This research investigates the impact of human capital development on the manufacturing sector in Nigeria. It spanned through the period 1982 through 2016. The data used for this work were sourced from the Central Bank of Nigeria(CBN) statistical bulletin 2016 and the World Bank Development Indicators 2017. Adequate statistical measures(OLS) have been employed using a time-series analysis in the study. For objective two and three in this paper, one model was used to capture them and the variables of interest are government expenditure on education and government expenditure on health. The results revealed for the second and third objective of the research, that human capital development has a positive relationship with manufacturing output, though the two variables are not statistically significantly different from zero. This brings to limelight that for the manufacturing sector to achieve steady state level of output and satisfactory level of economic growth and development, there is need for human capital development to take place.

1. TITLE PAGE
The Impact of Human Capital Development on the Manufacturing Sector in Nigeria

2. APPROVAL PAGE
This Project has been supervised and approved as having satisfied the conditions for the award
of a Bachelor of Science Degree in Economics, Faculty of Social Sciences, University of
Nigeria, Nsukka.
................................................ ................................................
Dr. NATHANIEL URAMA DATE
(PROJECT SUPERVISOR)
................................................ ................................................
PROF. STELLA MADUEME DATE
(H.O.D ECONOMICS)
................................................ ................................................
PROF. LEONARD UGWU DATE
(DEAN OF THE FACULTY)
................................................ ................................................
EXTERNAL SUPERVISOR DATE

3. DEDICATION
This research work is dedicated to the glory of God.

4. ACKNOLEDGEMENT
I am ever thankful to God Almighty for his graces and my benefactor Sir & Lady J. I. Ukoh
with whom all my aspirations of being in the varsity come true when all hope was lost. Also
my Mother Late Mary-Theresa Ukoh through whom I came to this world, where ever you are,
I know you must be happy with me. More so, grateful to my supervisor, Dr. Nathaniel Urama
for devoting his precious time to see to the successful realization of this research work. Not
forgetting my guys with whom I did this work, especially, the one who provided me with a
guide that really guided me from start to finish, all thanks.

5. ABSTRACT
This research investigates the impact of human capital development on the manufacturing
sector in Nigeria. It spanned through the period 1982 through 2016. The data used for this
work were sourced from the Central Bank of Nigeria(CBN) statistical bulletin 2016 and the
World Bank Development Indicators 2017. Adequate statistical measures(OLS) have been
employed using a time-series analysis in the study. For objective two and three in this paper,
one model was used to capture them and the variables of interest are government expenditure
on education and government expenditure on health. The results revealed for the second and
third objective of the research, that human capital development has a positive relationship with
manufacturing output, though the two variables are not statistically significantly different from
zero. This brings to limelight that for the manufacturing sector to achieve steady state level of
output and satisfactory level of economic growth and development, there is need for human
capital development to take place.

6. TABLE OF CONTENTS
TITLE PAGE ........................................................................................................ i
APPROVAL PAGE ........................................................................................................ ii
DEDICATION ……………………….................................................................... iii
ACKNOWLEDGEMENT …........................................................................................ iv
ABSTRACT …..................................................................................................... v
TABLE OF CONTENT ……………………………………………………………. vi
LIST OF TABLES ……………………………………………………………………. vii
LIST OF FIGURES ……………………………………………………………………. vii
CHAPTER ONE ....................................................................................................... 1
INTRODUCTION ........................................................................................... 1
1.1 BACKGROUND OF THE STUDY ................................................................... 1
1.2 STATEMENT OF THE PROBLEM ................................................................... 5
1.3 RESEARCH QUESTIONS …………………………………………............... 9
1.4 RESEARCH OBJECTIVES ………................................................................... 9
1.5 RESEARCH HYPOTHESES ................................................................... 9
1.6 SCOPE OF THE STUDY ................................................................... 10
1.7 SIGNIFICANCE OF STUDY …………………………………………... 10
1.8 JUSTIFICATION OF STUDY …………………………………………... 10
CHAPTER TWO …………………………………………………………………... 12
THE LITERATURE REVIEW ............................................................................... 12
2.1 CONCEPTUAL FRAMEWORK ....................................................... 12
2.1.1 HUMAN CAPITAL …………………………………………………... 12
2.1.2 APPROACHES TO HUMAN CAPITAL …………………………… 15
2.1.3 MANUFACTURING …………………………………………………… 16
2.1.4 MANUFACTURING SECTOR …………………………………… 17
2.2 THEORITICAL LITERATURE …………….................................... 18
2.2.1 THEORIES ON HUMAN CAPITAL ………………………………….... 18
2.2.2 THEORIES ON MANUFACTURING SECTOR ………………….... 23
2.3 EMPIRICAL LITERATURE ................................................................................ 25
2.4 LIMITATIONS OF PREVIOUS STUDIES ........................................................ 31
CHAPTER THREE ……………………………………………………….….... 33
RESEACH METHODOLOGY ................................................................................. 33
3.1. THEORETICAL FRAMEWORK ..................................................................... 33
3.2 MODEL SPECIFICATION ................................................................................. 36
3.3 ESTIMATION PROCEDURE ……………………………......................... 36
3.4 JUSTIFICATION OF VARIABLES ……...............................…...…. …. 37
3.5 TECHNIQUES FOR EVALUATING ESTIMATES ................................. 38
3.5.1 THE ECONOMIC CRITERIA/EVALUATION OF A PRIORI SIGNS…... 38
3.5.2 THE STATISTICAL CRITERION (FIRST ORDER) TEST …...………... 39
3.5.3 ECONOMETRIC CRITERIA (SECOND ORDER) TEST………...…….... 40
3.6. DEFINITION OF VARIABLES ………………….............................. 41
3.6.1 MANUFACTURING OUTPUT ……………………………………. 41
3.6.2 GOVERNMENT EXPENDITURE ON EDUCATION ……………. 42
3.6.3 GOVERNMENT EXPENDITURE ON HEALTH ……………. 42
3.6.4 FOREIGN DIRECT INVESTMENT ……………………………. 42
3.6.5 EXCHANGE RATE ……………………………………………. 43
3.6.6 INTEREST RATE ……………………………………………. 44

7. 3.6.7 POPULATION GROWTH RATE ……………………………………. 44
3.7 SOURCES OF DATA ………………………………………......….......... 45
3.8 SOFTWARE APPLICATION ……………………........................ 45
CHAPTER FOUR ……………………………………………………………………. 46
PRESENTATION AND INTERPRETATION OF RESULT …………………...... 46
4.1 TIME SERIES PLOTS OF DATA ……………………………………………. 46
4.2 DESCRIPTIVE STATISTICS ……………………………………......……. 47
4.3. PRE-ESTIMATION TESTS ……………………………………………. 48
4.3.1 STATIONARY/UNIT ROOT TEST ………………….......……………... 48
4.4 PRESENTATION OF OLS REGRESSION RESULTS ……….……………. 49
4.4.1 EVALUATION OF REGRESSION RESULTS ……………………... 49
4.4.1.1 ECONOMIC CRITERIA OR COEFICIENT INTERPRETATION ……... 49
4.4.1.2 STATISTICAL CRITERIA …………………………………………….… 51
4.4.1.3 ECONOMETRIC CRITERIA (POST-ESTIMATION TEST) …………… 52
4.5 EVALUATION OF RESEARCH HYPOTHESIS …………………………...… 56
4.5.1 HYPOTHESIS ONE ……………………………………………………... 56
4.5.2 HYPOTHESIS TWO ……………………………………………………... 56
CHAPTER FIVE ……………………………………………………………………... 57
SUMMARY OF FINDINGS, POLICY RECOMMENDATIONS AND CONCLUSION
…57
5.1 SUMMARY OF FINDINGS …………………………...………………… 57
5.2 POLICY RECOMMENDATIONS ………………………...……………. …….. 58
5.3 CONCLUSION …………………………...………………………… 59
REFERENCES
APPENDIX
LIST OF TABLES
TABLE 4.1 …………………………………………………………………… 47
TABLE 4.2 …………………………………………………………………… 48
TABLE 4.3 …………………………………………………………………… 49
TABLE 4.4 …………………………………………………………………… 53
TABLE 4.5 …………………………………………………………………… 55
TABLE 4.6 …………………………………………………………………… 55
LIST OF FIGURES
FIG. 1.1 ……………………………………………………………………………. 4
FIG. 4.1 ……………………………………………………………………………. 46
FIG. 4.2 ……………………………………………………………………………. 54

8. CHAPTER ONE
INTRODUCTION
BACKGROUND OF STUDY
According to Adekola, (2014) “the economic prosperity and functioning of a nation depend on
its physical and human capital stock.” Whereas the former has traditionally been the focus of
economic research, factors affecting the enhancement of human skills and talent are
increasingly figuring in the research of social sciences. Prior before First World war (WW I),
there has been emphasis amongst nations to develop her physical resources, but after the
Second World war, there has been a paradigm shift to capital stock. This shift is unarguably
due to socio-economic wave of the environment and the society at large. In recent times,
world’s attention is being focused on the importance of human resources development as
panacea to problems associated with economic growth of nations. Since the growth of tangible
capital stock of a nation depends to a considerable degree on human capital development.
Without adequate investment in developing human capital which is the process of increasing
knowledge, skills and the capacities of people in the country, the possibility of the growth of
that nation might be minimal (Gyang, 2011 in Sowunmi, Eleyowo, Salako, & Oketokun, 2015).
According to Iheriohanma & Ukachukwu, (2009) Nigeria is endowed with abundant natural
and human resources. It is expected that with such abundance of natural and human capital
resources, Nigeria would have become a prominent figure among the most industrialized
nations in the world. Sadly, one would wittingly agree that the situation appears to be the
reverse. Nigeria continues to wallow in economic under-development and technological
backwardness. Iheriohanma (2004), posits that Nigeria’s development experience since her
Independence has been that of relatively poor economic performance. The nation’s Gross
Domestic Product (GDP) is decreasing and decline in productivity has led to reduced income,
organisational closures, layoff’s and increased human misery.
At a period when most countries – developed and developing – are embracing the knowledge-
based production (in this work, I adopted it as still human capital) process as a panacea to
ineffectiveness in today’s national and global economy, Nigeria it appears, is finding it difficult
to truly understand the necessity of knowledge– based production or how to carry out the
changes required to bring it into fruition. Efforts in the past which attempted to reverse this
trend were unsuccessful primarily because Nigeria has an economic system which suffers from
a plethora of deficiencies. Prominent among these is the relegation of human capital to a
secondary role in the production process. Beginning with the four National Development Plans,
through Austerity Measure, Structural Adjustment Programme (SAP), the vision 2010 (later
shifted to 2020), to the political leaderships Seven Point Agenda, the various administrations
failed to nurture economic growth and development through clearly defined human capital
development strategies to evolve competitive market-oriented economy.
In a bid to fast track the country’s economic development, the Nigerian government has over
the last century formulated several economic development plans. The most recent of these is
the Vision 2020 which encapsulates the strategic trajectory that is expected to position the
country among the 20 most developed nations of the world by the year 2020. Among other

