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Solid Minerals, Government Effectiveness and Poverty Reduction in Nigeria
By
OLOFIN, Olabode Philip (Ph.D)1
Faculty of Social Sciences, Dept. of Economics, ObafemiAwolowo
University, Ile-Ife, Nigeria
+2348033809505, [email protected], [email protected], [email protected]
&
ODELEYE, Anthonia, T. (Ph.D)
Department Of Economics, University Of Lagos, Akoka, Lagos, Nigeria
+2348033618174,[email protected] [email protected]
1 Corresponding Author
1
Abstract
Using annual time series between 1996 and 2014, this study examines the impact of
disaggregate solid minerals and government effectiveness on poverty level in Nigeria. The
results from the study show that coal, metaore, quarry and others reduce poverty level, while
government effectiveness relates positively to poverty level in Nigeria. The results were
statistically significant. The study shows that investment on different types of solid minerals
could reduce poverty level in Nigeria, while there is a need to improve government
effectiveness in Nigeria if poverty reduction is to be achieved.
Key Words: Solid Minerals; Government Effectiveness; Poverty level; Nigeria.
JEL classification codes: I32, 013, Q01, Q32.
2
1. Introduction
Despite the richness of Nigeria in solid minerals and other natural resources, (Barth,
2016; Alison-Madueke, 2009), there exists high level of poverty caused by lack of diversification
of the economy due to economic mismanagement. Studies have shown that solid minerals are
capable of spurring economic growth as well as promoting social wellbeing (Bridge, 2008).
Although, these mineral resources are distributed throughout Nigeria, few are being exploited,
usually at small-scale levels. Before crude oil became the major source of foreign revenue in
1970s, solid mineral sub-sectors ranked second to the agricultural sector as source of export
earnings. Its contribution to national output was 10 % of GDP in 1970 (Kogbe and Obialo,
1974). Recently, it has been noted that the intervention of Nigerian Export-Import (NEXIM)
Bank in solid minerals sectors led to the creation or sustained over 8,000 direct jobs and helped
the miners to generate over $200,000.00 in foreign exchange (Orya, 2015). This shows the level
of its potential in driving Nigerian economy to her desired goal if properly harnessed.
With the current fall in global oil price and high poverty level, the Nigerian government has
realized the importance of diversifying the economy from agriculture which is currently the
focused sector. While a plethora of scholarly works on the contribution of agriculture to the
Nigerian economy have been done, however, for solid mineral resources and its impact on the
Nigerian economic development, there is a dearth of research. The few available studies focus on
mining and economic growth without looking at the contribution of other types of solid minerals.
Aside from this, studies have shown that increased economic growth does not transform to
increased social well-being of people in Nigeria; we therefore consider analyzing the impact of
different types of solid minerals on poverty reduction, hoping that different types will impact
3
poverty differently. Furthermore, when we consider the seriousness of the present
administration’s diversification agenda, and the potentials embedded in solid minerals, we
extend the study to the analysis of different types of solid mineral and government effectiveness
on poverty reduction in Nigeria. This is to probe into the role of government on the success of
solid minerals development in Nigeria. To the best of our knowledge, no known study in Nigeria
has gone as far as we have in this study.
2. Literature Review
One of the early examples of research on the impact of exploitation of the solid minerals
is the study of Roderick (2001). In the study, he used qualitative approach and discovered that
accrued benefits of exploited solid mineral resources could be sustained, in spite of inevitable
decline associated with their exploration. Examining the study of Solomon (2000), it was argued
that Botswana’s economy, like Korea and Thailand has been mineral-driven and that the
economy had an unbroken three decades of real per capita income growth of more than 7 percent
per annum on average. The growth was sustained because the country did not use her
commonwealth to fight wars or squander it on non-essentials like other developing economies
which are endowed with mineral resources. These findings were tantamount to the assertion that
investment in solid mineral can lead to economic growth because it has the ability to generate
additional revenue and reducing unemployment (Okubor, 2014). In the studies of Ayodele et al,
(2013) and Akongwale et al., (2013), it was noted that exploitation of solid minerals could help
in reducing poverty rate, as it has capacity to create jobs; given its forward linkage by providing
inputs to other sectors (industrial, agriculture) of the economy. The linkage is expected, will
increase tax base of government with its attendant multiplier effects.
4
Based on the study of Adeniyi et al. (2013)on the effects of solid minerals on economic
growth of Nigeria, it was revealed that the solid mineral sector is crucial to economic
development, wealth creation and poverty alleviation of any economies. Although, qualitative
analysis was employed, it recommended that best practices and mechanisms that have been used
by different countries to formalise and regulate mining explorations in order to attain sustainable
development in the mining sector is needed to be adopted by Nigeria for economic sustainability.
