




































Copyright © CC-BY-NC 2019, CRIBFB | AESR 

                       American Economic & Social Review; Vol. 5, No. 1; 2019 

                  ISSN 2576-1269   E-ISSN 2576-1277  

Research Article               Published by Centre for Research on Islamic Banking & Finance and Business, USA 

 

     33 
 

Financial Structure and Economic Growth: The Nigerian 

Experience, 1980-2017 
 

 

Emeka Nkoro PhD   

Department of Economics  

University of Port Harcourt 

Nigeria 
E-mail: nkoro23@yahoo.co.uk 

 

Aham Kelvin Uko PhD 

Ministry of Environment, Abia State 

Nigeria 

 

Abstract   

This study investigated the role of financial structure in explaining economic growth dynamics in Nigeria using 

annual time series from 1981-2017. The study employed the vector error correction model (VECM) in the analysis 

of the data. As lead up to financial structure and economic growth relationship analysis, the competing theoretical 

views of bank and market based financial system and economic growth were explored. The result of the study 

showed that economic growth, financial development variables and the underlying control variables are 

cointegrated. The result of the economic growth effect of financial development showed that stock market and bank-
based have a significant effect on growth. This implies that both bank-based and market-based matter in explaining 

economic growth dynamics.  On the relationship between financial structure and economic growth, the study 

revealed that economic growth, financial structure and the underlying control variables have a long run relationship. 

The study also revealed that financial structure which captures the combination of stock market-based and bank-

based has a positive significant effect on growth. A significant coefficient of financial structure implies that financial 

structure matters in explaining growth. Therefore, the study posits that the overall financial structure is the most 

useful way to assess the financial systems since both bank and stock market system matter in explaining economic 

growth as against bank-based versus market-based debate. Based on the empirical evidence, the study therefore 

recommends that there should be continuous holistic reforms of both banking and stock market simultaneously, as 

the development in one sector has a neglect effect on the other.  

 

Keywords:  Stock Market, Financial Market, Financial Structure, Economic Growth, Vector Error Correction 
Model. 

 

1. Introduction  

Historically, there has been debate among scholars over the role of the structure of the financial systems to economic 

growth. Specifically, the debate is about the relative importance of bank-based and market-based financial systems 

in stimulating economic growth (Gerschenkron, 1962,  Stiglitz, 1985, Allen and Gale, 1999 and, Levine, 2002). 

Empirical studies (Hoshi et al, 1991, Mork and Nakkamura, 1999, Weinstein and Yafeh, 1998 and, Arestis et al., 

2001) from developed economies of the world- the United States of America and United Kingdom show that 

financial structure matters in explaining economic growth. The United States of America and United Kingdom are 

often portrayed as market-based economies while Germany and Japan are described as bank-based economies. The 

results from the developed countries never provided a realistic reference point for developing countries given the 

critical issues of differences in development and structure of both economies.  Contrarily, cross-section studies 

revealed that financial structure is irrelevant to economic growth. That is, neither the bank-based nor the market-

based financial system can explain economic growth; rather the studies opined that it is the overall provision of 

financial services (combination of banks and financial markets) that are important (Demirguc-Kunt and Levine, 

1996, Levine, 2003 and, Beck and Levine, 2002). Therefore, Levine (2001) was of the view that it may be better to 

think not in terms of banks versus stock markets but in terms of banks and stock markets. However, Luintel and 

Khan (2002) showed that panel estimates often do not correspond to country-specific estimates. This could be as a 

result of cross-country differences and, measurement, statistical, and conceptual problems. Consequently, 



Copyright © CC-BY-NC 2019, CRIBFB | AFBR 

www.cribfb.com/journal/index.php/aesr                                      American Economic & Social Review                                              Vol. 5, No. 1; 2019 

 

34 
                           

generalizations based on panel results may also be misleading at country level; hence the relationship between 

financial structure and economic growth remains inconclusive. These conflicting results call for country-specific 

study which is the concern of this study. 

Recently, the emergence of global financial crisis has made developed and developing economies to shift away from 

free market fundamentals to a regulated economic regime. As a measure of curbing the financial crisis, the 

governments of these economies take up major stakes in the financial markets through the injection of funds into the 

institutions of the economy and, this has raised critical issues in policy formulation. Some of the developed and 

developing countries injected liquidity in the form of preference shares while others injected liquidity in the form of 

tier-2 capital(bank supplementary capital). Scholars were of the view that this decision to move from free market 

based economy to regulated economic regime was informed by the countries’ preference for a particular financial 

structure based. According to Levine and Zervos (1998), developed economies show strong preference to a 

particular financial structure that exerts more influence on economic growth.  

To mitigate the effects of 2007/2008 global financial crisis, the Nigerian government decided to bail-out only banks 

in the form of tier-2 capital. However, the government never considered to bail-out the capital market, especially 

when the stock market was not spared by the crisis. This has the capacity of promoting the bank-based financial 

structure over the market-based financial structure. Empirically, studies have shown that assessing whether the 

relationship between bank development and growth holds when controlling for stock market development hampers 

the ability to make policy decisions on whether the overall financial structure matters for growth as well as 

identifying the separate impact of banks and stock markets on economic growth (Caporale et al., 2002). Hence, the 

following questions are relevant: does overall financial structure influence economic growth? Which of these 

structures exerts more influence on economic growth? This calls for an empirical investigation. 

The rest of the work is structured as follows; section two provides reviews of related and relevant literature, section 

three explains the method of analysis, section four focuses on the empirical results and discussions and, section five 

presents the conclusion and recommendations. 

2.Review of Literature 

Theoretical Review 

Gerschenken (1962) was the first to classified the financial system into two categories; bank-based and market-

based financial structure and ever since this has generated serious debate among scholars. The argument has been 

polarized along the following lines; (1) the standard parameters or measurement for classifying a country’s financial 

system either as bank-based or market-based; (2) which of these classifications exert more influence on economic 

growth; and (3) the determinants of a country’s financial structure. Also, according to scholars (La Porta et al, 1997 

and, Beck and Levine, 2002 and, Arestis and Luintel, 2004), the relationship between financial structure and 

economic development are discussed within four competing theories of financial structure. These competing 

theories are the bank-based view, the market-based view, the financial services view and the legal based view. These 

theories are examined in brief in what follows. However, before looking at the various theories of financial 

structure, it is proper to define financial structure. According to Stulz (2001), financial structure entails the 

institutions, financial technology, and rules that guide financial activity at a point in time, and also Merton (1995) 
added that it provides a payment system, that is, a mechanism for pooling funds, ways of transmitting resources 

across space and time, ways to manage uncertainty and control risk, price information to allow the economy to 

implement a decentralized allocation, and ways to deal with the asymmetric information problems that arise when 

one party to a financial transaction has information that the others do not have. 

