education and economic growth

CHAPTER ONE

INTRODUCTION

1.1 BACKGROUND TO THE STUDY

The study of economic growth across countries has gone in phases with

economists explaining the various factors that contribute to the growth and

ultimately the development of the country. We tend to be concerned about the

disparity in development cum state of welfare across countries.

Basically, economists study economic growth across countries for at least three

reasons. First, to understand the source of varied patterns of growth. Concern for

this becomes paramount because persistent disparities in economic growth rates

across countries over the years led to large differences in welfare. Secondly, there

has emerged a rigorous broad based body of a theoretical hypothesis on economic

growth that is ambiguous in scale and scope. Third is the fact that the first wave

of empirical growth analysis by making strong controversial claims have

provoked yet newer ways of analyzing the growth process. (Quah D. T. et al,

1999)

The history of economic growth studies show that countries have differing growth

paths. This can begin to explain the welfare disparities among countries. Thus,

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while in the late 18th century, economic transformation began in England and

spread gradually to other parts of Europe and North America, it did not get to

Asia (Japan to be precise ) until the 1950s. These different growth paths gave rise

to income gaps between nations; which is in no way permanent as current

evidence has shown.

As economic growth, a component of economic development, does not take place

in a vacuum; there are basic factors that motivate growth which include basic

resources, land, labour, capital, human capital, education, training and health and

productivity. The availability of these engines of growth is in no way a guarantee

for growth. It is improving a country’s investment performance in both human

and physical assets that is important for growth (Essien)

Education and its impact on economic growth has not received the required

attention through the years. Schultz (1961), the pioneer in the field talks about the

“moral issue of treating education as an investment in man”. Galbraith (1964) in

the same vein took people to be the common denominator of progress and stated

that “no improvement is possible with unimproved people”. These positions

reinforce the view that the human factor and the level of education are indeed the

most crucial determinants of a country’s level of economic development.

Following this the enthusiasm for education studies had led to various attempts at

measuring both human capital and the rate of return on education. Education has

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thus become treated as an investment rather than consumption. Denison’s (1964)

dominant hypothesis is that education positively affects economic growth since it

results in increases in the level of cognitive skills possessed by the labour force

and consequently its marginal productivity.

The role of education in the development of society cannot be overemphasized.

The socio political and economic well being of a nation is in many ways

determined by the quality and level of educational attainment of the population.

Thus, education, a productive investment in human capital, is a tool adopted by

developing countries for accelerating economic development and promoting

standards of living.

According to World Bank (1999), from a global perspective, economic and social

developments are increasingly driven by the advancement and application of

knowledge. Education in general and higher education in particular are

fundamental to the construction of the knowledge economy and society in all

nations. Poverty, an implication of a low level of development, is characteristic of

the uneducated members of the society. The 1996 World Bank Poverty

Assessment on Nigeria stated that “... poverty in Nigeria, in addition to its

overwhelming rural and regional characteristic is also strongly influenced by

education…Those without education account for most of the poor and an

overwhelmingly large fraction of the extreme poor”

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In a UNDP (1996) report where countries were ranked based on life expectancy,

educational attainment and basic purchasing power, Nigeria ranked 147th country

out of 174 and soon dropped to the 141st position in 1997. Thus, the report

described Nigeria as a low human development country due to the fact that 47.5%

of the population are still illiterates. Otherwise stated, low educational attainment

has implication for economic development, incidence of poverty.

The East Asian economic miracle of economic growth and advancement had

increased investment in education as one its motivation. This incident has

undoubtedly raised interest in the study of the role of education in the growth

process. Thus, the importance of education as a means of enhancing growth in

Nigeria cannot be overemphasized, as education contributes vitally, substantially

economic benefits directly and indirectly to individuals and society.

The major objective of this work is to establish the link between education and the

process of economic growth and development with specific reference to Nigeria.

1.2 STATEMENT OF THE PROBLEM

The world was once said to be at the same level of civilization. Now the tale is

different with the question of wide disparity of economic growth and

development among countries of the world. The question then arises as to the

cause of different levels of growth among countries. Countries are laden, even

internally, with disparities in income and welfare.

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The positive relationship between education and expected future income

translating to economic growth is well established by several studies. (Schultz

1961, Psacharopoulos, 1985, Barro and Sala-I-Martin 1995, Strauss et al 1995).

However, inspite of the clear evidence of strong returns to education many

economies still exhibit low educational attainment, especially in the rural areas of

the developing world. Then one begins to question the wide disparity in economic

growth and development.

Economic theories suggest a strong causal link from education to growth but the

empirical evidence has not been unanimous and conclusive. The disparity in

growth is perceivable by the global, continental and even national growth

conditions of countries. Lopez, Thomas and Wang (1988) focus on two factors

that could serve as explanations for why empirical studies have not

overwhelmingly supported the theories. They made the following observations

using panel data for the period of 1970- 94 from 20 developing countries to

investigate the relationship between education, policy reforms and economic

growth

First is the fact that the distribution of education affects economic growth. The

distribution of education matters. An overly skewed distribution of education

tends to have a negative impact on per capita income in most countries.

Controlling for education distribution using the appropriate functional form leads

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to positive and significant effects of average education on per capita income,

while failure to do so leads to insignificant or negative effects of average

education. Second is the fact that economic policy environment greatly affects the

impact of education on growth by determining what people can do with their

education. Results indicate that economic policies that suppress market forces

tend to reduce the impact of education on economic growth. Moreover, the stock

of physical capital is negatively related to economic growth for economies in the

sample, implying a declining marginal productivity of capital. (Lopez, Thomas

and Wang 1988)

Despite all efforts at providing educational opportunities for most of those who

need them, educational opportunities in Nigeria remain unequally distributed,

drop out and repeater rates are rather high, the quality of education provided is

poor and even graduates from the educational institutions discover that what they

have to offer is not in consonance with the employer’s requirements (Omolewa

and Daniel-Okiei, undated). Thus, Africa’s low profile in education and gender

disparities compromises Africans abilities to develop future leaders and informed

citizens.

1.3 SCOPE OF THE STUDY

In observing the Nigerian experience, the study covers a period of 35 years from

1970 -2004.

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1.4 OBJECTIVES OF THE STUDY

The broad objective of the study is to examine the impact of education on

economic growth and development.

Sub-objectives of the study are as follows:

1. To determine the relationship between education and economic

growth in Nigeria.

2. To examine the relationship between education and productivity.

3. To establish a link between education and human capital.

4. To examine the impact of human capital development on

economic development

1.5 SIGNIFICANCE OF THE STUDY

The world economy has gone through different eras. We have experienced the

industrial revolution. We approach the knowledge economy, the information age

where the advancement of every economy and society will be on the ticket of the

level of information it is trading with. The openness of the economy to

information increases its tendency to improve in technology and improvement in

technology leads to greater productivity, increase in productivity has implication

for rise in economic growth. Consequently, economic growth, through its effect

on income and aggregate expenditure improves living standard of a populace – an

expression of economic development. This study will enlighten on the ‘multiplier’

effect of appropriate education on the future incomes of the country as a whole.

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Armed with the information from this study, policy makers would push for

policies that advocate increased revenue allocation to the social services sector,

especially education and health. An attempt will be made in the discussion and

recommendation section to address the issue of widespread unemployment among

the university graduates in Nigeria. Employers, government and private, would

identify here that there is a link between education, training and productivity of

labour.

In summary, the study provides policy implications as it relates to the vital link

between education, economic growth and development. This paper, in addition,

will be of importance to those who hope to further research into this field or

related fields of study.

1.6 RESEARCH QUESTIONS

This study attempts to give answers to the following questions

1. Is there a cause and effect relationship between education and economic

growth?

2. What are the factors that are responsible for educational attainment in

Nigeria?

