Download Domestic Macroeconomic Policies and Private

Domestic Macroeconomic Policies and Private
Fixed Capital Formation in Nigeria:
A VAR Approach
By
Okoli, R. Obioraa
Onah, F. E. b
Amalaha, R. Obinnac
and
Nwosu, O. Christiand
June, 2007
Domestic Macroeconomic Policies and Private Fixed Capital Formation
in Nigeria: A VAR Approach
Abstract
The study has as its objectives, to determine the impact of macroeconomic policies on
private capital formation in Nigeria. In addition, the study sought to evaluate ipso facto
the pattern of responses of private investment to shocks on macroeconomic Policies.
And finally, to determine the causal ordering of the mediating variables connecting
private investment and macroeconomic variables. The study applied the co- integrated
vector autoregressive framework. The first objective of the model was resolve by
estimating the short run dynamic error correction model. For the second objective,
VAR model was estimated to determine the impulse response functions and variance
decomposition using Cholesky decomposition so as to determine the response of private
investment to shocks on macroeconomic policies. The third objective was resolved by
conducting a granger causality test. Empirical investigation reveal that macroeconomic
policies like, interest rate policy, exchange rate policy, the size of the public sector,
domestic credit policy and the real GDP growth plays a prominent role in the
performance of private investment in Nigeria. The results of both the dynamic short
run model, impulse response and pair wise Granger causality test revealed that
domestic credit to the private sector exerts a more significant influencing on the
performance of the private investment. The study recommends that the expansion of
the banking sector loanable fund to the private sector should be at the heart of the
monetary policy design in Nigeria. In addition, the terms on which banking sector
advances are extended to private investors should be reviewed and efforts should be
intensified to wipe off all unofficial parallel markets or the so-called black market
since they facilitate not only faster depreciation of the Naira through round tripping
there by facilitating facilitate huge capital flight and illegal transfer of funds.
Keywords:
Domestic Macroeconomic Policies; Private Fixed Capital Formation; VAR Model
____________________
a
Department of Economics, University of Nigeria, Nsukka.
Tel: +234-803-094-5881. E-mail: [email protected]
b
Prof. Onah, F.E is the Head of Department, Department of Economics,
University of Nigeria, Nsukka
c
Development Economics Unit, Department of Economics, University of Nigeria, Nsukka.
Tel: +234-803-362-8283, 802-373-6892. E-mail:
[email protected]
d
Department of Statistics, University of Nigeria, Nsukka.
Tel: +234-805-324-1950. E-mail: [email protected]
ii
List of Tables
Table 4.1:
Table 4.2:
Table 4.3
Table 4.4
Table 4.5
Table 4.6
Table 4.7:
Unit Root Statistics
Johanson Co- integration Test Statistics
Impulse Response for Private Investment
Variance Decomposition for Private Investment
Impulse Responses for GDP
Variance Decomposition for GDP
Result of Granger Causality Test
iii
Table of contents
Abstract………………………………………………………………………………... ii
List of Tables…………………………………………………………………………….iii
Chapter one: Introduction
1.1Background…………………………………………………………………………...1
1.2 Problem Statement………………………………………………………………….3
1.3 Objective of the Study……………………………………………………………....7
1.4 Hypothesis…………………………………………………………………………...7
1.5 Scientific Contribution……………………………………………………………...7
1.6 Significance of Study
1.7 Scope of the Study…………………………………………………………………...8
Chapter two: A Review of Literature…………………………………….9
2.1 Theoretical Underpinnings………………………………………………………….9
2.2 Empirical Literature……………………………………………………………….15
2.3 Limitations of Previous Study……………………………………………………..19
Chapter three: Methodology……………………………………………..20
3.1 The Model…………………………………………………………………………..20
3.2Model Justification…………………………………………………………………..23
3.3 Estimation Procedure………………………………………………………………24
3.4 Method of Results Evaluation……………………………………………………...25
3.5 The Data……………………………………………………………………………..26
Chapter Four: Presentation and Interpretation of Empirical
Results……..................................................................................................27
4.1 Result Presentation…………………………………………………………………27
4.2 Unit Root Analysis………………………………………………………………….27
4.3 Co Integration Analysis…………………………………………………………….28
4.4.1 Short-Run Dynamic VAR Model………………………………………………..29
4.4.2 Impulse Response and Variance Decomposition……………………………….31
4.4.3 Granger Causality Test…………………………………………………………..37
4.5 Evaluation of Hypothesis…………………………………………………………...40
4.6 Police Implications of Findings…………………………………………………….41
Chapter five: Summary, Policy Recommendation and Conclusion.......42
5.1 Summary of Findings………………………………………………………………42
5.2 Policy Recommendations…………………………………………………………...43
5.3 Conclusion…………………………………………………………………………..44
iv
Chapter one
Introduction
1.1 Background
The impact of macroeconomic policies on private capital formation, a topic of obvious
concern to policy makers, has attracted considerable interest in the analytical and
empirical literature. Economic theory has paid considerable attention to this debate.