The bank-based theory lays emphasis on the positive role of banks in development and growth, and also, stresses 

the shortcomings of market-based financial systems. It argues that banks can finance development more effectively 

than markets in developing economies, and, in the case of state-owned banks, market failures can be overcome and 

allocation of savings can be undertaken strategically (Gerschenkron, 1962). The bank-based view stresses that a well 

functioning market-based systems reveal information publicly, thereby reducing incentives for investors to seek and 

acquire information about firms. However, banks can make investments without revealing the decision immediately 

in public markets and, this creates incentives for them to research firms, managers, and market conditions with 

positive ramifications on resource allocation and growth. This argument is that if information is going to be revealed 

by the market, no one is motivated to collect it. This is known as free-rider problem. As a result, competitive market 

system may be characterized by under-investment in information. Consequently, well developed market systems 

have a negative impact on the identification of innovative projects, and thereby impede efficient resource allocation 

(Stiglitz, 1985 and, Boot, Greenbaum, and Thakor, 1993). Also, information asymmetries are thus accentuated, more 



Copyright © CC-BY-NC 2019, CRIBFB | AFBR 

www.cribfb.com/journal/index.php/aesr                                      American Economic & Social Review                                              Vol. 5, No. 1; 2019 

 

35 
                           

so in market-based rather than in bank-based financial systems (Boyd and Prescott, 1986). The distortions that 

emanate from asymmetric information can be eased by banks through forming long-run relationships with firms and, 

through monitoring, to control moral hazard. Consequently, scholars (Stiglitz, 1985 and, Bhide, 1993) assert that 

bank-based financial systems can produce better improvement in resource allocation and corporate governance than 

market-based institutions  

On the contrary, the market-based theory emphasizes the advantages of well-functioning markets, and stresses the 

problems of bank-based financial systems. The market based theory opines that big, liquid and well-developed 

markets foster growth and profit incentives, enhance corporate governance and, facilitate risk management (Levine, 

2002, and, Beck and Levine, 2002). The inefficiencies that are inherent in bank- based system as stressed by Levine 

(2002) can hinder firm innovation. For instance, once banks acquire substantial inside information about firms in the 

process of financing firms, banks can extract rents from firms and, firms must pay for their greater access to capital. 

In terms of new investments or debt renegotiations, powerful banks can extract more of the expected future profits 

from the firm than in a market-base system (Hellwig, 1991). This ability to extract part of the expected revenue to 

potentially profitable investments may limit the firm’s effort to undertake innovative and profitable ventures (Rajan, 

1992). Also, with the acquire substantial inside information about firms, the bank can conspire with firm managers 

against outsiders, which in turn hampers competition, corporate controls, the creation of new firms, and long-run 

economic growth (Hellwig, 1998). Market-based financial systems reduce the inherent inefficiencies associated with 

banks and are, thus, better at enhancing economic development and growth. In a related study, Boyd and Smith 

(1998) demonstrated that financial structure changes as countries go through different stages of development, and 

the countries become more market-based as development proceeds. 

The financial services view theory is consistent with both the bank-based and the market-based views (Merton and 

Bodie, 1995 and, Levine, 1997). It embraces both, but downplays their importance in the sense that the distinction 

between bank-based and market-based financial systems matters less than was previously thought.  However, 

according to World Bank (2001), it is the financial services itself that are by far more important than the form of 

their delivery. In financial services view theory, the issue is not the source of finance, but the creation of an 

environment where financial services are soundly and efficiently provided. The focus of this view is on the creation 

of better functioning banks and markets rather than on a particular type of financial structure in place. Also, the 

financial services theory suggests that neither banks nor markets matter, rather the combination of both. Thus, 

financial services view focuses on how to create better functioning banks and markets, and not the bank-based 

versus market-based debate. There are different components of the financial system; but do not compete each other, 

but ameliorate different costs like transaction and information cost in the system (Boyd and Smith, 1998, Levine, 

1997 and, Demirguc-Kunt and Levine, 2001). Under these circumstances, financial arrangements focuses on 

ameliorating market imperfections and provide financial services that are well placed to facilitate savings 

mobilization and risk management, assess potential investment opportunities, exert corporate control, and enhance 

liquidity. 

The legal-based view theory is an extension of the financial services view and also rejects the bank-based versus 

market-based debate. The theory stresses the role of creditor and investor rights for financial intermediation 

(Laporta, Lopez-de-Silanes, Shleifer, and Vishny, 1998). It is the legal system that make and enforces these rights. 

From this perspective, a well functioning legal system facilitates the operation of both markets and intermediaries in 

providing services to the private sector. It is the overall level and quality of financial services – as determined by the 

legal system – that improves the efficient allocation of resources and economic growth. 

Empirical Review 

A number of empirical studies have been conducted on relative importance of bank-based system and market-based 

system in stimulating economic growth. These studies were done on country-specific as well as cross-country 

approach. 

Studies on Germany and Japan use measures of whether banks own shares or whether a company has a ‘main bank’ 

respectively (Hoshi et al., 1991, Mork and Nakamura,1999 and, Weinstein and Yafeh, 1998). These studies provide 

evidence that view Germany and Japan as bank-based systems. This confirms the distinction between bank based 

and market-based financial systems. However, a reassessment of the Japanese financial system benefits in view of 

the economy’s poor performance in the 1990s reveals that the bank-based nature of this system is not beneficial. In 

response, Weinstein and Yafeh (1998) were of the view that bank dependence can lead to a higher cost of funds for 

firms, since banks extract rent from their corporate customers. Similarly, studies on the US and the UK provide 



Copyright © CC-BY-NC 2019, CRIBFB | AFBR 

www.cribfb.com/journal/index.php/aesr                                      American Economic & Social Review                                              Vol. 5, No. 1; 2019 

 

36 
                           

evidence in favour of market-based financial systems (Wenger and Kaserer, 1998 and, Levine, 1997). Hence, the 

U.S. and UK were view as market-based systems. Goldsmith (1969), however, argues that the findings from the 

comparative analysis of bank-based system and market-based system in the case of Germany and the UK for the 

period 1864-1914 does not contribute to the debate since there was no significant difference in the rate of growth of 

the two economies. Levine (2002) reaffirmed Goldsmith’s (1969) argument by concluding that financial structure 

did not matter much since the countries have very similar growth rates. Hence, Levine (2002) examined the relative 

importance of bank-based system and market-based system in stimulating economic growth using a broad cross-

country approach that allows treatment of financial system structure across many countries with different growth 

rates. The findings of this study support financial services view and the legal-based view as against the bank-based 

and the market-based views. It is the elements of a country’s legal environment and the quality of its Financial 

Services (FSs) that are most important in stimulating general economic growth. The bank-based and the market-

based systems are supportive of the financial services and legal views and, that a better-developed financial system 

is what stimulates economic growth. In contrast, Tadesse (2000) examined the relative importance of bank-based 

systems and market-based systems in stimulating economic growth using a cross-country regression for 36 countries 

from 1980–1995 and found a difference between bank-based and market-based financial systems. For 

underdeveloped financial sectors, bank-based systems outperform market-based systems. 

Demirguc-Kunt and Levine (1996), using cross-country data from forty-four industrial and developing countries for 

the period 1986 to 1993 to examined the relative importance of bank-based systems and market-based systems to 

economic growth and thereafter,  concluded that countries with well-developed market-based institutions also have 

well-developed bank-based institutions; and vice versa, thereby supporting the view that the distinction between 

bank-based and market-based financial systems is of no consequence. Contrarily, Levine and Zevos (1998), adopted 

a cross-country regression for a number of countries covering the period 1976 to 1993 and concluded that higher 

stock market liquidity or greater bank development lead to higher growth, irrespective of the development of the 

other. In particular, market-based systems influence growth through the provision of liquidity that enables 

investment to be less risky, such that companies have access to capital through liquid equity issues (Harris, 1997). 

Summarily, the World Bank (2001) reached a conclusion that the evidence should be interpreted as clearly 

suggesting that both the development of bank-based and market-based financial systems promote economic growth 

and, each can complement the other. 

