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TO WHAT EXTENT DOES FINANCIAL SECTOR DEVELOPMENT STIMULATE
NON-OIL GDP GROWTH IN NIGERIA?
By
Frank Iyekoretin OGBEIDE (Ph.D)
Department of Economics and Statistics
University of Benin, P.M.B. 1154, Benin City.
frank.ogbeide@uniben.edu; 08032748574
and
Iyore ASEMOTA
Department of Entrepreneurship
University of Benin, P.M.B. 1154, Benin City.
iyore.asemota@uniben.edu; 07060597237

ABSTRACT
Exploring the finance-growth nexus in an oil-driven economy requires substantial effort to remove the portion of
GDP attributable to hydrocarbon output from the overall output so as to focus on the real productive sector.
Incidentally, this aspect of analysis on finance-growth relationship appears missing in finance literature, and this
paper attempts to fill the gap. Hence, this study examines the relationship between financial development and
Nigeria’s non-oil real GDP using cointegration, error correction and granger causality on data from 1980 to
2014. Johansen cointegration test provides evidence of long-term relationship between non-oil real GDP and its
determinants. Using error correction, the two measures of financial development employed produce mixed effects on
the real economy. Growth in private credit, a measure of volume, spurs non-oil real GDP but wider interest rate
margin, measuring intermediation efficiency hinders it. In addition, the pairwise granger causality test lend support
to the feed-back hypothesis, whereas unidirectional causation runs from interest rate spread to non-oil real GDP.
Based on findings, the study recommends that policies to engender financial development should be carried-out in a
stable macroeconomic environment to guarantee growth of the real economy in the long-run.
JEL Classification Codes: E40, E44, O16.
Keywords: Financial Development, Non-oil GDP, Misery Index, Interest Rate Spread/Margin.
INTRODUCTION
The origin of the finance-growth debate is traceable to Bagehot (1873) who gave a theoretical
discussion on how the financial sector can stimulate the real economy. Other notable contributors to
the finance-growth debate are found in the works of Schumpeter (1911), Hicks (1969), Goldsmith
(1969). McKinnon (1973) and Shaw (1973). Ever since, there have been several studies attempting to
explain the role of financial sector development in stimulating economic growth and findings from
these studies remain inconclusive. However, most economic researchers believe that the presence of
a well-developed financial system stimulates higher economic growth

Vol. 17 No.2

Journal of Monetary and Economic Integration

trajectory because financial institutions serve as an intermediary between the deficit and surplus
economic units in an economy.
In Nigeria, the need to stimulate the non-hydrocarbon real GDP, following the global economic
crisis in the early 1980s, culminated in the adoption of several economic reforms to broaden the
real economy. Nigeria adopted the Structural Adjustment Programme (SAP) designed by the
International Monetary Fund (IMF)/World Bank in 1986 as a productive mechanism to
galvanize the non-oil sector. Financial liberalization, conceived to deepen the financial sector in
Nigeria, was an integral part of the economic reforms initiatives to accelerate the growth
potentials of the private sector. In fact, numerous studies have suggested that liberalizing the
financial system would lead to higher levels of financial development, which support savings
mobilization and lending to economic agents in the real sector. See studies like Anyanwu,
(1995); Oyaromade, (2005); Berube and Cote, (2000); Chinn and Ito, (2002); Bekaert, Harvey
and Lundblad, (2005); Tressel and Detragiache, (2008). These authors aptly demonstrate how
financial system can stimulate economic growth by identifying and funding profitable projects.
After so many years of financial reform process in Nigeria, the productive base of the economy
is still considered weak, and export remains structurally unbalanced in favour of hydrocarbon
production which accounts for about 80% of government revenues (see Anyanwu, et al., 1997;
Iyoha and Oriakhi, 2002; Olofin and Afangideh, 2009). For instance, manufacturing capacity
utilization was as high as 78.7% in the 1970s, but declined as low as 43.8% in the 1980s, while it
fluctuated between 36.1% and 55.5% over 2000 and 2010 periods (see Obadan and Edo, 2004;
CBN, 2010). This trend of manufacturing in Nigeria is at variance with the moderate rise in
trajectory of credit to the private sector of the economy which averaged 9.8% of GDP in 1980s,
but rose to 17.3% in 2001 to 2010 periods, and further to 20.9% between 2011 and 2013.
During these periods, however, gross national output rose in tandem with the flow of credits by
the banking sector, but performance of the non-oil sector remained relatively subdued over the
same period. The above observation raises fundamental question as to what extent financial
sector development, following financial reform in the past three decades in Nigeria, has
stimulated the non-oil sector of the economy.
At the moment, several scholars have explored the impact of financial sector on economic growth
using varying econometric techniques. For a natural resource-driven economy like Nigeria, such
studies may be broadly restrictive for failing to take into cognizance the composition of the country‘s
real output. Nigeria, being rich in natural resources has a fairly large portion of her GDP explained by
activities in the oil industry. Hence, a useful study exploring the finance-growth nexus in Nigeria
should remove the aspect attributable to hydrocarbon output from the overall national output, and
focus on the growth in the real productive sector of the economy. Accordingly, this paper
investigates empirically the finance-growth nexus in Nigeria over a period spanning from 1980 to
2014, with the objective of ascertaining whether financial development has so far stimulated non-oil
real GDP in Nigeria and also develop better understanding of the effect of natural resource
dependence on the productive sector. Dependence on natural resource, for example, has been found
to undermine institutional efficiency which also affects economic structure and growth trajectory
(Edo, 2003; Beck, 2011). This paper contributes to the debate on finance-growth nexus, amidst very
limited studies which tries to ascertain the impact of financial development on non-oil real GDP
from a country specific perspective. In this study also there is an attempt to ascertain the robustness
and sensitivity of the claim that financial development spurs growth, using two different measures of
financial sector development, defined in terms of the

