AHAM NZENWATA
ABSTRACT
This paper
empirically investigates the impact of equity stock traded in the Nigerian
Stock Exchange on the economy. One of the objectives of the study was to
examine the extent and direction of the relationship between gross domestic
product and stock market variables including All Share Index, Market
Capitalisation and Value of transactions. Annual time series data on the
Nigerian economy spanning 1988 to 2010 was collected and analysed using
Ordinary Least Squares regression technique. The results of the analysis
revealed that stock market activities are positively related to economic
growth. In view of the findings, it was recommended that incentives should be
provided that will encourage more companies to get quoted. It was also
recommended that transparency in NSE should be ensured in order to boost
confidence and attract more investors both domestic and foreign.
1.
INTRODUCTION
Considerable
amount of empirical studies have been carried out on the importance and role of
the stock market in the process of mobilising saving for economic growth and
development (see for example Demirguc-Kunt and Levine, 1996; Greenwood and
Smith 1996; Rouseau and Wachtel, 2000). For
instance, Rouseau and Wachtel (2000) in Riman et al (2008) advanced four
reasons for the importance of stock market on financial institutions. According
to them, venture capital investments will be more attractive in countries where
an equity market exists than one without an adequately functioning public
equity market. Secondly, a well functioning stock market encourages capital
inflows – both foreign direct investment and portfolio investments. Thirdly,
the provision of liquidity through organized exchanges encourages both
international and domestic investors to transfer their surpluses from short term
assets to the long-term capital market, where the funds can provide access to
permanent capital for firms to finance large, indivisible projects that enjoy
substantive scale economies. Finally, the existence of a stock market provides
important information that improves the efficiency of financial intermediation
generally.
But, the
mobilization of savings through the mechanism of the stock market for capital
formation needed for economic growth is only one side of the coin. Notable authors
and researchers have also given reasons why the stock market mechanism can act
as a disincentive for long term capital formation. Stiglitz (1985) and Demirguc-Kunt
and Levine (1996) argued that stock markets had the tendency to discourage
savings due to the uncertainty inherent in returns to investment and secondly,
stock market liquidity encourages investor’s myopia, adversely affecting
corporate governance, thereby reducing the cross benefit from economic growth.
The
Nigerian experience is a good example of both the positive and negative effects
that the stock market can have on economic activities. For example, (Edo, 1995;
Osinubi, 1998; Alile, 1996 and Soyode, 1990) have documented the gains made by
the Nigerian economy due to the activities in the stock market. But as recent
experience has also shown (the global financial crises), wealth created through
investments in the stock market can also be destroyed through the activities of
some elements of the market. Such failures of the market can act as a
disincentive/deterrence to long term investment through the stock market.
The one
feature of empirical studies on the stock market from which we in intend to
depart in this paper is the aggregation of all trading activities in the stock market.
In a typical stock exchange, instruments traded will include bonds and
debentures, equities and preference shares and funds. Equities or ordinary shares are the most important security traded on the
Nigerian stock market. Our aim in this paper therefore is determine the extent
and direction of the relationship between equities trading in the stock market
and economic growth.
2.
LITERATURE REVIEW
As
stated earlier in this paper, quite a large number of empirical research has
been devoted to the study of the relationship that exist between the stock
market and by extension the capital market and economic growth. Among the
numerous studies include the following: Stiglitz (1985), Benchivenga and Smith,
(1991), Atje and Jovanic (1993), Demirguc-Kunt and Levine (1996), Greenwood and
Smith (1996), Levine and Zervos, (1996), Bencivenga et al and (1996) Rousseau
and Wachtel (2000).