9. objectives, Vision 2020 is expected to transform the Nigerian economy into a sound, stable,
and globally competitive economy with a GDP of not less than $900 billion and a per capita
income of $400 per annum, ensure a vibrant and globally competitive manufacturing sector
that contributes significantly to GDP with at least 40% local content, and also guarantee a
modern and vibrant education system which provides for every Nigerian the opportunity and
facility to achieve his maximum potential and provides the country with adequate and
competent manpower (Monimah, 2010). The last objective is obviously an acknowledgement
of the strategic role of human capital in economic development. Apart from the fact that about
50 percent of the resources used in production can safely be classified as human capital, human
capital, often referred to as human resource, stands unique among other resources in the
production process in the sense that it is the only resource with the intelligence and
organizational ability required to effectively combine the other resources to produce (Ugbam,
2011). It has been argued that the success or achievement of any development plan will depend
largely on the realisation of the critical role of human capital and that investment on human
capital accounts for the rapid economic development of most countries.
To further buttress this point, the government expenditure on education and health, which to
an extent can serve as a yardstick in showing commitments of the government towards
developing the human capital stock of her citizenry, over the years is shown below:
Fig 1.1 Government Recurrent Expenditure on Education and Health (1986-2016)
Source: Author’s computations from CBN, (2016) Statistical Bulletin.
The above chart, taking a cursory look at the human development, in the light of public
expenditure on education and health, showed that from 1986-till date, human capital has been
growing in Nigeria. It has been discovered that if an economy is to develop its human capital
base, there must be the support of capital resources to complement human capital development.
These capital resources could include Federal funding through increased budgetary allocation
to the educational sector, infra- structural development, enactment of policies, provision of
subsidies, grants, scholarships, as well as an enabling environment that support learning.
Amongst all these variables for human capital development via the educational sector, the
major issue of concern is government effort, through policy development and funding patterns,
geared towards improving educational system. From the chart, one can clearly see that in recent
past, there has been a decrease in government expenditure on education. Considering health, it
experienced an increase not until the year 2011 when it declined and picked up in the year
2013, hits its peak in 2015 and still yet declined. This prompts a puzzling question to an
observer who would ask “what is the essence of formulating development plans that is geared
towards improving the manufacturing sector and at the same time neglecting the sufficient
conditions?”
The objective of human capital within organisations in a nation is to maximize returns on
investment. Human capital is not mere commodities or resources but creative and social beings
in a productive enterprise. Harnessing and marshalling the enormous potentials of this resource
is crucial to efficient and effective production and economic progress. Abundant resources
alone cannot lead to economic renaissance. It is the ability to create a labour force (human

10. capital) that possesses the skills, knowledge, talents, abilities, competences, e.t.c. to be
competitive in the global economy of the 21st century that can turn the national fortune around.
Human capital, organisations and national economies exist in a world of constant evolutionary
activity. Nigeria, the giant of Africa is faced with the intimidating and overwhelming challenge
of developing her human capital. This is primarily because the 21st century economy has made
it imperative more than ever that nations must become increasingly and competitively skilled
in their own knowledge-based production and become active creators and contributors to
international economy, thinking and decision making. In the light of the above, the broad
objective of this paper is to explore the critical need for the development of human-capital in
Nigeria with regard to the challenges of the emergent 21st century knowledge-based
production.
STATEMENT OF PROBLEM
The core subject matter in this study is to determine the nature of relationship between human
capital development and the manufacturing sector in Nigeria and to find out if, truly, human
capital development have an impact in the growth of the manufacturing sector. Economists can
never exhaust the arguments that underlie the interaction and relationship between human
capital and the manufacturing sector. This paper’s objective is not to put an end to this argument
but to lend its foot to the subject matter.
Akinlo (2012) noticed that the huge revenues from oil which should provide opportunity for
increased expenditure and investment has rather complicated macroeconomic management and
also made the economy highly oil dependent. Distressingly, he noted that in spite of the huge
rents from oil, the economy still grapples with high and rising unemployment rate, declining
manufacturing production, high and rising level of poverty and poor infrastructural
development. And these have adverse implications on economic growth.
Ogunlowo (2008) observed that the economy recorded tremendous self-sustaining growth and
expansion
when it relied on agriculture before crude oil became the mainstay. Revenue from agriculture
was appropriately used to build landmark social and economic infrastructure, while providing
basic services like education, health, water and electricity supply. The then revolutionary free
education programme in the western region was funded entirely from cocoa, rubber and palm
oil proceeds. In fact, many of the great intellectuals the country pride itself today were
beneficiaries of that programme. Udosen, et al., (2009) in Adekola, (2014) further mentioned
that the foremost universities in Nigeria – the then University of Ife (now Obafemi Awolowo
University), Ahmadu Bello University, Zaria and University of Nigeria, Nsukka, (UNN) were
not built from foreign grants or loans, but from proceeds from cotton, groundnut, rubber and
palm oil. Moreover, the establishment of first generation teaching hospitals and developments
of cities like Ibadan, Kano, Kaduna, Enugu, etc; are also attributed to income from agriculture.
It is really a matter of regret that after over decades of experimenting in the art of
industrialization, most of our industries still remain lukewarm to the fundamental concepts of
industrial engineering technology. The level of technology has been very low. It is a common
observation that many of the capital equipment and machinery used in the factories are obsolete

11. and are of low yielding and low efficiency capacity. In case of their breakdown, repairs are
more difficult because their models have since been discarded. The result is that production is
often disrupted in our factories. The body of empirical research unequivocally leans toward an
affirmation of direct causation for which the East Asian countries are recent examples. This
consensus was not forged from the beginning; it was inspired partly by disenchantment with
absolute growth-oriented development strategies pursued in the fifties and sixties which
neglected or marginalized the social sector- education, health and others, yet failed to deliver
robust growth in industries or achieve poverty reduction as well. The argument of those that
may be termed the “growth fundamentalist school” manifestly lost its force and was in urgent
need of revision. Thus, attempts to placate growing social and political discontent occasioned
by deepening poverty led to the shuffling of relative emphasis on purely growth-oriented
policies and concerns about social conditions (World Development Report (WDR), 1995)
Partly, also, a body of solid empirical evidence confirming that investment in human capital
could spur productivity and accelerate development instigated it. This, in effect is a repudiation
of the mainstream conventional prescription of cutbacks in social programmes on the excuse
that they are a burden on the national budget. Needless to say, that such spending fosters social
peace necessary for the economic apparatus to function effectively. Moreover, it constitutes a
direct affront on the economic doctrine that holds income maximization as the supreme
objective of national economic policy and a measure of the wealth of nation. The corollary:
human resources -not capital, income or material resources are the basis for the wealth of
nations. Clearly the era of ignoring human resource development is now passed; skating over
the human resource factor may not only imperil the growth process, it may ground it.
Undoubtedly, human beings are the active agents who accumulate capital, exploit natural
resources, build social, economic and political organizations to advance productivity in
industries and national development. Significantly though, the progress made has been less
rapid to markedly attenuate Nigeria’s dependence on expatriates for the operation of many vital
functions. Particularly worrisome has been the deterioration in the quality of educational
service at all levels, especially at higher education levels where persons are trained to take up
leadership roles in science, technology, management and business. Moreover, the expansion of
human capital stock has not been matched by a commensurate advancement in physical capital.
The net consequence has been paltry growth of productivity, income and meager returns to
education over the years.
The developments in Nigeria’s education system have attracted considerable empirical scrutiny
(Yusufu 2000 in (Anumudu, 2010)). The mechanics of how human capital influences
productivity has however attracted modest inquiry. The political rhetoric surrounding this issue
is quite long, but argumentation with scientific investigation especially for Nigeria that is faced
with astronomical level of unemployment unexpectedly among the highly educated. Therefore,
it is pertinent to investigate how significant education is to industrial productivity in the context
of high unemployment among the well-read. In view of this, the critical research questions are:
why has the productivity in industries been fluctuating around very low levels of performance?
Is increase in productivity level of firms over the period attributable to the nation’s level of
learning? What really determines the effectiveness of human capital in labour productivity in
industries? These questions constitute the focal problem of this research.

