Download Financial Dualism, the Informal Sector and Economic Growth: An

International Journal of Empirical Finance
Vol. 4, No. 7, 2015, 467-478
Financial Dualism, the Informal Sector and Economic Growth: An
Econometric Investigation of the Nigerian Evidence
Ebele P. Ifionu1, Reginald C. Ibe2
Abstract
This study empirically examined the impact of the informal financial sector on economic growth in Nigeria
from 1981-2013. The stationarity of the variables in the model were first tested via the Augmented DickeyFuller (ADF) and Phillip Perron (PP) unit root tests and results indicate that all variables were integrated in
the order of I (1). Having confirmed the stationarity of the variables (GDPPC, DFIND, INSEC, RINTR, and
TSAV),the analyses was pushed further to determine the long-run equilibrium relationship between the
variables in the model by using the trace statistics test and the maximum eigenvalue test of the Johansen
multivariate cointegration test after the order of linear deterministic trend. The informal financial sector
impacts negatively on gross domestic product per-capita in Nigeria. Other variables that impact negatively on
GDP are real interest rate, degree of financial depth while total savings has a positive but insignificant
relationship. A major policy recommendation which drawn from the above findings is that the linkage
between the formal and informal sectors in Nigeria should be strengthened towards full elimination of
dualistic market. Deposit money banks and the monetary authority should evolve policies aimed at reaching
the unbanked informal sector agents, especially the rural households and the urban informal production units.
This will deepen the financial sector and assist in mobilizing the much needed savings that will engender
investment and growth in the economy.
Key words: Osusu, Financial Depth, Financial Sector unit root; cointegration, heteroskedasticity.
1. Introduction
The Nigerian financial system is characterized by the coexistence of two seemingly parallel financial
sectors with little or weak linkage sharing the market in a manner similar to that of oligopolistic competition.
This situation is called financial dualism. The two sectors are characterized by different levels of
development, technology, patterns of patronages, and more importantly interest rate (price) setting. The
formal financial institutions comprise the deposit money banks, merchant banks as well as the micro-finance
banks which are all involved in mobilizing funds and creating credits in the economy. The informal groups
operate at the lower end of the market and are usually developed towards satisfying specific financial needs
of its members. There has been a growing concern among economists, researchers and policy makers in
Nigeria over the relatively low savings rate in Nigeria. This concern is due to several reasons. First, domestic
savings is of vital importance in the sustenance and reinforcement of the savings-investment-growth chain in
developing economies (Nwachukwu, 2011). Second, countries that save more tend to grow faster, provided
that their financial system is deep (World Bank, 1989). Third, increasing savings and ensuring that they are
directed to productive investment are central to accelerating economic growth and development (United
Nations, 2005). Furthermore, higher savings leads to capital accumulation, which in turn leads to economic
growth and development. Therefore, the importance of savings in the overall growth and development of the
economy cannot be over emphasized. In Nigeria, financial institutions such as deposit money banks (DMBs)
are the main agents of savings mobilization and to effectively mobilize deposits, the deposit money banks
1
2
University of Port Harcourt
University of Port Harcourt
© 2015 Research Academy of Social Sciences
http://www.rassweb.com
467
E. P. Ifionu & R. C Ibe
should offer relatively high deposit rates while inflation rate is stable. Unfortunately, the deposit rates offered
by banks in Nigeria have been generally low in the last five decades with an average of 9%; while inflation
rate has been relatively high with an average of 19% in the last decade. A trend analysis of the ratio of total
savings to GDP in Nigeria shows that the savings rate has been fluctuating. For example, the savings/GDP
ratio in 1960 was 2%. It increased to 7.8% and 11.6% in 1970 and 1980, respectively. In 1990 and 2000, it
declined to 11.1% and 8.4% respectively. In 2011, the savings/GDP ratio in Nigeria stood at 17.4% (CBN,
2011).