Furthermore, Saibu, Bowale and Akinlo (2009) investigated the relationship between economic growth and financial 

structure, i.e.,the degree to which an emerging economy is market based or bank based. In particular, this study 

empirically assessed the competing theoretical views of financial structure and economic growth dynamics in 

Nigeria using vector error correction model over a 30 year period. The result shows that changes in financial 

structure in Nigeria have no significant influence on real growth rate. The result shows further that despite the 

negative effect of bank-market on economic growth, bank-market has positive effect on stock market development 

hence suggesting that neither the bank-market nor stock market based system is a dominant factor on economic 

growth in Nigeria. Therefore, the controversy between bank based and market based is not a Nigerian phenomenon, 

as both theoretical positions are not supported by evidence. Rather, the results are more consistent with the financial 

services view that both bank and stock market are relevant to the growth of an emerging economy like Nigeria. 

Similarly, Ujunwa, Salami, Nwakoby and Umar (2012) examined the impact of competing financial structure 

theories on economic growth in Nigeria for the period, 1992-2008 using the Ordinary Least Square (OLS) regression 

approach. The results showed that despite the non-significant influence of bank-based theory and legal-based theory, 

both have positive effect in promoting economic growth while the result shows further that market-based theory and 

the financial service theory were non-significant but exhibited negative influence in promoting economic growth. 

These results are consistent with Saibu, Bowale and Akinlo (2009) findings. Also, Olofin and Afangideh (2009) 

investigated the role of financial structure in economic development in Nigeria using aggregate annual data from 

1970 to 2005. It developed a small macro econometric model to capture the interrelationships among aggregate bank 

credit activities, investment behaviour and economic growth given the financial structure of the economy. Three 

stage least square estimation technique was adopted. The result shows that financial structure has no direct effect on 

output growth but through bank credit and investment activities. The finding from the simulation results equally 

confirmed that what matters is overall financial development and not bank-based versus market-based debate. This 

supports financial services theory. The simulation result also confirmed that both capital market-based and bank-

based financial development have similar impact on the real sector of the economy, thereby relegating the capital 



Copyright © CC-BY-NC 2019, CRIBFB | AFBR 

www.cribfb.com/journal/index.php/aesr                                      American Economic & Social Review                                              Vol. 5, No. 1; 2019 

 

37 
                           

market-based versus bank-based debate to the background, and favour the combination of the both. Luintel, Khan, 

Arestis and Theodoridis (2008) examined the relationship between financial structure and economic growth using a 

sample of fourteen countries for the period 1976 to 2005. Fully Modified OLS (FMOLS) of Phillips and Hansen 

(1990) was employed and, thorough scrutiny of the study results was done through bootstrap exercises. Several 

hypotheses about the prospective role of financial structure and financial development on economic growth were 

tested. These exercises were done due to the fact that much of the recent empirical work that analyzed multi-country 

dataset at firm-, industry- and aggregate-levels utilizing the panel and/or pure cross-section frameworks concluded 

that financial structure is irrelevant. Hence, Luintel, Khan, Arestis and Theodoridis (2008) were among scholars that 

have raised doubts about the irrelevant of financial structure in explaining growth in multi-country studies. In 

addressing this concern the study analyzed 14 low-and-middle income countries using both time series and dynamic 

heterogeneous.  Evidence from the study shows that cross-country heterogeneity cannot be addressed and this mark 

important cross-country differences in the relationship under investigations. This shows that data from the sampled 

countries cannot be pooled. This also underpins our focus on a time series analysis. The study also revealed that 

panel and the country-specific parameters (estimates) do not correspond hence limiting the economic value of panel 

estimates. Furthermore, the study revealed that various countries in the panel study are on the balanced growth path 

raising concern on pooled regressions. Overall, the study reveals that the irrelevance of financial structure in panel 

or cross section studies may be because they do not sufficiently account for the cross country heterogeneity. 

Nevertheless, the study shows that output level, capital stock, financial structure and financial development variables 

are co-integrated. Also, the study reveals that, financial structure and financial development significantly explain 

economic growth for the majority of the sampled countries, this holds under time series and panel estimates. 

The literature reviewed suggests that the issue between financial structure and its impact on economic growth is yet 

to be resolved. Specifically, the argument on the relative importance of bank based and market based to economic 

growth is still on. Cross-country and country-specific studies financial structure and its impact on economic growth 

have been carried out but the controversy still persists. However, evidence on Nigerian economy is still scanty 

except on cross-sectional basics where Nigerian data are lumped up with other countries. Therefore, it is imperative 

to examine whether changes in financial structure or the overall financial systems impact on a typical developing 

economy like Nigeria, whose overall financial sector is expanding both in size and complexities. This study intends 

to contribute to the existing literature. This is done by utilizing annual time series data from 1981-2017 to develop a 

model that captures the relationships between financial structure variables and economic growth. 

3. Methodology 

3.1 Data and Sources 

The annual data for this study were basically from secondary sources. Specifically, the data were from Central Bank 

of Nigeria (CBN) statistical bulletin, various issues, Securities and Exchange Commission, Nigeria (2017) and 

World Development Indicators (WDI). The annual data covers the sample period, 1981-2017. The choice of the 

period and frequency of data was because of availability of data. The variables used in the model specification are 

real gross domestic product growth which is used to measure economic growth  as the dependent variable while 

labour employed, represented by percent growth in labour force participation, Kp is the physical capital or 

investment, captured by log gross fixed capital formation as percent of GDP, financial structure, represented by the 

stock market capitalization ratio over credit to private sector ratio, degree of openness, government 

expenditure/GDP and inflation served as the explanatory variables.  

3.2 Model Specification 

3.2.1 Analytical Framework 

The analytical framework of this study is based on the neoclassical model of economic growth which stresses capital 

and labour as the main determinants of output (economic growth). Technological progress is generally acclaimed as 

an additional determinant of output and it comes into the model as a time related trend (t). According to the 

neoclassical model, the relationship between economic growth and these variables is expressed in the form of a 

production function. Therefore, the conventional form of Cobb Douglas production function as in Saibu et al, (2009) 

is adopted as basis.  Thus: 

 

Y = ALα Kβ        (1) 

                                Where α, β>0 
 



Copyright © CC-BY-NC 2019, CRIBFB | AFBR 

www.cribfb.com/journal/index.php/aesr                                      American Economic & Social Review                                              Vol. 5, No. 1; 2019 

 

38 
                           

Where Y represents output produced, L is the utilized labour, K is the utilized capital and α, β and are the parameters 

representing the output elasticity of each input (labour and capital). Theoretically, it is argued that the labour and 

capital are embodiment of several other inputs that are also directly influencing output growth even when the 

traditional inputs are unchanged; hence there is need for simple modification of eqn 1. Thus, one of such possible 

inputs is the financial resources committed into production process. In line with this argument, capital can be 

decomposed into fixed physical (Kp) and, financial (Kf) resources which are generated from the financial sector 

(Saibu et al, 2009). Thus:  

 

Y = ALα Kp
 ϴ Kf

 φ       (2) 

                                Where α, (β= ϴ+φ) ≥ 0 

 

Kf  is the level of financial capital utilized in the production process, and it is an increasing function designed to 

capture the channel through which financial factors raise the rate of return on investment and subsequently output. 

The model in equation (2) is transformed into partial log linear form: 

 

       InY = InA + αL+ ϴInKp + φKf +Ut    (3) 

 
Where U represents other variables that might also be impacting on the growth of output. 

 

Apart from the labour, investment and financial factors, evidences from previous studies revealed that many other 

factors influence economic growth. Saibu et al, (2009) indentified public investment, degree of openness and 

inflation as other factors influencing growth. The model of the study differs from Saibu et al, (2009) with little 

modification in area of the determinant variables. This study incorporated into the model total government 

expenditure and gross fixed capital formation as against public investment on infrastructure and gross private 

investment in Saibu et al, (2009).  

