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ABSTRACT
There have been several different views on the relationship between government education expenditure and economic growth and most importantly as it regards its result. The study examined government expenditure on expenditure on education and economic growth in Nigeria.
The source of data gathering was based on secondary data spanning from 1981-2020, which was obtain from the CBN statistical bulletin 2021, word development indicators (WDI) 2021 and the federal Reserve Bank of St. Louis(2021) data analysis was carried out using quantitative for numerical descriptive while the variable hypothesized in these model uses tested using the augmented Dickey fuller test for the stationarity in the variables, Bound co-integration technique will be used to examine the long run relationship between the dependent and the independent variables, using the ARDL error correction model(ECM) which tells us the long run effect and the speed of adjustment, that is the rate at which the previous period disequilibrium is adjusted towards equilibrium path on an annual basis.
The result showed that the ECM term is in line with our a priori expectation. The negative sign and the statistical significant of ECM at 10 percent implies that the speed of adjustment to its long run equilibrium is 16.1 percent. Thus the ECM will adequately act to correct any deviations of the short run dynamics to its long run equilibrium by 3 percent quarterly. The coefficient of determination measured by the R2 is 0.70 which implies that 70percent of the total variations in per capital GDP is accounted for by the explanatory variables: Recurrent expenditure on education, capital expenditure on education, human capital development and tax revenue. The adjusted R2 total variations between 50 percent. The F stats result indicates that the overall test is significant at 1 percent. From the ARDL result, the Durban Easton statistics was at 1.9 percent indicating that auto correlation is absent in the estimated model, this makes the estimated model reliable and fit for policy perspective. Thus this tells us that the explanatory variables are jointly significant and the overall model is good for policy forecast.
