According to Sessional paper No. 1 of 1986 on
Economic management for economic reforms in Kenya, the financial market is key
in achieving meaningful economic growth and development. Capital markets assist
in liquidity provision, price discovery, general reduction in transaction
costs, and risk transfer. They reduce information costs through the generation
and dissemination of information on firms leading to efficient markets in which
prices incorporate all available information (Yartey
& Adjasi 2007). The Capital market in Kenya dates
back to 1922 when the Stock exchange was started, however, there was little
activity until the late 1980s when the government
adopted reforms that were aimed at reviving the financial sector. The Capital
markets in Sub-Saharan Africa, Kenya displayed extreme thinness and illiquidity
compared with other emerging markets of South East Asia (Ziorklui,
2001). In 1986, The Government of Kenya made a deliberate policy effort to
foster the growth of the Capital Markets through the adoption of The Sessional
Paper No.1 of 1986, which recognized the Capital
Markets as key to achieving meaningful economic growth and development. The
Government through the policy; recommended that a regulatory framework be set
up to regulate and facilitate the development of the Capital Market in Kenya.
The birth of The Capital Markets Authority in December 1989 was a step forward
following the deliberations of The Sessional Paper No.1
of 1986. The Capital Markets Authority Act (Chapter 485 a) facilitated the
setup of The Capital Markets Authority and its functions, but even after the
establishment of the Capital Markets Authority, Kenya still lagged with a thin
and illiquid capital market (Ngugi, 2003). While Kenya's financial sector is
viewed as substantially diversified, it is dominated by banking institutions
which have not evolved to provide long-term capital adequately (Ngugi, Amanja & Maana, 2008). Economic growth can be described
as the sustained increase in the welfare of an economy. For some, economic
growth is synonymous with ―economic development and is associated with
such things as the growth of population (especially the working population),
development of resources, technological advancement and increasing capital
formation. Generally, economic growth means growth of output and discussions of
economic growth are conducted in quantitative terms. Economic growth is
commonly measured as the annual rate of increase in a country's gross domestic
product (GDP) by economists or by related indicators, such as gross national
product (GNP) or gross national income (GNI) which is
derived from the GDP calculation (Arthur, 1964) Iram and Nishat (2009) describe
economic growth as the indicator of the health of an economy, and that capital
is one of the pre-requisites to maintain and enhance the momentum of growth.
Simply put, a country's economic health can be measured by 4 looking at the
country's economic growth and development. Economic growth is what mainly
determines the material well-being of a nation.
Financial deepening is a term used to refer to
the increasing provision of financial services. It can refer to both a wider
choice of services and better access for different socioeconomic groups. One of
the key features of financial deepening is that it accelerates economic growth
through the expansion of access to those who do not have adequate finance
themselves. Typically, in an underdeveloped financial system, the incumbents
have better access to financial services through relationship banking. Moreover,
incumbents also finance their growth through internal resource generation
(Goswami & Sharma, 2011). Financial deepening refers to the improvement or
increase in the pool of financial services that are tailored to all levels of
society. It also refers to the increase in the ratio of money supply to GDP
that ultimately postulates that the more liquid money is available in the
economy, the more opportunities exist in that economy for continued and
sustainable growth. It supports the view that: Development in Financial sectors
leads to the development of the economy as a whole (Cole, 1974). Conceptually,
financial depth is often understood to mean that: sectors and agents can use a
range of financial markets for savings and investment decisions, including at
long maturities (access); financial intermediaries and markets can deploy
larger volumes of capital and handle larger turnover, without necessitating
large corresponding movements in asset prices (market liquidity); and the
financial sector can create a broad menu of assets for risk-sharing purposes
(hedging or diversification). In other words, deep markets allow savers to
invest in a broad range of quality investment and risk-sharing instruments and
allow borrowers to tap a broad range of financing and risk management
instruments (Goswami & Sharma, 2011).
The Kenyan government has a vision of
transforming the country into the middle-income level and industrializing
economy by the year 2030 and they have identified the financial sector as one
of the areas that would help in attaining this critical target. The Capital
Markets Authority of Kenya acknowledges that the Kenyan financial markets are
at different stages of development. Whereas Kenya has a well-developed and
liquid government bond market, the equities market on the other hand is
characterized by relatively few listings, which are skewed towards financial
companies, and low liquidity (Capital Markets Master Plan, 2014). Ambitious
targets have been set for improvements in listings, liquidity and performance
of new product areas to develop the Kenyan financial markets. The first is to
improve the ratio of equity market capitalization to GDP which currently stands
at 50% to 70% by end-2023. The second target is the number of GEMS listings,
which reflect the supply of future main board listed companies, to increase by
3-4 annually. The third target is to raise the ratio of corporate bonds
outstanding to GDP to reach 40% by the end of 2023 and lastly, the value of
outstanding exchange-traded derivative contracts to reach USD 200 billion by
end-2023 which is an ambitious target, given that the market has not yet been
launched, but is achievable by comparison with other markets (Capital Markets
Master Plan, 2014). Kenya is one of the countries in the African continent
having a well-developed financial system based on the ground. During the last
two decades, several reforms translated by developments and innovations have
taken place in the Kenyan banking sector that have led to an increase in the
sector's assets. Such developments have mainly been driven by financial
innovations in the sector. Specifically, the reduction of the retention ratio
from 6 to 5.25 per cent by the Central Bank of Kenya (CBK)
made loans more affordable to the public; the transformation of Non-Bank
Financial Institutions (NBFI) into commercial
banks(e.g. Equity and Family banks); and the introduction of new products and
financial service delivery channels (such as M-pesa,
Islamic banking, mobile banking, agency banking and the integration of
Automated Teller Machines (ATMs) by microfinance institutions) to name a few
(Bakang, 2015).
