FINANCIAL DEVELOPMENT AND ECONOMIC GROWTH IN NIGERIA Fidelis O. Ogwumike and Afees A. Salisu

Abstract This paper examines the short run, long run and the causal relationship between financial development and economic growth in Nigeria from 1975 to 2008. Using the Bound test approach, this study finds a positive long run relationship between financial development and economic growth in Nigeria. Financial intermediation- credit to private sector, stock market and financial reforms exert significant positive impact on economic growth. Further, analysis of the short run dynamics reveals that about 40% of the resulting disequilibrium is captured each period indicating minimal deviations from the equilibrium. In addition, the result of the VAR-Granger causality test lends support to the supply-leading hypothesis. Therefore, appropriate regulatory and macroeconomic policies that will foster the expansion and development of the Nigerian financial institutions should be pursued by the relevant authority. JEL Classification Codes: C21, C61, I32 Keywords: Financial reform, economic growth, bound-test, causality,

INTRODUCTION The pursuit of economic growth and sustainable development is one of the core macroeconomic goals in every nation. Economic growth is usually anchored on the financial development of a country. This is underscored by the fact that an effective financial system, in addition to the economic transformation role, provides the possibility of better savings mobilisation and allocation of same for development purpose (Levine, 1997). This can be achieved through increasing the level of investment in general as well as in human resources in particular to induce and sustain economic growth and development. The goal of financial development is to achieve efficiency in the financial sector and engender financial deepening and economic growth. Thus, in the present paper, we attempt to quantify the extent to which financial development in Nigeria has enhanced economic growth.



Ogwumike and Salisu are both lecturers in the Department of Economics University of Ibadan. Corresponding Author’s Email: [email protected]

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The question of the relationship between financial development and economic growth has been widely addressed by economic literature. Notably,taking into consideration the role of economic growth in fostering financial development and the role of financial development in enhancing economic growth. In addition to the demand-following and the supply-leading hypotheses, there is a third strand of arguments in the literature which submits that there is a feedback relationship between financial development and economic growth.2 In this paper, we also evaluate these hypotheses using appropriate methodology in order to ascertain the one that reasonably captures the financial development-growth nexus in Nigeria. The extensive financial reforms initiated in Nigeria in 1987 as part of the Structural Adjustment Porgramme (SAP) include the deregulation of foreign exchange market, interest rates, rationalisation of credit controls, licensing of new banks and, institutional and regulatory changes (Ikhide and Alawode, 2002). Further, since the return to democracy in 1999, more far-reaching financial reforms have been initiated including the pension fund, 2004; bank consolidation policy, 2005; insurance, 2007; and capital market reform. These financial reforms were expected to foster an efficient financial system that would encourage domestic savings and investment and hence engender economic growth and development. The concern in Nigeria is that financial institutions (mostly banks) have not performed to expectations in terms of mobilising savings for financing long-term development projects in the real sector (Adeoye and Adewuyi, 2005). Further, there is no apparent and appreciable contribution of financial deepening to economic growth in the postSAP era (Ayadi, Adegbite and Ayadi, 2008 and Ayadi, 2009). However, as noted by Nzotta and Okereke (2009), some studies on financial development and economic growth in Nigeria relied on money market indicators (see Ogun, 1986; Oyejide, 1986; Edo, 1995; Ndebbio, 2004; and Akinlo and Akinlo, 2007) and they established a positive and significant relationship between financial development and economic growth. Further, some of these studies have employed either theories and methodologies that omit some of the direct (credit supply and real interest rate) and indirect (stock market) channel(s), or models that ignore the short run effects. Against this background, this study seeks to answer the following questions:  To what extent has financial development enhanced economic growth in Nigeria?  What is the direction of causality between financial development and economic growth in Nigeria? 2

Each relationship will be discussed in the literature review section with empirical evidence provided.

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The primary objectives of this study are to re-examine the finance developmenteconomic growth puzzle by including non-money market indicators; and consequently, the causality framework is extended to account for these indicators in testing for the probable existence of demand-following or supply-leading hypothesis or the feedback in Nigeria. Essentially, the Bounds test approach (developed by Persaran et al, 2001 and suitable for small sample size study) is employed to answer the first research question. The multivariate causality however often referred to as VAR-Granger causality test is used to attend to the second. The latter method helps to circumvent probable biased and inconsistent inferences arising from restricting endogenous variables in the pairwise causality test. The rest of the paper is organised as follows: The next section discusses financial systems and economic performance in Nigeria. This is followed by a review of the theoretical and empirical evidences. The next section discusses the methodology. Results and interpretations are presented just before the conclusion. THE FINANCIAL SYSTEM AND ECONOMIC PERFORMANCE IN NIGERIA The Nigeria financial system has experienced intensive restructuring and rapid marketoriented transformations since the adoption of the SAP in 1986. Prior to this time, the financial system was regulated as evidenced by ceiling on interest rates and credit expansion, high reserve requirements, selective credit policies and restriction of entry into the banking industry. Following deregulation, the bank and non-bank financial institutions witnessed unprecedented increase due to the incentives provided for growth and expansion of financial institutions. For example, the number of banks rose from 41 in 1986 to 115 in 1997. Further, the number of bank branches rose from 1,323 in 1986 to 2,551 in 1997. Similarly, the number of community banks (microfinance banks) increased from 169 in 1990 to 695 in 2009; and the number of specialised non-bank financial institutions3 increased from 84 in 1990 to 242 in 2008. This deregulation spurred competition in the industry, forcing many banks to adopt various strategies required to consolidate their existence. Inefficiency in banking operations, poor management and misallocation of resources as well as political

3

These include 80 insurance companies, National Economic and Reconstruction Fund (NERFUND), Nigeria Social Insurance Trust Fund (NSITF), National Deposit Insurance company (NDIC), and Nigerian Stock Exchange (NSE) in 1990. The 242 non-bank financial institutions in 2008 include 75 Finance Houses, 75 insurance companies, 5 discount houses, 81 primary mortgage institutions, NERFUND, NSITF, NDIC, NSE, NAICON, and PENCOM (see CBN Statistical Bulletin, 2008).

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interference resulted in bank distress which further weakened the capacity of the financial system in resource mobilisation. Hence, by 1991, government came up with the policy of guided deregulation which resulted in pegging of lending and deposit rates, placement of embargo on further licensing of banks, among other measures. Following the adoption of universal banking in Nigeria in 2000, commercial and merchant banks were merged and they became Deposit Money Banks (DMBs) 4.The Debt Management Office (DMO) established in 2000 also spurred investment in Federal Government bonds. In 2005, banks consolidation policy was put in place, which increased the minimum paid-up capital for commercial banks to N25b; and the total number of banks fell from 85 to 25. The effect of the consolidation was to foster the creation of larger banks having better access to fund market. Deregulation of banking operations allowed entry and competition in the financial system. For example, the share of commercial banks in savings mobilized fell gradually from 99% in 1960 to 84% in 1985 and further to 70% in 1994. This trend indicates a more diversified financial system in which other institutions such as microfinance or community banks and merchant banks played major roles in deposit mobilisation and investment financing. The average growth of saving between 1985 and 2000 was 26% while the average before deregulation era (1975-1985) was 20%.This clearly indicates a greater mobilisation during deregulation. Another important direction of change in the financial environment is the development of new financial instruments and increases in the number of equity traded in the capital market. Banks and other financial market participants were able to raise funds from a wide array of financial instruments. Although capital market reforms started as far back as 1988 with the creation of second tier securities market, it was not until 1993 that further deregulatory measures were taken by replacing pricing and other direct controls with indirect controls. However, the 1999 reforms brought changes in the Securities and Exchange Commission and enhanced listing disclosure and check insider trading. Similarly, the foreign exchange market reform started in 1986 when a second-tier foreign exchange market was established and since then, the market has continued to witness several policy reversals and modifications to date. In 2000, reforms in the area of foreign exchange deposit took place, allowing the public to receive foreign currency

4Banks

were now allowed to complement their primary banking services with securities and insurance businesses, that is, banks were empowered to carry out all banking and non-banking services (such as issuing house business, underwriting, capital issue and participating in clearing house activities).

