Empirical Analysis of Financial Sector Development and … … · · 2017-06-07The financial...

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International Journal of Financial Economics

Vol. 5, No. 1, 2016, 46-60

Empirical Analysis of Financial Sector Development and National

Savings: Evidence from Nigeria Economy

Henry Waleru Akani1, Austin Ayodele Momodu2

Abstract

This paper set out to examine whether there is a dynamic long run relationship between financial sector

development and Nigeria National Savings in addiction to determining the direction of causality among the

variables. Time series data were sourced from Central Bank of Nigeria (CBN) Statically Bulletin from 1980 –

2014. The study modeled Gross National Savings as the percentage of Gross Domestic Product (GDP) as our

dependent variable while our independent variables were Commercial Banks Credit as percentage of GDP

(CBC/GDP), All Share Price Index as the percentage of GDP (ASPI/GDP), Broad money supply as a

percentage of GDP (M2/GDP) to captured the level of financial deepening, Interest Rate (INTR), Exchange

Rate (EXR) and Inflation Rate (INFR) were used. The study employed the Johansen. Co-integration Test,

Augmented Dickey Fuller Unit Root Test, Granger Causality Test and Vector Error Correction Model were

used to examine the relationship between the dependent and the independent variables. The empirical results

demonstrate vividly that there is a long run dynamic and significant relationship between financial sector

development proxied by national savings and a negative long run relationship between national savings and

inflation rate in Nigeria. The static regression result indicates that all the independent variables except inflation

rate have positive effect on National Savings. The Unit Root Test indicates non-stationarity at level. The study

concludes that financial sector impact significantly to Nigerian total saving. It therefore recommends for

financial sector deepening and well management Strategies to enhance National Savings in Nigeria.

Keyword: Financial Sector Development, National Savings, Co-Integration and Causality Tests

1. Introduction

There is no doubt saying that the Nigerian Financial Sector has over the years undergone structural,

institutional and policy changes/reforms to reposition it for greater effective intermediation functions that can

facilitate the realization of sound monetary policy and macroeconomic goals. For instance the Structural

Adjustment Program (SAP) in 1986 led to the deregulation of interest rate and more importantly the banking

sector, the capital market and other financial institutions has been repositioned with the formation of policies,

programmes, reforms, regulatory cum supervisory measures to increase the capital base and deepening the

operational efficiency for greater performance. According to CBN Report (2012), Nigerian Total Domestic

Savings as percentage of GDP wings between 13.04%, 16.95%, 23.25%, 17.46% 19.86% and 21.63% between

2007 and 2013 respectively.

The financial sector plays significant role in savings mobilization through the intermediation functions of

Deposit mobilization and resources allocation, Savings is primarily used to finance investments and it is that

part of an individual income not spent on consumption. Thus, much of the disparities in Economic Performance

between the developing and developed countries have been blamed on difficulties in savings caused by the

low level of financial sector development (Ndebbio, 2004).

1Department of Banking and Finance, Rivers State University of Science and Technology Nkpolu - Port Harcourt, Rivers

State, Nigeria 2Senior Lecturer, Department of Banking and Finance, Rivers State University of Science and Technology Nkpolu -Port

Harcourt, Rivers State, Nigeria


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Furthermore, low domestic savings rates will result to low macroeconomic performance because

domestic resources are unable to finance investment as a result of deficiency in the financial system to bridge

the savings investment gap or the financial disequilibrium that exist among the different economic units. The

consequences of this are depending on foreign savings through capital flows, this makes the economy to be

sensitive to external shocks (Nnanna, 2004). The important of savings to Economic development remained

very critical to policy makers, analyst, administrators and little wonder why. Economic theories assumed

investment as the function of savings.

In theory, the positive real interest rates approaches anchors on the financial repression Hypothesis

associated with Mckinion (1973) and Shaw (1973) call for great concern and the main argument underlying

this theory is the regulated Nominal interest rate result in very low and even Negative interest rate which among

other things underline efficiency in the financial market which can lead to negative saving or dis-savings.

Unfortunately, the nature of financial sectoral development and savings elasticity in some developing countries

is still very controversial while there are empirical studies which have established significant relationship

between financial sector development and increase in Gross Domestic Savings (Nnanna, Englama, and Odoko,

2004). This argument is confirming the argument on the relationship between finance and Economic growth

and economic growth and finance. With particular reference to Nigeria empirical studies on the relationship

between financial sector development and Gross National Savings is dearth and inadequate to direct policy

reforms in the financial sector (Nwanyanwu, 2011). Evidence from the existing few studies is mixed and lack

for the basis for policy implementation. There is therefore, as yet no conclusive evidence in support or against

the relationship between financial sector development and national savings. More so, within the Nigerian

context, there is an apparent lack of research in this all-important area of financial economics. Against this

backdrop, the objective of this paper is to contribute to the on-going debate and specifically to find out whether

there is a long run dynamic relationship between financial sector development and National savings in Nigeria,

as well as to certain the direction of causality among the variables. The rest of the paper is arranged as follows.

