







































American Interdisciplinary Journal of Business and Economics  

ISSN: 2837-1909| Impact Factor: 6.72 

Volume. 10, Number 2; April-June, 2023;  

Published By: Scientific and Academic Development Institute (SADI)   

8933 Willis Ave Los Angeles, California  

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EXPLORING THE RELATIVE SIGNIFICANCE OF BANKING AND  

STOCK MARKET DEVELOPMENT IN PROMOTING ECONOMIC  

GROWTH IN DEVELOPING COUNTRIES  
  
  

Levin H.  
Institute of Islamic Banking and Finance, International Islamic University Malaysia 50400 

Kuala Lumpur, Malaysia  

 
Abstract: This study investigates the relative contributions of banking sector and stock market development 

on the economic growth of developing countries. Using panel data from 20 developing countries over the 

period 1989 to 2010, the study adopts panel co-integration and Fully Modified Ordinary Least Squares 

techniques to analyze the data. The results indicate that intermediated funds have a more significant 

contribution to the growth process than the stock market, and banks and stock markets are substitutes rather 

than compliments in financing economic activities in these countries. In addition, the study finds a strong 

positive influence of financial development on economic growth. The findings highlight the importance of 

deepening and strengthening the financial systems of developing countries and promoting financial 

integration locally and across borders.  

 
Keywords: Banks, Stock Market, Development, Developing Countries, Panel Co-integration, Economic 

Growth  

  

  

Introduction: The role of financial sector development in enhancing economic growth has been a widely 

debated issue in recent years. Various studies have explored the nexus between financial sector development 

and economic growth, and the results have been mixed. While some studies suggest a significant positive 

relationship, others find no significant relationship or even a negative one. The specifics of the relationship 

between financial sector development and economic growth vary across countries due to differences in 

financial systems, institutional frameworks, and economic conditions.  

Developing countries, in particular, face significant challenges in financing economic activities, especially 

through the banking and stock markets. These challenges have prompted policymakers to implement reforms 

aimed at deepening and strengthening the financial systems of these countries. Nevertheless, there are still 

unresolved issues in the finance-growth literature, particularly in the context of developing countries. This 

study seeks to contribute to this literature by examining the relative contributions of banking sector and stock 

market development to economic growth in developing countries. The study uses a panel dataset of 20 

developing countries over the period 1989 to 2010, employing panel co-integration and Fully Modified 

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Ordinary Least Squares techniques to analyze the data. The study provides insights into the extent to which 

intermediated funds and stock markets contribute to the growth process in developing countries, as well as 

the relationship between banks and stock markets in financing economic activities. The findings of this study 

have significant implications for policymakers and provide insights into the ways in which developing 

countries can deepen and strengthen their financial systems to promote economic growth.  

2.0 LITERATURE REVIEW  

In a pioneer work, King and Levine (1993) investigate the finance-growth relationship in a cross-country 

study involving 80 countries and found that financial development is strongly associated with real per capita 

GDP growth, the rate of physical capital accumulation and improvements in the efficiency with which 

economies employ physical capital. This finding is further reinforced by Levine and Zervos (1998) who found 

that both stock market liquidity and banking development positively predict growth, capital accumulation and 

productivity even after controlling for economic and political factors. Their results also revealed that stock 

markets provide different category of financial services from banks.   

In another perspective, Rioja and Valev (2003) investigate the effects of financial development on the sources 

of growth in countries belonging to different income group. The results showed that finance has a strong 

positive influence on productivity growth primarily in higher income economies, whereas in lower income 

economies, the effect occurs primarily through capital accumulation. This has revealed that financial 

intermediaries in the developing countries lack the capacity to effectively select and monitor most profitable 

investments, rather some social and political parameters are used in providing funding. This might lead to 

moral hazard and financial instability, which may stifle the contribution of finance to growth or even making 

financial development to adversely affect growth. This finding is further supported by Dufrenot, Mignon, and 

Peguin-Feisolle (2010). They found that, while financial intermediation is a positive determinant of growth 

in developed countries, it acts negatively on the economic growth of developing countries. In contrast, 

Baliamoune-Lutz (2010) found that there was no strong evidence that finance leads economic development 

in 18 sub-Saharan Africa (SSA) countries.   

