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International Journal of Management Sciences

Vol. 5, No. 9, 2015, 639-649

Effect of Financial Intermediation on Economic Growth in Cameroon

Moutie Giscard1, Ngouhouo Ibrahim2, Kamajou François3

Abstract

Cameroonian economic policy from 1988 restructured the financial sector towards a greater Financial

Intermediation (FI). This article seeks to understand the influence of FI on economic growth in Cameroon.

This principal objective is split into two specific objectives: (1) to determine the impact of FI on economic

growth and (2) to identify the nature of the link between FI and Economic Growth in Cameroon. In order to

attain this principal objective, we use secondary data for the period 1977 to 2006. The impact of FI on

growth is realized by a multiple linear regression and the relationship between FI components and economic

growth measured by GNP per capita is modeled by a Vector Auto Regression model. The study shows that

FI has a positive and non-significant impact on economic growth in Cameroon through private credit,

monetary mass, intermediation margin as well as bank restructuring. It also shows no causal effect of FI on

growth and vice versa. This could be explained by the restructuring of the banking system, bank over

liquidity, MFE’s instability and poor growth environment. Thus banks and Micro Finance Establishments

(MFE) might consolidate their management system in order to ensure their credibility as well as their

continuity. The Banking Commission of Central Africa (COBAC) and the Cameroonian government should

intensify the process of the stabilization of the micro finance sector and create a credible financial market.

Keywords: Bank, Micro Finance Establishments, Credit, Saving

1. Introduction

At the beginning of the 1960’s, all the African countries beyond the political ideologies were confronted

with the choice of development strategy. These development strategies (Planning and Structural Adjustment

Plan) carried out under the impulse of the international institutions (World Bank, International Monetary

Fund, African Development Bank) were based on the stimulation of the growth through investments, taking

into account the financial component. After the fall of the oil prices and raw materials, the 1980s witnessed a

massive debt of the developing countries. The Cameroonian economic policy since 1988 has restructured the

financial sector towards a greater financial intermediation with the advent of structural adjustment and the

promulgation of the 1990 and 1992 laws related to cooperative companies and common initiatives groups.

Thus many cooperatives were created (MC2, MUFFA, Cofinest) in order to satisfy the marginalized

population from classical banks. Taking into consideration the fact that, in any liberal economy, a well

developed financial sector promotes economic activities, domestic investment and accumulation of wealth

through credits and cost reduction of financial intermediation, we can say that Financial Intermediation (FI)

has a special effect on Economic growth in Cameroon. Within this context, this article titled "Effect of

Financial Intermediation (FI) on Economic growth in Cameroon" aims to determine the impact of the

Financial Intermediation on Economic growth and to understand the nature of the link between FI and

Economic Growth in Cameroun.

1Master in Economic Analysis and Policy, University of Dschang 2Assistant Professor of University of Dschang 3 Professor of University of Dschang

M. Giscard et al.

640

2. Theoretical Framework

Many theories exist on the relationship between Financial Intermediation and Economic Growth. These

include: the theory of Financial Intermediation, the theory of financial liberalization, the theory of

endogenous growth and that of microfinance and economic growth.

Financial Intermediation

This is an activity through which an institutional unit acquires financial credit and simultaneously,

contracts engagements on its own account by means of financial transactions on the market (Biales, 2006).

Financial Intermediation has certain characteristics, among those, we can quote the three most important: (1)

the fact that it is based on two bilateral relations: on one hand between the non-financial agent or the

borrower and the financial intermediary and on the other hand between this intermediary and the source of

financing used; (2) the fact that it supposes exchanges of information at the individual level whereas at the

level of market information, it is collective and (3) the rate of intermediation which measures the share of the

finances brought by the financial agents as a ratio of the finances from which the non-financial agents

benefit. In a historitical way, we distinguish two types of intermediation; one in the broad sense and another

in a strict sense. The first results from an approach known as the supply from financing because it gathers

under the label of intermediate finances the whole of the contests granted to the non-financial agents by all

the financial institutions. This rate calculated thus brings down the whole finances in which various

institutions take part on the total of non-financial finances granted to agents. The second rate results from an

approach known as the demand for financing because it privileges the choice that applicant made with the

profit of recourse to financial intermediaries.