Section II deals with empirical literature while section III is the methodology, model specification and data are

presented. Section IV presents our empirical findings and results while conclusion and recommendation were

made in section V.

2. Literature Review

Financial liberalization rests on the McKinnon (1973) and Shaw (1973) view that it “increases savings,

improves efficiency with which resources are allocated among alternative investment projects and therefore

raises the rate of economic growth” (Nzotta and Okereke, 2009).). Financial liberalization, a prescription to

the problems of financial repression is justified in countries where there are distortions in the financial sector,

that is, financial repression and restriction. Financial repression can be described by policies that distort the

domestic capital and financial markets. These distortions are a result of a number of government measures and

regulations. These measures include: controlled interest rates on deposits, often administratively set below the

market clearing rates and high reserve requirements on commercial banks, which attract low or even zero

interest rates. In a repressed financial system, commercial banks are also compelled, as a monetary policy

requirement, to invest in low coupon government bonds a certain proportion of their total reserve holdings.

Other measures and regulations involve: sectoral lending guidelines; unconducive legal and institutional

framework that restrict entry into the banking industry, leading to public ownership of major banks; and,

controls over the exchange rate. These regulations and their effects affect the operation of financial markets,

since they tend to reduce the flexibility and flow of savings to the formal financial sector.

Moreover, they increase the fragility of the banking system that in turn results in reduced volume of credit

and low rates of investment that affects adversely the rate of economic growth.

Although the exact nature of an ideal reform package for the financial sector will vary with country

specific circumstances, a set of policy measures are generally taken to compromise the standard paradigm.

Nonetheless, in general, financial sector liberalization involves removal of financial repression (interest rate

H. W. Akani & A. A. Momodu

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controls, directed Credit, and high reserve ratios), rehabilitation of the banking system and the deepening and

development of capital market. The basic argument in the financial repression theory is an existence of a

positive relationship between savings and the real interest rates. According to Fry (1988), the policy approach

to positive real interest rates has two paths: rising of nominal interest rates or reduction of the rate of inflation.

An additional prescription is reduction of the required reserves; and/or, elimination of credit allocation

directives and preferential credit allocations at concessional interest rates. An alternative approach is suggested

by the financial structuralists (Deaton, 1987). These argue in favor of expansion of the branches of financial

institutions that are considered to influence savings directly.

Financial Intermediation and Savings

The financial sector contributes to the efficiency of the entire economy by spreading information about

expectations and allocation of resources from savers to investors. Restrictions to entry permit firms in the

financial system to extract monopoly rents from savers and borrowers. High reserve ratio tends to extract

seignior age for the government at the expense of private saving. Ceilings on interest rates result in

disintermediation. This is because the low interest rate discourages savings and investment in favor of wasteful

consumption, investment in physical assets and other inflation hedges, and informal financial sector activities.

Therefore, innovations in financial development can alter the growth rate of the economy, through improved

efficiency of intermediation and an increase in savings rate. Financial liberalization and the consequent

increase in geographical density of financial institutions, range of financial instruments, and the quality of

financial regulations and supervision, typically lead to financial deepening that will be reflected in a permanent

increase in stocks (and a temporary increase in flows) of financial savings. Although this increase might simply

show a portfolio shift and not an increase in overall private saving, it has been argued for East Asia that

financial deepening has contributed to growth in overall saving.

Literatures on the impact of financial intermediation on saving seem to granger cause financial

intermediaries. However, Patrick (1966) argues that causation is bi-directional: financial intermediation is both

supply-leading and demand-following, that is the setting up of financial intermediaries enhances saving and it

may, itself be enhanced by the existence of unintermediated saving in the economy.

Financial development, that is increase in geographical density of financial institutions, range of financial

instruments, and the quality of financial regulations and supervision promotes saving mobilization and

economic growth. To link financial intermediation to saving and economic growth, recent contributors to the

new growth literature have reconsidered the role of financial intermediaries (Raza, 2015) . Odior, (2013) gives

some examples of indicators of financial development. These include the ratio of monetary aggregates (M1 or

M2) to GDP, share of financial intermediation done by commercial banks, volume of lending to the private

sector measured by ratio of flow of credit to the private sector to GDP, and, direct indicators of financial

repression such as the reserve ratio or ex post real interest rate. Fry (1988) observes that only three quantitative

measures of financial conditions have received attention in the literature. These include the real deposit rate of

interest, population per bank branch and financial intermediation ratio.

In general, it follows from the financial repression hypothesis (FRH) and the structuralist view that

improved financial intermediation reduces the portion of national savings that is diverted by the financial

system into “non-productive” uses, and, as a result, the rate of capital accumulation increases for a given

savings rate. This is achieved because financial intermediation enhances savings mobilization by providing to

savers a variety of relatively safe financial instruments. It has, therefore, become

Increasingly important to assess the potential role of improved financial intermediation in the process of

savings mobilization.