3. What are the factors responsible for economic growth in Nigeria?

4. What is the impact of education on economic growth in Nigeria

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1.7 HYPOTHESIS OF THE STUDY

In an effort to realize the objective of this study, we will subject this hypothesis to test.

- Ho: there is no statistically significant relationship between the level of education and

economic growth

1.8 METHODOLOGY OF THE STUDY

Method of data collection.

The data for this study are secondary data mainly time series obtained from the

Central Bank of Nigeria Annual reports and Statement of Accounts (various

years), Central Bank of Nigeria statistical bulletin, Federal Office of statistics.

Method of Data Analysis

Econometric approach will be applied and the method of Ordinary Least Squares

(OLS) which is one of the econometric methods of estimation will be utilized in

estimating the specified parameters of the model.

1.9 SOURCES OF DATA AND INFORMATION

Secondary data used is obtained from diverse sources such as:

1. Central Bank of Nigeria Statistical Bulletin (2004)

2. Central Bank of Nigeria: Economic and Financial Review (various issues)

3. Central Bank of Nigeria: Annual Reports and Statement of Accounts

(various issues)

4. Federal Office of Statistics (2001)

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5. Journal articles

6. Textbooks and

7. NES publications

1.10 LIMITATION OF THE STUDY

It is common knowledge that secondary data are laden with estimation errors. The

extent of accuracy of our findings and estimations will thus be limited by the

extent of the accuracy of data obtained. The paucity of data for economic

variables that is characteristic of all research work will also be a major limitation.

For lack of quantitative evidences, we will not capture the ‘quality’ of education

in our model.

The scope of the study will be limited to the research materials consulted due to

time and resource constraints.

Another issue is the discrepancy in the data presented by various organization –

Central Bank Of Nigeria, National Bureau of Economic Research to mention a

few. The validity and reality of such data obtained is therefore questionable.

The poor data quality is an adjoining issue. It leads to difficulty in empirically

verifying models.

Expenditure values on health and nutrition would have been useful to measure the

potential impact on human capital and economic performance. Data on these are

however not readily available. Also statistics on state and local government

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education expenditure are not readily available and so are not included in the

study.

1.11 STRUCTURE OF THE STUDY

The remaining part of the study will be structured as follows. Chapter two, which

is the literature review, will present the review of relevant literature which

includes conceptual frameworks, methodologies, empirical evidences, theories,

propositions, hypothesis, findings and conclusions of other scientific works and

writings related to my research topic. This section is imperative because scientific

research, as we have it, is not done in isolation. Scientific knowledge is

cumulative, that is, it builds on existing knowledge. Chapter three embodies the

research methodology. Here, we will specify our empirical models and the data

required to carry out the study. We shall also present in detail the method of data

analysis. Chapter four constitutes the empirical analysis. It will include data

presentation and, statistical analysis and presentation of results and concluded

with interpretation and discussion of results. Chapter five which is a summary

will present recommendations and conclusions of the study.

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CHAPTER TWO

LITERATURE REVIEW

INTRODUCTION

This constitutes a review of relevant literature which includes conceptual

frameworks, methodologies, empirical evidences, theories, propositions,

hypothesis, findings and conclusions of other scientific works and writings related

to my research topic.

2.1 THEORIES OF ECONOMIC GROWTH

The study of economic growth has gone in phases with the neoclassical traditional

views on economic growth (exogenous growth models) and more recently the

new growth theories (endogenous growth models). The most important work of

the exogenous class models of growth is that done by Solow (1956). The basic

neoclassical model assumes that technological change is exogenous to the

economic process (Solow 1956, 57, 70). The old neoclassical notion of economic

growth states that as physical and human capital are accumulated, their increasing

contribution to output diminishes. This has such implication for developing

countries that, since they have smaller endowments of physical and human

capital, they will grow faster than rich countries for the same level of investment

in physical and human assets. It was thus predicted that poor economies will

eventually catch up with rich economies and personal incomes will converge.

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Contrariwise, evidence shows that developing countries are not catching up with

developed countries. Studies of average growth rate of countries show that the

developed nations appear to have grown at a faster rate. Thus, the old neoclassical

theory is not able to account for the diverging development of nations and the

exogenous technical change is questioned. (Harry Anthony Patrinos, undated).

The main drawback of the neoclassical growth theory is that it does not explain

how or why technological progress occurs. It is this shortcoming that has led to

the development of the endogenous growth theory, which endogenizes

technological progress cum knowledge accumulation.

Here, we will be examining formal endogenous growth models that claim that

education plays a central role in the process of economic growth.

One of the most prominent and influential contribution is that of Lucas (1988)

which is in turn related to previous work by Uzawa (1965). In these models, the

level of output is a function of the stock of human capital. They posited that in the

long run, sustained growth is only possible if human capital can grow without

bound. This makes it difficult to interpret the Uzawa-Lucas conception of human

capital in terms of the variables traditionally used to measure educational

attainment, such as years of schooling. Their use of the term “human capital”

seems more closely related to knowledge, rather than skills acquired through

education.

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Bils and Klenow (2000) presented a way of relating the Uzawa-Lucas model to

the data by suggesting that the quality of education could be increasing over time.

Following this knowledge imparted to school children in the year 2000 is superior

to the knowledge that would make a greater difference to their productivity in

later employment. Even if average educational attainment is constant over time,

the stock of human capital could be increasing in a way that promotes rising

levels of output. (Temple 2001)

At higher level education, there are courses in which the knowledge imparted has

greater effect on productivity than ever before (e.g. computer science,

economics), but there are others whose vocational qualifications are less

convincing.

With the primary and secondary schooling’s focus on basic skills such as literacy

and numeracy, the idea that increases in the quality of schooling drive sustained

growth is even harder to support. It is worthy of note that the Lucas and Uzawa

models are typically silent on exactly how the increase in the quality of schooling

is brought about: that individuals can raise the stock of human capital, or

knowledge, simply by allocating some of their time to its accumulation.

An alternative class of models places more emphasis on modeling the incentives

that firms have to generate new ideas. Endogenous growth models based on the

analysis of research and development, notably the landmark contribution of

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Romer (1990), yields the result that the steady –state growth rate partly depends

on the level of human capital. Underlying this was the assumption that human

capital is a key input in the production of new ideas. This view is held in contrast

with the Uzawa-Lucas framework, as it opens up the possibility that even a one

time increase in the stock of human capital will raise the growth rate indefinitely.

As many endogenous growth models posit, human capital must be of a necessity

be above a threshold for an innovation to take place at all.

The Uzawa-Lucas framework can be seen as a model of knowledge accumulation

similar to that of Romer, but easier to analyze; Restrictive assumptions are needed

to yield the Romer result that the long run growth rate depends on the level of

human capital (Jones, 1995). But even under more general assumptions, a rise in

the level of human capital is likely to be associated with a potentially substantial

rise in the level of output brought about through a transitional increase in growth

rates.

In most endogenous growth models based on research and development, the stock

of human capital is taken to be exogenously determined. More papers, notably

Acemoglu (1997) and Redding (1996) have relaxed this assumption, and

considered what happens when individuals can choose to make investments in

education or training, while firms make investments in research and development.

For some parameter values, multiple equilibria are possible, since the incentives

of workers to invest in human capital, and those of firms to invest in research and

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development, are independent. This provides a way of formalizing earlier ideas

about the possible existence of a “low skill, low-quality trap” in which low skill

levels and low rates of innovation reflect a coordination failure (Finegold and

Soskice 1988). The models suggest that, at the aggregate level, greater investment

in education or training might raise expenditure on research and development and

vice versa.

Another interesting aspect of recent growth models is their suggestion that

individuals may under-invest in education. Rustichini and Schmitz (1991)

examine this argument in detail. They present a model in which individuals divide

their time between production, original research, and the acquisition of knowledge

(through education) will raise their productivity in subsequent research, but since

they do not fully capture the benefits of research, they will tend to spend too little

time acquiring knowledge relative to the socially optimal outcome. Rustichini and

Schmitz calibrate a simple model, and find that although policy intervention has

only small effects on the allocation of time to education, it can have a substantial

effect on the growth rate.