In line with the objectives of the study which is investigating the competing views on the role of the financial 

structures (bank-based view, market-based view, financial service view and the legal system service view) in 

promoting economic growth in Nigeria, equation (3) is modified. Therefore the estimated equation is of the form: 

 

InRGDPi = B0 + B1GLF + B2Inkp + B3Kf  + B4C + Ut     
     (4) 

 

Where RGDPi is the real gross domestic product, GLF is the labour employed, represented by percent growth in 

labour force participation(GLP), Kp is the physical capital (captured by log gross fixed capital formation as percent 

of GDP(DI)), Kf captures respective financial structures or financial development variables (bank sector credit to 

private sector as a percentage of GDP(BCP_R) and stock market capitalization as a percentage of GDP(SMC_R)) 

and, C captures the control variables (degree of openness(OPENN), log government expenditure/GDP(TGEX_R) 

and inflation(INF)). The degree of openness is measured as the ratio of total trade to GDP (Foreign Trade/GDP) and 

is used as the openness of the economy, government expenditure/GDP is government expenditure as a ratio of GDP 

and inflation is the log difference of composite consumer price indices. Also, to investigate the overall role of 

financial structure (combination of the competing views) in promoting economic growth in Nigeria hence, the 

estimated equation is of the form: 

 

      InRGDPi = B0 + B1InGLF + B2InDI + B3FS_R + B4InC + Ut                  (5) 

 

The variables definitions remain the same with eqn 4 except DI and FS_R. DI is the log gross fixed capital 

formation as percent of GDP which captures investment. FS_R captures the overall financial structure. FS_R is 

defined as the stock market capitalization ratio over credit to private sector ratio. That is, FS_R a conglomerate 

index of stock market activity and bank activity. A significant FS_R implies that financial structure matters in 

determining economic growth while an insignificant of FS_R implies that financial structure is inconsequential in 

determining growth. 

3.2.2 Method of Data Analysis 

As this study is based on time series data so the first step is to check whether the series are stationary or not. 

Augmented Dickey-Fuller (1979)(ADF) and Phillips-Peron (1988)(PP) tests are used for testing stationarity. If the 



Copyright © CC-BY-NC 2019, CRIBFB | AFBR 

www.cribfb.com/journal/index.php/aesr                                      American Economic & Social Review                                              Vol. 5, No. 1; 2019 

 

39 
                           

ADF and Phillips–Peron statistics confirm that, there exist or no unit roots in the series, next is to verify whether 

long run relationship exists between financial structure and economic growth.  In doing this, it is the features of the 

series that determine the cointegration test technique to be adopted. If all the variables are stationary at level, the 

simple regression technique is adopted, hence no need to test for long relation of the series or if the stationarity of 

variables are mixed, I(0), I(1), the autoregressive distributed lag bound technique is employed or if all the series are 

integrated at I(1) then Johansen and Juselius co-integration technique (1991) is adopted. Also, the number of the 

cointegrating equations determines the model to adopt. If the number of cointegrating equation is one, the Error 

Correction model (ECM) is employed or if the number of cointegrating equation is more than one, Vector Error 

Correction model (VECM) is employed or if there is no cointegrating equation, the Unrestricted Vector 

Autoregressive model (VAR) is adopted. However, given the feature of the stationarity of the series and the order of 

the VAR using Akaike’s Information Criterion, Johansen and Juselius co-integration technique (1991) is adopted to 

identify the long-run equilibrium relationship, if it exists. The presence of such relationship rules out spurious 

relationship among the underlying variables. Having established more one cointegrating vector, the Vector Error 

Correction Model (VECM) model is applied to check what happens within the short run and long run. Also, to 

establish if there is causality between the different types of financial structure (or overall structure) and economic 

growth, the Vector Error Correction (VEC) Granger causality test is used. The vector error correction (VECM) 

model is expressed as follows: 

 

       ∆Yt = μ +  Γ1∆Yt-1+⋯+ Γp-1∆Yp-1 +  αECMt-1+ ϵt        (6) 

 
 

Where ∆ is a difference operator and Y is a vector of I(1) variables that are involved in this study, ϵt  is a vector of 

white noise errors, ECM is the residuals of the long-run model lagged one period, and α is a vector of adjustment 

coefficients. These latter indicate the adjustment to long-run equilibrium. They should be statistically significant and 

have a negative sign. The Granger causality among these variables is tested through the vector error correction 

model. 

4. Results and Discussions 

4.1Test Results 

4.1.1Unit Roots Test 

The time series properties of the data were evaluated by using Augmented Dickey Fuller (ADF) and Phillips-Perron 

(PP) procedures for the presence of unit roots. The unit roots test results reported in Table 1 show that the variables 

are non-stationary at level but unequivocally stationary at first difference, implying that they are I(1) properties. This 

is deduced from the fact that the absolute values of the ADF/PP test statistics of the variables at levels are less than 

the absolute value of the critical values of the ADF/PP at 1 or 5 percent significance level. However, the reverse is 

the case for the first differences of the variables. 

Table 1: ADF/PP Statistics for Testing Unit Roots in the Variables 

 

Variable 

 

Series 

ADF-Test PP-Test 

At Level 1st Diff At Level 1st Diff 

Economic Growth RGDP  0.0321 -3.3397*  0.8578 -3.1798* 

Labour  GLF -1.8314 -9.4417* -3.0905 -9.4417* 

Investment  DI -2.8903 -5.5399* -2.9000 -5.1218* 

Bank Credit to Private Sector Ratio BCP_R -0.8169 -6.3365* -0.8169 -6.3370* 

Stock Market Cap Ratio SMC_R -1.7674 -5.8978* -1.5751 -9.5326* 

Inflation Rate INF -2.8593 -6.1392* -2.7318 -9.3995* 

Total Government  Expenditure TGEX_R -2.4359 -8.5933* -2.2520 -8.5247* 

Degree of Openness  OPENN -1.7873 -7.4157* -1.6699 -7.5446* 

Financial Structures FS_R -2.6408 -5.8248* -2.6408 -7.1130* 

 
Critical Values 

1% -3.6268 -3.6329 -3.6268 -3.6329 

5% -2.9458 -2.9484 -2.9458 -2.9484 

Source: Calculations by Authors using Eviews 9. *significant at 1% and 5% level 

 



Copyright © CC-BY-NC 2019, CRIBFB | AFBR 

www.cribfb.com/journal/index.php/aesr                                      American Economic & Social Review                                              Vol. 5, No. 1; 2019 

 

40 
                           

4.1.2 Cointegration Test 

Since all the variables are integrated of order one, next is to examine the long run relationship of the variables by 

using Johansen and Juselius co-integration procedure. This test is carried out by defining the vector Zt = [X1t, X2t] as 

the set of all variables in equation (4) wherein all variables could potentially be endogenous.  

Table 2:  Johansen and Juselius Co-integration Tests  

Eigenvalue Trace Statistic Critical Value (5%) No. of CE 

Model 1: LRGDP GLF LDI BCP_R SMC_R  LTGEX_R OPENN INF  

 0.860335  235.9368  159.5297 None * 

 0.783126  167.0389  125.6154 At most 1 * 

 0.660958  113.5436  95.75366 At most 2 * 

 0.543581  75.68660  69.81889 At most 3 * 

 0.511029  48.23455  47.85613 At most 4 * 

 0.378007  23.19372  29.79707 At most 5 

 0.144209  6.574798  15.49471 At most 6 

 0.031612  1.124278  3.841466 At most 7 

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

Trace test indicates 5 cointegrating eqn(s) at the 0.05 level 

Source: Calculations by Authors using Eviews 9.  

