004).
In short, human capital development is equally important for both advance
and the developing countries to accelerate the long run growth process. Quality
education along with high school enrollment rate has improved the long run growth
in many developed countries (Hanushek, 2013). Increase in enrollment rates put a
strong positive impact on long run economic growth in developing countries as
23
well (Baldecci et al., 2008). The human capital accumulation has been an important
source of economic growth in advanced economies (Abbas, 2000). The
contribution of the human capital accumulation to economic growth has been
remarkable over the past two decades, in many regions (Fernandez and Mauro,
2000). A number of studies have emphasized on the cross country analysis to sort
out the relationship between human capital development and economic growth. It
is seen that both primary and secondary school enrolment leads to higher levels of
economic growth (Barro, 1991). Human capital development through secondary
school enrollment have a significant impact on the long run economic growth in a
number of countries (Mankiw et al., 1992).
2.2.2 Human Capital and Poverty
Reduction of poverty is one of the important goals of development. It is still
a challenge for a large number of economies across the globe, in spite of serious
efforts in this regard. For instance, poverty has risen sharply in both Eastern Europe
and Central Asia during 1970-2000. Moreover, the income of the poorest ones and
the number of people below the poverty line do not decline significantly (Sala-iMartin, 2003 a). Despite rapid economic growth in many regions, poverty remains
a real threat for a number of workers in the developing world. Moreover, it is
observed that a huge bulk of adults is unable to earn above US dollar two-a-day in
most of the developing economies (ILO, 2011). In short, economic growth is vital
to eradicate poverty but it not a sufficient condition (Matilda, 2013).
A good number of studies emphasize on the accumulation of human capital
through investment in health and education in order to reduce poverty. As there
24
exist a transparent relationship human capital development and poverty alleviation.
Investment in education and training is essential to accumulate the human capital.
It enhance the worker's efficiency and promotes the economic growth. Moreover,
spending on education significantly adds to the health condition of the workforce
and enables the poor workers to earn decent income (Becker, 1995). Investment in
education and health along with high rate of economic growth reduces the level of
poverty. A good number of economies have achieved the pro-poor growth through
the accumulating of human capital. As education and good health improves the
quality of the workforce so they create better jobs and earn more wage to reduce
the level of
poverty a faster pace (Khan, 2001). Investment in education is
important to develop the human capital. Education helps and enables the rural
workforce to participate in the economic activities. Higher levels of education are
linked to more wages and the self-employment as well in the rural areas, in
particular. Ability to earn higher wage and creation of self-employment reduces the
level of poverty. So the governments and policy have to focus on human capital
investment in order to reduce the poverty in long run (Winters and Chiodi, 2008).
It is a key to invest in education in order to break out the vicious circle of
poverty. Quality education raises the skills and capabilities of the workers to create
the decent jobs. Furthermore, it enables the biggest part of the population to
accumulate human capital to produce the higher levels of output and to earn high
incomes (Santos, 2009). Investment in education along with economic growth is
among the most important factors that reduce the poverty level. Empirics reveal
that decline in income inequality and the secondary school education have
significantly reduced the level of poverty in a good number of countries. Moreover
25
education increases the earning capacity of the workers. So the governments and
policy maker should focus on the promotion of education to eradicate poverty from
the developing countries (Janjua and Kamal, 2011). Human capital development
through investment in health, education and training enhance the productivity of
the workers, in rural areas particularly. As a consequence, they earn more income
to reduce the level of poverty (Allahdadi and Aref, 2011).
Human capital development through investment in education is essential to
reduce poverty, especially in the developing countries. As education breaks the
vicious circle of poverty by enhancing the capabilities of the workers to produce
the higher levels to output, so more emphasis should be given to education of the
poor in order to curb the poverty (Awan et al., 2011). Investment in education is
preliminary to reduce the poverty, especially in the developing countries. As there
exists a strong positive and significant relationship between poverty and
educational investment. It enhances the productivity of the workers to reduce the
poverty level by creating the decent employment, in long run. Moreover, faster
economic growth and physical capital formation are also important to eliminate
poverty. So the policy makers and the governments should invest more in
education in order to reduce poverty, particularly in the rural areas (Afzal et al.,
2012).
2.2.3 Human Capital and Employment
Having a quick glance on the problem of unemployment which is the most
undesirable consequence of the recent economic crisis, it has crossed two hundred
million people in 2010 (ILO, 2011). There exists a positive relationship between
26
economic growth and employment as predicted by Okun (1962), however the
transformation rate of economic growth into employment generation remains slow
in a number of developing countries (Fosu, 2010). Furthermore, the US economy
has observed the highest ever unemployment rate, that was eight percent in the last
half of 2012, in spite of resumption of output growth since 2009 (Levine, 2013). In
short, economic growth alone may not generate enough employment to absorb the
majority of workers.
Human capital development through education and health enhance the
learning capacity and the capabilities of the work force. It allows the workers to
better understand and hence execute the sophisticated production techniques.
Similarly, better nutrition positively contributes towards the health of the workers.
So the healthier workers are more efficient and punctual as physical health is a
prerequisite for the healthy brain. As a consequence, they produce more productive
and decent employment and earn higher incomes (Bloom et al., 2004;
Balakrishnan, 2013).
Human capital accumulation through education allows the participation of
the majority of the workforce in the growth process. It ensures the participation of
female worker as well and enable them to earn relatively higher age (Winters,
2012). There exist a significant and positive relationship between entrepreneurship
education and employment. Education of the entrepreneurs contributes positively
towards the creation of employment. Furthermore, public investment in health and
education also put a significant impact on employment (Ekanem and Emanghe,
2014). Human capital development through substantial investment in both health
and education enables the majority of the workers to participate and hence
27
contribute in the growth process by creating more productive and decent
employment. So the governments and policy makers need to lay more emphasis on
the development of human capital to engage the large number of workers in the
growth process (Tanaka, 2015).