On the other hand, Kiran, Yavuz and Güriş (2009) investigate the long-run relationship between financial 

development and economic growth in 10 emerging countries for the period 1968 to 2007. Employing the 

panel co-integration technique and fully modified OLS the study finds that financial development has a 

significant positive influence on economic growth. Similarly, in Africa, Ahmed (2010) employed the same set 

of techniques and finds a long-run equilibrium relationship between financial development and economic 

growth; furthermore, financial development is found to cause economic growth. On whether stock markets 

and banks are compliments or substitute, Dey (2007) found that bank credit and stock market liquidity are 

inversely related and they substitute each other in providing external financing to firms.   

These conflicting findings suggest that there are still unresolved issues in the financegrowth literature, 

especially in the context of the developing countries. More so, the afore reviewed studies were silent on the 

relative importance of bank and stock market development to growth and whether the increasing role of stock 

market in developing countries is at the expense of banks or it is just complimenting it. This study is an attempt 

to fill the literature gap by using more recent methods and wider dataset involving several developing 

countries.   



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3.0 DATA AND METHODOLOGY  

Based on the extant literature and insight from the endogenous growth model, the following model is specified 

to investigate the relationship between financial development and economic growth in developing countries:  

lnGDPit  1i lnFDit  2i lnGFCFit  3i lnCVit  (1)   

Where GDP is the real GDP, FD is a vector of financial development indicators, GFCF is gross fixed capital 

formation, CV is a vector of control variables; all are in natural log, the disturbance term it is assumed to be 

white noise and follows a one-way error component model.Eight different specifications of the above model 

were estimated. The first four measure the independent effects of broad money, bank credit, stock market 

capitalization and stock market turnover on economic growth. The fifth and sixth specifications measure the 

contemporaneous effect of banking sector and stock market development on economic growth. The last two 

specifications, involve the interactive terms of banking and stock market development. It is used to investigate 

whether they are substituting or complimenting each other.   

The financial development indicators used are ratio of broad money to GDP (BMG) and ratio of private credit 

by the banking sector to GDP (CRD). The BMG is used to measure the overall financial depth of the economy 

or the level of monetization in the economy. However, in developing countries, where a large component of 

the broad money stock is currency held outside the banking sector, broad money is less indicative of the degree 

of financial intermediation by banking institutions (Esso, 2010). McKinnon (1973) hypothesis however, posits 

that in developing countries, a broadly defined demand for money complements the demand for physical 

capital. This position is derived from an outside money model in which economic units are constrained to 

self-finance and there are considerable indivisibilities in investment. Therefore, cash balance holdings are 

positively related to the propensity to invest, this informs the choice of this indicator in this study. Specifically, 

banking sector development is measured by the ratio of private credit by deposit money bank to GDP; it is 

included to reflect the actual financial intermediation activity of commercial banks.    

Two indicators of stock market development are employed, namely market capitalization (MCP) and stock 

traded (STR) both as ratios of GDP, representing the size and liquidity of the stock market, respectively.The 

first equals the value of the shares of listed companies on domestic exchanges; it reflects the ability to mobilize 

capital and diversify risk, whilethe second indicator measures the activity of the stock market trading volume 

relative to the size of the economy, thus,it reflectsthe liquidity that stock market provide to economic agents 

(Mohtadi & Agarwal, 2004).   

Gross fixed capital formation is used as a proxy for capital accumulation. Furthermore, some variables are 

included in the model to control for the possible effects of other growth determining factorsin order to avoid 

misspecification bias. These variables are total government expenditure (TGE) and trade openness (OPN). 

Government expenditure may lead to budget deficit, which if financed by borrowing from the financial system 

and has the potential of crowding-out private investment and hence negatively affects growth. Alternatively, 

government spending if effectively carried-out, may contribute positively to growth.Trade openness may 

contribute positively to economic growth by providing domestic entrepreneurs access to foreign markets.  

Data utilized in this research is on annual basis and in 2005 constant US dollars (USD), covering the period 

from 1989 to 2010 for each country, hence constituting a balanced panel. The data is obtained from the World 

Development Indicatorsand Global Financial Development Databaseof the World Bank.The list of the 

countries considered in this study and descriptive statistics of the variables are contained in Appendices1 and 

2 respectively.   

