effort was made to select school curricula that would meet the long-run . to a positive relationship between education and economic growth. Although earlier. In the long run, however, higher education incentives may increase the rate of study showed that there was long-run relationship between economic growth. Keywords: education, economic growth, human capital, investment, skilled workers. important role to play in determining the long- run growth rate of a country's economy. .. Adenuga () examine the relationship between economic.
The results of their study suggests there is long run relationship between enrolments in primary and tertiary levels of education and the average years of schooling with output per week. Afzal et al used an autoregressive distributed lag ARDL model in Pakistan to confirm the existence of direct relationship between school education and economic growth both in the short-run and long- run.
Tamang applied Johansen co-integration test to support the presence of long run relationship between government spending on education and economic growth in India. On the other hand, Hussin et al used vector autoregressive regression VAR to show evidence of a positive relationship between economic growth proxy by GDP and fixed capital formation, labour force and government expenditure on education in Malaysia.
In contrast, there are some studies that either do not support the existence of long run relationship between government spending on education and economic growth or have revealed weak relationship. Obi and Obi found using Johansen co-integration that long run relationship does not exist over the period of and On the other hand, studies that reported weak relationship between education and economic growth include the work of Bils and KlenowPritchettBosworth et al For example, Bils and Klenow using a panel of 52 countries between to argued that it was too weak to conclude that education or school achievement significantly contributed to economic growth.
Bosworth et al assessed sources of growth to Indian economy; the authors concluded that education's contribution to India's economic growth has been negligible. Some other studies have also confirmed De Meulmester and Rochet recent arguments that the relationship between education and economic growth are not always positive.
This probably cannot be unconnected with the previous argument presented by Blaug and Sheehan that an investment in education is nothing but a mere consumption because investment in acquiring knowledge or skills is only for individual interest and does not contribute to economic growth.
In most cases, the empirical study conducted by Devarajan et al on panel of 43 developing countries is used by those in this line of argument to support their fact. In the Devarajan et al study, government expenditure on education is found to negatively correlate with economic growth. In addition, there are group of studies that found relationship between government expenditure on education and economic growth is either a one way process or a two way process.
The study established a bi-directional causality between investment in education and economic growth. The result of this study is contrary to an early study conducted by Pradhan that investigates the causality between public education spending and economic growth in India during to In that study, the author revealed there is unidirectional causality between education and economic growth in the Indian economy.
The direction of causality is from economic growth to education spending and not vice versa. Also Omojimite conducted both co-integration and Granger causality test to investigate whether there is strong relationship between public expenditure on education and economic growth in Nigeria using a time series data for the period of to The results revealed public expenditure Granger cause economic growth but the reverse is not the case.
The causality test also discovered that there is a bi-directional causality between public recurrent expenditures on education and economic growth.
In the result output, it was also reported that no causal relationship was established between capital expenditure on education and economic growth, as well as between primary school enrolment and economic growth. From the reviews of the empirical studies conducted in both developing countries and Nigeria, it is quite obvious that the relationship between government spending on education and economic growth is debatable.
Some might say it has positive effect and vice versa, but a thorough observation would show that the differences from the previous studies could arise from the type of methodology used, lack of harmonised data, the type of variables chosen, type of econometric specification used and other factors. The present study contributes to this debate by further revisiting robustness of an empirical evidence on the relationship between government spending on education and economic growth using both Johansen co-integration and vector error correction model VECM to estimate long run and short run dynamics between different types of government spending on education and economic growth in the case of Nigeria.
The study will also add to the debate on causality between disaggregated government spending on education and economic growth.
This is because even though regression analysis deals with dependence of one variable to other variables, it does not imply causation or direction of influence Omojimite, The study started by first testing for unit root to check for stationarity.
This is because standard errors produced using non-stationary variables would be biased. The implication of this is that the conventional criteria used to judge whether there is a causal relationship between the variables would be unreliable. In addition, if non-stationarity is ignored a significant relationship could be established when none really existed Granger and Newbold, Afterward, we test formally for the co-integration of the time series and finally, set up the appropriate Error Correction Model before we test for causality using Granger causality test.
These procedures however, raise several methodological issues that are treated individually in the following headings. Sources of Data collection The data used was generated entirely from secondary sources. All variables were transformed into natural logarithm form to reduce problem of heteroskedasticity Unit Root Test In order to obtain reliable model that captures the relationship between government spending on education and economic growth, a unit root test is employed to examine the time series properties of the variables to be used in the study.
This to large extent will enable us avoid the problems of spurious regression. ADF test has advantage over DF because it included extra lagged terms of the dependent variable in order to eliminate problems of autocorrelation. The following equation present the possible form of the ADF test: The test involves testing the following hypothesis: Therefore to know when to use the error correction model ECMone needs to test for the presence of co-integration.
Engle and Granger establish that co-integration exist if the residual of the OLS equation, ut contains a unit root.
