Determinant of Private Sector Credit and Its
Implication on Economic Growth in Nigeria: 2000-2017
Olorunmade
Gbenga
Department of
Banking and Finance
Faculty of
Management Science, Kogi State
University, P.M.B
1008, Anyigba, Kogi State, Nigeria
E-mail:[email protected]
Samuel Olusegun James
Department of
Banking and Finance
Faculty of
Management Science, Kogi State
University, P.M.B
1008, Anyigba, Kogi State, Nigeria
E-mail: [email protected]
Adewole� Joseph�
Adeyinka
Department of
Banking and Finance
�Faculty of Management and Social Sciences
Adekunle Ajasin
University
P.M.B 001, Akungba
Akoko, Ondo State, Nigeria
E-mail: [email protected]
Abstract
The
study examined the determinant of private sector credit and its implication on
economic growth in Nigeria. The fluctuation in the supply of money and credit
is the basic causal factor at work in cyclical process; when money supply
falls, prices decrease, profit decrease, production activities become sluggish
and production falls and when money supply expands, price rise, profit increase
and the total output increases and finally growth takes place. The main
objective of this study is to examine the relationship between Private Sector
Credit and Gross Domestic Product. Data were obtained
from Central Bank of Nigeria statistical bulletin. Simple regression analysis
was used to achieve the stated objective. It was revealed in the determinant of
credit supply equation 1 that there was significant relationship between Total
credits to private sector and money supply in Nigeria. It was also discovered
in the Private Sector Credit and Economic Growth Equation 2�that
there was significant relationship between
private sector credit and economic growth in Nigeria. The study therefore
recommends that there should be persistence increase of money supply
to Nigerian economy in order to increase the flow of credit to the real sector
of the Nigerian economy, financial institutions should distribute more credit
to the real sector for productive purposes in order to increase Gross domestic
product.
Keywords: Private
Sector Credit, Money Supply, Economic Growth, Gross Domestic Product, Credit
Supply.
The debate on
the role of finance in economic development has been an ongoing one, especially
in developing countries. This dates back to the work of the likes of Schumpeter,
(1911) who advocated the concept of finance-led growth.� The financial intermediation role is
generally performed by the financial sector, which channels savings into
productive investment. Deposit-taking institutions in particular are well
recognized for performing the crucial role of sourcing finance to support
private sector consumption and investment in Nigeria. Credit to private sector
refers to financial resources provided to the private sector, such as loans and
advances, purchases of non-equity securities, trade credits and other accounts
receivable, which establish a claim for repayment.� In this regard, credit can be viewed from two
angles; namely: trade or commercial credit and banking system credit. Freear
(1980), says trade credit refers to transactions which involve the supplier
handing over goods or performing a service without receiving immediate payment
and payment to be made in the future.
Several
empirical studies have shown that the efficient provisioning of credit has a
positive and significant effect on output and employment opportunities while a
low level of financial development and its attendant inefficient private sector
credit system distorts economic growth.�
A strong and inclusive financial system; and availability of investable
funds play vital roles in financing economic project and activities that would
promote economic growth and development. This is because access to credit
enhances the productive capacity of firms and enhances their potential to grow.
In recent years,
private sector credit and economic growth linkage has been a major issue in
economic discourse all around the world and empirical literature has been
inconclusive on this issue. However, balance of evidence seems to favour a
positive relationship between private sector credit and economic growth.� This belief has led the Nigerian government
through the Central Bank of Nigeria to continue to build a robust and inclusive
financial system to fast track economic growth and to serve as a growth
catalyst to other emerging economies in Africa.�
Economic growth has long been considered an important goal
of economic policy with a substantial body of research attempting to explain
how this goal can be achieved. Most of the empirical studies have focused on
explanatory variables selected on the basis of their relevance to policy
formulation or base on their theoretical relevance. However, Banks play very
important roles in the economic development and growth of any nation. As an
important component of the financial system, they channel scarce resources from
the surplus economic units to the deficit economic units in an economy
(granting credit) as such this activities form part of their existence. The
loan resources (Bank Credit) can be in the form of short term credit, medium
term credit, long term credit and contingent fund. Thus, these Bank credits to
a reasonable extends, exert reasonable influence on the pattern and trend of
economic growth in Nigeria.