Education is a key to employment. It raises the productivity of the workers
and allows them to earn higher hourly wages. Furthermore, education ensures the
participation of both male and female labor in output generating activities to raise
the living standard of the individuals (Castel et al. 2010). Human capital
development through primary and secondary school enrollment positively
influence the employment outcomes in both rural and the urban areas of the
developing countries. Moreover, it allows the participation of the workers in the
growth process. However, primary education is insufficient to earn higher incomes
(Wanbugu, 2011). Education is positively related to employment. It allows the
individuals to get jobs Furthermore, it leads to the re-employment of the
unemployed labor force as well (Riddell and Song, 2011).
2.2.4 Human Capital and Income Inequality
Income inequality is considered as the most important economic problem in
both developing and advance countries. The data set shows that the aggregate
economic growth has raised the income inequality in a number of large counties
during 1970 to 2000 (Sala-i-Martin, 2003 a). In the last two decades, the income
inequality has risen in many regions (IMF, 2013). Furthermore, the problem of
rising income inequality has been more worsen, especially after the global financial
crisis (Bordo and Meissner, 2012).
28
As it is a well-established fact that economic growth alone is not a
sufficient tool to reduce the income inequality. So a large number of studies
emphasize on human capital development in order to reduce the income inequality.
Human capital development through education and health enhance both the
learning and absorption capacities and capabilities of the work force. It also enables
the individuals to better understand, adopt and even produce and hence execute the
sophisticated production techniques. Furthermore, the healthier worker are more
efficient and punctual. They work for more hours, avail no more sick leaves and
serve for a good number of years. So they have been highly learned, experienced
and productive enough to earn higher wages. Consequently, this leads to the
reduction in the income inequality and hence the distribution (Bloom et al., 2004:
Balakrishnan, 2013; Anand et al., 2014).
Development of human capital by increasing the average years of schooling
is a key to reduce the income inequality in developing countries, in particular. As
education along with trade openness reduces the income inequality through
enhancement of the productivity of the workers. So the governments and
policymakers in the developing countries need to pay greater attention to develop
the human capital by investing more in education in order to alleviate the rising
income inequalities (Mahmood and Noor, 2014). Human capital formation through
improvements in both quantity and quality of education reduces the income
inequality. Better and equal access to education along with quality education
enables the workers to better understand the new technology. This raises the
productivity of workers to earn more in order to eliminate the income inequality
(Andersen, 2015). Human capital development is essential to reduce the income
29
inequality and to accelerate the process of development. Human capital
development through education enhances the productivity of the workers to earn
more income by creating productive and decent employment. So the governments
have to invest more in education to reduce the income inequalities and to enhance
the process of development (Ayodeji and Adebayo, 2015).
Human capital formation through educational attainment along with social
expenditures improves the distribution of income in number of countries.
Moreover, the increased number of schooling allows the work force to earn high
income by raising the productivity (Gregorio and Lee, 2002). Human capital
accumulation improves the process of development by reducing the income
inequalities. As compared to physical capital formation, the human capital
development is more inclusive. It not only raises the productivity of the workers
but also ensures the participation of the large number of workers. So more
emphasis should be given to human capital accumulation so as to reduce the
income inequality (Galor and Moav, 2004). Educational attainment is important for
the accumulation of the human capital. It raises the competencies and the
productive skills of the workers. As the result, they acquire the ability to produce
the higher levels of output to earn more wages. This significantly reduces income
inequality, particularly in the developing countries (Johansen, 2014). Human
capital accumulation through education is important to eliminate the income
inequalities. Quantity and the quality of education improves the skills of the
workers to produce the higher levels of output. So they earn more wages which, in
turns improves the distribution of income and raises the standard of living (Checchi
and Werfhorst, 2014). Human capital formation is a key to reduce the income
30
inequality. It raises the worker's productivity and allows the majority of the
workers to participate in the growth process so as to improve the distribution of
income (Galor, 2012).
31
Chapter 3
MATERIALS AND METHODS
This chapter presents the materials and methods designed to analyze the
impact of human capital on inclusive growth. The first section of this chapter is
devoted to the theoretical framework. The next section presents the definitions and
the construction of the variables. While the last section presents the study area,
sample size and the estimation technique used for sake of the analysis.
3.1 THEORETICAL FRAMEWORK
As the most important objective of this study is to examine the impact of
human capital on inclusive growth. While the inclusive growth refers to the
sustained economic growth that is accompanied by the eradication of poverty,
reduction in income inequality and the creation of employment (Anand et al., 2013;
Ramos et al., 2013). Similarly, the human capital consists of both the education
human capital and the health human capital. Now we link the human capital and
the inclusive growth through different channels that are; the human capital and
economic growth channel, human capital and poverty reduction through
employment creation approach and lastly the human capital and income inequality
reduction through increased earnings channel to inclusive growth.
Firstly, we explain the human capital and economic growth channel to the
inclusive growth. As education and healthcare are the two important components of
human capital and an important policy instrument to achieve the sustained long run
economic growth. Education enhances both the learning and absorption capacities
32
and the capabilities of the labor force. It also enables them to better understand,
adopt and even produce the sophisticated production techniques. Furthermore, the
educated workers accumulate more human capital through learning by doing and
hence become more productive as compared to the ordinary workers. Lastly, it
allows the individuals to produce new ideas that ultimately leads to technological
improvements in the long run.
Similarly, the good health is necessary for a high-quality brain. It enables
the workers to better understand and hence execute the most modern production
techniques. Moreover, the healthier workers are always more efficient and
productive. Because, they work for more hours, avail no more sick leaves and serve
for a good number of years to acquire relatively better productive skills. In short,
they are experienced enough to produce more as compared to the ordinary,
inexperienced and unhealthy labor force. Consequently, these improvements in
technology along with more productive and efficient labor force leads to high and
more sustainable long run economic growth (Nelson and Phelps, 1966; Romer,
1987, 1990; Fernandez and Mauro, 2000; Bloom et al., 2004). While this high and
sustainable long run economic growth is the first and the foremost ingredient and
even a prerequisite to the inclusive growth. It is also a key to reduce the extreme
poverty by creating more productive and decent employment opportunities
especially in the developing countries (Ali and Zhuang, 2007).
