SUMMARY
OF FINDINGS
The
main objective of this research work are to examine the impact and relationship
of foreign aid on poverty in Nigeria.
Empirically, this work succeeds in providing father analysis of these
objectives in Nigeria.
Considering the various theories with postulates that foreign aid has either
positive or negative impact on poverty in Nigeria, the ordinary least square
estimates of the true impact and relationship between foreign aid and poverty
in Nigeria
was developed. From the results, it has been shown that ODA does not reduce
poverty in Nigeria, rather the reduction in the living standard of 1980’s which
overflowed into the 1990’s was attributable to he structural adjustment
programs, corruption, institutional failure, mismanagement, administrative
incompetence and lots more which arose
form the adherence to the donor policies. Basically, it is noticed that foreign
aid is designed to serve the strategic and economic interest of the donor
countries thus making development and poverty reduction of the recipient count
ineffective. More so these aid is often wasted on over priced goods and
services from donor countries and as such discourages local production,
disrupts economies of scale and increases the p9veryt rate in the country.
READ MORE ON FOREIGN AID
· PRESENTATION OF REGRESSION RESULTS AND ANALYSIS GOTTEN FROM THE IMPACT OF FOREIGN AID ON POVERTY IN NIGERIA
· RESEARCH METHODOLOGY OF THE IMPACT OF FOREIGN AID ON POVERTY IN NIGERIA - AFRICA
· RESEARCH METHODOLOGY OF THE IMPACT OF FOREIGN AID ON POVERTY IN NIGERIA - AFRICA
· EMPIRICAL LITERATURE OF IMPACT OF FOREIGN AID ON POVERTY IN NIGERIA
· THEORETICAL LITERATURE REVIEW OF THE IMPACT OF FOREIGN AID ON POVERTY IN NIGERIA
· IMPACT OF FOREIGN AID ON POVERTY IN NIGERIA
Ideally, one would expect the poverty rate
/poverty incidence (thus the population in poverty) in Nigeria to have
a positive relationship with its population growth rate, but our empirical
result shows otherwise and this could be explained by the fact the increase in
population would lead increase in labour force and thus increase in output. Hence
the increase in output reduces the level of poverty. More so , the level of
consciousness about poverty amongst the people has made them to make ends meet
despite the odds they face in the country.
Furthermore,
the regression result showed a positive relationship been poverty and capital
expenditure and this indicates that the amount invest by the government on
infrastructure and other social amenities does not reduce poverty in the
country. This could be attributed to the fact that the capital expenditure is mostly
devoted to cities and not inculcating
rural, thus causing rural-urban migration and this leads to neglect of
agricultural production for life in the cites. It could also be attributed to
the level of corruption and nepotism in the county, where contracts are
inflated and also competence is neglected in the award of contracts. Hence
increase I capital expenditure increases the poverty level in the country, but
its impact is not significant. In addition, the regression result shows that
the past level of poverty in the country affects the current level of
poverty positively.
POLICY
RECOMMENDATION
From
the findings of the research and the facts on ground, the researcher would
recommend
1. The government has to get committed to
poverty reduction by facing the facts on ground and tackle corruption which has
posed a threat to poverty reduction as well as economic development. Hence the
poverty alleviation programs should be more purposeful and aimed at the poor in
the country rather than being used to compensate political allies and
contractors.
2. The
government of Nigeria
should as a matter of priority consider the people of the country when
accepting foreign aid rather than the interest of the donor nations.
3. For foreign aid to t be effective, the
practice of attaching harsh economic policy conditions, privatization, trade liberalization
and government reduction in spending must stop.
4. A sincere and promising design of poverty
reduction strategies must involve all stakeholders especially the grassroots,
the poor and independent monitors. More so, workable mechanisms must be put in
to effectively manage aid funds in order to have positive impact on the poor
and to curb aid’s diversion.
5. Another area of our recommendation is the
time lag involved in policy making and policy impact. The changing nature of
the Nigeria
economy, if there is zero-time lag for an impact of a policy to be felt, and
then it would be easier to discern and simultaneously monitor the effectiveness
of policies meant to fight poverty in Nigeria. This will go a long way in
checking conflicting policy effects and also make foreign aid more effective.
6. The
level of infrastructural development and other capital expenditure in Nigeria should
be diversified with the rural areas involved in the various projects and
development plans so as to make the life in rural areas better and thus reduce
poverty.
CONCLUSION
The research work shows that despite
the volume of ODA received by Nigeria
the level of population in poverty has not declined. More so, the capital
expenditure of the government has not effectively curbed poverty since it
encourages rural-urban migration and thus discouraging agricultural production.
This research work has contributed
immensely in explaining the analytical impacts of Foreign Aid On Poverty in
Nigeria and the policy recommendations is confident that poverty which has
assumed a multidimensional aspect will be curbed if proper policy is carried
out sincerely to alleviate the poverty.