There is a
general consensus that for economic growth to take place there should be strong
support from the financial sector which provides a source of funds. The role
played by finance of bringing together borrowers and lenders cannot be under
estimated in the modern society. The important role of financial development in
fostering growth and that their association is of a long term is supported by
several studies, (Cecchetti and Kharroubi (2012), Osman (2014)). The banking
sector attracts deposits which can either lie idle or be used productively. The
banking sector changes deposits into assets that are advanced to the private
sector. The private sector supports economic growth in the country and the
availability of financial assets provides huge mileage to this sector in
advancing growth. These resources can be in the form loans, non-equity
securities, trade credit and accounts receivables which generate a claim for
repayment. The amount of resources available is limited due to the fact that
part of it is taken by the government. The advancement of debt to the
government has a potential of crowding out debt to the private sector which
subsequently affects growth of output. Credit to the private sector can have a
positive impact on sectoral GDP, (Were et al (2012) and Iqbal et al (2012)).
2. Statement of the Problem
Modern theories of economic
growth have attempted to explain the relationship between the private sector
credit and economy growth factors and specify the condition under which an
economy would steadily grow on the equilibrium path. Most economical of the
world have experienced business cycles at different stages of their economic
growth. The economic history of various economies is in fact a history of ups
and downs, booms and slump prosperity and depression. Business cycles influence
business decisions tremendously and set the trend for future business. The
period of prosperity opens up new and longer opportunities for investment,
employment and production and thereby promotes business.� On the contrary, the period of depression
reduces business opportunities. A profit maximizing entrepreneurs must
therefore, analyse the economic environment of the period relevant for his
important business decision particularly those pertaining to forward planning.
According to Dwivedi,
(2008), Business cycle theories lay major emphasis on the monetary and credit
system in their analysis of business cycle popularly refers to as monetary
theory of business cycle. According to this theory the main cause of business
cycle is the fluctuation in monetary and credit market. The fluctuation in the
supply of money and credit is the basic causal factor at work in cyclical
process. Hawtrey in Dwivedi, (2008), opens that business cycles are nothing but
successive phases of inflation and deflation and all the changes in the level
of economic activities are only reflections of changes in money flows. He
stated further that when money supply falls, prices decrease, profit decrease,
production activities become sluggish and production falls and when money
supply expands, price rise, profit increase and the total output increases and
finally growth takes place. He concluded that the principal factor affecting the
money supply is the credit mechanism i.e. the volume of credit created by the
banking and non-banking system. Following this assertion that money supply
forms the bedrock of business cycle through credit flow into the system; it is
imperative to look intently at various factors that would determine the volume
of credits that goes into the economy at a particular period of time so as to
maintain economic stability.
3. Objectives of the Study
The major objective of this
study is to examine
the relationship between Private Sector Credit and Gross Domestic Product.
Specific objectives are to:
�
Examine the relationship between Credits to private
sector�and Money Supply in Nigeria.
�
Examine the
relationship between Gross Domestic Product and
Credit to private sector�in
Nigeria.
4. Statement of Hypotheses�������������������������������������������������
�
Ho:� There is no significant
relationship between Credits to private sector�and Money
Supply in Nigeria.
�
Ho:� There is no significant relationship
between Gross Domestic Product and Credit to private sector�in
Nigeria.
5. Significance of the Study
There is the need to deepen
the financial sector and reposition it for growth and integration into the
global financial system in conformity with international best practices. One of
the most important policy concerns in most countries is the effect of private
sector credit on growth and development.
This study is important at
this level of economic development when efforts are being made to reposition
the financial system to enable it play key roles in economic development of
Nigeria. The study essentially examined in an empirical manner, the nature of
financial deepening in Nigeria since 2000 up to 2017 representing era of
financial sector reform in Nigeria. The study ascertained the critical factors
that have affected the level of private sector credit flows in Nigeria.
This study was justifiable since it employed the crucial methodology
analysis used in examining the flows of credit by financial institutions in
Nigeria. Thus, the study followed the work of Laffont and Garcia (1977) and
Blundell-Wignall and Gizycki (1992) which was modified to suite the Nigerian
case by Adeoye (2003) as a result of its distinguishing factors that affect
both the demand and supply of banks� credit to the economy. While most studies
conducted on bank credit and growth examined the banks activities up to 2003
(Adeoye 2003; Oluitan 2003), the periods covered also made the study unique to
others. It covered eighteen years ranging from 2000 to 2017 in Nigeria.
Although, the relationship between credit and economy growth has been well
documented in both international and domestic literature, this work added to
the research by examining the relationships within individual sectors which is
a quiet departure from previous studies that focused on aggregate credit growth
level. This is equally of value to policy makers since it identified which
sectors are most efficient in their use of credit.