Clearly, the relatively poor rates at which domestic savings in Nigeria is growing is a source of worry to
policy makers in Nigeria. Recent empirical evidences in Nigeria point to a growing informal sector (Oduh et
al, 2008; Ariyo & Bekoe, 2012; Ogbuabor & Malaolu, 2013). This hampers the savings mobilization efforts
of deposit money banks and other financial institutions in Nigeria because most informal sector transactions
are conducted in cash to avoid official detection (Oduh et. al, 2008; Buehn & Schneider, 2008). Recognizing
the significance of the informal financial system, the Nigerian government has devised measures that could
help in integrating the transactions at this level into the formal system so as to bring about rapid and
sustainable development of the economy. They include establishment of Peoples bank and Community banks
in the rural areas of the country. Others are the Better Life for Rural Women (BLP) and the Family
Economic Advancement Programme (FEAP). Though it is often difficult to regulate activities of the informal
sector, however, a strengthened supervision of the formal financial system could have linkage effects on the
informal sector especially on the part of the clientele, which makes the transactions at this level enormous.
The informal institutions assist in mobilizing savings for rural development; but what appear unsettled
concerns such issues as the degree of relative effectiveness of the two types of financial sectors in mobilizing
funds for development and, the effectiveness of the strategies and mechanism of credit mobilization,
allocation and utilization for clearly defined objectives. Though some of these issues have been addressed
somehow in such studies as Aluko (1980), Chandanvaker (1985), Falegan (1987) and Akanji (1994); their
findings are still inconclusive and requires further investigation on more recent data. Clearly, one question
that remains unanswered is the relationship between the informal sector and its contribution to economic
growth in Nigeria. Providing an answer to this question through scientific analysis represents a viable
approach to supporting economic policies for integrating the formal and informal sectors thereby eliminating
dualistic markets. Herein, lies the motivation for this study which examined empirically, the relationship
between the informal financial sector and economic growth over the period 1981 – 2013. Furthermore, this
study will deepen our understanding of the phenomenon called financial dualism, informal financial sector
and its contribution towards promoting savings, investment and economic growth in Nigeria.
For ease of analyses and presentation, the rest of this study is structured as follows; Section 2 presents
the analytical framework, a review of related literature, nature of the informal financial sector in Nigeria.
Section 3 is research methodology which identifies the variables and model specification for the study.
Empirical findings and analyses are discussed in section 4. Conclusion and recommendation is in section 5.
2. Literature Review
The Analytical Framework
A careful examination of the views that established the basics on which the reforms in the formal
financial sector was carried out can not only embrace the informal financial system but also meaningfully
integrate them for the benefit of the entire society. Thus, the McKinnon (1973) and Shaw (1973) analytical
framework will be helpful in achieving this. The framework is rooted on the premise that growth in an
economy depends strongly on the strength and depth of the financial sector (Adam 1998; Ezirim and
Muoghalu; 2004; Adam, 2005; Raza. 2015). In this relationship, consumption and investment are both
influenced by interest rate, as individuals and other economic agents consider between current and future
consumptions. It portrays an inverse relationship between interest rate and the demand for loanable funds.
Therefore, allowing the markets to determine the allocation of credits with real interest rate moving towards
equilibrium, funds with high-level rate would be avoided by investors and lenders would not fancy the trend,
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International Journal of Empirical Finance
so interest rate will drop, ceteris paribus. A viable formal sector will help in integrating the informal sector as
public confidence is guaranteed; those in the informal financial sector will be encouraged to channel most of
their activities to the formal system, as the fear of losing their hard-earned income during bank failure
becomes almost non-existent.