12. RESEARCH QUESTIONS
In the course of this research, some questions have piqued the interest and curiosity of the
researcher. These questions form the research questions. They include:
What is the trend in government expenditure on Education and health in Nigeria?
If government expenditure on health affects the manufacturing sector in Nigeria.
If government expenditure on Education affects the manufacturing sector in Nigeria.
RESEARCH OBJECTIVES
Though, the broad objective of this research is to establish the impact of human capital
development on the manufacturing sector in Nigeria. The following specific objectives will be
used to achieve the overall objective;
To evaluate the trend in government expenditure on Education and health in Nigeria
To find out if government expenditure on health affects the manufacturing sector in
Nigeria.
To find out if government expenditure on Education affects the manufacturing sector
in Nigeria.
RESEARCH HYPOTHESIS
H01: There is no impact of government expenditure on health and manufacturing sector in
Nigeria.
H02: There is no impact of government expenditure on Education and the manufacturing sector
in Nigeria.
SCOPE OF STUDY
This is study will be delineated to the geographical confines of Nigeria to enable a more in-
depth comparison and the time scope of the research will be limited to 1982-2016. This period
is considered in this study due to the availability of sufficient data during the years 1982 to
2016 to make meaningful observations to improve on current empirical literature.
SIGNIFICANCE OF STUDY

13. This research paper will be of particular importance to the government and policy making
bodies, to guide them in the process of policy formulation and implementation. The solutions
that will be proffered at the end of this study will be useful not only to Nigeria but will have a
wider applicability in Sub-Saharan countries and developing countries around the world. The
empirical results from this study will serve as bedrock for further research inquiry by students,
lecturers and independent researchers. International organizations, like the World Bank, United
Nations and International Monetary Fund, will also find the arguments raised and the findings
in the research worthwhile.
JUSTIFICATION OF STUDY
Productivity – growth must of necessity enhance the realization of other important national
economic objectives such as attainment of higher average real income or leisure time, even
distribution of income and employment opportunities. It also promotes other important national
non – economic objectives, such as satisfaction, physical and social environment, national
defense and social justice. If we truly inculcate and practice the productivity culture, there
would be an obvious improvement in our quality of life. Productivity improvement would not
be at the expense of our people; rather it would result in the reduction of waste in its entire
ramification. This includes waste of time, materials, equipment, capital, foreign exchange and
above all human efforts. The purpose of the research (as indicated in the objective of study)
will proffer possible policy recommendations and options that will synergize the development
of human capital in such a way that will foster sustainable growth that will bring about
sustainable development in the manufacturing sector.

14. CHAPTER TWO
LITERATURE REVIEW
CONCEPTUAL FRAMEWORK
HUMAN CAPITAL
Economically, capital is referred to as ‘those factors of production used to create goods or
services that are not themselves significantly consumed in the production process’ while, the
human element takes charge of all economic activities such as production, consumption, and
transactions necessary to move the products to the consumers (Boldizzoni, 2008.) According
to Kucharčíková, (2011) there are several definitions and approaches to understanding human
capital. Ideas about the importance of human capital and investment in human capital was
directly or indirectly associated with the importance of education as early as the beginnings of
economic theory in the work of W. Petty and A. Smith.
Bontis,et al (1999) defined the human capital as the human factor in the organization; the
combined intelligence, skills and expertise that gives the organization its distinctive character.
The human elements of the organization are those that are capable of learning, changing,
innovating and providing the creative thrust which if properly motivated can ensure the long-
run survival of the organization. Moreover, the definition emphasises the role of motivation in
leveraging these capacities. The definition acknowledges the importance of ‘distinctive
character’. Finally, it alludes to the outcome of business sustainability, referring to the ‘long-
term survival of the organisation’.
Davenport (1998) says that people possess innate abilities, behaviors and personal energy and
these elements make up the human capital they bring to their work. Armstrong (2006) defines
the human capital as knowledge and skills which individuals create, maintain, and use.
According to Kucharčíková, (2011), the new theories of economic growth characterized the
human capital as the sum of the individual congenital and acquired skills, knowledge, and
experiences of individuals. Organization for Economic Co-Operation and Development
(OECD) (2001), defined human capital as the knowledge, skills, competencies, abilities, and
other attributes embodied in individuals that facilitate the creation of personal, social and
economic well-being.”
Alika and Aibieyi (2014), brings to our consciousness that often writers omit “commitment”
in their listing of the characteristics of human capital such as knowledge, skills, experience,
which may appear to them very important. But no matter the knowledge, skills, experience,
etc. one may possess, without the spirit of “commitment” to perform, the individual may still
not perform as expected unless there is the “commitment” to perform creditably the given task
or job.
The human capital is a synonym of knowledge embedded in all levels such as an individual, an
organisation and/or a nation. Laying credence to the voice of Frank & Bemanke (2007) in (Prof.
Dr. Kwon, 2009), human capital is “an amalgam of factors such as education, experience,

15. training, intelligence, energy, work habits, trustworthiness, and initiative that affect the value
of a worker's marginal product.” They emphasise the role of human capital on worker
productivity in their definition.
The shift of the focus by the global economy towards more knowledge-based sectors (such as
research and development, pharmaceuticals and ICT-based sectors), has encouraged policy
makers to attend more critically to skills and human capital development (OECD, 1996).
More recent definitions of human capital include that of Thomas et al (2013,), who define
human capital, as the ‘people, their performance and their potential in the organisation’. The
inclusion of the term ‘potential’ is important as it indicates that employees can develop their
skill and abilities over time. This definition is in line with the definition of Dess and Picken
(1999), who suggest that human capital, consists of ‘the individual’s capabilities, knowledge,
skills and experience of the company’s employees and managers, as they are relevant to the
task at hand, as well as the capacity to add to this reservoir of knowledge, skills, and experience
through individual learning’. Dess and Picken’s definition of human capital is much more
expansive than others and crucially highlights that individuals can ‘add’ to their knowledge
base through learning.
In the light of the above I adopt the definition by Dess and Picken. This is because human
capital is vital and it includes the natural ability, innate and acquired skills, knowledge,
experience, talent and inventiveness. All these characteristics are components of the human
capital. The essence of creation, increasing the value and effectiveness of human capital, is
spending money now but expected benefits will flow in future. Forms of increasing the value
of human capital are expenditure oriented for example to health, safety, science, research and
education. Laying credence to what the World Bank said as cited in Mba, (2013), in fast
economic growth requires three fundamental factors. These factors are natural capital, physical
capital and human capital. Of these three factors, however, human capital has a major share in
generating economic growth (contributing 64 per cent). This point had been aptly captured by
Harbison (1973) still in Mba, (2013) when he wrote that:
“Human resource, not physical capital, not income or material resources constitute the ultimate
basis for the wealth of nations. Capital and natural resources are passive factors of production,
human beings are the active agents who accumulate capital; exploit natural resources; build
social, economic and political organizations; and carry forward national development. Clearly,
a nation which is unable to develop the skills and knowledge of its people and to utilize them
effectively in the national economy will be unable to develop anything else”
The implication of the above statement is that no country can make any meaningful economic
progress without developing the knowledge, skills and capabilities of its citizens to manage
available resources. It is an incontrovertible fact that human capital constitutes the most
precious assets of any nation. This therefore underscores the imperative for building requisite
human capital for sustainable development in the manufacturing sector, since it is one of the
most productive sectors of the economy.
APPROACHES TO HUMAN CAPITAL

16. In economics theory, there are two basic approaches to human capital which are
Macroeconomic approach and
Microeconomic approach as identified by Kucharcikova (2011).
These approaches are further subdivided into various subheads in line with business economics.
The approaches as used by economists and other scholars to the understanding of human capital
are however applied in this work. The goal of human capital approach, according to Ndinguri,
et al (2012) sought to improve values, team work, consciousness among individual employees
and overall collective performance.
According to Kucharcikova (2011), the microeconomic aspect has two approaches and are
classified under business economics and the managerial economics. According to him, in
business economics, human capital has been considered as a factor of production.
Kucharcikova (2011) further added that under managerial view, human capital is seen as a
business resource or asset which forms part of the market value of the company, while in
macroeconomic approach, human capital is viewed as one of the factors of production, and the
sources of the economic growth.
MANUFACTURING
According to Kalpakjian, (1995) in Scallan (2003), the basis of manufacturing can be traced
back as far as 5000–4000 BC, the word ‘manufacture’ did not appear until 1567, with
manufacturing appearing over 100 years later in 1683. The word was derived from the Latin
words manus (meaning ‘hand’) and facere (meaning ‘to make’). In Late Latin, these were
combined to form the word manufactus meaning ‘made by hand’ or ‘hand-made’. Indeed, the
word factory was derived from the now obsolete word manufactory. In its broadest and most
general sense, manufacturing is defined as (DeGarmo et al., 1988):
“the conversion of stuff into things.”
However, in more concise terms, it is defined in the Collins English Dictionary (1998) as:
‘processing or making (a product) from raw materials, especially as a large-scale operation
using machinery.’
In a modern context, this definition can be expanded further to:
“the making of products from raw materials using various processes, equipment, operations
and manpower according to a detailed plan.”
Manufacturing, a branch of industry, is the application of tools and processes for the
transformation of raw materials into finished products. Manufacturing includes all intermediate
processes required for the production and integration of a product’s components. According to
Mrs. Olubunmi Osuntuyi, Secretary General of International Chamber of Commerce Nigeria,
in an article written by Nwaoguji Charles, (2016) on Daily Sun News online, “manufacturing
is undoubtedly the principal propellant in transforming human and natural resources.”
2.1.4 MANUFACTURING SECTOR

17. According to Business Dictionary (2017), manufacturing sector is the agglomeration of
industries engaged in chemical, mechanical, or physical transformation of materials,
substances, or components into consumer or industrial goods. The manufacturing sector is
closely connected with engineering and industrial design. Some industries, such as
semiconductor and steel manufactures use the term fabrication instead. The development of
manufacturing sector to this day still relies heavily on research into manufacturing processes
and materials and the development of new products. Those countries that have been at the
forefront of the development of manufacturing have come to be known as the developed
countries, while those that have very little manufacturing are considered underdeveloped.
The manufacturing sector has shown strong growth in recent years. Nonetheless, National
Bureau of Statistics (NBS) (2014), in one of its reports in October on the manufacturing sector
states that the sector faces ongoing challenges, including an inadequate electricity supply, poor
infrastructure and plant maintenance, and heavy dependency on agricultural inputs, which
themselves are vulnerable to shocks. Its strengths are nonetheless abundant; semi-skilled yet
low paid workforce, the availability of domestically sourced inputs and most importantly, a
huge domestic demand for consumer products. It therefore displays great potential for future
expansion.
THEORETICAL LITERATURE
The concept of human capital and manufacturing are very popular in economic discourse. Both
contemporary and non-contemporary economists have developed and formulated theories of
human capital and manufacturing to explain the relationship between the two variables. This
part of the paper will explain these various economic theories.
THEORIES ON HUMAN CAPITAL
HUMAN CAPITAL THEORY
The topic of human capital was elaborated by economists, representatives of the Chicago
School in the 60s of the 20th century. “Attention of Chicago Economists also focused on
building human capital theory, which was a major contribution to theoretical research in
education. Their theory of human capital has become a ‘decoration’ Chicago School,”
(Volejníková, 2005). The leader of this school was Schultz who in 1981 wrote: “Take into
account the innate and acquired skills. Those are important and may invest to expand and will
form the human capital.” The most important author and promoter of human capital theory is
Gary Becker. In his book Human Capital in 1964 developed a theoretical basis for deciding on
investment in human capital (Becker, 1993).
Gary Becker’s classic work, human capital, elaborates on the notion of human capital in the
context of neoclassical economics. It registers that investment in human could be viewed as
similar to investment in other means of production, like factories or mines. In developing
Becker’s work further, another economist, Theodore Schultz, set out to map how rates of return
from education could be calculated in countries with different levels of income, different
attitudes to forgoing earnings to develop human capital (Severine and Lila, 2009). Human
capital theory holds that it is the key competences, skills, knowledge and abilities of the