In
support of their argument in favour of the stock market as a driver of economic
growth Bencivenga et al (1996) and Levine (1991) argued that market liquidity,
the ability to trade equity easily play a key role in economic growth. They
agreed that stock markets provide assets to savers who would easily and readily
liquidate them whenever they desire, while simultaneously allowing firms
permanent access to capital raised through equity issue. Levine and Zervos
(1996) examined whether there is a significant empirical relationship between
stock market development and long-run economic growth. The study used pooled
cross-country time-series regression of forty-one countries from 1976 to 1993. The
finding was that a strong positive correlation between overall stock market
development and long-run economic growth exist. But the liquidity that is
created through the process of trading in equity kept in constant check through
regulation in order to deter asset bubbles building up through the activities
of speculators. If not regulated, such asset bubbles are likely to lead to
stock market collapse as happened in 2007/2008.
But
Nyong (1997) in a similar study but this time utilising data from only Nigeria
developed an aggregate index of capital market development and used it to
determine its relationship with long-run economic growth in Nigeria. The study
employed a time series data from 1970 to 1994. For measures of capital market
development 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
were used. The four measures were combined into one overall composite index of
capital market development using principal component analysis. A measure of
financial market depth (which is the ratio of broad money to stock of money to
GDP) was also included as control. The result of the study was that capital
market development is negatively and significantly correlated with long-run
growth in Nigeria.
From the
above, we can see that the debate concerning the contribution or relationship
between the stock market development and economic growth is far from being
settled. While Bencivenga et al (1996), Levine (1991) and Levine and Zervos
(1996) are of the opinion that the stock market development is positively
correlated with economic growth, Stiglitz (1985) and Demirguc-Kunt and Levine
(1996) doubt if such correlation really exists, Nyong (1997) asserts that the
relationship is negative (in the case of Nigeria). This paper intends to add
its voice to the debate -at least in the case of Nigeria- by
using data and methods that will be explained in the next section to hopefully
draw reliable conclusions about the relationship between the stock market
(equities only) and economic growth.
3.
METHODOLOGY
Analytical
Techniques and Estimation Methods
The study adopted a simple econometric model
patterned after the multiple regression model. Accordingly a single economic
growth model is specified to determine the nature of relationship between Gross
Domestic Product (GDP) and such explanatory variable as Market Capitalization
(MKTCAP), Value of Transaction (VTRAN) and the All Share Index (INDEX). The
model was estimated using the Ordinary Least Squares (OLS) technique.
The Model
The underlying hypothesis of this study is that a
significant relationship exists between the economic growth variable (GDP) and
stock market variables- MKTCAP, VTRAN and INDEX. Thus, we can theorize that
economic growth is a function of stock market capitalization and the value of
transaction of the Nigeria stock exchange. The model used in the study is:
G D P = f (MKTCAP, VTRAN, INDEX) and can be
specified as follows:
GDP = α + α 1MKTCAP + α2VTRAN + α3INDEX + ei
Where GDP = Gross Domestic Product
MKTCAP
=Market Capitalization
α =
coefficient of the constant term
α 1, α2, α3 , = coefficients of the
predictors and
ei =the
error term
Our a priori expectation is that α 1, α2, α3 >
0
4.0 RESULTS AND DISCUSSION
Table 1 below show the result obtained from the
analysis of the data. The analysis was done using Statistical Package for
Social Sciences (SPSS). The results are discussed under the subheadings - Global
Analysis of Utility of the Models and Relative Analysis of Predictors.
Table 1.
Regression Results
|
Variables
|
Coefficient
|
Std. Error
|
t-Statistic
|
Prob.
|
|
(Constant)
MKTCAP
VTRAN
INDEX
|
2481536.820
1604.160
3.513
67.372
|
1210718.902
780.259
5.182
131.678
|
2.050
2.056
.678
.512
|
.054
.054
.506
.615
|
|
R
R Square
Adj. R Square
S E of Estimate
|
.915a
.838
.812
4.02098E6
|
|
Durbin-Watson
F- Stat (Prob.)
|
1.284
32.667 (.000)
|
4.1 Global Analysis of Utility of the Models
The
global utility of the model analysis tests for the overall fitness or
appropriateness of the model in explaining the phenomena under study. Thus, the
R Square and Adjusted R Square gave .838 and .812 respectively. The value of
the R Square indicates that about 83.8% of the variations in the economic
growth proxy (GDP) can be attributed to variations in the independent variables
i.e. MKTCAP, VTRAN, INDEX, while the remaining 16.2% is attributed other
variables not included in this study. The F-Statistic gave a value of 32.667
with a corresponding Prob. of .000. The above results indicate that the model
is a good fit for the data.
