RELATIONSHIP BETWEEN STOCK MARKET DEVELOPMENT AND ECONOMIC GROWTH IN KENYA. BY RAYMOND NYAMAKANGA D63/79634/2012 A RESEARCH PROJECT SUMBMITTED IN PARTIAL FULLFILMENT OF THE REQUIREMENTS FOR THE AWARD OF THE MASTER OF SCIENCE IN FINANCE, UNIVERSITY OF NAIROBI NOVEMBER, 2013
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RELATIONSHIP BETWEEN STOCK MARKET DEVELOPMENT AND
ECONOMIC GROWTH IN KENYA.
BY
RAYMOND NYAMAKANGA
D63/79634/2012
A RESEARCH PROJECT SUMBMITTED IN PARTIAL FULLFILMENT
OF THE REQUIREMENTS FOR THE AWARD OF THE MASTER OF
SCIENCE IN FINANCE, UNIVERSITY OF NAIROBI
NOVEMBER, 2013
DECLARATION
This research project is my original work and has not been submitted for any
award in any other University.
Signed:
Name:
Registration Number:
This project has been submitted for examination with my approval as
University Supervisor.
Dr J. Aduda: Senior lecturer, School of Business University of Nairobi.
Sign: Date:
ii
DEDICATION
I hereby dedicate this paper to my Lord Jesus and my Family. Words cannot express how
humbled I am to have them as pillars in my life.
iii
ACKNOWLEDGEMENTS
I would like to thank my Family for the support the have given me and also the support and
direction that I have been given by my supervisor Dr Aduda over this project. I would also like
to acknowledge my Lord and Savior Jesus Christ for increased favor in my life and graces that
are abound each day. Finally I would like to thank the University of Nairobi for the valuable
professional skills that I have gotten from the institution which I shall use for the rest of my
career and life.
iv
ABSTRACT
This study aimed at finding the causal relationship between stock market development and
economic growth in Kenya. The development of a stock market is determined by a number of
factors that include market capitalization, liquidity, regulation and trades. This paper sought to
investigate the causal relation between stock market capitalization, turnover and economic
growth. Previous studies done on African stock markets characterize them to be small and
hindered by various factors such as thin trading and illiquidity. These studies also point out that
countries with well developed financial markets have a better level of per capita income than
those with less developed markets. This notion is also confirmed by theory which states that
there is a big role that financial markets (stock markets) play in boosting economic activity
through provision of long-term capital for projects and risk diversification.
There has not been a lot of work done on causal relationship between stock market development
and economic growth in Kenya. Few studies show that traditionally the economy follows the
stock market in terms of capitalization and there is some what lack of consensus on liquidity.
The Kenyan stock market has made various strides in improving some of the aspects that are
deemed to result in the development of the stock market and this has seen the increase in the
number of listed firms on the bourse and also the improvement of regulatory laws that govern
trading and disclosures. This study therefore aims to use the Granger test for causality on stock
market capitalization to GDP ratio which represents the size of growth of the stock market, the
stock market turnover ratio and GDP growth in Kenya over the period 1993-2012. The results
show a strong positive relationship between stock market development and economic growth
stemming from a one sided causal relation from market capitalization to economic growth while
market liquidity (stock market turnover ratio) showed a non causal effect to economic growth.
With the results found it is recommended that measures that boost the size of the stock market
should be implemented so as to raise economic activity as the stock market in Kenya is seen to
be forward looking and a proponent of long run economic growth.
v
TABLE OF CONTENTS
Declaration page…………………………………………………………………………..ii
Dedication………………………………………………………………………………...iii
Acknowledgements……………………………………………………………………….iv
Abstract……………………………………………………………………...…………….v
Abbreviations……………………………………………………………………………..ix
CHAPTER ONE…………………………………………………………………………1
Introduction……...……………………………………………………………………….1
1.1 Background to the Study………………………………………………………………1
Hypothesized Trace 0.05No. of CE(s) Eigenvalue Statistic Critical Value Prob.**
None * 0.945474 74.09149 29.79707 0.0000At most 1 * 0.700930 21.72819 15.49471 0.0050At most 2 4.28E-05 0.000771 3.841466 0.9786
Trace test indicates 2 cointegrating eqn(s) at the 0.05 level * denotes rejection of the hypothesis at the 0.05 level **MacKinnon-Haug-Michelis (1999) p-values
Unrestricted Cointegration Rank Test (Maximum Eigenvalue)
Hypothesized Max-Eigen 0.05No. of CE(s) Eigenvalue Statistic Critical Value Prob.**
None * 0.945474 52.36330 21.13162 0.0000At most 1 * 0.700930 21.72742 14.26460 0.0028At most 2 4.28E-05 0.000771 3.841466 0.9786
Max-eigenvalue test indicates 2 cointegrating eqn(s) at the 0.05 level
35
* denotes rejection of the hypothesis at the 0.05 level **MacKinnon-Haug-Michelis (1999) p-values
From the above figure we can see that both the Trace and the Maximum Eigen values are
high when the probabilities are closer to zero. The null hypothesis shows 3 possibilities
that is (α = 0, 1 or 2) against a general alternative hypothesis. The Trace results from the
above figure suggest that there is at most 2 co-integrating vectors as the trace statistics for
the α = 0, 1 hypotheses are rejected at the 5% level. These results are also boosted by the
Maximum Eigen Value as it also rejects the null that α = 0, 1, or 2 at the 5% level. This
shows that there are two co-integrating vectors. These results are significant because
according to Engel and Granger (1987), it rules out the possibility of having spurious
correlation and brings out the possibility of having more than one direction in a granger
test of causality.