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For our own purpose we will employ the pre-programmed Johansen co-integration test provided by the Eviews. And once co-integration among the variables has been established, the Error Correction Model which allows estimating the short run relationship between variables can be employed Engle and Granger, The Error Correction Model ECM The ECM corrects for shocks that drive the variables away from the long run trend, given the fact that for co-integrated non-stationary series, a suitable combination makes the series stationary.
For this it implies that ECM exploits the fact that an appropriate linear combination of co-integrated variables yields a stationary series to correct for temporary common deviations from the long term relationships between the two variables. With ECM therefore, we can transform co-integration from a source of error into an added tool for uncovering information. The error correction models of co-integration can therefore be specified as follows: Granger Causality Test The test is named after the first causality tests performed by Clive Granger in It analyses the extent to which the past variations of one variable explains or precede subsequent variations of another.
The test come in pairs, testing whether variable xt Granger causes variable yt and vice versa. Formally the Granger causality test analyses whether the unrestricted equation: Data and Variables We used an annual data of the variables from to which was sourced mainly from the Central Bank of Nigeria statistical data and the World Bank Development Indicators.
We therefore included in the model based on availability of data the following variables: In economic literature, the variable is usually used as a proxy to economic growth of a country. It is also a socio-economic indicator used in the measurement of growth of a nation CBN, 2. It refers to payment for non-financial assets in educational sector used in the production process for more than one year.
Extraction from estimation output using E-views 7 Note: This obviously implies, the variables are integrated of the same order I 1.
This further suggests there is need to test for co-integration in order to see whether there is long run relationship among the first order integrated variables. Thus, we can reject the null hypothesis that there is no co-integration in the data and conclude that there is long run relationship between GDP, capital and recurrent government expenditure on education in Nigeria.
Extraction from estimation output using E-views 7 From the normalized co-integration we can see that there is a positive relationship between GDP as a proxy of economic growth and education expenditure. The result specifically shows that a one unit change in capital expenditure on education will account for a corresponding change in the GDP by about 5. It therefore indicates the short run causality between gross domestic product as proxy of economic growth, capital and recurrent government spending on education respectively.
The table below presents the detail result regarding the short run causalities: Extraction from estimation output using E-views 7 Table 4 shows the result of Error-Correction Model with two lags.
From the result, the Error Correction Term which shows the speed of adjustment, is statistically significant and has a negative sign - 0. The result denotes a satisfactory convergence rate to equilibrium point per period. Although the short run coefficient of lagged GDP and capital expenditures were not significant, the short run coefficient of recurrent expenditure on education is statistically significant and also the joint coefficient of significance F- Statistics shows that the variables are jointly significant in explaining output variations in Nigeria.
Gyimah-Brempong, Paddison and Mitiku investigated the effect of higher education human capital on economic growth in African countries using panel data over the — period, a modified neoclassical growth equation, and a dynamic panel. They found that all levels of education human capital, including higher education human capital, have positive and statistically significant effect on the growth rate of per capita income in African countries. Their result differs from those of earlier research that find no significant relationship between higher education human capital and income growth.
They also claimed that the growth elasticity of higher education human capital is twice as large as the growth impact of physical capital investment. While this is likely to be an overestimate of the growth impact of higher education, it is robust to different specifications and points to the need for African countries to effectively use higher education human capital in growth policies.
Nabil, Simon and Yu examined the dynamic effects of public investment in human capital in the Canadian context of population ageing using a computable overlapping-generations model OLG. The decisions of time allocation between learning, working and leisure activity are endogenously determined in the model and react differently to tax policy changes.
Learning time and public expenditures on education both improve human capital accumulation and effective labour supply.
The simulation results indicated that a tax-financed increase in public spending on education may have significant crowding-out effects in the short run. In the long run, however, higher education incentives may increase the rate of human capital accumulation which in turn could mitigate the negative effects of population ageing. Furthermore, economic and welfare effects analysis shows that the impact depends on the distortions implied by alternative tax instruments and the productivity of public expenditures on education.
Lawanson in his work used an ordinary least squares model to estimate the role of education and health in human capital investment and economic growth in Nigeria.
He found that on the average, human capital actually enhances economic growth in Nigeria although, the government expenditure on health and primary education enrollment have negative coefficients which are inconsistent with a priori expectation.
Daudain his study on human capital formation and economic growth in Nigeria used the endogenous growth model in his investigation into their relationship, she employed enrolment in the different levels of education, primary, secondary and tertiary as proxies for human capital and found long-run positive relationship between human capital formation and economic growth in Nigeria with a feedback mechanism. Amassoma and Nwosa studied the causal nexus between human capital Investment and economic growth in Nigeria for sustainable development in Africa at large between and using a Vector Error Correction VEC and Pairwise granger causality methodologies.
The findings of the Vector Autoregression VAR model and pairwise estimate reveal no causality between human capital development and economic growth.
The study recommends the need to increase budgetary allocation to the education and health sector and the establishment of sound and well-functioning vocational institute needed to bring about the needed growth in human capital that can stimulate economic growth.