The Nature of the Informal Financial Sector in Nigeria
The informal financial sector generally entails financial activities that occur outside the immediate
control of government agencies. It involves those financial transactions that operate without official
regulations, conventions and polices. Even when they do; they are not compelled by any possible means to
render official returns on its operations or processes. Thus, informal sector activities generally consist of
enterprises, which render no account to any regulatory agent. They are not fully organized, but they play
essential roles in the economy (UNDP, 1997). In Nigeria, there are a lot of intermediary functions in the
informal financial sector. The "Esu-Esu" scheme is the most developed and widely practiced financial
intermediation; it is a system that targets the low-income, artisans and petty-traders in the country. The Esusu
system is a kind of savings mobilization strategy which operates as a revolving scheme that continues until
each member has benefited from the scheme and is seen to be capable of offering a more promising solution
to people’s financial problems than do the commercial banks (Falegan, 1987). The preference of many
people to save through the Esusu scheme without any interest earnings appears irrational to those who do not
understand the actual functioning of the benefit of the insurance element in the system, a ready access to the
use of funds in lump sums than individuals would have been able to make available on their own. As
explained by Bascom (1982), Esusu has features which resemble a credit union, an insurance scheme and a
savings club, but it is distinct from all these. It is a fund to which a group of individuals make fixed
contributions of money at fixed intervals. The total amount contributed by the entire group is assigned to
each of the members by rotation. ‘Esusu’ is different from a club in that many Esusu groups hold no
meetings and members are not frequently known to one another. ‘Esusu’ thus refers to fund not members.
The Esusu arrangement is helpful in business finance because it provides members or contributors with a
lump sum that can be employed in their business and it is usually easy to obtain one’s collection well in
advance of one’s turn if there is an urgent need for business investment or other expenditure. Personal
savings of loans and grants from parents, relations and friend are another major source of finance in Nigeria.
Most businesses do not qualify (due to size and bad organization) for commercial loans from the formal
institutions and so have relied on the informal market for finance. Bouman (1978) explained that the major
benefits of the Esusu saving scheme include closeness, accessibility, simple procedures, flexibility and
adaptability to many purposes. This easy access contrasts with the formal finance institutions to which large
segments of rural population have no access at all while many others find access difficult. Thus, these
attributes make the informal sector popular among many small savers in both the urban commercial
environment as well as the rural areas however; the modalities of operation vary from locality to locality
(Akanji, 1994).
Another type of informal financial institution used as savings strategy which is prominent is the Daily
Contribution Scheme. It is a scheme where people unknown to themselves contribute varying amounts daily
to an organizer (collector). The money is kept in safe custody for the contributors (from which the collector
can grant short-term loan) till the end of the month when he returns the amount contributed less a day’s
contribution as commission that is equivalent to about 3 percent of the monthly contribution. The collector of
funds comes around daily to collect the funds of the people who are interested in engaging in this scheme.
The monies collected are determined by the amount of money that can be spared by the contributor, although
the initial contribution determines the amount that will be contributed daily. According to Steel and Aryeetey
(1994), a market woman typically sees her ‘banker’ every day to deposit as little as 10 percent of her daily
income. At the end of the month, she get back her accumulated savings, with which she replenishes her stock
or buys something that she could not afford out of one day’s profits. This scheme is advantageous in that the
contributor can borrow against his/her accumulated savings even before the end of the month. This is one of
the important roles of the informal financial sector in filling the gap created by orthodox banks. Whether or
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E. P. Ifionu & R. C Ibe
not the accumulated savings can be collected the same day, like banks depends on where the request is made,
the amount involved, and the safe-custody the collector uses. Another advantage of the scheme is that it
makes savings easy since the amount contributed is usually small, though the contributions can accrue to a
fairly bulky amount later; it requires no waste of time and substantial transportation cost. Steel and Aryeetey
(1994) further pointed out that the collectors differ from a community bank and group-based organizations in
that they are individual entrepreneurs who perform financial service without any capital of their own.
Another informal financial mechanism that exists in Nigeria is the money lending business (UNDP,
1997). It is an age-old system of financial intermediation channeling funds from areas of surplus to areas of
need. This informal transaction ranges from an interest-free close family transfer to interest loan guarantee of
the notable moneylender. Again, this type of business is outside the formal regulation of state institutions, yet
they play very important role in the economy. The transaction is purely based on confidence and, trust
between the parties to the transaction (Duruji and Osabuohien, 2005). Many non-governmental organizations
(NGOs) exist, which engage in financial intermediation, acting as intermediaries between the formal finance
institutions and the borrowers. Most of them undertake their savings and lending on the principles of selfhelp. Examples of such groups include the Community Development Trust Fund (CDTF) in Lagos, the
Community Women Association of Nigeria (CWAN) in Ondo State, the Live Above Poverty (LAPD) in Edo
State, the Farmers Development Union (FADU) in Oyo State, and the Women Farmers Association
(WAFAN) in Kano State among others. They all exist with the purpose of channeling surplus funds into
investible areas in the economy and make access to credit less difficult (UNDP, 1997; Okafor, 2000; Umoh
and Ekpo, 2005).