More recently, Romer (2000) has pointed out that models of growth driven by

research and development should potentially inform education policy. He notes

that, in the models reviewed above, growth is determined by the quantity of inputs

used in research and development, not simply expenditure upon it. One reason

this point matters is that incentives to encourage research and development, such

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a tax credits, may be ineffective unless they encourage a greater number of

scientists and engineers to work towards developing new ideas. To illustrate this,

consider a very simple model, in which a fixed supply of scientists only work in

research and development and are the only input to the research process. Then an

increase in research and development spending will simply raise the wages of

scientists, with no effect on the number of researchers engaged in research and

development or the growth rate.

In summary, the models of the new growth theory are important for several

reasons: First, they see human capital as an important input in the creation of new

ideas and this mechanism provides a relatively appealing justification for viewing

education as a central determinant of growth rates, even over long time intervals.

Second, they sometimes yield the result that the laissez faire outcome delivers

slower growth than is socially optimal.

The models suggest that policy makers wishing to raise the level of output have

several options; not just direct support for research and development, which may

be difficult to implement and monitor- but also subsidies to certain kinds of

education.

2.2 EDUCATION AND ECONOMIC GROWTH

Easterlin formulated an interesting hypothesis in 1981 using an historical

approach. His study strove to explain the underdevelopment in some countries of

the world by the late arrival of mass primary education, which delayed the process

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of technology transfer. He based his study on a small number of western and

developing countries and he claimed that the reason why economic growth has

spread so slowly among the nations of the world is because of geographical

diffusion of technology. This limitation he linked to both the quantity and quality

of the educational systems. Since technology transfer is intimately linked to the

educational process, Easterlin therefore sees schooling as a crucial variable. The

spread of technology depends on learning potentials linked to formal schooling.

A problem however arises when curricula is insufficiently adapted to national

requirements or when curricula is totally inappropriate. This accounts for why

“the human capital revolution had little impact on educational theory and policy

in developing countries”, with the exception of the four Asian tigers. (Mehmet,

1999:137)

A first test to Easterlin’s hypothesis was provided by Hanson (1989) in his study

of 37 ex-colonies of the most developed European countries in 1960. Hanson

(1989) finds first that schooling in these countries was determined primarily by

socio-cultural and political factors. By regressing several indicators of economic

development, of technology, and of income on the adult literacy rate, he then went

on to show that all coefficients for the literacy rate (corresponding to the several

regression equations) are statistically significant. In particular, increases in the

literacy rate have a statistically significant (and positive) impact largely

contributed to the debate. For example, Benavot (1989) applies a panel regression

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methodology to 93 developed and developing countries to investigate the long

term effects of enrolment rates at primary and secondary levels (1960- 1985). His

results provide “evidence that primary education substantially differences

(Benavot, 1989). Interestingly in developing countries, educational expansion

among school age girls at primary level has a stronger effect on long term

economic prosperity than does educational expansion among school age boys”.

Educating girls is a foundation of the next generation of human capital; it reduces

poverty and contributes directly to sustainable economic growth (ADB, 2000;

Schultz 2002)

In his literature review of the education- growth relationship,

Psacharopoulos(1993) claims that in general, the rate of return to education are

higher for primary education than for further education, and that primary

education contributes more to growth in Developing Countries than in Developed

countries. A substantial primary schooling system is essential for economic

growth in the first stages of economic development. The widespread basic literacy

affects positively economic development in developing countries is multifold.

Basic education (up to age of 14) is sufficient to absorb simple technologies, and

leads to macro-economic productivity gains. Mass formal schooling preceded

economic growth in western countries such as the USA and Germany, whereas

the case of generalized basic education is often cited as the key explanatory

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element of the four East Asian Tigers’ fast growth experience in modern times

(Chowdhury and Islam, 1993; Sen., 1997).

Adult literacy rates, taken as the most visible result of widespread schooling at

primary level, were all above 50% in 1960 and above 85% in the mid 1980s in

South Korea, Taiwan, Hong Kong and Singapore. These economies had

substantially high literacy rates and high levels of primary education before they

embarked upon their export-led growth economic recovery.

On the other hand, studies relating to the impact of tertiary education on economic

growth provide mixed results. The plurality of conclusions of studies is explained

by a variety of factors, among which are: the fact that different studies rely on

different variables (enrolment rates as opposed to literacy rates of the working

population; the non uniformity in the definitions of educational levels across

countries; finally, the linear form of the models used, concealing thereby the

effect of structural breaks and of critical values.

Graff (2001) tried to bring some explanations for this “higher education puzzle”.

One is the law of diminishing returns, which states that the marginal contribution

of education to productivity growth decreases with the accumulation of human

capital stocks. This leads to the view that the major beneficial impact of

computerization, of digitalization, and of the corresponding tertiary education, on

productivity and growth are over in the developed countries (Gordon, 2000)

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In order to understand the extent to which the use of different educational

attainment indicators may lead to consistent, or alternatively, to different and

contradictory analysis and results, Lall (2001:149) analyses the correlation of

three particular indicators with per capita income, using data on 120 countries. He

finds that tertiary technical enrolment is highly correlated with incomes

nevertheless. These findings suggest is that wealthier countries have a greater

financial ability to invest in human capital at the higher levels of education than

poorer countries. The study of the human capital accumulation- economic

development relationship in indeed laden with the cause and effect confusion (is

human capital the cause of economic development or is economic development

the cause of increasing human capital accumulation? Is it a bi-directional

relationship). The positive impact of economic growth on education explains the

development of tertiary education in developed countries where a much larger

amount of public funding is required.

In spite of the various shortcomings when measuring exactly educational

attainment (as a proxy of human capital accumulation) and when studying the

human capital –growth relationship, two major conclusions can be drawn from the

various studies undertaken on this issue.

- i- educational attainment indicators are highly correlated with the wealth levels of

countries; in particular, mass primary education has a positive impact on growth

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- ii- different levels of education have different impacts on growth, depending on

the stage of economic development reached by the various countries and also on

the quality of education (Andresso O’Callaghan 2002)

2.3 EDUCATION AND PRODUCTIVITY

If education is effective as a signal for productivity then the better educated really

are more productive and will thus earn more even after the employer has learned.

Evidence from Italy by Brown and Sessions (1999) show that individuals who

plan to become self-employed do not have as large an incentive to invest in

education. Thus, the return to education for this group only reflects productivity

while the returns for the employees reflects both human capital and a value as a

signal

Under the human capital theory, the content of the curriculum matters to wages.

In particular, Miller and Volker (1984) suggest that graduates employed in jobs

that are related to their earlier degree studies are exploiting their human capital

while those who are employed in some different field are only exploiting the

value that their degree has a signal for productivity.

Chevalier et al (2003) found evidence of the effect of education on wages.

Supporting the human capital interpretation of the correlation between education

and wages. The Human capital explanation due to Becker (1962) suggest that the

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correlation between education and wages is due to the education enhancing

productivity.

The importance of educating the human factor with knowledge and skills holds

very crucial implications for modern production as reflected in the distribution of

income among people who own knowledge and skills and physical capital.

The link between education and productivity is perceived by employers. They pay

for employee training because they expect to cover their costs and gain additional

profits from increased productivity. Educated and skilled folks are usually able to

deliver greater output or more valuable output in the market place and their

employers tend to recognize that fact with higher wages. (Beyond economic

growth undated)

Education is a component of human development as health is. Education has been

noted to have a strong effect on labour productivity. Birdsall (1993) using

agriculture data from Malaysia, Ghana and Peru showed that hat each extra year

of a farmer’s schooling is associated with an annual increase in output of 2.5%. In

a similar effort, Duflo (2000) estimated an increase in wages in Indonesia of 1.5

to 2.7% for each additional school built per 1000 children.