Also, the study identified that labour mismatch is an issue that government needs to reckon with in order to accelerate and sustain economic growth. In this regard, policy-makers in conjunction with employers and individuals need to update information on the real labour market value of different qualifications, in order to help them navigate through the increasingly complex education system and make the optimal kinds of educational investment decisions needed to propel economic growth.
Oluwatobi and Ogunrinola examined the relationship between human capital development efforts of the Government and economic growth in Nigeria. They seek to find out the impact of government recurrent and capital expenditures on education and health in Nigeria and their effect on economic growth.
The data used for the study are from secondary sources while the augmented Solow model was also adopted. The dependent variable in the model is the level of real output while the explanatory variables are government capital and recurrent expenditures on education and health, gross fixed capital formation and the labour force. The result shows that there exists a positive relationship between government recurrent expenditure on human capital development and the level of real output, while capital expenditure is negatively related to the level of real output.
Adelakun conducted a study on human capital development and economic growth using OLS technique. It evaluates human capital using the GDP as proxy for economic growth; total government expenditure on education and health, and the enrolment pattern of tertiary, secondary and primary schools as proxy for human capital.
He concluded that there is a positive relationship between government expenditure on education and health as well as pattern of enrolment in primary, secondary, and tertiary institutions in enhancing economic growth in the long run. Adawo examined the contributions of primary education, secondary education and tertiary education to economic growth in Nigeria using an econometric model.
These variables were proxied by school enrolment at various levels. Other variables included physical capital formation, and health measured through total expenditure on health. In all primary school input, physical capital formation and health were found to contribute to growth. Secondary school input and tertiary institutions were found to dampen growth. Isola and Alani examined the contribution of different measures of human capital development to economic growth in Nigeria.
The study used data from Nigeria and adopted the growth account model which specifies the growth of GDP as a function of labour and capital. The model also included a measure of policy reforms. Based on the estimated regression and a descriptive statistical analysis of trends of government commitment to human capital development, the study found that though little commitment had been accorded health compared to education, empirical analysis showed that both education and health components of human capital development are crucial to economic growth in Nigeria.
Adelowokan examined the effect of education and health expenditures on economic growth in Nigeria between and using a static regression model.
He also established the long-relationship between human capital spending and economic growth using the Engle-Granger two-step cointegration procedure. The study found that public investment and public consumption in education and health exerted positive influence on economic growth, while, private investment exerted negative effect on economic growth in Nigeria.
Similarly, the study showed that there was long-run relationship between economic growth and expenditure on education and health in Nigeria.
Akbari, Moayedfar, and Jouzaryan, investigated the effect of human capital on the economic growth of Iran in the long run and the short run using the auto-regressive distribution lag model. The results obtained from the estimation of the model under study are indicative of positive and significant effect of human capital on the economic growth of Iran. Thus, it is hoped that the results obtained from this study can attract the attention of authorities to the development and improvement of the human capital of the country.
Onyeagu and Okeiyika investigated the interaction between foreign direct investment and human capital on growth in Nigeria and tried to ascertain the long run sustainability of Foreign Direct Investment FDI- induced growth process using error correction mechanism.
They found that FDI in Nigeria, had a negatively significant relationship to growth in the long run, meaning that the contribution of FDI in Nigeria is small and human capital had negative significant effects on growth in the long-run.
The study claimed that this was due to shortage of skilled labour in the country. Linda investigated the common opinion on the positive relationship between human capital development and economic growth using simple production function to estimate the human capital impact on labour productivity. The study proxied human capital with average years of schooling from — and human capital stock and found that female human capital has positive impact on labour productivity during the period — Eric focused on human capital as a driver of economic growth for developing countries.
He argued that this has led to undue attention on school attainment. Developing countries have made considerable progress in closing the gap with developed countries in terms of school attainment, but recent research has underscored the importance of cognitive skills for economic growth.
He claimed that attention has been shifted to issues of school quality and, in that area developing countries have been much less successful in closing the gaps with developed countries. Without improving school quality, developing countries will find it difficult to improve their long run economic performance.
Mba, Mba, Ogbuabor and Ikpegbu examined the relevance of human capital development on the growth of the economy using the ordinary least squares OLS technique. In the study, the GDP was used as a proxy for economic growth; Per Capita Real Gross Domestic Product, primary school enrolment, public expenditure on education and health, life expectancy and stock of physical capital as proxy for human capital.
The study found that there was a strong positive relationship between human capital development and economic growth. Mehrara and Musai investigated the causal relationship between education and GDP in developing countries by using panel unit root tests and panel cointegration analysis for the period A three-variable model is formulated with capital formation as the third variable.
The results showed a strong causality from investment and economic growth to education in these countries.
Yet, education does not have any significant effects on GDP and investment in the short- and long-run. It means that it is the capital formation and GDP that drives education in mentioned countries, not vice versa. Therefore the findings of the paper supported the point of view that it is higher economic growth that leads to higher education growth. It seems that as the number of enrollments rise, the quality of education declines.Education: The Path to Economic Growth
Moreover, the formal education systems are not market oriented in these countries. This might be the reason why huge educational investments in these developing countries fail to generate higher growth.