Even with the studies already done in Kenya,
happenings in the financial sector have not been interrogated in the context of
financial deepening and economic growth. In 2016, the parliament passed capping
on interest rate charged by commercial banks on loans hence affecting the
ability of commercial banks to create credit. Additionally, the last few years
have seen a major shift from brick-and-mortar banking to mobile-based banking
hence transforming the process of financial intermediation greatly in terms of
mobile banking loans and other transactions that have a bearing on financial
deepening. There is a need therefore to address the relationship between
financial deepening and economic growth, especially by incorporating the role
of mobile banking, and direct capital inflow in financial deepening and
economic growth. This study therefore seeks to fill the gap by studying the
effect of financial deepening and the growth of Kenya's economy. This study
therefore sought to answer the question: what is the effect of financial
deepening on the economic growth of Kenya?
2. Literature Review
2.1 Theoretical framework
Several theories have been advanced in financial literature to postulate the relationship between financial deepening efficiency and economic growth. The current study specifically relied on three theories that served as the base of the study. The theories include financial intermediation theory, financial liberalization hypothesis and Keynes theory.
2.1.1
Financial Intermediation Theory
Financial intermediation is a process that
involves surplus units depositing funds with financial institutions that then
lend to deficit units. Bisignano (1998) and Leland and Pyle (1977) identify
that financial intermediaries can be distinguished by four criteria: first,
their main categories of liabilities (deposits) are specified for a fixed sum
which is not related to the performance of a portfolio. Second the deposits are
typically short-term and of a much shorter term than their assets. Third, a high
proportion of their liabilities are chequeable (can be withdrawn on demand).
And fourth their liabilities and assets are largely not transferable. The most
important contribution of intermediaries is a steady flow of funds from surplus
to deficit units. According to Scholtens
and van Wensveen (2003), the role of the financial intermediary is essentially
seen as that of creating specialized financial commodities. These are created
whenever an intermediary finds that it can sell them for prices which are expected
to cover all costs of their production, both direct costs and opportunity
costs. Financial intermediaries exist due to market imperfections. As such, in
a 'perfect' market situation, with no transaction or information costs,
financial intermediaries would not exist. Numerous markets are characterized by
informational differences between buyers and sellers. In financial markets,
information asymmetries are particularly pronounced. Borrowers typically know
their collateral, industriousness, and moral integrity better than do lenders.
On the other hand, entrepreneurs possess inside information about the projects
for which they seek financing (Leland and Pyle, 1977). Moral hazard hampers the
transfer of information between market participants, which is an important
factor for projects of good quality to be financed.
2.1.2 Shaw’s
Financial Liberalization Hypothesis
Shaw (1973) advanced financial liberalization
theory to explain the relationship between the deregulation of the financial
sector and financial deepening. According to Shaw's (1973), financial deepening
hypothesis, financial liberalization tends to raise the ratio of private
domestic savings to income. With the real growth of financial institutions,
many investors have access to borrowing. There arise incentives for saving with
many players and borrowings become cheaper. Savings also tend to rise in the
Government sector. With financial deepening, savings from the foreign sector
respond to financial liberalization. There is an inflow of capital and easy access
to foreign capital markets, which remove distortions in relative prices.
Liberalization permits the financial process of mobilizing and allocating
savings to displace inflation and foreign aid. Liberalization enables superior
allocation of savings through widening and diversifying financial markets
wherein investment opportunities compete for savings flow. The savers are
offered a wider menu of portfolio choices. The market is broadened in terms of
scale, maturity and risk (Shaw, 1973). Information is available more cheaply.
Local capital markets are integrated and new avenues for pooling savings and
specializing in investments are possible. Prices are used to discriminate
between investment opportunities. In this context, Shaw (1973) states that
"Financial depth seems to be an important pre-requisite for competitive
and innovative disposition of savings flows." Thus, financial
liberalization and allied Policies bring an equal distribution of income. It
reduces monopoly rents arising out of import and other licenses to a few
importers and bank borrowers. It contributes to the stability of growth in
output and employment (Shaw, 1973). Critics of financial liberalization
policies have argued that the efficient markets paradigm is fundamentally
misleading when applied to capital flows. In the theory of the second best,
removing one distortion need not be welfare-enhancing when other distortions
are present (Evans, 2017). If the
capital account is liberalized while import-competing industries are still
protected, for example, or if there is a downwardly inflexible real wage,
capital may flow into sectors in which the country has a comparative
disadvantage, implying a reduction in welfare (Okpe, 2018). If information
asymmetries are endemic to financial markets and transactions, in particular in
countries with poor corporate governance and low legal protections, there is no
reason to think that financial liberalization, either domestic or
international, would be welfare-improving (Stiglitz, 2000). Moreover, in countries
where the capacity to honour contracts and to
assemble information relevant to financial transactions is least advanced,
there can be no presumption that capital would flow into uses where its
marginal product exceeds its opportunity costs.