0 i  it   



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To estimate the long run relationship between financial development and economic growth in the panel of 20 

countries over the period 1989 to 2010 panel co-integration test is adopted. Generally, panel co-integration 

involves three stages; firstly, panel unit root tests panel co-integration test and estimation of long run 

coefficients. The Levin and Lin (1993) and Levin, Lin and Chu (2002) panel unit root test -LLC, Im, Pesaran 

and Shin (2003) –IPS, Breitung (2000) and Maddala and Wu (1999) -MW The advantage of MW test over 

IPS is that its value does not depend on different lag lengths in the individual ADF regressions (Kiran, Yavuz 

& Güriş, 2009; Bangake & Eggoh, 2010).    

Residual-based panel co-integration test by Pedroni (1999, 2000 & 2004) is adopted. The test takes into 

account the heterogeneity of the cross-section units, by using idiosyncratic parameters, which are allowed to 

vary across the cross-section unitsThe test considers the following regression equation:   

yit  i  it  1i x1i,t  2i x2i,t  ... Mi 

xMi,t  ei,t (2) t  1...T,i  1...N  

Where T is the number of observations over time; N represents number of cross section units (countries); M 

is the number of the regression variables; y and x are assumed to be integrated of order one and αi varies 

across individual countries in the panel. The residual, which is to be tested for stationarity is given by:   

eit  eit 1  uit or by the following augmented equation: (3)    

pi eit  i eit 1  ij  eit j  vit  

(4)   

j 1  

The study adopted the Pedroni (2000; 2001) Fully Modified OLS (FMOLS) estimator, which is based on the 

correction of the dependent variable using the long‐run covariance matrices in order to remove the nuisance 

parameters and then applies the standard OLS estimation technique to the corrected variables.  This method 

has many advantages, among them are; it accounts for the serial correlation and endogeneity in the regressors 

that are usually present when long-run relationship exists. In addition, it tackles the problems of 

nonstationarity in regressors and simultaneity bias as well as generates consistent estimates of the β 

parameters in small samples (Christopoulos & Tsionas, 2003; Kiran, Yavuz & Güriş, 2009).   

4. RESULTS AND DISCUSSIONS   

4.1  Results   

The results of the panel unit root tests at the levels of the variables are presented in Table 1. Deterministic 

trend and individual effects (intercept) are included in the tests, going by the plot of the variables, which 

shows the presence of linear trend and intercept. Generally, the null hypothesis of unit root could not be 

rejected at 5%, implying that the variables are not stationary at levels. However, there is an exception in the 

cases of LCRD, LGFCF and LMCP, which were respectively reported to be stationary by the MW, LLC and 

IPS tests. But given the weaknesses of these tests as highlighted earlier and that in all the three cases, the other 

three tests reported the variables to be non-stationary, the variables are considered to be non-stationary at 

levels.  

TABLE1.Results of Panel Unit Root Test at Levels   

  
Variables   Common unit root process    Individual unit root process   LLC  Breitung   IPS  

  MW   

 
LBMG   -0.314    0.482    0.703    35.530   

LCRD    1.227    1.257   -0.251    66.935***   



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LGDP   -0.164    1.893    0.438    45.876   

LGFCF   -3.482***   -0.837   2.974    29.688   

LMCP   -0.244   -1.283   -1.665**    51.354   

LOPN    0.170    0.045   -1.042    51.423   

LSTR   -0.013   -0.643   -0.914    50.003   

LTGE   0.815   -1.311   4.836    15.297   

 
Note: ***, ** and * denote statistical significance at 1%, 5% and 10%, respectively. Selection of lag length is 

based on Schwarz information criteria.  

Upon taking the first difference of the variables, the null hypothesis of unit root was unanimously rejected by 

all the tests at 1%, thus, the variables turned out to have no unit rootas reported in Table 2. This means that, 

all the variables are stationary at first difference and hence, integrated of order one. Consequently, the basis 

toinvestigate the existence of long run relationship through panel co-integration test is provided. TABLE 

2.Results of Panel Unit Root Test at First Difference   

  
Variable   Common unit root process    Individual unit root process   

   LLC   Breitung   IPS   MW   

LBMG   -11.838***   -8.663***   -12.817***    202.433***   

LCRD   -7.465***   -5.086***   -10.615***    172.129***   

LGDP   -10.170***   -5.333***   -8.466***    137.850***   

LGFCF   -10.162***   -7.345***   -8.458***    136.748***   

LMCP   -11.480***   -8.368***   -10.257***    164.668***   

LOPN   -13.209***   -3.264***   -10.127***    161.404***   

LSTR   -10.513***   -4.723***   -11.344***    187.615***   

LTGE   -11.228***   -5.300***   -12.611***    202.262***   

Notes: ***, ** and * denote statistical significance at 1%, 5% and 10%, respectively.    