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in a domiciliary account so as to ensure that such remittances were retained in savings within the banking system. In all, the capital market deregulation coupled with the banking sector reforms (in particular, recapitalisation), foreign exchange and pension reforms ushered in an era of rapid growth in the capital market (Ogwumike and Afangideh, 2008). For example, market capitalisation rose from N6.8 billion in 1986 to N9,563.0 billion in 2008; and the value of shares traded rose from N497.9 million in 1986 to N1.68 trillion in 2008. What effects did financial development in Nigeria have on economic growth? Evidences show that prior to SAP, the government through its low interest rate policy tried to spur investments and growth of the economy. This era of low interest rate led to negative real rates of interest on deposits as well as loans and hindered the proper functioning of the financial system due to inability to mobilise savings and facilitate investment5. The consequence was a serious economic disruption which resulted in currency depreciation and external debt repayment problems as well as adverse consequence on the volume and productivity of investment. Figure 1 shows that over the period, the real deposit rate was predominantly negative and lowest during the period of deregulation/guided deregulation (1987 to 1996). Similarly, the real GDP growth rate was negative (at its lowest point) during the prereform era until 1985 when a positive real GDP growth rate of 9.5% was achieved. Interestingly, the period after financial reform was introduced in 1987 ushered in a positive change in real GDP growth rate. The real GDP growth rate again worsened during the period of guided deregulation starting from 1991. It attained the peak in 2002; and declined thereafter.

5

For example, low lending rates encouraged less productive investments and discouraged savers from holding domestic financial assets. Directed credits to priority sectors often resulted in deliberate defaults given that serious action could not be taken against defaulters. In fact, such loans are often seen as part of recipients’ share of the national cake.

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Figure 1: Selected Financial development indicators and real GDP growth rate in Nigeria Credit of Private Sector/GDP (%) Real Deposit Rate (%) GFCF/GDP (%) Stock Market Capitalization/GDP (%) GDP Growth Rate (%)

Rates in Percentage (%)

Bank Deposit Liability = M2 - Currency in Circulation/GDP (%)

Source: Graphed from data computed from Central Bank of Nigeria (2008) Statistical bulletin

Credit to the private sector as a percentage of GDP only attained its pre-reform level around 1990/1991 and after 2005. In fact, this development could be attributed partly to the divergence between deposit and lending rates. For example, the average interest rate spread (i.e, average lending rate minus average deposit rate) worsened during the period of deregulation. It rose from 1.0% in 1986 to 14.1% in 2005. The implications of high lending rates and low deposit rates are obvious: low incentive to save as savings are discouraged which negatively affect banks’ ability to mobilise funds. This in turn affects investment which maintained a downward trend throughout the period except between 2007 and 2008; and consequently retarded economic growth. Generally, the

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wide interest rate spread between deposit and lending rates encouraged speculation in financial transactions. Financial reform through interest rates liberalisation was expected to bring about a positive real deposit rates that would enable banks mobilise funds for investment. However, real deposit rates in Nigeria have been predominantly negative even after financial reform and banks have engaged in speculative activities at the expense of lending to the real sectors of the economy. Stock market capitalization as a ratio of GDP, gross fixed capital formation as a ratio of GDP, and bank deposit liability as a ratio of GDP equally revealed mixed performance over the period under consideration. Some of the indicators only had marginal changes in their trends between the two periods. However, most of them except real GDP growth rate witnessed significant improvements since 2005.

REVIEW OF THEORETICAL AND EMPIRICAL LITERATURE Review of Theoretical Literature The pioneering work of Schumpeter (1912) on finance-growth nexus argues that financial development will induce economic growth, through efficient allocation of funded resources to the productive sectors of the economy. Robinson (1952) however, challenges this view on the premise that it is the necessity from high economic growth that creates the need and demand for financial sector. Thus, in this view, it is the improvements in the economy that drive higher demands for the use of money which consequently promote financial development. In other words, financial markets develop and progress as an aftermath of increased demand for their services from the growing real sector. These two views were later formalized by Patrick (1966) who identified two possible causal relationships between financial development and economic growth, namely the "supply-leading" (i.e. finance-led growth) hypothesis and the "demand-following" (growth-led finance) hypothesis. The former encapsulates the views of Schumpeter (1912) and the later represents that of Robinson (1952). Both the Keynesian monetary growth models and the Mackinnon and Shaw models support the supply-leading hypothesis. However, they differ markedly in the role of government and interest rates in the financial market. Keynes affirmed that there is a historical and natural tendency for real interest rates to rise above its full employment equilibrium level and that this should necessitate government intervention to reduce it and stimulate growth. Tobin (1965) in the model of money and economic growth supports the growth-enhancing implication of low and regulated interest rates. He noted that since households have two assets - money and productive capital, the higher is the return on capital relative to money, the more capital households will hold relative to money. This produces a higher capital/labour ratio, a higher labour productivity and

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hence higher economic growth. Therefore, reducing interest rate, which is the return on money, increases the pace of economic growth. On the other hand, financial repression- controlled interest rate and high reserve requirements are the main focus of McKinnon Shaw School. They argue that the policy is harmful to long-run growth because it reduces the volume of fund available for investment (Eschenbach, 2004). Both McKinnon (1973) and Shaw (1973) contend that controlled lending and deposit rates lead to non-price rationing of credit, which results into repressed financial system and slow growth. They affirmed that financial reforms that liberalize the financial market will lead to greater financial development. Also, that a financial liberalization would not only propel financial allocation efficiency of credit from the unproductive sectors to the productive sectors, but would deepen the financial sector savings (deposits liabilities) role through a positive real interest rate. They termed this the complementarity hypothesis between real money balance and investment. Essentially, under this hypothesis, exogenous liberalization reforms will cause interest rate to be positive, which in turn increases savings liabilities, and credit allocation efficiency that eventually transform to real investments and increase output and economic growth. The endogenous growth literature have reached similar conclusion that financial intermediation has a positive effect on the steady-state growth (Greenwood and Jovanovic 1990; Becivenga and Smith 1991; Pagano 1993); and that government intervention in the financial system has a negative effect on the growth rate. In addition, the endogenous growth theory predicts a positive relationship between real income, financial depth and real interest rate (see also King and Levine, 1993). As argued in the literature, financial intermediaries through debt intermediation promote investment, which in turn, raises the level of output (Shaw, 1973; and Luintel and Khan, 1999). Similarly, Levine and Zervos (1996) state that, stock market promotes investment through the provision of long- term (working) capital which in turn, raises output and growth. Likewise, Khan and Senhadji (2000) advocate the nonexclusion of stock market contribution to economic growth, prior to which, the Levine model (1991) contends that investment will be discouraged when market participants (i.e. investors, accumulated idle saving) are risk averse with no capital/stock market to look/invest in. Similarly, studies such as Atje and Jovanovich (1993), Greenwood and Smith (1997), Levine and Zervos (1998), among others, suggest that stock market liquidity is a catalyst for long-run growth in developing countries. Without a liquid stock market, many profitable long-term investments would not be undertaken as savers would be reluctant to tie up their investments for long periods of time.