2.1.3 Keynes
Theory
John Maynard Keynes (1936) advanced Keynesian
theory in in financial economic analysis. This theory assumes equilibrium with
less than full employment where both employment and income are fluctuating. The
theory views interest as a reward for parting with liquidity. It provides that
the interest rate is determined by the demand and supply of money. The theory
opined that the supply of money is usually determined by monetary authorities
while the demand for money is a function of income and interest rate (Keynes,1936). This theory assumes equilibrium with less
than full employment where both employment and income are fluctuating. The
theory views interest as a reward for parting with liquidity. It provides that
the interest rate is determined by the demand and supply of money. The theory
opined that the supply of money is usually determined by monetary authorities
while the demand for money is a function of income and interest rate.
The theory further explained that the
transitionary and precautionary motive of liquidity is dependent on income
while the speculative motive is dependent on interest rate, it is interest
elastic. The Keynesian theory implies that a low-interest rate as a component
of cost administered is detrimental to increasing savings and hence investment
demand. Proponents of this theory argue that an increase in the real interest
rate would have strong positive effects on savings which can be utilized in
investment because those with excess liquidity would be encouraged to save
because of the high-interest rate, thus banks would have excess money to lend
to investors for investment purpose thereby raising the volume of productive
investment. Keynes also emphasized that the rate of interest is purely a
monetary phenomenon.
This theory introduced the concept of a liquidity
trap, a situation where low-interest rates discourage savings and consequently
reduce investments due to a lack of investable funds. Anyingang
and Udoka (2012), in their study, observed that the Keynesian liquidity
preference theory of interest rate is a stock theory. It is a stock analysis
because it takes the supply of money as given during the short run and
determines the interest rate by liquidity preference or demand for money. This
theory alludes to the Nigerian situation under the regulated interest era,
where the monetary interest rate set by government authorities was low and the
real interest rate was even lower because of inflation. The low interest rate
encouraged inefficiency in the use of capital and the resultant negative growth
trend in investment. The negative trend was also because of a lack of
investable funds as people preferred to hold liquid cash as there was no
adequate inducement to part with liquidity. Keynes's theory is regarded as an
improvement over classical theory as it considers interest as a monetary
phenomenon that links the present and the future. This theory abandoned the
assumption of full employment and introduced the concept of unemployment
therefore, it considered the change in the income level and its relation with
savings and investment. Thus, in Keynesian analysis more investment leads to
more consumption, or in other words, investment and consumption go together.
Keynesian analysis is more realistic in the context of the unemployment of
resources prevailing in the economy. Opponents of this theory insist that it is
an indeterminate, incomplete, inadequate and unrealistic theory of interest
rates.
2.2 Empirical Review
A study by Ndebbio
(2004) on financial deepening, economic growth and development. This study
identifies the range of financial assets that can adequately approximate
financial deepening, which simply means an increase in the supply of financial
assets in the economy. FD is represented by two variables, the degree of
financial intermediation/development (M2/Y) and the
growth rate in per capita real money balances (GPRMB).
Because of a lack of data on other measures of financial assets in most SSA countries, broad money (M2)
was used as a numerator for both variables. Estimations depending on the two
measures of FD and other explanatory variables of interest were done with the
ordinary least squares (OLS) multiple regression procedure. Three modelled
equations, with justifications for each, were estimated and analyzed. A
cross-country regression was used for 34 SSA
countries. To even out year-to-year fluctuations as well as reflect underlying
structural changes, the variables were calculated on a decade-average basis.
Two policy implications derive from the study: that SSA
countries should strive hard to make real money balances grow, and that these
countries should also come up with policies to improve financial
development/intermediation. Given such factors as price stabilization,
elimination of fiscal deficit and removal of various restrictions on financial
institutions, real money balances could be made to grow. Financial
intermediation/ development could positively affect output growth if, among
other suggested ways, the volume of investment is raised.
Research by Nzotta
& Okereke (2009) examined financial deepening and economic development in
Nigeria between 1986 and 2007. The central focus is that a high level of
financial deepening is a necessary condition for accelerating growth in an
economy. This is because of the central role of the financial system in
mobilizing savings and allocating the same for the development process. The
study made use of secondary data, sourced for 22 years. The study specified
nine explanatory variables for the study based on theoretical underpinnings.
The study sought to establish a relationship between these variables and the
financial deepening index. The two stages' least square analytical framework
was used in the analysis. A trend analysis was also done in the study. At the
end of the study, the study found that the financial deepening index has been
low in Nigeria over the years. The study also found that the nine explanatory
variables, as a whole were useful and had a statistical relationship with
financial deepening. However, four of the variables; lending rates, financial
savings ratio, cheques/GDP ratio and the deposit money banks/GDP ratio had a
significant relationship with financial deepening. The study concluded that:
the financial system has not sustained an effective financial intermediation,
especially credit allocation and a high level of monetization of the economy.
Thus, the regulatory framework should be restructured to ensure good risk
management and corporate governance and to stem systemic crises in the system.