18. workforce that contributes to organizations competitive advantage. It focuses attention on
resourcing, human resource development, and reward strategies and practices. According to
Human Capital Theory, education is an investment because it is believed that it could
potentially bestow private and social benefits (Odhong et al., 2014).
SOLOW GROWTH MODEL
Manufacturing sector is very germane to the development of any nation most especially the
underdeveloped ones. And over the years, Economists have for a long time discussed the causes
of economic growth and the mechanisms behind it. The theory of the growth of conventional
economy began with the neoclassical proposition of Solow (1956), which basically highlights
issues such as “constant returns to scale, diminishing marginal productivity of capital,
exogenously determined technical progress and substitutability between capital and labour”.
Consequently, Solow’s initiative foregrounds the elements of savings and investment as
important factor responsible for immediate growth in economy. For the long- time experience,
progress and sophistication in technology is identified to be core, even though the foregoing is
seen as “exogenous” to the economy concerned. Suffice to submit that even though the
neoclassical growth approach favours labour and capital as indices of growth in economy, other
alternatives such as growth in technology, which is considered exogenous, have remained
unexplored. This omission, as well as inconsistent practical evidence, has necessitated the quest
for alternatives by researchers. Specifically, the contribution of progress in technology as an
important stimulus to sustainable economic growth has been continuously adopted when
regular and progressive returns to capital are emphasized.
ENDOGENOUS GROWTH THEORY
This theory associated with Paul Romer in the mid-1980s. It is also called the AK-model. They
place greater importance on the need for governments to actively encourage technological
innovation. They argue in the free market classical view firms may have no incentive to invest
in new technologies because they will struggle to benefit in competitive markets. Place
emphasis on increasing both capital and labour productivity. They argue that increasing labour
productivity does not have diminishing returns, but, may have increasing returns They argue
that increasing capital does not necessarily lead to diminishing returns as Solow predicts. They
say it is more complicated, it depends on the type of capital investment. According to Romar
(1986), human capital has a great role to play in stimulating growth, he believes that technology
results from innovation which is due to the development of human capital.
THEORY OF UNBALANCED GROWTH
The theory of unbalanced growth as posited by Prof A. O. Hirschman stressed on the need of
investment in strategic sectors of the economy instead of all the sectors simultaneously as these
major sectors would serve as a propeller of growth for other sectors for rapid development and
the accruement from these sectors utilized for development of other sectors. Other sectors
would automatically develop themselves through what is called “linkage effect” (Ajudua &
Ojima, 2016.) Hirschman posited that underdeveloped countries are characterised by low per
capita income, income inequality, poverty, low productivity, high dependence on agriculture,
high rate of consumption, low savings rate, high unemployment etc, hence less and scarce

19. resource to direct towards many sectors. The real scarcity however stems from the ability to
bring resources into play, thus Hirschman posited a big push (investment) in strategic selected
industries or sectors of the economy and contends that deliberate unbalancing of the economy
is the best method of development as development transcends from the major sectors of the
economy to the minor, from one industry to another; from one firm to another etc. Thus, if the
economy is to be kept moving ahead, the maintenance of existing imbalances such as tension,
disproportions and disequilibrium should be the goal as they can be seen from the angle of
profit and losses. Hirschman further divides the initial investment into two related activities;
directly productive activities and social overhead capital. The theory holds that an economy
should chose to invest in one of these two fields. If an economy invests in Social infrastructure
(e.g. roads, water sanitation, transport, banking), it is left for the people to utilize this
infrastructure and push towards a growth in directly productive activities (e.g. mining,
agriculture, manufacturing). Also, if an economy invests in directly productive activities,
people eventually earn enough to work on building their own infrastructure. Whichever the
type of investments, it will yield an ‘extra dividend’ of induced decisions resulting in additional
investment and output. However, social overhead capital, and directly productive activities
cannot be expanded simultaneously because of the limited ability to utilize resources. Going
by this, if there is an improvement in power generation to the manufacturing firms, its induces
acceleration in production and by so doing, the capacity utilization rate is improved, leading to
an increase in output of the sector which further entails, higher investment and savings, product
varieties etc. this provides the rational for the inclusion of the variable, electricity supply as
one of the independent variables.
SKILL ACQUISITION THEORY
As defined by Vanpatten & Benati (2010) Skill refers to ability to do rather than underlying
competence or mental representation". According to Trofimovich & McDonough (2013), skill
theory "refers to a cognitive repetition phenomenon in which prior exposure to specific
language forms or meaning facilitates speaker's subsequent language processing". The
scientific roots of Skill Acquisition Theory can be found in different branches of psychology,
which ranges from behaviorism to cognitivism and connectionism (Dekeyser and Criado,
2013). This theory draws on Anderson's Adaptive Control of Thought (ACT) model which
itself is a kind of cognitive stimulus-response theory (Ellis and Shintani, 2013). According to
Chapelle (2009), this theory falls under the category of general human learning. The theory
assigns roles for both explicit and implicit learning and, as a general theory of learning, it claims
that adults commence learning something through largely explicit processes, and with
subsequent sufficient practice and exposure, move into implicit processes. Development,
within this theory, entails the utilization of declarative knowledge followed by procedural
knowledge, with the latter’s automatization (Vanpatten & Benati, (2010) in (Odhon’g &
Omolo, 2015)
As elaborated by Vanpatten and Benati (2010), using declarative knowledge involves explicit
learning or processes; learners obtain rules explicitly and have some type of conscious
awareness of those rules. The automatization of procedural knowledge entails implicit learning
or processes; learners begin to proceduralize the explicit knowledge they own, and through

20. situational suitable practice and use, the behavior becomes second nature. This theory supports
the secondary school enrollment as an independent variable in the study. This is because, at
this stage it is expected that one can comfortably learn the basic skill required of any work
upon graduation. It assisted in answering the research question on how human capital
developments influence performance of the manufacturing sector.
SUSTAINABLE RESOURCE THEORY
Sustainable Resource Theory is much like scarce resource theory except for one major point:
the concern for the long-term versus short-term agenda. Thurow (1993) in (Odhon’g & Omolo,
2015) informs us that “in the future, sustainable advantage will depend on new process
technologies and less on new product technology. New industries of the future depend on brain
power. A man-made competitive advantage replaces the comparative advantage of Mother
Nature (natural-resources endowment) or history (capital endowments). The implication of this
theory to this paper being that human capital investments must add value to creating sustainable
long-term economic performance (Swanson and Holton, 2001).
THEORIES ON MANUFACTURING SECTOR
LEWIS’S THEORY OF UNLIMITED SUPPLIES OF LABOUR
Propounded by Prof Arthur Lewis in 1954, the theory posits that underdeveloped countries are
characterized by overpopulated labour at subsistence wage, and as such development can take
place when such excess labour is withdrawn from the agricultural dominant sector to the
industrial sector while maintaining a zero-marginal labour as no output would be lost in such
transfer (Jhingan, 2013). This can lead to creation of new industries or expansion of existing
ones. The theory assumes that the economy runs as a dual economy characterised by traditional
and industrial sector, and the unlimited supply of labour in the underdeveloped countries arises
due to high population, unemployment/underemployment, high birth rate etc. Lewis posited
that the wages in industrial sector remain constant. Consequently, the capitalists will earn
surplus. Such surplus will be re-invested in the modern sector which helps to absorb the labour
which migrated from traditional sector. However, the speed with which this expansion occurs
is determined by the rate of industrial investment and capital accumulation in the modern
sector. This process of modern self-sustaining growth and employment expansion will
continue till all the surplus rural labour is absorbed in the new industrial sector. Thereafter,
additional workers can be withdrawn from agricultural sector only at a higher cost of lost food
production because this will decrease the labour to land ratios. In this way, the MPL will be no
more zero. Thus, labour supply curve will become positively sloped along with the growth of
modern sector (Jhingan, 2013). Therefore, structural transformation of the economy will take
place through shifting from traditional rural agriculture to modern urban industry.
KALDOR’S MODEL OF ECONOMIC GROWTH
Kaldor postulated a growth model, in which he tried to provide a framework for relating the
genesis of technical progress to capital accumulation. Kaldor analysed and posited that
development hinges on four fundamental concepts; increasing returns in the manufacturing
sector; effective demand constrained growth; the agriculture-industry relationship and internal-