4.2 Relative Analysis of Predictors
The analysis
of predictors investigates the individual contributions or relationships between
economic growth variable (GDP) and the stock market variables of market
capitalization (MKTCAP), Total Value of Transactions (VTRAN) and All Share
Index of the Exchange (INDEX). It also tests for the direction and magnitude of
such relationships. From the results in table 1 above, we can see that all
three independent variables are positively related to GDP. This is in line with
our a priori expectation that α 1, α2, α3 >
0. Thus, the values of the coefficients of the independent variables MKTCAP,
VTRAN and INDEX are 1604.160, 3.513, and 67.372 respectively. This indicate
that for every one unit change in any of the independent variables, GDP is
predicted to change by 1604.160, 3.513, and 67.372 respectively in the same
direction.
But all
three independent variables were individually statistically insignificant in
their relationship with Gross Domestic Product 5% level, but quite significant
at the 10% level. The implications here is that each independent variable taken
as an individual does not significantly contribute to economic growth but taken
as a unit, they are statistically significant as shown by the global
statistics.
5. CONCLUSION AND POLICY RECOMMENDATIONS
From the
analysis of results above, we can draw the following conclusions: first the
results of the global statistics showed that the model was a good fit for the
data. The global statistics also indicated that taken as a unit, the
independent variables statistically significant in predicting changes in
economic growth. Secondly, the results also satisfied our a priori expectation
that the independent variables are positively related to gross domestic growth.
This has the implication that any additional increase in the independent
variables will lead to increase/growth in the economy. This is in line with
findings of Levine and Zervos (1996) of a strong positive relationship between
stock market activities and economic growth.
On the
basis of the above findings, we make the following recommendations.
i.
That government should provide incentives that will encourage
companies to get quoted on The Exchange
or conversely disincentives (penalties) for companies that are eligible to be
quoted but who are reluctant to do so
ii.
Policies that will encourage investors (both domestic and foreign) to actively
participate in the stock market in order to increase activities and boost
liquidity. This could take the following forms.
·
Further reduction in transaction costs
·
Reduction of taxes on dividends and capital gains
·
Boost the confidence of participants by ensuring transparency.
REFERENCES
Alile, Hayford (1996): “Dismantling
Barrier of Foreign Capital Inflows” The Business Times of Nigeria 14th April,
page 5.
Atje, R. and Jovanovic, B., 1993.
“Stock Markets and Development” European Economic Review. 37: pp632-640.
Benchivena, V. R and Smith, B. D.,
1991. “Financial Intermediaries and Endogenous Growth” The Review of Economic
Studies, 50, pp195-209
Bencivenga, V, Smith, B and Starr R.,
1996. “Equity Markets, Transaction Cost and Capital Accumulation: An
illustration” World Bank Review. 10, (2): pp 241-265
Central Bank of Nigeria, Statistical
Bulletin, 2010 Edition
Dailami, M and Atkin, M., 1990.”Stock
Markets in Developing Countries: Key issues and a research agenda” Policy
Research and External Affairs working Papers, the World Bank
Dermiguc-Kunt, A and Levine, R.,
1995. “Stock Market, Corporate Finance and Economic Growth; an overview” World
Bank Working Paper (1): 389
Dermirguc-Kunt, A and Levine, R.,
1996. “Stock Market Development and Financial Intermediaries, Stylized Facts”
The World Bank Economic Review. 10(20): pp 291-321.
Edo, Samson E, (1995): “An Estimation
of a Model of Long-term Securities Investment in Nigeria” Nigerian Economic and
Financial Review (N. E. F. R.) December 1995 Vol. 1 2: 45-53
Greenwood, J and Smith B., 1996.
“Financial Markets in Development and the Development of Financial markets”
Journal of Economic Dynamics and Control. 21: pp145-181.