The work of Agba (2007) corroborates this finding in his qualitative and quantitative
(descriptive) analysis of the mining sector component of Nigeria. The comparative study of
subsectors in Nigeria by Nwanne (2014) also showed that solid minerals components had
negative and insignificant relationship with economic growth. These findings differ from other
studies on Nigeria, which indicated positive and significant association between solid mineral
sector’s development and economic growth. However, his submission might be attributed to the
models (parsimonious and over-parameterized) he adopted since studies have shown that too
parsimonious and over-parameterized models may lead to erroneous conclusions (Poleto et al.,
2011).
In addition, mining industry is regarded as a key driver of economic growth in
developmental process. It can drive economic expansion to higher levels of social and economic
wellbeing (Bridge, 2008). That assertion corroborated the experiences of USA, Canada and
Australia respectively where rent from successive mining activities led to their economic growth.
Specifically, Reynolds (1979) noted that profit from copper in 17th century Sweden was used to
fund some aspects of development; similarly, rent earned from gold was used for infrastructural
development in Australia and South Africa respectively. In addition, Britain's property was
partly attributed to the rents earned by the exploration of minerals from her colonies.
5
Recent evidence suggests that, solid minerals have the potential to contribute
significantly to the economic development of a country and reduce poverty level. For instance,
mining could create significant economic benefits, including direct benefits in form of income
and employment, as well as indirect benefits in form of local or international purchase of mining
inputs (see Olalekan et al., 2016). It has been noted that solid minerals sector is the largest source
of government revenues in most mining countries and till date it is still the highest contributor in
terms of foreign direct investment (FDI) of most developing countries (Madeley, 1999). For
example, Ghana mining sector has low capacity for employment generation since it is highly
capital intensive. However, its contribution to the nation’s GDP has been upward trending and
remains a key industry for the growth and development of the Ghanaian economy (AmponsahTawiah and Dartey-Baah, 2011). Sectoral contributory analysis of the economy shows that
revenue from the sector went up from 798 million dollars in 2004 to 995.2 million dollars in
2005 accounting for about 13% of the total collection of the Internal Revenue Service. (Ghana
Chamber of Mines, 2005).
Data from several sources have identified the increasing role of mineral sectors in Africa.
Mining is the second largest export in the Rwandan economy. $210.6 Million of foreign
exchange was generated by the sector in 2014. It currently employed 20,000 labour force, with
its total cumulative investment of USD 150 million. Zambia produces about 20% of the world’s
emeralds. In recent year (2000), investment in Zambian mining sector has been in excess of
USD 8 billion with over 80,000 jobs created in 2013 against 27,000 jobs in 2000. (Zambia
Development Agency, 2014; and Rwanda Development Board, 2016). Empirical studies provide
strong evidences that solid minerals could contribute greatly toward economic development in
Nigeria. This study offers some important insights into the role of solid minerals in economic
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growth. Overall, there seems to be some evidences indicating that solid minerals could enhance
job creations that can lead to poverty reduction in Nigeria.
Table 1: Contribution of Solid Minerals to the Economies of Selected SubSaharan African Countries (1987).
S/N
1.
2
3
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
Country
Botswana
Zaire
Zambia
Zimbabwe
Guinea
Niger
Liberia
Ghana
Gabon
Mauritania
Sierra-Leone
Togo
Senegal
Burkina Faso
Nigeria
Mining Exports as % of Total Export GDP
90
73
93
43
92
80
58
19
19
31
74
29
9
20
0.4
Source: Vision 2010 (1999) P.218.
From table 1, the contribution of the mining sector to Nigerian GDP is pitifully small
(0.4%) especially when compared to other African countries over the same period. Igualada
(2016) attributes this phenomenon to the country’s huge concentration on oil sector. The range is
considerable too high from 90% of GDP in Botswana to less than 1% in Nigeria. Export earnings
of over 50% were generated in Sierra Leone, Namibia, Botswana and Zambia and 10 other
countries gained over 20% of export earnings from solid minerals in comparison to Nigeria's
0.4%, during the same period. The implication of this is that, if the sector is given appropriate
7
considerations, it will enhance economic growth and consequently reduce poverty level in the
country.
3.
