ROLE OF HUMAN CAPITAL IN ECONOMIC DEVELOPMENT: AN EMPIRICAL STUDY OF NIGERIAN CASE By Risikat Oladoyin S. Dauda, Ph. D Department of Economics University of Lagos Akoka, Lagos E-mail: [email protected] com [email protected] edu. ng ABSTRACT Although several theories of endogenous growth point towards a positive effect of human capital on growth, empirical evidence on this issue has been mixed. Despite various efforts of the successive Nigerian governments, virtually all indices of human development especially those of health and education are embarrassingly low.

These indices include infant and maternal mortality rates, life expectancy at birth, population per physician, adult literacy rate, gross primary and secondary enrolment ratio. In the same vein, the level of resource commitments to health and education compare very unfavourably with the situation in other developing countries. Using the human capital model of endogenous growth developed by Mankiw, Romer and Weil (1992), this paper examines empirically the role of human capital in Nigeria’s economic development.

The paper employed a variety of analytical tools, including unit root tests, cointegration tests and error correction mechanism (ECM). Empirical results indicate that there is, indeed a long-run relationship among labour force, physical capital investment proxied by real gross domestic capital formation, human capital formation, proxied by enrollment in educational institutions and economic growth in Nigeria. Findings show that there is a feedback mechanism between human capital formation and economic growth in Nigeria.

Thus, the policy implication of the findings is that government should place a high priority on human capital development. Efforts should be intensified to increase investment in human capital to achieve the growth which would engender economic development. Most importantly, education should be given prominence in Nigeria’s developmental efforts. This would propel the economy to higher levels of productivity. 1. INTRODUCTION The role of human capital in economic growth cannot be overemphasized.

The development of human capital has been recognized by economists to be a key prerequisite for a country’s socio-economic and political transformation. Among the generally agreed causal factors responsible for the impressive performance of the economy of most of the developed and the newly industrializing countries is an impressive commitment to human capital formation (Adedeji and Bamidele, 2003; World Bank, 1995, Barro, 1991). This has been largely achieved through increased knowledge, skills and capabilities acquired through education and training by all the people of these countries.

It has been stressed that the differences in the level of socio-economic development across nations is attributed not so much to natural resources and endowments and the stock of physical capital but to the quality and quantity of human resources. According to Oladeji and Adebayo (1996), human resources are a critical variable in the growth process and worthy of development. They are not only means but, more importantly, the ends that must be served to achieve economic progress. This is underscored by Harbinson (1973) who opined that “human 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 country 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”. Nigeria’s overarching objective since independence in 1960 has been to achieve stability, material prosperity, peace and social progress.

However, this has been hampered as a result of internal problems. These include inadequate human development, primitive agricultural practices, weak infrastructure, uninspiring growth of the manufacturing sector, a poor policy and regulatory environment and mis-management and misuse of resources. In order to ensure the economy delivers on its potentials, the country experimented with two development philosophies-a private sector-led growth in which the private sector served as the “engine house” of the economy and a public sector – driven growth in which the government assumed the “commanding heights” of the economy.

The initial low level of private sector development, however, led to public sector dominance of the economy, encouraged by growth in the oil sector (UNDP, 2009). It is noteworthy that since the advent of civilian rule in 1999, growth performance has improved significantly. The last seven years witnessed an average growth rate of about 6 percent (UNDP, 2009:5; CBN, 2008). However, economic growth has not resulted in appreciable decline in unemployment and poverty prevalence.

Human development has remained unimpressive as shown by the indicators in Table 1. Over the years, successive Nigerian governments recognized the importance of human capital formation in the development process and have embarked on various programmes and projects which led to the establishment of educational institutions and health centres throughout the country. However, in the late 1970s and early 1980s, federal government spending grew substantially resulting in fiscal crisis, inflation, and heavy borrowings.

Subsequently, through the austerity measures adopted in 1982 and structural adjustment programme introduced in 1986, the country attempted to bring down fiscal deficits as part of its stabilization and adjustment programmes, often by reducing public spending on across-the board basis. These reductions resulted in unprecedented economic and social costs as human resources development was neglected with adverse long-term development consequences (Oyinlola and Adam, 2003). Thus, the ultimate goal of economic development which underscored the need to improve the well-being of people was overlooked.

