This paper examines the extent of causal relationship between stock market ..... e = white noise disturbance error term ln= Natural logarithm .... GDPR level has an inverse effect of 18% on current economic performance. This reversed result ...
REIKO INTERNATIONAL JOURNAL OF SOCIAL AND ECONOMIC RESEARCH VOL. 8 NO. 3C SPECIAL EDITION OCTOBER 2015 THE NIGERIAN STOCK EXCHANGE: IT’S IMPACT ON THE PERFORMANCE OF THE NIGERIAN ECONOMY (1981-2012): AN ECONOMETRIC APPROACH. OGBOLE FRIDAY OGBOLE (PHD) Department of Accounting Federal University Wukari, Nigeria. And SAMSON ADENIYI ALADEJARE Department of Economics Federal University Wukari, Nigeria.
ABSTRACT
The Stock Market is a specialized financial market. It has the potential to mobilize savings and investments for economic and industrial growth. As a long term security provider, the market enhances economic performance in different national economies. This paper examines the extent of causal relationship between stock market variables and economic performance in Nigeria. Time series analysis and Vector Error Correction Mechanism were used in the analyses. Annual data (1981 to 2012) were used; sourced from statistical bulletin, Central Bank of Nigeria (2012) and World Bank Development Index (2013). The variables used are: Gross Domestic Product Growth Rate (explanatory), while total number of deals, total value of deals, annual market capitalization and real interest rate are all explanatory. The findings reveal that the performance of the economy is influenced by the level of real interest rate, total number of deals, total value of deals and the market capitalization. The study recommends among others an enabling macroeconomic environment to sufficiently enhance the performance of the stock market. Thus, stock market regulators should address policy issues to boost the confidence of investors through improved policy formulation, objective implementation and appropriate supervision to occasion a stable macro-economic environment. Keywords: Gross Domestic Product, Growth Rate, Real Interest Rate, Total Number of Deals, Total Value of Deals, Market Capitalization, Vector Error Correction Mechanism. JEL CODE 59 – SE 1
OGBOLE FRIDAY OGBOLE (PHD) AND SAMSON ADENIYI ALADEJARE THE NIGERIAN STOCK EXCHANGE: IT’S IMPACT ON THE PERFORMANCE OF THE……. I. Introduction The stock market provides equity and a direct form of finance to potential investors for investment purposes. It is a long-term lubricant in the economic growth process thus an important yardstick for measuring a country's economic strength and development. A number of stock market indices may also be used as a guide in the measurement of changes in the general level of economic activities within an economy. The stock market provides long-term capital for governments and industry to finance new projects, expand and modernize industrial/commercial concerns. The rate of expansion of the economy often slows down when capital resources are lacking. It has been observed that while developed economies harness the potentials of both money and capital markets for economic growth and development (Samuel, 1996; DemirgucKunt and Levine, 1996), developing economies generally lay emphasis on the money market with little consideration for the capital market (Nyong, 1997). Interestingly, with the introduction of structural adjustment program (SAP) in Nigeria, the country’s stock market has grown very significantly (Soyode, 1990;Alile, 1996). The deregulation of the financial sector and the privatization exercises exposed investors and companies to the significance of the stock market. Equity financing became very cheap and flexible and assumed a critical role in sustainable development of the economy (Okereke-Onyiuke, 2000). Also, the financial structures of firms change as economies develop (Nyong 1997). However, the central objectives of the stock exchanges worldwide remain the maintenance of an efficient market to enhance economic growth (Alile, 1997). Studies of developed and emerging markets in relation to the relationship between stock market performance and economic growth vary in findings (Akinifesi, 1987; Samuel, 1996; Demirguc-Kunt and Levine, 1996;; Levine and Zervos, 1996; Obadan, 1998; Onosode, 1998; Emenuga, 1998; Osinubi, 1998). A well developed stock market enhances savings and provides investment capital at lower costs by offering financial instruments to savers to diversify their portfolios. These markets efficiently allocate capital resources to productive investments, which would eventually promote economic growth (Dailami and Aktin, 1990). This study therefore, empirically investigates whether the Nigerian Stock Market promotes economic growth in Nigeria. Ordinary least square method of analysis was used amongst others, on secondary data for the period 1981 to 2012. The remainder of the study is organized as follows: Section two reviews the literature; section three deals with the methodology and section four, the empirical analyses. Section five concludes the study with summary and recommendations. II.