Interest Rate Liberalization and Savings

In their FRH, McKinnon (1973) and Shaw (1973) argue that in countries characterized by financial

repression, raising nominal interest rates relative to inflation would increase saving and supply of investible

resources in an economy. This assertion is based on the assumption that most investments in financially


49

repressed economies are confined to self-finance. This, coupled with the lumpiness and/or indivisibility of

investment, requires investors to agglomerate enough money balances (bank deposits) prior to the undertaking

of higher yielding investment. As a result, accumulation of money balances becomes a conduit for capital

formation such that money balances and capital formation become complementary assets in a repressed

financial system.

Determinants of Savings

o The Level of Income in the Economy

The fundamental assumption of the life-cycle hypothesis is that an individual seeks to maximize the

present value of lifetime utility subject to the budget constraint. The theory predicts that consumption in a

particular period, and thus the decision to save, depends on expectations about lifetime income. According to

this theory, the lifetime of an individual is divided into a working period and a retirement period.

Individuals are assumed to be net savers during the working period and dissevers during the retirement

period. In the light of that, growth of per capita income will result in an increase of aggregate saving rate,

because it increases the lifetime earnings and saving of younger age groups relative to older age groups

(Athukorala and Sen, 2004). Thus countries with higher per capita growth rates are expected to have higher

saving ratios than countries with lower growth rates. However, there is another view indicates that the size of

this effect is likely to decline as per capita income rises and may even become negative for rich countries where

investment opportunities and growth are relatively lower (Masson et al, 1998).

o Demographic Factors

Demographic factors such as population age-structure and dependency ratio also affect saving

performance. During childhood and old age, people on average consume more than they produce through their

labor. During the middle years, people produce more than their consumption. The life cycle theory assumed

that when there are too many young people to support, consumption increases and saving declines.

The theory distinguished between dependency ratio and population growth on its effect on saving ratio.

It indicated that although an increase of population growth rate may increase the number of active workers

(savers) relative to the number of retired (dissevers), however, this may be accompanied by an increase of

young ratio (dissevers) in the population as well. Thus the net effect of population growth on aggregate saving

is theoretically unclear (Athukorala and Sen, 2004).

o Fiscal Policies

The neo-classical version of the lifecycle model assumes that a decline in government saving (more

budget deficit) will tend to raise consumption and discourage saving by shifting the tax burden from present

to future generations. As a result of that, a decline in government savings will cause a decline in national

savings.

There is another view indicates that an increase in government savings would have no effect on national

savings, as it would be completely offset by a corresponding fall in private savings The Ricardian Equivalence

(Ozean et al, 2003). According to the Ricardian Equivalence Hypothesis, it does not matter whether

government finances its expenditure through taxes or by borrowing. The Ricardian Equivalence depends on

the assumption of perfect capital markets, and therefore saving behaviour does not experience any uncertainty.

However, if this assumption does not hold, then perfect substitution between public and private savings will

not be achieved (Athukorala and Sen, 2004).

o Interest Rate

The life-cycle theory introduced that the net effect of the real interest rate on savings is unclear. The net

effect of the real interest rate on savings can be decomposed into two effects. The substitution effect implies

that a higher interest rate increases the current price of consumption relative to the future price, and thus

affecting savings positively. The other effect, which is called the income effect, indicates that if the household

is a net lender, an increase in the interest rate will increase lifetime income, and so increase consumption and


50

reduce saving. Therefore, it is expected that the interest rate will have a positive impact on saving ratio only

when the substitution effect dominates the income effect. In developing countries where financial markets are

still not well developed, substitution effect is expected to be much greater than income effect, and thus the real

interest rate is likely to have a net positive impact on domestic savings (Özcan et al, 2003). However, the

complexity and distortions in both the real and the financial sides of the economy tend to reduce the benefits

of an increase in interest rates, and thus the positive impact on domestic savings may not be achieved.

o Inflation and Macroeconomic Uncertainty

The life cycle hypothesis implies that inflation is neutral because of the absence of money illusion, and

thus inflation does not have a real effect on saving behaviour. However, uncertainty in the form of inflation

should rise saving since risk adverse consumers tend to set some resources aside as a precaution against

possible adverse changes in future income (Loayza et al, 2000). In that case, individuals will limit their present

consumption and save more in order to consume more in future. On the one hand, inflation could affect savings

through real wealth. Inflation acts as a tax on money balance holdings, so if individuals wish to maintain the

real value of their money balance holdings (the real balance effect), saving will rise with the rate of inflation

(Hussein and Thirlwall, 1999).

o Financial Development

The degree of financial sector development and the range and availability of financial assets to suit savers

represents another important factor in promoting savings. The expansion of bank branches and improving the

accessibility to banking facilities will result in reducing the cost of banking transactions, and thus motivate

individuals' savings. On the other hand, if financial institutions are not well organized and stable, savings will

be kept in non-monetary terms such as jewelry and real estate, and this may defeat the main purpose of saving.