Table 1: Nigeria’s Human Development Summary Statistics by Zones, 2008 |Zones |Human Development Index |Human Poverty |Gender Development |Gender Empowerment |Inequality Measure | | |(HDI Value) |Index (HPI) |Measure (GDM) |Measure (GEM) |(INQ) | |North Central |0. 490 |34. 65 |0. 478 |0. 244 |0. 49 | |North West |0. 420 |44. 15 |0. 376 |0. 17 |0. 44 | |North East |0. 322 |48. 90 |0. 250 |0. 118 |0. 42 | |South West |0. 523 |21. 50 |0. 507 |0. 285 |0. 48 | |South East |0. 471 |26. 07 |0. 455 |0. 315 |0. 38 | |South South |0. 573 |26. 61 |0. 575 |0. 51 |0. 41 | Source: UNDP (2009:5) Summary: Human Development Report Nigeria 2008-2009, UNDP, Abuja In more recent times, renewed attention was paid to the role of human capital formation in the country’s development process and this has prompted the federal government to declare in its 1999-2003 economic policy programme that “the economy exists for and belongs to the people, and at all times the general well-being of all the people shall be the overriding objectives of the government and the proper measure of performance” (FGN, 1999).

This policy statement of the government is further reiterated in the National Economic Empowerment and Development Strategy (NEEDS). The provision of high-quality education and health care to all the country’s citizens is considered a key element of public policy by all levels of government. Against the above background, the aim of this study is to examine the impact of human capital formation on economic growth in Nigeria between 1977 and 2006 and on the basis of the findings, recommend policies and measures for improving human capital formation in the country.

Following the introduction, section two presents a review of relevant literature while section three outlines the analytical framework and the model. Section four discusses the empirical results and section five concludes the paper. 2. Literature review Human capital has been defined in various ways. For the purpose of this study, the general definition given by the United Nations Economic Commission for Africa (1990) is considered.

The concept of human capital refers to the knowledge, skills, attitudes, physical and managerial effort required to manipulate capital, technology, and land among other things, to produce goods and services for human consumption (UNECA, 1990). Human capital formation, on the other hand, refers to the process of acquiring and increasing the number of persons who have the skills, education and experience that are critical for the sustainable growth and development of a country.

The economic benefits of human capital formation arise from making people more productive by improving their nutrition, health, education and other social indices through adequate and proper investments. According to Okojie (1995) human capital formation is associated with investment in man and his development as a creative and productive person. It is a continuum, a continuing process from childhood to old age, and a must for any society or enterprise that desires to survive under the complex challenges of a dynamic world. Schultz (1961) in his work identified strategies for human resource development.

These include the following: (i) investment in health facilities and services, broadly conceived to include all expenditure that affect the life expectancy, strength and stamina, and the vigour and vitality of the people; (ii) on-the-job training, including old-type apprenticeships organization by firms; (iii) formally organized education at the elementary, secondary and higher levels; (iv) study programme for adults that are not organized by firms, including extension programmes notably in agriculture; (v) migration of individuals and families to adjust to changing job opportunities development.

In line with this, Meier (1970) opines that human resource development concerns the two-fold objective of building skills and providing productive employment for non-utilized or underutilized manpower. Both stem from investment in man in the form of education and training which are known to be institutional mechanisms for enhancing people’s knowledge, skills and capabilities. Several studies have attempted to investigate the relationship between human capital and economic growth and these studies have shown mixed results.

In his study of 98 countries between 1960 and 1985, Barro (1991) using school enrolment rates as proxies for human capital found that the growth rate of real per capita is positively related to initial human capital proxied by 1960 school enrolment rates. Mankiw, Romer and Weil (1992), augmenting the Solow’s growth model, empirically show that the effects of saving or investment and population growth rates are biased upward whenever human capital formation is excluded. Their model explains nearly 80 percent of the cross-country variation in per capita income, which is about 30 percent larger than when human capital is excluded.

For the categories of countries, (low-income, intermediate and OECD countries), investment in human capital substantially influenced per capita income at 1 percent level of significance. Similarly, Burnett et al (1995) show that massive investment in both primary and lower secondary school significantly explained the development ‘miracle’ experienced in East Asia. Grammy and Assane (1996), using varied forms of human capital investment, such as school enrolment, human development and economic liberty index evidently pointed out that human capital formation propels growth in per capita income.