4.4 Granger test for Causality
According to Olweny and Kimani (2011) the decision rule for the causality test states that
if the p-values of the estimates are higher than the 10% level then we fail to reject the null
hypothesis and when the p-values of the estimates is below the 10% significance level we
reject the null hypothesis. The results of the granger test for causality on GDP, MktCap,
TVR and control variables are therefore shown below shown in the Table below.
Table 4: Granger test for causality
Null Hypothesis: Obs F-Statistic Prob. Findings L_MKTCAP does not Granger Cause L_GDP 19 11.9017 0.0033 causality L_GDP does not Granger Cause L_MKTCAP 1.66131 0.2158 no causality
36
L_TVR does not Granger Cause L_GDP 19 2.71077 0.1192 no causality L_GDP does not Granger Cause L_TVR 0.73364 0.4044 no causality L_BSD does not Granger Cause L_GDP 19 0.47525 0.5005 No causality L_GDP does not Granger Cause L_BSD 1.8398 0.1938 No causality L_CPI does not Granger Cause L_GDP 19 0.39539 0.5384 No causality L_GDP does not Granger Cause L_CPI 0.00053 0.9819 no causality L_EXP does not Granger Cause L_GDP 19 0.02481 0.8768 no causality L_GDP does not Granger Cause L_EXP 2.51306 0.1325 no causality L_TRADE does not Granger Cause L_GDP 19 3.36305 0.0853 causality L_GDP does not Granger Cause L_TRADE 1.20915 0.2878 no causality L_TVR does not Granger Cause L_MKTCAP 20 0.00614 0.9385 no causality L_MKTCAP does not Granger Cause L_TVR 1.19626 0.2893 no causality L_BSD does not Granger Cause L_MKTCAP 20 0.20602 0.6556 no causality L_MKTCAP does not Granger Cause L_BSD 0.18734 0.6706 no causality L_CPI does not Granger Cause L_MKTCAP 20 1.12728 0.3032 no causality L_MKTCAP does not Granger Cause L_CPI 0.00969 0.9227 no causality L_EXP does not Granger Cause L_MKTCAP 20 0.37582 0.548 no causality L_MKTCAP does not Granger Cause L_EXP 13.5662 0.0018 Causality L_TRADE does not Granger Cause L_MKTCAP 20 1.76291 0.2018 no causality L_MKTCAP does not Granger Cause L_TRADE 0.62081 0.4416 no causality L_BSD does not Granger Cause L_TVR 20 0.00823 0.9288 no causality L_TVR does not Granger Cause L_BSD 0.02801 0.8691 no causality L_CPI does not Granger Cause L_TVR 20 2.58442 0.1263 no causality L_TVR does not Granger Cause L_CPI 0.07332 0.7898 no causality L_EXP does not Granger Cause L_TVR 20 0.00813 0.9292 no causality L_TVR does not Granger Cause L_EXP 3.69026 0.0717 Causality L_TRADE does not Granger Cause L_TVR 20 0.21734 0.647 no causality L_TVR does not Granger Cause L_TRADE 0.01693 0.898 no causality L_CPI does not Granger Cause L_BSD 20 0.00722 0.9333 no causality L_BSD does not Granger Cause L_CPI 0.25741 0.6184 no causality L_EXP does not Granger Cause L_BSD 20 2.91629 0.1059 no causality L_BSD does not Granger Cause L_EXP 0.11683 0.7367 no causality
4.5 Results and Discussion
The results from the figure above are done on a granger test for causality on data
spanning 20 years from 1993-2012 on the variables GDP, MKtCap, Turnover and control
37
variables (national expenditure, banking sector credit to local firms, trade in relation to
GDP and inflation) . From the results we see that there is a one-sided causality between
economic growth and stock market development in Kenya. The direction of this causality
runs from Stock market development (stock market capitalization to GDP ratio) to
economic growth (GDP growth rate). These results are in line with what other researches
have also found in particular in relation to the forward-looking characteristic of the stock
market (Fama, 1981). Other significant results also show no relationship between the
Stock market turnover ratio and the GDP growth rate in Kenya, which confirms the
findings by Osamwonyi and Kasimu (2013).