Similarly, the eradication of poverty by creating productive and decent
employment through human capital development is another way to achieve more
inclusive growth. Human capital development through better access to education
and health care enhance the productivity of workers, as discussed earlier.
33
Moreover, better education along with good health allows the workers to get the
decent jobs. It also enables the individuals to create new businesses and hence
more jobs in order to reduce the level of poverty that enhances the degree of
inclusiveness (Tanaka, 2015; Anand et al., 2014; Adedeji, 2013; Bloom et al.,
2004). For instance, education raises the quality of workers and enables them to
create productive employment that reduces the poverty and promotes the inclusive
growth (Balakrishnan, 2013).
Finally, the human capital development through education and health
reduces the income inequality by enhancing the earning capacity of the workforce.
Educated and healthy workers are productive and efficient as they better
understand, absorb and execute the contemporary productive techniques. Similarly,
the educated workers accumulate more human capital through learning by doing.
Lastly, the healthy worker serves for a good number of years. So they are skilled,
experienced and hence earn more wages to reduce the income inequality that raises
the degree of inclusiveness (ADB, 2011; Lee et al., 2013; Tanaka, 2015).
In conclusion, human capital development through education and health is
essential to achieve the inclusive growth in two different ways. Firstly, it promotes
the inclusive growth by accelerating the economic growth that is essential to reduce
poverty by creating the decent employment opportunities. Secondly, it leads to the
inclusive growth by reducing poverty through the creation of productive
employment and jobs. Furthermore, it reduces the income inequality by enhancing
the earning capacity and the capabilities of the labor force. As eradication of
poverty, reduction of income inequality and the creation of employment along with
34
sustained and long run economic growth are the important indicators of the
inclusive growth.
3.1.1 Human Capital and Inclusive Growth
As the economic growth is an important ingredient of inclusive growth
along with poverty eradication, employment generation and reduction in the
income inequality. However, the inclusive growth lays a greater emphasis on the
participation of all the segments of the population in the growth process. So we will
first develop a framework for economic growth and hence add up the other
important ingredients of inclusive growth to it to reflect the inclusiveness of the
growth process. As economic growth is the first and the foremost and even an
inevitable component of inclusive growth (Anand et al., 2013).
We start from the basic model of long run economic growth constructed by
Solow (1956) and Swan (1956). The Solow-Swan model is basically a neoclassical
form of production function that assumes constant returns to scale along with
diminishing returns to each of the factor input and some positive elasticity of
substitution of inputs. The basic equation of Solow-Swan model is;
𝑌 = 𝐴𝐹(𝐾, 𝐿)
3.1
Where Y is output, A is the exogenous technological change, K is physical
capital and L is the labor force. The Cobb-Douglas form of the above model,
specified by Barro and Sala-i-Martin (2003) is given by;
𝑌 = 𝐴𝐾 𝛼 𝐿𝛽
3.2
35
Where A ˃ 0 is the level of the technology and α is constant with 0 ˂ α ˂ 1.
Similarly β is also a constant with 0 ˂ β ˂ 1.
It is now important to note that Solow (1956) assumes the output, Y is the
function of only two factor inputs that are labor and capital denoted by L and K
respectively. While the technology, A is exogenous. One of the most important
prediction of Solow and Swan model is that, in the absence of technological
progress the growth process must cease and come to an end (Barro and Sala-iMartin, 2003).
However, in late eighties the contemporary research on the economic
growth has challenged the assumption of diminishing returns. A good number of
studies, particularly Romer (1986), Lucas (1988) and Rebelo (1991) have
proclaimed that the returns on investment in capital goods like human capital are
not necessarily diminishing. Furthermore, the incorporation of human capital is
important to avoid the diminishing return on physical capital accumulation, as
mentioned by Barro and Sala-i-Martin (2003).
Following the guidelines of the above studies, we incorporate the human
capital that consists of both education human capital and health human capital into
the production function in the functional form, as specified by Bloom et al. (2004).
Hence the above production function will take the following form;
𝑌 = 𝐴𝐾 𝛼 𝐿𝛽 𝑒 𝜑1𝑆 + 𝜑2𝐻
3.3
The human capital consists of two components that are education and
health; denoted by S and H respectively. Here S is the secondary school enrolment
36
that is a proxy for education and h is health which we proxy with life expectancy.
While φ1 and φ2 are the coefficients. The impact of human capital on output is
expressed in the powers of an exponential because it links the log wages to both the
years of schooling and the health status, as explained by Bloom et al. (2004) in his
study in the same way.
For linearity, we take log of equation 3.3
𝑙𝑜𝑔 𝑌𝑖𝑡 = 𝑙𝑜𝑔 𝐴𝑖𝑡 + 𝛼 𝑙𝑜𝑔 𝐾𝑖𝑡 + 𝛽 𝑙𝑜𝑔 𝐿𝑖𝑡 + Ф1 𝑆𝑖𝑡 + Ф2 𝐻𝑖𝑡 + 𝑙𝑜𝑔𝑒𝑖𝑡
3.4
We express all the variables in per capita form, hence the eq. 3.4 becomes
𝑦𝑖𝑡 = 𝛼0 + 𝛼1 𝑘𝑖𝑡 + 𝜑1 𝑆 𝑖𝑡 + 𝜑2 𝐻𝑖𝑡 + 𝑒𝑖𝑡
3.5
Where yit, α0, kit, lit and eit are the logs of Yit, Ait, Kit. Lit and eit respectively.