6. Literature Review
Determinants
of Credit to Private sector
Financial
institutions like banks, pension funds, insurance corporations and foreign
exchange companies provide financial resources in the form of loans, trade
credit, purchases of non-equity securities and other receivables to the private
sector. The total of such monies is expressed as a percentage to GDP to give
credit to private sector. Empirical work focuses on the effect of different
factors on the level of financial resources extended to the private sector.
Evidence shows that the drivers of credit to private sector can either have a
positive or a negative effect. Studies that show factors which have a negative
influence are several. Hofmann, (2001) shows that innovations in short term
interest rates have a significant negative effect on bank credit, Gross
Domestic Product and property prices. Standard demand factors failed to explain
the development of credit over the long term. This study showed that the long
term negative relationship between credit to private sector and interest rates
could only be explained by including property prices in the model. Abuka and
Egesa (2007) argued that government borrowing from banks, a proxy of government
debt, crowded out the extension of credit to the private sector within the East
African Region. This was supported by Sogut, (2008) who showed that in the high
income countries private sector credit is negatively related to central
government debt. The other factors that reduce extension of credit to the
private sector include prime lending rate and reserve ratio, Enisan and Oluwafemi,
(2015). This is consistent with a study by Sharma and Gounder, (2012) which
shows that, in a regional grouping, factors which are detrimental to growth in
credit to private sector include average lending rates and inflation.
Pissarides,
(2001) provides evidence that one of the major challenges experienced by the
private sector is the failure by the local banking sector and the under
developed financial markets to respond to the demand for finance. A banking
sector that is under capitalized with low liquidity often fails to support the
private sector. This is worsened by inadequate legal and regulatory environment
and poor effective supervision by the central bank. Rashid (2011) also provides
evidence that an increase in foreign banks in the financial sector where there
is overreliance on non-deposit based funding will lead to less resources being
extended to the private sector. This is so because an increase in foreign banks
results in less deposits being attracted by local banks and these foreign banks
tend to allocate less of their deposits to the private sector. In the end local
banks will lend less to the private sector due to a limited deposit base. Haas
and Lelyveld (2002) argued that foreign banks can be a source of cross border
credit as they supply more financial resources to their subsidiaries especially
during crisis periods. Thus it may be beneficial to increase the level of
financial liberalization in the banking sector to attract more foreign
participation by banks to increase credit flows to the private sector.�
There is strong
evidence in literature supporting the existence of positive relationship
between private sector credit and factors like economic growth in both the
short and long term. Studies reviewed from literature shows that the factors
that have a positive influence on credit to private sector include broad
money� supply, cyclical risk premium,
stronger economic growth, GDP per capita, democracy, financial deepening, rule
of law, liquidity ratio, trade openness, investment profile, socioeconomic
factors, financial liberalization and real interest rate, exchange rate,
private domestic savings, external debt, (Enisan and Oluwafemi (2015), Touny
(2014), Raza et al (2014), Assefa (2014), Anthony (2012), Iqbal� et al (2012), Rachdi and Mensi (2012) and
Frimpong� and Marbuah (2010)). However
Touny (2014) also argue that in the long term economic growth does not continue
to improve credit extension to the private sector but will instead have a negative
impact. A different perspective was brought by Atoyebi et al (2012) who argued
that growth in private investments are better explained by changes in the
political situation. The creation of an enabling environment through provision
of infrastructural facilities and security is necessary for the improvement in
the extension of credit to the private sector. As such private investment is
hindered by macroeconomic instability and political disturbances. There are
studies that show that a causal relationship may not exist between credit to private
sector and economic growth which shows the existence of a Schumpeterian
independent hypothesis, (Osman (2014) and Nezakati et al (2011) and Aliero et
al (2013)). Sogut (2008) showed that in the high income countries private
sector credit is positively related with Journal of Poverty, Investment and
Development of public sector debt, which is in contradiction to other studies.
According to Shijaku and Kalluci (2013) lending incentives are created by
having a lower cost of lending, reduced government borrowing and more
qualitative bank credit.�
Meaning of credit
Chester (1920) defines Bank
credit as credit extended by banks to borrowers. He stressed further that,
Bankers frequently use the term in the plural, meaning advances made to their
borrowing customers. Whether the borrower withdraws the amount of the proceeds
of his loan in cash at once or leaves it on deposit with the lending bank, the
loan in either case constitutes credit extended. Just as a merchant extends
credit to he who pays for his purchase at a later time, so the banker extends
credit to the business man who borrows money. Whether the money is taken from
the bank at the time the loan is made, the next day, or ten days later, makes
no essential difference; bank credit may take even the form of an overdraft.