32

level of credit extended to the private sector and interest rate spread to measure financial sector
efficiency.
Meanwhile, this paper is organized into five sections. Following this introductory section,
section two provides a review of relevant literature. Section three discusses theoretical
framework, with methodology and model specification. Section four presents the empirical
results, while the last section contains concluding remarks and policy implications.
LITERATURE REVIEW
Theoretical Literature
Financial development, induced by policies of financial reform policy, tends to influence both
savings and investment decisions. Researchers like, Schumpeter, (1911); McKinnon, (1973);
Shaw, (1973); Greenwood and Jovanovic, (1990); De Gregorio and Guidotti, (1995);
Greenwood and Smith, (1997) contended that well-functioning financial system can promote
overall economic efficiency because it can mobilize higher level of savings, enhance capital
accumulation, transfer resources from traditional (non-growth) sectors to modern growthinducing ones, and also promote a competent entrepreneur response to business opportunities.
Theorists, using endogenous growth models also observed that finance through its positive
impact on savings and capital accumulation accelerates economic growth by providing
information on firms (Diamond and Dybvig, 1983; Pagano, 1993; Romer, 1994; Levine, 1997,
2005) highlights the theoretical literature on the finance-growth relationship, suggesting that
better developed financial systems experience faster economic growth. In his model, financial
systems affect investment and economic growth by providing such functions as facilitating the
trading, hedging, diversifying, and pooling of risks.
However, some authors are skeptical about the validity of finance-growth nexus. The
Conservative Theory of Finance and Growth, mainly the post-Keynesians, argued that the
financial sector may cause aggregate output and growth to in fact decline. Aryeetey (2003) hinted
that financial liberalization (total deregulation of markets), amidst presence of institutional and
structural bottlenecks, may not yield desired economic growth.
Another school, loosely referred to as, the Imperfect Asymmetric Information School often
associated with Jaffee and Russell, (1976); and Stiglitz and Weiss, (1981). They examined the
problem of financial development under asymmetry information and costly credit that results in
credit rationing that could eventually lead to market failure. They believed that government
intervention is only desirable when it removes asymmetry information and transaction costs. In
the presence of asymmetry information, they concluded that the effect of finance on economic
growth would produce mixed outcomes across economies, even among countries with
comparable structural features.
In line, Eggoh and Villieu, (2014) model explained the lack of consensus in the finance-growth
nexus, such that two identical economies that converge on the same balanced growth path will
grow at different rates during the transition phase. The model thus, explained why two countries
with similar fundamentals (for instance, preferences, technology and initial capital and bank loan
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Journal of Monetary and Economic Integration