LITERATURE REVIEW Levine and Zervos (1996), used a pooled cross-country time-series regression of forty-one countries' data (1976 to 1993), patterned after Demirgüç-Kunt and Levine (1996), by conglomerating stock market measures ( size, liquidity, and integration with world markets) into indices of stock market development. The growth rate of Gross Domestic Product (GDP) per capita was used as a criterion variable while variables 2
RIJSER VOL. 8 NO. 3C SPECIAL EDITION OCTOBER 2015 designed to control for initial conditions, political stability, investment in human capital, and macroeconomic conditions and the conglomerated index of stock market development were the explanatory variables. The result showed a strong correlation between overall stock market development and long-run economic growth. This is in line with theories of positive relationship between stock market development and economic growth. Nyong (1997), in Nigeria, used an aggregate index of capital market development and established a negative and significant correlation with long-run economic growth as well as a bi-directional causality between them. He combined into one overall composite index of capital market development using principal component analysis the ratio of market capitalization to GDP (in percentage), the ratio of total value of transactions on the main stock exchange to GDP (in percentage), the value of equities transaction relative to GDP and listings. A measure of financial market depth (which is the ratio of broad money to stock of money to GDP) was also included as control variable. Using data from 1980–2000 and employing least square regression, Osinubi (2001), established a positive link between economic growth and stock market development and recommended the pursuit of policies geared towards rapid development. Also, Caporale and Soliman (2004) show that an organized and well managed stock market stimulates investment opportunities. Alajekwu and Nieuwerburgh et al (2005), established in Belgium, using stock market indicators from 1873–1935 that institutional changes affecting the stock market explain the time-varying nature of the link between stock market development and economic growth. Furthermore, Brasoveanu, et al (2008), found that in Romania, for the period 2000 to 2006 capital market development is positively correlated with economic growth through feed-back effect. Soumya & Jaydeep (2008), established a bi-directional causal relationship between real market capitalization ratio and economic growth and a strong causal flow from the stock market development to economic growth for the Indian economy using the techniques of unit–root tests and the long–run Granger non-causality test proposed by Toda and Yamamoto (1995). In France, Vazakidis and Adamopoulos (2009), using data from the period 1965 to 2007 discovered a significant positive association between economic growth and stock market development, and that interest rate negatively impacted on stock market development. Sudharshan and Rakesh (2011), studied the possibility of the stock market performance leading to economic growth or vice versa. They also examined short-run and long-run dynamics of the stock market using monthly Index of Industrial Production (IIP) and quarterly Gross Domestic Production (GDP)(1996 to 2009). Unit root tests, Granger Causality test, Engle-Granger Cointegration test and Error Correction Model were employed. The monthly results of Granger causality test suggest that there is a bi-directional relationship between Index of Industrial Production (IIP) and Stock prices and quarterly results reveal that there is no relationship between GDP and BSE but in the case of NSE and GDP there is a unidirectional relationship that runs from GDP 3
OGBOLE FRIDAY OGBOLE (PHD) AND SAMSON ADENIYI ALADEJARE THE NIGERIAN STOCK EXCHANGE: IT’S IMPACT ON THE PERFORMANCE OF THE……. to NSE. The Engle-Granger residual based cointegration test suggests that there is a long-run relationship between the stock market performance and economic growth. Similarly, the results of error correction model reveal that when the long-run equilibrium deviates then the economic growth adjusts to restore equilibrium by rectifying the disequilibrium. Chinwuba and Amos (2011), examined the impact of the Nigerian capital market performance on economic development of Nigeria and constructed two models. The dependent variables identified in models 1 and 2 were Gross Domestic Product and Gross Fixed Capital Formation respectively. The explanatory variables were Market capitalization, All Shares Index, Value of Transactions, Volume of Transactions and Number of listed companies for each of the models. The Ordinary Least Square (OLS) regression models were used for the analysis. The result indicates that Market Capitalization, All-Shares Index and number of listed companies were positively related to and capable of influencing Gross Domestic Product; while Volume of transactions and Market Capitalization were positively related to Gross Fixed Capital Formation. This shows that the performance of the capital market impacts positively on the development of the Nigerian economy. In addition, the study of Ohiomu and Godfrey (2011), reveals a positive relationship between economic growth and stock market development variables. Achugbu (2012), also believes that Stock Markets are expected to increase economic growth. Alajekwu and Achugbu (2012), also investigated the impact of stock market development on economic growth of Nigeria using a 15-year time series data (19942008). The stock market capitalization ratio was used as a proxy for market size while value traded ratio and turnover ratio were used as proxy for market liquidity. The results show that market capitalization and value traded ratios have very weak negative correlation with economic growth while turnover ratio has very strong positive correlation with it, implying that liquidity has propensity to spur economic growth in Nigeria and that market capitalization influences market liquidity. John and John (2012), examined the extent of causal link between stock market performance and economic growth in Nigeria. The study employed Time Series data on Gross Domestic Product (GDP) and key stock market performance indicators (1984 to 2011). The Ordinary Least Square (OLS) Technique was adopted. The results indicate that about 88% of the changes in economic growth could be attributed to changes in stock market performance in the short run, which shows that Market Capitalization (MKTCAP), Value of Transaction in the market (VALTRAN) and All share Index (ALLSVI) are significant predictors. The long run effect was shown to stand at 95% with MKTCAP and ALLSVI as having significant influences. The Error Correction Model coefficient of 0.39 suggested a slow speed in operators’ ability to adjust to shocks in stock market performance and in restoring investors’ confidence in such circumstances. The relationship between stock market performance and economic growth in Nigeria was examined by Okodua, Henry and Olabanji (2013). They utilized the bounds 4
RIJSER VOL. 8 NO. 3C SPECIAL EDITION OCTOBER 2015 testing co- integration (autoregressive distributed lag estimation) procedure and found out that in the long-run, overall output in the Nigerian economy is less sensitive to changes in stock market capitalization as well as the average dividend yield. Thus in its present level of development, the Nigerian stock market may not effectively serve as a measure or predictor of the overall health of the Nigerian economy as well as its direction in the long-run. The study also finds that the long-run growth of the Nigerian economy is highly sensitive to marginal variations in interest rate. This suggests that macroeconomic variables in the country are at present more useful in shaping the longrun direction of the Nigerian economy. The foregoing reviews however show little or no empirical attention to the nexus or interaction between our specific variables of study. This suggests an empirical gap which this study intends to fill. The finding would help the financial authorities to appreciate the impact of the stock market behavior on the performance of the aggregate economy. III.