Selection of lag length is based on Schwarz information criteria.  

The results of the Pedroni panel co-integration tests for the various specifications statedearlier are contained 

in tables three and four. Like in the case of the unit root tests, deterministic trend and individual effects are 

also included in the co-integration tests; this is because including time specific effects makes the Pedroni 

panel cointegration tests more powerful (Carlsson, Lyhagen & Österholm, 2007).  

TABLE 3.Results of Pedroni Panel Co-integration Tests for Banking and Stock Market Independent Models   



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Private Credit   

   

  

Market   

Broad Money   

Capitalisation   

 Stock Turnover   

  

 Statistic   ρ-  

Value   

Statistic   ρ-  

Statistic Value   

ρ-  

Value   

Statistic   ρ-  

Value   



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Panel Statistics        Within-Dimension        

Panel v- 

Statistic   

26.589***   0.000   27.700***    0.000  21.153***  0.000   23.938***   0.000   

Panel rho-  

Statistic   
1.997   0.977   1.764    0.961   2.500   0.994   1.602   0.946   

Panel PP-  

Statistic   
-3.137***   0.001   -3.733***    0.000  -1.786**   0.037   -3.313***   0.001   

Panel ADF-  

Statistic   

-3.006***   0.001   -3.623***    0.000  -2.105**   0.018   -4.256***   0.000   

Group   

Statistics   

      Between- 

Dimension   

      

Group rho-  

Statistic   

3.987   1.000   4.190    1.000   4.443   1.000   3.994   1.000   

Group PP-  

Statistic   
-4.340***   0.000   -1.933**    0.027  -1.789**   0.037   -1.720**   0.043   

Group ADF-  

Statistic   

-3.588***   0.000   -2.268**    0.012  -2.938***  0.002   -3.774***   0.000   

Note: ***, ** and * denote statistical significance at 1%, 5% and 10%, respectively.   

The results in Table 3, revealed that three of the five within dimension and two of the three between dimension 

Pedroni panel co-integration tests, have rejected the null hypothesis of no co-integration. Therefore, we can 

deduce that a long run equilibrium relationship exists between economic growth on one hand and monetary, 

banking and stock market development represented by broad money, private credit, market capitalization and 

market turnover as well as other control variables on the other hand.  

TABLE 4.Results of Pedroni Panel Co-integration Tests for Concurrent Banking and Stock Market Models   

   CRD*MCP    CRD*STR    CRD & MCP   CRD & STR   

   Statistic   ρ-  

Value   

Statistic   ρ-  ρ-  

Statistic Value   Value   

Statistic   ρ-  

Value   

Panel Statistics         Within-Dimension         

Panel v-Statistic   21.153***    0.000    23.938    0.000    24.375***    0.000    27.301***   0.000   

Panel   rho-  

Statistic   
2.500 

  
 0.994    1.602    0.946   2.845     0.998   2.569     0.995   

Panel PP-Statistic  -1.786**    0.037   -3.31***    0.001   -3.188***     0.001   -3.157***    0.001   

Panel   ADF-  

Statistic   

-2.105**    0.018   -4.26***    0.000   -3.529***     0.000   -3.785***    0.000   

Group Statistics         Between-Dimension         

Group   rho-  
Statistic   

4.443    1.000   3.994    1.000  4.878    1.000   4.672     1.000   

Group   PP-  

Statistic   
-1.789**    0.037   -1.720**    0.043  -4.775***    0.000   -3.667***    0.000   

Group   ADF-  

Statistic   

-2.938***    0.002   3.774***    0.000  -4.687***    0.000   -4.738***    0.000   



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Notes: CRD*MCP and CRD*STR are models involving the interactive terms (product of) private credit and 

market capitalisation and stock turnover ratio respectively, while CRD&MCP and CRD&STR are models 

simultanously involving private credit and each of market capitalisation and stock turnover respectively.    ***, 

** and * denote statistical significance at 1%, 5% and 10%, respectively.  

Similarly, Table 4 shows that majority of the seven Pedroni panel co-integration tests reject the null hypothesis 

of no co-integration at 1% or 5% level of significance. This means the long run relationship between economic 

growth and the various measures of financial development in developing countries is robust irrespective of 

whether banks and/or stock market are considered independently or jointly. However, the results from both 

tables have shown thatPanel rho and Group rho-tests consistently accept the null of no co-integration. But this 

is not worrisome; since a Monte Carlo simulation by Pedroni (2004) shows that the two tests tend to 

underestimate the rejection of the null when N and T are small. Therefore, we conclude that long run 

relationship exists between the variables and thus proceed to estimate the long run coefficients.   