Topel (1999) tables an argument for the correct specification of the relationship

between education and productivity. In a labour economics specification of a

constant relationship between the log of productivity and level of years of

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education changes in the average level of education and the growth rate of

productivity. He found out a significant relationship between changes in

education levels and productivity growth.

Taking a look at the Nigerian experience, there appears to be a direct relationship

between the output per head and the literacy rate since most basic tasks in recent

times rely on efficient written communication and dissemination of information

through computers, electronic and print media among the labour work force. In

consonance with this Adewole (1998), noted that: the average citizen with at least

basic literacy and numeracy can be helped to cope adequately with the problems

of meeting his needs for food, shelter, clothing and the maintenance of good

health as well as learn how to manage his own economic affairs, his role as a

good citizen in the community and his part in the family.

2.4 EDUCATION AND HUMAN CAPITAL

Economists like Alfred Marshall (1930) and Adam Smith (1937) had already

also stressed the significance of education in human capital formation. Myers

(1964) maintained that the most obvious way of developing human capital is

formal education, beginning with first level education with various forms of post

primary education and post secondary education.

Human capital, as distinct from physical capital, is a combination of people’s

abilities, knowledge and skills. In the 1980s, evidence from the United States

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showed that income receipts on knowledge and skills (through wages and salaries

exceeded the income receipts from physical capital (through dividends and

undistributed corporate profits. It was with this phenomenon that economists

began to appreciate the existence of human capital.

The 1990s ushered in the awareness of a new era in global economic development

with the knowledge economy- knowledge based and knowledge driven economy.

This awareness arose from the fact that countries that invested most actively in

knowledge creation and adaptation (through investment in research and

development activities) as well as in knowledge dissemination (through

investment in education as well as in Information and Communications

Technology) tended to become most successful in solving their development

problems. (Beyond Economic Growth, undated)

Consequently there arises the notion that even poor countries, who are

characterized by insufficient resources to invest in the creation of new knowledge,

can advance in their development provided that they succeed in absorbing

advanced global knowledge and adapting it to the needs of their developing

economies. A well educated and adaptive population is seen as central to this task.

The East Asian economic miracle is living proof of this assertion. (World Bank,

1993)

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Education and training are tools whereby most human capital is built, thus

enhancing an individuals economic productivity. By enhance productivity we

mean that this education and training enables the individual produce more and

more valuable goods and services and thus to earn a higher income. Investment in

human capital is a responsibility accepted by economic actors – government,

workers, employers in devoting their money and time to education and training.

The investments are liable to yield dividends.

We can identify the varying motivations for investment in education. Government

spends public funds on education because they believe that a better educated

population will contribute to faster and more sustainable development. Employers

pay for employee training because they expect to cover their costs and gain

additional profits from increased productivity.

Beyond Economic Growth (Undated) notes that economic returns to education are

not always the same; saying that returns to education may be lower if

- the quality of education is low or knowledge and skills acquired at school do not

match market demand. In this case, investments in human capital were not

efficient enough, resulting in less human capital and lower returns to individuals

and society.

- there is insufficient demand for human capital because of slow economic growth.

In this case, workers’ human capital may be underused and under-rewarded.

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- workers with lower and higher education and skills are deliberately paid similar

wages to preserve a relative equality of earnings as used to happen in centrally

planned economies. These distortions in relative wages are being eliminated as

part of these countries transition to market economies

It is pertinent to note that the rate of increase in the national stock of human

capital is crucial to the rate of economic development as this constitutes vital

determinants of a country’s ability to produce and adopt technological

innovations. Investing in human is however not sufficient for rapid economic

growth it must be accompanied by the right development strategy.

Education expenditure in Nigeria became a matter of keen consideration from

1960 at the advent of the Ashby Commission’s Report on “Investment in

Education” which led to the increase I the university places available to Nigerian.

Certainly, education is a growing sector in Nigeria and there is correlation

between education and economic development. Insufficient and uncertain

budgetary allocation has been the bane of the deterioration of education’s impact

on human capital development. A major finding of the World Bank (1994), in

comparison with other countries (as Ghana, Zimbabwe, Philippines, Thailand,

Mexico, Cameroon, Kenya) Nigeria spent less of its total government budget in

education; as education expenditure, as a percentage of Gross National Product,

was higher in Ghana, Kenya and Zimbabwe than in Nigeria. With a continuation

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of such trend in education financing, the effect on the overall human capital

development hope of the country would be devastating.

Examining the education expenditure and human capital development relation,

Adamu (2002) in Awopegba (2002) stated that human capital formation

transcends mere acquisition of intellectual ability through formal education

system. It is through human capital investment, an indispensable component of

the development process. Buffie (1994) in a cross country study investigated the

reducing human capital. In his model, he distinguished between skilled and

unskilled labour in manufacturing sector. His finding show that the investment on

human capital formation ultimately leads to capital accumulation.

2.5 THEORIES OF EDUCATION AND ECONOMIC DEVELOPMENT

According to Adedeji S. O. and R. O Bamidele (2002), contemporary discussions

on education and economic development have been dominated by 3 main

theories, namely, the human capital, the modernization and the economic

dependence theories.

The Human Capital Theory

This theory emphasizes how education increases the productivity and efficiency

of workers y increasing the level of their cognitive skills. Theodore Schultz, Garry

Becker and Jacob Mincer introduced the notion that people invest in education to

increase their stock of human capital. The proponents see human capital as their

28

stock of economically productive human capabilities, which can be formed by

combining innate abilities with investments in human beings (Babalola 2000).

Examples of such investments include expenditures on education, on-the-job-

training, health and nutrition. Such expenditures increase future productive

capacity at the expense of current consumption. However, the stock of human

capital increases in a period only when gross investment exceeds depreciation

with the passage of time, with intense use or with lack of use.

The provision of education is seen as a productive investment in human capital,

an investment which the proponents of human capital theory considers to be

equally or even more equally worthwhile than that in physical capital. In fact,

contemporary knowledge in the United States acknowledges that investment in

human capital is three times better than that basic literacy enhances the

productivity of workers in low skill occupations. They further state that an

instruction that demands logical or analytical reasoning or provides technical and

specialized knowledge, increases the marginal productivity of workers in high

skill or professional positions. Moreover, the greater the provision of schooling

the greater the stock of human capital in society and, consequently, the greater the

increases in national productivity and economic growth.

The Modernization Theory

This theory focuses on how education transforms an individual’s value, belief and

behaviour. Exposure to modernizing institution, such as schools, factories and the

29

mass media, inculcates modern values and attitudes. These attitudes include

openness to new idea, independence from traditional authority, willingness to plan

and calculate future exigencies and a growing sense of personal and social

efficacy. According to modernization theorists, these normative and attitudinal

changes continues through out the life cycle, permanently altering an individual’s

relationship to the social structure. The greater the number of people exposed to

modernizing institutions the greater the level of individual modernity attained by

the society. Once a critical segment of the population changes in this way, the

pace of society’s modernization and economic development quickens. Thus,

educational expansion through its effects on individual values and benefits sets in

motion the necessary building blocks for a more productive work force and for a

sustained economic growth.

The Dependence Theory

This theory arose from Marxist conceptualizations based on the dynamics of the

world system that structure conditions for economic transformation in both the

core and periphery of the world economy. The proponents of this theory argue

that the prevalence of foreign investment capital, the presence of multinational

corporations, concentration on exporting of primary products and the dependence

on imported technologies and manufactured goods constrain long term economic

development. However, certain features of the world polity, such as state fiscal

strength, degrees and regime centralization and external political integration may

contribute to economic growth in the developing world.

30

Critics of these theories have, however, point to the evidence of widespread

unemployment and its negative impact on economic growth. It was also pointed

out that educated individuals with modern attitudes and values are causes of brain

drain with its deleterious impacts on the stock of trained personnel, potential

entrepreneurs and, consequently, on the rate of growth and development. It is not

surprising then that many people have become more cautious and skeptical about

the presumed positive economic impact of education.