A study by Nwanna and Chinwudu (2016) examined financial deepening and economic
growth in Nigeria from 1985 to 2014. It focused on the impact of the stock
market and bank-deepening variables such as money supply, market
capitalization, private sector credit and financial savings on the economic
growth of Nigeria. Stock market provides the avenue through which long-term
funds can be raised for investment projects. It is reputed to perform critical
functions, which promote economic growth and prospects of the economy. The
study adopted the supply-leading hypothesis. The study used annual time series
data from 1985 to 2014 obtained from the Central Bank of Nigeria statistical
bulletin. The ordinary least square (OLS) econometric techniques were employed
in which variations in the dependent variable, economic growth, measured by
gross domestic product growth rate were regressed on money supply ratio to
gross domestic product, private sector credit ratio to gross domestic product,
market capitalization ratio to gross domestic product and financial saving
ratio to gross domestic product using time series data from 1985 to 2014. The
result of the analysis reveals that both bank-based and stock market financial
deepening proxies have significant and positive effects on economic growth and
that the banking sector and stock market in Nigeria have an important role in
the process of economic growth. Based on the findings there should be
improvement by encouraging more participation in the stock market. Easing
restrictions on international capital and entry into the stock market to ensure
more companies are listed.
A study by Sindani
(2013) set to establish the impact of the financial sector deepening on
economic development in Kenya. The study adopted a Quantitative comparative
design. The target population for this study was: 44 banking institutions (43
commercial banks and 1 mortgage finance company - MFC),
operating in Kenya as of 31st December 2011. The study used secondary data
collected from the Central Bank of Kenya and Deloitte reports. Since the data
used was secondary, the study conducted a census of the Banking sector where
all the 44 commercial banks were included. This study established that the
financial sector was stable during the study period as witnessed by the stable
number of banking institutions following stringent regulations by the Central
Bank of Kenya which had reduced the frequency of commercial banks becoming
bankrupt. During the period of the study (2007-2011), financial sector
deepening was high as the commercial banks strived to leverage their operations
through the adoption of new technologies including automation of bank processes
and adoption of Automated Teller Machines as opposed to offering their services
only through physical brick and mortar branches. The economic growth started at
a high of 7.1 then fluctuated to a low of 1.5 in 2008.
A paper by Bakang (2015) investigated the effects
of financial deepening on economic growth in the Kenyan banking sector. The
study achieves this objective using quarterly time series data from 2000 to
2013. Financial deepening, the independent variable was captured by four
alternative indicators: Liquid Liabilities (LL) as a ratio to nominal Gross
Domestic Product (GDP); Credit to the Private Sector (CPS) as a ratio to
nominal GDP; Commercial Bank Assets as a ratio to commercial bank assets plus
Central Bank Assets (CCBA); and Commercial Bank Deposits (CBD) as a ratio to
nominal GDP. The dependent variable, economic growth, was measured by real GDP.
All the variables were integrated at level I (1) and the Johansen Jeluisus cointegration test showed evidence of
cointegrating equations between GDP and financial deepening indicators. Four
models were estimated to determine the long-run and short-run effects. The
study found that the banking sector in Kenya has an important role in the
process of economic growth. Specifically, the empirical results reveal that
liquid liabilities, credit to the private sector, commercial-central bank
assets and commercial bank deposits have positive and statistically significant
effects on GDP. The study recommends therefore to reinforce existing policies
that would encourage the public to save more money with commercial banks.
Increasing the interest rate paid to depositors on their deposits, for example,
would incite people to save more. In addition, the study recommends the intensification
of financial inclusion policies through increased access and usage of formal
banking services while reducing bank transaction costs. This would encourage
more people to participate in economic activities and to borrow and invest
more.
A study by Gries, Kraft, & Meierrieks (2009) sought to establish Linkages between
Financial Deepening, Trade Openness and Economic Development in Sub-Saharan
Africa. The study tested for causality in 16 Sub-Saharan African countries. The
study used principal component analysis to obtain a broad indicator of
financial deepening. The study employed unit root and cointegration tests to
analyze the properties of the investigated time series and to identify possible
long-run relationships between them. Subsequently employing Hsiao's version of
Granger causality testing within a VAR/VECM.. The
empirical results can be summarized as follows. First, cointegration evidence
shows that finance, growth and openness do not share significant long-run
relationships for most of the sample. Second, the study detected only limited
support for causal interactions between financial depth and economic
development. In particular, there is evidence of finance-led growth only in
three out of 16 cases. Third, for most countries, the study detected either a
demand-following or insignificant relationship between finance and growth. We
thus provide support for more sceptical views on
direct finance-growth linkages. Fourth, the study was not able to identify any
predominant causal relationship for SSA.
Additionally, there is only limited evidence that suggests that either
financial deepening has promoted economic development indirectly via
influencing trade openness or that openness has enhanced growth as a byproduct
of its impact on financial development.