STUDY METHODOLOGY Unit root tests were performed on the series in the vector-auto regression (VAR) model. If the series are stationary, then the results obtained from the VAR model are valid; if non-stationary, cointegration test is required to verify whether the series in the VAR model are cointegrated or not. The prominent cointegration test for VAR model is the Johansen Cointegration test. If the test indicates the existence of cointegration in the model, then the VAR model gives the long run causality similar to the long run relationship in a single-equation model. Similarly, the short run dynamics of the VAR model are captured with the Vector Error Correction Model which is similar to the short run adjustment. ∆Yt= Γ1 ∆Yt-1+ Γ2 ∆Yt-2+...+ Γp−1 ∆Yt-p+1+ ΩYt-1+ εt; t=1, ...,T (1) WhereΓi =− (I−Π1 − ... − Πi), ( i = 1,..., p − 1) and Ω = − (I−Π1 − ... − Πp) Ω = ϕβ1 Where ϕ represents the speed of adjustment to disequilibrium and β is a matrix of long-run coefficients. Therefore, the term β1 Yt-1 embedded in equation (1) is equivalent to the error correction term in a single-equation, except that β1 Yt-1 contains up to (n-1) vectors in a multivariate model. Long run and short run equilibrium can be determined from the vector error correction model (VECM). There is long run causality if ϕ is statistically significant and different from zero. The short run causality is determined following the VAR- Granger causality framework. For simplicity, we can specify the VECM models as follows: p=4
GDPRt=α1 + ∑ai i=1 p=4
GDPR
p=4 p=4 p=4 GDPR GDPR GDPR GDPRt-i +∑βj RINTt-j+∑γk lnTNDLt-k+∑γL lnTVNDLt-L + j=1
∑γMRGDPlnMACAPt-M + φ1ECM1t-1 + e1t
k=1
L=1
(2)
M=1
5
OGBOLE FRIDAY OGBOLE (PHD) AND SAMSON ADENIYI ALADEJARE THE NIGERIAN STOCK EXCHANGE: IT’S IMPACT ON THE PERFORMANCE OF THE……. RINTt=α1 +
p=4 ∑aiRINTRINTt-i i=1
p=4 p=4 p=4 RINT RINT +∑βj GDPRt-j+∑γk lnTNDLt-k+∑γLRINTlnTVNDLt-L + j=1
k=1
L=1
p=4
∑γMRINTlnMACAPt-M + φ2ECM2t-1 + e2t
(3)
M=1 p=4
lnTNDLt=α1 + ∑ai
TNDL
p=4 p=4 p=4 TNDL TNDL TNDL lnTNDLt-i +∑βj GDPRt-j+∑γk RINTt-k+∑γL lnTVNDLt-L +
i=1
j=1
k=1
L=1
p=4
∑γMTNDLlnMACAPt-M + φ3ECM3t-1 + e3t
(4)
M=1 p=4
p=4
p=4
p=4
lnTVNDLt=α1 + ∑aiTVNDL lnTVNDLt-i+∑βjTVNDLGDPRt-j+∑γkTVNDLRINTt-k+∑γLTVNDLlnTNDLt-L + i=1
j=1
k=1
L=1
p=4
∑γMTVNDLlnMACAPt-M + φ4ECM4t-1 + e4t
(5)
M=1 p=4
p=4
p=4
p=4
lnMACAPt=α1+∑aiMACAPlnMACAPt-i+∑βjMACAPGDPRt-j+∑γkMACAPRINTt-k+∑γLMACAPlnTNDLt-L + i=1
j=1
k=1
L=1
p=4
∑γMMACAPlnTVNDLt-M + φ5ECM5t-1 + e5t
(6)
M=1
Where: GDPR = Gross Domestic Product Rate RINT = Real Interest Rate TNDL = Total Number Deals TVNDL = Total Value of Number Deals MACAP = Market Capitalization α = Constant term φ = Speed or rate of adjustment p = lag length for the Unrestricted Error-Correction Model (UECM) e = white noise disturbance error term ln= Natural logarithm RESULT PRESENTATION AND ANALYSIS Stationarity Test
This study applied a more efficient univariate Dickey Fuller-GLS test for autoregressive unit root (Elliot, Rothenberg, and Stock 1996). The test regression included both a constant with no trend and a constant with trend for levels as well as
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RIJSER VOL. 8 NO. 3C for the first differences of the variables.