Levine, R., 1991. “Stock Markets,
Growth and Tax Policy” Journal of Finance. XLVI: 1445-1465.
Levine, R and Zervos, S., 1996.
“Stock market development and long-run growth” World Bank Economic Review
10(2): 323-339.
Levine, R and Zervos, S., 1996.
“Stock Market Development and Long-run Growth” The World Bank economic Review.
88: pp323-339.
Nyong, Michael O. (1997): “Capital
Market Development and Long-run Economic Growth: Theory, Evidence and Analysis”
First Bank Review, December 1997: 13-38.
Osinubi, Tokunbo S. (1998): Stock
Market Development and Long-run Growth in Nigeria”. Unpublished M.Sc. Economics
Dissertation, University of Ibadan Nigeria.
Riman, H. B., Esso I. E. and Eyo, E.,(2008) Stock Market
Performance and Economic Growth in Nigeria; A Causality Investigation, Global
Journal of Social Sciences Vol. 7, No. 2, 2008: -85-91
Rousseau, P. L and Wachtel, P., 2000.
“Equity Markets and Growth; Cross Country Evidence on timing and outcomes,
1980-1995” Journal of Banking and Finance, 24, 1933-1957.
Soyode, A. (1990): ‘The Role of
Capital in Economic Development” Security Market Journal Nigeria Vol.6.
Stiglitz, J. E., 1985. “Credit
Markets and the Control of Capital” Journal of Money, Credit and Banking, 71,
324-376.
APPENDIX
TABLE
1.
|
PERIOD
|
GROSS DOMESTIC PRODUCT
|
MARKET CAPITALIZATION
|
VALUE OF TRANSACTION
|
ALL SHARE INDEX
|
|
1988
|
139085.30
|
10.00
|
624.80
|
233.6
|
|
1989
|
216797.54
|
12.80
|
27.90
|
325.3
|
|
1990
|
267549.99
|
16.30
|
66.90
|
513.8
|
|
1991
|
312139.74
|
23.10
|
143.40
|
783
|
|
1992
|
532613.83
|
31.20
|
400.00
|
1107.6
|
|
1993
|
683869.79
|
47.50
|
456.20
|
1543.8
|
|
1994
|
899863.22
|
66.30
|
793.60
|
2205
|
|
1995
|
1933211.55
|
180.40
|
1788.00
|
5092.2
|
|
1996
|
2702719.13
|
285.80
|
6916.80
|
6992.1
|
|
1997
|
2801972.58
|
281.90
|
10222.60
|
6440.5
|
|
1998
|
2708430.86
|
262.60
|
13555.30
|
5672.7
|
|
1999
|
3194014.97
|
300.00
|
14071.20
|
5266.4
|
|
2000
|
4582127.29
|
472.30
|
28145.00
|
8111
|
|
2001
|
4725086.00
|
662.50
|
57648.20
|
10963.1
|
|
2002
|
6912381.25
|
764.90
|
59404.10
|
12137.7
|
|
2003
|
8487031.57
|
1359.30
|
113882.50
|
20128.9
|
|
2004
|
11411066.91
|
2112.50
|
223772.50
|
23844.5
|
|
2005
|
14572239.12
|
2900.10
|
254683.10
|
24085.8
|
|
2006
|
18564594.73
|
5121.00
|
468588.40
|
33189.3
|
|
2007
|
20657317.66
|
13294.60
|
1074883.90
|
57990.2
|
|
2008
|
24296329.29
|
9562.99
|
1675613.80
|
31450.78
|
|
2009
|
24794238.66
|
7030.77
|
685304.40
|
20827.17
|
|
2010
|
29205782.96
|
9918.20
|
799896.80
|
24770.52
|
Source: CBN Statistical Bulletin, 2011
Edition
Regression
|
Descriptive Statistics
|
|||
|
|
Mean
|
Std. Deviation
|
N
|
|
GDP
|
8.0261E6
|
9.27291E6
|
23
|
|
MKTCAP
|
2.3790E3
|
3863.47416
|
23
|
|
VTRAN
|
2.3873E5
|
4.32610E5
|
23
|
|
INDEX
|
1.3203E4
|
14403.72269
|
23
|
|
Variables Entered/Removedb
|
|||
|
Model
|
Variables Entered
|
Variables Removed
|
Method
|
|
1
|
INDEX, VTRAN, MKTCAPa
|
.
|
Enter
|
|
a. All
requested variables entered.
|
|
||
|
b.