2.6 HUMAN CAPITAL ACCUMULATION AND ECONOMIC

GROWTH

Modern empirical growth studies have expressed concern for the long run effect

of education on output. Human capital has long played a role in economic growth

theory (Lucas 1988).

Barro (1991), Mankiw, Romer and Weil (1992) found that enrolment rates are

important determinants of long run growth after controlling for initial output

changes in the enrolment rates may not affect the actual education levels for

years. On the contrary, some prominent studies such as those of Benhabib and

Spiegel (1994) and Pritchett (1996) find no relationship between growth rates of

education and growth rates of productivity after controlling for growth rates of

physical capital. They find that initial level of average education per worker is a

significant determinant of output growth.

31

2.7 OPERATIONAL DEFINITIONS

Education

Education has as many definitions as many writers in the field. In the perspectives

of indicators educators, education is the framework for social, economic

technological development. According to O’ Connell (1994) defines education as

the mechanism designed to bring about in the persons submitted to it, certain

skills and attitudes that are judged to be used and desirable in his society.

Education is a universal practice engaged in by society…it describes the total

process of human learning by which knowledge is imparted, faculties trained and

skills developed. It is a continuos process of growth and development in the

mental aspect of one’s being that influences every other aspect of one’s existence-

physical, social, economic and otherwise.

Nigeria’s formal education system is of three (3) main levels, the primary school

education, the secondary education and the tertiary education. In the former days

there had been basically two forms of education- traditional and Islamic. The

traditional education consisted of general and informal training in character,

intellectual and physical development which was the hallmark for the preservation

of socio-cultural values and norms.

The introduction of western education came in 1842 through the European

Christian religious missionaries. The southern and western regions embraced the

32

missionary activities more than the northern region. This can well account for the

yawning gap of educational inequality between the southern and northern regions.

Human Capital

This refers to productive investment in human persons. It includes skills, abilities,

ideals and health resulting from expenditures on education, on-the-job training

programs and medical care. This is as opposed to physical capital which are

tangible investment goods such as plants, equipment, machinery, buildings

Economic Growth

This is the steady process by which productive capacity of an economy is

increased over time to bring about rising levels of national output and income.

Labour Productivity

This is the level of output per unit of labour input, usually measured as output per

worker hour or worker year.

Open economy

This is an economy that encourages foreign trade and has extensive financial and

non-financial contacts with the rest of the world in areas such as education,

culture and technology.

33

Development

This is the process of improving the quality of all human lives. Three equally

important aspects of development are :

1. raising people’s living levels- their incomes and consumption levels of

food, medical services, education etc through relevant economic growth

processes;

2. creating conditions conducive for the growth of people’s self esteem

through the establishment of social, political and economic systems and

institutions that promote human dignity and respect; and

3. increasing people’s freedom by enlarging the range of their choice

variables, as by increasing varieties of consumer goods and services

Endogenous growth theory

An extension and modification of the traditional growth theory designed to

explain why long run equilibrium growth can be positive and divergent among

countries and why capital tends to flow from poor to rich countries despite the

former’s low capital-labour ratio.

Production Function

This refers to a technological relationship between the quantity of a good

produced and the quantity of inputs required to produce it.

34

Non-formal Education

This refers to any non-school based program that provides basic skills and

training to individuals. Examples include adult education, on-the-job training

programs and agricultural and other extension services.

Basic Education

This is the attainment of literacy, arithmetic competence and elementary

vocational skills

Public Good

This is an entity that provides benefits to all individuals simultaneously and

whose enjoyment by one person is in no way diminished by that of another.

Formal Educational System

This refers to the organized and accredited school system with licensed teachers

standard curricula, regular academic years and recognized certification. It

encompasses primary, secondary and tertiary educational institutions.

35

CHAPTER THREE

RESEARCH METHODOLOGY

INTRODUCTION

This comprise of the theoretical /analytical framework of the models, model

specification, estimation techniques, apriori expectation, definition of some of the

variables, criteria for decision making as well as the presentation of data.

3.1 THEORETICAL FRAMEWORK

There are several factors for consideration when seeking to promote economic

growth which include basic resources, land, labour, capital, human capital,

education, training and health and productivity.

Generally, speaking the neoclassical theory is built on a technological relationship

between output and production inputs as labour and capital and land. The Cobb-

Douglas production function is an empirical variant of this approach. As in

growth accounting the analysis is decomposed into the growth of labour, capital

and total factor productivity. When growth rates of output and capital are equal,

the rate of growth of output is determined by the rate of growth of labour force

and technological progress.

36

Summarily, Solow (1957) discovered that most of the growth in output was

explained by a linear trend in time which he termed “technical change” (“index of

our ignorance” in the words of Abramowitz and “the residual”

Taking a tow from the neoclassical viewpoint which is based on a technological

relationship between output and productive inputs such as we consider the

pioneering work of Solow and its extensions finds an empirical variant in the

Cobb-Douglas production function. Solow’s method of measure of the residual

and his estimate were criticized on many grounds; that the residual approach was

not of much use in understanding the growth process because it is based on the

concept of a stable production function and if there are very large shifts in it; his

approach was based on the unrealistic assumptions perfect competition, constant

returns to scale and complete homogeneity amongst other criticisms

As noted in Adamu (2002), the neoclassical theory which stated that changes in

the quantities of factor input account for growth (Solow 1957, Khan 1997, Iyoha

2000), thus, we consider the neoclassical production function

Y = F (A, K, L) ----------------------------------------------------------------- (1)

Where Y: Output

A: Level of technology

K: Physical capital stock

L: Quantity of labour

Differentiating the equation and dividing through and rearranging we obtain

37

∆Y = ∆A + Fk (AK) (K) + FL (AL) (L) ----------------------------------------- (2)Y A (Y) (K) (Y) (L)

Where

Y: Rate of growth of outputK

KK: Rate of growth of capital

LL: Rate of growth of labour

Fk, FL: Social marginal product of capital and labour respectively

∆A: Hicks neutral rate of change of the technical progressA

Accumulation of physical capital and an increase in the labour force with

improved technological embodiment causes growth to occur. Human capital is

considered to be the key determinant of labour productivity as it facilities the

absorption of new technology, increases the rate of innovativeness and promotes

efficient management

In several studies of sources of growth, Denison estimated the contribution of

difference resources with the help of a Cobb-Douglas type production function.

For instance, in calculating the contribution of education to output, Denison

treated workers of different educational categories as different inputs. In the index

he computed contribution of increases in output per unit of inputs comprised

38

advances in knowledge resource shift from agriculture to industry and economies

of scale.

Denison distinguished between advance in knowledge and education. Saying that

advance in knowledge is a technical change; the contribution of education

increases the quality of the labour force. He thus referred to advance in

knowledge as the true residual and education as guesstimated. In distinction from

the Solow’s approach, he attributes increases in growth to improvement in the

quality of labour force as a consequence of better and more education. Some of

his conclusions are said to be of doubtful worth. Thus, leaving the residual factor

in economic growth as the “coefficient of our ignorance”. (Jhingan 2003)

The Keynesian framework of analysis is based on the presumption that demand

drives the economic system while supply responds in tandem. The seminal work

of Kaldor (1967) on Verdoorn’s law which posits a correlation between output

and productivity growth, and also draws correlation between output and

productivity growth, and also draws affirmation from the export-led development

thought. Verdoorn’s law theorizes a virtuos circle between output and

productivity growth.

New growth studies interest birthed the influential articles of Lucas 1988 and

Romer 1986. They advanced an endogenous mechanism for the generation of

39

economic growth, a source of increasing returns associated with the accumulation

of human capital.

3.2 NATURE OF RESEARCH METHOD

The Ordinary Least Square method of estimation will be used to show the causal

relationship between education and economic growth. We preferred the Ordinary

Least Squares method for the following reasons.