Table 3:  Johansen and Juselius Co-integration Tests  

Eigenvalue Trace Statistic Critical Value (5%) No. of CE 

Model 2: LRGDP GLF LDI FS_R LTGEX_R OPENN INF  

 0.749327  146.2738  125.6154 None * 

 0.556757  97.84755  95.75366 At most 1 * 

 0.516777  69.37022  69.81889 At most 2 

 0.476369  43.91552  47.85613 At most 3 

 0.361429  21.27165  29.79707 At most 4 

 0.119897  5.573383  15.49471 At most 5 

 0.031031  1.103296  3.841466 At most 6 

*(**) denotes rejection of the hypothesis at 5%(1%) significance level. Trace test indicates 2 cointegrating eqn(s) at 

the 0.05 level 

Source: calculations by Authors using Eviews 9. 

Tables 2 and 3 reveal that there exists co-integration among the variables. That is, there exist a long run relationship 

among the variables in Tables 2 and 3.  Given the existence of more than one cointegrating vectors in both models, it 

is pertinent to adopts Vector Error Correction model (VECM) for the analysis of the relationship between financial 

structure and economic growth. 

4.2.The Pairwise Correlation Result 

As lead up to the multivariate analysis of the model, the correlation among the underlying variables is examined. 

Table 4 shows that economic growth is only positively correlated with FS_R, BCP_R and SMC_R measures. This is 

in line with the theoretical underpinnings which suggest that finance promotes economic growth. FS_R, BCP_R and 

SMC_R have correlation coefficient of 46 %, 87 % and 83 % respectively with economic growth. 

Table 4: Correlation Coefficients 

 LRGDP GLF LDI FS_R BCP_R SMC_R LTGEX_R OPENN INF 

LRGDP  -  0.260 -0.103  0.459  0.874  0.832 -0.440 -0.379 -0.337 

GLF  0.260  -  0.613 -0.076  0.429  0.241 -0.559 -0.673 -0.208 

LDI -0.103  0.613  - -0.400  0.195 -0.119 -0.377 -0.633 -0.074 

FS_R  0.459 -0.076 -0.400  -  0.117  0.787 -0.188  0.244 -0.270 

BCP_R  0.874  0.429  0.195  0.117  -  0.682 -0.495 -0.683 -0.281 

SMC_R  0.832  0.241 -0.119  0.787  0.682  - -0.435 -0.292 -0.370 

LTGEX_R -0.440 -0.559 -0.377 -0.188 -0.495 -0.435  -  0.579  0.235 

OPENESS -0.379 -0.673 -0.633  0.244 -0.683 -0.292  0.579  -  0.273 

INF -0.337 -0.208 -0.074 -0.270 -0.281 -0.370  0.235  0.273  - 

Source: Calculations by Authors using Eviews 9.  



Copyright © CC-BY-NC 2019, CRIBFB | AFBR 

www.cribfb.com/journal/index.php/aesr                                      American Economic & Social Review                                              Vol. 5, No. 1; 2019 

 

41 
                           

4.3Vector Error Correction Model (VECM)  

To analysis the long and short run relationship between the variables in the models and economic growth, the study 

employed VECM. The VECM results are as follows: 

4.3.1 Economic Growth Effects of Financial Development 

This sub-section investigates the relative contribution of both bank and stock market system with control variables 

in explaining growth. Table 5 shows the result. 

 

Table 5: Long Run Model of Economic Growth Determinants 

Variable  Coefficient Standard Error t-Statistics 

C -15.38154   

GLF 0.022182 0.39784 0.05576 

LDI 1.855416 0.15656 11.8515* 

BCP_R -0.217988 0.01066 -20.4443* 

SMC_R 10.91057 0.90122 12.1065* 

LTGEX_R 0.816945 0.11539 7.08004* 

OPENNESS 0.745104 0.33840 2.20186** 

Note. *(**) indicate significance at  1% (5%) 

Source: calculations by Authors using Eviews 9.  

The essence of this sub-section is to examine the significance of bank and stock market activity on economic growth 

and, whether both are substitute or complement in the long run. Table 4 shows that bank activity has a negative 

effect on economic growth while the stock market activity has a positive effect on economic growth. The 

implications of the signs of the financial development variables are x-rayed below.   

From Table 5, the bank activity has a negative effect on economic growth in the long run. This result is inconsistent 
with the bank-based financial structure theory which posits that the unique role of banks in identifying good 

projects, mobilizing resources, monitoring managers and managing risks promotes economic growth. The result is 

consistent with Ayadi et al. (2013) who also found a negative relationship between bank sector and growth and, 

attributed it to deficiencies in credit allocation in the economy. The negative relationship does not mean that the 

banking sector is underdeveloped rather it could be explained by credit allocation problem in Nigeria. Most 

borrowings in Nigeria are not channelled to productive ventures but rather for consumption spending which does not 

promote economic growth in the long run. Also, most banks are engaging less in financial intermediation activities. 

For instances, some have become selling agencies, revenue collectors and they are now facilitators of black market 

forex dealing. Hence, bank engages more in non-financial intermediation and unproductive activities than their 

traditional banking function of intermediating fund from the surplus sector to deficit sector. Therefore, the bank 

activities in relation to economic performance have negative effect. 
Table 5 reveals that the stock market activity has a positive effect on economic growth in the long run. This is 

consistent with market based theory which opines that big, liquid and well-developed markets foster growth and 

profit incentives; enhance corporate governance and, facilitate risk management (Levine, 2002, and, Beck and 

Levine, 2002). The inefficiencies that are inherent in bank- based system as stressed by (Levine, 2002) are being 

reduced by Market-based financial systems. It is argued that there is an inverse relationship between stock (bond) 

price and the interest rate. If the bank interest rate is high, then investor who requires funds will prefer going to the 

stock market to raise fund since the cost of raising fund in the bank is very high. Hence, a market-based financial 

system is better at enhancing economic growth. 

On whether both are substitute or complement, the result from Table 5 reveals that the signs on both the bank and 

stock market variables are different; the bank activity sign is negative while stock market sign is positive which 

implies that both are substitute. Hence, this supports the hypothesis that bank and stock market are substitute. This 

result collaborates with Saibu et al, (2009) and, inconsistent with The World Bank (2001). The reasons for this result 
could be based on theoretical argument and problems in credit allocation. However, it is proper to focus on the 

significance or otherwise of the coefficients of financial development variables, rather than their signs (Arestis et al, 

2004 and, Olofin and Afangideh, 2009). Given the bank and market system variables, it shows that the both are 

significantly influencing economic growth in Nigeria. The significant of the coefficients of both bank and stock 

market imply that both systems matter while the reverse is the case. However, to confirm whether both bank and 

stock market system matter or not in explaining economic growth in Nigeria, the relationship between financial 

structure (overall financial system which combined both systems) and economic growth was examined (see section 

4.5 ).  

 



Copyright © CC-BY-NC 2019, CRIBFB | AFBR 

www.cribfb.com/journal/index.php/aesr                                      American Economic & Social Review                                              Vol. 5, No. 1; 2019 

 

42 
                           

Table 6: Multivariate VECM Causality Test (Short Term) 

Dependent   

Variable 

Independent   variable ECT(-1) 

D(LRGDP) D(BCP_R) D(SMC_R) 

D(LRGDP) - 0.3306 0.2095 -0.042689*** 

D(BCP_R)  0.0205** - 0.0008*  4.142087* 

D(SMC_R)  0.8917 0.2370 - 0.031604 

   *Significant at 1%, **significant at 5% and ***significant at 5% 

Source: calculations by Authors using Eviews 9.  