The human capital consists of both education and health. Now combining
both of the components of human capital and hence generalizing our empirical
model as;
𝑌it = 𝛼 + 𝛽𝐻𝐶𝑖𝑡 + 𝛷𝑋𝑖𝑡 + 𝑒𝑖𝑡
3.6
Where 𝑌𝑖𝑡 is the GDP per capita. It is the first ingredient of inclusive
growth, HCit is the human capital that is consists of health and education, Xit is the
vector of controlled variables such as gross fixed capital formation, labor force,
foreign direct investment and trade openness and 𝑒𝑖𝑡 is the error term.
The main objective of our study is to examine the impact of human capital
on inclusive growth. While economic growth is one of the important ingredients of
inclusive growth along with poverty eradication, employment generation and
reduction in the income inequality (Anand et al., 2013; Ramos et al., 2013). Now
37
we develop different econometric models to analyze the impact of human capital
on the other components of inclusive growth that are poverty, income inequality
and employment one by one, for the detailed analysis.
𝑌𝑖𝑡 = 𝛼 + 𝛽𝐻𝐶𝑖𝑡 + 𝛷𝑋𝑖𝑡 + 𝑒𝑖𝑡
3.7
Where, Yit is the Poverty (the second ingredient of inclusive growth), Xit is
the vector of controlled variables. These variables include GDP per Capita, Foreign
Direct Investment and Trade Openness.
𝑌𝑖𝑡 = 𝛼 + 𝛽𝐻𝐶𝑖𝑡 + 𝛷𝑋𝑖𝑡 + 𝑒𝑖𝑡
3.8
Where, Yit is Income inequality. It is the third ingredient of inclusive
growth. X3i is the vector of controlled variables including GDP Per Capita,
Population Growth, Foreign Direct Investment and Trade Openness.
𝑌𝑖𝑡 = 𝛼 + 𝛽𝐻𝐶𝑖𝑡 + 𝛷𝑋𝑖𝑡 + 𝑒𝑖
3.9
Where, Yit is the employment (the fourth ingredient of inclusive growth).
Lastly, we will combine all four ingredients of inclusive growth that are
economic growth, poverty, income inequality and employment by developing an
index. Hence, our model will take the form;
𝑌𝑖𝑡 = 𝛼 + 𝛽𝐻𝐶𝑖𝑡 + 𝛷𝑋𝑖𝑡 + 𝑒𝑖𝑡
3.10
Where, Yit is the Index of inclusive growth, Xit is the vector of controlled
variables. These variables include gross fixed capital formation, population growth,
foreign direct investment and trade openness. The eit is the error term.
38
3.2 DEFINITION AND CONSTRUCTION OF VARIABLES
This section presents the definitions and construction of both the dependent
and the explanatory variables.
3.2.1 Dependent Variables
Inclusive growth is our dependent variable. We use proxies for inclusive
growth such as growth, poverty and income inequality. In literature, there is
commonly agreed definition of inclusive growth (Klasen, 2010). Therefore, we use
relatively a broader definition to cover all four aspects of inclusive growth
specified by Rauniyar and Kanbur (2009), Ramos et al. (2013) and Anand et al.
(2013). These four ingredients/indicators are given below.
3.2.1.1 GDP Per Capita
Economic growth is the first and foremost ingredient of inclusive growth
(Anand et al., 2013). In literature, a number of proxies have been used to capture
economic growth. However, we have used GDP per capita, measured at current US
dollars as a proxy for economic growth. This proxy has also been used by Aoyagi
and Ganelli (2015) and Anand et al. (2013) to capture economic growth.
3.2.1.2 Income Inequality
Income inequality is also an important ingredient of inclusive growth
(Anand et al., 2013; Aoyagi and Ganelli, 2015). In this study, we have used Gini
net as a proxy for inclusive growth following Aoyagi and Ganelli (2015) and Hur
(2014). Gini net excludes both taxes and transfers (Hur, 2014).
39
3.2.1.3 Poverty
Poverty is another proxy of inclusive growth. Eradication of poverty is
essential to more achieve inclusive growth (Osmani, 2008; ILO, 2011; Alexander,
2015). Head count index/ratio is a most commonly used proxy for poverty.
However, we have used population undernourishment as a proxy to measure
poverty due to the unavailability of data for the developing countries.
3.2.1.4 Employment
Employment is also an important ingredient of inclusive growth (Rauniyar
and Kanbur, 2009; ILO, 2011; CAFOOD, 2014; Alexander, 2015). We have used
employment to population ratio (%) as a proxy for employment following Ramos
et al. (2013).
3.2.1.5 Inclusive Growth Index
Our last dependent variable is the index of inclusive growth. It consists of
all four indicators of inclusive growth specified by Ramos et al. (2013) and Anand
et al. (2013) that are mentioned earlier. The index of inclusive growth is
constructed by using Principal Component Analysis in three steps. Firstly, we have
selected the indicators that are; economic growth, poverty, income inequality and
employment. In the next step, we have selected/set the dimensions of the said
indicators. In last step, we have assigned weights to each indicator according to its
importance.
3.2.2 Explanatory Variables
3.2.2.1 Human Capital
40
Human capital is our variable of interest. We have disaggregated human
capital into education and health. We use secondary school enrollment (% gross) as
a proxy for educated human capital following Barro (1991), Adedeji et al. (2013),
Anand et al. (2013) and Hur (2014).
Similarly, life expectancy at birth (in years) is used as a proxy for health. In
literature, a number of studies have used life expectancy at birth (in years) as a
proxy to measure the health human capital. These studies include Bloom et al.
(2004), Adedeji et al. (2013), Matilda (2013) and Hur (2014).
3.2.2.2 Labor Force
Labor force is also our explanatory variable. We have used labor force
(total) participation in percentage as a proxy, following Hur (2014).
3.2.2.3 Trade Openness
Trade openness is measured as the sum of export and import to the GDP
ratio, following Aoyagi and Ganelli (2015) and Hur (2014).