21. external market relations (Targetti, 1992). Kaldor believed that economic development requires
industrialization which is presupposed by agriculture revolution and accompanied by export-
led growth policies. He held that the manufacturing sector is the engine of growth and the
more the outputs of the manufacturing sector; the greater is the productivity in the system as a
whole (Wulwick, 1992.) This relies on several factors, firstly, the growth of manufacturing
provides capital goods and technical advances embodied in them as input for other sectors;
secondly, an increase in output and employment in the manufacturing sector reduces the
employment in agriculture but not its output; thirdly greater activity in the manufacturing sector
produces greater turnover per worker in the distribution sector (Targetti & Foti, 1997). He
posited that technical progress depends on the rate of capital accumulation (Jhingan, 2013).
Kaldor postulated that investment at any period depends partly on change in output and partly
on the change in profit on capital in the previous period. The model introduced the technical
progress function in place of the usual production function.
EMPIRICAL LITERATURE
Over the years, there has been an extensive discourse on the concept of the impact of human
capital development and the manufacturing sector. Various researchers have conducted
empirical inquiries into the relationship between human capital and the manufacturing sector.
The most poignant and recurring questions in this research include: Is there any short run or
long run relationship between human capital investment and manufacturing sector in Nigeria?
Is the relationship, if it exists, causal or by mere coincidence? Is there any impact of human
capital investment on manufacturing sector in Nigeria? To answer these questions, studies on
human capital has been carried out in different countries, regions sub-regions and continents
of the world. In this sub-section of this research, the researcher will summarize selected
empirical findings that are relevant to the research topic.
Jelena, et al., (2012) conducted a study on the impact of knowledge management on
organizational performance. The aim of this paper is to show that through creating,
accumulating, organising and utilising knowledge, organisations can enhance organizational
performance. The impact of knowledge management practices on performance was empirically
tested through structural equation modelling. The sample included 329 companies both in
Slovenia and Croatia with more than 50 employees. The results show that knowledge
management practices measured through information technology, organizations and
knowledge positively affect organizational performance.
Josan (2013) in (Odhon’g & Omolo, 2015) conducted research through content analysis to
analyze the relationship between human capital & organizational effectiveness. Organizational
effectiveness is characterized by competitiveness, innovation and excellence. Competitiveness
depends on skills & human capital investment. Human capital investment is characterized by
investing in education, health & training. She narrates that globalization has resulted in new
economy named as knowledge economy, in which human capital variables education &
training- plays a significant role. Based on the existing literature it was analyzed that
investment in human capital is directly proportional not only with the productivity of the
organizations- trainings increase productivity by 16%; but also, with profitability. An increase
of over twice the size of the wages increased because of trainings was witnessed in materials.

22. It was also concluded that in strategic triad- Business strategy, human capital strategy and
Human Resource Strategy – human capital strategy is a critical component.
Marimuthu, Arokiasamy, & Ismail, (2009) explored human capital and its impact on firm
performance and bring to our understanding that there are reasonably strong evidences to show
that the infusion of ‘human capital enhancement’ in organizations promotes innovativeness and
greater firm performance. In the light of this, the understanding of firm performance in relation
to human capitals should not be regarded as a phenomenon that only adds ‘more zeros’ in a
firm’s profits; it is rather transforming the entire workforce as the most ‘valuable assets’ in
order for the organization to pave ways for greater achievements via innovativeness and
creativity. Hence, companies should therefore, come up with some effective plans especially
in investing the various aspects of human capital as not only does it direct firms to attain greater
performance but also it ensures firms to remain competitive for their long-term survival.
Ismail, (2009) analysed the impact of human capital attainment among workers for the Malay
owned manufacturing and services enterprises on output and labor productivity. The analysis
is based on 574 Malay firms surveyed in 2001/2002, which covers 264 manufacturing
enterprises and 310 services enterprises in Peninsular Malaysia. The sample is selected from
the Malay firms registered with the Malaysian Malay Chamber of Commerce (MMCC). The
output and labor productivity of the firms are regressed against the human capital variables like
education and training together with physical capital stock. The study shows that for the
manufacturing enterprises an effective labor plays a higher and significant role on output and
labor productivity growth. The capital- labor ratio is an important determinant of labor
productivity. In carrying this research, made use of the ordinary least squares (OLS) method.
Labuschagne & Kleynhans, (2012) explored potential human capital constraints in the South
African economy. Human capital constraints are aspects of human capital that limit the
productivity and eff ectiveness of the workforce. The work indicated that an inadequately
educated workforce and restrictive labour regulations are the two major human capital
constraints facing the South African economy. The consequences of investing in education
were shown to be a form of capital, namely human capital. Empirical evidence indicated that
there is a positive relationship between educational attainment and output per worker and
therefore productivity. Managers with higher levels of education achieved higher levels of
output per worker from their labour force.
Asghar, Danish, & Rehman, (2017), discussed human capital and labour productivity. This
study was designed to investigate the role of human capital in labour productivity in district
Lahore. For analyzing this relationship, cross sectional study was conducted, and data was
collected from 243 firms, which include manufacturing, trading and service sector. The
empirical analysis reveals that all the sectors have heterogeneous effect of human capital on
labour productivity. Education appears to be significant and positively related to labour
productivity in all the sectors with greater effect in manufacturing sector. Skills and training
have also noticeable effect on labour productivity.
Olayemi, (2015) investigates the relationship between human capital investment and industrial
productivity in Nigeria using secondary data spanned through 1978 to 2008. The study found

23. that government expenditure on education maintained a positive long run relationship with
index of industrial production while government expenditure on health and Gross Capital
Formation exhibited long run negative relationship with the dependent variable. Consequently,
it was recommended among others that more stock of physical capital needed to be acquired,
to facilitate more investment in human capital and thereby enhance industrial productivity in
Nigeria. This study made use of the co-integration and error correction model (ECM)
techniques as part of the estimation methods.
Acquah & Hushak, (1978) examined human capital and labor turnover in manufacturing
industries, the case of a relatively undeveloped region in Southeast Ohio. A model developed
by Parsons was used to test the statistical hypothesis. The results for the quit and lay-off rates
support the investment hypothesis that the layoff rate is related negatively to firm’s investment
in specific human capital, whereas the quit rate is related negatively to a worker's investment
in specific human capital.
Ojokuku & Sajuyigbe (2015), mentioned that in today’s knowledge economy, firm
performance and competitive advantage are derived more from what a firm knows and the
human capital that permits the firm to use what it knows. Their study offered a field insight
into the relationship between human capital development and SMEs’ performance in Nigeria,
through a survey of 80 randomly selected SMEs operating in Ibadan, south western Nigeria.
Pearson Product Moment Correlation Coefficient and Multiple Regression Analysis were used
to analyse the data. The result showed that human capital development variables have
significant effect on SMEs performance. Specifically, this study has drawn attention to the need
for SME operators to key into the benefits of participating in seminars, trade fairs, workshops
and exhibitions as a means of developing their human capital through the acquisition of current
knowledge that will positively impact their performance, thereby enhancing the SMEs’
capacity for growth and potentials for survival.
Ugbam & Ozioma, (2016) assessed the state of human capital development in Nigeria with a
view to determining the extent to which it can support the Nigerian manufacturing sector in
achieving the objectives established for it by the countries policy document, vision 2020. It
relied on existing data (secondary) and using OLS technics to achieve its objectives. It was
found that there is a very strong positive relationship between human capital development and
global competitiveness; that mainly as a result of inadequate funding, the state of human capital
development in the country must improve significantly in order provide the manufacturing
sector with the quantity and quality of human capital that will enable it to achieve the objectives
prescribed for it by vision 2020.
Okuwa, Nwuche & Anyawu, (2016) conducted a work on the impact human capital
development and organizational resilience in selected manufacturing firms in Rivers state.
Using simple random sampling technique and Taro Yamen's formula, 119 managers were
drawn from the 31 manufacturing firms in Port Harcourt. The statistical tool adopted was
spearman rank order correlation coefficient. Their findings showed that performance
management and training have influence on organizational agility and organizational adaptive
capacity in manufacturing firms. From the findings, they concluded that human capital
development has significant influence on organizational resilience.

24. Anumudu, (2010) examined the effect of human capital on labour productivity in
manufacturing industries in Enugu and Anambra States. The study applied the OLS method
and the principal component Analysis in the estimation. The evaluation results show that
human capital has a positive effect on the sectoral labour productivity level of the industry.
Adejumo & Adejumo, (2017) in order to address the direction of causality between human
capital and productivity growth in Nigeria, the study first investigated the pattern of
productivity growth in Nigeria between 1970 and 2010. This study empirically determined the
productivity growth in Nigeria, as well as the causal relation between human capital
development and productivity growth in Nigeria using the Engle-Granger causality test. The
results revealed that productivity growth has been very low and unstable in Nigeria. In addition,
the nexus between human capital and productivity growth was examined. The findings revealed
that while productivity growth caused human capital development, human capital development
did not cause productivity growth.
Abdul Karim & Ahmad, (2012) emphasizes the importance of human capital in the
development of manufacturing sector in Malaysia. A log-linear model that covers a period of
1981-2010 for the dependent variable was developed to estimate the influences of labor
productivity, employment and investment in education and health on the sector’s development.
The findings highlight the significance of human capital in which the variable of employment
has the highest elasticity in contributing to the share of gross domestic product (GDP) of
manufacturing sector.
Teixeira, (2002) presents a paper which provides a review of the literature focusing the
relationship between human capital and performance essentially at firm level. The exposition
is approached in three different but interrelated perspectives: economic, technological and
survival. In conclusion, he said that the clear direction of all the studies respecting human
capital and economic performance pointed to the ‘rationality’ conveyed by human capital
theory, namely that of increasing the quantity of firm’s human capital. In this context it cannot
be conceived that, in large swathes of seemingly still successful industrial capitalism there are
distinctly low limits on the demands placed on the education and training system by employers,
unless one resorts to the belief that these employers must be ill-informed or irrational.
In conclusion, the empirical literatures reviewed in this section all agree to the fact that human
capital development and manufacturing sector performance have a long-run relationship. We
can also discover from the literature review that there is a dearth of empirical works on the
impact of human capital development on the manufacturing sector in Nigeria.
2.4 LIMITATIONS OF PREVIOUS STUDIES
Apart from the problem of very few empirical literatures, the researcher also discovered that
there are even fewer qualitative research works on the topic. Qualitative research is important,
especially for topics like this, as it brings the discourse closer home. This is due to the financial,
time and energy constraints that researchers face in conducting qualitative research. Another
limitation of previous studies is that their timeframes mostly stop at 2010. Recent economic
events from 2014-2017 (the oil market crises, the Greek financial crises, the recession in
Nigeria etc.) are not taken into consideration thereby questioning their relevance or their