stocks) might display different correlations between financial development and economic
growth and as such conclusion from their modeling framework shed light on the possibilities
that financial development can either positively or negatively affects economic growth dynamics.
Empirical Literature
A number of economists have provided evidence to show the linkage between the financial
sector and GDP growth. Economies with efficient financial system are found to grow faster
while inefficient financial system bear the risk of failure or negative growth (see Adeniyi, 2006;
Beck 2011; Kurronen, 2012). Nnanna, Englama and Odoko (2004) found a strong relationship
between financial development and economic performance based on the notion that scarcity of
long-term finance is the major obstacle to attaining higher investments and output growth in
developing countries. Green, Kirkpatrick and Murinde, (2006) posited that financial sector by
encouraging micro and small enterprises contribute to poverty reduction and economic growth.
Beck, Demirguc-Kunt, and Maksimovic, (2005) provided evidence that finance is a binding
constraint to firms‘ growth, even for new firms that rely on external sources of finance.
Jalilian and Kirpatrick, (2007) and Odhiambo, (2010) found that financial deepening through
improvement in intermediating efficiency lowers cost and improves access to credit for the
poor. Productivity may improve as the number of unbanked people declines, thereby boosting
economic growth through increased access to funds. Odedokun (1996) and Olofin and
Afangideh (2009) in their study on financial structure and economic growth in Nigeria, using 3stage least square estimation technique for 1970 to 2005 periods, concluded that developed
financial systems alleviate growth-financing constraints by increasing bank credit and investment
activities with resultant rise in output. A study conducted by Khan and Senhadji (2003) confirms
a strong positive and statistically significant relationship between financial depth and growth
using cross sectional analysis covering 1960 to 1999 for 159 countries. King and Levine (1993)
found, using cross-country data for 80 countries over the period 1960-1989, that different
financial indicators have strong and robust correlation with economic growth. Allen and
Ndikumana (1998), using panel technique on data for Southern African Development
Community (SADC), found financial development, defined in terms of level of credit to the
private sector, volume of credit provided by banks and liquid liability of financial system to
positively and significantly influence economic growth.
Mwaura, Ngugi and Njenga, (2009) addresses whether level of financial development are
associated with differences in economic growth from 1984 to 2002, using a sample of thirteen
(13) African countries. They estimated a base-line model of real income per capita, using panel
data technique before financial development variables were progressively introduced. The study
finds that financial development contributes immensely in explaining growth in real income, as
coefficients associated with financial development remained high.
Deidda and Fattouh (2002) establish a non-linear relationship between financial development
and economic growth using dataset of King and Levine (1993a). They found no significant
relationship between financial development and growth in low-income countries, whereas, in
high-income countries, this relationship is positive and significant.
The process of financial intermediation is believed to also help absorb exogenous shocks in the real
sector. Aghion, et al. (2005) confirms the existence of linkages between financial development and
growth volatility, especially in developing countries. Acemoglu and Zilibotti, (1997); Sylvanus