3. Methodology
The research design adopted for this study was descriptive. The descriptive approach to this study was the most preferred as the study attempts to investigate what effect financial deepening has on economic growth in Kenya. Descriptive research studies are those studies which are concerned with describing the characteristics of a particular individual, or of a group, whereas diagnostic research studies determine the frequency with which something occurs or its association with something else (Kothari, 2004) Secondary data was used in this study. The data on capital market capitalization was sourced from the Nairobi Securities Exchange. Data on cash transfers from abroad, mobile banking transactions, and commercial bank deposits were sourced from Central Bank of Kenya websites whereas data on real economic growth (GDP) and direct capital inflow was sourced from the Government of Kenya through the Kenya National Bureau of Statistics (KNBS) as well as World Bank development indicators. The study population was quarterly data for 11 years giving a total of 44 observations per variable. The study used both descriptive and inferential statistics in analyzing the data. First, the data collected was sorted, classified and collated. Descriptive statistics such as mean and standard deviation for each variable were calculated and tabulated using tables and inferential statistics. The STATA computer software was used in the analysis of data. Data was analysed using inferential statistics informed by regression and correlation analysis. To measure the effect of financial deepening on the economic growth of Kenya the researcher used regression analysis. The effect was examined at a 95% confidence level while employing a student t-test. The study adopted a multivariate regression model to determine the effect of financial deepening on economic growth to regress the independent variables against the dependent variable. The general form of a multiple regression model is as given in equation (1).
Y = β0 + β1X1 +β2X2+ β3X3+ β4X4 + ɛ………………………..……………………………………………………….……… (1)
Where:
Y= Dependent variable is Gross Domestic Product Growth rate: Measured using Nominal GDP growth rate.
X1= Total deposits of the banking industry: Natural logarithm of aggregate deposits in the commercial banking sector.
X2= Capital market Capitalization: Natural logarithm of capitalization of the Nairobi stock exchange.
X3= mobile banking innovation: Natural logarithm of the total commercial banking mobile banking transactions volume.
X4 = Direct capital inflow: Natural logarithm of total cash transfers from abroad.
βo: Intercept term measuring the level of economic growth when financial deepening is held constant.
βi: Coefficients of independent variables measuring the responsiveness of economic growth due to a percentage change in financial deepening proxies.
ɛ: Stochastic Term that captures other variables that also affect economic growth which are not part of the model.
The data was subjected to diagnostic tests to evaluate conformity with multiple regression model assumptions. This would ensure the validity of the results. The study employed normality, heteroscedasticity, multicollinearity, serial correlation and unit root diagnostic tests. The test is conducted to test whether data exhibits a normal distribution. If the data is not normally distributed, it may not display the correct relationship between the variables studied (Garson, 2012). The study employed the Shapiro-Wilk test to test normality. The test is most appropriate for a sample size of 50 or less. The choice of this test is informed by the small number of samples to be studied. Data is normal if the significance values for Shapiro-Wilk tests are greater than the P-value statistic test of 0.05. A value below 0.05 depicts that the data is not normally distributed. Gujarati (2003) described heteroscedasticity as lacking constant error variance. The study used the Breusch-Pagan / Cook-Weisberg test by using the regression residual value of the independent variables. There is no heteroskedasticity if the significance values are greater than the P-value statistics test of 0.05. Kothari (2004) postulates that multicollinearity exists if there is an association of independent variables. Therefore, independent variables ought to be linearly independent of each other. Cooper and Schindler (2006) assert the existence of multicollinearity leads to invalid significance tests due to the distorted regression coefficients. The study employed the Variance Inflation Factor (VIF) to test the existence of multicollinearity. If VIF is less than 5, then there is no existence of multicollinearity (Gujarati, 2003). Gujarati (2003) posits that serial correlation exists if an error term of one period is correlated with that of subsequent periods. The study used the Wooldridge Drukker test to test the existence of autocorrelation. Data has no serial correlation if the P value is greater than the 5% level of significance. Unit root test is conducted to ensure that the variables are stationary. Gujarati (2003) posit that data has no unit roots if the variance, autocorrelation and mean of the data structure do not vary with different periods. Wooldridge (2012) asserted that stationarity ensures that the regression results are not spurious thereby guaranteeing robust regression results. The study employed the Augmented Dickey-Fuller (ADF) unit root test to evaluate the availability of unit roots in the data. If the P-value is greater than a 5% level of significance, it implies the data is not stationary i.e. availability of unit roots.
.
4. Results
The study initially targeted to collect data on financial deepening and economic growth in Kenya. The study targeted quarterly data for 18 years beginning 2000-2017 but due to fact that data on mobile banking was only available from 2007 to 2017 accounting for 11 years.
4.1 Descriptive Analysis
Table 1: Summary of Descriptive Statistics
|
Statistics |
Direct
capital inflow |
Mobile
banking |
GDP |
Banking
deposits |
Capitalization |
|
Minimum |
42685.79 |
0.064391 |
315849 |
983.2 |
689.045 |
|
Maximum |
188168.3 |
301.63 |
1150141 |
2845.3 |
2447.72 |
|
mean |
93827.41 |
135.2931 |
660790.4 |
2234.2 |
1521.20959 |
|
standard Dev |
39782.04 |
106.4297 |
335411.7 |
465.7 |
671.400264 |
|
Obs |
44 |
44 |
44 |
44 |
44 |
Direct capital
inflows capture the finances received from abroad into the domestic economy. The results are presented in Table 1. The mean direct
capital transfers was Ksh. 93827.41 million suggesting
that the average quarterly direct capital inflow from aboard was about Ksh. 93827 million. The standard deviation for quarterly
direct capital inflow was Ksh. 39782.04 demonstrating
that direct capital inflows were spread around the mean with about Ksh.3978 Million. The
minimum quarterly direct capital inflow was Ksh. 42685.79
million and the maximum quarterly direct capital inflow was ksh.188168.3 million. Mobile banking was measured
by the value of mobile banking transactions. The mean quarterly mobile banking was
Ksh. 135.2931 billion suggesting that the average mobile
banking was about ksh.135 billion. The standard deviation for quarterly
mobile banking was Ksh.106.4297 billion demonstrating
that mobile banking was spread around the mean with about Ksh 106 billion.