At the beginning of the seventies, the concept of financial liberalization appeared with the work of

McKinnon and Shaw (1973) whose analysis aimed at showing that within the framework of an economy in

which financial repression exist, the fixing of the interest rates below their value of balance reduces saving,

fixes investment below its optimal level and deteriorates the quality. In this context, financial liberalization

(rise of real interest rate) will increase saving and thus will allow investment’s growth. As title of recall,

financial repression can be defined as being the various interventions of the government on financial sector

(a raised of obligatory reserve or fixing of interest rate). According to this theory, financial liberalization is a

simple and effective means to accelerate economic growth in the developing countries. International

organizations (International Monetary Fund and World Bank) as well as several developing countries were

allured by this theory so that, as of the middle of seventies, a certain number of countries set up the process

of financial liberalization.

This theory born in the years 1990, supposes that the returns to scale are increasing while capital

(finance) and knowledge are endogenous. The third factor taken into account to explain Growth (C) is,

according to different versions of this theory, human capital, research and development or public capital.

The World Bank estimates that approximately a billion people throughout the world live in poverty but

several million of them would be able to develop businesses if they could reach financial services. In fact

according to Christen et al.. (2006), microcredit programs make it possible for the poor to create

employment by developing small projects and help each other mutually to leave their state of poverty.

Moreover, other services accompaying these programs have significant effects on the socio-economic life of

the served populations: mobilization of the saving and training given to the poor. Furthermore, according to

Marion (1990) “microentrepreneurs do not need subsidies, but of a fast and less constraining access to

services adapted to their needs and to the local context (…)”.

Microcredit thus constitutes a powerful instrument of the fight against poverty since it makes it possible

for the poor to increase their incomes and improve their living conditions, increase their productivity and

their efficiency, develop microbusinesses, (…) and reduce the risks to which they are exposed. Therefore, the

successes obtained as regards the supply of financial services to the poor give a glimmer of hope to the

development organisations, governments, stakeholders and recipients. As an example, we can quote the

Grameen Bank in Bangladesh which developed a very popular model reproduced in several countries of the

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641

world. However, microcredit must find a compromise between the viability of the institution and

accessibility to a greater number of the poor. In fact, the impact of microfinance on growth thus passes

through the fight against poverty so that the underprivileged people can survive and undertake small

economic activities. But what becomes the customers whose MFE close after a relatively short lifespan like

Cofinest and Godly Business Funds?

Review of Literature

The empirical relationship between the development of the financial sector and the economic growth is

more solid. There is now a wide literature which justifies this relationship with the use of a large variety of

data (Raza et al., 2011, Khan, 2000 and Levine, 1996). The hypothesis capitalization helps growth has been

around for several years but a firm demonstration appears only in the year 1990.

The study by Goldsmith (1969) on the relationship between economic growth and the measures of the

correct functions of the financial system uses the value of credit of FI relating to the GDP to measure the

financial development; under the assumption that the size of the financial system is positively correlated with

openness and the quality of financial services. Using data on 35 countries from 1860 to 1963, Goldsmith

arrives at the following result: there exists an approximate parallelism between economic development and

financial development for several decades; the fact that periods of faster economic growth are accompanied

by financial development. The work of Goldsmith presents some weaknesses: The use of observations only

limited to 35 countries; the lack of control of other factors which affect economic growth (Levine and Renelt,

1992); absence of analysis as for the fact if financial development is associated to the growth of the

productivity and to the accumulation of the capital; the possibility that the size of the FI does not measure in

a suitable way the operation of the financial system and the narrow association between the size of the

financial system and the economic growth does not identify the direction of causality (Barro and Salt-I-

Martin, 1996).

Goldsmith (1969) is one of the first economists to show the interrelationship between financial

development and economic growth by using data of 35 countries (developed and under developed) from

1860 to 1963. By measuring financial development by the total Financial credit ratio on GDP, it showed that

this ratio is positively correlated with economic growth. However, the study didn’t take into account other

factors which could affect economic growth.

Later, the study of King and Levine (1993) under the title "Finance and Growth: Schumpeter Might Be

bearing Right "on a sample of 80 countries (developed and under developed) over the period 1960 to 1989

showed that the bivariate analysis reveals a strong positive correlation between financial development and

growth. In addition, in the multivariate analysis, the results remain significant even after having included

various variables which influence the economic growth.