The fourth major type of informal savings strategy is the professional traders association. Members of
the traders association are those sellers, dealing in the same types of business or those operating in the same
market place. Their main objective is to help members in their time of need and protect the interest of their
members. Members make contribution weekly or monthly and the money collected is disbursed to members
in form of loan at concessionary interest rate. The loan must, however, be repaid together with its interest at
the end of the year.
Lastly, Cooperative thrift and credit societies that appear to be the most standardized informal financial
institution with well-organized savings mobilization strategy in the informal market is also prominent in the
rural economy. The objective of this category of institution is mainly to provide savings facilities and
granting short-term loans to members in various firms. The sources of funds of the cooperative include
shares, special savings, entrance fees and dues. Entrance fees and weekly dues are used for the administration
of these societies. Shares held by members represent the main source of the loanable funds. The special
savings may be shared at a particular time or distributed in rotation, while loans are given to members on
personal recognition and, or, guarantors could be demanded if the members total financial holding in the
society is inadequate.
3. Methodology
The authors hypothesize that there is a relationship between Gross domestic product per capita
(GDPPC) the dependent variable and (DFIND, INSEC, RINTR, TSAV) the independent variables. This
study covered the period 1981 to 2013 (a total of 33 observations) based on the availability of data. The
functional form on which our econometric model is given as:
Y = f (X1, X2, X3, X4)
This can be specifically stated as follows:
GDPPC = f (DFIND, INSEC, RINTR, TSAV)
Eq. (1)
The above model is specified linearly in the form of an equation as follows:
GDPPC = β0 +β1DFIND + β2INSEC + β3RINTR + β4TSAV + Ut
Eq. (2)
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International Journal of Empirical Finance
Where:
GDPPC = Growth rate of real gross domestic product per capita
DFIND = Degree of financial depth (proxied by ratio of broad money (M2) to GDP
INSEC = Growth rate of the size of the informal financial sector in Nigeria
RINTR = Real interest rate (nominal interest rate minus inflation rate)
TSAV = Total savings to GDP ratio
β0 = is the slope
β1, β2, β3, β4 = are the coefficients
Ut = is the stochastic error term
A priori expectations, β1, β2, β4 > 0, β3 < 0
4. Presentation of Results and Discussion
Table 4.1: Augmented Dickey-Fuller (ADF) and Phillips Perron (PP) Unit Root Test Results
VARIABLES
GDPPC
5%
DFIND
5%
INSEC
5%
RINTR
5%
TSAV
5%
-
ADF Test-STATS
-4.697983
-2.960411
-4.697983
-2.960411
-4.697983
-2.960411
-5.856853
-2.960411
-5.936698
-2.960411
PP Test-Stats
-4.702006
-2.960411
-4.702006
-2.960411
-4.702006
-2.960411
-9.264583
-2.960411
-6.556826
-2.960411
Status
I (1)
I (1)
I (1)
I (1)
I (1)
Source: Authors compilation from EVIEWS 7.0 printout
Table 4.1 depicts the results of the unit root tests of the variables: GDPPC, DFIND, INSEC, RINTR and
TSAV. As shown, the results of the Augmented Dickey-Fuller (ADF) and Phillips Perron (PP) test statistics
indicate the absence of unit root among the variables. This suggests that they are integrated I (1) at 5%
significance level since the critical values are less than the test statistics in absolute terms, and thus we reject
the hypotheses of no stationarity in all the cases (Raza et al., 2015)
Cointegration between GDPPC, DFIND, INSEC, RINTR and TSAV
Having confirmed the stationarity of the variables (GDPPC, DFIND, INSEC, RINTR, and TSAV) at I
(1). The analyses was pushed further to determine the long-run equilibrium relationship between the
variables in the model by using the trace statistics test and the maximum eigenvalue test of the Johansen
multivariate cointegration test after the order of linear deterministic trend. The results are summarized in
Table 4.2a and 4.2b respectively.