After exploring the long run association between economic growth and measures of financial development, we now 

proceed to multivariate Granger causality test based on VECM. At this juncture, it is important to note that the 

documented cointegration among the variables suggests only their long run association and, while it implies 

causality but does not reveal the directions of causation among them. Table 6 reports the multivariate causalities 

among the economic growth and financial variables. It examines the short run line of causation between economic 

growth and financial structure and, other variables. Also, Multivariate VECM causality helps to determine how the 

underlying variables enter the model. Relatively, the Multivariate VECM causality is preferred to VECM system 

equation in differences since the interpretation of VECM system equation is difficult. 

Table 6 shows that there is no any causation in short term running from financial development variables (BPC_R 

and SMC_R) to economic growth (LRGDP) in the Nigeria economy while there is long run causality between 

financial development variables and economic growth. Also, the result reveals that there is a short-run interaction 
between LRGDP and BPC_R, which runs from economic growth (LRGDP) to financial development (BPC_R).  

This finding supports the view, the growth-led finance hypothesis. Based on this view, the financial development in 

Nigeria follows economic growth. 

The adjustment coefficients (ECT(-1)) in Table 6 show the speed of adjustment towards equilibrium path. As shown 

in the Table, the coefficient of adjustment in LRGDP equation is rightly signed and statistically significant at 10 

percent significance level. This shows that the underlying variables are cointegrated and a long run equilibrium 

relationship exists between the variables. The result also reveals that the LRGDP adjust by 4 percent every year 

whenever the variables drift away from the long run equilibrium, which is quite slow. On the other hand, the 

coefficients adjustment in equation BPC_R is wrongly signed and significant while that of SMC_R is wrongly 

signed and not significant. 

4.4 Model Appraisal 
Model Appraisal is aimed at validating the parameter outcomes achieved by the estimated model. The Appraisal is 

important because if the residuals from the estimated model are problematic, it then means that the model is not 

efficient and the parameter estimates may be biased. Some of the tests carried out on the model are; AR roots, serial 

correlation, normality and hetroscedasticity. The results are presented below. 

 

AR Roots Test 
 

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

-1.5 -1.0 -0.5 0.0 0.5 1.0 1.5

Inverse Roots of AR Characteristic Polynomial

Figure 1:  AR Roots Graph  
Source: Calculations by Authors using Eviews 9.  



Copyright © CC-BY-NC 2019, CRIBFB | AFBR 

www.cribfb.com/journal/index.php/aesr                                      American Economic & Social Review                                              Vol. 5, No. 1; 2019 

 

43 
                           

 

The AR roots test result in Figure 1 indicates that the estimated model is stationary since there are no roots lying 

outside the unit cycle, meaning that the model is stable. 

 

Table 7: VEC Residual Serial Correlation LM Tests  

Lags LM-Stat Prob 

1  36.77971  0.9008 

2  47.05216  0.5524 

* Probs from chi-square with 49 df. ** Null Hypothesis: no serial correlation at lag order h 

Source: calculations by Authors using Eviews 9.  

 

The serial correlation LM test result of zero probability value indicates the presence of serial correlation while high 

probability of the LM statistic indicates no serial correlation. In Table 7  the probability of 0.5524 at lag 2 is high; 

therefore, the null hypothesis is rejected and concludes that there is no serial correlation among the underlying 

variables. 

 
Table 8: Residual Normality Test 

 Chi-sq  P value  

Skewness   0.365750   0.5453 

Kurtosis   0.031476  0.8592 

Jarque-Bera   0.397226 0.8199 

*Null Hypothesis: residuals are multivariate normal 

Source: calculations by Authors using Eviews 9.  

Table 8 reveals a clear indication of normal distribution. This is because all the probabilities are above 5% and 10%, 

hence the null hypothesis of normality is rejected. 

 

Table 9: Hetroscedasticity Test (White test with no cross terms) 

Joint Test: 

Chi-sq Df Prob. 

 866.9252 840  0.2526 

*The null hypothesis: there is no heteroskedesticity 

Source: calculations by Authors using Eviews 9.  

Table 9 shows that the null hypothesis cannot be rejected since the probability (0.2526) is greater than 5% and 10%. 

This, therefore, means that there is no model misspecifications and hence can be relied on. 

 

4.5 Economic Growth Effects of Financial Structure 
This sub-section examines the effect of financial structure (the overall financial system) on growth. Table 10 shows 

the result. 

 

Table 10: Long Run Model Effect of Financial Structure on Economic Growth 

Variable  Coefficient Standard Error t-Statistics 

C -2.162760   

GLF -15.28466 4.31484 -3.54235** 

LDI  10.65363 1.28779  8.27280* 

FS_R  222.2282  57.9683  3.83362** 

LTGEX_R  0.122002  1.41658  0.08612 

OPENN 10.81927 2.88405  3.75142** 

INF -0.036314  0.01505 -2.41233** 

Note. *(**) indicate significance at 1% (5%) 

Source: calculations by Authors using Eviews 9.  

 



Copyright © CC-BY-NC 2019, CRIBFB | AFBR 

www.cribfb.com/journal/index.php/aesr                                      American Economic & Social Review                                              Vol. 5, No. 1; 2019 

 

44 
                           

From Table 10, Financial structure (FS_R) is positively and significantly related to economic growth in Nigeria in 

the long run. Theoretically, the result is consistent with the market-based view. Higher coefficient (222.2) of FS_R 

means a system that is capital market-based dominant while a lower FS_R coefficient means more of a bank-based 

system (Olofin and Afangideh, 2009). The stock market based view posits a significant positive relationship 

between financial structure (FS_R) and economic growth while the bank-based view predicts a negative 

significance relationship between financial structure (FS_R) and economic growth. It is important to note that stock 
market liquidity, as measured by the market capitalization and banking sector activity, as measured by bank credit to 

private sector are more robust in predicting economic growth. This is inconsistent with the Levine and Zervos 

(1998) and Saibu et al, (2009) results that market capitalization is not a robust predictor of economic growth. 

Consequently, the debate between bank based and market based is not a Nigerian phenomenon. 

However, for the purposes of this study, it is important to focus on the significance or otherwise of the coefficient of 

FS_R, rather than its sign (Arestis et al, 2004 and Olofin and Afangideh, 2009). A significant coefficient of FS_R 

implies that financial structure matters while the reverse is the case. The result posits that the overall financial 

structure (FS_R) is the most useful way to distinguish financial systems (Levine, 2002) since both bank and stock 

market system matter in explaining economic growth as against bank-based versus market-based debate. This is 

consistent with financial services theory as well as Olofin and Afangideh (2009) but inconsistent with Saibu et al, 

(2009). 