1. The parameter estimates obtained by the OLS are optimal in nature.

2. The computation procedure is fairly simple as compared to other

econometric techniques.

3. The least square method has been used in a wide range of econometric

relationships with fairly satisfactory results.

4. The technique is simple to understand.

The computer statistical software Microfit 4.0 will be used in calculating the

Coefficient of Determination (R2), t- test, Durbin-Watson test for autocorrelation.

3.3 RESEARCH DESIGN

M odel Specification

Taking a cue from the work of Adamu (2002), which is based on the studies by

Odusola 1998, Grammy and Assane (1996), Mankiw, Romer, Weil (1992), we

specify our model in an attempt to determine the impact of human capital

40

formation (through investments in education) on economic growth and ultimately

on development in Nigeria.

Y = F (CED, RED, CAP, LAB,)

Where

Y: Real GDP as a proxy for economic growth

CED: Capital Expenditure on Education

RED: Recurrent Expenditure on Education

CAP: Physical Capital Formation proxied by Gross Capital Formation

LAB: Labour Force

F: Functional relationship

Investment in human capital (built up through education) is proxied by recurrent

and capital expenditure in education. The choice of this proxy is firmly supported

by the United Nations Development Programme 1996.

Linearizing the above functional form and stating it econometrically, we have

Y = α0 + α1CED + α2RED + α3CAP + α4LAB + U ------------------- (2)

The apriori expectations are α1, α2, α3, α4 > 0

Introduction of Variables, Definition of variables and Apriori Expectation

The following table gives a summary of the variables and their expected signs.

41

Table 1: Definition of Variables and Apriori Expectation

Variable Definition Expected Sign

Y

CED

RED

CAP

LA

Real Gross Domestic Product

Capital expenditure on education

Recurrent expenditure on

education

Physical Capital Formation

proxied by Gross Capital

Formation

Labour Force

(+)

(+)

(+)

(+)

3.4 DATA SOURCES

Secondary data was obtained and used for the study. Sources of Data include the

following Central Bank of Nigeria Statistical Bulletin (2004); Central Bank of

Nigeria: Economic and Financial Review (various issues); Central Bank of

Nigeria: Annual Reports and Statement of Accounts (various issues); Federal

Office of Statistics (2001); Journal articles; Textbooks; NES publications.

42

3.5 POPULATION AND SAMPLE DESIGN

The model for the study is estimated for the period 1970- 2004. Previous studies

stopped at 2000. This marks the point of difference of this study.

3.6 METHOD OF DATA PRESENTATION AND ANALYSIS

Criteria for Decision Making

This involves the various tests that will be carried out in order to drive

information from our data analysis.

1. Coefficient of Determination

2. Standard Error

3. Student t-test

4. Durbin-Watson test for Autocorrelation

5. F-Test

6. Regression Coefficient

1. Coefficient of Determination (R 2 )

This show the percentage of the total variation of the dependent variable that can

be explained by the independent variable(s). In other words, this shows the extent

to which the explanatory variable influences the dependent variable. In testing

this, high value of R2 depicts that the explanatory variable influences the

dependent variable to a high degree. The coefficient of determination is a measure

of the goodness of fit.

43

2. Standard Error

This is applicable in judging the statistical reliability of the estimate of the

regression coefficient. It provides a measure of the degree of confidence a

researcher can attribute to a parameter estimates. This test also helps us determine

whether or not our parameter estimates are significantly different from zero (0).

3. Student t- test

This also tests for the significance of our parameter estimates. In performing the

test, the following must be made about the model

- Define the null and alternative hypothesis

- Choose the desired level of significance (5%)

- Define the degree of freedom

Thus, we could now test the null hypothesis (Ho: b1=0) against the alternative

hypothesis, (Ha: b1≠0) in doing this, we compare the t- computed at n-k degree of

freedom with the t-generated from the table. We will be using 5% level of

significance in this study. If t- computed is greater that (>) t from table, we say

that our estimate of b1is significant and hence, we reject the null hypothesis and

accept the alternative hypothesis.

44

4. Durbin- Watson Test for Autocorrelation

This is a test for autocorrelation of our parameter estimate. However, this test is

appropriate only for the first order autoregressive scheme. In the test, we

formulated the null hypothesis;

Ho: b1=0 (Us are not autocorrelated with the first order scheme). This is tested

against the alternative hypothesis.

H1: b1≠ 0 (the Us are correlated with the first order scheme)

To test the null hypothesis using the D-W test, we could change H0: b=0 to H0:

d= 2 and that the values of “d” lies between 0 and 4. Hence, we could conclude on

the following ways.

If there is no autocorrelation, then d=2. Likewise if d= 0, we have a perfect

autocorrelation. However, if 0<d<2, then there is some degree of autocorrelation

(which is stronger if d is closer to zero). Also if d=4 there exist perfect negative

autocorrelation. And if d lies between 2 and 4, that is 2<d<4; there is some degree

of autocorrelation.

5. F- Test

The value of the F- statistics and its probability are used to test for the overall

significance of the model.

45

6 Signs and magnitude of regression coefficient

The signs (+ or -) must conform to the apriori expectations stated earlier. This is

important because decisions based on econometric analysis alone might be wrong

if it does not conform to economic theories.

46

CHAPTER FOUR

DATA ANALYSIS AND INTERPRETATION

INTRODUCTION

Having specified the model for this study in the preceding chapter, this chapter

focuses on the presentation, estimation and analysis of data and the interpretation

of results. To this end, section 4.1 focuses on the presentation of data used in the

study. In section 4.2, we present the Stationarity results. The regression

estimation result and interpretation is presented in section 4.3. Conclusively, we

subject the hypothesis earlier stated to test and discuss the main findings of the

study in section 4.4.

47

4.1 PRESENTATION OF DATA

TABLE 4.1: Data on Variables of the Study

YEAR Y C CED RED CAP LA1970 54148.9 1 3 3.2 *NONE* 22.351971 65707 1 4.2 4.4 *NONE* 22.9741972 69310.6 1 21.3 7.3 *NONE* 23.621973 73763.1 1 16.3 10.4 *NONE* 24.2911974 82424.8 1 134.4 62.5 *NONE* 24.991975 79988.5 1 631.1 218.9 19159.5 25.7211976 88854.3 1 529.2 522 27024.3 26.4781977 96098.5 1 255.8 248.3 28721.3 27.2711978 89020.9 1 431.9 394.7 24191.5 28.1021979 91910.7 1 206.7 360.4 19770.6 28.9731980 96186.6 1 729.4 509.1 21010 29.1711981 70395.9 1 217.2 712.8 17043.3 30.0981982 70243.1 1 412.4 511.8 1484.7 31.0671983 65958 1 367.2 588.8 95279.9 32.0691984 62474.2 1 87.6 657.9 5417 33.0871985 68286.4 1 126.2 697.9 5387.7 34.111986 70806.4 1 391.4 483.8 7215.5 35.1441987 71194.9 1 94.6 354.1 7016.5 35.3091988 77733.2 1 327.9 1458.8 6749.7 36.3461989 83179 1 387.5 3011.8 6955.8 37.4021990 92238.5 1 416.3 3402.8 10389.4 38.4811991 94235.3 1 297 1256.3 10541.6 39.5931992 97019.9 1 507.2 1907 10608.3 40.7541993 99604.2 1 995.1 6034.6 11716.8 41.9571994 100936.7 1 2051.9 3602.4 9493.1 43.2061995 103078.6 1 2426.4 9746.4 6098.8 44.5091996 106600.6 1 3215.7 11667 6785.5 45.8271997 109972.5 1 3808.2 12983.1 8067.6 47.1591998 113509 1 10579.3 14034.8 8050 48.5741999 116655.5 1 8576.6 23047.2 6186.9 502000 121207.8 1 10529.2 39034 6894.1 51.5322001 126323.8 1 19860 39884.6 8741.5 53.0782002 131489.8 1 9215 100240.2 9243.5 54.672003 136450 1 14680.2 64755.9 9662.8 56.312004 145380 1 9053.1 76527.7 10291.7 57.999