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E. P. Ifionu & R. C Ibe
Table 4.2a: Unrestricted Cointegration Rank test Result (Trace)
Unrestricted Cointegration Rank Test (Trace)
Hypothesized
No. of CE(s) Eigenvalue
Trace
Statistic
0.05
Critical Value Prob.**
None *
At most 1
At most 2
At most 3
At most 4
75.16987
39.34319
21.06528
8.945866
2.050048
69.81889
47.85613
29.79707
15.49471
3.841466
0.685163
0.445457
0.323585
0.199442
0.063991
0.0175
0.2468
0.3536
0.3704
0.1522
Trace test indicates 1 cointegrating eqn(s) at the 0.05 level
* denotes rejection of the hypothesis at the 0.05 level
**MacKinnon-Haug-Michelis (1999) p-values
Source: eviews 7.0 printout
From Table 4.2a, it can be seen that the Trace Statistics is computed to be 75.16987 while the critical
value at alpha 0.05 level is 69.81889 at the Non-hypothesized No. of CE(s) of none indicates a rejection of
the null hypotheses of no co-integrating equation. Thus the alternate hypothesis of one cointegrating equation
is not rejected.
Table 4.2b: Unrestricted Cointegration Rank test Result (Maximum Eigenvalue)
Unrestricted Cointegration Rank Test (Maximum Eigenvalue)
Hypothesized
No. of CE(s) Eigenvalue
Max-Eigen
Statistic
0.05
Critical Value Prob.**
None *
At most 1
At most 2
At most 3
At most 4
35.82667
18.27792
12.11941
6.895818
2.050048
33.87687
27.58434
21.13162
14.26460
3.841466
0.685163
0.445457
0.323585
0.199442
0.063991
0.0289
0.4721
0.5359
0.5015
0.1522
Max-eigenvalue test indicates 1 cointegrating eqn(s) at the 0.05 level
Equally, the Max-eigenvalue result on table 4.2b indicates one cointegrating eqn.(s) at the 0.05 level
(statistic = 35.82667, critical value = 27.58434). These results indicate that there exist a sustainable long run
equilibrium relationship between the GDPPC, DFIND, NSEC, RINTR and TSAV.
Relative Long Run Relationship between GDPPC, DFIND, INSEC, RINTR, and TSAV
Table 4.2c: Normalized cointegrating coefficients (Standard error in parentheses)
1 Cointegrating Equation(s):
Log likelihood -492.6583
Normalized cointegrating coefficients (standard error in parentheses)
GDPPC
DFIND
INSEC
RINTR
TSAV
1.000000
-317.2789
-903.6953
79.55652
491.2257
(309.609)
(140.396)
(38.2876)
(474.046)
Table 4.2c depicts the long run cointegration equation showing the nature and magnitude of the
observed long run relationships. The equation is normalized for GDPPC – the dependent variable. The
normalized beta coefficient representing the long run relative statistical relationship between the GDPPC and
DFIND is shown to be -317.2789 and Standard error of 309.609, suggestion a t-statistic of 0.98. This is not
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International Journal of Empirical Finance
significant at 5% level. By implication, there exist a statistically insignificant relationship between the
GDPPC and DFIND variable. The sign implication suggests a negative relationship which is in disagreement
with a priori expectation. On the other hand the normalized beta coefficient representing the long run relative
statistical relationship between the GDPPC and INSEC is calculated to be -903.6953 with a standard error of
140.396 (t-statistic = 1.55). The computed t-statistic is far from being significant at 5% significant level.