3.2.2.4 Physical Capital
We have used gross foxed capital formation (percentage of GDP) as a
proxy in order to measure the physical capital following Hur (2014) and Ali et al.
(2012).
3.2.2.5 Foreign Direct Investment
We have used total FDI capital stock as proxy to measure the foreign direct
investment by following Anand et al. (2015).
41
3.2.2.6 Population Growth
We have taken the data of population growth (rise in population per
year/annual percent) in percentage following Johansen (2014).
3.3 DATA SOURCES
We use a panel of nineteen selected developing countries across the world
(see details in appendix-II) for the period 2000-2014 following Aoyagi and Ganelli
(2015). Here, it is important to mention that the developing is mainly based on the
availability of data.
Lastly, we have collected data from different sources. Data for economic
growth, physical capital, labor force, education, health, FDI, trade openness and
population growth have been collected from World Development Indicators. While
the data for poverty and income equality has been taken from UN Data Set and
SWIID respectively. Further details are given in Appendix I.
3.4 ESTIMATION TECHNIQUES
In this study, we have used the panel data to sort out the relationship
between human capital and inclusive growth. For this purpose, we have used
Generalized Method of Movements (GMM) following Mahmood and Noor (2014)
and Anand et al. (2013). The Generalized Method of Movements is supposed to be
the most suitable estimation technique in order to avoid the problem of endogeniety
(Anand et al., 2013).
3.4.1 The Linear GMM Estimator
42
In the following, we will briefly discuss that how the linear GMM estimator
is used in a dynamic panel data model. The basic set up is defined as:
𝑦𝑖𝑡 = 𝑥𝑖𝑡 𝛽 + 𝑢 𝑖𝑡
3.11
where β is the column vector of the coefficients that are estimated in the model.
While y and 𝑢 are the random variables and x is the vector of k regressors. The
GMM estimator hinges greatly on the assumption that the instruments are
orthogonal to the errors.
Now the data generating process in the dynamic panel models is iterated as:
𝑦𝑖𝑡= 𝛼𝑦𝑖𝑡−1 + 𝑥𝑖𝑡 𝛽 + 𝑢𝑖𝑡
3.12
Equation 3.12 may also be written as:
𝛥𝑦𝑖𝑡 = 𝛼𝑦𝑖𝑡−1 + 𝑥𝑖𝑡 𝛽 + 𝑢𝑖𝑡
3.13
This is our first difference GMM estimator. The GMM estimator controls
the problem of endogeniety by using the internal instruments. These instruments
are based on the lagged values of the explanatory variables used in the model.
Furthermore, it allows the consistent estimation of the parameters by taking second
or more lags even in the presence of measurement error which is the common
critique of the GDP data (Bond et al., 2001).
3.4.2
Post Estimation Technique
In GMM estimation, we may check the joint validity of the instruments
again by using the Sargan or Hansen test. It tells us that whether the instruments
are valid. In order to check the first order correlation in levels, it is required to look
43
for whether the second order correlation in difference exists or not. The rejection of
second order autocorrelation indicates that there is no autocorrelation.
3.4.3 Advantages of Using Panel GMM
It is important to note that Generalized Method of Movements (GMM) has
some advantages especially in the empirical estimation of economic growth. It has
been observed that the researchers usually use the average of output growth in
order to avoid the cyclical dynamics. As the result, the number of periods used in
the standard growth literature is generally small. The GMM estimator allows the
arbitrarily distributed fixed individual and time effects for the penal analysis.
Furthermore, the use of internal instruments based on the lagged values of the
explanatory variables allows them to become weakly exogenous (Bond et al.,
2001).
44
Chapter 4
RESULTS AND DISCUSSION
4.1 SUMMARY STATISTICS
It has been already mentioned in the introductory part of this study that the
analysis of the impact of human capital on inclusive growth is amongst our key
objectives. In this regard, we have used the penal data for nineteen developing
countries over the period 2000-2014. The summary statistics of the variables under
consideration is given below (Table 4.1).
Table 4.1: Summary Statistics of the Variables under Consideration.
Variable
Obs
Mean
Standard
Deviation
Minimum
Maximum
Income Inequality (Gini net)
285
41.303
8.3804
30.12
70.012
285
16.218
9.4053
4.90
43.20
GDP Per Capita
285
3.2937
0.3984
2.364
4.053
Employment to population Ratio
285
54.3036
11.72
30.70
81.95
Inclusive Growth Index
285
0.2448
1.0435
-2.240
3.490
Labor Force
285
59.096
10.954
40.26
85.45
Life Expectancy
285
67.305
7.2685
46.60
79.40
Physical Capital
285
23.391
6.0552
7.020
45.90
Secondary School Enrollment
285
66.595
19.371
21.03
95.04
Population Growth
285
1.6884
0.7432
0.142
4.96
Trade Openness
285
4.3022
1.9065
1.90
8.96
FDI
285
3.4567
3.2553
0.10
15.0
Poverty (Population
Undernourishment)
Source: WDI, SWIID and UN data set.
45
4.2 RESULTS DISCUSSION
Prior to the discussion of empirical results, it is important to mention that
we have constructed the index of inclusive growth to analyze the relationship
between human capital and inclusive growth. This index consists of all four
ingredients of inclusive growth that are economic growth, poverty, income
inequality and employment. Therefore, we used five econometric models. The first
four models examine the relationship between human capital and the all four
ingredients of inclusive growth one by one. While the fifth model analyzes the
impact of human capital on the index of inclusive growth.
4.2.1 Empirical Findings of Model I (Economic Growth)
Empirical findings of our first model given in eq. (3.6), in which economic
growth is our dependent variable are given below (table 4.2). The reason behind is
that the economic growth is first and the foremost ingredient of inclusive growth
(Anand et al., 2013).
The empirical results show that fundamental determinants of economic
growth like initial income, physical capital, education, health, labor force
participation, trade openness and foreign direct investment are significant.