Methodology, Data Measurement and Sources
Both Dynamic Ordinary Least Square (DOLS) and Fully Modified Ordinary least Square
(FMOLS) models were used to analyse the impact of different types of solid minerals and
government effectiveness on poverty level in Nigeria. Most studies on poverty rely on monetary
poverty measures such as the headcount index, it has been argued that possessing an increased
income does not necessarily mean an improvement in the well-being of people especially if this
increased income does not translate to accessibility of basic necessities of life. Ravallion (1996)
argued that since poverty is multi-faceted, multiple indicators are necessary including measures
of distribution of real expenditure per adult, access to non-market goods like health and
education, distribution within households and the personal characteristics of the poor. Thus, in
this study, we employed multidimensional approach by using human development indicators (i.e.
longevity, measured by life expectancy at birth which captured the capability of living a long and
healthy life, real per capita income and infant mortality rate that captured the material hardship
aspect of poverty, (see Masud and Yoncheva, 2005; Chirino and Melian, 2006; Morrissey, 2004;
Olofin, 2012). We employed principal component analysis on our human development indicators
to arrive at a single variable used to measure poverty. Government effectiveness is defined as the
perceptions of the quality of the civil service and the degree of interdependence from political
pressures, the quality of policy formulation and implementation and the credibility of
governments’ commitment to such policies. Data were collected from the World Governance
Indicators and Central Bank of Nigeria (CBN) Statistical Bulletin (2014).
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Studies have shown that if series are cointegrated, i.e. given the time series vector ( yt .x t )
with cointegration relationships as stated below:
yt  x  t   d1t  1  1t
(2)
xt  1 d1t  2 d 2t   t
(3)
 t   2t
(4)
Where d1t and d 2 t are deterministic trend regressors. d1t enters both the cointegration equation
and the regressors equations, while d 2 t enters only the regressors equations. 1t is the
cointegrating equation error, while  2t are regressors innovations. Suppose innovation  t =
( 1t ,  2t ) are strictly stationary and ergodic with zero means, contemporaneous covariance
matrix  , one- sided LRCOV matrix . and non-singular LRCOV matrix  .
  
  11 12 
 21  22 

  
'
   E (t , t  j )   11 12  (5)
j 0
21 22 

  
'
   t , t  j   11 12 
j  
21 22 

  E ( t , t )
Ordinary Least Square (OLS) estimator becomes consistent with convergence at a faster rate
than standard. However, if there is long run correlation (LRCOV) between 1t and  2t ( 12 ), or
cross-correlation between cointegration equation error and the regression innovations ( 12 ), OLS
estimation will possess an asymptotic distribution that is non-Gausian, asymptotically biased,
asymmetric and exhibition of non-scalar nuisance parameters. This then implies that
conventional testing process will become invalid. Fully Modified Ordinary Least Square
(FMOLS) as proposed by Phillips and Hansen (1990) and DOLS as proposed bySaikkonen,
9
(1992); Stock and Watson, (1993) could be used to attenuate the problem The estimator is
asymptotically unbiased and have fully efficient normal asymptotic, allowing for standard Wald
ˆ ˆ and 
ˆ are parts of
tests using asymptotic chi squared statistical inference. Suppose ˆ12, 
22,
12
22
the LRCOV respectively, FMOLS can be obtained by transforming the regressors and regressand
and then apply OLS procedures (see The Stata Journal (2012). Thus, in this study we take
advantage of cointegration regression based on LRCOV in STATA software, using both
dynamic OLS and FMOLS and examine the impact of disaggregate solid minerals, government
effectiveness on poverty reduction in Nigeria.
4.
Model Specification.
Based on the findings that solid minerals are capable of increasing economic growth,
reduce unemployment and thereby promote welfare of people, we specify our poverty equation
as:
povertyt= f(totsolidmt, coalt, metaoret, quarothert, goveffectt)
( 1)
Where: totsolidm = total solid minerals; metaore = metal ore; quarother = quarry and others; and
goveffect = government effectiveness.
5. Theoretical Framework of the Study.
Based on the identified causes of poverty and its multifaceted definitions, various
theories of poverty have been discussed in the literature (see Blank, 2003; Goldsmith and
Blakely, 1992; Jennings and Kushnick,1999; Rodgers, 2000; Schiller, 1989; Shaw, 1996). These
theories are: individual-deficiencies theory of poverty which links poverty with individual’s
action (Weber, 2001); cultural belief system theory of poverty which links poverty with people’s
10
culture (Valentine, 1968); economic, political and social discrimination theory of poverty which
links poverty with failure of economic, political and social system to provide equal opportunity
and resources for welfare improvement of people (Rank, Yoon and Hirschl, 2003); geographical
disparity theory which links poverty with differences in geographical location (Shaw, 1996); and
cumulative and cyclical interdependency theory which links individual situations and community
resources; and posits that they are mutually dependent (Bradshaw, 2000). All these theories
support community intervention in eradicating or reducing poverty.