Taken as a whole, however, the theoretical predictions are ambiguous. Depending on
their underlying assumptions, some approaches predict a negative relationship, while
others predict a positive one.
Empirical literature on growth has consistently showed that the rate of accumulation of
physical capital or investment is an important determinant of economic growth. Results
provide evidence that public capital investments are a key input in the private sector
producion process for they affect both the steady state level of income per capita and the
rate of economic growth on the transition paths towards the equilibrium (Nair, 2005).
Furthermore, there are other important empirical evidences why private investment
should be at the centre of the debate on how to promote growth and raise employment.
Ndikuman (2005), while accepting that investment is a robust determinant of growth,
especially equipment investment, believe that private investment is a key determinant of
cross-country difference in long run economic growth. This has led observers to identify
low investment as one of the leading causes of the slow growth in developing countries in
general and in African countries in particular. The UN Millennium Project (2005) has reemphasized the need for a big push strategy in investment to help poor countries break
out of their poverty trap and achieve the Millennium Development Goals (MDGs). The
report argues further that, to enable all countries achieve the MDGs, there should be
identification of priority private investments to empower poor people, and these should
be built into MDG-based strategies that anchor the scaling-up of private investment..
In more than 40 years since independence, Nigeria has never grown at 7 percent or more
for more than three consecutive years (NEEDS, 2004).
Between 1975 and 2000,
Nigeria’s broad based macroeconomic aggregate-growth, the terms of trade, the exchange
1
rates, government revenue and spending – were among the most volatile in the
developing world. The economy has been caught in a low growth trap, characterized by
a low savings – investment equilibrium (at less than 20 percent). With an average annual
investment rate of barely 16 percent of GDP, Nigeria is far below the minimum
investment rate of about 30 percent of GDP required to unleash a poverty reduction
growth rate of at least 7 – 8 percent per year (NEEDS, 2004). A fairly large and growing
literature has developed around attempts to explain this poor growth performance. In
providing what is perhaps one of the best reviews of literature, Collier and Gunning
(1999) zero in on several important factors whose impact on African growth performance
is mediated through their negative implications for investment, particularly private
investment. In their view, “cumulatively” the variables have contributed to a capital
hostile environment. This in turn has reduced the rate of return on private investment.
These factors include: high risk, capital hostile environment, poor finance and low
savings
In Nigeria, unsurprisingly, the policy orientation has been akin to that of other developing
countries in manifesting an increasing reorganization of the potential role the private
sector could play in mobilizing the country’s formidable and copious natural and human
resources. These concern, however, do not seem to have been matched by an appropriate
and consistent blend of policies to bolster private sector investment. The reported
performance of private investment in Nigeria has been less than satisfactory, and slightly
less than the average for Sub-Sahara Africa (SSA). The Nigerian private sector spent only
around 21 percent of the countries national income over the period 1970-1980. The
period 1981-1991 marked a notable low performance with private investment/GDP ratio
of only 11 percent (The corresponding average for SSA was around 14 percent). By
1992-2003, it fell further to 7 percent (CBN, 2004). Not only has private investment been
diluted over the 1980s and has remained so over the period 1990 – 2000, it has also been
volatile. To use the 1980s as an example, private investment as a percentage of GDP
dropped from 21 percent to 19 percent from what it was in 1970-1980 representing a drop
of 47 percent. Between 1991- 2003, it further dropped by 36 percent from 11 percent to 7
percent CBN (2004). This poor performance is attributed to successive attempts to
2
sustain fiscal balances and external balances by a pursuit of credit restraints to galloping
inflation, and to a continual devaluation of domestic currency to correct price distortion
and accumulate foreign resources.
Prescription of solutions to the poor performance of private investment that characterized
a growing economy like Nigeria is of great policy concern. To what extent is there really
a relationship between private capital formation and macroeconomic policy? Particularly,
there are unresolved questions regarding the powers of a country’s domestic monetary
and fiscal policies in bolstering private capital formation. Ndicumana (2005) stated that it
is largely within the power of developing countries to boost private capital formation by
adopting appropriate blend of domestic policies on domestic credit to the private sector,
the exchange rate, interest rate and fiscal policies. But this has not been fully supported
by the country’s experience as shown in the poor performance of private investment. This
further casts doubts on the ability of the country to induce “investment transition” which
is required to meet the MDGs of reducing poverty by scaling up private investment.