34

and Abayomi, (2001). Ramcharan, (2008) hinted that financial deepening could promote
economic diversification by serving as a counter-cyclical medium to dampen economic
uncertainties. In addition, Greenwald and Stiglitz, (1993) held that efficiency in financial market
mitigates information asymmetries, and as such enables economic agents to process information
more effectively that in turn lowers growth volatility. Ang, (2007) examined the extent to which
financial development contributes to output expansion in Malaysia during the periods between
1960 and 2003. Using augmented neoclassical growth framework and ARDL bounds procedure,
the study posits that aggregate output and its determinants, including financial development,
private capital stocks and labour force are cointegrated in the long-run; and that these variables
exerts a positive impact on economic development. Accumulation of public capital was found to
curtail output expansion in the long run. Ardic and Damar, (2006), using both OLS and dynamic
panel GMM techniques, showed that financial deepening (proxy by ratio of total deposit
received by the banking sector to GDP) has a positive and significant impact on growth rate of
real GDP per capita in selected provinces in Turkey over 1996 to 2001 periods.
However, some authors are also skeptical about the validity of the positive effect of finance on
economic growth see DeGregorio and Guidotti, 1995. In line, DeGregorio et al (1995) observed that
financial development significantly reduces economic growth in Latin America countries during
episodes of spiraling inflationary tendencies. Bayoumi, (1993), using UK data from 1971 to 1988,
observed an inverse relationship between financial liberalization, which involves the relaxation of
credit constraints, and savings pattern in the banking system. The study posits that by removing
constraints to borrowing, economic agents would likely raise their consumption rate, rather than
savings, which thus negatively affect the capacity of financial system to provide credit to investors in
the real economy. Agca, De Nicolo and Detragiache, (2008) highlighted that financial liberalisation
has not succeeded in improving access to credit at lower cost of funds in emerging markets, but such
strategy led to higher leverage in companies in advanced countries.
Study by Demetriades and Law (2006) showed that financial depth does not affect growth in
economies with fragile institutions. Allen and Gale (2000) examined the financial structure of
Germany, Japan, UK and the United States and found that bank-based systems offer better risk
sharing services than markets-based ones. Demirgüç-Kunt and Levine, (2001) argued that countries
with weak legal institutions tend to have bank-oriented financial systems rather than market oriented
ones. Demirgüç-Kunt and Levine, (1996) show that developing countries have less developed banks
and stock markets, but more bank-based; whereas developed countries financial sector are larger,
more active and efficient. Demirgüç-Kunt and Huizinga, (2000) argued that financial structure has
important implications for bank profitability and margins, hence long-run economic growth. Tadesse,
(2002) shows that although market-based systems outperform bank-based systems among countries
with developed financial sectors, bank-based systems are superior to market-based systems among
countries with underdeveloped financial sectors. Beck, Levine and Loayza, (2000), however, finds no
evidence of differences between the two financial systems (market-based or bank-based systems) in
terms of influence on economic growth.
Interestingly, Serhan and Mohammad (2013) study is among the very few empirical studies relating
effects of finance on non-oil sector. The study reported a lack of long-run relationship between
financial intermediation and non-hydrocarbon output growth. The OLS estimation shows that
financial development has a statistically significant negative effect on real non-hydrocarbon GDP per
capita growth. Beck (2011) found that banking systems are smaller in resource-based economies and
that stock markets are less liquid due to lower trading activities, thus limiting the

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Vol. 17 No.2

Journal of Monetary and Economic Integration

level of investment and growth. His study essentially provided evidence of resource curse in the
financial development, which in turn limits private sector-led economic diversification.
Furthermore, Bakwena and Bodman (2010) argued that credit to the private sector in resource
dependent nations often lagged behind what is obtainable among resource-poor countries. The
study concluded that financial institution is highly dependent on the nature of export
commodity. They carried out the analysis of the role of financial development in oil and non-oil
(mining) economies using a traditional panel data and GMM approaches.
Fink, Haiss and Mantler, (2005), using a sample of 33 countries (11 transition economies and 22
market economies), found that financial development has positive growth effects in the shortrun, rather than in the long-run. Fink, et al. (2005) investigated the impact of the credit, bond
and stock segments in nine (9) European Union (EU)-accession countries over the early
transition years (1996–2000) and compared these to mature market economies and to countries
at an intermediate stage. They found that the transmission mechanisms differ, and that financial
market segments with links to the public sector (but not to stock markets) contributed to
economic stability and growth in the transition economies.
Findings on causality between financial development and growth have been sharply debated in the
literature, and four schools of thoughts are discernible (Greenwood and Smith, 1997). Studies, like
Fry (1989), Roubini and Sala-i-Martin, (1992), King and Levine, (1993); Arestis and Demetriades,
(1997); Rousseau and Wachtel, (2000); Levine, Loayza and Beck, (2000); Enisan and Olufisayo,
(2009); Hassan, Sanchez and Yu, (2011) support the supply-leading hypothesis that financial
development causes economic growth; while Jung, (1986); Liang and Teng, (2006); and Odhiambo;
(2009); allude to the demand-following hypothesis, implying finance follows where enterprise leads.
Bi-directional link (feedback hypothesis) was found in studies by Lewis, (1955); Demetriades and
Luintel, (1996); Luintel and Khan, (1999); Al-Yousif, (2002), Ang, 2008; Pradhan, 2011 while results
obtained by Lucas, (1988); Eng and Habibullah, (2011) dismissed finance as an over-stressed
determinant of economic growth1. To these authors, financial intermediation does not play an
important role in economic development process. These divergent views amongst economists
indicate that the finance-growth debate is far from over.

