CHAPTER FIVE
SUMMARY OF FINDINGS, RECOMMENDATION AND CONCLUSION
5.1 Summary of Findings
On the application of statistical techniques employed, the following information surfaced;
i. Human capital development has significant effect on economic growth in Nigeria within the period under study i.e. 1983-2010.
ii. The entire regression plane is statistically significant. This means that the joint influence of the explanatory variables (GEE and GEH) on the dependent variable (RGDP) is statistically significant.
iii. The computed coefficient of Multiple determination (R2= 0.955249) shows that 95.53% of the total variations in the dependent variable (RGDP) is accounted for, by the in the explanatory variables namely Government Expenditure on Health (GEH) and Government Expenditure on Education (GEE).
iv. The total variation of 4.47% in the dependent variable is attributable to the influence of other factors not included in the regression model.
5.2 Conclusion
Human Capital Development has been regarded as the basic instrument for economic growth and development in Nigeria over the years. In this study however, several theories were adopted in accessing the extent to which economic growth has been empowered through training. Such indices include gender, related investment index, human poverty index, gender empowerment measure and among others.
Judging by these measures, it is imperative to note that human capital investment in resources, skills, mental, knowledge, and desired work attitude has helped greatly in many organizational survivals. However, through development on human resources in Nigeria, it has helped and saved the economy from borrowing experts, managers and diverse technicians from other countries of the world. It has also increased the personal earnings of individuals as well as the supply of skilled and highly health educated manpower needed for economic development of Nigeria’s economy.
5.3 Recommendation
In the light of the findings made, the following recommendations are stated;
· There are needs for the authorities to improve funding expenditure relating to education and health with particular emphasis on infrastructure e.g. maintaining standard libraries and laboratories which were among the things which will develop human resources.
· In addition, training and development must not be seen to be lopsided, in which case, some group of people will be trained where as others are left because of political, ethnic, religious or social consideration.
· Government spending ought to focus on kindergarten, pre-school and primary education, where the educational paths are set. This will help to develop human resources from the stage of life.
· In the course to develop human resources, government should embark on programmes which focus on employment opportunities. High rate of employment will undermine under-utilization of human resources.
· Good investments in human resources development require some rationality for proper utilization of human resources. Therefore, individuals should be taught how existing knowledge should be used to develop new products, to introduce new processes and production methods and social services; and people must be encouraged to develop entirely new ideas, products, processes and methods through creative approaches.
· More so, undue influence of government will definitely mar whatever measures it takes to ensure economic growth. To ensure positively strong relationship between growth and education/ health, it might be imperative to emphasize on qualitative education and focus more attention on science, technology and research institutions.
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Barney, J.B. (1995); Looking Inside for Competitive Advantage: Academy of Management Executive, 9 (4), Malaysia.
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Lucas, R.E. (1998); On the Mechanics of Economic Development. Journal of Monetary Economics 22 (1).
Mankiw, N.G., Romer, P. and Weil D. (1992); A Contribution to the Empirics of Economic Growth. Quarterly Journal of Economics 107 (2).
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Publishers, London, 1980.
APPENDIX I
YEAR
|
RGDP
(
|
GEE
(
|
GEH
(
|
1983
|
185,598.14
|
967.4
|
218.79
|
1984
|
183,562.95
|
861.2
|
152.65
|
1985
|
201,036.27
|
850.2
|
188.22
|
1986
|
205,971.44
|
1074.8
|
215.32
|
1987
|
204,806.54
|
653.5
|
137.81
|
1988
|
219,875.63
|
1084.1
|
606
|
1989
|
236,729.58
|
1941.8
|
701.3
|
1990
|
267,549.99
|
2294.3
|
757.7
|
1991
|
265,379.14
|
1554.2
|
755.8
|
1992
|
271,365.52
|
2060.4
|
338.16
|
1993
|
274,833.29
|
7999.1
|
4224.5
|
1994
|
275,450.56
|
10283.8
|
3054.98
|
1995
|
281,407.40
|
12728.7
|
5045.9
|
1996
|
293,745.38
|
44294
|
4683.21
|
1997
|
302,022.48
|
50216
|
6514.9
|
1998
|
310,890.05
|
26721.3
|
11866.07
|
1999
|
312,183.48
|
31563.8
|
24025.57
|
2000
|
329,178.74
|
67568.1
|
21787.28
|
2001
|
356,994.26
|
59744.6
|
44650.27
|
2002
|
433,203.51
|
109455.2
|
53229.42
|
2003
|
477,532.98
|
79436.1
|
39698.98
|
2004
|
527,576.04
|
93767.9
|
60607.14
|
2005
|
561,931.39
|
120035.5
|
77314.23
|
2006
|
595,821.61
|
165213.7
|
100339.8
|
2007
|
634,251.14
|
185771.8
|
133071
|
2008
|
672,202.55
|
216413.3
|
157686.7
|
2009
|
718,977.33
|
197300.6
|
157329.1
|
2010
|
776,332.21
|
233788.9
|
179462.4
|
Source: CBN Statistical Bulletin Volume 21, 2013
REGRESSION RESULTS
Dependent Variable: RGDP
| ||||
Method: Least Squares
| ||||
Date: 05/19/13 Time: 17:35
| ||||
Sample: 1983 2010
| ||||
Included observations: 28
| ||||
Variable
|
Coefficient
|
Std. Error
|
t-Statistic
|
Prob.
|
C
|
234627.4
|
10429.75
|
22.49596
|
0.0000
|
GEE
|
1.621767
|
0.499125
|
3.249219
|
0.0033
|
GEH
|
0.926136
|
0.668985
|
1.384390
|
0.1785
|
R-squared
|
0.955249
|
Mean dependent var
|
370586.1
| |
Adjusted R-squared
|
0.951669
|
S.D. dependent var
|
176822.3
| |
S.E. of regression
|
38873.12
|
Akaike info criterion
|
24.07495
| |
Sum squared resid
|
3.78E+10
|
Schwarz criterion
|
24.21769
| |
Log likelihood
|
-334.0493
|
Hannan-Quinn criter.
|
24.11859
| |
F-statistic
|
266.8245
|
Durbin-Watson stat
|
0.829061
| |
Prob(F-statistic)
|
0.000000
| |||
Dependent Variable: LOG(RGDP)
| ||||
Method: Least Squares
| ||||
Date: 05/19/13 Time: 17:36
| ||||
Sample: 1983 2010
| ||||
Included observations: 28
| ||||
Variable
|
Coefficient
|
Std. Error
|
t-Statistic
|
Prob.
|
C
|
11.36174
|
0.211714
|
53.66563
|
0.0000
|
LOG(GEE)
|
-0.029729
|
0.073991
|
-0.401789
|
0.6913
|
LOG(GEH)
|
0.189782
|
0.062668
|
3.028380
|
0.0056
|
R-squared
|
0.876232
|
Mean dependent var
|
12.72465
| |
Adjusted R-squared
|
0.866330
|
S.D. dependent var
|
0.439988
| |
S.E. of regression
|
0.160864
|
Akaike info criterion
|
-0.715562
| |
Sum squared resid
|
0.646928
|
Schwarz criterion
|
-0.572826
| |
Log likelihood
|
13.01787
|
Hannan-Quinn criter.
|
-0.671926
| |
F-statistic
|
88.49508
|
Durbin-Watson stat
|
0.619067
| |
Prob(F-statistic)
|
0.000000
| |||