Then Roubini and Salt-I-Martin (1992) made studies on cross section and showed that financial

development has a positive effect on GDPs growth rate after having controlled the influence of various

factors which can affect growth like education, inflation or political stability. However this correlation

between financial development and economic growth depends on the countries considered. These results

suggest that Financial Intermediation can have a significant effect in developing countries. No study has been

done in Cameroon and therefore it is necessary to investigate its situation with a different methodology.

Research Hypotheses

In order to attain this main objective, we use secondary data such as Gross Domestic Product, Private

credits, monetary mass and Intermediation margin collected from BEAC, COBAC, the International

Monetary Fund, Camcull and the MC2 network headquarters in Cameroon and the National accounting board

of Cameroon statistics using data for the period 1977 to 2006.

Our objective is to apprehend the influence of certain financial and monetary variables on the economic

growth in Cameroon. For that purpose, we put forward after a review of the literature two fundamental

hypothesis of which the first one is supplemented by three sub-hypothesis as followed:

M. Giscard et al.

642

H 1: There is a positive effect between Financial Intermediation and Economic growth such as:

h1: Credits granted to the private sector influence positively real GDP;

h2: Monetary mass M2 influences negatively real GDP;

h3: Intermediation margin affects positively growth via credits.

H 2: Financial Intermediation causes Economic growth.

3. Methodology

On the basis of these hypotheses, we defined a certain number of variables justified on theoretical basis

for each objective. The impact of FI on growth is achieved by a multiple linear regression model using

secondary data for the period 1977 to 2006. We thus retained as endogenous variables representative of the

concept of economic growth, the GDP per capita noted LGDP. Exogenous variables are logarithm of private

credits (LCcmlt), logarithm of monetary mass (LM2), logarithm of Intermediation margin (LMi) and a

dummy variable “D”. The Dummy represents banking reorganization taking value 0 before the

reorganization and value 1 after banking reorganization in 1990.Then the relationship between FI

components and economic growth is modeled by the Vector Auto Regression (VAR) model which captures

the main problems of endogeneity and causality. Under the fundamental hypothesis that Financial

Intermediation causes Economic growth, we define as endogenous variables representative of the concepts of

economic growth and Financial Intermediation, the GDP per capita noted LGDP, LCcmlt, LM2 and LMi.

Exogenous variables are constant variable and the lag variables. From our variables coded above, we obtain

two models to be estimated as:

The multiple regression model :

LGDPt = B0 + B1 LCcmltt + B2 LM2t + B3 LMit + B4 Dt + et

With t= 1977…, 2006; n= 30 observations

B0; B1; B2; B3; B4 the model coefficients of regression assigned to the respective exogenous variables;

Dt: the banking reorganization which is the Dummy variable.

The VAR model.

(

LPib𝑡LCcmlt𝑡LM2𝑡 LMi𝑡

) = (

𝑎0 𝑎1 𝑎2 𝑎3 𝑎4 𝑏0 𝑏1 𝑏2 𝑏3 𝑏4𝑐0 𝑐1 𝑐2 𝑐3 𝑐4 𝑑0 𝑑1 𝑑2 𝑑3 𝑑4

)

(

1LPib𝑡−𝑝LCcmlt𝑡−𝑝LM2𝑡−𝑝

LMi𝑡−𝑝 )

+(

𝜀1𝑡𝜀2𝑡𝜀3𝑡 𝜀4𝑡

)

With t=1977…, 2006; n= 30 observations; a0… 4; b0… 4; c0… 4; d0… 4 parameters of the model

comparable to the coefficients of regression.

4. Results and Interpretations

Analysis of the Impact of Financial Intermediation on Economic Growth

To model the relationship between private credits, monetary mass, financial intermediation margin and

Economic growth, we use a multiple linear regression. Indeed, we use software Eviews7 to estimate the

model. The model consists of an endogenous variable LGDP and four exogenous variables: LCcmlt; LM2,

LMi and D the variable dummy representing the banking restructuration.