Furthermore, the instruments used are valid and no autocorrelation is found.
Results in table 4.2 reveal that human capital development through
education (secondary school enrolment) has a positive and significant impact on
GDP Per Capita. This indicates that the education enhances the skill and hence the
productivity of the workers so they are able to produce the higher levels of output.
46
Table 4.2: Dependent Variable: Economic Growth (GDP Per Capita).
Variable
Coefficients
Lag GDP Per Capita
0.18**
(0.041)
0.012*
(0.062)
0.613**
(0.014)
0.012**
(0.031)
0.021***
(0.000)
0.007***
(0.000)
0.091**
(0.031)
0.26***
(.000)
Labor Force
Physical Capital
Life Expectancy
Education (SSER)
Trade Openness
FDI
Constant
Number of observations
Number of countries
Sargan P-value
266
19
0.06
AR1 (P value)
0.0012
AR2 (P value)
0.0932
Note: P values for z-test are in parenthesis. *,**,*** shows significance at 10, 5
and 1 percent respectively.
Moreover, education improves the quality of labor force and the most important
source of production (Bloom et al., 2004; Afzal et al., 2012; Ali et al., 2012; Barro,
1991). Similarly, human capital development through health (life expectancy)
positively affects the GDP Per Capita and significant as well. This result is in line
with the finding of Bloom et al. (2004). However, the contribution of education
and health not as strong as it may be. The possible reasons are that the developing
countries emphasize less on education and health as compared to the developed
nations (Hur, 2014).
47
The initial level of income (Lag GDP Per Capita) has a significant positive
impact on economic growth. Similarly, the impact of trade openness and foreign
direct investment is also positive and significant. These results are consistent with
the findings of Anand et al. (2013). Initial level of income, trade openness and FDI
are among standard economic growth determinants. Furthermore, trade openness
fastens the economic through efficient allocation of resources (Anand et al., 2013).
Lastly, the impact of physical capital and labor force participation on
economic growth is positive and significant. Especially, the impact of physical
capital (Gross Fixed Capital Formation) is stronger. These results are in line with
the findings of Afzal et al. (2012). Bloom et al. (2004) and Anand et al. (2004).
Furthermore, it satisfies the finding of Solow (1956) that the physical capital
accumulation leads to the long run economic growth.
4.2.2 Empirical Findings of Model II (Poverty)
Table 4.3 presents the empirical findings of our second model given in eq.
(3.7), where poverty is dependent variable.
Empirical results show that there is a negative and significant relationship
between economic growth and poverty. As one percent increase in economic
growth (GDP Per Capita) reduces poverty by 6.2 percent. This shows that the
economic growth is an important measure to reduce poverty even in the developing
countries. Moreover, it creates employment opportunities and raises the living
standard of the individuals (Matilda, 2013; Fosu, 2010; Auon, 2004).
Human capital development through both education and health is also
negatively and significantly related to poverty. The results reveal that one percent
increase in education reduces the poverty level by 3.1 percent. It shows that human
48
Table 4.3: Dependent Variable: Poverty (Population Undernourishment).
Variable
Coefficients
GDP Per Capita
-0.062**
(0.042)
-0.008*
(0.061)
-0.031*
(0.063)
-0.007
(0.201)
-0.012*
(0.071)
0.29**
(.002)
Life Expectancy
Education (SSER)
Trade Openness
FDI
Constant
Number of observations
Number of countries
Sargan P-value
266
19
0.053
AR1 (P value)
0.0016
AR2 (P value)
0.0861
Note: P values for z-test are in parenthesis. *, **, *** shows significance at 10, 5
and 1 percent respectively.
capital development through education is important to eradicate poverty.
Furthermore, education is amongst the significant policy tools to eradicate poverty
by enhancing the earning ability and the quality of the population in many
developing countries (Afzal et al., 2012; Janjua, 2011; Auon, 2004; Becker, 1995).
Similarly, human capital development through health (life expectancy) is also
important to reduce the level of poverty. It enables the labor force to participate in
the economic activities and to perform better. As the result, the healthy workers not
only participate in the production process but earn more wages to get out of
poverty (Allahdadi and Aref, 2011: Bloom et al., 2004).
49
Lastly, trade openness and foreign direct invest are also negatively
associated to poverty. However, the coefficient trade openness is statistically
insignificant. This highlights the need for the transformation of trade benefits
towards the eradication of poverty, in the developing countries (Matilda, 2013).
While foreign direct investment significantly contributes towards the eradication of
poverty. It lowers the poverty level by creating more employment opportunities
(Akmal et al., 2012).
4.2.3 Empirical Findings of Model III (Income Inequality)
Table 4.4 presents the empirical findings of our third model given in eq.
(3.8), where income inequality is dependent variable. Empirical results show that
the GDP Per capita, human capital development through education and health,
trade openness and FDI are inversely related to the income inequality and
significant. While population growth is positively associated to the income
inequality.
Our first explanatory variable that is GDP Per Capita is negatively related
to income inequality and significant at 5 percent. As one percent increase in GDP
Per Capita reduces the income inequality by 5.1 percent. This indicates that
economic growth is essential to reduce the income inequality in the developing
countries as well. As, it creates the decent employment opportunities to absorb
more workers in the production process (Mahmood and Noor, 2014; Fosu, 2010).
However, the transformation of the growth towards the reduction of income
inequality is relatively slow (Fosu, 2010).
The results show that the human capital development through education and
health has a negative and significant impact on the income inequality. Education
50
Table 4.4: Dependent Variable: Income Inequality (gini net).
Variable
Coefficients
GDP Per Capita
-0.051**
(0.031)
-0.014*
(0.081)
-0.032*
(0.092)
0.021*
(0.063)
-0.122***
(0.001)
-0.0012*
(0.065)
0.31*
(.091)
Life Expectancy
Education (SSER)
Population Growth
Trade Openness
FDI
Constant
Number of observations
Number of countries
Sargan P-value
266
19
0.067
AR1 (P value)
0.037
AR2 (P value)
0.091
Note: P values for z-test are in parenthesis. *,**,*** shows significance at 10, 5
and 1 percent respectively.