SPECIAL EDITION
OCTOBER 2015
Table 1: Dickey Fuller GLS Unit Root Test Applied to Variables Varia bles GDPR RINT TNDL TVND L MAC AP
LEVEL Constant Decisio n Rule 2.268858* I(0) * 4.816277* I(0) ** 1.510141 0.946955
Trend & Constant 4.041931* ** 5.373130* ** 3.480862* * 2.058716
0.359913
1.553097
Decisio n Rule I(0) I(0) I(0)
1ST DIFFRENCE Constant Decisio Trend & n Rule Constant 0.647355 6.705307* ** 7.977590* I(1) 5.363889 ** 2.261522* I(1) 2.070210 * 1.085577 3.731754* * 5.567929* I(1) 6.021890* ** **
Decision Rule I(1) I(1)
I(1) I(1)
Source: Computed by Authors Note: ***, **, * denote rejection of the Null hypothesis of a unit root at 1%, 5% and 10% respectively based on MacKinnon critical values. From table 1 results, not all the variables were found to be stationary at level. DF-GLS unit root tests results for the variables indicate that all variables are I(1). The Phillips-Perron( PP) unit root test result in table 2, serve as a verification test for the order of integration of the variables. It also confirms that all the variables are I(1). Thus, we can use Vector Error Correction Mechanism as a tool of analysis as adopted by this study. Table 2: Phillips-Perron Unit Root Test Applied to Variables LEVEL 1ST DIFFRENCE Varia Constan Decis Trend & Decisi Constan Decis Trend & bles t ion Constant on t ion Constan Rule Rule Rule t GDPR 5.06710 I(0) 5.441396 I(0) 10.2266 I(1) 10.1425 7*** *** 0*** 7*** RINT 4.76484 I(0) 5.183654 I(0) 17.8322 I(1) 20.1663 7*** *** 5 0 TNDL 1.46558 2.289592 5.63415 I(1) 5.52636 6 7*** 3*** TVND 1.30379 2.499349 7.43952 I(1) 9.84225 L 2 6*** 4*** MACA 1.60206 0.784299 5.50980 I(1) 9.85255 P 3 3*** 0*** Source: Computed by Authors
Decisio n Rule I(1) I(1) I(1) I(1) I(1)
Note: ***, **, * denote rejection of the Null hypothesis of a unit root at 1%, 5% and 10% respectively based on MacKinnon critical values. This section shows the unit root test result conducted on the variables. In the first step, 7
OGBOLE FRIDAY OGBOLE (PHD) AND SAMSON ADENIYI ALADEJARE THE NIGERIAN STOCK EXCHANGE: IT’S IMPACT ON THE PERFORMANCE OF THE……. the DF-GLS and the Phillips-Perron test were conducted at level respectively; with the variables found to be non-stationary. A further test for stationarity by first level of differencing shows the variables are stationary. Therefore, the null hypothesis of the presence of unit roots in the variables is rejected and we conclude that the variables included in the model are stationary at their 1st difference. 4.2 Cointegration Test Result Table 3: Unrestricted Cointegration Rank Test (Trace) Hypothesized Eigenvalue Trace Statistic 0.05 Critical Prob. Value No. of CE(s) Value None* 0.810144 91.99947 69.81889 0.0003** At most 1 0.478913 42.15484 47.85613 0.1544 At most 2 0.402196 22.59970 29.79707 0.2663 At most 3 0.210334 7.164954 15.49471 0.5586 At most 4 0.002683 0.080583 3.841466 0.7765 Source: Computed by Authors Trace test indicates 1 cointegrating equation at the 0.05 level of significance. *, Denotes rejection of the hypothesis at the 0.05 level of significance ** , represents Mackinnon-Haug-Michelis (1999), P-values. Table 4: Unrestricted Cointegration Rank Test (Maximum Eigenvalue) Hypothesized Eigenvalue Max-Eigen 0.05 Critical Prob. Value No. of CE(s) Statistic Value None* 0.810144 49.84463 33.87687 0.0003** At most 1 0.478913 19.55514 27.58434 0.3728 At most 2 0.402196 15.43475 21.13162 0.2596 At most 3 0.210334 7.084371 14.26460 0.4792 At most 4 0.002683 0.080583 3.841466 0.7765 Source: Computed by Authors Max- eigenvalue test indicates 1 cointegrating equation at the 0.05 level of significance. *, Denotes rejection of the hypothesis at the 0.05 level of significance ** , represents Mackinnon-Haug-Michelis (1999) P-values. The cointegration results from both the Trace test and Max- Eigenvalue indicate the presence of a single cointegrating equation between the variables. This means there exists a long run relationship between the variables.