25. application in today’s world. Also, most of the works were either focused on a district or very
large group of countries (ranging from thirty to fifty-four).
Moreover, none of the materials reviewed enquired about the relevance of the variables
electricity supply, and total capital expenditure, which are human capital enhancements, to the
manufacturing sector. This is also one of the problems this research work will solve.
CHAPTER THREE
RESEARCH METHODOLOGY
THEORETICAL FRAMEWORK
According to Haavelmo (1944), the method of economic research points essentially at a
conjunction of economic theory and actual measurement using the theory and techniques of
statistical inference. In choosing the appropriate economic theory to adopt in the theoretical
framework of an empirical study, the researcher must consider the nature and type of the
research topic. The Solow Growth Model.
The Solow Growth model provides a starting point for this study. He employed the well-known
Cobb-Douglas production function to establish labour, capital, and technical progress (which
is exogenously determined) as important agents of growth while also stressing the importance
of savings and capital formation for economic development. Mathematically, the functional
relationship is written with the assumption of constant returns to scale thus:
Y=AKαL^(1-α) (1)

26. Where Y is given as output (or income), A is the level of technology (and the value is
determined outside the model), K and L are the physical stock of capital and units of labour
respectively. When perfect competition holds in addition to the previous assumption, α and1-
α are the parameters each of which measures the responsiveness of output with respect to
capital and labour respectively (or put differently, the capital’s and labour’s share of total
income respectively). A (the measure of technical progress) raises output from a given
combination of inputs and with the assumption of diminishing returns, increment in income
(output) falls with each successive change in variable input.
As more appealing to the eyes this model is, it is inappropriate for this study due to not
explicitly incorporating the human capital component. Therefore, according to Oluwatobi and
Ogunrinola (2011), a more reliable option is the augmented Solow model. Gregory Mankiw,
David Romer and David Weil proposed the augmented Solow model which include human
capital as an additional explanatory variable to physical capital and labour (Nafziger, 2006.)
the justification for the inclusion of human capital is also found in the works of the 1979 Noble
prize co-winner, Theodore Schultz (1961) when he argues that a society should invest in its
citizens through expenditures on Education, training, research and health that enhance their
productive capacity. The model is therefore, specified thus:
Y=AK^α (H〖L)〗^(1-α) (2)
When β becomes 1-α; where (2) becomes
Y=AK^α (H〖L)〗^β (3)
The variables Y, A and K are defined above and HL is the level of Human Capital.
If we take the Log of both LHS and RHS of (3), we have a deterministic log-linear model:
LogY=LogA+LogK^α+Log(H〖L)〗^β
LogY=LogA+αLogK+βLogHL (4)
The impact of K measured by gross capital formation has been well reported in various
studies, and drawing from Adenuga (2006), in Nigeria, too much attention has been given to
accumulation of Physical capital for growth and development without adequate attention to the
important role played by human capital in the developmental process of the manufacturing
sector. Therefore, the focus of this study necessitates specifying a model of human capital
conducted with a touch of factors that affect the manufacturing sector performance. Thus, since
A is exogenously determined, Y is measured by Manufacturing output and HL, a composite of
human capital measure by government expenditures on education and health; we specify a lin-
log econometric model to suit the Nigerian situation:
FUNCTIONAL SPECIFICATION OF THE MODEL
M_GDP = f(GEXP_EDUC,GEXP_HEALTH,FDI,EXCHR,INT,PGR,) (5)
LINEAR FORM OF THE MODEL:

27. M_GDP = β_0 + β_1 GEXP_EDUC+β_2 GEXP_HEALTH+β_3 FDI+β_4 EXCHR+β_5
INT+β_6 PGR(6)
ECONOMETRIC FORM OF THE MODEL
This is gotten by adding the error term to the mathematical form of the model at such we have
M_GDP = β_0 + β_1 GEXP_EDUC+β_2 GEXP_HEALTH+β_3 FDI+β_4 EXCHR+β_5
INT+β_6 PGR+μ (7)
Where:
MVGDP = Manufacturing Value as % of GDP
GEXPEDUC =Government expenditure on education
GEXPHEALTH =Government expenditure on health
FDI = Foreign direct investment
EXCHR = Exchange rate
INT= lending interest rate
PGR = Population growth rate
.
MODEL SPECIFICATION
Every qualitative research work requires a clear specification of the model to be used. This
model will be used for Nigeria.
MODEL ONE: THE ORDINARY LEAST SQUARE REGRESSION MODEL
Based on the second and third research objective, which is if government expenditure on health
and education affects the manufacturing sector in Nigeria, this model is designed to capture
that objective.
M_GDP = β_0 + β_1 GEXP_EDUC+β_2 GEXP_HEALTH+β_3 FDI+β_4 EXCHR+β_5
INT+β_6 PGR+μ (8)
ESTIMATION PROCEDURE
Having specified the model, it is now left for the researcher to adopt an econometric estimation
procedure to test the previously stated hypothesis. The Ordinary Least Square (OLS)
techniques of estimation will be adopted for this study. The choice of the estimation procedure
was influenced by the procedure’s desirable BLUE (Best Linear Unbiased Estimator) property.
It also emphasizes on the value of the standard error for precision and test for statistical
significance.
According to Gujarati (2013), the following are the assumptions of the Ordinary Least Squares
method include:

28. The regression model is Linear in parameter i.e. zero mean value of the disturbance
E (Uj | Xi) = 0
Homoscedasticity or equal variance of Ui i.e. Var ( ui )= σ2
No autocorrelation of the disturbance term i.e. cov (Ui, Uj) = 0 i ≠ j
There is no perfect multi-collinearity.
Normality of the error term.
JUSTIFICATION OF VARIABLES
GOVERNMENT EXPENDITURE ON EDUCATION
β_1: This parameter for government expenditure on education, based on a priori should be
positive. This came from the fact that the literate citizenry will have to be the ones to supply
the human capital skills needed in the manufacturing sector since they have received training
in the form of education. A positive government expenditure on education translates that
manufacturing output will be increased because you are qualified to get a technical skill, learn
an art, or earn a degree and when this is done, output increases and it promotes economic
growth.
GOVERNMENT EXPENDITURE ON HEALTH
β_2: This research work expects the parameter for government expenditure on health, based
on a priori to be positive. This came from the fact that increased government expenditures on
health, unequivocally means healthy citizenry and these will have to be the ones to promote
and engender the human capital skills needed in the manufacturing sector. A positive
government expenditure on health translates that manufacturing output will be increased
because a healthy worker and not a sick worker, that is always on sick leave, will have to be
the one to produce the output.
FOREIGN DIRECT INVESTMENT
β_3: this study expects this parameter to be positive this is because increased foreign direct
investment on the manufacturing sector should stimulate a positive return to manufacturing
output, because the foreigners will develop these sector so as to make sure that they have high
return for their investment.
EXCHANGE RATE
β_4: Exchange rate parameter is expected to be negative. This stems from theory that increase
exchange rate overvalues the currency and at such decreases investment from abroad. At such
it should be negative so as to hold.
INTEREST RATE
β_5: This parameter measures the rate at which the banks lend money to the public. The reason
for using the lending interest rate is that it affects the investment decision of the firms and the

29. consumers in the sense that if the lending interest rate increases, deters firms from borrowing,
and at such investment actions in the economy reduces, on the other hand if it reduces, it
increases the money available for investment.
POPULATION GROWTH RATE
β_6: the parameter for population growth rate is positive because an increase an increase in
the population makes much more available the labour needed in the manufacturing sector.
TECHNIQUES FOR EVALUATING ESTIMATES
The result of the model will be evaluated based on three criteria: economic (a priori
expectations), statistical and econometric criteria
THE ECONOMIC CRITERIA/EVALUATION OF A PRIORI SIGNS (TEST)
PARAMETER EXPLANATORY VARIABLES A PRIORI SIGNS
β0 INTERCEPT POSITIVE
β1 GEXP_EDUC POSITIVE
β2 GEXP_HEALTH POSITIVE
β3 FDI POSITIVE
β4 EXCHR NEGATIVE
Β5 INR NEGATIVE
Β6 PGR POSITIVE
THE STATISTICAL CRITERION (FIRST ORDER) TEST
The statistical criteria for this study include:
THE COFFICIENT OF DETERMINATION TEST R2
The R2 is used to measure the goodness of fit of the model. It ranges between zero and one and
the closer it is to 1 the better the fit. It gives the proportion or amount of total variations in the
dependent variable that is explained jointly by all the explanatory variables (Gujarati: 2013).
THE STUDENT t- TEST
According to the Gujarati (2013) this is used to test the individual significance of values of the
variable in the model. The test assesses whether the mean of the variables in the model
(independent variables) are statistically different from each other. If the value of the t- statistic
exceeds the t – critical, we reject the null hypothesis that the variable is statistically insignificant
at the 5% level of significance. Otherwise we do not reject and conclude that the variable is
statistically significant.