(secondary school enrollment) reduces the income inequality in two different ways.
Firstly, it enables the uneducated and the unskilled labor force to participate in the
production process. Secondly, it enhances the capabilities and skills of the workers
to produce enough to earn more wages (Hur, 2014; Matilda, 2013; Anand et al.,
2013). Similarly, health (life expectancy) also reduces the income inequality
significantly. The reason behind is that the healthier workers are productive and
efficient enough to earn high incomes so as to reduce the income inequality.
Because, they are better able to understand and execute the latest technology.
Furthermore, they work for a good number of years and experienced enough to
51
earn high incomes as compared to the unhealthy workers (Hur, 2014; Bloom et al.,
2004)
Population growth is positively associated to the income inequality and
significant. It is one of the reason behind rising income inequality in many
developing countries (Mahmood and Noor, 2014; Matlda, 2013). Trade openness is
negatively related to the income inequality and significant. It reduces the income
inequality by increasing the wages of both skilled and the unskilled workers
(Mahmood and Noor, 2014). Similarly, foreign direct investment negatively affects
the income inequality and significant. It reduces the income inequality by
improving the wage rates and the domestic policies in the developing countries
(Mahmood and Noor, 2014; Anand et al., 2013).
4.2.4 Empirical Findings of Model IV (Employment)
Empirical findings of our fourth model given in eq. (3.9), where
employment is our dependent variable are presented in the table 4.5 below.
Empirical results of our fourth model show that GDP Per capita, human
capital development through education and health, trade openness and foreign
direct investment are positively associated to the employment. While the
population growth is inversely related to the employment.
Our first explanatory variable GDP Per Capita is positively associated to
employment and significant. As one percent increase in GDP Per Capita raises the
employment to population ratio by 3.1 percent. This shows that the economic
growth is amongst the fundamental determinants of employment. Furthermore, it
52
creates more employment opportunities to absorb new workers (Bashier and
Wahban, 2013).
Table 4.5: Dependent Variable: Employment (EPR).
Variable
Coefficients
GDP Per Capita
0.031**
(0.041)
0.021*
(0.071)
0.031*
(0.063)
-0.123**
(0.000)
0.013**
(0.043)
0.021*
(0.074)
0.26**
(.032)
Life Expectancy
Education (SSER)
Population Growth
Trade Openness
FDI
Constant
Number of observations
Number of countries
Sargan P-value
266
19
0.063
AR1 (P value)
0.011
AR2 (P value)
0.0841
Note: P values for z-test are in parenthesis. *,**,*** shows significance at 10, 5
and 1 percent respectively.
Human capital development through education and health positively affects
the employment and significant. Human capital development through education
(secondary school enrollment) enhances the abilities and the capabilities of the
workers to participate in the productive activities. Moreover, it enables the
unemployed labor force to avail jobs with higher earnings (Winters, 2012;
Wambugu, 2011; Fosu, 2010). Similarly, human capital through health (life
expectancy) positively contributes towards employment. Because the healthier
53
workers are productive enough to create decent employment (Bloom et al., 2004;
Kapsos, 2005; Balakrishnan, 2013).
Population growth is negatively related to employment and significant. This
indicates that rise in population reduces the employment level. Moreover, it is one
of the reasons behind unemployment in most of the developing countries (Kapsos,
2005). Our second last explanatory variable trade openness is positively associated
to employment and significant. This shows that trade openness leads to an increase
in the employment as the share of exports rises, as highlighted by Kapsos (2005).
Moreover, trade openness promotes employment through efficient resource
allocation and dissemination of knowledge (Bashier and Wahban, 2013). Lastly,
foreign direct investment has a positive and significant impact on employment.
This indicates that the foreign direct investment promotes the level of employment.
Furthermore, this relationship is well established in the economic literature
(Bashier and Wahban, 2013).
4.2.5 Empirical Findings of Model V (Inclusive Growth)
Empirical findings of the fifth model given in eq. (3.10), where inclusive
growth is our dependent variable are given in the table 4.6 below.
In this model, our dependent variable is inclusive growth index which
consists of four components that are economic growth, poverty, income inequality
and employment. While physical capital, education, health, population growth,
trade openness and foreign direct investment are the explanatory variables.
Our first explanatory variable physical capital is positively related to
inclusive growth and significant. This indicates that gross fixed capital formation
54
Table 4.6 Dependent Variable: Inclusive Growth Index (IG).
Variable
Coefficients
Physical Capital
0.053**
(0.022)
0.023*
(0.063)
0.037**
(0.042)
-0.011**
(0.04)
0.027***
(0.000)
0.019**
(0.023)
0.29**
(.041)
Life Expectancy
Education (SSER)
Population Growth
Trade Openness
FDI
Constant
Number of observations
266
Number of countries
19
Sargan P-value
0.07
AR1 (P value)
0.001
AR2 (P value)
0.061
Note: P values for z-test are in parenthesis. *,**,*** shows significance at 10, 5
and 1 percent respectively.
promotes the growth inclusiveness. The result is in line with Hur (2014).
Furthermore, physical capital is amongst the fundamental determinants of
economic growth which the first and foremost ingredient of inclusive growth
(Anand et al., 2013).
Our variable of interest is human capital development through education
and health. Human capital development through education (secondary school
enrollment) is positively associated to inclusive growth and significant. Our result
is in line with the findings of Hur (2014), Anand et al. (2013) and Adedeji et al.
(2013). Education enhances the inclusiveness of growth through different channels.
Firstly, it improves the quality of labor force that promotes economic growth which
55
is the essential component of inclusive growth (Anand et al., 2013). Secondly, it
enables the labor force to participate in the growth process that creates employment
opportunities and reduces the level of poverty as well (Ali and Zhuang, 2007).