1.2 Problem Statement
Investment is key to economic growth.
Empirical studies like (Khan and Reinhart, 1990;
Kormendi and Mcquire, 1985; Lucas, 1988; Barro and Lee, 1994; Barro, 1995; Ghura
and Hadjimichael, 1996; Kehoe and McGrattan, 1999; Hernandez, 2000; Elenog and
Jayaraman, 2001; Ndikumana, 2000; and 2005) conducted in Africa have established
beyond doubt, the critical linkage between investment and the rate of growth. These
researchers further posit that private investment has a stronger more favourable effect on
growth than government investment. According to Hermandez – Cata (2000), the ratio of
private investment to GDP in sub-Saharan African countries had experienced poor rate of
growth between 1980s – 1990s. He stated further that private investment GDP/ratio was
less than 10 percent, compared with 16 percent in Latin America, 18 percent in advanced
countries and 16.5 percent in newly industrialized countries in Asia.
Viewed against the background of growing evidence of a strong link between high
investment and sustainable growth, a steady decline since 1980s of private fixed
3
investment in Nigeria has been a matter of considerable concern to policy makers. The
poor performance as experienced in Nigeria is akin to other countries in the region of
Sub-Saharan Africa. The private investment as a percentage of GDP, which was 19.1
percent in 1970, dropped to an average of 18.4 percent by 1980. By 1981-1990, it
dropped further to 11 percent and to 7 percent of GDP between 1991-2003 (CBN, 2004).
This poor performance has persisted despite efforts made in the past to change the trend.
The performance of private sector capital expansion over the last three decades dropped
as a result of weak relationship between the banking sector and private capital expansion.
This issue has remained one of the most complicated in the policy-making process and
design in Nigeria. This is due to the fact that expanding banking sector loanable funds
and their potential effect on domestic credits are at the heart of the concern of monetary
policy as designed and implemented in developing countries (Badawi, 2004). Mostly
guided by the central objective of curbing inflation and lack of variety in monetary tools
and instruments, monetary policy in Nigeria adopt tight measures in the process of
constraining credit by setting administered controls on the direction and terms of credit to
the private sector. Nigeria experienced a markedly low credit to GDP ratio: banking
sector advances to the private sector fell from around 19.8 percent in 1980s to 12.7
percent in 1990s (CBN, 2004). This performance seems quite alarming, especially when
compared to the needs of a typical Sub-Saharan African country of at least 15 percent
credit/GDP ratio in order to achieve private investment/GDP ratio of as high as 26
percent (ADB, 2004). This poor performance of the financial sector in easing credit
constraint is attributed to the failure of the monetary authorities in Nigeria to design a
comprehensive framework that incorporates a complete set of monetary, institutional and
prudential objectives which strike at the same time an appropriate balance between
inflation targets and expansion in bank advances to the private sector. Inflation rate
measured in terms of percentage in consumer price index (CPI) escalated from an
average of 20.5 percent in 1980-1994 to an average of 25.4 percent in 1995-1999 and fall
to an average of 12.9 percent, between 2000-2003 (Asogwa, 2005). This was attributed
to the weakness in Nigerian fiscal policy framework or what can be termed fiscal
procyclicality (Batin, 2004).
4
While the debate on the right monetary approach to adopt is still going on, policy analysts
are yet to come to a consensus regarding the impact of fiscal policy on private capital
formation. The differences in outcome may at least partly be explained by
methodological weakness of these studies. A large number of studies focus on aggregate
variables of fiscal policy, such as consumption, overall taxes or budget deficits. Thus,
they disregarded the importance of the composition of fiscal policies and thereby
overlooked the possibility that different policies may have different effects on private
capital formation.
In some cases, it is not entirely clear whether any empirical
association between fiscal variables and private capital formation operates through third –
variables relevant to private investment. These have implications for policy advice for
countries currently struggling with structural imbalance.
This point seems intuitive enough, but it is still a point of contention in the literature. In
particular, Ndikumana (2005) claims that it is largely within the power of the country
concerned to adopt appropriate domestic policies (monetary, fiscal and exchange rate) to
bolster private capital formation. However, despite efforts made in the past to bolster
private investment, private fixed capital formation in Nigeria is still below the average for
SSA.
Is this effort worth it? This research believes it does. Having recognized the role of
private capital formation in the growth process and the fact that no work known to us has
made attempt to answer the question of whether domestic macroeconomic policy
simulate private capital formation in Nigeria? The researcher believes that investigating
this is indeed expedient owing to the fact that Nigeria is currently mobilizing for the
second phase of it developmental program termed NEEDS II.