Its positive contribution to growth was statistically significant at 1 percent. Besides, the inclusion of the variable reduces the bias often associated with growth models that exclude human capital investment and, hence, the explanatory power of the model. In contrast, Benhabib and Spiegel (1994) employed a standard growth accounting framework to study the contribution of human capital to economic growth, they found a negative relationship between initial per capita income and growth.

Similarly, Pritchett (2001) found a negative impact of education on growth. There are large numbers of empirical studies that confirm the strong association between health and economic growth. For instance, Blooms and Sachs (1998), as cited in Hamoudi and Sachs (1999), provided empirical evidence on the relationship between health variables and economic growth rates and found that health variables play a significant role in determining economic growth rates.

They showed this by investigating cross-country data between 1965 and 1990, using a basic growth model, and they found that an increase of life expectancy by one percent accounted for an acceleration of GDP per capita growth by over 3% per annum. In addition, health and demographic variables explained over half of the differences in growth rates between Africa and the rest of the world over that same period. There are also various studies that address the important issue of gender dimension in human capital investment. For instance, Lagerlof (1999) xamines the impact of gender inequality in education on fertility and economic growth. Using an overlapping generation framework, the paper argues that initial gender inequality in education can lead to a self perpetuating equilibrium of continued gender inequality, with the consequences of high fertility and low economic growth. In the same vein, Schultz (1994) also argues that reducing gender inequality through access to education and the labour market will help reduce poverty, thereby increasing the rate of economic growth..

Ramirez, Ranis, & Stewart (1997) explored two way linkages between economic growth and human development empirically with the help of cross-country statistics. The study argues that public expenditures on health and education represent especially important links in determining the strength of the relationship between economic growth and human development. Two chains namely, economic growth to human development and from human development to economic growth can generate self-reinforcing, vicious cycles of development, as well as identifying lop-sided performers.

The study finds that over time lop-sided development rarely carry on: countries initially in favour of economic growth lapse into the vicious category. Hence, even though both human development and economic growth should be encouraged together, human development should be given first priority. Mustafa, Abbas, & Saeed (2005) emphasized the role of human resource development and vocational training for economic growth in Pakistan. The study reviewed and analyzed the status of vocational training, related policies and practices and their impact on development of human resource.

The effect of the rate and variability of increase in institutions, enrolment and teachers on output growth variability was also explored. As the fluctuations in rate and variability of vocational indicators have serious implications for the output growth variability hence, the output growth variability was regressed on the rate and variability of the institutions, enrolment, and teachers, to find out the growth and the variability impact of the vocational indicators on the output growth variability. The analysis of the impact of vocational indicators indicates that the long term planning is required to achieve the benefits of urrent policies. There is positive and significant relationship between the growth of institutions and output growth variability moreover; enrolment and teachers also play a significant role in determining the output growth variability. On the whole analysis shows that both the rate and variability of vocational indicators have positive and mostly significant impact on the output growth variability in the long run. Abbas (2001) analyzed the impacts of human capital on economics growth for Pakistan and Sri lanka.

The results of empirical analysis show that primary schooling enrolment rates has negative while secondary and higher schooling enrolment rates has positive and significant impact on economic growth for both countries in the sample. The study has also combined the schooling enrolment rates at different levels of education with employment to generate effective labour input that performed better as compared to simple schooling enrolment rates and it is again concluded that there are important growth effects associated with human capital.

In Nigeria, several studies have emerged in an attempt to provide quantitative evidence to the growth-human capital nexus. Akangbou (1983) and Mbanefoh (1980) determine the social and private returns to the different levels of education-primary, secondary and university, using cross-sectional data. On the basis of the positive rate of returns often computed, inference is made about the positive role of human capital on economic growth.

Odusola (1998) using ordinary least square technique found that human capital, proxied by real capital and recurrent expenditure on education, is positively related to growth, although the relationship is weak. The Nigerian Economic Society held a conference on human resource development in Africa in Nigeria in 2002 and several interesting papers were presented. Some of the papers showed a positive and significant contribution of human capital to economic growth (Adamu, 2003; Uwatt, 2003; Chete and Adeoye, 2003).