BASIC THEORY, MODEL SPECIFICATION AND METHODOLOGY
The framework for the study begins with the traditional Cobb-Douglas (CD) production
function. Labour and capital play significant role as inputs in generating desired output, and also
on equilibrium growth rates.
Y = f(K, L) = AK L

1

where 0 <α < 1 ……………… (1)
t

t

The CD function was modified by including finance into the equation as input in producing
output. This choice of modeling is based on the fact that financial intermediation is a veritable

1Kitchen (1986) termed this view ‗casino hypothesis‘ referring to scholars that do not consider

the activities of the financial sector as important for economic development.

36

input2 that translates into economy-wide benefits see McKinnon (1973); Shaw (1973); Diamond
and Dybvig (1983); Greenwood and Jovanovic (1990); Greenwood and Smith (1997); Levine
(1997, 2005); Beck (2011); Kurronen 2012). These researchers aptly demonstrated that financial
sector through its intermediating role helps to mobilize savings, and thus provide investors with
the required funds for investment, thereby improving economic growth trajectory. Hence,
financial development enters the CD function as indicated in equation 1. Taking into account
other key determinants of output from extant literature and for the Nigerian case, we provide an
extensive version of equation 1 to include natural resource dependence (NRR), which is a major
economic factor in most developing economies, Nigeria inclusive. See Equation 2.

Ytf FinD, K, L, NRR .............................................................................................

(2)

Where: Y is the output (measured by non-hydrocarbon GDP growth); FinD represent financial development,
measured by private sector credit as well as interest rate spread to account for financial sector efficiency); L is
Labour; K is stock of capital (investment); while NRR captures natural resources dependency, measured by
natural resource rent.
We also included a variable to account for the macroeconomic policy environment in our
model, captured by the misery index (MI), and computed by a simple summation of fiscal
deficit, unemployment rate and inflation rate. MI, thus reflects the extent of macroeconomic
instability in the country. The fact that fiscal environment is far more dominant in the country;
we added government capital expenditure (GCE) to the equation in show fiscal
stance/government size in line with extant literature.

Ytf FinD, K, L, NRR, MI , GCE ...................................................................................

(3)

Where: MI is misery index; GCE is government capital expenditure (employed as proxy for government size).
Other variables were earlier defined.
MODEL SPECIFICATION
In order to ascertain whether financial development has improved non-oil sector performance
in the Nigeria, a specific econometric form of Equation 3 in natural log-form including a
constant and error term is specified in Equation 4.

InRNGDP

0

1 In

FinDt

2 In

Kt

3 In

Lt

4 In
5

NRRt

In MI t

6 In

GCEt

t

.......(4)

2 Some theorists like Newlyn and Avramides, (1977) believes that financial sector can be ranked

pari passu with other numerous inputs in the production process.

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Journal of Monetary and Economic Integration

Where: InRNGDP is measured by non-hydrocarbon real GDP;

In FinDt

is financial development;

captured by two different measures of financial sector performance, namely domestic credit to private sector (DCPS)3
and interest rate spread (INTSP)4. In Kt is the growth of domestic investment; In Lt represents human

capital development, measured by secondary school enrolment rate; In
to capture economic structure;

In MI

t is macroeconomic

NRRt is growth in natural resource rent
instability, In GCEt is growth in government