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The view that financial development is an outcome of the growth in the real economy was originally put forward by Robinson (1952) who stated that "where enterprise leads finance follows". Interestingly, support for this view can also be found in the works of Friedman and Schwartz (1963, cited in Demetriades and Hussein, 1996) on the demand for money. They conclude that the causation would run from real GDP to financial development, through the demand for money. The work of Patrick (1966) popularized the “demand-following" hypothesis or the "growth-led finance” relationship. He contends that the creation of modern financial institutions, their financial assets and liabilities as well as services are in response to the demand for these services by investors and savers in the real economy. In essence, economic growth depends on the accumulation of input factors in the production process and technical progress; and finance is one of this input factor, which affects both production and technical progress. Patrick (1966) argues that the causation between financial development and economic growth varies according to the stages of development process. He advocates that the supply-leading pattern dominates the early stages of economic development, while the demand-following dominates the later stages. With the possibility of a cyclical causal relationship-feedback hypothesis, a two-way causal relationship between financial development and economic performance may exist. In this hypothesis, it is asserted that a country with a well-developed financial system could promote high economic expansion just as Schumpeter (1912) suggest, through technological changes, product and services innovation. This in turn creates higher demand on the financial arrangements and services as noted by Levine (1997). Hence, the exact transmission channels from finance to economic growth and in particular any estimate of their quantitative impacts is still subject to considerable uncertainty. Review of Empirical Literature A number of empirical studies have attempted to test these hypotheses and their findings have been mixed. Some of these studies have validated the supply-leading hypothesis (see for example, King and Levine 1993; Levine and Zervos, 1996; Levine, 1997; Arestis et al., 2002; Christopoulos and Tsionas, 2004; and Acaravci et al., 2007). Similarly, Akinlo and Egbetunde (2010) examine the long-run causal relationship between financial development and economic growth in ten Sub-Saharan African countries. The results show that financial development causes economic growth in four countries, while growth Granger causes financial development in one country. The results of the rest of the five countries support bi-directional causality. Similarly, Esso (2010) in a study using ECOWAS countries found supply-leading relationship in three countries, while growth causes financial development in one; and bi-directional causality in two countries. Kargbo and Adamu (2009) in a study on the relationship between financial development and economic growth in Sierra Leone the result supports the supply-leading hypothesis. Shittu (2012) finds a positive relationship

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between financial intermediation and economic growth. While some others provide evidence in favour of the demand-following hypothesis (see for example Lucas, 1988; Stern, 1989; Chandavarkar, 1992; Gurgay et al., 2007 and Shahnoushi et al., 2008; among others). The feedback hypothesis has been supported by such empirical works by Levine (1997), Luintel and Khan (1999) and Demetriades and Andrianova (2003). Odeniran and Udeaja (2010) test the competing finance-growth nexus hypotheses using Granger causality tests in a VAR framework. The results suggest bidirectional causality between financial development and economic growth. Kolapo and Adaramola (2011) examined the impact of capital market on economic growth in Nigeria. The evidence from this study reveals that the activities in the capital market tend to drive economic growth. The causality test results suggest a bi-directional causation between economic growth and the value of transactions in the stock market and a unidirectional causality from market capitalisation to economic growth. Osuji and Chigbu (2012) employ the Granger Causality test, Co-integration and Error Correction Method (ECM) to investigate the impact of financial development on economic growth Nigeria. The Granger tests indicate a bi-causality between Money Supply (MS) and Economic Growth (GDP). Thus, the debate on finance-growth relationship is still on-going and therefore offers a vacuum for future research. In addition to the consideration of both long-run and shortrun dynamics and the causal linkage between financial development and economic growth in Nigeria, the present paper also captures both the direct effect (which works through the price and quantity channel) and the indirect effect (through stock market channel). Essentially, the Bounds test approach (developed by Persaran et al, 2001 and suitable for small sample size study) and the multivariate causality however often referred to as VAR-Granger causality test are employed to answer the research questions. METHODOLOGY Model Specification In line with the extant literature, we use financial depth, financial intermediation and stock market capitalization to proxy financial development. Financial depth is conceived to be positively related to real income and real interest rate as postulated in the theoretical literature particularly in the McKinnon-Shaw models and the endogenous growth literature (see Luintel and Khan, 1999). The complementarity between money and capital supports the positive relationship between the level of output and financial depth (McKinnon, 1973). As argued in the literature, financial

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intermediaries through debt intermediation promote investment, which in turn, raises the level of output (see Shaw, 1973; and Luintel and Khan, 1999). Similarly, Levine and Zervos (1996) state that, stock market promotes investment through the provision of long- term (working) capital which in turn, raises output and growth. Also, a positive real interest rate, increases financial depth through increased volume of financial savings mobilization and by extension promotes growth through increasing the volume and productivity of capital. A higher real interest rate exerts a positive effect on the average productivity of physical capital by discouraging investors from investing in low return projects. In addition, the endogenous growth theory predicts a positive relationship between real income, financial depth and real interest rate (see also King and Levine, 1993). Based on the foregoing, and following Khan et al. (2005), the relationship between growth and financial development can be specified as:

RGDPt  f  BDL, CPS , RDR, INV , SMC t

(1)

Where: RGDP = Real Gross Domestic Product BDL = Bank Deposit Liability CPS = Credit to the Private Sector RDR = Real Discount Rate INV = Investment SMC = Stock Market Capitalisation In this study, the effect of financial sector reform through the introduction of structural adjustment programme in 1986 is examined. Thus, equation (1) is modified to include a dummy variable as specified below:

RGDPt  f  BDL, CPS , RDR, INV , SMC, DUM t

(2)

To estimate equation (2), we take the natural logs of both sides which will result in the following equation (3)

lnRGDPt  0  1lnBDLt  2lnCPSt  3 RDRt  4lnINVt  5lnSMCt  6 DUM t  ut

lnBDL  0, lnCPS  0, RDR  0, lnINV  0 and lnSMC  0

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(3)

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The dummy variable accounts for financial sector reform shifts in Nigeria. DUM = 0 from 1975 to 1985 and 1 from 1986 to 2008. Where ut denotes the white noise error term,