When time series data is used, it is first of all important that they preserve a constant distribution in

time.With the help of the Dickey-Fuller Augmented test, we find that our variables (LPibr, LCcmlt, LM2 and

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643

LMi) are globally integrated. In other words they are stationary at first difference. According to the principle

of group stationarity, we can thus carry out the estimation of the model.

The estimation of the model LGDPt = B0 + B1 LCcmltt + B2 LM2t + B3 LMit + B4 Dt + et

gives the following results:

Table 1: Results of the regression LGDP = f(LCcmlt, LM2, LMi, D) Dependent Variable: LPIB

Method: Least Squares

Date: 08/23/13 Time: 21:57

Sample (adjusted): 1977 2005

Included observations: 29 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

C 9.120368 1.171488 7.785283 0.0000

LCCMIT 0.370935 0.110045 3.370768 0.0025

LM2 0.097991 0.115056 0.851680 0.4028

LMI 0.046165 0.024785 1.862602 0.0748

D01 0.076329 0.085027 0.897701 0.3783

R-squared 0.881826 Mean dependent var 22.91491

Adjusted R-squared 0.862130 S.D. dependent var 0.252914

S.E. of regression 0.093909 Akaike info criterion -1.737393

Sum squared resid 0.211654 Schwarz criterion -1.501652

Log likelihood 30.19220 Hannan-Quinn criter. -1.663562

F-statistic 44.77240 Durbin-Watson stat 1.157330

Prob(F-statistic) 0.000000

From table 1, we note that all the variables have the awaited signs. The signs of the coefficients of

LCcmlt, LM2, LMi and D are positive, which mean that these variables have a positive impact on LPIB.

Gross domestic product is an increasing function of credits, monetary mass, intermediation margin and

banking restructuration. Thus banks and micro banks Financial Intermediation has a positive impact on

economic growth in Cameroon. When GDP increases by a unit, credits increase by 37%, monetary mass by

9,7% and intermediation margin by 4,6%. Refering to the values of probability, we note that the coefficients

of credits and intermediation margin are individually and statistically significant at 1% and 5% respectively

contrary to monetary mass and bank’s restructuration. Extremely from this report, we see that banking

restructuration and monetary mass have a positive but non significant impact on the economic growth.

The test of stationnarity of the residue of the equation of Gross domestic product shows that DF CAL is

higher than DF RED (in absolute value), thus the assumption of stationnarity of residue is accepted and it is

about a cointegration relation. The value of Durbin-Watson’s statistic (1,64<4) enables us to deduce the

absence of autocorrelation. Moreover, the coefficient of Adjustment R 2 = 0,881 close to a unit shows the

validity of the model and a weak omission of certain explanatory variables.

The estimation of the long run equilibrium relation is not sufficient. If it enables us to determine the

fluctuations of our dependent variables with the variables which influence them significantly or not in the

long run, it is consequently important to estimate the relation of short term schedule in the following table.

M. Giscard et al.

644

Dependent Variable: D(LPIB)

Method: Least Squares

Date: 08/23/13 Time: 22:10

Sample (adjusted): 1978 2005

Included observations: 28 after adjustments

White heteroskedasticity-consistent standard errors & covariance

Variable Coefficient Std. Error t-Statistic Prob.

C 0.019780 0.018433 1.073078 0.2949

D(LCCMIT) 0.299090 0.067891 4.405452 0.0002

D(LM2) 0.036320 0.062078 0.585069 0.5645

D(LMI) -0.024894 0.007913 -3.146171 0.0047

D01 0.010422 0.029552 0.352661 0.7277

RESID09(-1) -0.486545 0.262851 -1.851033 0.0776

R-squared 0.366824 Mean dependent var 0.042843

Adjusted R-squared 0.222921 S.D. dependent var 0.088239

S.E. of regression 0.077784 Akaike info criterion -2.082345

Sum squared resid 0.133109 Schwarz criterion -1.796873

Log likelihood 35.15283 Hannan-Quinn criter. -1.995073

F-statistic 2.549096 Durbin-Watson stat 1.641059

Prob(F-statistic) 0.057738

The Model with Correction of Error (MCE) is valid and overall satisfactory, since the coefficient of

correction of error is negative (-0,48) and significant to 10%. That confirms the validity of the MCE

representation.