Thus, the relationship between GDPPC and INSEC is negative and in disagreement with a priori expectation;
it is also not statistically significant at the conventional 5% level. The normalized beta coefficient
representing the long-run relative statistical relationship between the GDPPC and RINTR is calculated at
79.55652 with a standard error of 38.2876 (t-statistics = 0.48). The computed t-statistic is not significant at
5% significant level. Thus, the relationship between GDPPC and RINTR is negative and insignificant. This
sign is in agreement with our a priori expectation. The normalized beta coefficient representing the long run
relative statistical relationship between GDPPC and TSAV is calculated to be 491.2257 with a standard error
of 474.046 (t-statistics = 0.97). The computed t-statistics is not significant at 5% significance level. Thus, the
relationship between GDPPC and TSAV is positive and insignificant. This is in agreement with our a priori
expectation.
Relative Short Run Relationship between LOGGDP, LOGINSEC, LOGRINTR and LOGTSAV
The study employed the equation estimation method to estimate the short-run relationship between
GDPPC, DFIND, INSEC, RINTR and TSAV. The result is summarized on Table 4.2d.
Table 4.2d Equation estimation result
Dependent Variable: GDPPC
Method: Least Squares
Date: 07/05/15 Time: 11:24
Sample (adjusted): 1982 2013
Included observations: 32 after adjustments
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
DFIND
INSEC
RINTR
TSAV
GDPPC(-1)
DFIND(-1)
INSEC(-1)
RINTR(-1)
TSAV(-1)
-174.5133
6.624252
-2.179865
0.903747
-9.575695
0.993913
-0.278537
4.531632
-0.009554
1.531070
160.7856
7.123312
1.750194
0.604694
10.35168
0.088791
7.584303
1.911048
0.613317
11.06622
-1.085379
0.929940
-1.245499
1.494553
-0.925038
11.19389
-0.036725
2.371282
-0.015577
0.138355
0.2895
0.3625
0.2261
0.1492
0.3650
0.0000
0.9710
0.0269
0.9877
0.8912
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
F-statistic
Prob(F-statistic)
0.944036
0.921142
47.40174
49432.34
-162.8880
41.23461
0.000000
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Hannan-Quinn criter.
Durbin-Watson stat
671.3328
168.7995
10.80550
11.26354
10.95733
1.387328
Source: eviews 7.0 printout
473
E. P. Ifionu & R. C Ibe
As can be seen, the beta coefficient representing the relationship between GDPPC and DFIND after
adjustments is -0.278537 while the observed t-statistics is -0.036725 is not significant at 5% (prob. 0.9710).
We do not reject the null hypothesis of no significant relationship between GDPPC and DFIND in the short
run. The relationship is negative contrary to a priori expectation. The relationship between GDPPC and
INSEC 4.531632, while observed t-statistic is 2.371282 which is significant at 5% level (prob. = 0.0269).
Given these, we reject the null hypothesis of no significant relationship between GDPPC and INSEC in the
short run. More so, the observed relationship is positive, which is in agreement with a priori expectation. On
the other hand, though the relationship between GDPPC and RINTR is negaitive, it is not statistically
significant at 5% level (Beta = -0.009554; t-stat = -0.015577, prob. = 0.9877). Thus we do not reject the null
hypothesis of no significant relationship between GDPPC and RINTR in the short run. The beta coefficient
representing the relationship between GDPPC and TSAV is (beta = 1.531070; t-statistics = 0.138355, p =
0.8912). Given these, we do not reject the null hypothesis of no significant relationship between GDPPC and
TSAV in the short run. The observed relationship is positive and insignificant which is in agreement with a
priori expectation. Our R² which measures the overall fit of the regression line, in the sense of measuring
how close the points are to the estimated regression line in a scatter plot is 0.944036. It also the fraction of
the variance of the dependent variable (GDP) explained by the regression. Our regression has a good fit with
the data. The Durbin-Watson 1.387328 is below the traditional bench mark of 2.0 indicating the possibility of
serial auto correlation.