Therefore, the potential positive effect between the development of the consumer’s credit market and

household financial saving depends also on the degree of substitution between financial saving and other forms

of savings in the household asset portfolio. As a result of that, the potential impact of financial development

on private savings seems to be ambiguous (Athukorala and Sen, 2004).

o External Variables

The external variables that might be relevant to savings are the current account deficit and terms of trade.

It is supposed that an increase in the current account deficit (foreign saving) is associated by a partial decline

in private saving, as foreign saving may tend to act as a substitute to domestic saving (Özcan et al, 2003).

Terms of trade represents another external variable that may have an effect on saving behaviour especially

for the oil exporters. Positive terms of trade may result in an increase of savings through the positive effect on

wealth and income. The traditional explanation of this relationship is illustrated in the Harberger–Laursen-

Metzler hypothesis. It assumes that deterioration in terms of trade reduces real income and thus saving2. This

hypothesis assumed myopic expectations of consumers.

However, recent literature argues that a change in terms of trade has an ambiguous effect on saving

depending on whether the change in the former is seen to be permanent or temporary. A transitory improvement

in terms of trade causes only a transitory change in income, and thus should lead to higher saving rather than

higher consumption. This conclusion supports the direction of the Harberger-Laursen- Metzler effect.

Nevertheless, a permanent improvement tends to reduce saving as consumers increase their consumption.

Thus, the effect of terms of trade changes on saving depends on whether the change was anticipated or not

(Masson et al, 1998).

3. Methodology and Data

In carrying out country-specific and time-series analysis of data in financial econometrics, it is important

to examine the stationarity properties of the time series. A time series is stationary if its mean, variance and

auto-covariance are not time-dependent. Hence any series that is not stationary is called non-stationary. Two


51

basic types of time series models exist and these are autogressive (AR) models and the moving average process

(MA).

An AR model is one where the current value of a variable Y depends upon only the values that the variable

took in previous periods plus an error term. Thus, an AR model of order P, denoted as AR (Ip) can be expressed

as:

Yt = + Yt-1 + 2 Yt-2 +… Yt-p + 4…………………………… (1)

Where 4 is a white noise disturbance term. Alternatively, ……(2)

can be written as:

Yt = + 1 Yt-1 + 4 ……………………………………………..(3)

Where is a constant and 1….p are parameters of the model or using the lag operator, it becomes:

1i

Y1 = + 1L1Y1 4 ………………………………………...(4)

Or (L)Yt = + t where

(L) = (1-1L - 2L2…L)………………………………………………..(5)

On the other hand, if Ut is a white noise process with E (Ut) = 0 and Var (Ut) = a2, then

Yt = + Ut +1 U1 Ut-1 + 2Ut-2 + ………+q Ut-q…………………….. (6) is a qth moving average model denoted MA (q). . …………………….......(5)

can be restated as:

t1t1

i

tUUαY

q

1

……………………………………………..…(7)

Thus, a moving average (MA) model is linear combinations of white noise process such that Yt is a

function of current and lagged values of a white noise disturbance process. (Brooks, 2008). Using the lag

operator notation, equation (7) becomes:

tt

1

1

i

tUULαY

q

1

………………………………………………...........(8)

Or as tt

UL)(αY where

L = 1 + 1L+ 2L2 +……….+ qLq ……………………………………(9)

However, by combining this AR (p) and MA (q) models an ARMA (p,q) model is obtained. Thus, in an

ARMA model, the current value of some series Yt depends linearly on its own previous values plus a

combination of current and lagged values of a white noise error term. This can be stated as:

Yt = + 1Yt-1 + 2Yt-2 +…. + pYt-p + 1Ut-1 + 2Ut-2 + …qUt-q…(10)

Where

E(Ut = 0); E(Ut2) = 2; E(Ut U3) = 0, t s………………………(11)

It is evident from the foregoing that stationarity in a time series is a desirable property for an estimated

AR model. The reason being that a model whose co-efficients are non-stationary will have a non-declining

effect on the current values of Yt as time progresses which is counter productive, empirically defective and

could lead to spurious regressions.