The minimum quarterly mobile banking was ksh.0.064391
billion and the maximum mobile banking was Ksh. 301.63 billion. Capital capitalization was measured by the value of all publicly was
measured by the value of mobile banking transactions. The mean quarterly capitalization
was Ksh.1521.209 billion suggesting that the average capital
market capitalization was about ksh.1,521 billion.
The standard deviation for quarterly capital market capitalization was Ksh. 671.400264 billion demonstrating that the capital
market was spread around the mean with about Ksh 671 billion.
The minimum quarterly market capitalization was Ksh.
689.045 billion and the maximum market capitalization was Ksh.
2,447.72 billion.
The mean banking deposits were Ksh. 2234.2 billion suggesting
that the average banking deposits were about 2.3 trillion. The
standard deviation for the quarterly banking deposits was Ksh.
465.7 Billion in Kenya and was spread around the mean with about Ksh. 466 billion. The minimum and maximum quarterly
commercial banking deposits were Ksh.983.2 billion
and Ksh. 2845.3 billion Respectively. The proxy for
Economic growth was the real GDP for Kenya. The mean quarterly economic growth
was Ksh. 660,790.4 million suggesting that the
average economic growth was about Ksh. 661 billion.
The standard deviation quarterly economic growth was Ksh.
335411.7 million demonstrating that quarterly economic growth was spread around
the mean with about Ksh. 335412 million. The
minimum quarterly economic growth was Ksh. 315849
million and the maximum quarterly economic growth was Ksh.
2845.3 million.
Panel data was subjected to
diagnostic tests to evaluate conformity with multiple regression model
assumptions. This ensured the validity of the results. The study employed
normality, heteroscedasticity, multicollinearity, serial correlation and unit
root diagnostic tests. The study employed the Shapiro-Wilk test to test
normality as presented in Table 2
Table 2: Shapiro-Wilk test to test normality
|
Variable |
Obs |
W' |
V' |
z |
Prob>z |
|
Direct capital Inflows |
44 |
0.91578 |
3.972 |
2.587 |
0.00485 |
|
Mobile |
44 |
0.79247 |
9.788 |
4.278 |
0.00001 |
|
Deposits |
44 |
0.88966 |
5.204 |
3.093 |
0.00099 |
|
CAP |
44 |
0.8885 |
5.259 |
3.113 |
0.00093 |
|
GDP |
44 |
0.76983 |
10.856 |
4.472 |
0.00001 |
From Table
2, one rejects the null hypothesis H0 direct
capital Inflows (p = 0.00485), Mobile banking (p = 0.00001), bank Deposits (p =
0.00099) Capital market capitalization (p = 0.00093) and economic growth (0.00001).
This owes to p-values lower than 0.05. The data is not normal since the sample
size was small however, this cannot affect the estimation of the coefficient of
explanatory variables used in the study. The study
utilized the Breusch-Pagan / Cook-Weisberg test for heteroskedasticity test by
using the regression residual value of the independent variables. There is no
heteroskedasticity if the significance values are greater than the P-value
statistics test of 0.05. The results are shown in Table 3.
Table 3: Breuch-Pagan Test
|
|
Breusch-Pagan / Cook-Weisberg test for heteroskedasticity |
||||
|
Ho: Constant variance |
|||||
|
Variables: fitted values of GDP |
|||||
|
chi2(1) = 0.97 |
|||||
|
|
Prob > chi2 = 0.3255 |
|
|
|
|
There is no heteroskedasticity if the significance values are greater than the P-value statistics test of 0.05. The results show that the p-value was greater than chi2 hence the hypothesis that variances are constant was accepted thus, it can be concluded that there was no heteroscedasticity. The study employed the Variance Inflation Factor (VIF) to test the existence of multicollinearity. The results are shown in Table 5.