Economic Interpretation of the Impact of Financial Intermediation on Growth

Table 2 above presents the results of the basic regression where the dependent variable is the LGDP.

The explanatory variables are LCcmlt, LM2, LMi and D taken with their initial values at 1977. This

specification shows that private credits enters directly and significantly into the explanation of economic

growth. Indeed, the coefficient associated with the credits is 0,0025. We can deduce from it that, credits are

in short run, average and long run strongly correlated with growth. The empirical results confirm very well

the theoretical results as for the importance of banking and micro banking development on the economic

growth. As for the results concerning the development of monetary mass (M2), intermediation margin (Mi)

and banking reorganization (D), they also confirm the theoretical analysis. The coefficients associated with

LM2 (0,097), LMi (0,046) and D (0,076) being positive insinuate that the development of M2, Mi and the

banking restructuration positively affect economic growth in short, average and long run. The estimated

coefficients of the variables have all of the awaited signs. Although not being all statistically significant, the

estimated coefficients show a significant effect of financial development on the GDP future rates of growth

and the accumulation of capital.

We can stress here the importance of financial intermediation in the process of economic development

in Cameroon through intermediation margin (Mi) which would mobilize the capacity of granting private

credits. Thus, the presence of intermediation margin increases volume of credits and brings a better

allowance of resources towards investments projects. The financial factor (intermediation margin) can have

effects not only on the level of capital stock or on the level of productivity, but also on their rate of growth.

This regression has a good fit more especially as the R2 (0,881 close to one) is more than 70%. It shows

that the development of Ccmlt, M2, Mi and D act on economic growth both in the short and long run. These

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645

results are compatible with the fact that a dynamic financial system improves present and future GDP growth

rate.

Generally, there is implicitly an assumption according to which Financial Intermediation has a positive

impact on economic growth. For example provisions from payment services in economy have a positive

impact on the payment system of the economic activities (Johson, 1998). The great availability of investment

alternatives from Financial Intermediation affects the economy through an increase in investments efficiency,

a reduction of capital costs transfer from non-financial Agents (ANF) to Financial Agents (AF) and a change

of saving level (Pagano, 1993). Financial Intermediation contributes to the allowance of resources and

consequently to economic growth via a quantitative increase in Gross domestic product. Financial

Intermediation affects the economic growth through the level of saving as well as Financial Intermediation

reducing risks, involves large hopes for the investors and thus more investment or less investment for a

specific objective.

Analysis of the Relationship between Financial Intermediation and Economic growth

We use the stationnarity test of Dickey-Fuller and the test of AIC (Akaike Information Criteria) to

determine the number of lags, the estimation of the VAR model and finally the study of causality by the

method of Toda-Yamamoto. We noted above that our variables are globally integrated. But as far as we are

using the methodology of Toda-Yamamoto (1995), wether our variables (LPibr, LCcmlt, LM2 and LMi) are

stationary or not, we can thus carry out the model’s estimation.

To determine the lag, we used AIC, HQ and SC criteria. We find that the minimum lag is k=1. Thus

according to the assumption of the test of Toda-Yamamoto, the lag is p=k+1 i.e. p=2. Only the test of

information of Akaike (AIC) is taken into account, which enables us to carry out the estimation.

Table 3: Estimation of the VAR model

LOGPIB (I)

LOGCCM

(II)

LOGMI

(III)

LOGM2

(IV)

LOGPIB(-1)

0.740047

(0.29471)

[ 2.51107]

0.025226

(0.18855)

[ 0.13379]

0.030316

(0.04830)

[ 0.62761]

0.005714

(0.01243)

[ 0.45970]

LOGPIB(-2)

3.855238

(4.20259)

[ 0.91735]

0.624958

(2.68865)

[ 0.23244]

1.424377

(0.68880)

[ 2.06791]

0.156572

(0.17725)

[ 0.88332]

LOGCCM(-1)

-0.145055

(0.46468)

[-0.31216]

0.429352

(0.29728)

[ 1.44426]

-0.067276

(0.07616)

[-0.88335]

-0.005842

(0.01960)

[-0.29806]

LOGCCM(-2)

-3.634295

(4.20035)

[-0.86524]

-0.653059

(2.68722)