48

TABLE 4.2 Data After Correcting For Stationarity

YEAR DY CAP LA CED RED1970 NA NA NA NA NA1971 11558.1 NA 0.624 1.2 1.21972 3603.6 NA 0.646 17.1 2.91973 4452.5 NA 0.671 -5 3.11974 8661.7 NA 0.699 118.1 52.11975 -2436.3 19159.5 0.731 496.7 156.41976 8865.8 27024.3 0.757 -101.9 303.11977 7244.2 28721.3 0.793 -273.4 -273.71978 -7077.6 24191.5 0.831 176.1 146.41979 2889.8 19770.6 0.871 -225.2 -34.31980 4275.9 21010 0.198 522.7 148.71981 -25790.7 17043.3 0.927 -512.2 203.71982 -152.8 1484.7 0.969 195.2 -2011983 -4285.1 95279.9 1.002 -45.2 771984 -3483.8 5417 1.018 -279.6 69.11985 5812.2 5387.7 1.023 38.6 401986 2520 7215.5 1.034 265.2 -214.11987 388.5 7016.5 0.165 -296.8 -129.71988 6538.3 6749.7 1.037 233.3 1104.71989 5445.8 6955.8 1.056 59.6 15531990 9059.5 10389.4 1.079 28.8 3911991 1996.8 10541.6 1.112 -119.3 -2146.51992 2784.6 10608.3 1.161 210.2 650.71993 2584.3 11716.8 1.203 487.9 4127.61994 1332.5 9493.1 1.249 1056.8 -2432.21995 2141.9 6098.8 1.303 374.5 61441996 3522 6785.5 1.318 789.3 1920.61997 3371.9 8067.6 1.332 592.5 1316.11998 3536.5 8050 1.415 6771.1 1051.71999 3146.5 6186.9 1.426 -2002.7 9012.42000 4552.3 6894.1 1.532 1952.6 15986.82001 5116 8741.5 1.546 9330.8 850.62002 5166 9243.5 1.592 -10645 60355.62003 4960.2 9662.8 1.64 5465.2 -35484.32004 8930 10291.7 1.689 -5627.1 11771.8

4.2 PRE- ESTIMATION STATIONARITY TEST RESULTS

49

The regression analysis was based on time series data. The assumption upon

which estimation with time series data is based is that the time series data is

stationary. Formally, stationarity of time series can be checked by finding out if

the time series contains a unit root. The Dickey fuller and Augmented Dickey

Fuller are suitable for this purpose. However, in practice most economic time

series data are non- stationary. (Gujarati 1995)

To ascertain the validity of our estimation result, we first tested the underlying

assumption of stationarity of time series data. Most of time series data on the

variables used were stationary at first difference with only CAP, the proxy for

gross capital formation, which is stationary in levels.

Table 4.3: Stationarity Test Result

Variable Order of integration

DY I(1)*

CAP I(0)*

DCED I(1)*

CAP I(1)*

DRED I(1)*

*: Stationary at 10% level of significance

In seeking to estimate the variables, we found the first difference of all the variables

reflecting those which were stationary in levels and at order one (1). The data thus

50

generated was used in estimating our model. A summary of the results is featured in the

tables below.

4.3 REGRESSION RESULT

Table4.4: Regression Estimation Results

The Regressand is YRegressors Coefficients Standard Error T- Values (Probability)

Constant (C) -503.2238 4446.9 -0.11316 (0.911)

DCED 0.058012 0.53948 0.10753 (0.915)

DRED 0.030525 0.13522 0.22574 (0.823)

CAP -0.065930 0.076369 -0.86331 (0.396)

DLA 3127.4 3660.0 0.85449 (0.401)

R2 .08428

Adjusted R2 -0.63223

F 0.56889

D-W 2.0938

Where:

D: Differenced value of

Y: Real Gross Domestic Product (Real GDP)

CED: Capital Expenditure on Education

RED: Recurrent Expenditure on Education

CAP: Gross Capital Formation

51

LAB: Labour Force

It can be seen from the result presented in table 4.4 above that the explanatory

variables explain only about 8 percent of the variations in the dependent variable

and this does not connote a very good fit. Put differently, R2 is 8% indicating that

only 8% of the systematic variations in real GDP (Y) are accounted for by the

four variables taken together.

We also note that the Durbin Watson statistic is within an acceptable bound

(2.0938), this means that the result does not indicate the problem of serial

autocorrelation. The implication is that the regression result can be relied upon for

making any policy inference about the impact of education (human capital

investment) on the economic growth situation in Nigeria.

The Cochrane Orcutt method was adopted and the model was re-estimated to

correct for some variations. Table 4.5 below shows the final regression result

obtained using the data for the period 1970-2004.

Table 4.5: Estimation Results using Cochrane Orcutt Method

The Regressand is Y

52

Regressors Coefficients Standard Error T- Values (Probability)

Constant (C) - 9528.2 3240.9 -2.9400 (0.007)

CED 0.097989 0.12836 0.76342 (0.452)

RED 0.033437 0.027938 1.1968 (0.243)

CAP -0.090882 0.025929 -3.5051 (0.002)

LA 11250.1 2158.6 5.2118 (0.000)

R2 0.88875

Adjusted R2 0.74041

F 5.9913

D-W 2.1264

We obtained an improved result with the use of the Cochrane Orcutt method of

estimation. Broadly, the results obtained from the equation estimated show that

the model is well behaved and the explanatory variable explains about 88% of the

variation in the dependent variable. This is adjudged by the value of the R2. Also,

the result indicates no serial autocorrelation problems as evident in value of the

D-W statistics.

Our variable of interest is education proxied by recurrent and capital expenditure

on education. The table shows the existence of a positive relationship between

economic growth (proxied by real gross domestic product) and investment in

education.

Table 4.5 indicates that with the use of the Cochrane Orcutt method, the

coefficient of determination, that is, R-square value is over 88 percent. This

53

connotes that only about 12 percent of the dependent is not accounted for by the

Regressors.

The Durbin-Watson statistic of 2.1264 is close to the conventional point (that is,

2) thereby ridding the regression of the problem of autocorrelation.

The F- statistics and its probability indicates that the model has a good fit.

To detect the impact of education on economic growth in Nigeria we examine

whether the coefficient of recurrent and capital expenditure on education in Table

4 has the right sign and is statistically significant at the 5 percent level.

Consequently, we conclude that increased investment in human capital can lead

the economic growth in Nigeria.

It is evident from the table of reference (Table 4.5) that the capital and recurrent

expenditure possesses the right (positive) sign but neither of them is statistically

significant at the 5 percent level. Increased investment in education cum greater

labour productivity can serve to improve the economic growth situation of the

nation.

The table shows that a positive relationship exists between labour force and the

proxy for economic growth. However, gross capital formation failed to fulfill the

apriori expectation with its negative sign (instead of a positive sign). Despite this

54

result, it is common knowledge fact that investment in physical capital and human

capital are vital to the advancement of the economy.

This regression result mirrors the fact that there is a positive and significant

relationship between education and economic growth in Nigeria. Increased

investment in education, by the promotion of human capital, improves the quality

of the human resources of a nation and promotes labour productivity, which is a

vital factor for growth.

The implication of this finding is that the null hypothesis earlier formulated has to

be rejected. This means that education has a positive impact on the economic

growth situation and ultimately the development of the country.

4.4 TEST OF HYPOTHESIS AND DISCUSSION OF RESULT

Test of Hypothesis

In the statement of hypothesis earlier in this study, we specified the null

hypothesis that education does not have any significant impact on economic

growth in a developing country like Nigeria.