30. THE F- TEST:
This is the ratio of two independent estimates of variance, which have been obtained from
sample data. Each involves some loss of degree of freedom. If the two estimates are close to
each other, their ratio will approach the value of (1) i.e. the greater the discrepancies between
the two variances, the better the value of the ratio. It can be used to determine the joint
significance of the variables used in the model. If the F-statistic exceeds the F-critical value,
we reject the null hypothesis that the variables are jointly insignificant at the 5% chosen level
of significance. Otherwise, we do not reject the null. Again, the probability value of the F-
statistic may also be used in reaching the same conclusion. If the probability value < 0.05, we
reject the null and conclude that the variables of the model are jointly significant (Gujarati:
2013).
ECONOMETRIC CRITERIA (SECOND ORDER) TEST
This research would also carry out some econometric test to verify whether the estimated
regression result conform to the classical linear regression model assumption. The tests include
as recommended by Gujarati (2013) include:
NORMALITY TEST:
This is used to test whether the error term follows a normal distribution. Symbolically,
normality test is used to ascertain whether µt˜ N (0, δ2). The Jaque-Bera test which follows the
Chi-squared distribution will be adopted. If JB < JB critical value, we do not reject the null
hypothesis that the error term is normally distributed at the chosen level of significance, but if
otherwise we reject. We can as well use its probability value to judge the result.
MULTI-COLLINEARITY TEST:
This will test whether there is high or perfect linear relationship among variables. If the
correlation coefficient between two variables exceeds 0.8, then such variables have high multi-
collinearity. The correlation matrix will be used to detect multi-co-linearity in this model.
HETEROSCEDASTICITY TEST:
One of the assumptions of the random variable Ut is that its probability distribution should be
constant over all observation of Xi, that is, the variance of each disturbance term is the same
for all values of the explanatory variables. The aim of the test is to see whether the error
variance of each observation is constant or not. Non-constant variance can cause the model to
yield a biased result. The Whites general heteroscedasticity test will be employed (Gujarati et
al 2007).
AUTOCORRELATION TEST:
This test checks whether the error terms are serially correlated or not. Durbin-Watson (d) test
will be used for this test. Durbin Watson values ranges from 0 to 4. The Durbin Watson
distribution table is used to verify the exact value of Durbin Watson tabulated.
CO-INTEGRATION TEST:

31. This is a test that measures the long run relationship that may exist between two or more
variables. The test will be performed using the Johansen co-integration test, if they are
integrated of only order one, otherwise, it will not be performed.
DEFINITION OF VARIABLES
MANUFACTURING OUTPUT
Manufacturing is the processing of raw materials into finished goods through the use of tools
and processes. Manufacturing is a value-adding process allowing businesses to sell finished
products at a premium over the value of the raw materials used. The manufacturing output, the
output of all factories in a country, is a sub-set of industrial output. Humans have historically
sought ways to turn raw materials, such as ore, wood, and foodstuffs, into finished products,
such as metal goods furniture and processed foods. By refining and processing this raw material
into something more useful, individuals and businesses have added value. This added value
increased the price of finished products, rendering manufacturing a profitable endeavor. People
began to specialize in the skills required to manufacture goods while others provided funds to
businesses to purchase tools and materials. Economists and government statisticians use
various ratios when evaluating the role manufacturing plays in the economy. Manufacturing
value added (MVA), for example, is an indicator that compares manufacturing output to the
size of the overall economy. It is expressed as a percentage of GDP - gross domestic product
GOVERNMENT EXPENDITURE ON EDUCATION
General government expenditure on education (current, capital, and transfers) is expressed as
a percentage of GDP. It includes expenditure funded by transfers from international sources to
government. General government usually refers to local, regional and central governments.
GOVERNMENT EXPENDITURE ON HEALTH.
According to IndexMundi (2013), Public health expenditure consists of recurrent and capital
spending from government (central and local) budgets, external borrowings and grants
(including donations from international agencies and nongovernmental organizations), and
social (or compulsory) health insurance funds.
FOREIGN DIRECT INVESTMENT
According to the IMF and OECD definitions, direct investment reflects the aim of obtaining a
lasting interest by a resident entity of one economy (direct investor) in an enterprise that is
resident in another economy (the direct investment enterprise). This is the investment in the
construction of physical capital such as building factories and infrastructure (i.e., power,
telecom, ports etc) in the capital importing country. It may be done in several ways. Companies
or corporation may be specially set up for the purpose in the capital-exporting country to carry
out trade and industry in an underdeveloped country. Another method is that an already existing
corporation spreads out its business in another country by establishing branches. The “lasting
interest” implies the existence of a long-term relationship between the direct investor and the
direct investment enterprise and a significant degree of influence on the management of the
latter.

32. EXCHANGE RATE
It may be noted that the foreign exchange is the name given to any foreign currency. Thus, US
dollars or British pounds are foreign exchange for Nigeria. Further, the exchange rate is the
price of a country’s currency in terms of another country’s currency. Since exchange rate is a
price, its determination can be explained through demand for and supply of currencies. Suppose
we consider the transactions between two countries, Nigeria and USA. In this case therefore
the demand for and supply of dollar is the demand for and supply of foreign exchange from the
Nigerian perspective and the of a US dollar in terms of Nigerian Naira or a number of dollars
per Nigerian Naira is the exchange rate. The system of exchange rate in which the value of a
currency is allowed to adjust freely or to float as determined by demand for and supply of
foreign exchange is called a flexible exchange system which is also known as floating exchange
system. On the other hand, if the exchange rate instead of being determined by demand for and
supply of foreign exchange is fixed by the government, it is called the fixed exchange rate
system. Under this system, exchange rate is not determined by demand for and supply of
foreign exchange but it is pegged at a certain rate. The effective exchange rate is an indicator
to grasp country's international competitiveness in terms of its foreign exchange rates that
cannot be understood by examining only individual exchange rates between the country's
currency and other currencies.
INTEREST RATE
Like any other commodity, money has a price. The price of money is known as the interest
rate. For a saver, interest is the return that is received for money deposited in banks or credit
institutions. This interest is the price that the banks or credit institutions pays savers for using
their money to on-lend to individuals or businesses. For a person borrowing, interest is the
extra amount that is paid to lending institutions for borrowing money from them. In other
words, when repaying a loan the borrower pays the amount borrowed (known as the principal)
plus some extra money (which is the interest) to the lending institution for using their funds.
The rate of interest that is offered by financial institutions affects peoples’ decisions on whether
to save or spend their money. Usually, when interest rates are high people tend to save or
deposit more of their money. By doing so, consumers are postponing their current spending to
a later date i.e. keeping money aside for future spending. Additionally, when interest rates are
elevated, people tend to borrow less since it costs more to take out loans today and means lower
spending in the future when the loans fall due. Businesses operate the same way, as higher
interest rates will raise their business costs and reduce the incentive for borrowing. The
decisions by savers and borrowers affect consumption and investment decisions, and ultimately
aggregate demand and overall economic activity. If interest rates are high, people are expected
to spend less. More money will go into saving and less will be borrowed for spending on
consumption and investment. Conversely, if interest rates are low, individuals and businesses
save less as their return on deposits will be low. They are likely to borrow more as the cost of
borrowing is cheaper. Consequently, there will be more spending that will boost economic
activity.
POPULATION GROWTH RATE

33. According to Indexmundi (2013), the average annual percent change in the population,
resulting from a surplus (or deficit) of births over deaths and the balance of migrants entering
and leaving a country. The rate may be positive or negative. The growth rate is a factor in
determining how great a burden would be imposed on a country by the changing needs of its
people for infrastructure (e.g., schools, hospitals, housing, roads), resources (e.g., food, water,
electricity), and jobs. Rapid population growth can be seen as threatening by neighboring
countries and at such should be studied closely so as to know its impact.
SOURCES OF DATA
The availability of appropriate data greatly affects the practicability of a research. As stressed
by Madueme (2010), the unavailability of data conceals information and makes the research
process difficult and myopic in nature. This study covers the period of 1981-2016. The
variables of interest include; Manufacturing value added % of GDP (〖MV〗_GDP),
government expenditure on education (GEXP_EDUC), government expenditure on health
(GEXP_HEALTH),, foreign direct investment (FDI), exchange rate (EXCHR), interest rate
(INR), and labour supply proxied by the population growth rate (PGR). The data will be
sourced secondarily from World Bank Development Index (WDI) and 2016 Central Bank of
Nigeria’s (CBN) Statistical Bulletin.
SOFTWARE APPLICATION
The software application that will be used in testing the regression analysis in this research
work is EViews 9 package. The choice of package is due to the reason that the package is very
easy to handle, comprehensive and contains the necessary econometric tools required for this
study.
CHAPTER FOUR
PRESENTATION AND INTERPRETATION OF RESULT
4.1 TIME SERIES PLOTS OF DATA
Trend analysis is a method of analysis of time series data involving the comparison of data
over a significantly long period to detect the general pattern of relationship between associated
factors or variables and also to project the future direction of this pattern. It helps us to evaluate
the movement of variables over the years.
FIGURE 4.1
Source: Researcher’s estimation using Microsoft Excel Office 2016.

34. From the figure above, one can visualize government recurrent expenditure on health and
education. From this figure, government expenditure on education has always been on the
increase and has been more than government expenditure on health. In the early 1980s up until
the end of the decade, there were no distinguishable difference between government
expenditure on health and education, this could be attributed to the slow rate of population
growth increase in the country, but in the early 2000, there seem to be a gradual departure from
their equality. Since then, government expenditure on education has been on the increase over
the years. Also, the graph tells us that in recent times the government recurrent expenditure on
health and education have been on the decrease in relation to her other recurrent expenditures,
that seem to help us infer that, the reduced government expenditure on health, reduce also the
manufacturing output though (with an upward trend as could be visualized by the dotted light-
green and blue lines in the figure 4.1.)
4.2 DESCRIPTIVE STATISTICS
In order to achieve objective one of the study, the descriptive statistics of the variables
government expenditure on education and health are presented in table 4.1 below.
TABLE 4.1: DESCRIPTIVE STATISTICS
LNG__EXP_EDUC LN_G__EXP_HEALTH
Mean 22.61675 23.44216
Median 23.44575 24.40921
Maximum 26.27514 26.69050
Minimum 17.53673 18.90406
Std. Dev. 2.843798 2.672152
Observation 35 35
Source: Researcher’s estimation using E-views 9
From table 4.1, log of government expenditure on education in Nigeria has a mean value of
22.61675 from the period 1982-2016 and the median value is 23.44575. The maximum value
is 26.27514 and the minimum value is 17.53673. There is also a standard deviation of
2.843798. Log of government expenditure on health has a mean value of 23.44216 from the
period of 1982-2016 and the median value is 24.40921. The maximum value is 26.69050 and
the minimum value is 18.90406. There is also a standard deviation of 2.672152.
4.3 PRE-ESTIMATION TESTS
Pre-estimation test is carried out to know if the data suites the criteria for economic analysis.
The estimation tests required are the stationarity and co-integration tests.
4.3.1 STATIONARY/UNIT ROOT TEST
In order to test for stationarity of the variables, the unit root test for stationarity will be
employed using the Augmented Dickey-fuller (ADF) test.