capital expenditure, representing fiscal policy stance/government size, is the error term at period t.
ECONOMETRIC METHODOLOGY
The analysis begins with ascertaining the order of integration of the variables employed to avoid
spurious regression. This study uses the Augmented Dickey Fuller (ADF) technique to conduct test
of stationarity of each variable and is preferred over PP test (Philips and Perron, 1988) because it is
more reliable and superior for time series with autoregressive structure as it enhances white noise
residuals in the regression (DeJong et al., 1992; and Patra and Poshakwale, 2006). The null hypothesis
of the ADF test is stationarity, hence failure to reject at a given critical value implies existence of unit
root in the series. The test of cointegration is the second step after ascertaining the existence of unit
root, and this step involves investigating the existence of a long-run relationship amongst the
variables. Accordingly, Asteriou and Hall, (2007) noted that if two or more variables are cointegrated
in the long-term, they may drift at random from each other in the short run, but will ultimately return
simultaneously to equilibrium in the long run so that any disturbances in the short-run will be
corrected overtime. Engel and Granger (1987) noted that if two time series variables, pt and qt, are
both non-stationary in levels but stationary in first-differences, that is, both are I(1), then there could
be a linear combination of pt and qt, which is stationary. The time series variables that satisfy this
requirement are deemed to be cointegrated. Johansen (1988) maximum likelihood approach to
cointegration was employed because it circumvents the use of two-step estimators and serious
problems that cannot be resolved in the Engle and Granger single-equation framework. The optimal
lag length is determined by using Akaike Information Criterion and Schwartz Criterion. Also, we
evaluated the impact of financial development on non-oil real GDP in an error-correction modeling
(ECM) platform. The ECM coefficient reveals the speed of adjustment to long-run equilibrium from
a possible short-run distortion. Time-series data for the period from 1980 to 2014 was extracted from
Nigeria‘s

National Bureau of Statistics (NBS), Central Bank of Nigeria (CBN), the International Monetary
Fund (IMF) and the World Bank.
3 Private credit-to-GDP is preferred to other measures of financial development in most
influential studies because it shows the extent to which the private sector relies on the financial
system for funds and also for excluding credit to the public sector (see Demetriades and
Hussein, 1996; Tressel and Detragiache, 2008).

4 Interest rate spread measures the difference between lending and deposit interest rates; and is
often used to show financial sector efficiency (See Koivu, 2002). A wide spread negatively affect
investment in productive activities.

38

DISCUSSION OF EMPIRICAL RESULTS
In this section, we report the results of the estimated model and diagnostic test of the time series
properties of variables was also evaluated.
Testing for Stationarity
The ADF unit-root test is used to check if the variables are stationary, and the proper lags in the
tests was determined using the Akaike Information Criterion (AIC). The results are presented in
Table 1. From the results, we accept the hypothesis that the variables possess unit roots. Indeed,
the variables are integrated of order one, I (1).
Table 1: Results of Unit Root Test: 1970 – 2014
Variables

ADF Test
Statistic

95% Critical ADF
Value

Order of Integration

∆RNHGDP

-3.24

-3.52

I(1)

∆DCPS

-2.09

-3.52

I(1)

∆INTSP

-2.88

-3.52

I(1)

∆NR

-2.06

-3.52

I(1)

∆MI

-3.27

-3.52

I(1)

∆INV

-2.91

-3.52

I(1)

∆SSE

-2.83

-3.52

I(1)

∆GCE
-1.79
Source: Author‘s computation

-3.52

I(1)

Cointegration and Johansen (Multivariate) Test
Having established that the series in the analysis are not stationary at levels but first difference, we
proceeded to determine if a long-run meaningful relationship exist among used variables. All
variables are integrated of the same order, thus satisfying a critical requirement for adopting Johansen
multivariate cointegration test procedure. The cointegrated results are summarized in Table 2. From
the result, the trace and maximum eigen value statistics revealed the existence of at most three (3)
meaningful long-run equilibrium equations between non-oil real GDP and its determinants at the 5%
significance level, thus rejecting the null hypothesis of non-cointegration.

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Journal of Monetary and Economic Integration

Table 2: Unrestricted Cointegration Rank Test (Trace and Maximum Eigenvalue)

Hypothesi
zed
No of
CE(s)
None*
At most 1*
At most 2*
At most 3
At most 4
At most 5