The literature of financial econometrics is replete now with ample tests for stationarity in time series data

as well as different treatments to induce stationarity. Hence, in this paper, the Augmented Dickey – Fuller

(ADF) (1981), unit tests are employed to check whether the series data are stationary or not. That is, consider

an AR (1) process:

Yt = + Yt-1 + 4 ………………………………………………. (12)


52

Where and are parameters of the model and 4 is a white noise disturbance term. Yt is stationary, if

and only if, -1< 11 <1. However, if = 1, then Yt is a non-stationary series. That is, if the time series is started

at some point (t), the variance of Xt increases steadily with time and goes to infinity. On the other hand, if the

absolute value of 11 is more than t, then the series Yt is explosive. Hence, the hypothesis of a stationary series

is usually tested whether the absolute value 11 is strictly less than unity. Thus, for testing unit root, Yt4 is

subtracted from both sides of eq.(10), then we have:

Yt = + Yt-1 + 4 ……………………………………….………. (13)

Where = ( - 1) and the null hypothesis can be tested as Ho: = 0. This unit root test is however only

applicable where the series is an AR (1) process. For higher order serial correlation in the series, the assumption

of white noise disturbance term is violated. However, the ADF test corrects for high order correlation by

making the assumption of an AR(p) process as:

Yt = + Yt-1 +

p

j 1

Yt-j + 4 …………………………………………….…. (14)

That is, the additional lagged terms are included to ensure that the errors are uncorrelated. Hence, if the

calculated i=1ADF statistic is less than their critical values from the fuller’s table, then the null hypothesis Ho:

= 0 is accepted and the series are non-stationary or not integrated of order zero. Thus, to induce stationarity,

many time series need to be appropriately differenced. Hence, a time series is said to be integrated of order d,

if it has become stationary after differencing it d times. (Brooks, 2008; Alam et al., 2015).

In this paper, we examine whether the time series are co-integrated by adopting the method of Granger

(1969). That is, two or more variables are said to be co-integrated if each variable individually is integrated of

order one, but a linear combination of the variables is integrated of lower order say zero.

Thus, a long-run relationship between the variables is present when there exists at least one co-integrating

vector. That is, if Y1t and Y2t are co-integrated 1 (1) so that t, 1(0), then this implies that there exists a long-

run equilibrium between Y1t and Y2t to which the system converges overtime and the disturbance term can be

construed as the disequilibrium error. The first step in the Engle and Granger (1987) co-integration method is

to estimate the co-integrating equation.

Yt = 0 + 1 Xt + Ut………………………………………………….. (15)

and then to calculate the residual

Ut = Yt - 0 - 1 Xt ………………………………………………….. (16)

Then we check the stationarity of the residuals. Hence, if Y and X are co-integrated the error term will be

stationary and this is accomplished by testing the residuals of co-integrating regression for stationarity by

performing ADF unit root tests.

Granger Causality Test

To determine the direction of causality between the variables, we employ the standard Granger causality

test. (Granger, 1969). The test is based on vector error correlation model (VECM) which suggests that while

the past can cause or predict the future, the future cannot predict or cause the past. Thus, according to Granger

(1969). X Granger causes Y if past values of X can be used to the past values of Y. The test is based on the

following regressions:

tt

y

otUXYY

n

i

n

i

111

11

………..………………………. (17)

and

tt

y

otYXYX

n

i

n

i

11

1 11

………………………………. (18)

Where Xt and Yt are the variables to be tested while is the white noise disturbance terms. The null

hypothesis 1 = 1Y = 0 for all 1’s is tested against the alternative hypothesis 1 0 and 1

Y 0. If the co-


53

efficient of 1 are statistically significant but that of 1Y are not, then X causes Y. If the reverse is true, then Y

cause X. However, where both co-efficient of 1 and 1Y are significant then causality is bi-directional.

The Model

Given the above theoretical framework, the complete model of this study is presented thus:

TS/GDP = f(CBC/GDP, ASPI/GDP, M2/GDP,INTR, EXR, IFR)…….………... (19)

Transforming equation 5 into a testable form, we obtain

TS/GDP = 0 + 1 CBC/GDP+ 2 ASPI/GDP+ 3 M2/GDP+ 4 INTR+ 5 EXR+ 6 IFR+et ……(20)

Where;

TS/GDP = Percentage of Total Savings to GDP

CBC/GDP = Percentage of Commercial Banks Credits to Total GDP

ASPI/GDP = Percentage of Nigerian Capital Market All Share Price Index to GDP

M2/GDP = Percentage of Broad money supply to total GDP representing financial deepening.

INTR = Real Interest rate

EXR = Exchange rate per U.S. Dollar

INFR = Nigerian Inflation Rate

a0 = Intercept

61 = coefficient of independent variables to the dependent variable

et = Error term

A-priori Expectation of Result

The variables are expected to add positively to the dependent variable, therefore, β1, β2, β3, β4, β5, β6 > 0

Data

The study employed secondary data sources from statistical bulletin (various issues), Central Bank of

Nigeria (CBN), Annual Report as well as the Annual Reports of National Bureau Statistics (NBS). The sample

period chosen on account of availability of data is between 1980 – 2014.