Credit has been described as a device for facilitating transfer of purchasing
power from one individual or organization to another. As indicated by Oyatoya
(1983) credit provides the basis for increased production efficiency through
specialization of functions thus bringing together in a more productive union
the skilled labor force with small financial resources and those who have
substantial resources but lack entrepreneurial ability.
In general, total domestic
bank credit can be sub divided into two: credit to the private sector and
credit to the public sector. It has been empirically proved that credit to the
public sector is weak in generating growth within the economy because they are
prone to waste and politically motivated programmes which may not deliver the
best result to the populace while private credit had been observed to be the
dynamic instrument of accelerated growth (Beck et al 2005; Levine 2002;
Odedokun 1998; King and Levine 1993).
�Private sector credit is decomposed into two
categories: short-term credit that has contractual maturity of one year or less
and long-term credit that has contractual maturity longer than one year. Some
countries, most notably many of the transition economies, provide more detailed
data on credit maturity � up to one year, one to five years and longer than 5
years. Some countries report maturity longer than 7 or even 15 years. While it
would be interesting to investigate credit with different maturity structures
(e.g. medium-term, long-term, and �very long-term� credit), the only
categorization that is consistent across all countries is the one that divides
credit into short-term credit with maturity of one year or less and other
credits.
Determinants of Private
Sector Credit Flow and Economic Growth
The global financial crisis
has resulted in a worldwide slowdown of credit flows, which triggered a
discussion about the factors driving sluggish lending activity. Unlike previous
prominent crises (e.g. in East Asia and Latin America in the 1990s), the
current slowdown in lending is taking place in the absence of rising cost of
credit and amid record-low policy rates and monetary stimulus. Although the
decline in credit flows can be rationalized in view of the overall decline in economic
activity, some critics have argued that the slowdown of lending (despite
generally low interest rates) can be attributed to credit rationing by
financial institutions. According to this �credit crunch� hypothesis, in the
presence of asymmetric information interest rates do not equilibrate supply of
and demand for credit, and rational profit maximizing lenders deliberately
constrain the outflow of liquidity in an attempt to avoid the accumulation of
risky assets.
Understanding
whether sluggish credit activity is related to constrained supply or weak
demand for credit is important from a policy perspective. If the reduction of
credit flows is mainly a response to tightened credit standards by financial
institutions, then targeted monetary easing coupled with regulatory measures
aimed at relaxing prudential norms may be needed to remove the obstacles for
credit growth. Alternatively, if the reduction of credit flows is mostly driven
by the decline in credit demand amid slower business activity, then economic
policies aimed at expanding aggregate demand might be more effective in
stimulating credit growth.
The
interest rate structure is one of the most important indicators of the
financial sectors. It is also an important determinant of credit flow to the
private sector and overall investment activities. Lower lending rates and
liberal credit policy encourage higher flow of credit to the private sector
while rising lending rate and tight monetary policy which are essential tools
for controlling inflationary pressures, restrict credit flow to the private
sector (Economic Survey, 2007).
Hoffman,
(2001) asserted that Economic activity; interest rates and property prices may
affect credit via both credit demand and supply channels. Economic conditions
and prospects determine consumption and investment demand, and thus the demand
for credit. On the other hand, changes in economic activity are reflected in
firms� cash flow position and households� income. Cash flow and income
determine the ability of firms and households to repay their debts, so that
changes in economic activity may also affect the willingness of financial
institutions to extend credit. The state of economic activity may therefore
also determine the supply of credit.
Financing
costs, represented by market interest rates, have a negative effect on credit
demand. When interest rates go up, loans become more expensive and loan demand
is reduced. A monetary tightening, reflected by an increase in interest rates,
may also induce financial institutions to cut back credit supply. A reduction
in credit supply may also arise from reduced creditworthiness of firms and
households due to a deterioration in their financial positions following a
monetary tightening (balance sheet channel of monetary transmission). A
tightening of monetary policy, operated via open market sales by the central
bank, may also drain reserves and thus loanable funds from the banking sector,
which may also cause a reduction of loan supply
Furthermore,
they also found that property prices may also affect both credit demand and
credit supply. Property accounts for a substantial share of household assets,
so that changes in property prices may have a significant wealth effect on
credit demand. Since loans are often secured with real estate collateral,
property prices may also have a significant effect on the borrowing capacity of
the private sector. An increase in property prices increases the value of
collateralisable assets and thus the creditworthiness of firms and households.