 
Table 11: Multivariate VECM Causality Test (Short Term) 

Dependent   

Variable 

Independent   Variable  

ECT(-1) D(LRGD

P) 

D(GLF) D(LDI) D(FS_R

) 

D(LTGEX_

R) 

D(OPENN) D(INF) 

D(LRGDP)   0.36350

4 

 0.4650

08 

 1.2251

23 

 0.054826  0.042555  1.48960

4 

-

0.007709*

* 

D(GLF)  1.31572

6 

  0.1078

69 

0.63850

2 

 0.001995 0.028172 0.070575  0.003715 

D(LDI)  3.20862

4** 

 0.4935

29 

 2.09791

6 

0.048394 1.121156  0.71310

6 

-

0.033223*

** 

D(FS_R)  2.42873

8 

 0.6860

79 

2.52315

4 

  3.421969** 1.738158  1.07702

4 

-

0.001157*
* 

D(LTGEX_

R) 

 0.12928

6 

 0.2004

66 

 0.3417

08 

0.03394

8 

 0.033132  0.00229

4 

-0.008095 

D(OPENN)  3.18415

2** 

 2.5516

27 

 0.8235

14 

 0.3269

07 

 4.764959**   2.74369

5** 

-

0.030222*

* 

D(INF)  0.11706

2 

 0.4068

42 

0.44641

2 

 0.6803

21 

0.702241  0.233062   2.156642 

   *Significant at 1%, **significant at 5% and ***significant at 5% 

Source: calculations by Authors using Eviews 9.  

As shown in Table 11, the coefficient on FS_R was not significant on economic growth model in the short run in 

Nigeria. This reveals that the financial structure is not important in the short run. The results of Table 9 and the short 

run are different. The short run result shows that the insignificant of FS_R is inconsistent with that of the long run. 

This could be attributed to gestation gap between finance mobilization, project implementation and the impact of the 

project.  Results of the error correction representation (ECT(-1)), articulate the dynamic behaviour of the VECM 

model, where the coefficient of the error correction term in growth model is negative and highly significant at 5 % 

which confirms the existence of the long-run relationship between the underlying variables and represent the speed 

of adjustment with which the model attains the long-run steady state equilibrium following an exogenous shock in 
the short-run. In the growth model the ECT(-1) coefficient is about 0.008 percent which is quite slow. This means 

that the deviation from long-run equilibrium will be corrected by a speed between 0.008 percent every year. Next is 

model appraisal which aimed at validating the parameter outcomes of the estimated model. 

 



Copyright © CC-BY-NC 2019, CRIBFB | AFBR 

www.cribfb.com/journal/index.php/aesr                                      American Economic & Social Review                                              Vol. 5, No. 1; 2019 

 

45 
                           

4.5.1 Model Appraisal  

The AR roots test result in the appendices indicates that the estimated model is stationary since there are no roots 

lying outside the unit cycle, meaning that the model is stable. The serial correlation LM test result shows a 

probability of 0.9113 at lag 1 which is high; therefore, the null hypothesis is rejected and the study concludes that 

there is no serial correlation among the underlying variables. Also, the normality test result shows an indication of 

normal distribution. This is because all the probabilities of Skewness, Kurtosis and Jarque-Bera  at lag 1 are above 
5% and 10%, hence the null hypothesis of normality is rejected. Furthermore, the hetroscedasticity test reveals that 

the null hypothesis cannot be rejected since the probability (0.3685) is greater than 5% and 10%. This, therefore, 

means that there is no model misspecifications problem. 

5. Conclusion and Policy Recommendations 

This study examined the relationship between financial structure and economic growth in Nigeria. As lead up to 

financial structure and economic growth relationship analysis, the competing theoretical views of bank and market 

based financial system, and economic growth is explored. The results of the study show that stock market-based has 

a positive significant effect on growth while bank-based has a negative significant effect on growth. This implies 

that both bank-based and market-based are substitute, therefore, market-based financial system is better at enhancing 

economic growth. However, the study focuses on the significance of coefficients of financial development variables 

(bank-based and market-based), rather than their signs. Given the bank and market system variables, it shows that 

the both are significantly influencing economic growth in Nigeria. The significant of the coefficients of both bank 
and stock market variables imply that both systems matter in explaining economic growth in Nigeria, thereby 

favouring their combination. The result of the study also reveals that financial structure which captures the 

combination of stock market-based and bank-based financial development has a positive significant effect on 

growth. The coefficient of financial structure has a positive sign, significant and very high. This is consistent with 

the stock market view. Higher coefficient of financial structure means a system that is capital market-based 

dominant while a lower financial structure coefficient means more of a bank-based system. The stock market based 

view posits a significant positive relationship between financial structure and economic growth while the bank-

based view predicts a negative significance relationship between financial structure and economic growth. However, 

for the purposes of this study not to be defeated, the study focuses on the significance or otherwise of the coefficient 

of financial structure, rather than its sign and magnitude. A significant coefficient of financial structure implies that 

financial structure matters in explaining growth. Therefore, the study posits that the overall financial structure  is the 
most useful way to assess the financial systems since both bank and stock market system matter in explaining 

economic growth as against bank-based versus market-based debate. The result is consistent with the financial 

services view that both bank and stock market are relevant to the economic growth in Nigeria. Based on the 

empirical evidence, the study therefore recommends that there should be continuous holistic reforms of both 

banking and stock market simultaneously, as the development in one sector has a neglect effect on the other. None 

of the sectors should be excluded for reforms aimed at overall development of the financial system and the economy 

as a whole. 

References 

Allen, F. and Gale, D. (1999). Comparing Financial Systems. Cambridge, Mass.: MIT Press. 

Arestis, P., Demetriades, P.  and Luintel, K. (2001). Financial Development and Economic Growth: The Role of 

Stock Markets. Journal of Money, Credit, and Banking, 33(1):16-41. 

Arestis, P., Luintel, A. D.  and Luintel, K.B. (2004). Does Financial Structure Matter?The Levy Economics Institute 
of Bard College, Annandale-on-Hudson, NY. 

Ayadi, R., Arbak, E., Ben-Naceur, S. and De-Groen, W. P. (2013). Financial Development, Bank Efficiency and 

Economic Growth across the Mediterranean. Medpro Technical Report No. 30. 

Beck, T. and Levine, R. (2002).Stock Markets, Banks and Growth: Panel Evidence.NBER Working Paper Series No. 

9082. Cambridge, Mass.: National Bureau of EconomicResearch. 

Bhide, A. (1993). The Hidden Costs of Stock Market Liquidity. Journal of FinancialEconomics, 34(1): 1-51. 

Boot, A.W.A., Greenbaum, S.Y. and Thakor, A.V. (1993) Reputation and Discretion in Financial Contracting, 

American Economic Review, Vol. 83, pp.1165–1183. 

Boyd, J. H. and Prescott, E. C. (1986). Financial Intermediary-Coalitions. Journal ofEconomic Theory,  38(2): 211-

232. 

Boyd, J. H. and Smith, B. D. (1998). The Evolution of Debt and Equity Markets in Economic Development. 
Economic Theory, 12: 519-560. 

Caporale, G.C., Howell, G.A. and Soliman, A.M. (2002). Stock Market Development and Economic Growth: The 

Causal Linkage: Discussion Paper, Centre of Monetary and Financial Economics, South Bank University 

London. 



Copyright © CC-BY-NC 2019, CRIBFB | AFBR 

www.cribfb.com/journal/index.php/aesr                                      American Economic & Social Review                                              Vol. 5, No. 1; 2019 

 

46 
                           

Cental Bank of Nigeria Statistical Bulletin, Various Issues. 

Demirguc-Kunt, A. and Levine, R. (1996). Stock Markets, Corporate Finance and Economic Growth: An Overview, 

World Bank Economic Review, Vol. 10, No. 2, Pp.223–239. 

Demirguc-Kunt, A. and Levine, R. (2001). Financial Structures and Economic Growth: A Cross-Country 

Comparison of Banks, Markets and Development, Cambridge, Mass.:MIT Press. 

Dickey, D. A. and Fuller, W. A  (1979). Distributions of the Estimators for Autoregressive Time Series With a Unit 
Root. Journal of American Statistical Association, 74, 427–431. 