The long run coefficients of the co-integratingvector are estimated using the FMOLS estimator for the various 

specifications; the results are presented in Table 5. In all cases the dependent variable is real GDP.In the first 

model (involving bank private credit) presented in panel one of Table 5, it is clear that private credit is 

significantly contributing to economic growth, with every 1% increase in private credit resulting into 0.36% 

increase in real GDP. The other variables in the model are equally important for growth, as a percentage 

increase in gross fixed capital formation and trade openness are causing real GDP to increase by 0.21% and 

0.52% respectively. The only exception is government expenditure, which turnout to have negative influence 

on growth, though in negligible amount compared to other variables in the model.     

The positive effect of financial development on growth is even higher when the ratio of broad money to GDP 

is used as a proxy for financial development. The results in panel one of Table 5, show that a 1% increase in 

broad money will lead to 0.56% increase in real GDP,which is 0.20% larger than the effect of private 

credit.The same goes for gross fixed capital formation, which contribute 0.25% to GDP for every percentage 

increase. These phenomena have implied that to a large extent, investment in developing countries is 

selffinanced. However, the effect of trade openness is suppressed and government expenditure is no longer 

having any impact on GDP.    

Both indicators of stock market development, that is market capitalization and stock turnover are also 

significantly influencing real GDP, but to a lesser degree than private credit and broad money. From the results 

in panel two of Table 5, a 1% increase in market capitalization leads to 0.13% increase in real GDP. On the 

other hand, stock turnover, brings about only 0.06% increase in real GDP, this is indicative of low activities 

in the stock market of developing countries. Other variables in the stock market models exhibit about the 

same pattern as in the broad money and private credit models. Trade openness is still making tremendous 

positive contribution to GDP (0.40% and 0.57%, respectively) and government expenditure exert negative 

influence in only the stock turnover model. The effect of gross fixed capital formation is very insignificant in 

the market capitalization model, but slightly significant in the stock turnover model.  

TABLE 5.Long Run Estimates Using FMOLS   

    Banking and Monetary Sectors        

Variables   Coefficient   t-stat   ρ-Value   Variables   Coefficient   t-stat   ρ-Value   

LCRD   0.361***   8.241   0.000   LBMG   0.564***   7.587   0.000   

LGFCF   0.211***   2.775   0.006   LGFCF   0.252***   3.185   0.002   

LTGE   -0.116*   -1.836   0.067   LTGE   -0.066   -0.991   0.322   



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LOPN   0.515***   8.976   0.000   LOPN   0.392***   6.133   0.000   

      Stock Markets         

 LMCP   0.131***   5.542   0.000   LSTR   0.057***   2.891   0.004   

LGFCF   0.000***   2.983   0.003   LGFCF   0.169*   1.848   0.065   

LTGE   -0.017   -0.242   0.809   LTGE   -0.172**   -2.385   0.018   

LOPN   0.402***   6.036   0.000   LOPN   0.570***   8.658   0.000   

    Banks and Stock Market Concurrent       

LCRD   0.291***   6.600   0.000   LCRD   0.364***   8.327   0.000   

LMCP   0.093***   4.178   0.000   LSTR   0.018   1.074   0.284   

LGFCF   0.153**   2.057   0.040   LGFCF   0.176**   2.258   0.025   

LTGE   -0.017   -0.276   0.783   LTGE   -0.125**   -2.032   0.043   

LOPN   0.385***   6.319   0.000   LOPN   0.499***   8.865   0.000   

    Banks and Stock Market Interaction       

LCRD*LMCP   -0.083***   -8.538  0.000   LCRD*LSTR -0.065***   -7.049   0.000   

LGFCF   0.164**   2.205  0.028   LGFCF   0.060   0.720   0.472   

LTGE   0.036   0.566  0.571   LTGE   -0.099   -1.498   0.135   

LOPN   0.389***   6.656  0.000   LOPN   0.523***   8.806   0.000   

Notes:The coefficient of LGFCF in the LMCP model is 0.000000000010 and cannot be contained in the 

column, this is why 0.000 is written.    