Eige
n
value
0.921
9
0.800
1
0.733
2
0.265
9
0.195
3
0.130
1

Trace
Statisti
c
209.043
8
122.325
9

5%
Critica
l Value
103.847
3

Prob**

76.9727

0.0000

67.5724

54.0791

0.0020

22.6382

35.1927

0.5525

12.1268

20.2618

0.4375

4.7378

9.1645

0.3134

0.0000

Eige
n
value
0.921
9
0.800
1
0.733
2
0.265
9
0.195
3
0.130
1

Maxim
um
Eigen
value

7.3891

5%
Critic
al
Value
40.956
8
34.805
9
28.588
1
22.299
6
15.892
1

4.7379

9.1645

86.7179
54.7534
44.9342
10.5113

Prob*
*
0.0000
0.0001
0.0002
0.7932
0.6218
0.3134

**MacKinnon-Haug-Michelis (1999) p-values
Source: Author’s Computation
The Short Run (ECM) Results

The results of the estimation employing the error-correction modeling framework are presented
in Table 3. The adjusted R2 of the estimated model shows variations in real non-oil GDP is
explained by the combined effects of all the determinants while the F-statistics shows that the
overall model is highly significant at the 1% level. Also, standard error of the equation is
minimal indicating small distance between predicted and actual values of real non-oil GDP. The
DW statistic of 1.94 indicates absence of first-order autocorrelation in the model.
As shown in Table 3, growth in bank credit to the private sector exerts very significant positive
influence on the level of output growth in non-oil sector. The coefficient of interest rate spread,
a measure of financial efficiency, was observed to be negative and significant at the 10% level.
This shows that a wide gap between lending and deposit rates increases cost of funds, with
potential destabilizing effects on investment, employment and production in the real economy.
It can be observed that both measures of financial development employed in this study show
different impact on the real sector, indicating that financial sector does not have innately
growth-inducing force. Another interesting result from the study is that growth in rent collected
from natural resources negatively influence real non-hydrocarbon GDP growth, providing
evidence of resource-curse, though the coefficient was not significant at known conventional
tests level. Growth in domestic investment and government capital expenditure (representing
government size) both positively raise real economic activities as documented in extant
literature, but only domestic investment was significant at the 10% level.
Generally, increasing an economy's capital stock also increases its capacity for production, which
means an economy can produce more. Misery index, a measure of macroeconomic instability, is

40

found to be significant at the 5% level and influence is negative. This finding suggests that
unstable macroeconomic environment remains destructive to production in the real economy.
Unexpectedly, increases in secondary school enrolment (human capital development) have a
negative and significant influence on real non-oil GDP. Possible explanation may be poor
incentive structure to attract labour to the sector, and perhaps, the prevalence of wide-spread
brain-drain that limits innovation and investment, hence real production. The coefficient of the
error correction term has the expected negative sign and is significant at the 5% level, with a
relatively high speed of adjustment to long-run equilibrium of 62.2%. This shows that 62.2%
short-run divergences are recovered annually, which implies that it will take almost two (2) years
for any disequilibrium in the system to be fully restored.

Table 3: The dependent variable is real non-oil GDP growth.
Variable

Coefficient

t-Statistic

Constant

0.587

0.88

0.39

Domestic Credit/GDP (∆DCPS)

0.0015

5.76

0.0004***

Interest Rate Spread (∆INTSP)

-0.343

-1.85

0.0614*

Natural Resource Rent (∆NRR)

-0.495

-0.52

0.6671

Misery Index (∆MI)

-0.054

-2.33

0.0301**

Gross Investment (∆GI)

0.112

1.76

0.086*

Govt Capital Expenditure (∆GCE)

0.001

1.22

0.104

Secondary Enrolment(∆SER)

-0.065

3.51

0.012**

ECM(-1)

-0.6224

-2.74

0.0116**

R-Squared
Adjusted R-Squared

0.69742
0.67323

Prob.

Mean dependent var

0.100522

S.D. dependent var

0.857431

S.E. of Regression

0.70538

Akaike info criterion

1.396033

Sum squared Resid
Log likelihood

11.44392
-29.73257

Schwarz criterion
Durbin-Watson stat

1.568898
1.943363

*Significant at 10%, **Significant at 5%, ***Significant at 1%.
Source: Author’s Computation
Granger Causality Tests
We ascertain the interrelationships between the two main variables of focus in this study, which is
finance and non-oil real GDP nexus, using granger-causality test procedure. Causality, thus exist, in
the long-run only when the coefficient of the cointegrating vector is statistically significant and
different from zero (Granger and Lin, 1995). The general form of the model tested in an errorcorrection-based framework using granger-causality test is presented in Equations 5 and 6.