[-0.24302]

-1.434860

(0.68843)

[-2.08424]

-0.178249

(0.17716)

[-1.00615]

LOGMI(-1)

-0.683945

(1.28856)

[-0.53078]

-0.200441

(0.82437)

[-0.24314]

0.887778

(0.21119)

[ 4.20361]

-0.055636

(0.05435)

[-1.02369]

LOGMI(-2)

-0.404261

(1.35932)

[-0.29740]

-0.108141

(0.86964)

[-0.12435]

-0.350202

(0.22279)

[-1.57188]

0.052662

(0.05733)

[ 0.91854]

LOGM2(-1)

-0.920012

(5.26517)

[-0.17474]

1.706477

(3.36845)

[ 0.50661]

0.492173

(0.86296)

[ 0.57033]

0.738394

(0.22207)

[ 3.32504]

LOGM2(-2)

-0.400877

(6.17925)

[-0.06487]

0.088089

(3.95324)

[ 0.02228]

1.185546

(1.01277)

[ 1.17060]

0.311381

(0.26062)

[ 1.19475]

M. Giscard et al.

646

NB: - figures without brackets represent the coefficient of the variables

- figures in brackets represent the standard errors.

- figures in [ ] represent the value of t-student.

- C: is the constant.

The VAR model estimated above has a good fit. The R2 is more than 70% in general and the adjusted

R2 with a value of more than 60% in average. Furthermore, the F- statistic is globally significant. Referring

to the coefficients signs, GDP and M2 vary in the same direction with private credits citeris paribus. Only

intermediation margin varies in the opposite direction with credits, which means that when intermediation

margin increases, credits decrease which is not normal in practice. In fact the increase of Mi should instead

stimulate banks and MFE to grant more credits. This situation could be explained by poor growth

environment, research of guaranteed and slowness of the feasibility study of projects.

Results and Interpretation of the Causality Test

From the increasing interdependence between the variables, it arises from the literature that economic

growth causes Financial Intermediation; that Financial Intermediation causes to a certain extent economic

growth and without forgetting the debate according to which there exist a bi-directional link between

economic growth and Financial Intermediation. Several tests are performed to test the causality between the

variables, but within the framework of our study, the tests of causality according to Toda-Yamamoto used

are represented in the table below.

Table 4: Results of the test of Causality

Variables Number of

observations Khi-2 Probabilities Decisions

CCM → GDP 28 0.828246 0.6609 NO

M2 → GDP 28 0.124055 0.9399 NO

MI → GDP 28 1.182932 0.5535 NO

GDP → CCM 28 0.065555 0.9678 NO

GDP → M2 28 0.909067 0.6347 NO

GDP → MI 28 4.427219 0.1093 NO

M2→ CCM 28 0.654288 0.7210 NO

MI → CCM 28 0.233915 0.8896 NO

CCM → M2 28 1.081577 0.5823 NO

MI → M2 28 1.124322 0.5700 NO

CCM→ MI 28 5.002027 0.0820 YES

M2→ MI 28 6.470339 0.0394 YES

C

34.89327

(35.9158)

[ 0.97153]

-10.32133

(22.9775)

[-0.44919]

-12.07760

(5.88655)

[-2.05173]

0.018287

(1.51483)

[ 0.01207]

R2 0.532468 0.541571 0.901858 0.904425

Ajusted R2 0.335612 0.348548 0.860535 0.864183

F-statistic 2.704862 2.805734 21.82455 22.47456

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647

We can see from table 4 that there is an uni-directional causality from credits to intermediation margin

and from monetary mass to intermediation margin. This is due to the fact that profits realised by the financial

intermediaries (Banks and MFE) generally come from the granted loans. The creation of the quantity of

money in circulation M2 by the Banks influences the quantity of credits granted by the Banks and EMF. The

fact that credits cause intermediation margin is a good sign for foreign investors who could be potentials

borrowers in order to produce significant profits. When credits are rather high, they can carry intermediation

margin in Cameroon.

We will initially examine the causal relationship between Financial Intermediation and economic

growth; then between economic growth and Financial Intermediation; between growth, monetary mass,

intermediation margin and credits; between growth, credits, intermediation margin and monetary mass and

finally between growth, credits, monetary mass and intermediation margin.