Table 1: Annual Time Series Data of the Variables: 1980-2014

Year TS/GDP CBC/GDP ASPI/GDP M2/GDP INTR EXR INFR

1980 5.21 7.620 0.239 12.2 7.500 0.544 9.900

1981 6.96 9.099 0.323 15.3 7.500 0.636 20.900

1982 7.44 10.172 0.213 15.6 7.800 0.670 7.700

1983 8.58 10.079 0.362 16.1 10.300 0.748 23.200

1984 9.45 9.894 0.221 17.3 10.000 0.808 30.800

1985 9.30 9.043 0.235 16.6 11.750 3.316 3.230

1986 10.35 11.665 0.370 17.7 12.000 4.191 6.250

1987 9.67 9.078 0.198 14.3 19.200 5.350 11.760

1988 8.83 7.429 0.323 14.6 17.600 7.650 34.210

1989 6.23 5.757 0.160 12.0 24.600 9.650 49.020

1990 6.27 5.501 0.048 11.2 27.700 9.000 7.890

1991 6.92 5.737 0.044 13.8 20.800 9.754 12.190

1992 6.30 4.882 0.056 12.7 31.200 19.660 4.560

1993 7.80 6.026 0.074 15.2 36.090 22.630 57.140


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1994 7.93 6.729 0.070 16.5 21.000 21.886 57.410

1995 3.73 4.973 0.063 9.9 20.890 81.022 72.720

1996 3.34 4.202 0.173 8.6 20.860 81.252 29.290

1997 4.24 9.203 0.247 9.9 23.320 81.649 10.670

1998 5.01 6.840 0.340 12.2 21.340 83.807 7.860

1999 5.93 6.898 0.301 13.4 27.170 92.342 6.610

2000 5.74 7.571 0.419 13.1 21.550 100.801 6.690

2001 7.08 11.547 0.837 18.4 21.340 111.701 18.860

2002 7.60 12.245 0.762 19.3 30.190 126.257 12.880

2003 6.61 12.206 1.215 19.7 22.880 134.037 14.030

2004 6.99 13.314 1.979 18.7 20.820 132.370 15.010

2005 9.01 13.529 1.800 18.1 19.490 130.606 17.850

2006 9.37 13.597 2.533 20.5 18.700 128.276 8.210

2007 13.04 23.302 5.209 24.8 18.360 125.881 5.410

2008 16.95 32.101 6.911 33.0 18.700 121.904 11.500

2009 23.25 35.944 2.766 38.0 22.620 150.012 12.540

2010 17.52 22.676 2.354 32.5 22.510 150.650 13.720

2011 17.46 20.088 0.000 32.5 22.420 156.200 10.720

2012 19.89 18.036 1.995 34.3 24.650 155.820 12.000

2013 21.63 14.476 2.602 38.7 23.581 158.320 10.780

2014 23.37 10.916 3.209 43.1 22.512 160.82 9.56 Source: Author’s Computation

TS/GDP = Percentage of Total Savings to GDP

CBC/GDP = Percentage of Commercial Banks Credits to Total GDP

ASPI/GDP = Percentage of Nigerian Capital Market All Share Price Index to GDP

M2/GDP = Percentage of Broad money supply to total GDP representing financial deepening.

INTR = Real Interest rate

EXR = Exchange rate per U.S. Dollar

INFR = Nigerian Inflation Rate

4. Empirical Results

The empirical results of the multiple regressions estimated on the level series data are as presented in table

2 below. The estimated model shows R2, the co-efficient of determination is 71.2% while the adjusted R2 is

62.3% implying that 71.2% of the variations in National savings in Nigeria are explained by changes in other

independent variables

The estimated regression result shows the short-run relationship between the dependent and the

independent variables examined in this study. The coefficient of 0.712 indicates that 71.2% variation in the

level of Nigerian Total savings can be explained by variation in the level of the independent variables examined

in this study. While the remaining 29.8% can be traced to variables not captured in the model. The Durbin-

Watson statistics of 1.25 indicates the presence of serial auto correlation in the variables in the time series. The

F-statistics of 11.15 and the probability of 0.000781 shows that the models is significant which means that the

independent variables can predict the variation in the dependent variable. The β coefficient indicates that all

the variables except inflation rate have positive relationship with Total National Savings in Nigeria.


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Table 2: Level Series Multiple Regression Summary Results

Dependent Variable: TS_GDP

Method: Least Squares

Sample: 1980 2014

Included observations: 35

Variable Coefficient Std. Error t-Statistic Prob.