To test this hypothesis, we examine the t-ratio of the estimated model. If the

coefficient of capital and recurrent expenditure on education by the government in

the better regression result (that is, Table 4) is statistically significant, we reject

the null hypothesis and accept an alternative hypothesis that education impacts

positively on economic growth.

55

A quick glance at Table 4 reveals that neither of the coefficients of capital and

recurrent expenditure on education is statistically significant at the 5 percent

level; the t-ratio of capital expenditure stood at 0.76342 with a probability value

of 0.452. Also, the recurrent expenditure t- ratio was 1.1968 with a probability

value of 0.243. This implies that there is no statistically significant relationship

between education expenditure and gross domestic product in Nigeria.

From the table all the variables, except the gross capital formation, conform to

apriori specification in that they carry the right signs, but they are not all

statistically significant both at the 5 percent level and at the 10 percent level. Only

the labour force and the capital formation variables are statistically significant.

Discussion of Result

Overall, the result of this study has indicated that investment in education as a

part of human capital and improved quantity and quality of labour can serve as a

stimulant of growth in Nigeria. The influence of education on economic growth

is a circle of causation. Education increases the quantity and quality of labour

force. It leads to the upgrading of skill of manpower and the techniques of

production, which in turn raises the national labour productivity level. The

productivity level of labour increases national output and effects an upgrade in

living standards. A poor education system will produce an economy with weak

absorptive capacity to technological knowledge and information; this will prevent

investment from producing positive trickle down effects in a recipient (open)

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economy. We find that education influences growth through its effect on labour

more than it does as a factor input.

We find that the relationship between either of government recurrent expenditure

or capital expenditure on education is positive. The implication of this is that

increased investment in human capital holds a possibility of continuos growth for

the economy.

CHAPTER FIVE

SUMMARY, RECOMMENDATIONS AND CONCLUSION

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5.1 SUMMARY

The study explored the association between education and economic growth and

development. We have attempted to establish the relationship between education

and economic growth and development. We used the ordinary least square

technique to estimate our specified model. Our results have shown that investment

in human capital, investment in education and training can surely lead to

economic growth because of its impact on labour productivity and implicitly on

the degree of openness to new knowledge for the advancement of the human

resource and physical endowment of the nation. Returns on investment from

education can only be maximized with the appropriate kind and quality of

education and training.

5.2 RECOMMENDATION: ISSUES FOR CONSIDERATION

Education and unemployment

There is a skill gap that hampers job creation. The manpower producers are

insensitive to the labour market requirements. For instance, graduates get out of

the learning institutions only to find out that they do not have the requisite skills

for the available job positions. There is need therefore for the restructuring of the

education system for curricula that enhances knowledge, productivity and

inventiveness for a better life. Life applicable education is relevant for the

development of our society. There needs to be a constructive collaboration of the

manpower planners, producers and employers of labour.

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Lack of good education and unemployment contributes immensely to many social

ills including crime, prostitution and the breakdown of law and order. The society

should invest more on the youths and educate them to differentiate rights from

wrong. There should therefore adoptions that are requisite for the eradication of

corrupt social values.

Societal Definition of education

Education perspectives of any society needs to be defined in consonance with the

requirements of the society at the point in time. In Plato’s republic, education was

for the preservation of society. The Romans in their definition of education

intended to prepare the individual for governance. The element of character and

morality training in the Greek curriculum was significant because its products

were intended for democracy. We must define the purpose of education in the

Nigerian society. It is common knowledge that the bane of our development is

leadership at all levels. Thus, the education should be restructured to equip the

individual members of society with perspectives that will lead to the

transformation of our society.

The British system of education which we have adopted prepare the graduate for

the public work life. But for a country like ours that is in dire need of

development graduates and indeed pupils at various institutions of learning should

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be infused with the entrepreneurial mind. This will enable the promotion of small

scale industries towards economic advancement.

Quality of Education

The standards of education have been noted to fall since the 1980s. The returns

(public and private) to education have been low due to the high rate of

unemployment. The quality of education is hampered by lack of materials,

technical facilities, physical infrastructure, buildings, learning resources, and

computers. The emphasis on certification is the bane of all forms of corruption all

in the bid to acquire certificates. There needs to be a shift to focus on

contribution-targeted training for education recipients.

Government and Expenditure on Education

The expenditure on education is inadequate compared to international

benchmarks and the performance of other countries. Education is a public good;

the government needs to understand that people are at the heart of development

and thus prioritize their budget. Public expenditure disbursed should be properly

channeled to meet education needs. Incentives should be given to encourage more

private sector participation in education to raise enrolment and equip the populace

with skills and tools for personal and national development. Education should be

used to promote nationalistic perspectives in the members of the society.

Gender and Education

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There is a high rate of attrition among the female members of the population at

the primary and secondary levels than among their male counterparts. The reasons

why girls drop out of school are numerous; for economic contribution reasons

such as hawking (child labour), incapacitation of parents, early marriage and

teenage pregnancies, care of younger siblings. According to the UNDP (2000)

data for 1998 men recorded higher adult literacy rates than women in most

African states. Plato contends that women ought to share, as far a possible in

education and in other ways with men. He according laments that when women

do not get the same education as men the state is halved instead of being whole.

(Okonjo 2000).

Education is regarded as the cornerstone of women’s empowerment because it

enables them to respond to opportunities, to challenge their traditional roles and to

change their lives. This was reiterated in the Human Development Report

(UNDP, 1997) which stressed that an important strategy for empowering women

is to promote their access to education. In consonance the World Conference on

Education for All held in Jomtien, Thailand in 1991, drew attention to the gender

gap in educational opportunity and its consequences the human development.

(Okojie C.E.E 2002). Increased efforts towards promoting the education of girl

child should be embarked upon.

Perspective of Education

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The perspectives should change towards education. Education should be viewed

as the base for continuos self development. Education should go beyond

schooling; it should be seen as a tool for developing the human potential.

Omolewa (undated) stated the discovery that in the preliterate society education

was known to bring out the innate potential of an individual and enable such

individual to improve personal productivity. The achievement of full potential

inevitably contributes to the advancement of a community, region and nation. The

individual should therefore see education as a process of life long learning that

promotes the maximization of potential for the enhancement of societal values

and status.

Education and Globalisation

The world is becoming a global village with the increased possibility of linkages

between countries for transmission of information and technology. No nation can

possible grow without a strong educational and technological base. This is owing

to the fact that all knowledge that have resulted in technological breakthroughs

have emanated form the educational sector. The impact of education on economic

growth and development is indeed cyclical. Education causes the society to

embraces ‘openness’ which commands a flow of technology from the developed

Sountries to the developing countries. With the global economy getting more

technologically-oriented, requisite equipment with new knowledge and upgrading

of skills becomes necessary. The government and private sector educationists

should invest more in research and development activities.

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5.3 CONCLUSION

From our analysis there is strong evidence for the effect of labour on economic

growth. We can conclude in consonance with Datta (undated) that education

augments cognitive and other skills which in turn augments the productivity of

labour. This is also aligned with the findings of Romer and Weil (1992) that the

initial level of education per worker is a significant determinant of output growth.

We can conclude with the various analyses done in research on this field that

investment in education at all levels matter for development. Primary education

will help impart literacy and numeracy skills in the individual that sets the pace

for openness to knowledge at higher levels of learning. It could also help to

prevent the damaging effects of early marriage on the population. Secondary

education in addition to imparting cognitive skills could equip with vital

information for charting a career path. Higher education is essential for enhancing

openness to new knowledge, the development of the knowledge economy and the

equipment for the development of the industrial economy.

Suggestions for further research

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The recurrent and capital expenditure on education fulfilled the apriori

expectation but were statistically insignificant. Further research in this field could

combine the two expenditures and estimate as total government expenditure on

education, this could push for a better result of significance. Also, indicators of

literacy rate, student enrolment and teacher- student ratio could be computed to

capture the quality of education.

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