***, ** and * denote statistical significance at 1%, 5% and 10%, respectively.  

In the above models, roles of banks and stock market to economic growth are treated independently. However, 

in reality the two runs concurrently in financing real economic activities. In most cases firms do not restrict 

their sources of external finance to either banks or stock market alone, they rather explore both sources. Based 

on this assumption, models were estimated that combine bank credit on one hand and market capitalization 

and turnover on the other hand. The results in panel three of Table 5, revealed that banks still dominate the 

financing of real economic activities; a 1% increase in bank private credit accounts for 0.29% increase in real 

GDP as against mere 0.09% by market capitalization. The effect of banks become even more domineering, 

when stock market development is represented by market turnover ratio, which turn out to have no significant 

influence on real GDP.     

Having been able to ascertain the relative significance of banks and stock market to real GDP, the next task is 

to find out whether bank and stock market are compliments or substitutes. This is very relevant, because stock 

markets in many developing countries came into existence much later than banks, which means they either 

take away some part of the market share of banks or compliment them in providing finance to the private 

sector. The results in panel four of Table 5, shows thatthe interactive term of both bank private credit and 

market capitalization as well as stock turnover, are negative and statistically significant. This means that bank 

and stock market in developing countries are substitutes, rather than compliments.   

4.2 DISCUSSIONS OF FINDINGS  

From the empirical results presented and analyzed in the previous section, broad money appeared to be the 

most influential contributor to real GDP, above other financial development indicators. This implied that 

selffinance still dominates the economies of many developing countries, thereby conforming to the McKinnon 

(1973) hypothesis. According to this hypothesis, economic units are constrained to self-finance in developing 

countries, which are characterized by small-sized private firms. Under this condition, money plays an 



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important role in increasing the amount of physical investment, therefore, cash balances holdings are 

positively related to propensity to invest.    

Moreover, banks appeared to greatly play more roles in influencing real GDP than stock market. This shows 

that banks still dominate the financial system of developing countries; the obvious reason for this might be 

that the real sectors in developing countries are dominated by small and medium scale enterprises, which 

cannot access the stock market. This result confirmed Kronberger (2002) and Baliamoune-Lutz (2010) 

assertions that the financial systems of developing countries are dominated by banks, hence the bulk of 

investment financingis sourced from the banking sector.   

Market capitalization is also found to be more significant in influencing real GDP than market turnover. This 

is indicative of the fact that there are low activities in the stock markets of many developing countries. Most 

of the stock markets in developing countries were established recently, therefore, the stock market 

capitalisation largely represents initial public offerings by private firms and in some cases by privatized public 

enterprises. Thus, market capitalisation tends to have more effect on real GDP than stock turnover. The 

individual contribution of banks to real GDP is not significantly improved when stock market was introduced 

and vice versa. In the case of stock market, the introduction of banks even reduces its contribution to real 

GDP. This is indicative to the fact that the two are not compliments. In fact, the results clearly suggest that 

banks and stock market are substitute rather than compliment. This confirmed the findings of Dey (2007) and 

contradicts the findings of Boyd and Smith (1998).Overall, the findings of this study revealed that financial 

development in the form of monetary, banks and stock market development are positively influencing real 

GDP in developing countries. These results confirmed the findings of Levine and Zervos (1998) and Kiran, 

Yavuz and Güriş (2009).   

CONCLUSIONAND RECOMMENDATIONS   

The study concluded that the overall depth of the financial sector represented by broad money is the most 

significant contributor to growth; meaning that self-finance still largely constitutes the mode of financing real 

economic activities, which are majorly in the form of small and medium enterprises. On the relative 

importance of banks and stock market, the study found that the banking sector is to a large extent relatively 

more significant in financing real GDP than the stock market. This has confirmed the claim that the financial 

systems of developing countries are dominated by banks, with the stock market gradually catching up.  The 

stock markets of developing countries are also found to have low activities, as market capitalization plays 

significantly more role than stock turnover. Moreover, banks and stock markets are found to be substitutes, 

rather than compliments; meaning that they are competing for both savers funds and investment opportunities 

to finance; this will lead to efficiency in the activities of both. It also suggests that the introduction of stock 

markets in developing countries is gradually diversifying their financial system and lessening the traditional 

dominance of the banking system. The policy implication of these findings is that financial reforms should be 

implemented across the board that is in all the sectors of the financial system as against selective policy. This 

will ensure that the real economy gets the best from the financial system.    

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