CBC_GDP 0.236721 8.521348 2.028516 0.0041

ASPI_GDP 0.147891 31.65247 3.043292 0.0011

M2_GDP 0.562316 32.74209 2.341205 0.0032

INTR 1.567341 3.642845 1.598222 0.1222

EXR 2.673872 21.16926 1.770784 0.0883

INFR -2.215632 16.62684 -0.102916 0.8132

C 22.12312 151.6132 0.012724 0.2232

R-squared 0.712431 Mean dependent var 321.4321

Adjusted R-squared 0.623412 S.D. dependent var 46721141

S.E. of regression 636.8121 Akaike info criterion 21.21682

Sum squared resid 27562122 Schwarz criterion 21.53211

Log likelihood -134.3112 F-statistic 11.156721

Durbin-Watson stat 1.256211 Prob(F-statistic) 0.000781

Source: Author’s Computation

Given the non stationary features of the level series data, the ADF unit root test was concluded at the first

difference series of the results of the ADF tests (table 2).The model follows an integrating 1(0) and 1(1) process

and is therefore a stationary process.

Table 3: Unit Root Results

Variables ADF Statistics Critical value at 5% At 1% Order of Integration

TS_GDP -4.520 -2.959 -3.657 1(1)

CBC_GDP -5.028 -2.959 -3.657 1(1)

ASPI_GDP -4.113 -2.959 -3.657 1(1)

M2_GDP -2.362 -2.959 -3.657 1(1)

INTR -1.438 -2.959 -3.657 1(1)

EXR -2.729 -2.959 -3.657 1(1)

INFR -0.466 -2.959 -3.657 1(1)

Residual -5.281 - - 1(0)


The result of the ADF shows that all the variables are non-stationary at level. However, the residual shows

that the stationary at first difference therefore, the null hypotheses of non-stationarity were rejected.

Co-integration Test

Having established that all the variables in the model are integrated of order 1(0) and order 1(1) at first

differencing, we employed the Johansen co-integration test is presented in table 4 below and indicate the

existence of one co-integrating equation between the dependent and independent variables at the 5% level of

significance. This suggests that there is a long run steady states relationship between Banking sector

development and National Savings in Nigeria within the sample period. The co-integration test assumes a

linear deterministic trend in the data.


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Table 4: Johansen Co-integration Results Sample: 1980 2014

Included observations: 33

Test assumption: Linear deterministic trend in the data

Series: TS_GDP CBC_GDP ASPI_GDP M2_GDP INTR EXR INFR

Lags interval: 1 to 1

Likelihood 5 Percent 1 Percent Hypothesized

Eigenvalue Ratio Critical Value Critical Value No. of CE(s)

0.727145 74.2167 65.09 62.78 None **

0.258901 44.69021 24.94 25.15 At most 1**

0.245675 46.26521 28.51 16.97 At most 2**

0.321673 28.43132 57.28 24.16 At most 3*

0.258921 12.67121 19.62 25.75 At most 4*

0.268921 7.117821 45.01 10.64 At most 5

0.002692 0.034689 6.12 9.61 At most 6

*(**) denotes rejection of the hypothesis at 5%(1%) significance level

L.R. test indicates 1 co-integrating equation(s) at 5% significance level


The results of the co-integration indicate at least one co-integrating equation among the variables included

in the model at 5% significance level.

Table 5: Presentation of Normalized Co-integration Equation Normalized Cointegrating Coefficients: 1 Cointegrating Equation(s)

TS_GDP CBC_GDP ASP_GDP M2_GDP INTR EXR INFR C

1.000000 45.21131 -31.881 110.0056 -3.873214 -23.20281 56.97423 499.5634

(2.02141) (16.0589) (7.26712) (0.56367) (2.47183) (7.03889)

Log

likelihood

-334.1233


The normalized co-integration equation shows that CBC_GDP, M2_GDP, INFR have positive long-run

relationship with growth rate of Nigerian Gross Domestic Savings while ASPI, INTR and EXR have negative

long-run relationship.

Vector Error Correction Model (Vecm)

To further our analysis, the financial sector –National Savings relationship is now specified in a VECM

incorporating a one-period lag residual to examine the dynamic nature of the model. This is predicated on the

robust ability to the VECM to restrict the long run behaviour of the variables to coverage to their co-integrating

relationships while allowing for short-term adjustments dynamics.


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Table 6: Vector Error Correction Model (VECM)

Sample: 1980 2014

Included observations: 33 after adjusting endpoints

Standard errors & t-statistics in parentheses

TS_GDP CBC_GDP ASPI_GDP M2_GDP INTR EXR INFR

TS_GDP(-1) 0.392152 0.091221 -0.032963 -0.017536 0.095591 -0.079600 -0.048415

(0.134274) (0.20734) (0.02678) (0.03574) (0.08235) (0.10993) (0.14787)

(1.72022) (0.10190) (-1.23100) (-0.49062) (1.16073) (-0.72409) (-1.82522)

CBC_GDP (-1) -0.422113 0.782176 0.198856 -0.322489 -0.228529 0.056391 0.092782

(0.899142) (0.66914) (0.05556) (0.17396) (0.44031) (0.12749) (0.15134)

(-2.275499) (0.67443) (1.78438) (-1.45622) (-1.06781) (0.256324 (1.234895)

Source: Author Computation

From the above vector error correction results, the model shows that the speed of adjustment to

equilibrium is 86.1% which confirm the static regression results

Causality Test

Having established the long run dynamic relationship between the variables, we employ the granger pair-

wise causality test to determine the direction of causality test between financial Sector Development and

National Savings. (Granger 1969) The empirical results of the test demonstrate vividly that there is no causal

relationship running through the dependent and independent variables except from from TS_GDP to INFR at

5% level of significance. The results also agrees well the findings of such writers like Akani and Lucy (2015),

Granger, et al (2006) but contrary to the results of the studies by Richards and Sampson (2009).