0

is a constant parameter while

1

to

6

are parameter coefficients. Except

real deposit rate and the dummy, all the variables are expressed in logarithmic form. Also, all coefficients are expected to be positive. Banks deposit liabilities (BDL), our measure of financial depth, is calculated by taking the difference between total liquid liabilities and currency in circulation divided by nominal GDP. A higher ratio implies a greater financial intermediary development. The standard measure of financial depth in the literature is the ratio of broad money to GDP (i.e. M2/GDP). However, as stressed by Demetriades and Luintel (1996) and Luintel and Khan (1999), this ratio measures the extent of monetisation rather than of financial depth. They argue that in the developing countries, monetisation can be increasing without financial development occurring. In line with this argument, we regard M2/GDP as not an entirely satisfactory indicator of financial depth. We, therefore, include an alternative financial depth as a ratio of total bank deposit liabilities to nominal GDP (i.e. deducting currency in circulation from M2). The use of CPS as an indicator of financial intermediary has some advantages. More importantly,it excludes credit to the public sector as well as credit issued by the central bank. Thus, it represents more accurately the role of financial intermediaries in channelling fund to private market participants. De Gregorio and Guidotti (1995) argue that CPS has a clear advantage over other measures of monetary aggregate such as M1, M2 and/or M3 in that it reasonably captures the actual volume of funds channelled to the private sector. This financial indicator (CPS) has been previously used in investigating the relationship between financial development and economic growth in Nigeria (see Olomola, 1994; and Nzotta and Okereke, 2009). We interpret higher CPS/GDP as an indicator of more financial services and, therefore, greater financial intermediation. Real deposit rate (RDR) is calculated by taking the difference between the nominal deposit rate and inflation rate. Investment (INV) is seen as the expenditure on fixed assets (buildings, plant and machinery, vehicles, etc.), either for replacement or adding to the stock of existing fixed assets. It is measured as the ratio of gross capital formation to GDP. SMC is the ratio of stock market capitalization to GDP. The size of the stock market is positively correlated with the ability to mobilise capital and diversify risk6 .

6

Other complementary measures of stock market size are the stock market liquidity and risk diversification (Levine and Zervos, 1996). But, we have chosen market capitalization as a ratio

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Estimation Technique Autoregressive Distributed (ARDL) Bounds Test Approach This study employs the autoregressive distributed (ARDL) bounds test approach proposed by Pesaran et al. (2001), based on unrestricted error correction model. Compared to other cointegration procedures such as Engle and Granger (1987) and Johansen and Juselius (1990), the bounds test approach appears to have gained popularity in recent times for a number of reasons. First, the endogeneity problems and inability to test hypotheses on the limited coefficients in the long run associated with Engle-Granger method are avoided, that is, it has superior statistical properties on small samples as it is relatively more efficient in small sample data sizes evident in most developing countries. Second, the long run and short run parameters of the model are estimated simultaneously. Third, all the variables are assumed to be endogenous. Fourth, it does not require unit root testing usually employed to determine the order of integration of variables. Lastly, whereas all the other methods require that the variables in a time series regression are integrated of order one, I(1), only that of Pesaran et al. (2001) could be used regardless of whether the underlying variables are I(0), I(1) or fractionally integrated. Nonetheless, to apply the bounds test, it is important to ensure that the variables under consideration are not integrated at an order higher than one. In the presence of I(2) variables, the critical values provided by Pesaran et al.(2001) are no longer valid. The following ARDL representation of equation (3) will be estimated in order to test the existence of long run relationship between economic growth and financial development: k

k

k

k

k

i 1

i 1

i 1

i 1

i 1

lnRGDPt  0   1i lnBDLt i   2i lnCPSt i   3i RDRt i   4i lnINVt i   5i lnSMCt i k

  6i lnRGDPt i  7lnBDLt 1  8lnCPSt 1  9 RDRt 1  10lnINVt 1  11lnSMCt 1 i 1

 12lnRGDPt 1  13 DUM t  ut

(4)

To determine the optimal lag length for the ARDL model in equation (4), lag selection criteria such as the Schwarz Information Criteria (SIC) and Akaike Information of GDP as it reflects the size of the market more than the liquidity or risk diversification measures.

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Criterion (AIC) are employed and the lag combination that minimises these criteria is the optimal lag for the model. Investigating the presence of a long run relationship amongst the variables in equation (4) given the chosen lag requires the use of the Wald test (or F-test) in which the joint significance of the coefficients for lagged one variable is tested with F-statistics calculated under the null. We perform a joint significance test, where the null hypothesis (H0: β7 = β8 = β9 = β10 = β11 = β12 = β13 =0) against the alternative, (H1: at least one of the parameters is not equal to zero). Consequently, the computed F-statistic is then compared with the non-standard critical bounds values reported by the Pesaran et al. (2001). If the computed F-statistic exceeds the upper critical bounds value, then H0 is rejected. If the F-statistic lies below both the upper and the lower critical bounds value, it implies that the null hypothesis of no cointegration is not rejected. However, when the computed F-statistic falls or lies between the critical lower and upper bounds values, then the test becomes inconclusive. Once the cointegrating relationship is established, the short run dynamics is also analyzed. The error correction model representation of the ARDL model is specified in equation (5) below: k

k

k

k

i 1

i 1

i 1

lnRGDPt   0  1i lnRGDPt i   2i lnBDLt i  3i lnCPSt i   4i RDRt i i 1

k

k

i 1

i 1

 5i lnINVt i   6i lnSMCt i   ECM t 1   t

(5)

Where λ is the speed of adjustment parameter, ECM is the residual obtained from the long run estimation and  t is a white noise error term. In addition, we perform the CUSUM and CUSUMSQ test for parameter stability. Causality To complement this study, we conduct a causality test to establish the direction of causality between financial development (and hence the various measures of financial development) and economic growth. Essentially, this test is employed to determine whether the link between financial development and economic growth follows the supply-leading hypothesis or demand leading hypothesis or both. According to Granger (1968), a variable say y is said to granger cause another variable say x if past and present values of y help to predict x. This is the traditional GrangerCausality (based on a bi-variate relationship). However, this has its own limitations: a two-variable granger causality test without considering the effect of other variables is

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subject to possible specification bias, as pointed out by Gujarati (1995), “...a causality test is sensitive to model specification and the number of lags”. Therefore, the empirical evidence of two-variable Granger causality may be biased when the number of endogenous variables is more than two due to restriction of other endogenous variables in the model. To this note, we consider the VAR Granger Causality test that allows for several endogenous variables. The VAR Granger specification is given as: p

p

p

p

p

p

bdlt   1 j bdlt  j   2 j rgdpt  j   3 j cpst  j   4 j rdrt  j   5 j invt  j   6 j smct  j  1t        (6) j 1

j 1

j 1

p

j 1

p

j 1

p

j 1

p

p

p

rgdpt   1 j rgdpt  j   2 j bdlt  j   3 j cpst  j   4 j rdrt  j   5 j invt  j   6 j smct  j   2t      (7) j 1

j 1

p

j 1

p

j 1

p

j 1

p

j 1

p

p

cpst  1 j cpst  j  2 j rgdpt  j  3 j bdlt  j  4 j rdrt  j  5 j invt  j  6 j smct  j   3t      (8) j 1

j 1

j 1

p

p

p

j 1

j 1

j 1

p

p

p

j 1

p

j 1

p

j 1

p

rdrt  1 j rdrt  j  2 j rgdpt  j  3 j bdlt  j  4 j cpst  j  5 j invt  j  6 j smct  j   4t        (9) j 1

j 1

p

j 1

p

p

invt  1 j invt  j   2 j rgdpt  j   3 j bdlt  j   4 j cpst  j   5 j rdrt  j   6 j smct  j   5t      (10) j 1

j 1

j 1

p

j 1

p

j 1

p

j 1

p

p

p

j 1

j 1

j 1

j 1

j 1

j 1

smct  1 j smct  j  2 j rgdpt  j  3 j bdlt  j  4 j cpst  j  5 j rdrt  j  6 j invt  j   6t      (11)