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RIJSER VOL. 8 NO. 3C SPECIAL EDITION 4.3 The Vector Error Correction Model Test Result Table 5: Tabulated VEC results. T-Statistic in [ ]
OCTOBER 2015
dGDPR 0.328821 [ 1.67727]
dRINT 0.235028 [ 0.21875]
dlnTNDL 0.015493 [ 0.59351]
dlnTVNDL 0.018977 [ 0.63904]
dlnMACAP -0.025297 [-0.96256]
-0.187114 [-1.48923] -0.356082 [-4.99429]
-0.183985 [-0.26719] -0.082807 [-0.21192]
-0.008827 [-0.52760] -0.004293 [-0.45222]
-0.045313 [-2.38091] -0.014244 [-1.31897]
-0.019221 [-1.14116] 0.006707 [ 0.70169]
-0.114337 [-2.82068] -3.816876 [-1.65751]
-0.019642 [-0.08842] 20.24736 [ 1.60437]
-0.003018 [-0.55908] 0.005227 [ 0.01705]
-0.001041 [-0.16960] -0.670262 [-1.92156]
0.002150 [ 0.39569] -0.056511 [-0.18306]
dlnTVNDL(1)
-8.241324 [-3.41407] -3.944023 [-2.75160]
-3.838904 [-0.29018] -4.982003 -4.982003
-0.072094 [-0.22430] 0.097585 [ 0.51130]
0.175190 [ 0.47912] 0.086320 [ 0.39758]
0.093498 [ 0.28893] -0.051979 [-0.27051]
dlnTVNDL(2) dlnMACAP(1)
6.243972 [ 4.76273] 6.374642 [ 2.36909]
8.820669 [ 1.22768] -21.72738 [-1.47340]
0.176908 [ 1.01342] 0.507651 [ 1.41689]
0.184987 [ 0.93154] 1.468910 [ 3.60399]
-0.023206 [-0.13204] 0.172265 [ 0.47756]
dlnMACAP(2) C
7.825685 [ 2.41708] -1.660991 [-1.58618
3.007783 [ 0.16951] 1.953040 [ 0.34032]
-0.254829 [-0.59110] 0.032196 [ 0.23090]
0.042610 [ 0.08689] -0.094962 [-0.59869]
-0.341142 [-0.78598] 0.347742 [ 2.47714]
ECM (-1)
-0.665742 [-4.23221] 0.814044
1.718393 [ 1.99330] 0.689030
-0.020320 [-0.97015] 0.325488
-0.034969 [-1.46760] 0.684165
0.016498 [ 0.78235] 0.268087
0.479802 3.347783 1.161456 1.727233
-0.205503 0.566074 0.917181 1.482959
lnTVNDL(-1) 0.741402 [ 0.66806]
lnMACAP(-1) 2.455956 [ 2.57133]
dGDPR(-1) dGDPR(-2) dRINT(-1) dRINT(-2) dlnTNDL(-1) dlnTNDL(-2)
R-Squared Adj. RSquared 0.693719 0.487815 -0.110961 F-Statistic 6.765405 3.424336 0.745765 Akaike AIC 4.936143 8.338494 0.903641 Schwarz SC 5.501921 8.904272 1.469418 Long Run Cointegrating Equation Estimate on Eq 2. C RINT(-1) lnTNDL(-1) GDPR(-1) 18.22945 -0.655598 -3.614982 1.000000 [-6.12182] [-2.56641] Source: Computed by Authors
9
OGBOLE FRIDAY OGBOLE (PHD) AND SAMSON ADENIYI ALADEJARE THE NIGERIAN STOCK EXCHANGE: IT’S IMPACT ON THE PERFORMANCE OF THE……. The VECM result above shows that short run as well as long run relationship exist between the variables. The output for equation 2 is most significant (2nd column of table 5) based on the corresponding T values for each model. As a rule of thumb, the absolute value of 1.96 was used as minimum significant value for the T-Statistic. Thus, the short run values for equation 2 were analyzed. Similarly, the relationship represented by equation 2 has the only long run relationship or cointegration (see table 5) as confirmed by the single cointegrating relationship in table 3 and 4 respectively. Although the T-Statistic for this relationship is not significant, the short run relationship between lagged GDPR and current GDPR as shown in table 5, indicate a positive relationship between GDPR lagged by one period and current GDPR level. This shows that previous change in GDPR (lagged by one period) of 1% influences current economic performance by 0.33%. This means immediate previous year growth recorded in the performance of the economy has a tendency to positively impact on current economic performance. This could be due to continuity and completions of developmental projects and policies being carried forward from the immediate previous period into the current period. However, lagged GDPR by two periods indicate a non significant negative relationship with current GDPR levels. This means a 1% change in two period lagged GDPR level has an inverse effect of 18% on current economic performance. This reversed result from the one period lagged value of economic performance with current performance level can be related to the short fiscal nature of government budget planning. Government budgets in Nigeria have always been an annual event, with each year’s budget meant to address different government objectives without allowing for long term planning and gains of previous budget to adequately stimulate future economic performances. The short run relationship between RINT and GDPR shows a significant negative relationship. The lagged by one period value of RINT with GDPR indicate that a 1% rise in RINT would yield 0.36% fall in GDPR. Similarly, a 1% rise in lagged by two periods value of RINT would yield 0.11% fall in GDPR. This shows that when the price of capital rises, investors would not be willing to borrow at the new high rate resulting in a fall in the growth performance of the economy because output of the private sector is very crucial to the growth process of the economy. The relationship between the lagged by one value of TNDL show an inverse effect with current level of GDPR. The result indicates that a rise of 1% in lagged by one value of TNDL would lead to 3.82% fall in current level of GDPR. Similarly, the lagged by two value of TNDL also show an inverse relationship with current level of GDPR. A 1% rise in lagged by two TNDL would yield an 8.24% fall in current GDPR level. This shows that the total number of deals in the stock exchange market did not positively impact on the performance of the economy. Furthermore, TVNDL lagged by one shows a negative impact on current level of GDPR. The result shows that a 1% increase in the previous volume of total number of 10