Table 1: Variance Inflation Factor
|
Variable |
VIF |
1/VIF |
|
Direct Capital Inflows |
2.06 |
0.485437 |
|
CAP |
2.84 |
0.352113 |
|
Mobile |
3.39 |
0.294985 |
|
Deposits |
1.08 |
0.925926 |
|
Mean VIF |
2.3425 |
|
Results in Table 5 show that all
the variables had a variance inflation factor (VIF) of less than 5 and an
overall VIF of 2.3425. These results show that the multicollinearity problem
was very low. The study used the Wooldridge Drukker test to test the existence
of autocorrelation. A data has no serial correlation if the P value is greater
than the 5% level of significance. The results are shown in Table 6
Table 2: Autocorrelation Tests
|
Wooldridge test for autocorrelation |
|
H0: no first-order autocorrelation |
|
F( 1, 10) = 0.332 |
|
Prob > F = 0.5770 |
The value of P was greater than the 5% level
of significance. The results are shown in table 6. The study therefore
concludes that the was no serial correlation problem and thus error term of one
period is correlated with that of subsequent periods. The
study employed the Augmented Dickey-Fuller (ADF) unit
root test to evaluate the availability of unit roots in the data. If the
P-value is greater than a 5% level of significance, it implies the data is not
stationary i.e. availability of unit roots. The results are shown in Table 7
Table 3: Augmented Dickey-Fuller
Unit Roo
|
Variable Name |
Statistic (Adjusted) |
P-Value |
Comment |
|
Banking deposits |
-9.1936
|
0.000 |
Stationary |
|
Capital market capitalization |
-25.2806 |
0.000 |
Stationary |
|
Mobile banking |
-14.6408
|
0.000 |
Stationary |
|
Direct capital inflows |
-18.2333 |
0.000 |
Stationary |
|
|
|
|
|
All the values of P were less
than a 5% level of significance, which implies the data is stationary i.e. absence
of unit roots. Results are shown in Table 7.
Regression
analysis was multiple as there were four independent variables. The independent
variables were direct capital transfers, mobile banking, bank deposits and
capital market capitalization. The dependent variable was economic growth measured
by Real GDP. Multiple regression analysis involved the calculation of the
coefficient of determination, Analysis of Variances (ANOVA) and regression
coefficients (Table 8).
Table 4. 4: OLS Regression Analysis
|
Source SS |
df MS Number of obs = |
44 |
|
F(4, 39) = |
184.88 |
|
|
Model 11.2905935 |
4 2.82264838 Prob > F = |
0 |
|
Residual .595416423 |
39 .015267088 R-squared = |
0.9499 |
|
Adj R-squared = |
0.9448 |
|
|
Total 11.8860099 |
43 .276418836 Root MSE = |
0.12356 |
|
GDP Coef. |
Std. Err. t P>|t| [95% Conf. |
Interval] |
|
Cap Inflows .4853428 |
.1112539 4.36 0.000 .2603105 |
0.710375 |
|
Mobile .0621813 |
.0178975 3.47 0.001 .0983824 |
0.0259801 |
|
Deposits .0085088 |
.0042794 1.99 0.054 .0001471 |
0.0171647 |
|
CAP .8682275 |
.0996484 8.71 0.000 .6666696 |
1.069785 |
|
_cons 1.662703 |
.8293403 2.00 0.052 -.0147961 |
3.340202 |
Tables 8 indicate that the model explains only 94.48% of the variations in Economic growth (GDP) as shown by the coefficient of determination (R2) value of 0.9448 hence only 5.52 % of Variations in economic growth are explained by other factors not included in the model. It is therefore clear that financial deepening explains only 94.448 % of variations in economic growth. Additionally, according to Table 8, the overall significance of the model was 0.000 with an F value of 184.88. The level of significance was lower than 0.05 and this means that financial deepening does show a statistically significant effect on economic growth in Kenya (GDP). Table 8 further shows the coefficients of independent variable financial deepening proxies and the values of p and values of t. The model was thus estimated as
GDP = 1.662703 + .4853428 Direct capital inflows + .0621813 Mobile
banking + .0085088 bank
deposits + .8682275 Capital market
capitalization.
The estimated model above shows the causal
effect relationship between the independent variable financial deepening and
the dependent variable Economic Growth of Kenya. The estimated intercept term 1.662703
shows the level of economic
growth in terms of Real Economic Growth when the independent variables are held
constant. The coefficients estimate of the model are explained in detail in the
following discussion.
The researcher established that banking deposits had a
statistically insignificant effect on economic growth measured by GDP (β1
= .0085088, p = 0.054 > α = 0.05). Capital
market capitalization had a statistically significant effect on economic growth
(β2 = .8682275, p = .000 < α = 0.05). Mobile
banking had a statistically significant effect on economic growth (β3 = .0621813,
p = 0.001 < α = 0.05).
Finally, direct capital Inflows had a statistically significant effect on economic
growth (β4= .4853428, p = .000 < α = 0.05).
5. Discussion
The researcher established that banking deposits
had no significant effect on the economic growth of Kenya using regression
analysis it was established that real GDP that was used as a proxy of banking deposits
had a statistically insignificant effect on economic growth measured by GDP
(β1 = .0085088, p = 0.054 > α = 0.05). The value β1 was
positive showing that an increase in banking deposits leads to an increase in
economic growth in Kenya however the effect was not statistically significant
implying the relationship between banking deposits is not strongly associated
with the economic growth of Kenya. The insignificant effect could be explained
by the fact that it is not enough to generate savings that lie idle in
commercial banking institutions. For savings to contribute to meaningful
economic growth, the funds need to be invested in economic activities. The
coefficient of banking deposits (β1) measures the responsiveness of
economic growth to changes in banking deposits.