This multivariate causality test requires as a precondition, the estimation of a corresponding VAR model as specified in equations 6 –11. Data Sources The study is based on annual data sourced from Central Bank of Nigeria (CBN) Statistical Bulletin and Annual Report and Financial Statement (various years). Data on stock market capitalisation was sourced from the Nigerian Stock Exchange Fact Book (various years). ESTIMATION RESULTS AND DISCUSSION Although the ARDL approach to cointegration does not require the pre-testing of the variables included in the model for unit root, the ADF unit root test is however considered as this is necessary for VAR Granger causality test. The results are presented in Appendix 1. Virtually all the variables in the model are stationary at first difference and thus integrated of order 1 (i.e. I(1) series). Test of cointegration shows that the computed F-statistic of 5.55 exceeds the lower and upper bounds critical values

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of 3.15 and 4.43, respectively at the 1 per cent significance level, using Pesaran et al (2001). Thus, the null hypothesis of no cointegration is rejected, implying long run relationship among rgdp, bdl, cps, rdr, inv, and smc7. Table 1: Bounds Tests for the Existence of Cointegration Dependent variable Critical F-statistic = 5.55 value Lower bound Upper bound Frgdp(rgdp│bdl, cps, 1% 3.15 4.43 rdr, inv, smc, dum) 5% 2.45 3.61 10% 2.12 3.23 Notes: Asymptotic critical value bounds are obtained from Table CI (iii) case III: unrestricted intercept and no trend for k = 6 (Pesaran et al, 2001).

Long and Short Run Dynamics The long run coefficients are presented in Table 2. As shown, the estimates of bank CPS, SMC and financial reform/deregulation (DUM) have the expected signs while the BDL, INV and the RDR do not conform to the theoretical expectation. Four of the variables are statistically significant at the one per cent while financial reform DUM is significant at 5 per cent level. The RDR and BDL do not seem to impact significantly on long run growth in Nigeria. Observably, financial intermediation proxied by bank CPS is an important factor contributing to economic growth in the Nigerian economy and is highly significant at one per cent. The coefficient of financial intermediation indicates that in the long run, a one per cent increase in financial intermediation increases real output by 0.90 per cent. The results are contrary to the findings of Osuji and Chigbu (2012) for Nigeria. Also, a one per cent rise in SMC increases real output growth by 0.57 per cent. The coefficient of the RDR contributes an insignificant negative effect. This suggests that RDR does not appear to have any significant contribution on aggregate output in the country. Thus, it is logical to conclude that the low interest rate on deposits is not encouraging to stimulate the required level of savings to boost investment and economic growth in Nigeria.

7

The test for cointegration was also carried out using Johanson cointegration test. A long run relationship exists. While the trace test indicates three cointegrating equations at 1% level, the max-eigenvalue test also indicates three cointegrating equations. With two cointegrating equation(s) at 5% and one cointegrating equation at 1%.

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Table 2: Estimates of the Long Run Coefficients ARDL (1, 0, 0, 1, 1) Dependent Variable: RGDP Coefficient p-value Const 10.5583 0.00001*** BDL -0.104503 0.67363 CPS 0.902922 0.00974*** RDR -0.00259726 0.57172 INV -0.957859 0.00009*** SMC 0.565489 0.00026*** DUM 0.58097 0.02275** *** (**) critical values at 1% (5%). All variables are significant at 5% level

R-squared Adjusted R-squared F-statistic Durbin-Watson stat

0.889678 0.865162 36.28970 (0.000) 1.445337

Source: Authors’ analysis

Although highly significant, the coefficient of investment, measured as Gross Fixed Capital Formation to GDP has a negative value of – 0.96 per cent, indicating that investment has not promoted economic growth in Nigeria. Notably, from existing growth literature, investment share is mostly a robust variable explaining economic growth. Previous studies have attributed this negative coefficient of investment in relation to real output in the case of Nigeria to the following factors: (i) most public sector infrastructure investments are not worthwhile; (ii) government implemented public projects that turned out to be money-draining projects; (iii) government contracts were awarded at inflated prices or completely abandoned after mobilisation fees have been paid; (iv) there was looting of public funds which are central to savings and investment; (v) low per capita income in Nigeria resulting in low private domestic saving and thus may not be a major source of investment; (vi) frequent regime changes and its attendant poor policy implementation, leading to lower long run investment; (vii) public and private corrupt practices which divert scarce resources from productive activities to unproductive activities arresting economic growth; and (viii) the frequent use of deposits by Nigerian banks to trade in foreign exchange and government treasury bills, among others, rather than channelling mobilized funds to the real sector of the economy (see Soludo, 2004; Onwiodukokit and Adamu, 2005; Guseh and Oritsejafor, 2007; and Obamuyi, 2009). Given the insignificant negative RDR, the estimated coefficient of financial depth (BDL) is also negative (-0.11). Previous studies on Nigeria have also found this

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negative relationship between financial depth and the level of real output growth. For example, Adeoye and Adewuyi (2005) show that financial depth measured by M2/GDP lags behind the tempo of economic activities and may not have been the source of real GDP growth in Nigeria. Adeoye and Adewuyi (op. cit) attributed this poor performance of financial depth in Nigeria to three factors: (i) Macroeconomic instability due to high inflation rates; (ii) removal of foreign exchange control without appropriate measures to avoid rapid exchange rate depreciation; and (iii) the introduction of treasury bill (TB) auctions which made TB rates more attractive to larger depositors who opted for TBs at the expense of time deposits. Finally, the coefficient of financial reform dummy though relatively small is significant and positive (0.58). Financial reforms which ensued healthy competition and therefore improved service delivery by the financial institutions in Nigeria appear to be growthoriented Nonetheless, concerted efforts geared towards improving the management of the liberalisation process through effective monitoring and regulatory framework may drive a higher impact of financial reforms on growth. . Short Run Dynamics Premised on the tenet that financial development reforms especially in developing countries lack credibility and continuity, a short run analysis becomes unavoidable. The results obtained from the short run dynamic are presented in Table 3. The results show that the estimated lagged error correction term (ECMt-1) is negative and highly significant. This supports the co integration among the variables represented by equation (1). The feedback coefficient is -0.41, which suggests a fairly high speed of adjustment to equilibrium after a shock. Approximately, 41 per cent of the disequilibria from the previous year’s shock converge or adjust back to the long run equilibrium in the current year. Also, at least one of the representations of each variable in the error correction model is statistically significant although at different levels of significance. For example, while ∆invt-1 and Δrgdpt-1 representing change in investment and economic growth respectively are statistically significant at 5% and 1%, ∆rdrt-1, ∆cpst-1 and ,∆smct-1 denoting change in real deposit rate, credit to private sector and stock market capitalization respectively are all significant at 10%. This suggests that the impact of financial development on the real sector has lag effects. Although, the short-run response of current RDR is positive, its contribution is small and insignificant. This is justifiable in Nigeria because low deposit interest rate makes savings unattractive as a sizeable proportion of income is spent on “consumer goods”. Further, the changes in real output respond positively to the changes in SMC in the short run. Therefore, increased access to long term financing may enhance the growth process in Nigeria. However, changes in real output respond negatively to changes in

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BDL; thus, suggesting inefficient and weak financial intermediaries in the mobilization of funds for productive activities.