Adamu (2003) undertook an empirical investigation to determine the impact of human capital formation on economic growth in Nigeria between 1970 and 2000, using cointegration and error-correction mechanisms. The results indicate that investment in human capital in the form of education and training can lead to economic growth because of its impact on labour productivity. Chete and Adeoye (2003) explored the association between human capital investment and economic growth in Nigeria. A number of methodological approaches were employed to examine this link.

Specifically, the Granger causality tests were inconclusive on the direction of causality. The variance decomposition analysis shows that “own shocks” constitute the predominant source of variation in employment growth’s forecast errors and income growth’s forecast errors, and that innovations of employment growth can be better predictors of income growth. The impulse response analysis reveals that there are considerable oscillations in the response patterns of income and employment to unanticipated shocks in each other.

The paper observed a mismatch between the manpower needs of the country and the skills turned out by the educational system. Uwatt (2003) provided empirical evidence on the role of human resource development proxied by enrolment in educational institutions on economic growth in Nigeria, using the augmented Solow growth model and relying on cointegration and error-correction methodology. The results showed that human resource development does not only contribute positively to economic growth in Nigeria, but its impact is strong and statistically significant.

This occurs despite the decline in the quality of education at all levels since the mid 1980s. Contrary to the conventional wisdom, Ayara’s (2003) study observed that the growth of educational capital shows a significant negative effect on economic growth in Nigeria. This is in line with the studies by Pritchett (2001), Islam (1995) and Hoeffler (1999). Could this be interpreted to mean that educational investment is harmful to growth in Nigeria? Due caution must be exercised in interpreting the result. However, several factors might be responsible for this.

Some possible explanations offered by the Pritchett (2001) and Ayara (2003) include the following; (i) existence of brain drain; (ii) the newly created educational capital might have gone into privacy that is, privately remunerative but socially unproductive activities; (iii) incessant strike actions by the academic and non-academic staff of Nigerian universities; (iv) failure of the educational system to provide qualified manpower that would enhance productivity growth; (v) there may be slow growth in the demand for educated labour, so that the supply of educational capital has utstripped demand and returns to schooling have declined. 3. Analytical Framework and the Model. An endogenous model of economic growth appears to be the most suitable for the study. The model suggests that endogenous factors such as government policies, political stability, market distortions, human capital etc. , can significantly affect economic growth. It is a widely used growth model to provide a systemic investigation of the human capital-economic growth nexus. For example, Uwatt (2003) and Adamu (2003) used it to assess the role of human capital in the Nigerian economy.

This study is different from previous studies in terms of the analytical tools used. Also, the data used is extended to 2006. The framework for this study is adapted from Adamu (2003). It assumes a standard neoclassical production function which begins from a premise that changes in quantities of factors of production account for growth. The neo-classical model is based on the Cobb-Douglas function and is given as: Y= F (A, K, L) ———————————————————————– (1) Where Y, K, L are aggregate real output, capital and labour respectively, and A denotes technical progress or total factor productivity.

When we differentiate equation (1) with respect to time, divide by Y and rearrange the terms, it gives equation (2) as: [pic]- – – – – – – – – – – – – – – – – – – (2) Where; Y/K = Rate of growth of output; K/K= Rate of growth of capital; L/L= Rate of growth of labour force. FK FL = Social marginal product of capital and labour respectively; (A/A= Hicks neutral rate of change of technological progress. Modern economic growth depends on the accumulation of physical capital and an increase in labour force with improved technological embodiment without which labour cannot be effective.

Human capital is a factor influencing labour productivity because it facilitates the absorption of new technology, increases the rate of innovativeness and promotes efficient management (Adamu, 2000). Consequently, for high labour productivity, an integral part of technological progress is investment in human capital and thus is termed endogenous factor because accumulation of physical capital is enhanced by the knowledge, skills, attitudes and health status of the people who partake in such exercise. Thus, there is a strong and positive relationship between investment in human capital and output growth.