The causality table above shows that Financial Intermediation does not have a causal effect on growth

in Cameroon. Refering to the p-values (less than 10%), we see that there is no causal relationship between

private credits (Ccmlt), Monetary mass (M2), intermediation margin (Mi) and Gross domestic product in

Cameroon from 1977 to 2006. In other words FI doesn’t granger cause economic growth in Cameroon. This

result can be explained according to the literature by the restructuring of the banking system between 1980

to1992, bank overliquidity, MFE’s instability and poor growth environment in Cameroon. Actually, let us

note that the Financial Intermediation must be strong enough to lead to growth.

In Cameroon, short term credit are low and do not make possible a durable foundation of mass

production. Also, banks and MFEs are demanding as for the quality of the guarantee to be provided by the

borrowers, not forgetting the fact that the high interest rates do not encourage the investors who risk averse.

Thus these banks are overliquid whereas the level of investment through credits of the country is low. This

non causality could also be explained by significant opening of the cameroonian economy and by the perfect

mobility of capital.

Moreover, the fact that FI does not have a causal link to growth could be also explained by the

weakness of investment which does not carry economic growth. Let us also note that during the economic

crisis that started in 1987 in Cameroon up to 1994, we recorded negative growth rates, which led to a fall of

investment rate. Let us also note that administrative slowness and high taxes are likely to discourage

investments which also discourage private credit.

Actually, the non causality effect of growth on FI in Cameroon is due to the consequences of the

Structural Adjustment Program as well as the HIPC which put the country in a vast building site in all

sectors, creating multiple fictitious jobs while increasing the income of a minority of Cameroonians. One can

believe that the profit drawn from the investments is not invested to consolidate the existing economic

activities. Thus a high level of economic growth does not create demand for certain financial instruments

which find their answers in the development of the financial markets in Cameroon. One can also explain this

non causality by the weight of the debt of the country. Indeed, one could think that profits from growth are

swallowed by debt service.

There is no relationship of causality between GDP, M2, Mi and private credits. This situation could be

explained by ungrowth environment, research of guarantee and slowness in the feasibility study of projects.

It means that margin profit resulting from credit operations is not reinvested. The main reason of this

rationing is the fight against the risk of anti selection and moral risk. Thus, uncertainty and information

asymmetry which characterize markets, in particular credit market, leads financial institutions to rationate

credits.

There is a causal relationship between credit (Ccmlt), M2 and Mi. This is explained by the fact that

profits realised by the financial intermediaries (Banks and MFE) generally come from the granted loans. The

creation of the quantity of money in circulation M2 influences the quantity of credits granted by the Banks

and EMF. The fact that credits cause intermediation margin is a good sign for foreign investors who could be

potentials borrowers in order to produce significant profits. When credits are rather high, they can carry

M. Giscard et al.

648

intermediation margin in Cameroon. On the other hand, a relationship of causality between GDP and the

intermediation margin (Mi) hardly exist because its p-value is greater than 0.1.

5. Conclusion

This article at the same time offers an empirical relativisation of the concept "intermediate market

economy" and an illustration of the importance gained in recent years by the capital market. The

econometric software Eviews enables us to carry out the different regressions. The test of Fischer made it

possible to deduce that the first model of multiple linear regression is overall nonsignificant; but some

exogenous variables in the model contribute to the explanation of economic growth. To this end the analysis

of the signs of the coefficients enabled us to conclude that credits to private sector; monetary mass as well as

intermediation margin induce in a positive way the growth. That confirms our first assumption. The Granger

causality test of Toda-Yamamoto shows that Financial Intermediation does not have a causal effect on

economic growth in Cameroon, contrary to several empirical studies which testify that it is FI that causes

growth. This could be explained by unproductive investments (which are centered on the means and not the

results), corruption and especially the diversions of funds in the attribution of government contracts which

brings a bad quality of realization, or the period of study which would be very large and the effects are felt

on the results. This disappearance is due to the fact that the socio-economic environments in which Banks

and MFE as well as the amounts of the deposits and credits are differents. It should be noted that, Goldsmith

in 1969, recognized that there is a link between the long run growth rate of the economy and the level of the

evolution of financial sector.

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