Table 7: Pair - Wise Granger Causality Test Results

Pairwise Granger Causality Tests

Sample: 1980 2014

Lags: 2

Null Hypothesis: Obs F-Statistic Probability

CBC_GDP does not Granger Cause

TS_GDP

32 0.07744 0.99861

TS_GDP does not Granger Cause CBC_GDP 0.16965 0.54482

ASPI_GDP does not Granger Cause

TS_GDP

32 0.21066 0.45062

TS_GDP does not Granger Cause ASPI_GDP 0.13115 0.59533

M2_GDP does not Granger Cause

TS_GDP

32 0.13965 0.77025

TS_GDP does not Granger Cause M2_GDP 0.14462 0.85632

INTR does not Granger Cause TS_GDP 32 1.48382 0.30311

TS_GDP does not Granger Cause INTR 0.26112 0.50012

EXR does not Granger Cause TS_GDP 32 0.07246 0.73132

TS_GDP does not Granger Cause EXR 1.35946 0.31971

INFR does not Granger Cause TS_GDP 32 1.00457 0.37998

TS_GDP does not Granger Cause INFR 4.23120 0.04564



58

The result of the Granger Causality Test above shows that there is no casual relationship running through

the dependent to the independent variables and the independent to the dependent variables except TS_GDP to

INFR.

5. Discussions of Findings

The objective of the Nigeria Financial Reforms has been to reposition Nigerian Financial Sector to be an

active player instead of a spectator in the global financial market and to be an effective intermediation between

the deficit and the surplus economic unit by bridging the savings and investment gap through effective

mobilization of Domestic Savings. This study was formulated to investigate the extent to which the financial

sector has affected Nigerian’s savings mobilization. The result from the static regression reveals that the

independent variables have positive relationship except the level of inflation to Nigerian savings. This finding

confirms the expectation of the result and the financial intermediation process. It is also in line with the

objectives of the financial sector reforms such as the deregulation of interest rate in 1986 following the

Structural Adjustment Programs (SAP), the internationalization of the Nigerian Capital market and the

consolidation through recapitalization of the financial institutions, for instance the recapitalization the banking

and the insurance industries.

However, the negative effect of inflation rate confirms the expected result. High rate of inflation

discourages savings as money loses its value as the inflation increases. The insignificant effect of the

independent variables is traceable to monetary policy and macro-economic shocks in the system such as the

global economic meltdown that affected Nigerian financial sector negatively that led to the collapse and

insolvency of some of the financial institutions such as the capital market crash in 2007 following the margin

loans from the banking industry. The recent withdrawal of 75% of public sector deposit from the banking

system constrains the lending habit of the banking industry which can also affect negatively the level of

national savings. The overall findings of this study is in line with all empirical studies such as Loayze et al

(2000), Ozcan et al (2003), Athukorala and Sen (2004).

6. Conclusion and Recommendations

From the result of the study, the researcher draws the following conclusion:

(1) Commercial banks credit has positive and significant relationship with Nigerian Gross National

Savings. This finding confirms the A-Prior expectation of the result and the objective of the financial

sector reforms in Nigeria.

(2) All share price index has positive and significant relationship with Nigerian Gross Domestic Savings.

This finding confirms the expected result and the principle of financial intermediation.

(3) Broad money supply impact positively on the level Nigerian Gross Domestic Savings. This finding is

in line with the objective of Nigerian Financial Sector deepening and development.

(4) Interest and exchange rate impact positively to Nigerian Gross Domestic Savings.

(5) Inflation rate have negative relationship with Nigerian Gross Domestic Savings. This finding confirms

macro-economic and monetary policy theories.

(6) 71.3% variation in Nigerian level of Gross Domestic Savings can be traced to variation in the

independent variables.

7. Recommendations

(1) The banking sector should further be reformed and its operational efficiency increased for effective

financial intermediation that will Granger cause increase in domestic level of savings.


59

(2) The capital market should also liberate to enhance capital formation and increase in the level of savings

in the economy.

(3) There should be an expansionary monetary policy that will increase investment borrowing to boost

income in the economic that will enhance savings.

(4) Macro-economic environment should properly be harmonized with the monetary policy objectives.

(5) There should be full deregulation of interest rate to enhance savings in the economy.

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