As a result, financial institutions are more willing to extend loans, so that
the supply of credit to the private sector increases. Thus, economic activity,
interest rates and property prices may affect both credit demand and credit
supply. The problem of identifying demand and supply effects in the analysis of
credit aggregates is well known and is most likely one of the reasons why there
are so few studies analyzing the determinants of credit aggregates.
Nevertheless, we still think that it is important to understand which factors
drive the development of credit aggregates, even if it is not possible to
clearly identify the demand and supply effects.
Empirical Review����
Goodhart,
(2008) investigates the determinants of credit growth in the United States and
the United Kingdom over a long sample period (United States 1995-2005, United
Kingdom 1995-2005). He finds that the change in house prices has a
significantly positive effect on credit growth in the United Kingdom, but not
in the United States. Rolling regression estimates suggest that in the United
Kingdom the relationship between credit and house price has strengthened over
the postwar period.
Borio
et al (2010) investigate the relationship between credit-GDP ratios and
aggregate asset prices for a large sample of industrialized countries over the
period 1990-2005. They find that the development of credit conditions as
measured by the credit-GDP ratio is in many countries a major driving force of
aggregate asset prices. Based on simulations of their estimated models they
show that the boom-bust cycles in asset markets of the early 1990s would have
been much less pronounced or would not have occurred at all had credit ratios
remained constant.
Good
hart and Hofmann, (2011) find cross-country evidence for a long-run
relationship between bank credit, GDP and residential property prices. Based on
impulse response analysis they also show that there is a two-way relationship
between credit and residential property prices. All these studies are reduced
form exercises, focusing on the existence of significant relationships and
paying less attention to structural interpretation. But, as we have already outlined
above, the identification of credit demand and credit supply effects of changes
in property prices is problematic, since property prices may affect both credit
demand and credit supply.
Odedokun,
(2013) analyses a sample of 71 developing countries over varying periods that
generally span 1991-2011 in order to generate information about the causality
issue. The findings are strongly in favour of the "finance causes
growth" hypothesis. Using time-series regression analysis, the author
comes to the conclusion that financial intermediation promotes economic growth
in roughly 85 Per cent of the countries. Secondly, financial intermediation
plays an equally important role in promoting growth as other factors, such as
export expansion, capital formation ratio, and is more important in this
context than labour force growth. Thirdly, he observes growth-promoting effects
of financial intermediation primarily in low-income LDCs. Interestingly he
finds that growth-promoting patterns of financial intermediation are practically
invariant across various countries and regions for the period. He shows that
marginal spillovers from the financial to the real sector are larger on average
than vice versa, but decrease over time and relative to marginal spillovers
from the real sector. He interprets this as an indication that finance caused
growth in earlier stages of Taiwan�s economic development while the
relationship was reversed later on. Some studies, however, come to a different
conclusion with respect to the causality issue.
Mattesini,
(2015) uses the lending-deposit spread as a proxy for monitoring cost related
to asymmetric information. His estimates refer to the period 1998-2013 and a
sample of forty countries. The spread is particularly significant in explaining
the growth performance for the whole sample and for the subsample of developed
economies. For the low-income subsample, however, there is no significant
relation between the spread and growth. The author attributes this to the
existence of financial repression in developing countries, which may also
affect the size of the spread.
Empirical
evidences revealed that, the most commonly cited reasons for the shortage of
long-term bank loans in Nigeria are the low levels of long-term liabilities in
the banking system that can be used as funding sources. The low levels of
long-term liabilities increase the maturities mismatch problem and raise the
liquidity risks, thus limiting banks� ability to issue long-term loans. Other
potential explanations include low quality and low transparency of borrowers
(opacity), high credit risks, weak protection of creditor rights, and low
efficiency of bank-level risk management systems.� While the legal and business environment is
systematic risk factors, other factors such as the availability of long-term
funds, the access to best corporate borrowers and the management team expertise
in controlling bank credit risks are bank-level factors that may vary
substantially across the Nigerian banking sector.