Dependent Variable: GDP
|
|
||
|
Model Summaryb
|
|||||
|
Model
|
R
|
R Square
|
Adjusted R Square
|
Std. Error of the Estimate
|
Durbin-Watson
|
|
1
|
.915a
|
.838
|
.812
|
4.02098E6
|
1.284
|
|
a.
Predictors: (Constant), INDEX, VTRAN, MKTCAP
|
|
||||
|
b.
Dependent Variable: GDP
|
|
|
|||
|
ANOVAb
|
||||||
|
Model
|
Sum of Squares
|
Df
|
Mean Square
|
F
|
Sig.
|
|
|
1
|
Regression
|
1.585E15
|
3
|
5.282E14
|
32.667
|
.000a
|
|
Residual
|
3.072E14
|
19
|
1.617E13
|
|
|
|
|
Total
|
1.892E15
|
22
|
|
|
|
|
|
a.
Predictors: (Constant), INDEX, VTRAN, MKTCAP
|
|
|
||||
|
b.
Dependent Variable: GDP
|
|
|
|
| ||
|
Coefficientsa
|
||||||||
|
Model
|
Unstandardized Coefficients
|
Standardized Coefficients
|
t
|
Sig.
|
Collinearity Statistics
|
|||
|
B
|
Std. Error
|
Beta
|
Tolerance
|
VIF
|
||||
|
1
|
(Constant)
|
2481536.820
|
1210718.902
|
|
2.050
|
.054
|
|
|
|
MKTCAP
|
1604.160
|
780.259
|
.668
|
2.056
|
.054
|
.081
|
12.365
|
|
|
VTRAN
|
3.513
|
5.182
|
.164
|
.678
|
.506
|
.146
|
6.838
|
|
|
INDEX
|
67.372
|
131.678
|
.105
|
.512
|
.615
|
.204
|
4.895
|
|
|
a.
Dependent Variable: GDP
|
|
|
|
|
|
|
||
|
Collinearity Diagnosticsa
|
|||||||
|
Model
|
Dimension
|
Eigenvalue
|
Condition Index
|
Variance Proportions
|
|||
|
(Constant)
|
MKTCAP
|
VTRAN
|
INDEX
|
||||
|
1
|
1
|
3.230
|
1.000
|
.02
|
.01
|
.01
|
.01
|
|
2
|
.608
|
2.304
|
.60
|
.01
|
.03
|
.00
|
|
|
3
|
.126
|
5.071
|
.26
|
.00
|
.34
|
.47
|
|
|
4
|
.036
|
9.450
|
.11
|
.98
|
.62
|
.52
|
|
|
a.
Dependent Variable: GDP
|
|
|
|
| |||
|
Residuals Statisticsa
|
|||||
|
|
Minimum
|
Maximum
|
Mean
|
Std. Deviation
|
N
|
|
Predicted Value
|
2.5155E6
|
3.1491E7
|
8.0261E6
|
8.48666E6
|
23
|
|
Residual
|
-1.08342E7
|
7.22339E6
|
.00000
|
3.73678E6
|
23
|
|
Std. Predicted Value
|
-.649
|
2.765
|
.000
|
1.000
|
23
|
|
Std. Residual
|
-2.694
|
1.796
|
.000
|
.929
|
23
|
|
a.
Dependent Variable: GDP
|
|
|
|
||
For
comments, observation or other feedback or if you need assistance with your
research projects/papers, you can contact the author via E-mail:
researchmidas@gmail.com or call/Whatsapp (+234)0803-544-6622
No comments:
Post a Comment