Table 3: Error Correction Representation of ARDL Model (1, 0, 0, 1, 1, 1) selected on the basis of AIC Coefficient Std. Error t-ratio p-value Const 0.0542039 0.0416698 1.3008 0.20742 ΔRGDPt-1 0.54113 0.161936 3.3416 0.00309*** ΔBDLt -0.0787969 0.14095 -0.5590 0.58205 ΔCPSt 0.347677 0.193879 1.7933 0.08735* ΔRDRt 0.000717117 0.00214902 0.3337 0.74192 ΔRDRt-1 -0.0039473 0.00223683 -1.7647 0.09216* ΔINVt -0.157638 0.179651 -0.8775 0.39016 ΔINVt-1 0.339038 0.160764 2.1089 0.04713** ΔSMCt 0.0925685 0.16848 0.5494 0.58850 ΔSMCt-1 -0.297369 0.16564 -1.7953 0.08702* ECMt-1 -0.412019 0.124025 -3.3221 0.00324*** Note: ***, ** and * represent level of significance at 1%, 5% and 10% respectively.

R-squared F(10, 21) Log-likelihood Schwarz criterion

0.561392 2.687874 15.72400 6.675087

Adjusted R-squared P-value(F) Akaike criterion Durbin's Watson

0.352531 0.027006 -9.448008 0.168738

Stability Tests We also performed CUSUM and CUSUMSQ stability test for estimated error correction model. This is important in order to investigate whether the above long and short run relationships found are stable for the entire period of study. The methodology used is based on the Cumulative Sum (CUSUM) and the Cumulative Sum of Squares (CUSUMSQ) tests proposed by Brown et al. (1975). Unlike the Chow test that requires break point(s) to be specified, the CUSUM tests can be used even if we do not know the structural break point. The CUSUM test uses the CUSUM of recursive residuals based on the first n observations and is updated recursively and plotted against the

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break point. The CUSUMSQ makes use of the squared recursive residuals and follows the same procedure. Figure 2 shows that the plots of CUSUM and CUSUMSQ are within the five per cent critical bound, thus providing evidence that the parameters of the model do not suffer from any structural instability over the period of study. In other words, all the coefficients in the error correction model are stable.

Fig. 2: CUSUM and CUSUMSQ Plots for Stability Tests

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Granger Causality Test Result: The comprehensive report of the VAR granger causality is presented in the appendix. Extract of the result is however shown in table 4 below for easy reference: At 5 per cent level of significance, the VAR Granger causality test reveals that all the financial development variables in the model jointly have a causal effect on economic growth but not always individually (as “bdl, and cps” do not granger cause “rgdp” individually). However, economic growth (rgdp) does not appear to granger cause financial development. Overall, the causality result appears to support the view that causality runs from financial development to economic growth and therefore, the "supply-leading" hypothesis seems evident in Nigeria. This is in line with the findings of Adelakun (2010) for Nigeria using the traditional bi-variate granger causality. The results are contrary to the findings of Osuji and Chigbu (2012) and Samson and Elias (2010) for Nigeria, who found a bi-directional causal relationship between economic growth and financial development. Table 4: Multivariate VAR Granger Causality Test Result Equtn 6

Equtn 7

Equtn 8

Equtn 9

Equtn 10

Equtn 11

BDL

RGDP

CPS

RDR

INV

SMC

D.V

(0.826) {0.661}

(3.514) {0.172}

(0.128) {0.937}

(1.769) {0.016}**

(2.623) {0.269}

(2.136) {0.343}

(0.6598) {0.719}

D.V

(0.1227) {0.9405}

(1.057) {0.589}

(8.197) {0.016}**

(0.134) {0.854}

(0.026) {0.986}

CPS

(1.9338) {0.380}

(3.4539) {0.1779}

D.V

(0.111) {0.945}

(1.8425) {0.398}

(1.347) {0.509}

(0.089) {0.956}

RDR

(3.9814) {0.136}

(5.4172) {0.066}*

(8.6548) {0.013}**

D.V

(3.593) {0.165}

(1.792) {0.408}

(2.460) {0.292}

(1.4452) {0.485} (7.3328) {0.025}**

(9.808) {0.00}*** (5.034) {0.080}*

(2.4424) {0.2949} (3.7076) {0.1566}

(4.029) {0.133} (0.375) {0.829}

D.V

(0.014) {0.992}

(5.3167) {0.070}**

D.V

(6.550) {0.037} (1.974) {0.372}

Equation Variable BDL RGDP

INV SMC DUM

DUM

(2.2686) (1.507) (0.3901) (2.913) (0.9476) (0.445) D.V {0.321} {0.470} {0.8228} {0.233} {0.6226} {0.800} ALL (26.608) (21.75) (31.774) (9.572) (20.742) (8.769) (22.19) {0.008}*** {0.04}** {0.001}*** {0.653} {0.054}** {0.722} {0.03}** NOTE: ( ) = Chi-Sq, { } = Prob, and D.V = Dependent Variable. ***, **, and * indicate significance at 1, 5 and 10% respectively. Source: Authors’ Analysis.

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CONCLUSION AND POLICY IMPLICATIONS This study examined the empirical relationship between financial development and economic growth in Nigeria from 1975 to 2008, using Bound test Autoregressive Distributed Lag (ARDL) approach. The results show that there exists a unique long run relationship between financial development and economic growth. Thus, financial development is an important determinant of economic growth in Nigeria. In the long run, financial reform (though small), credit to private sector and stock market exerted positive impact on economic growth. While financial depth- bank deposit liability and real deposit rate (although insignificant) and investment showed a negative impact on real income. However, in the short run, most of the variables were statistically significant; thus, justifying evidence of lag effect between financial development and economic growth. Also, we find a stable long run relationship between financial development and economic growth, as indicated by the CUSUM and CUSUMSQ stability tests. Five interesting results are obtained from this study. First, financial development enhances economic growth in Nigeria. In particular, credit to private sector and stock markets in Nigeria have yielded positive and significant results. Second, we find evidence of unidirectional causality running from financial development (particularly stock market) to growth. This implies that the development of the Nigeria stock market can significantly influence economic growth. Hence, capital market-based financial system causes growth in Nigeria. Third, financial depth does not contribute to growth in the reform era. Fourth, all financial development indicators have lag effects in the short run. This suggests that the impact of financial development on the real sector is not instantaneous. Finally, financial reform in Nigeria though with a positive impact in the long run, may still require further improvements. Based on the above findings, the following policy implications are conceived: i.