Merriest,
(2016), looked at the effect of financial sector reformation on the level of
investment in an economy. He investigated the extent to which financial
liberalization can improve private investment in developing countries. He made
used of a simple portfolio model of investment for Argentina from 1996 to 2013,
during which the country was affected by various interest rate regimes. His
findings show that the increase in� real
interest rate, which is a typical element of financial reforms, does not
necessarily involve a positive effect on private investment unless the
authorities are careful to ensure that bank deposits are closer substitutes to
unproductive assets (cash, gold) and foreign assets rather than capital goods.
The flow of domestic credit to the private sector is not absorbed by the need
of the public sector.
Moshi
and Kilindo, (2017) considered the effect of government policy on private
investment over the 2000-2015 periods in Tanzania. Regression results from the
ordinary least squares estimation technique among others, showed that the real
exchange rate had a negative and significant effect, indicating that
devaluation reduced the profitability of private investment in the Tanzanian
economy during the study period.
Critique
of Gaps in the Literature
Many
researchers have focused on private sector credit and economic growth but
majority of the researchers have failed to work on the determinant of private
sector credit. However, this study intends to make a different as it will
examine the determinant of private sector credit in Nigeria.
Theoretical Review
Theory of Economic
Growth
Economic growth is closely linked to the
intricacies of the financial system. A well developed and
efficient financial system helps in allocating financial resources to the best uses
in the real sector, thereby promoting economic growth. As the real sector
grows, the demand for financing increases and in this way the financial sector
grows in tandem with the economy, signifying a two way causal relationship
between finance and growth. In developed countries, financing generally flows
both from the banking system and the capital markets, while in most developing
and transition economies the capital markets lag behind, which shifts the
burden of financing to the banking system.
There are numerous
growth models in literature. However, there is no consensus as to which
strategy will achieve the best success. The achievement of sustained growth
requires minimum levels of skills and literacy on the part of the population,
(Nnanna, 2004). Some of these existing growth models are Two-Gap Model, Marxian
Theory, Schumpeterian Theory, and Harrods - Domar Theory of Growth,
Neo-Classical Model of Growth, and Endogenous Growth Theory. The growth models
relevant to this are Neo-Classical Model of Growth, and Endogenous Growth
Theory, since these growth models explain the situation in developing economies
such as Nigeria. The neo-classical model of growth was first devised by Robert
Solow. The model believes that a sustained increase in capital investment
increases the growth rate only temporarily. This is because the ratio of
capital to labour goes up (there is more capital available for each worker to
use) but the marginal product of additional units of capital is assumed to
decline and the economy eventually moves back to a long-term growth path, with
real GDP growing at the same rate as the workforce plus a factor to reflect
improving �productivity�. A "steady-state growth path" is reached
when output, capital and labour are all growing at the same rate, so output per
worker and capital per worker are constant. According to Todaro, the
Neo-classical economists believe that to raise an economy's long term trend
rate of growth requires an increase in the labour supply and an improvement in
the productivity of labour and capital. Differences in the rate of
technological change are said to explain much of the variation in economic
growth between developed countries. This is shown in the model below. The
aggregate production function, Y = F (K,
L) is assumed characterized by constant returns to scale. For example, in
the special case known as the Cobb-Douglas production, at time t we have
Y(t) = K (t)a (A(t)L(t)1-a�����������������������������(1)
Where Y
is gross domestic product, K is the
stock of capital (which may include human capital as well as physical capital),
L is labour, and A(t) represents the productivity of labour, which grows over time
at an exogenous rate. Because of constant returns to scale, if all inputs are
increased by the same amount, say 10%, then output will increase by the same
amount (10% in this case). More generally
γY =F(γK, γL)���������������������������(2).
where γ is some positive amount� (1.1 in the case of a 10% increase). Because
γ� can be any positive real number,
a mathematical �trick� useful in analyzing�
the implications of the model is to set γ� = 1/L, so that
Y/L=f (K/L, 1), or, y=f (k)���������������������� (3)
This simplification allows us to deal with
just one argument in the production function.
y=AKa���� ���������������������������
(4)
This represents an alternative way to think
about a production function, in which everything is measured in quantities per
worker. Equation 4 states that output per worker is a function that depends on
the amount of capital per worker. The more capital with which each worker has
to work, the more output that worker can produce. The labour force grows at
rate n per year, say, and labour
productivity growth, the rate at which the value of A in the production
function increases, occurs at rate λ. the total capital stock grows when
savings are greater than depreciation, but capital per worker grows when
savings are also greater than what is needed to equip new workers with the same
amount of capital as existing workers have.