RIJSER VOL. 8 NO. 3C SPECIAL EDITION OCTOBER 2015 deals would yield a fall of 3.94% in current level of economic performance. However, a 1% rise in TVNDL lagged by two periods would cause a rise of 6.24% in current economic performance. This shows that the impact of total value of the number of deals on the performance of the economy is more of a long run phenomenon rather than a short run case. MACAP lagged by one and two periods influence GDPR positively. The result shows that a 1% rise in immediate previous year total value of market capitalization yields about 6.37% increase in current economic performance. Likewise a 1% increase in the lagged by two periods value of MACAP improves current economic performance by 7.83%. This means that the value of the market capitalization of the stock exchange has a significant positive impact on the general performance of the economy. The ECM result for equation 2 happens to be the only one which is rightly signed and as well significant as indicated from its T-statistic. The ECM result shows the rate at which the system corrects itself back to equilibrium if there is any distortion in the system. In order words, it shows how much of the distortion or shock from the previous period is being corrected in the present period. The ECM for equation 2 is -0.67.This means that in the case of disequilibrium or distortion from the previous period, 67% of this distortion or shock would be corrected in the present period or annually. This process would continue until equilibrium is restored. Thus, the ECM value therefore indicates that it would take the economy a year and five month for equilibrium to be restored if there is distortion in the system. The estimated long run relationship for equation 2 on table 5 shows that RINT and TNDL both impact negatively on economic performance as in the short run. The results show that a 0.65% fall in RINT would yield a 1% rise in GDPR in the long run and a 3.6% fall in TNDL would induce a 1% rise in GDPR. The reason for this behavior is the same with the reasons given above in their short run inverse relationship. However, TVNDL and MACAP both show a positive long run impact on economic performance. Also, a 0.74% increase in TVNDL would induce a 1% rise in GDPR. Likewise a 2.4% increase in MACAP would yield a 1% rise in GDPR. These behaviors are also not different from their short run relationships. Causality Test Result. Table 6: VEC Granger Causality/Block Exogeneity Wald Test Dependent Variable: d(GDPR) Regressors Chi-sq df dRINT 25.67030 2 dlogTNDL 12.94468 2 dlogTVNDL 26.63208 2 dlogMACAP 8.091144 2 All 39.38701 8
P.value 0.0000 0.0015 0.0000 0.0175 0.0000
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OGBOLE FRIDAY OGBOLE (PHD) AND SAMSON ADENIYI ALADEJARE THE NIGERIAN STOCK EXCHANGE: IT’S IMPACT ON THE PERFORMANCE OF THE……. Dependent Variable: d(RINT) Regressors Chi-sq df P.value dGDPR 0.275242 2 0.8714 dlogTNDL 2.875450 2 0.2375 dlogTVNDL 1.697373 2 0.4280 dlogMACAP 2.911000 2 0.2333 All 11.15535 8 0.1931 Dependent Variable: dlogTNDL Regressors Chi-sq dGDPR 1.462399 dRINT 0.321171 dlogTVNDL 1.502383 dlogMACAP 3.692464 All 6.928602 Dependent Variable: dlogTVNDL Regressors Chi-sq dGDPR 11.56761 dRINT 2.777340 dlogTNDL 4.317795 dlogMACAP 15.39989 All 33.88668 Dependent Variable: dlogMACAP Regressors Chi-sq dGDPR 1.446649 dRINT 0.506928 dlogTNDL 0.136987 dlogTVNDL 0.105406 All 4.369514 Source: Computed by Authors
df 2 2 2 2 8
P.value 0.4813 0.8516 0.4718 0.1578 0.5444
df 2 2 2 2 8
P.value 0.0031 0.2494 0.1155 0.0005 0.0000
df 2 2 2 2 8
P.value 0.4851 0.7761 0.9338 0.9487 0.8223
The VEC granger causality result in table 6 shows the direction of causality between the variables. The significance of the result is judged based on the corresponding probability values; either when the variables causality were observed individually or jointly. The first section of the table shows that RINT, TNDL, TVNDL and MACAP all cause growth of economic performance individually as well as jointly. The probability values show the significance of the causation at 5% level of significance. Thus, we can say that improvement in the performance of the economy relies more on the improvement in the stock exchange variables used in this study as well as on the level of real interest rate. This is either when the variables are being observed independently or jointly. 12
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VOL. 8 NO. 3C SPECIAL EDITION OCTOBER 2015 However, the result shows that the causality running from the regressors to the dependent variables (RINT, TNDL and MACAP) in the other sections of the table were not significant. The result when TVNDL was made dependent variable shows that RINT and TNDL do not affect TVNDL individually. Put differently, real interest rate and the total number of deals do not impact individually on total value of the number of deals. On the contrary GDPR and MACAP have a positive and significant impact on TVNDL. Also when the causation of the explanatory variables was observed jointly on TVNDL, the result shows a significant level of causation. Impulse Response Analysis The impulse response function is a shock to a VAR system. It identifies the responsiveness of the dependent (endogenous variable) in the VAR when a shock is put to the error term. We can alternatively say the impulse response function, measures how other variables in the model respond when one standard deviation positive shock is being put into a variable. In this study, the behavior of the variables was being examined when a shock is being applied to the system within a ten year period. The first box summarizes the response of GDPR to shocks in the regressors for a ten year period. It can be observed that economic performance would respond positively to any shock on economic performance, real interest rate and market capitalization within a ten year period. However, when a shock occurs in total value of deals, economic performance responds negatively for two and a half years before responding positively to this shock for remaining period. The same scenario