However, this study hinged on cumulative and cyclical interdependency theory of
poverty in the sense that it incorporates other theories one way or the other. The theory has its
origins in the work of Myrdal (1957) where he used the theory of interlocking, circular
interdependence within process of cumulative causation to explain economic underdevelopment
and development. In his study, he explained the close linkage between individuals and
community wellbeing in a cascade of negative consequences, and that when a factory is closed or
other crises occurred, cascade of personal and community problems, including migration of
people from a community may ensue. Therefore, interdependence of factors causing poverty can
accelerate once a cycle of decline occurred. This cycle can also be explained in terms of failure
to secure employment, leading to low consumption spending, low saving, inability to invest in
training and education, disinvestment etc. causing poverty. This chain can lead to deterioration
of self-confidence, depression, hopelessness as well as socially unacceptable behaviors such as
kidnapping, rebellion and other social vices. This shows that various structural and political
factors in the cyclical theory can reinforce each other, with economic factors linked to
community, political and social variables. One thing that should be noted is that the cycle may
not be easy to break because of its complexity. However, studies have suggested that provision
11
of education (which is a means of increasing skills), and policies that enhance gaining both
political and economic power are means by which the cycle can be broken (see Duncan, 1999;
Goldsmith and Blakely, (1992).Considering various government actions at improving the
economy so as to “gain” legitimacy and popular support in the pursuit of poverty reduction
agenda, many policies and programmes such as providing self-employed type of education,
encouraging agriculture, as well as developing mining and other sectors of the economy may be
designed and implemented with the aim of diversifying the economy. This then implies that
government investment in solid minerals sector; and government effectiveness could serve as
important determinants of poverty reduction in Nigeria.
6. Discussion of Results and Recommendations.
Annual time series between 1996 and 2014 were used for the estimation of the study. Before our
regression was carried out, we examined the stationarity of our data and found that they were
I(1) series. The findings from both the FMOLS and DOLS show negative relationship among
poverty and disaggregate solid minerals. These results were statistically significant. However,
there was positive relationship among poverty, government effectiveness and total solid minerals
and the results were statistically significant. The results show that disaggregated solid minerals
are capable of reducing poverty in Nigeria, while government effectiveness and total solid
minerals promote poverty. These findings are presented in Table 2 and Table 3 below. Inability
of government effectiveness to reduce poverty may not be farfetched in a country that is
characterized with high level of corruption. As a matter of fact, Nigeria is highly positioned
among the countries which lack effectiveness. The findings of this study corroborate that of
Adeniyi et al. (2013) and Bridge (2008), although they did not consider government
12
effectiveness in their study. Our study recommends diversification of Nigerian economy towards
solid minerals sector and posits that improvement in government effectiveness could be an
important variable that can be used to achieve poverty reduction in Nigeria.
Table 2
Cointegration Results (FMOLS)
VAR lag(user)
Kernel
= 0
Number of obs = 18
= bartlettR2
=
Bandwidth(neweywest) = 8.9472
S.e.
=
Long run S.e.
=
PovertyCoef.
Adjusted R2
=
.9875161
.1519984
.0578574
Std. Err. z
totsolidm 14.10672 2.552679
coal
.9904535
P>|z|
5.53
-6.20
[95% Conf. Interval]
0.000
19.10987
-15.57357
2.513082
metaore -11.50894
2.619121
-4.39
0.000
-16.64232 -6.375557
quarother-14.05945
2.552693
-5.51
0.000
-19.06264 -9.056263
goveffect 2.124942
.0306001
69.44
0.000
2.064967
Source: Authors
13
0.000
9.103556
-20.49912 -10.64802
2.184918
Table 3:
Co-integration Results (DOLS)
Source
SS
df
MS
Number of obs
=
F(5, 14)
= 2545.226
Model
35.15050243
5
7.0301
Prob> F
=
Residual
.3953326138
14
0.0282
R-square
= .9888782
Total
35.54583504
18
PovertyCoef. Std. Err.
t
0.0000
Adjusted R2
= .9849062
Standard error
= .1680418
1.974768613
P>|t|
[95% Conf. Interval]
Totsolidm
14.95586 2.224442
6.72 0.000
10.1849
coal
-16.40277 2.189133
-7.49 0.000
-21.098 -11.70755
Metaore
-12.39267 2.275651
-5.45 0.000
-17.27345 -7.511881
quarother
-14.90811 2.224721
-6.70 0.000
-19.67967 -10.13656
Goveffect
2.142326
.023145
92.56 0.000
Source: Authors
14
2.092685
19
19.72681
2.191967
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