The Solow equation (Equation 5) gives the
growth of the capital-labour ratio, k (known as capital deepening), and shows
that the growth of k depends on
savings sf (k), after allowing for
the amount of capital required to service depreciation, k, and after capital
widening that is, providing the existing amount of capital per worker to net
new workers joining the labour force, nk.
That is
∆k= sf (k) � ( δ+ n)k�
�����������������������(5)
For simplicity we are assuming for now that
A remains constant. In this case, there will be a state in which output and
capital per worker are no longer changing, known as the steady state. (If A is
increasing, the corresponding state will be one in which capital per effective
workers is no longer changing. In that case, the number of effective workers
rises as A rises, the job.)� To find this
steady state, set ∆k =0:
Sf (k*) = ( δ+ n)k*����������������������������������������(6)
The notation k* means the level
of capital per worker when the economy is in its steady state. The capital per
worker k* represents the steady state. If k is higher or lower than k*, the economy will return to
it; thus k* is a stable equilibrium. In the Solow equation, we see
that when (n +δ)k� < sf(k),∆k > 0. As a result, k in the economy is growing toward the
equilibrium point k*. by similar reasoning to the right of k*,(n + δ)k > sf (k) and as a
result ∆k < 0.
�By
the chain rule,
Y = dY = ∂Y∂K + ∂Y∂L� �����������������..............�� (7)
������
dt����� ∂K� ∂t�����
∂L� ∂t
By the exponent rule, we know that�
∂Y=A(α+β)Kα+β+1 L1-α��� ����������������������(8)
�
∂K
∂Y=AKα+β(1-α)L1-α1��� ����������������������� (9)
�∂L
Combining these three equations, we have
Y=dY/dt=[AKα+βL1-α][(α+β)
K + (1- α) L]���
�������(10)
��������������������������������������������������������������� K������������ L
The first term in brackets in the preceding
expression is of course output, Y. For a steady state, K/K, L/L, and Y/Y are
all constant. From the above
K= 1- δK = sY � δK������
������������������������. (11)
Dividing this expression through by K, we
have
K = sY � ���������
���������������������������. (12)
For K/K constant in the preceding
expression, we must have Y/K constant. If this ratio is constant, we have
K = Y = g. a constant growth rate
So from the expression for dY/dt in the
preceding expression, for the aggregate production function, with L/L = n,
which is also a constant, we have
Y=(α+β)(K)+(1-α)L g = (α
+β)g + (1 � α)n�������
������������� (13)
��������������������������������� [1
� (α + β)]
7. Methods for achieving the stated objectives
The strategies used
for achieving the stated objectives were simple regressions of which two
equations were formulated in order to achieve the three specific objectives
stated. In the equations, the hypotheses stated were tested. The equations are
Determinant of credit supply equation 1, Private Sector Credit and
Economic Growth Equation 2. Several authors have also used this approach in their works (Reinhart
& Tokatlidis, 2000; Olukotun, Adewole
& James, 2015; Popoola M.A, Adewole J.A & Idih O.E, 2018) and they were able to arrive at unbiased and
accurate results. As a result of this, the approach of regression analysis
cannot create a weakness in terms of the results presentation. The data used
for this study were source from Central Bank of Nigeria Statistical Bulletin
which is Total Credit to Private sector, Total Money Supply and Gross Domestic
Product.
The data were choosing to examine the
determinant of private sector credit and also measure the relationship between
private sector credit and economic growth.
8. Discussion on Findings
The data collected for
analysing the determinant of private sector credit and its implications on
economic growth in Nigeria was presented in Appendix (see appendix A).
EQUATION 1: From the results of the determinant of credit supply equation I, the correlation coefficient (R) was 0.996. This means that there was a
strong correlation between dependent and independent variable. The coefficient
of determination (R-Squared) was 99.2%. This means that 99.2% variation in the dependent
variable was explained by the independent variable and 0.8% of the variation in
the dependent variable is explained by the disturbance term or error term. This
disturbance terms are inflation, economic meltdown, low productivity, low
profitability, non-performing loans etc. In other words, 99.2% variation in
total credit to private sector was well explained by variation in money supply.
0.8% variation in the dependent variable was explained by variation of the
variables excluded from the model (see appendix B).
The confidence
intervals result revealed that the level of confidence interval 95%. This means
that the samples data of the model reflects the fraction of calculated
confidence intervals that encompass the true population.The Durbin-Watson result
is 1.511. The Durbin-Watson statistics is a number that tests for
autocorrelation. Autocorrelation is a mathematical representation of the degree
of similarity between lagged versions of itself over successive time intervals.