Lastly, education raises the capabilities and skills of the worker to produce that
higher level of output in order to earn more wages. This ultimately leads to the
reduction in income inequality (Hur, 2014; Matilda, 2013; Anand et al., 2013).
Similarly, human capital development through health is positively related to
the inclusive growth and significant. This indicates that the improved health (life
expectancy) is essential to enhance the degree of inclusiveness. Our result is in
relevance to the findings of Hur (2014) and Adedeji et al. (2013). As healthier
workers are better able to understand and execute the contemporary methods and
techniques of production. Because better health is prerequisite for a good brain
(Bloom et al., 2004). Moreover, they work for a good number of years and
productive enough to produce the higher levels of output. As the result, they not
only fasten the growth process to create employment but earn relatively higher
wages to reduce the income inequality that leads to more inclusive growth (Hur,
2014; Adedeji et al., 2013).
Population growth is negatively associated to inclusive growth and
significant. This shows that increase in population reduces the degree of
inclusiveness. Because rapid increase in population not only raises unemployment
and hence poverty and income inequality but also minimizes the fruits of economic
growth for the lower segments of population, in particular (Matilda, 2013; Kapsos,
2005). While trade openness has a positive and significant impact on inclusive
growth. It indicates that the trade openness helps the countries to achieve more
56
inclusive growth through efficient resource allocation that fosters the economic
growth (Bashier and Wahban, 2013). Furthermore, it creates employment
opportunities to enhance the degree of inclusiveness (Aoyagi and Ganelli, 2015;
Anand et al., 2013).
Lastly, foreign direct investment is positively associated to inclusive growth
index and significant. Our result is in line with the findings of Anand et al. (2013).
Foreign direct investment promotes the degree of inclusive growth by creating
decent employment opportunities and fostering the growth process. Furthermore, it
improves the wages rates of both skilled and unskilled workers in the developing
countries that lead towards more inclusive growth by reducing the income
inequality (Mahmood and Noor, 2014; Anand et al., 2013).
57
SUMMARY
CONCLUSION
The contribution of economic growth in the world economic development
is significant. However, the existence of poverty, unemployment and the rising
income inequalities particularly, after the global financial crisis are still a challenge
for most of the economies and demands for an alternative growth process. More
specifically, the economies need such type of a growth process that creates more
jobs to reduce poverty and income inequality. That is why, a number of
researchers, policy makers and international agencies are emphasizing on the
promotion of inclusive growth.
In spite of significant attention paid to the promotion of inclusive growth,
there is no unanimous definition of this concept. Inclusive growth is a broad
concept that include large part of the labor force of a country and reduces the
poverty as well. Inclusive growth concentrates on both the economic output and
the distribution of income at the same time. In short, it is considered as the most
suitable pathway to distribute the fruits of economic growth among masses and to
ensure the participation of the lower segments of population in the growth process.
One of the main objectives of this study is to analyze the impact of human
capital on inclusive growth. We have disaggregated human capital into education
and health human capital. While inclusive growth consists of four components that
are economic growth, poverty, income inequality and employment. Empirical
results show that human capital development through both education and health
positively affects the degree of inclusiveness by enhancing economic growth and
58
employment, by reducing poverty and the income inequality, in the developing
countries. Human capital development enhances the productive skills of the
workers to reduces poverty by fostering economic growth. Furthermore, it reduces
the income inequality by creating employment opportunities.
In spite of human capital development through education and health, gross
fixed capital formation, trade openness and foreign direct investment are found to
be the important determinants of inclusive growth. Gross fixed capital formation,
trade openness and foreign direct investment foster the inclusive growth while
population growth has a negative impact on inclusive growth.
POLICY RECOMMENDATIONS
Based on the empirical findings, this study recommends that more attention
should be paid to the development of human capital through both education and
health. Because human capital development through education fosters economic
growth that creates decent employment to reduce poverty. Furthermore, it lessens
the income inequality by increasing the wages of the labor force.
59
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Appendix-I
Table 1: Summary of variable definitions and sources.
Variable
Definition of Variable
Source of Data
Economic Growth
GDP Per Capita in current US World Development Indicators
Dollars.
Poverty
Percentage of the
undernourishment.
Income Inequality
Gini after taxation and transfers Squire
Income
(gini net).
Dataset (SWIID)
Employment
Employment to population ratio, at World Development Indicators
working age.
Physical Capital
Gross Fixed Capital Formation (% World Development Indicators
of GDP).
Labor Force
Labor force (total) participation in World Development Indicators
percentage.
Education
Secondary School Enrollment (% World Development Indicators
gross).
Health
Life expectancy at birth, total World Development Indicators
(years).
Foreign Direct Investment
Foreign Direct Investment, net World Development Indicators
inflows (% of GDP).
Trade Openness
Sum of imports and exports divide World Development Indicators
by GDP.
Population Growth
Population
percentage).
population UN Data Set
growth
Inequality
(annual World Development Indicators
71
Appendix-II
Table 1: List of countries with middle income (WB, 2014).
i) Countries with high middle income:
Algeria
Iran, Islamic Rep.
Jamaica
Jordan
Lebanon
Malaysia
Namibia
ii) Countries with lower middle income:
Bhutan
Egypt, Arab Rep.
Ghana
India
Indonesia
Mongolia
Morocco
Nigeria
Pakistan
Philippines
Thailand
Kenya
72
Appendix-III
Table 1: Principal Component Analysis. KMO Test
KMO and Bartlett's Test
KMO Bartlett's Test
0.638
of Sphericity
Chi. Square
120.964
Degree of Freedom
06
Sig.
0.00
Table 2: Component Matrix.
Variable
Component
GDP Per Capita
-0.773
Poverty
-0.538
Income Inequality
0.724
Employment
0.634
73