Causality between GDPPC, DFIND, INSEC, RINTR, and TSAV
Table 4.2e: Pairwise Granger Causality Result
Pairwise Granger Causality Tests
Date: 07/05/15 Time: 11:50
Sample: 1981 2013
Lags: 1
Null Hypothesis:
Obs
F-Statistic
Prob.
DFIND does not Granger Cause GDPPC
GDPPC does not Granger Cause DFIND
32
2.45814
1.34015
0.1278
0.2565
INSEC does not Granger Cause GDPPC
GDPPC does not Granger Cause INSEC
32
6.94169
0.95668
0.0134
0.3361
RINTR does not Granger Cause GDPPC
GDPPC does not Granger Cause RINTR
32
1.62486
0.77360
0.2125
0.3863
TSAV does not Granger Cause GDPPC
GDPPC does not Granger Cause TSAV
32
0.32002
4.28873
0.5759
0.0474
INSEC does not Granger Cause DFIND
DFIND does not Granger Cause INSEC
32
0.05341
3.79498
0.8188
0.0611
RINTR does not Granger Cause DFIND
DFIND does not Granger Cause RINTR
32
3.38543
0.09891
0.0760
0.7554
TSAV does not Granger Cause DFIND
DFIND does not Granger Cause TSAV
32
3.66381
3.45402
0.0655
0.0733
RINTR does not Granger Cause INSEC
INSEC does not Granger Cause RINTR
32
2.07236
1.54095
0.1607
0.2244
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International Journal of Empirical Finance
TSAV does not Granger Cause INSEC
INSEC does not Granger Cause TSAV
32
4.18097
0.28127
0.0501
0.5999
TSAV does not Granger Cause RINTR
RINTR does not Granger Cause TSAV
32
0.02743
2.57450
0.8696
0.1194
Source: eviews 7.0 printout
Because there exist relationship between variables does not necessarily imply causality. To test the
existence of causality the study employs the Granger Causality procedure to test the direction of causality
among the nominated variables of GDPPC, DFIND, INSEC, RINTR, and TSAV. The results of the pairwise
Granger Causality test are summarized on Table 4.2e.above. It can be seen from Table 4.2e that INSEC
granger-caused GDPPC (F= 6.94169; prob. = 0.0134), the unidirectional causality flows from the informal
sector the gross domestic product per capita. On the other hand, GDPPC granger-cause TSAV (F=4.28873;
prob. = 0.0474). This implies that causality flows from GDPPC to TSAV, therefore a unidirectional causality
exists. Thus we reject the null hypothesis of no causal relationship between GDPPC and TSAV. Finally,
there is a unidirectional causality between total savings (TSAV) and the informal sector (INSEC). TSAV
granger cause INSEC (f=4.18097; prob. 0.0501).
Diagnostic Tests
Table 4.3a: Breusch-Godfrey Serial Correlation LM Test
Breusch-Godfrey Serial Correlation LM Test:
F-statistic
Obs*R-squared
0.758339 Prob. F(1,21)
1.115290 Prob. Chi-Square(1)
0.3937
0.2909
Table 4.3b: Ramsey RESET Test
Ramsey RESET Test
Equation: UNTITLED
Specification: GDPPC C DFIND INSEC RINTR TSAV GDPPC(-1)
DFIND(
-1) INSEC(-1) RINTR(-1) TSAV(-1)
Omitted Variables: Squares of fitted values
t-statistic
F-statistic
Likelihood ratio
Value
1.377626
1.897853
2.768662
df
21
(1, 21)
1
Probability
0.1828
0.1828
0.0961
Table 4.3c: Breusch-Pagan-Godfrey Heteroskedasticity Test
Heteroskedasticity Test: Breusch-Pagan-Godfrey
F-statistic
Obs*R-squared
Scaled explained SS
0.713525 Prob. F(9,22)
7.230214 Prob. Chi-Square(9)
6.247068 Prob. Chi-Square(9)
0.6912
0.6132
0.7150
Source: eviews 7.0 printout
475
E. P. Ifionu & R. C Ibe
Because of the low Durbin-Watson value from our equation estimation result we carried out the BreuschGodfrey serial correlation test and the result indicates we don’t have a problem with that. Also the Ramsey
RESET test for the stability of our model shows our model is well specified. We tested for heteroskedasticity
and it also indicates the model does not have that problem.