In this regard, several studies have attempted to integrate exogenous forces with endogenous factors in explaining economic growth across countries by using augmented Solow neoclassical production function. These studies include but not limited to the following; Romer (1990), Mankiw, Romer and Weil (1992), Gemmell (1996), Grammy and Assane (1996) and Chete and Adeoye (2003). Generally, the impact of human capital on economic growth is incorporated according to the Mankiw, Romer and Weil (1992) framework and is given below as: Y(t) = K(t) ( H(t) ( (A (t) L(t ) )1-(-(————————————————-(3) Where;

Y is output; K = Physical capital and H = the Human Capital Stock; L=Labour force; A is level of technology and (,( ( 1, implying decreasing returns to capital. By implication, there is a strong and positive relationship between investment in human capital and output growth. Based on the literature reviewed earlier, the following model is specified to evaluate the impact of human capital formation on economic growth in Nigeria. RGDP = (GCF, LBF, PRI, SEC, TER)………………………………………… (4) Where RGDP = Real gross domestic product as a proxy for economic growth. GCF = Real gross capital formation LBF = Labour force.

PRI = Primary education enrollment SEC = Secondary education enrollment TER = Tertiary institution enrollment U = White noise For estimation purposes, we can re-specify equation (4) in a log-linear functional form: This will give: InRGDP =? 0+? 1InGCF+? 2InLBF+? 3InPRI+? 4InSEC+? 5InTER+U……………… (5) The a priori expectations are as follows: ?1, ? 2, ? 3, ? 4, ? 5, > 0 The equation was estimated using a variety of analytical tools, including unit root tests, co-integration tests and error correction mechanism (ECM). The results are discussed below. The data used for the study covers the period 1977 and 2006.

The study employed secondary data which are derived from various issues of CBN Annual Report and Statement of Accounts, CBN Statistical Bulletin and World Bank African Development Indicators. 4. Empirical Results 4. 1. Unit Roots Test It has been established in the literature that most time series variables are not stationary and using non-stationary variables in the model might lead to spurious regression which cannot be used for precise prediction. Hence, our first step is to examine the characteristics of the data in order to determine whether the variables have unit roots i. , whether it is stationary and the order of integration. For this purpose, the Augmented Dickey-Fuller test is used. A variable is stationary if the absolute ADF value is higher than any of the absolute Mackinnon values. The result of the stationarity test with intercept term is presented in Table 2. The results showed clearly that all the variables are non-stationary at level. This suggests the need to difference the series to obtain stationarity. At first difference, however, all the variables are stationary and are integrated of order 1.

Since all the variables are integrated of the same order, cointegration analysis is justified. 2. Cointegration test results Co-integration test is carried out in order to determine the long-run relationship between the dependent and independent variables when one or all of the variables is/are non-stationary at level which means they have stochastic trend. Essentially, it is used to check if the independent variables can predict the dependent variable both now (short-run) or in the future (long-run). The long –run relationship among the variables were examined using Johansen (1991) cointegration framework.

The result is presented in table 3. It revealed that there is cointegration among the variables. This is because the likelihood ratio value of 116. 0695 is greater than the critical value of 103. 18 at 1 percent level of significance. We reject the null hypothesis of none**of the hypothesized number of cointegrating equations. In the same vein, the likelihood ratio value of 71. 55996 is greater than the critical value of 68. 52 at 5 percent level of significance. We reject the null hypothesis of at most 1* of the hypothesized number of cointegrating equations. TABLE 2: RESULTS OF STATIONARITY (ADF UNIT ROOT) TEST VARIABLES |ADF TEST STATISTICS |CRITICAL VALUES (5%) |ORDER | | | | |OF INTEGRATION | | |LEVEL |1ST DIFFERENCE |LEVEL |1ST DIFFERENCE | | |LNRGDP |-0. 6319 |-5. 0659 |-2. 9705 |-2. 9750 |1(1) | |LNGCF |-0. 2715 |-3. 616 |2. 9705 |-2. 9750 |1(1) | |LNLBF |-1. 8501 |-4. 4125 |-2. 9705 |-2. 9750 |1(1) | |LNPRI |-0. 7957 |-3. 6520 |-2. 9705 |-2. 9750 |1(1) | |LNSEC |-2. 4085 |-4. 5318 |-2. 9705 |-2. 9750 |I(1) | |LNTER |-0. 7947 |-3. 3491 |2. 9705 |-2. 750 |1(1) | Source: Extracted From the Computer output. Accordingly, the likelihood ratio (LR) test indicates 2 cointegrating equations at 1and 5 percent level of significance respectively. For the remaining number of hypothesized cointegrating equations (at most 2, 3,4 and 5), we do not reject the null hypothesis as their likelihood ratio values are less than the critical values at 5 percent level of significance. The main conclusion is that there is the existence of long-run relationships amongst the variables. The variables may wander away from themselves, but in he long-run, there is the existence of relationship amongst them. TABLE 3: JOHANSEN COINTEGRATION TEST Eigenvalue Likelihood 5 percent 1percent Hypothesized Ratio Critical value Critical value No of CE(s) 0. 795998116. 0695 94. 15103. 18None ** 0. 62941871. 55996 68. 5276. 07At most 1* 0. 54983443. 76491 47. 2154. 46At most2 0. 36090121. 41703 29. 6835. 65At most 3 0. 2118908. 881563 15. 4120. 04At most 4 0. 0760352. 214281 3. 766. 65At most 5 *(**) denotes rejection of the hypothesis at 5% (1%) significance level. L. R. test indicates 2 cointegrating equations(s) at 5% significance level.