Any increase in banking deposits by one unit should lead to an increase
in economic growth by .0085088 units. Using OLS regression analysis, it was
established that Capital Market capitalization had a statistically significant
effect on economic growth measured by GDP (β2 = .8682275, p = .000 <
α = 0.05). The value of coefficient of capital market capitalization
(β2) was positive showing that any increase in capital market
capitalization should lead to economic growth. The relationship was
statistically significant implying that when the activities at the capital
market in enhanced and the number of firms trading their shares at the capital
market improves their likely to be positive economic growth. The value of the
coefficient of capital market capitalization shows that for every one-unit
increase in capital market capitalization, Economic growth increases by
.8682275 units. The researcher also sought to establish the effect of mobile
banking on economic growth finding that mobile banking had a statistically
significant effect on economic growth (β3 = .0621813, p = 0.001 <
α = 0.05). The value β3 was positive showing that any increase in
mobile banking leads to economic growth in Kenya. The effect was statistically
significant implying that mobile banking is a major contributor to the economic
growth of Kenya and that mobile banking leads to improved economic growth by
allowing economic units access to financial services including deposits,
transfer of money, payment of transactions and credit, all this mobile banking services
have the potential of stimulating economic growth. The value of the coefficient
of mobile banking shows that for every one-unit increase in mobile banking
activities, the rate of economic growth increases by .0621813 units. The study
established that Direct capital inflows had a statistically significant effect
on economic growth measured by GDP (β4= .4853428, p = .000 < α =
0.05). The value β4 was positive showing that an increase in direct
capital inflow from abroad leads to improved economic growth in Kenya. The effect
of direct capital inflow was statistically significant implying that the inflow
of funds from abroad inform of foreign investment, transfers from Kenyan
citizens living abroad and repatriation of profits back home from Kenyan firms
abroad leads to improved financial deepening as more funds are made available
for investment purposes that should translate to economic in Kenya. The value of the coefficient of direct
capital inflows shows that every one-unit increase in direct capital inflow
leads to improved economic growth by .4853428 units.
6. Conclusions
Given the fact that banking
deposits had a statistically insignificant effect on economic growth measured
by GDP, the study concludes that banking deposits had a weak effect on economic
growth because it is not enough to generate savings that lie idle in commercial
banking institutions. For savings to contribute to meaningful economic growth,
the funds need to be invested in economic activities. Given that Capital Market
capitalization had a statistically significant effect on economic growth, the
study concludes that there was a strong relationship between capital market
capitalization and economic growth and that an enhanced number of firms trading
their shares in the capital market improves their likelihood of being positive
economic growth. Given that the findings
showed that mobile banking had a statistically significant effect on economic
growth, the study concludes that mobile banking is a major contributor to the
economic growth of Kenya and that mobile banking leads to improved economic
growth by allowing economic units access to financial services including
deposits, transfer of money, payment of transactions and credit. Finally, given
that Direct capital inflows had a statistically significant effect on economic
growth the study concludes that direct capital inflow has a major and strong
relationship with economic growth since funds from abroad lead to improved
financial deepening as more funds are made available for investment purposes
that should translate to economic in Kenya. The current study has roots in the
empirical literature. A study by Nwanna and Chinwudu (2016) established that both bank-based and stock
market financial deepening proxies have significant and positive effects on
economic growth and that the banking sector and stock market in Nigeria have an
important role in the process of economic growth. A paper by Bakang (2015)
revealed that liquid liabilities, credit to the private sector,
commercial-central bank assets and commercial bank deposits have positive and
statistically significant effects on GDP. A study by Gries, Kraft and Meierrieks (2009) detected only limited support for causal
interactions between financial depth and economic development.
Based on the findings and
conclusions of the study, several recommendations can be made. Given that
banking deposits lead to an increase in economic growth in Kenya and that the
relationship between banking deposits is not strongly associated with the economic
growth of Kenya. The study recommends that the government should not just focus
on savings mobilization in the economy rather they should focus on policies and
strategies that translate savings to investments. For savings to contribute to
meaningful economic growth, the funds need to be invested in economic projects.
Given that the relationship between capital market capitalization was
statistically significant implying that when the activities at the capital
market in enhanced and the number of firms trading their shares at the capital
market improves their likely to be positive economic growth. The study
recommends that the government should continue strengthening the capital market
by putting in place a supportive business environment that encourages the setup
of companies that may list their shares at the Nairobi securities exchange. The
government through capital market authority should put in policies to attract
capital into the capital market. Because mobile banking had a statistically
significant effect on economic growth, the study concluded that mobile banking
is a major contributor to the economic growth of Kenya. The study recommends
that the government of Kenya through the central bank and communication
authority should continue strengthening mobile banking. Strong mobile banking
should lead to improved economic growth by allowing economic units access to
financial services including deposits, transfer of money, payment of
transactions and credit. Finally, given that Direct capital inflows had a
statistically significant effect on economic growth and the conclusion that
direct capital inflows were strongly related to economic growth, The study
recommends that the government continue putting in place policies that
encourage improved capital inflows from abroad. The inflow of funds from abroad
in the form of foreign investment, transfers from Kenyan citizens living abroad
and repatriation of profits back home leads to improved financial deepening as
more funds are made available for investment purposes that should translate to
economic in Kenya.
Conflicts of Interest
“The authors declare no conflicts of interest.”
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