can also be observed when a shock occurs in total number of deals. In this case, the economy responds negatively up to a five year period before later responding positively to the shock for the next five year period. The second box gives a picture of the behavior of RINT when a shock is being applied to the regressors within a ten year period. We can also observe that real interest rate responds positively only to shock in economic performance, throughout the ten year period. Its response to shocks in total number of deals, market capitalization and real interest rate fluctuated from negative to positive at different intervals as could be observed in the box. For instance, when a shock was applied to market capitalization and total value of deals real interest rate responded almost entirely in like manner to shocks in both variables. This is observed by turning out negatively for the first two and half years before responding positively for the remaining years. The third box shows the response of TNDL to shocks in the regressors also within a ten year period. Unlike the first two analyzed boxes total number of deals tends to respond positively almost entirely throughout the period to shocks in economic performance, total number of deals, market capitalization, real interest rate and total value of deals. In fact, the response of TNDL to a shock in TNDL happens to be very positively high when compared to response to shocks in other variables. The fourth box represents the response of TVNDL to shocks in the regressors within a ten year period. The result shows that total value of the number of deals respond positively to shocks in total number of deals, market capitalization and total value of the number of deals within a ten year period. However, the response to shocks in economic performance and real interest were negative. The fifth box represents the 13
OGBOLE FRIDAY OGBOLE (PHD) AND SAMSON ADENIYI ALADEJARE THE NIGERIAN STOCK EXCHANGE: IT’S IMPACT ON THE PERFORMANCE OF THE……. response of MACAP to shocks in the regressors within a ten year period. Shocks to economic performance and real interest rate generated an inverse reaction from market capitalization, the reaction from shocks to real interest rate being the most obvious. On the contrary, the response of market capitalization to shocks in total number of deals, market capitalization and total value of the number of deals all turn out to be positive. Residual Diagnostic Test Table 7: VEC Residual Normality Tests. Null Hypothesis: residuals are multivariate normal Component 1 2 3 4 5 Joint
Jarque-Bera 0.261345 1.389327 0.487105 0.771076 0.200544 3.109397
df 2 2 2 2 2 10
Prob. 0.8775 0.4992 0.7838 0.6801 0.9046 0.9787
Source: Computed by Authors The Jarque-Bera normality test in table 7 above shows the summary of the residual test conducted on the residuals. The result shows that the residuals of the various models used in this study are normally distributed. This is judging from the probability values, of which all are greater than the 0.05 or 5% level of significance. Thus, the null hypothesis of residuals are multivariate normal cannot be rejected. Table 8: VEC Residual Serial Correlation LM Tests. Null Hypothesis: no serial correlation at lag order h Lags
LM-Stat
Prob
1 2 3 4 5 6 7 8 9 10 11 12
14.90686 17.07382 17.54273 19.17167 25.31049 18.21758 27.51478 25.27889 30.50445 17.71484 23.10352 23.58452
0.9435 0.8791 0.8612 0.7888 0.4451 0.8330 0.3307 0.4468 0.2060 0.8543 0.5715 0.5435
Probs from chi-square with 25 df. Source: Computed by Authors 14
RIJSER VOL. 8 NO. 3C SPECIAL EDITION OCTOBER 2015 Table 8 gives the result of the serial correlation test conducted on the residuals. None of the probability values is significant at the 0.05 level of significance. Thus, the null hypothesis of no serial correlation at lag order h cannot also be rejected. This means the residuals of the study are free from serial or auto correlation. Table 9: VEC Residual Heteroskedasticity Test Null Hypothesis: residuals are homoskedastic Joint test: Chi-sq
Df
Prob.
343.9328
330
0.2875
Source: Computed by Authors Table 9 is a final representation of the heteroskedasticity test conducted on the residuals of the study. The accompanying probability value also shows none significance at the 0.05 level of significance. Thus, the null hypothesis of residuals being homoskedastic cannot be rejected. IV. • •
•
Conclusions and Recommendations From the study we can conclude as follows: The performance of the economy is influenced by the level of real interest rate, total number of deals, total value of the deals and the market capitalization. Change in real interest rate inversely affects economic performance both in the short run and long run. That is, a rise in the level of interest rate would discourage investors from borrowing to invest thereby causing a fall in economic performance since the performance of the economy is also a function of the volume of the number of investment in the economy. The volume of total number of deals impact inversely on the performance of the economy in both the short and long run.
•
The total value of the deals has an inverse relationship with economic performance in the short run. However, the long run result shows a positive relationship with economic performance, which invariably means the impact of the value of all deals in the stock exchange starts from an inverse relationship in the short run to a positive one in the long run.
•
The market capitalization for the stock exchange has a positive significant impact on the performance of the economy in both the short run and long run. This behavior confirms findings by John and John (2012), that the market capitalization has a positive impact on the performance of the economy.