Source: Author’s Computations 4. 3EMPIRICAL RESULTS OF THE DYNAMIC MODEL (ECM) Although long-run equilibrium relationship may occur among variables in the regression model, short-run equilibrium may not occur. Error correction mechanism is therefore used to correct or eliminate the discrepancy that occurs in the short-run. The coefficient of error-correction variable gives the percentage of the discrepancy between the variables that can be eliminated in the next time period. The coefficients of the explanatory variables in the error correction model measure the short-run relationship.

When conducting error correction technique, an overparameterized model is usually expressed to deal with the problem of misspecification in the model. This is followed by the parsimonious model, which is derived after some stepwise elimination of relatively insignificant parameters in the overparameterized model. The results from the overparameterized model are presented in Table 4. The parsimonious model is obtained from a stepwise elimination of insignificant dynamic variables until parsimony is obtained; the result of this process is given in table 5.

From Table 5, it is revealed that a physical capital formation proxied by real gross fixed capital formation has a positive and significant relationship with real gross domestic product. Its coefficient is statistically different from zero at 5 percent level. The empirical results show that the coefficient of labour force (LBF) is positive in compliance with the theoretical expectation and also statistically significant at 5 percent level. The variable denoting human capital components i. e. school enrolments at the primary, secondary, tertiary levels comply with the a priori expectations.

That is, they have positive coefficients. All the human capital variables except, primary school enrolment are significant. This is shocking but not unexpected. This result is supported by the work of Abbas (2001) who found that primary education made no significant impact on the economic growth of Pakistan and Sri Lanka. The reasons for the positive but not significant effect of primary education on economic growth performance in Nigeria are not far-fetched. This indicates that unskilled people, i. e people with low level of education has little or no capacity to increase productivity.

These people do not contribute significantly to economic growth because many engage in jobs that are often not accounted for in the national income. Besides, majority of these people dwell in the rural areas and opportunities given to them by way of loans by the government and financial institutions are often abused. The loans are collected and diverted to unprofitable use e. g. marrying more wives. By so doing, these unskilled people cannot contribute significantly to growth. To address this problem, policy measures must be put in place to ensure that those with primary education should also be encouraged to acquire secondary education.

The results, however confirmed the importance of human capital formation in Nigeria’s development process. The implication is that policy measures that are targeted at improving the educational human capital can effectively enhance national income. It is obvious from the coefficient of multiple determination (R2) that the model has a good fit as the independent variables were found to jointly explain 82 percent of the movement in the dependent variables. Gross fixed capital formations, labour force, school enrolment at the secondary and tertiary levels are the major determinants of real gross domestic product in Nigeria.

The fitness of the model is confirmed by the F-statistic which is significant at 1 percent. The error correction variable (ECM), which is minus 2. 2546, was highly significant validating the error correction model specification. This shows that a feedback of -2. 25 from the previous year’s disequilibrium from the long-run elasticity of the identified variables can determined economic growth. The strong significance of the ECM connotes the existence of a long-run equilibrium relationship between real gross domestic product and the factors affecting it.

