PRESENTATION AND ANALYSIS OF RESULTS FROM AN ASSESSMENT ON IMPACT OF HUMAN CAPITAL DEVELOPMENT ON ECONOMIC GROWTH OF NIGERIA (1980-2008)



Having estimated model, variables considered are Real Gross Domestic Product (dependent variable), Government Expenditure on Health and Government Expenditure on Education (Independent variables) it covers the period of years: 1980-2008

PRESENTATION OF RESULTS

GDP            =   + 2.2287  +  0.17246GEH  + 2.299GEE
  T*           =     (17.589)      (0.111)              (2.210)         
  S.E        =      (1.2671)       (1.5560)           (0.9999)           
  t0.025          =       
  F (2, 26)    =      95.65
  F0.05    =       3.37
  R2               =          0.8804 
  DW        =      0.762


ANALYSIS OF RESULTS
                                 
(a)    T-test: It is used to test for the statistical significance of the individual estimated parameters. The calculated t-value for the regression coefficients of GEH and GEE are 0.11 and 2.210 respectively. Since the caculated t-value of GEE is greathan than the tabulated t-value at 5% level of significance; we conclude that the regression coefficient is statistically significant. However, the regression coefficient of GEH is not  statistically insignificant.  

(b)     Standard Error test: It is used to test for statistical reliability of the coefficient estimates.
      S(b1) = 1.5560     S(b2) =  0.9999   
       b1/2    =  0.08623      b2/2    = 1.104595
Since S(b1) < b1/2, we conclude that the coefficient estimate of b1 is statistically significant. However, coefficient estimate of GEE is  statistically significant.

(c)     F-Test: This is used to test for the joint influence of the explanatory variables on the dependent variable. The F-calculated value is 95.652 while the F-tabulated value is 3.37 at 5% level of significance. Since the F-calculated value is greater than the F-tabulated value, we conclude that the entire regression plane is statistically significant. This means that the joint influence of the explanatory variables (GEE and GEH) on the dependent variable (GDP) is statistically significant. This result can as well be confirmed from the F- probability which is statistically significant.

(d)     Coefficient of Determination (R2): It is used to measure the proportion of variations in the dependent variable, which is explained by the explanatory variables. The computed coefficient of determination (R2=  0.88804) shows that 88.04% of the total variations in the dependent variable LGDP) is influenced by the variation in the explanatory variables namely Government Expenditure on Health (GEH) and Government Expenditure on Education (GEE)  while 11.95% of the total variation in the dependent variable is attributable to the influence of other factors not included in the regression model.

(e)     Durbin Watson statistics: It is used to test for the presence of positive first order serial correlation. The computed DW is 0.762. At 5% level of significance with two explanatory variables and 29 observations, the tabulated DW for dL and du are 1.270 and 1.563 respectively. The value of DW is less than the lower limit. Therefore, we conclude that there is evidence of positive first order serial correlation
  
TEST OF HYPOTHESIS

       F-test is employed in testing the hypothesis. Using 5% level of significance at 2/26 degrees of freedom, the  F-tabulated value is 3.37 while calculated F-value is 95.652. Since the calculated F-value is greater than the tabulated F-value Ho is. Thus, Hi is accepted on the proposition that Human Capital Development had significant impact on Economic growth in Nigeria  within the period under study i.e. 1980-2008.

IMPLICATION OF THE RESULT  
            The regression result  shows that there existed a positive relationship between dependent variable (RGDP) and the explanatory variables (GEH and GEE). It is estimated from the result that a unit increase in government expenditure on health and government expenditure on education, on the average, will lead to increase by 0.17 and 2.21 units in GDP respectively. However, holding the explanatory variables constant, GDP increase by 2.23 units. It is obviously seen that the sign borne by parameters estimate meet the prior expectations.
          The entire repression plan is statistical significant. Invariably, the joint information of the explanatory variables has a significant influence on the dependent variable. Also, the coefficient of multiple determinations shows a valid goodness of fit. However, there is presence of autocorrelation. This could be attribute to the absence or omission of some variable which are captured in the stochastic variables but not included in the regression model.
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