35. DECISION RULE:
If the absolute value for the ADF statistics > the critical value at 5% level of significant, such
is stationary, otherwise it is non-stationary.
TABLE 4.2 UNIT ROOT TEST
VARIABLES ADF
STAT
@LEVELS
5% CRITICAL
VALUES ADF STAT
@1ST DIFFERENCE5% CRITICAL
VALUES ORDER OF
INTEGRATION
MV_GDP -1.229919 -3.548490 -6.883368 -3.552973 I(1)
G__EXP_EDUC -1.608092 -3.548490 -5.397481 -3.552973 I(1)
G__EXP_HEALTH -3.892692 -4.859812 -19.04403 -4.859812 I(1)
FDI -3.512763 -3.574244 -6.892450 -3.552973 I(1)
EXCH_R -1.455494 -3.548490 -3.906913 -3.552973 I(1)
INT
-2.274928 -3.548490 -5.313778 -3.557759 I(1)
PGR -4.215257 -3.595026 I(0)
Source: Researcher’s computation using Eviews9
From table 4.2, manufacturing value, government expenditure on education and on health,
foreign direct investment, exchange rate, and interest rate are stationary at first difference while
population growth rate is stationary at level form.
4.4 PRESENTATION OF OLS REGRESSION RESULTS
TABLE 4.3 REGRESSION RESULTS (DEPENDENT VARIABLE: M)
Variable names Coefficients Standard error T-statistics P-value
C -4.008871 13.65024 -0.293685 0.7712
G__EXP_EDUC 0.014331 0.007859 1.823502 0.0789

36. G__EXP_HEALTH 0.020203 0.012218 1.653528 0.1094
FDI -7.68E-10 1.32E-10 -5.800377 0.0000
EXCH__R -0.027397 0.005797 -4.726407 0.0001
INT
-0.164745 0.047626 -3.459130 0.0018
PGR 5.760301 5.234057 1.100542 0.2805
Source: Researcher’s computation using EViews 9
R-squared = 0.831662, Adjusted R-squared = 0.795590, F-statistic = 23.05539, Prob(F-
statistic) = 0.000000, Durbin-Watson stat = 1.428573.
4.4.1 EVALUATION OF REGRESSION RESULTS
4.4.1.1 ECONOMIC CRITERIA OR COEFICIENT INTERPRETATION
In table 4.4, the estimated co-efficient for G__EXP_EDUC is 0.014331. This signifies that a
unit change in government expenditure on educcation leads to 0.014331 units increase in
manufacturing output as a percentage of gross domestic product. This does conform to a priori
expectation because an increase in government expenditure on education increases
manufacturing output. The estimated co-efficient for G__EXP_HEALTH is 0.020203. This
shows that a unit increase in government expenditure on health will lead to 0.020203 units
increase in manufacturing output as a percentage of gross domestic product. This does conform
with a priori, and we can infer that increased government expenditure on education does
increase manufacturing output. The estimated co-efficient for FDI is -7.68E-10. This shows
that one-unit increase in foreign direct investment will lead to -7.68E-10 units increase in
manufacturing output as a percentage of GDP. One can infer from this that foreign direct
investment may not have been directed at the manufacturing sector, it may have been directed
at other competing or priority sectors like the energy, construction, services sectors of the
economy. The estimated co-efficient for exchange rate is -0.027397. This shows that one
percentage increase in exchange rate will lead to -0.027397 percent decrease in manufacturing
output. This conforms with a priori, because if the currency is overvalued, it discourages
foreigners to invest in such an economy, thereby leading to reduced investment level in the
economy coming from abroad. The estimated co-efficient for lending interest rate is -0.164745.
One percent increase in lending interest rate, decreases manufacturing output by -0.164745%.
This does conform with a priori, and one can postulate that lending interest rate has a negative
relationship with investment decision in an economy, because increased lending rate
discourages investors that wish to borrow money for investment purposes. This is so, because
the opportunity cost of money is high. The estimated co-efficient for labor supply as proxied
by population growth rate is 5.760301. This shows that a percent increase in population growth
rate will lead to 5.760301% increase in manufacturing output. This indicates that the a priori
does hold here. Since increased population increases manufacturing output, it then means that

37. the firms in the manufacturing sector makes use of labour intensive methods rather than capital
intensive production methods.
4.4.1.2 STATISTICAL CRITERIA
COEFFICIENT OF DETERMINATION (R2) AND ADJUSTED R2
The coefficient of determination (R2) measures the proportion of the variation in
manufacturing output (percent of Gross Domestic product) is explained by government
expenditure on education, government expenditure on health, foreign direct investment,
exchange rate, interest rate, and labour supply proxied by the population growth. The R2 for
Nigeria in Table 4.4 is 0.831662. This implies that the explanatory variables; government
expenditure on education, government expenditure on health, foreign direct investment,
exchange rate, interest rate, and labour supply proxied by the population growth rate explain
about 83.16% of the total variations in the dependent variable (manufacturing output). This
signifies that the model is a good fit. To check if the model is parsimonious enough the model
was adjusted for degree of freedom, the R square was adjusted to get the Adjusted R2 which is
0.795590. Since the difference between the R square and the Adjusted R square is negligible,
it signifies that that the model is parsimonious.
F-TEST
The f-test is used to test for the overall significance of the model. If the value of the f statistics
from the regression result exceeds the f-value from the f-distribution table, then the model is
statistically significant. If otherwise, then it is statistically insignificant. When using the
probability value, it implies that if the probability value is less than 0.05, then the model is
statistically significant. The F-statistic is 23.05539, and the Probability value = 0.000000 which
is less than 0.05. Therefore, the models are statistically significant.
T-TEST
The t-test is used to test for the statistical significance of a variable. If the value of the t-statistics
from the regression result exceeds the t-value from the t-distribution table, then the variable is
statistically significant. If otherwise, then it is statistically insignificant. When using the
probability value, it implies that if the probability value is less than 0.05, then the variable is
statistically significant. From the regression result in table 4.4, the variables foreign direct
investment, exchange rate and interest rate are statistically significantly different from zero.
On the other hand, government expenditure on education, government expenditure on health,
and labour supply proxied by the population growth rate are not statistically significantly
different from zero.
4.4.1.3 ECONOMETRIC CRITERIA (POST-ESTIMATION TEST)

38. Post estimation will be employed in order to test for stability and to determine if the result can
be used for forecasting. Post estimation test include: normality test, autocorrelation test, and
heteroscedascity test.
CORRELATION MATRIX (MULTICOLLINEARITY TEST)
The correlation matrix shows the degree of relationship, either positive or negative, between
all the variables under consideration. If there is a high either a positive or negative degree of
relationship between the explanatory variables, then the problem of multicollinearity is in
existence in the model. High correlation of above 0.8 between explanatory variables is not
desirable while high correlation of above 0.8 between dependent and independent variables are
desirable. This is so because a high correlation between dependent variables would make it
difficult to analyze the different impact of the individual explanatory variables that are
correlated, on the dependent variable
TABLE 4.4 CORRELATION MATRIX
GMO G_EXP_EDUC G__EXP_HEALTH FDI EXCH__R INT
PGR
GMO 1.000000 0.207432 0.228215 -0.240688 -0.177845 -0.540604
0.244814
G_EXP_EDUC_ 0.207432 1.000000 0.978521 0.752631 0.847859
-0.104392 0.694926
G__EXP_HEALTH 0.228215 0.978521 1.000000 0.742612 0.834863
-0.118244 0.696618
FDI -0.240688 0.752631 0.742612 1.000000 0.728495 -0.052756
0.702140
EXCH__R -0.177845 0.847859 0.834863 0.728495 1.000000
0.081673 0.510125
INT -0.540604 -0.104392 -0.118244 -0.052756 0.081673 1.000000
-0.376359
PGR 0.244814 0.694926 0.696618 0.702140 0.510125 -0.376359
1.000000
Source: Researcher’s computation using Eviews9.
From table 4.5, there is positive high correlation between government expenditure on education
and government expenditure on health of 0.978521 (this is greater than 0.8). However,
Christopher Achen in Gujarati (2013), stated that multicollinearity is not a serious problem in
econometric estimation and thus can be disregarded.

39. NORMALITY TEST
This study will carry out a normality test to check if the residuals, a proxy for stochastic error
term, follow a normal distribution or not. The normality test that will be used in this study is
Jarque-Bera (JB) test of normality.
DECISION RULE:
Reject the null hypothesis if JBcal > JBtab (0.05) with 2 degrees of freedom, do not reject if
otherwise.
The JBCal has been calculated from the software used in the conducting the Jarque-Bera test.
Thus the results are presented below.
JBcal = 3.559291
The JBtab was gotten from aa four-figure table with 2 degrees of freedom. Thus we have,
JBtab(0.05) = 5.991
FIGURE 4.2 NORMALITY TEST
Source: Researcher’s computation using Eviews9
Following the decision rule, in Fig 4.2, since 3.559291 < 5.991 that is JBcal < JBtab we fail to
reject the null hypothesis (H0) and thus conclude that the error terms are normally distributed.
Therefore, error term is normally distributed. The shape of the histogram does follow a normal
distribution and therefore the error term is normally distributed.
AUTOCORRELATION TEST
We used Breusch-Godfrey serial correlation LM test to check for autocorrelation
TABLE 4.5 BREUSCH-GODFREY SERIAL CORRELATION LM TEST
F-statistic 1.057716 Prob. F(4,23) 0.3617
Obs*R-squared 2.633432 Prob. Chi-Square(4) 0.2680
Source: Researcher’s computation using Eviews9
The decision rule is to reject Ho if the autocorrelation probability value which follows the chi-
square distribution is less than 5%, otherwise do not reject Ho. From table 4.6, the probability
value 0.3617 is greater than 0.05. Therefore, since the probability value (0.4712) is greater than
5%, we do not reject the Ho which means there is no presence of autocorrelation.