5. Conclusion
Following the lack of empirical evidence on the relationship between the informal financial sector and
economic growth in Nigeria, this study investigated the causal relationship of that sector and economic
growth for the period 1981 to 2013 as a means of providing evidence based policies that will enhance the
growth and development of the economy. The study started by testing the stationarity of the variables of
interest in the model. Results of the Augmented Dickey-Fuller (ADF) and Phillips Perron (PP) test statistics
indicate the absence of unit root among the variables. This suggests that they are integrated in order I (1)
since the critical values were less than the test statistics in absolute terms, and thus we reject the hypotheses
of no stationarity in all the cases. Being integrated as a group, the analysis was pushed further to ascertain
whether the variables are co-integrated or not. Thus, the study employed the Unrestricted Cointegration Rank
Tests (Trace and Maximum Eigenvalue) after the order of linear deterministic trend. The results indicate the
existence of long-run equilibrium relationship between gross domestic product (GDP), the dependent
variable, degree of financial depth proxied by ratio of broad money (M2) to GDP (DFIND), growth rate of
the size of the informal sector (INSEC), real interest rate (RINTR) and total savings deposits to gross
domestic product ratio (TSAV). In the long-run GDP has a negative and insignificant relationship with the
degree of financial depth, informal sector and real interest rate, a positive and insignificant relationship with
total savings. In the short run, GDP has a positive and significant relationship with the informal sector,
positive and insignificant relationship with total savings, but a negative and insignificant relationship with
both the degree of financial depth and real interest rate. There is unidirectional causal relationship between
the informal sector and gross domestic product per capita, with the flow from the informal sector, gross
domestic product to total savings with the flow from GDPPC to TSAV and between total savings and the
informal sector with flow from total savings to the informal sector.
6. Recommendation
The Nigerian financial system is highly dichotomized between the formal and informal sectors. Both
sectors should complement each other in which case the policies and regulations made in the formal should
filter favourably to the informal. In as much as the informal finance is very essential to small-scale
investment, policies need to be designed in order to integrate this silent but salient growth element. The
informal financial sector thrives where access to banking services are limited, so they bridge the gap created
by formal financial institutions. Moreover, informal financial market serves a broad segment of the
population and it is not the desire of any government to have a large segment of the economy fall outside
regulatory ambience. The dominance of the Nigerian informal system with reference to the informal financial
sector is because of the presence of underpinning factors that propel patronage. The fragmentation of the
Nigerian financial system stems from the weak linkages and wider difference in risk- adjustment returns.
This leaves out a large clientele for the informal financial sector, which is clearly manifested by structural
problems inherent in the formal banking sector. The informal sector stands to reap the dividends of these
shortcomings. The strengthening of the banking system via viable policy is capable of integrating the
informal sector smoothly into the operation of the formal sector. The informal financial system in Nigeria is
vibrant and employs a large segment of the workforce. For example, a solid and revitalized banking system is
capable of attracting the funds accumulating in the hands of informal operators, like the Esusu thrift
collector, the traditional money lenders, and others. A system that is predictable and reliable can stimulate
short-term investment by these operators. The effect will be that the government via its regulatory
institutions will be able to gather satisfactory data on the financial system to make better and more reliable
476
International Journal of Empirical Finance
economic planning. This finding is in harmony with Ezirim and Muoghalu (2004) that bank consolidation
will increase the scope of banking system in Nigeria. However, Onwioduokit and Adamu (2005) and
Aryeetey (2003) had related views but with mixed feelings. Policy makers and the government should
encourage the integration of the formal and informal sectors as this would have a strong positive impact on
economic growth. Deposit money banks and the monetary authority should evolve policies aimed at reaching
the unbanked informal sector agents, especially the rural households and the urban informal production units.
This will deepen the financial sector and assist in mobilizing the much needed savings that will engender
investment and growth in Nigeria.
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