These results prove that there is a long run relationship between stock market
development and economic growth in Kenya. The granger test of causality also
confirmed the results from the Jansen co-integration test that there were two co-
integrating vectors signaling a long term relation. The Jansen co-integration test showed
that there were at most 2 long term relations on the tested variables and these have since
been shown to be uni-directional relationships from MktCap to GDP. The data also
underwent unit root testing namely the Augmented Dickey Fuller test to make sure that
the results that are derived are not spurious. With the above mentioned results it implies
that the Nairobi securities exchange is a forward looking stock market and should
therefore be looked at seriously as one of the major sources of growth in Kenya.
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CHAPTER FIVE
SUMMARY
5.1 Summary
39
The aim of the study was to determine the causality relationship between the NSE market
capitalization, turnover and economic growth. Theory has highlighted how the stock
market impacts the economy through provision of funds for long-term projects for the
real economy.NSE market capitalization to GDP and turnover ratio represented the
development of the NSE in terms of size and liquidity. While African stock markets have
been characterized by weak trading and liquidity constraints, the stock exchange in
Kenya has seen growth over the years to try and address these issues and in the process
modernize operations. This has resulted in the NSE automating its trading in 2006,
improving regulation laws and integrating the NSE with international markets in a bid to
boost stock market development.
Stock market development being in itself affected by measures such as improved
regulation and liquidity will eventually reap benefits for the economy as investor become
willing to invest in long term projects and also have the peace of mind of easy exit of
their investments in the market. As such the measures put in place by the CMA to
enhance the capital markets in Kenya have seen the Stock exchange develop to become
on of the best performing bourses on the African continent and also one of the biggest in
terms of size. This should translate to increase level of economic activity and hence
formed the basis for the study, using the notion by Levine (1991) that nations with well
developed financial markets are associated with a better per capita income level.
The study therefore took a causal relationship approach in analyzing stock market
development and economic growth in Kenya using the VAR technique namely the
40
granger test for causality. The study also sought to answer the question of the direction of
the causal relation as well. The granger test for causality showed that there is a long run
relationship between stock market development and economic growth in Kenya and also
that there is a causal relation between the two with the direction of causality being one
sided moving from stock market development to economic growth. This therefore means
that the stock market in Kenya is forward looking.
5.2 Conclusion
The Study found a one sided causality direction between market capitalization to GDP
and economic growth while there was no causal relation between stock market turnover
and economic growth (GDP growth rate). This shows that stock market development in
terms of size (market capitalization) has a big role to play in boosting economic activity.
These results also show that future economic activity can be forecasted or predicted by
looking at both performance and development of the NSE. These results are in line with
the studies done by Olweny and Kimani (2011) and Osamwonyi and Kasimu (2013) who
found the NSE 20 Share index to predict the economic growth in Kenya.
5.3 Recommendations
The results of this study show that stock market development is an important aspect of
economic growth in Kenya and hence it is recommended that the Capital markets
authority CMA continue to find way to ensure that the bourse continually integrates into
the global markets and also open up more foreign investor trading. The NSE also needs to
41
work in tandem with the CMA on this regard. Some noteworthy projects that have been
put in the pipeline by the NSE are the financial derivate market proposal and also the
proposal to allow for online trading.
Online trading will ensure that international investors are able to trade on the equities
listed on the NSE anywhere in the world and this has potential to not only boost the daily
turnover but also the market capitalization of the bourse which will have positive long
term impact on the Kenyan economy. Financial derivate markets offer a new and
innovative way to investments in the country as opposed to only Equities and Bond
markets. Increased regulation by the CMA will also impact positively on the country`s
credit ratings in light of the new opportunities that high growth African countries face in
the Euro-Bond markets which Kenya is also looking to exploit (Business daily, 2013).
These measures are of utmost importance in pushing economic activity in the country and
also government should also provide support to these institutions so that by growing the
investor trading and base with online trading and access to derivative markets, the
Kenyan economy can further advance to reach the intended goal of Kenya becoming a
middle income economy. On the research front it is therefore recommended to look at the
benefits or the impact of online trading and the financial derivative markets at a time
when they are already functioning in the country.
42
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