Table 4: Modelling the impact of human capital on economic growth in Nigeria (A Dynamic Error Correction Model) – Overparameterized model Summary of the Result of the Estimation Equations Dependent variable: log of Real Gross Domestic Product (LNRGDP2) |INDEPEDENT VARIABLES |COEFFICIENT |STD. ERROR |T-STATISTIC |PROB. | |D(LNGCF, 2) |0. 870469 |0. 516510 |1. 685292 |0. 1262 | |D(LNGCF(-1),2) |0. 436771 |0. 13334 |1. 056701 |0. 3182 | |D(LNGCF(-2),2) |0. 250700 |0. 428129 |0. 585571 |0. 5726 | |D(LNLBF, 2) |0. 090755 |0. 079974 |1. 134801 |0. 2858 | |D(LNLBF(-1),2) |-0. 016950 |0. 081265 |-0. 208574 |0. 8394 | |D(LNLBF(-2),2) |0. 029262 |0. 076568 |0. 382175 |0. 112 | |D(LNTER, 2) |0. 508742 |0. 310977 |1. 635946 |0. 1363 | |D(LNTER(-1),2) |0. 091558 |0. 403566 |0. 226871 |0. 8256 | |D(LNTER(-2),2) |-0. 016605 |0. 350022 |-0. 047440 |0. 9632 | |D(LNSEC, 2) |1. 257007 |1. 039329 |1. 209441 |0. 2573 | |D(LNSEC(-1),2) |0. 41689 |1. 057491 |0. 417676 |0. 6860 | |D(LNSEC(-2),2) |-0. 022610 |0. 836841 |-0. 027018 |0. 9790 | |D(LNPRI, 2) |1. 173409 |0. 943805 |1. 243275 |0. 2452 | |D(LNPRI(-1),2) |0. 325717 |1. 101884 |0. 295598 |0. 7742 | |D(LNPRI(-2),2) |-0. 439730 |1. 076728 |-0. 408394 |0. 925 | |ECM (-1) |-2. 503907 |0. 525930 |-4. 760917 |0. 0010 | |C |-0. 051907 |0. 087026 |-0. 596456 |0. 5656 | R-Squared = 0. 837416 Adjusted R-Squared = 0. 548378 F-Statistic = 2. 897248 Prob (F- Statistic) = 0. 054770 Durbin – Watson Statistic = 1. 543159 Table 5: Modelling the impact of human capital on economic growth in Nigeria (A Dynamic Error Correction Model) – Parsimonious Model Summary of the Result of the Estimation Equations

Dependent variable: log of Real Gross Domestic Product (LNRGDP2) |INDEPEDENT VARIABLES |COEFFICIENT |STD. ERROR |T-STATISTIC |PROB. | |D(LNGCF, 2) |0. 766625 |0. 224611 |3. 413119 |0. 0028 | |D(LNLBF, 2) |0. 138746 |0. 040470 |3. 428414 |0. 0027 | |D(LNTER, 2) |0. 482038 |0. 193250 |2. 494367 |0. 215 | |D(LNSEC, 2) |1. 046394 |0. 468385 |2. 234046 |0. 0371 | |D(LNPRI, 2) |0. 827553 |0. 504533 |1. 640234 |0. 1166 | |ECM (-1) |-2. 254602 |0. 278936 |-8. 082880 |0. 0000 | |C |-0. 027514 |0. 066925 |-0. 411125 |0. 6854 | R-Squared = 0. 82

Adjusted R-Squared = 0. 76 F-Statistic = 14. 72 Prob (F- Statistic) = 0. 00 Durbin – Watson Statistic = 2. 04 * (**) Significant at 1% (5%) respectively Sources: Extract from Computer Output. 5Summary, Conclusion and Recommendations The paper has attempted to examine the relationship between human capital formation and economic growth in Nigeria. The human capital model of endogenous growth developed by Mankiw, Romer and Weil (1992) is used for the study. The paper employed a variety of analytical tools, including unit root tests, cointegration tests and error correction mechanism (ECM).

Empirical results indicate that there is, indeed a long-run relationship among labour force, physical capital investment proxied real gross domestic capital formation, human capital formation and economic growth in Nigeria All the variables appear with the expected positive signs. The variable denoting human capital components i. e. school enrolments at the primary, secondary, tertiary levels comply with the a priori expectations. That is, they have positive coefficients. All the human capital variables except, primary school enrolment are significant in economic growth and development.

It is evident that there is a feedback mechanism between human capital investment (at least on secondary and tertiary education) and the real gross domestic product in Nigeria. Thus, the policy implication of the findings is that government should place a high priority on human capital development. Efforts should be intensified to increase investment in human capital to achieve the growth which would engender economic development. Most importantly, education should be given prominence in Nigeria’s developmental efforts.

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