•
The error correction mechanism shows that shocks to the explanatory variables (RINT, TNDL, TVNDL and MACAP) either individually or jointly, have a significant impact on the performance of the economy. It would take the economy about a year and five months for equilibrium to be restored back into the system. 15
OGBOLE FRIDAY OGBOLE (PHD) AND SAMSON ADENIYI ALADEJARE THE NIGERIAN STOCK EXCHANGE: IT’S IMPACT ON THE PERFORMANCE OF THE……. • The causality test shows the direction of causality to flow from RINT, TNDL, TVNDL and MACAP to GDPR, that is, a uni-directional causality from the regressors to the dependent variables. The impact on the performance of the economy is as a result of the changes in these variables. •
The study suggests some policy issues and recommendations as follows: Stock market regulators should ensure an enabling macroeconomic environment for the stock market operation to realize its full potentials and boosting the confidence of investors
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Market capitalization should be increased by encouraging more companies to be listed on the floor of the Exchange by modifying listing requirements without sacrificing investors’ interests. The determination of stock prices should also be deregulated.
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Encouraging investment in the stock market through appropriate monetary and financial policies to mobilize savings for investment. Small and medium scale enterprises should be encouraged through various tax incentives and reduced listing requirements to enter the market. Such policies have been used in other countries with positive results. The government should educate the populace on the need to be abreast with the activities of the market.
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Provision of infrastructural facilities (electricity, etc) as well as investment security by the government. Internationalization of the stock market and allowing for the listing of foreign currency denominated securities.
•
References Alajekwu, U. B., & Achugbu, A. A. (2012). The Role of Stock Market Development on Economic Growth in Nigeria: A Time Series Analysis. African Research Review. Pp. 51-70 Alile, H. I. (1984). The Nigerian Stock Exchange: Historical Perspective, Operations and Contributions to Economic Development. Central Bank of Nigeria Bullion, Silver Jubilee edition vol. II pp. 65-69. Alile, H. (1997). Government Must Divest. The Business Concord of Nigeria 2nd December, p. 8. Caporale,G. M., Howells, P. G. and Soliman, A. M. (2004). Stock Market Development and Economic Growth: The Causal Linkages, Journal of Economic Development 29(1):33-50. Chinwuba, O., & Amos, O. A. (2011). Stimulating Economic Development through the Capital Market: The Nigerian Experience. Jorind 9(2) 16
RIJSER VOL. 8 NO. 3C SPECIAL EDITION OCTOBER 2015 Dailami M. and Atkin, M., (1990). Stock Markets in Developing Countries: Key Issues and a Research Agenda Policy, Research, and External Affairs Working Papers No. WPS 515, Country Economics Department, The World Bank Group. Demirguc-Kunt, A. & Levine, R. (1996). Stock Markets, Corporate Finance and Economic Growth: Overview; World Bank Economic Review 10(2). Demirguc-Kunt, A. & Maksimovic, V. (1996). Stock Market Development and Finance Choices of Firms The World Economic Review 10 ( 2) 341 – 369. John U. I. & John C. O. (2012). Stock Market Performance and Economic Growth in Nigeria(1984-2011). Journal of Emerging Trends in Economics and Management Sciences. Pp 971-977. Levine, R. and Sara Z. (1996). “Stock Market Development and Long-run Economic Growth” The World Bank Review 10(2). Nieuwerburgh, S. V., Buelens, F & Cuyvers, L. (2005). Stock Market Development and Economic Growth in Belgium; New York: Stern School of Business Nyong, M. O. (1997). Capital Market Development and Long-run Economic Growth: Theory, Evidence and Analysis First Bank Review, December pp 13-38. Obadan, M. I. (1998). Presidential Address presented on the “ Capital Market and Nigeria’s Economic Development” at one day seminar organized by Nigeria Economic Society at the Institute of International Affairs, Lagos 21st January . Ohiomu, S., & Godfrey, O. E. (2011). The Effect of Stock Market on Economic Growth In Nigeria. JORIND (9)1 Okereke-Onyiuke N. (2000). Stock Market Financing Options for Public Projects in Nigeria. The Nigerian Stock Exchange Fact book 2000. Okodua H. & Ewatan .O. O. (2013). Stock Market Performance and Sustainable Economic Growth in Nigeria: a bound testing co-integration approach. Journal of Sustainable Development. 6(8). Onosode, G. O. (1998). “The Capital Market and Nigeria’s Economic Development” at one day seminar organized by Nigeria Economic Society at the Institute of International Affairs, Lagos 21st January . Osinubi, T, S. (2001). Does Stock market Promote Economic Growth in Nigeria? https://uwivet.edu/.../Does%20the%20Stock%20Market%20promote% 20Economi c%20 Growth.pp.33-50. Samuel, C. (1996). “Stock Market and Investment: The Governance Role of the Market The World Bank Review 10( 2) 17
OGBOLE FRIDAY OGBOLE (PHD) AND SAMSON ADENIYI ALADEJARE THE NIGERIAN STOCK EXCHANGE: IT’S IMPACT ON THE PERFORMANCE OF THE……. Soumya, G. D., & Jaydeep, M. (2008). Does Stock Market Development Cause Economic Growth? A Time Series Analysis for Indian Economy. International Research Journal of Finance and Economics Sudharshan, R. P. & Rakesh, G (2011). An Empirical Analysis of Stock Market Performance and Economic Growth: Evidence from India. International Research Journal of Finance and Economics Vazakidis, A. and Adamopoulos, A., (2009). Stock Market Development and Economic Growth American Journal of Applied Science 6 (11)1933-1941.
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