In other words, it is a situation in which a time series data is influenced by
its own historical values. The Durbin-Watson statistics is always between 0 and
4. The general rule states that a value of 2 means that there is no
autocorrelation in the samples. Values approaching 0 indicate positive
autocorrelation and values towards 4 indicate negative autocorrelation.
However, the Durbin-Watson result of this model indicated there is autocorrelation
since the value of 1.511 is not up to 2. The Collinearity Diagnostics result
reveals that Variance Inflation Factors (VIF) is 1.00. The general rule is that
VIFs exceeding 4 warrant further investigations while VIFs exceeding 10 are
signs of serious multicollinearity requiring correction. Since VIFs result is
1.00 in this model, it does not require further investigations (see appendix
B).
Testing for the statistical significant at 5% (Determinant of credit supply equation 1)
Ho:��������� bβ
� Ho: There is no significant relationship between credit to
private sector and money supply in Nigeria.
Decision
t0.05 at (18 � 2)
16 degrees of freedom was statistically significant because the analysis of
variance (ANOVA) P � value < 0.05; p - value = 0.000 . Therefore, H1
is accepted and Ho is rejected. There was significant
relationship between Total credits to private sector and
money supply in Nigeria. This means that there is enough money supply that guaranteed
enough credit to the real sector of the Nigerian economy (see appendix B).
EQUATION 2: From the results of Private Sector Credit and Economic Growth Equation
2, the correlation coefficient (R) is 0.989. This means that there is a
positive or strong correlation between dependent and independent variable. The coefficient of determination (R-Squared) is 97.7%. This means that
97.7% variation in the dependent variable was well explained by the independent
variable and 0.23% of the variation in the dependent variable is explained by
the disturbance term or error term. This disturbance terms are inflation,
economic meltdown, low productivity, low profitability, non-performing loans
etc. In other words, 97.7% variation in Gross Domestic Product was explained by
variation in total credit to private sector. 0.23% variation in the dependent
variable is explained by variation of the variables excluded from the model
(see appendix C).
The confidence intervals
result revealed that the level of confidence interval 95%. This means that the
samples data of the model reflects the fraction of calculated confidence intervals
that encompass the true population. The Durbin-Watson result is 1.376. The
Durbin-Watson statistics is a number that tests for autocorrelation.
Autocorrelation is a mathematical representation of the degree of similarity
between lagged versions of itself over successive time intervals. In other
words, it is a situation in which a time series data is influenced by its own
historical values. The Durbin-Watson statistics is always between 0 and 4. The
general rule states that a value of 2 means that there is no autocorrelation in
the samples. Values approaching 0 indicate positive autocorrelation and values
towards 4 indicate negative autocorrelation. However, the Durbin-Watson result of
this model indicated that there is autocorrelation since the value of 1.376 is
not up to 2. The Collinearity Diagnostics result reveals that Variance
Inflation Factors (VIF) is 1.00. The general rule is that VIFs exceeding 4
warrant further investigations while VIFs exceeding 10 are signs of serious
multicollinearity requiring correction. Since VIFs result is 1.00 in this
model, it does not require further investigations (see appendix C).
Testing for statistical significant at 5% (Private
Sector Credit and Economic Growth Equation 2).
Ho:�������� bβ
� Ho:� There
is no significant relationship between private sector credit and economic growth in Nigeria.
Decision
t0.05 at (18 � 2)
16 degrees of freedom was statistically significant because Analysis of
variance (ANOVA) P � value < 0.05; p - value = 0.000 . Therefore, H1 is
accepted and Ho is rejected, meaning that bβ is not equal to zero i.e.
there was significant relationship between private sector
credit and gross domestic product in Nigeria. This means that private sector credit
impacted positively on economy growth in Nigeria within the period of analysis
(see appendix C)����������������������������������������������������������������
9. Conclusion
It was obvious
from the results of the study that the financial sector reform strategies
adopted in Nigeria have been geared towards making credit available to support
the economy. As a result of this, supply of credit to the real sector has been
improved.
10. Recommendations
Base on the
objective and findings of this study, the study therefore recommends that:
� There should be
persistence increase of money supply to Nigerian economy in order to increase
the flow of credit to the real sector of the Nigerian economy.
� Financial
institutions should distribute more credit to the real sector for productive
purposes in order to increase Gross domestic product.
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