41

Vol. 17 No.2

Journal of Monetary and Economic Integration

m

InRNHGDPt

01,i

InCRPSt

t

i

i 0

(5)

m

InCRPSt

01,i

InRNHGDPt

i

t

i 0
m

InRNHGDP
t

0

InINTSP

1,i

t i

t

i 0

(6)

m

InINTSPt0

1,i

InRNHGDPt

i

t

i 0

Table 4 presents the results of the pair wise granger causality analysis between measures of
financial development and non-oil real GDP growth. The decision rule is that when the Chisquare has a probability value which is significant at conventional test levels would denote the
rejection of the null hypothesis. From the results, bi-directional causation exists between non-oil
real GDP (RNHGDP) and domestic credit to the private sector (DCPS). This indicates the
existence of reciprocal externality between the financial and real sectors. On the other hand, a
unidirectional causation runs from interest rate spread (INTSP), a measure of financial sector
efficiency, to non-oil real GDP (RNHGDP), but not in the opposite direction. This suggests
that inefficiencies in financial sector intermediation have remarkable influence on the real sector.
These sets of outcome support findings from the impact analysis relating to the diverging
outcomes of financial development measures (private credit and interest rate spread) on the real
economy which thus pose a challenge for monetary authorities in Nigeria to both monitor the
volume of credit as well as efficiency of financial intermediation process.
Table 4: Granger Causality Test
ChiNull Hypothesis
Statistic
Prob.

Decision

RNHGDP does not Granger Cause DCPS

6.73091

0.0013***

Do not accept

DCPS does not Granger Cause RNHGDP

2.98393

0.0352**

Do not accept

RNHGDP does not Granger Cause INTSP

0.10225

0.9028

Do not reject

INTSP does not Granger Cause RNHGDP
1.89393
*Significant at 10%, **Significant at 5%, ***Significant at 1%.
Source: Author’s Computation

0.0683*

Do not accept

42

Stability Test Analysis
The plots of the cumulative sum of recursive residuals (CUSUM) and cumulative sum of squares
of recursive residuals (CUSUMSQ) stability tests are shown below and close observation
indicates that all the parameters of the estimated regression are stable over the study period as
they fall within the 5% critical bound.
Plots of the Cumulative Sum of Recursive Residual (CUSUM)
16
12
8
4
0
-4
-8
-12
-16
86

8890

92

94

96

98

00

0204

CUSUM

06

08

10

5% Signific anc e

Plots of the Cumulative Sum of Squares of Recursive Residual (CUSUMSq)
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0
-0. 2
-0. 4
92

94

96

98

00

02

CUS UM of S quares

04

06

08

10

12

5% S ignific anc e

CONCLUSIONS AND POLICY IMPLICATIONS
This paper examined the impact of financial sector development on real non-hydrocarbon GDP
growth in Nigeria over the last few decades using cointegration, error correction methodology and
granger causality. From the findings, the following conclusions are discernible. It was found that
increases in interest rate spread, natural resource rent, macroeconomic instability and secondary
school enrolment have short-run destabilizing effects on real economy, whereas growth in private
sector credits, domestic investment and government capital expenditure support it. Result shows that
62.2 percent short-run divergences are recovered annually, which implies non-oil sector have quick
adjustment process to restore long-run equilibrium. This may mean that the current poor outcome of
the sector could be attributed to structural and institutional bottlenecks such that any effort to
develop the non-oil sector of the economy would quickly pay-off in a short period. Overall, it can be
noted that the two measures of financial development used in this study, namely private credit and
interest rate spread, had differing impact on the real economy, revealing the need for monetary
authorities to adopt holistic approach to setting prudential guidelines to

43

Vol. 17 No.2

Journal of Monetary and Economic Integration

not just improve the volume of credit to the real economy but also be mindful of the efficiency
of financial intermediations. Additionally, results from the granger-causality test has lend
support to conclusions in extant literature that the finance-growth relationship depend on the
kind of indicators used to represent financial development, as well as methodology and
economic structure of countries under study. There is also the need for government to make
conscious effort at limiting the current dependence on hydrocarbon industry for fiscal
sustenance, create conducive macroeconomic environment that enhances real production, while
also ensuring that human resources are given the right kind of training that support higher levels
of economic activities in the non-oil sector of the economy.

44

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