The role of deposit money banks in contributing to growth will remain an illusion if banks continue to pursue trade in foreign exchange, invest in government treasury bills and directly fund the importation of goods (Onwioduokit and Adamu, 2005) at the expense of promoting viable and efficient investment in the real sector of the economy. It is therefore recommended that effective means of improving credit channels and liquidity to private firms by banks should be encouraged by CBN.

ii.

The long run relationship between financial development and economic growth shows that the former is significant in promoting real income. Hence,

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policies should be directed towards promoting a more competitive environment that enhances service delivery among financial institutions. iii.

Poor performance of financial reforms has been attributed to improper sequencing of the reform agenda coupled with frequent policy reversals and reintroduction (Ikhide and Alawode, (2002). Government should therefore implement reforms that will enhance financial intermediation through stable and sustainable real positive interest rates followed by sound macroeconomic, monetary and fiscal policies targeted at low and sustainable inflation rates.

iv.

Equity market in Nigeria is not yet well-developed. Nonetheless, flow from our causality results shows that stock market facilitates growth in Nigeria. In order to spur a mature stock market in Nigeria and hence a higher level of growth, we recommend policies geared towards the expansion and development of the Nigerian stock market. For example, promoting a more liberalised capital market will increase the efficiency of the stock market. This will also ensure that stock prices truly reflect their fundamental worth (values) or the expected future profitability of companies. Therefore, resources can be effectively channeled to the most efficient and productive companies, which will be better positioned to implement their investment plans and hence, stimulate economic growth.

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REFERENCES Acaravci, A., Ozturk, I. and Acaravci, S.K. 2007. Finance-growth nexus: Evidence from Turkey. International Research Journal of Finance and Economics 11: 1450–2887. http://www.eurojournals.com/finance.htm. Adelakun, O. J. 2010. Financial Sector Development and Economic Growth In Nigeria. International Journal of Economic Development Research and Investment Vol. 1, No 1, April 2010. Pp 25-41 Adeoye, B. W. and Adewuyi, A. O. 2005. Benefits and costs of financial sector reforms: Nigeria’s experience. In: Cost and benefits of economic reforms in Nigeria. Selected Paper for the 2005 Annual Conference of the Nigeria Economic Society 4.1:Chap 16. Akinlo, A. E. and Akinlo, O. 2007. Financial development, money, public expeniture and national income in Nigeria. Journal of Social and Economic Development vol. 1 Arestis, P. and Demetriades, P. 1997. Financial development and economic growth: Accessing the evidence. The Economic Journal 107.442: 754 – 770. Arestis, P., Demetriades P., Fahouh, B. and Mouratidis, K. 2002. The impact of financial liberalisation policies on financial development: Evidence from developing economies. January 2002. Ayadi, F.S. 2009. Causality, In: Foreign Direct Investment and Economic Growth in Nigeria. Repositioning African Business and development for the 21st Century Simeon Sigue (Ed). Proceedings of the 10th Annual Conference. IAABD. Ayadi, O.F., Adegbite, E.O. and Ayadi F.S. 2008. Structural adjustment, economic sector development and economic prosperity in Nigeria. International Research Journal of Finance and Economics 15. Chandavarkar, A., 1992. Of finance and development: Neglected and unsettled questions, World Development 22, pp. 133-142. Christopoulos, D.K. and Tsionas, E. 2004. Financial development and economic growth: Evidence from panel unit root and cointegration tests. Journal of Development Economics 73: 55-74. De Gregorio, J. and Guidotti, P. 1995. Financial development and economic growth. World Development 23.3:433-448. Demetriades, P. O. and Andrianova, S. 2003. Finance and growth: What we know and what we need to know. October, 19, 2003. and Luintel, K.B. 1996. Financial development, economic growth and banking sector controls: Evidence from India. The Economic Journals 106.435:359 – 374. and Hussein, A.K. 1996. Does financial development cause economic growth? Time series evidence from 16 countries. J. Dev. Econ., 51: 387-411. Edo, S. E. 1995. An estimation of a model of long-term securities investment in Nigeria. Economic and Financial Review.Vol 1 No. 12.

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Engle, R. F and Granger, C.W.I (1987) Cointegration and Error correction: Representation, estimation and Testing. Econometrica, 55:251-276. Fry, M.J. 1978. Money and Capital or Financial Deepening in Economic Development? Journal of Money, Credit and Banking, November, 464-475. Granger, C.W.J. 1969. Investigating causal relations by econometric models: cross spectral methods. Econometrica, 37: 424-438. Granger, C.W. 1986 .Developments in the study of contegrated economic variables. Oxford Bulletin of Economics and Statistics 48:213-228 Gujaraiti, D. N. 1995. Basic Econometrics 3rd ed. McGraw-Hill, New York Gurgay, E., VeliSafakli, O. and Tuzel, B. 2007. Financial development and economic growth: Evidence from Northern Cyprus. International Research Journal of Finance and Economics8©EuroJournals Publishing, Inc. 2007 http:///www.eurojournals.com/ finance.htm Guseh, J. S and Oritsejafor, E. 2007. Government size, political freedom and economic growth in Nigeria, 1960 – 2000. J. Third World Stud. March 22. Ikhide, S.I. and Alawode, A.A. 2002. On the sequencing of financial liberalisation in Nigeria. The South African Journal of Economics 70.1:95-127 Johansen, S and Juselius, K. 1990. Maximum likelihood estimation and inference on cointegration – with application to the demand for money. Oxford Bulletin of Economics and Statistics 52: 169-210. Khan, M.A., Qayyum, A and Sheikh, S.A. 2005. Financial development and economic growth: The case of Pakistan. The Pakistan Development Review 44: 4 Part II (Winter 2005) 819 – 837. King, R.G. and Levine, R. 1993. Finance and growth: Schumpeter might be right. The Quarterly Journal of Economics 108, 717 – 737. Levine, R and Zervos, S. 1996. Stock market development and long run growth. A symposium issue on stock markets and economic development. The World Bank Economic Review 10.2:323-339. Oxford Journals: Oxford University Press. Levine, R. 1997. Financial development and economic growth: Views and Agenda. Journal of Economic Literature 35: 688-726. Lucas Jr., R.E. 1988. On the mechanics of economic development, Journal of Monetary Economics 22, pp. 3-42. Luintel, K. B. and Khan, M. 1999. A quantitative reassessment of the finance-growth nexus; Evidence from a multivariate VAR. Journal of Development Economics 60: 381-405. Mckinnon, R.I. 1973. Money and capital in economic development. Washington, D.C. Brookings Institute. Ndebbio, J.E.U. 2004. Financial deepening, economic growth and development: Evidence from selected Sub-Saharan African countries, African Economic research Papers. No. 142, AER, Nairobi. Nzotta, S.M. and Okereke, E.J. 2009. Financial deepening and economic development of Nigeria: An empirical investigation. African Journal of Accounting,