Gerschenkron, A. (1962). Economic Backwardness in Historical Perspective, A Book of Essays. Cambridge, Mass: 

Harvard University press, Cambridge, MA. 

Goldsmith, R. (1969). Financial Structure and Development, New Haven, Yale University Press, CY. 

Harris, R. D. F. (1997). Stock Markets and Development: A Reassessment. European Economic Review, 41: 139-

146. 

Hellwig, M. (1991). Banking, Financial Intermediation and Corporate Finance. European Financial Integration, 35, 

63 

Hellwig, M. (1998). On The Economics and Politics of Corporate Finance and Corporate Control,  

Sonderforschungsbereich 504 Publications, University of Mannheim. 

Hoshi, T., Kashyap, A.and Scharfstein, D. (1991). Corporate Structure, Liquidity and 

Investment: Evidence from Japanese Industrial Groups. Quarterly Journal of Business and Economics, 
106: 678-709. 

Johansen, S. and Juselius, K.(1991). Testing Structural Hypothesis in a Multivariate Cointegration Analysis. Journal 

of Econometrics, Vol. 53, p.21 

La Porta, R, Lopez-de-Silanes, F., Shleifer, A. and  Vishny, R.W. (1997). Legal Determinants of External Finance. 

Journal of Finance, 52: 1131-1150.  

La Porta, R., Lopez-de-Silanes, F., Shleifer, A. and Vishny, R. W. (1998). Law and 

Finance. Journal of Political Economy,  106(6): 1113-1155 

Levine, R. (1997). Financial Development and Economic Growth: Views and Agenda. Journal of Economic 

Literature, Vol. 35, No. 2, pp.688–726. 

Levine, R. (2001). International Financial Liberalization and Economic Growth. Review of International Economics, 

9, 688-702 
Levine, R. (2002) Bank Based or Market Based Financial System Which is Better?, Working Paper Carlson School 

University of Minnesota. 

Levine, R. (2003). More on Finance and Growth: More Finance More Growth? Federal Reserve Bank of St. Louis 

Review, 85 (4): 31-46. 

Levine, R. and Zervos, S. (1998). Stock Markets, Banks and Economic Growth. American Economic Review, 88 (3): 

537-558. 

Luintel, K. B. and Khan, M. (2002). Are International R&D Spillovers Costly for the U.S.? Discussion Paper, 

Department of Economics and Finance: Brunel University. 

Luintel, K. B., Khan, M., Arestis, P. and Theodoridis, K.(2008). Financial Structure and Economic Growth. Cardiff 

Economics Working Papers/ Cardiff Business School Working Paper Series, E2008/3. 

Merton, R. C. (1995). A Functional Perspective of Financial Intermediation. Financial Management, 24: 23-41.  

Merton, R. C. and Bodi, Z. (1995). A Conceptual Framework for Analysing the Financial Environment. In D.B. 
Crane et al (eds.), The Global Financial System: A Functional Perspective. Boston, Mass.: Harvard 

Business School. 

Mork, R. and Nakkamura, M. (1999). Banks and Corporate Control in Japan. Journal of Finance, 54: 319-340. 

Olofin, S.O and Afangideh, U.J. (2009). Financial Structure and Economic Growth in Nigeria: A Macroeconometric 

Approach‖, Centre for Econometric and Allied Research(CEAR) 

Phillips, P., & P. Perron, P. (1988). Testing For A Unit Root In Time Series Regression. Biometrica, 75, 333–346. 

Rajan, R. (1992). Insiders and Outsiders: The Choice Between Informed and Armies Length Debt. Journal of 

Finance, Vol. 47, No. 4, pp.1367–1400. 

Saibu, O M, Bowale, K. I E. and Akinlo, A. E. (2009).Financial Structure and Economic Growth: Empirical 

Evidence from Nigeria. International Journal of Business and Emerging Markets, Vol. · January, 

Inderscience Enterprises Ltd. 
Security and Exchange Commission Statistical Bulletin (2017), Vol. 1.2, June. 

Stiglitz, J. E. (1985). Credit Markets and the Control of Capital. Journal of Money, Credit and Banking, 17 (1): 133-

152. 



Copyright © CC-BY-NC 2019, CRIBFB | AFBR 

www.cribfb.com/journal/index.php/aesr                                      American Economic & Social Review                                              Vol. 5, No. 1; 2019 

 

47 
                           

Stulz, R. M. (2000). Financial Structure, Corporate Finance and Economic Growth.International Review of Finance, 

1, 11-38. 

Stulz, R. M. (2001). Does Financial Structure Matter for Economic Growth? A Corporate Finance Perspective. In 

Financial Structure and Economic Growth: A Cross-Country Comparison of Banks, Markets, and 

Development, eds. A Demirguc-Kunt, R Levine. Cambridge, MA:MIT Press. 

Tadesse, S. (2000). Financial Architecture and Economic Performance: International Evidence,Working Paper, 
University of South Carolina. 

Ujunwa, A.,  Salami, O.P., Nwakoby, I. and Umar, A. H.  (2012). Financial Structure and Economic Growth in 

Nigeria: Theory and Evidence. International Journal of Economics and Finance, Vol. 4, No. 4; April. 

Published by Canadian Center of Science and Education 

Weinstein, D. E. and Yafeh, Y. (1998). On the Costs of a Bank-Centered Financial System: Evidence from the 

Changing Bank Relations in Japan. Journal of Finance,53: 635-672. 

Wenger, E. and Kaserer, C. (1998). The German System of Corporate Governance: A Model Which Should not be 

Imitated.” In S.W. Black and M. Moersch (eds.), Competition and Convergence in Financial Markets: The 

German and Anglo-American Models. New York: North Holland. 

World Bank (2001). Finance for Growth: Policy Choices in a Volatile World. A World Bank Policy Research 

Report. Washington D.C.: World Bank. 

World Development Indicators (WDI). 
 

Appendices 

 

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

-1.5 -1.0 -0.5 0.0 0.5 1.0 1.5

Inverse Roots of AR Characteristic Polynomial

AR ROOTS GRAPH OF FINANCIAL STRUCTURE AND GROWTH 
Source: calculations by Authors using Eviews 9.  

VEC Residual Serial Correlation LM Tests of FS_R and Growth 

Lags LM-Stat Prob 

1  36.26966  0.9113 

2  51.68200  0.3695 

* Probs from chi-square with 49 df. ** Null Hypothesis: no serial correlation at lag order h 

Source: calculations by Authors using Eviews 9.  

Residual Normality Test of FS_R and Growth 

 Chi-sq  P value  



Copyright © CC-BY-NC 2019, CRIBFB | AFBR 

www.cribfb.com/journal/index.php/aesr                                      American Economic & Social Review                                              Vol. 5, No. 1; 2019 

 

48 
                           

Skewness   0.059595    0.8071 

Kurtosis   0.338092   0.5609 

Jarque-Bera    0.397687 0.8197 

*Null Hypothesis: residuals are multivariate normal 

Source: calculations by Authors using Eviews 9.  

Hetroscedasticity Test (White test with no cross terms) of FS_R and Growth 

Joint Test: 

Chi-sq Df Prob. 

 457.4501 448  0.3685 

*The null hypothesis: there is no heteroskedesticity 

Source: calculations by Authors using Eviews 9.  

 

 

 

 

 

Copyrights  

Copyright for this article is retained by the author(s), with first publication rights granted to the journal. This is an 

open-access article distributed under the terms and conditions of the Creative Commons Attribution license 

(http://creativecommons.org/licenses/by/4.0/). 

 

 

 

 