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APPENDIX ONE
RAW DATA
YEAR
|
P
|
ODA
|
GR
|
PGR
|
CAP
|
GRGDP
|
1980
|
18.26
|
34.4
|
2.68
|
3
|
10163.4
|
4.2
|
1981
|
21.5
|
39.25
|
6.14
|
2.8
|
6567
|
13.1
|
1982
|
24.5
|
34.95
|
4.45
|
2.7
|
6417.2
|
-0.2
|
1983
|
28
|
46.75
|
4.2
|
2.6
|
4885.7
|
-5.3
|
1984
|
31.3
|
32.39
|
6.95
|
2.6
|
4100.1
|
-4.8
|
1985
|
34.73
|
31.71
|
3.77
|
2.6
|
5464.7
|
9.7
|
1986
|
35.05
|
58.12
|
8.73
|
2.7
|
8526.8
|
2.5
|
1987
|
35.8
|
67.62
|
13.79
|
2.7
|
6372.5
|
-0.7
|
1988
|
36.5
|
118.08
|
35.52
|
2.7
|
8340.1
|
9.9
|
1989
|
37.1
|
344
|
127.8
|
2.7
|
15034.1
|
7.2
|
1990
|
37.6
|
255.08
|
124.7
|
2.6
|
24048.6
|
8.2
|
1991
|
38.35
|
258.32
|
130.77
|
2.6
|
28340.9
|
4.8
|
1992
|
39.07
|
258.82
|
116.26
|
2.5
|
39763.3
|
2.9
|
1993
|
46
|
288.42
|
53.44
|
2.5
|
54501.8
|
2.2
|
1994
|
52.85
|
189.66
|
43.16
|
2.5
|
70918.3
|
0.1
|
1995
|
60.05
|
210.9
|
32.56
|
2.5
|
121138.3
|
0.2
|
1996
|
67.11
|
188.75
|
24.14
|
2.5
|
212926.3
|
4.3
|
1997
|
67.4
|
199.75
|
27.01
|
2.5
|
26965.7
|
2.7
|
1998
|
67.5
|
203.09
|
30.06
|
2.4
|
309315.6
|
1.9
|
1999
|
67.7
|
151.8
|
47.59
|
2.4
|
498027.6
|
1.1
|
2000
|
67.9
|
173.7
|
49.49
|
2.4
|
239450.9
|
5.4
|
2001
|
68.1
|
176.17
|
98.23
|
2.4
|
438696.5
|
3.1
|
2002
|
68.35
|
297.93
|
105.69
|
2.4
|
321378.1
|
1.5
|
2003
|
68.5
|
308.19
|
113.2
|
2.4
|
241688.3
|
10.3
|
2004
|
68.7
|
576.87
|
163.23
|
2.4
|
351300
|
10.6
|
2005
|
77.7909
|
6408.74
|
5846.55
|
2.4
|
519500
|
5.4
|
2006
|
80.11968
|
11427.9
|
11383.95
|
2.4
|
552385.5
|
6.2
|
2007
|
82.44845
|
1956.18
|
1320.9
|
2.4
|
759323
|
6.4
|
2008
|
84.77723
|
1289.78
|
842.92
|
2.3
|
960900
|
6
|
SOURCE: CBN STATISTICAL BULLETIN, 2008
APPENDIX TWO
REGRESSION RESULT
Dependent Variable: P
|
||||
Method: Least Squares
|
||||
Date: 11/09/11 Time: 09:04
|
||||
Sample: 1980 2008
|
||||
Included observations: 29
|
||||
Variable
|
Coefficient
|
Std. Error
|
t-Statistic
|
Prob.
|
C
|
245.8542
|
34.56362
|
7.113094
|
0.0000
|
ODA
|
0.011446
|
0.012607
|
0.907943
|
0.3733
|
GR
|
-0.010647
|
0.012492
|
-0.852342
|
0.4028
|
PGR
|
-79.53131
|
13.16922
|
-6.039182
|
0.0000
|
CAP
|
2.26E-05
|
9.77E-06
|
2.313773
|
0.0300
|
GRGDP
|
0.272130
|
0.335517
|
0.811075
|
0.4256
|
R-squared
|
0.892563
|
Mean dependent var
|
52.17435
|
|
Adjusted R-squared
|
0.869207
|
S.D. dependent var
|
20.30234
|
|
S.E. of regression
|
7.342395
|
Akaike info criterion
|
7.007199
|
|
Sum squared resid
|
1239.948
|
Schwarz criterion
|
7.290088
|
|
Log likelihood
|
-95.60438
|
F-statistic
|
38.21587
|
|
Durbin-Watson stat
|
0.775839
|
Prob(F-statistic)
|
0.000000
|
Dependent Variable:
LOG(P)
|
||||
Method: Least Squares
|
||||
Date: 11/09/11 Time: 09:06
|
||||
Sample: 1980 2008
|
||||
Included observations: 25
|
||||
Excluded observations: 4
|
||||
Variable
|
Coefficient
|
Std. Error
|
t-Statistic
|
Prob.
|
C
|
7.452407
|
1.063112
|
7.009992
|
0.0000
|
LOG(ODA)
|
0.212939
|
0.087926
|
2.421798
|
0.0256
|
LOG(GR)
|
-0.129545
|
0.062113
|
-2.085636
|
0.0507
|
LOG(PGR)
|
-4.986452
|
0.834317
|
-5.976690
|
0.0000
|
LOG(CAP)
|
0.041455
|
0.032670
|
1.268911
|
0.2198
|
LOG(GRGDP)
|
-0.004304
|
0.022743
|
-0.189229
|
0.8519
|
R-squared
|
0.936304
|
Mean dependent var
|
3.946906
|
|
Adjusted R-squared
|
0.919541
|
S.D. dependent var
|
0.417874
|
|
S.E. of regression
|
0.118531
|
Akaike info criterion
|
-1.221722
|
|
Sum squared resid
|
0.266942
|
Schwarz criterion
|
-0.929192
|
|
Log likelihood
|
21.27153
|
F-statistic
|
55.85799
|
|
Durbin-Watson stat
|
1.253807
|
Prob(F-statistic)
|
0.000000
|
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