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Economics, Finance and Banking Research 5.5 http://www.bcentral.cl/Estudios/DTBL/doctrab.htm. Obamuyi, F.M. 2009. An investigation of the relationship between interest rates and economic growth in Nigeria. Journal of Economics and International Finance 1.4: 093-098. Ogun, O. D. 1986. A note on financial deepening and economic growth: Evidence from Africa, Nigerian Journal of Social and Economic Studies vol. 28, No. 2. Ogwumike, F.O. and Afangideh, U. J. 2008. Financial development and income distribution in Nigeria. Journal of Monetary and Economic Integration 8.1:63-89 Olomola, S. A. 1994. Financial liberalisation and economic growth under Structural Adjustment Programme in Nigeria.African Journal of Economic Policy 1.1 Onwioduokit, E. A. and Adamu, P. A. 2005. Financial liberalisation in Nigeria: An assessment of eelative impact. In: Cost and Benefits of Economic Reforms in Nigeria. Selected Paper for the 2005 Annual Conference of the Nigeria Economic Society 4.1:Chap 14. Oyejide, T. A. 1986. The financial system and economic growth: Evidence from Africa. Nigerian Journal of Social and Economic Studies vol. 28, No. 2. Osuji C. C and Chigbu, E.E 2012. An Evaluation Of Financial Development And Economic Growth Of Nigeria: A Causality Test. Kuwait Chapter of Arabian Journal of Business and Management Review. Vol. 1, No.10; June 2012. Pp 27-44 Patrick, H. T. 1966. Financial development and economic growth in underdeveloped countries. Economic Development and Cultural Change 14.2:174–189. The University of Chicago Press. Pesaran, M.H., Shin, Y. and Smith, R. J. 2001. Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics 16:289-326. Samson O.O and Elias A.Udeaja 2010. Financial Sector Development and Economic Growth: Empirical Evidence from Nigeria. Economic and Financial Review. Volume 48/3. September, 2010. Pp 91-124 Shahnoushi, N., Ebadi, A.G., Daneshvar, M., Shokri, E. and Motallebi, M. 2008. Causality between financial development and economic growth in Iran. World Applied Sciences Journal 4.5:736-740. Shaw, E.S. 1973. Financial deepening in economic development. Oxford University Press, New York. Soludo, C. C. 2004. Consolidating the Nigerian banking industry to meet the challenges of the 21st century. An address by the Governor of the Central Bank of Nigeria at the Special Meeting of the Bankers’ Committee, Abuja, 6 July. Stern, N. 1989. The economics of development: a survey. Econ. J., 99: 597-685.

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APPENDIX Appendix 1: Augmented Dickey Fuller Test of Unit Roots Variables Level (first ADF critical 1% (5%) Order of difference) integration Rgdp -1.766151 -3.64342 (-2.954021) I(1) (-5.77383) -3.64342 (-2.954021) Bdl -1.306175 -3.64342 (-2.954021) I(1) (-5.617117) -3.64342 (-2.954021) Cps -2.366272 -3.64342 (-2.954021) I(1) (-5.373915) -3.64342 (-2.954021) Rdr -4.092583 -3.64342 (-2.954021) I(0) Inv

-1.680999 (-4.8207) -0.254409 (-6.306457)

Smc

-3.64342 (-2.954021) -3.64342 (-2.954021) -3.661661 (-2.960441) -3.653730 (-2.957110)

I(1)

Stationary Non-stationary Stationary Non-stationary Stationary Non-stationary Stationary Stationary Non-stationary Stationary Non-stationary Stationary

I(1)

Source: Computed by the authors

VAR Granger Causality Specification: p

p

p

p

p

p

bdlt    1 j bdlt  j    2 j rgdpt  j    3 j cpst  j    4 j rdrt  j    5 j invt  j    6 j smct  j  1t        (1) j 1

j 1

j 1

p

j 1

p

j 1

p

j 1

p

p

p

rgdpt   1 j rgdpt  j   2 j bdlt  j   3 j cpst  j   4 j rdrt  j   5 j invt  j   6 j smct  j   2t        (2) j 1

j 1

p

j 1

p

j 1

p

j 1

p

j 1

p

p

cpst  1 j cpst  j   2 j rgdpt  j  3 j bdlt  j   4 j rdrt  j  5 j invt  j   6 j smct  j   3t        (3) j 1

j 1

j 1

p

p

p

j 1

j 1

j 1

p

p

p

j 1

p

j 1

p

j 1

p

rdrt  1 j rdrt  j  2 j rgdpt  j  3 j bdlt  j  4 j cpst  j  5 j invt  j  6 j smct  j   4t        (4) j 1

j 1

p

j 1

p

p

invt  1 j invt  j   2 j rgdpt  j   3 j bdlt  j   4 j cpst  j   5 j rdrt  j   6 j smct  j   5t        (5) j 1

j 1

j 1

j 1

p

j 1

p

j 1

p

p

p

p

j 1

j 1

j 1

j 1

j 1

j 1

smct  1 j smct  j  2 j rgdpt  j  3 j bdlt  j  4 j cpst  j  5 j rdrt  j  6 j invt  j   6t        (6)

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Vol. 12, No.2

Journal of Monetary and Economic Integration

APPENDIX 2: VAR Granger Causality Test Result VAR Granger Causality/Block Exogeneity Wald Tests Sample: 1975 2008 Included observations: 32 Dependent variable: RGDP Excluded Chi-sq df BDL 0.826737 2 CPS 3.453877 2 RDR 5.417169 2 INV 9.808842 2 SMC 5.034929 2 DUM 1.507184 2 All 21.75883 12 Dependent variable: BDL Excluded Chi-sq df RGDP 0.659779 2 CPS 1.933760 2 RDR 3.981442 2 INV 1.445193 2 SMC 7.332820 2 DUM 2.268625 2 All 26.60874 12 Dependent variable: CPS Excluded Chi-sq df RGDP 0.122673 2 BDL 3.514217 2 RDR 8.654840 2 INV 2.442379 2 SMC 3.707630 2 DUM 0.390087 2 All 31.77493 12 Dependent variable: RDR Excluded Chi-sq df RGDP 1.057740 2 BDL 0.128899 2 CPS 0.111617 2 INV 4.029493 2 SMC 0.375164 2

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Prob. 0.6614 0.1778 0.0666 0.0074 0.0807 0.4707 0.0403 Prob. 0.7190 0.3803 0.1366 0.4855 0.0256 0.3216 0.0088 Prob. 0.9405 0.1725 0.0132 0.2949 0.1566 0.8228 0.0015 Prob. 0.5893 0.9376 0.9457 0.1334 0.8290

Vol. 12, No.1

Fidelis O. Ogwumike and Afees A. Salisu

DUM 2.913223 2 0.2330 All 9.572549 12 0.6534 Dependent variable: INV Excluded Chi-sq df Prob. RGDP 8.197907 2 0.0166 BDL 1.769129 2 0.4129 CPS 1.842458 2 0.3980 RDR 3.593599 2 0.1658 SMC 5.316692 2 0.0701 DUM 0.947564 2 0.6226 All 20.74233 12 0.0543 Dependent variable: SMC Excluded Chi-sq df Prob. RGDP 0.314066 2 0.8547 BDL 2.623620 2 0.2693 CPS 1.346975 2 0.5099 RDR 1.792863 2 0.4080 INV 0.014759 2 0.9926 DUM 0.445504 2 0.8003 All 8.769080 12 0.7225 n 3 is column 2 multiplied by 148 to convert current US dollar to Naira

119