The few existing studies on capital formation in Nigeria are not comprehensive. The
study by Ekpo (1999) is on public expenditure and growth. The work failed to look at the
role of monetary and exchange rate policies on private capital formation in Nigeria.
Badawi (2004) stated that the exchange rate policy of a country is very crucial especial to
5
the import dependent industries. Furthermore, the work failed to look at impulse
responses. Even at that, there is an urgent need to extend this study because of emerging
trends in Nigeria’s macroeconomic environment. .Iyoko (2006) investigated the
relationship between public and private investment in Nigeria. This work tends to
reinforce the findings by Ndikumana (2005) that public investment those not crowd out
private investment in Africa. The study failed to look at the present level of private
capital formation in Nigeria and the macroeconomic fundamentals responsible for this
dismal performance. The works by Akpokodje (2000), Ahmet and Gaobo (2005) are not
country specific, hence, the need to carryout a country specific assessment. These works
also did not investigate the magnitude of shocks transmitted from one variable to the by
testing for impulse responses and variance decomposition. The research lacuna is derived
from this gap.
This work will depart from existing studies (known to us) by assessing the impact of
macroeconomic policy on private capital formation in Nigeria using an econometric
framework encompassing other conventional determinants of investment, and applying a
range of estimation techniques that control for issues such as simultaneity, countryspecific effects and parameter heterogeneity, while investigating both the short run and
long rung effects of policies as neglected by past studies. In doing this, the mediating
variables responsible for the transmission of policies will be determined, while impulse
responses will be identified and variance decomposition will also be investigated using
Choleski decomposition. The research question arising from the above issues are as
follows:
1) What are the impacts of macroeconomic policies on private capital formation?
2) What is the pattern of responses of private investment to shocks on
Macroeconomic policies?
3) What is the direction of the causal ordering of the mediating variables connecting
Private investment and Macroeconomic policies?
6
1.3 Objectives of the Study
The objectives include
1)
To determine the impact of macroeconomic policies on private capital formation
in Nigeria.
2)
To investigate the pattern of responses of private investment to shocks on
macroeconomic Policies.
3)
To determine the causal ordering of the mediating variables connecting private
investment and Macroeconomic policies.
1.4 Research Hypotheses
1)
Macroeconomic policies have no impact on private capital formation in Nigeria.
2)
Private investment has no significant impulse responses in Nigeria.
3)
The mediating variables connecting private investment and macroeconomic
Policies have no causal ordering in Nigeria.
1.5 Expected Scientific Contribution
By using a VAR model to test the stated hypothesis, this work would have build a model
of private capital formation and macroeconomic policies for Nigeria by extending the
neoclassical accelerator model, taking into account some specific constraints faced by the
developing world. In doing so, the study presents four novelties:
1) The work will provide deeper understanding of the relationship between
macroeconomic policies and Private capital formation in Nigeria and expose the
impediments to investment growth in Nigeria.
2)
A VAR model will be used to assess the performance of private investment in
Nigeria.
3) The impulse response will indicate the magnitude of the shocks transmitted from one
variable to another (among the explanatory variables) and will serve as a guide on
Policy formulation as regards to investment in Nigeria.
4) The relationship between macroeconomic variables and private capital formation will
be tested in a Country specific approach method as opposed to the usual cross-country
analysis
7
1.6)
Significance of Study
This work set to determine the impact of macroeconomic policies on private capital
formation in Nigeria. Since economic literature has established that private investment is
an elixir to economic growth, a work of this nature is indeed expedient. This work by
providing a deeper understanding of the relationship between macroeconomic policies
and private capital formation in Nigeria will expose impediments o investment growth in
Nigeria.
1.7) Scope of the Study
This study will cover the period 1970-2004; a sample size of 35 years is necessary in
order to have enough observation for the computing of VARS
8
Chapter Two
A review of Literature
2.1 Theoretical Underpinnings
A number of theories have emerged to explain private investment behaviour in developed
countries. Though literatures are inconclusive in their assessment of the impact of
macroeconomic policies on investment, the majority does find a negative association
between both variable (Seven, 1998). Economic theory has paid considerable attention to
this debate, taken as a whole, the theoretical predictions are ambiguous. Depending on
their underlying assumptions some approaches predict a negative relationship, while
some predict a positive one.
Literature on private investment behavior in industrialized countries has distinguished a
set of factors determining firm’s investment decision. The basic of the majority of these
approaches and the simplest among them is the accelerator theory of investment, also
known as “acceleration principal”. It says that, other things being equal, an increase in a
firm’s output will require a proportionate increase in its stock of capital equipment. The
implication of acceleration theory is that, the level of output or the changes in aggregate
demand determines investment or the change in capital stock. That firm’s output required
would induce the firm to instantly increase its stock of fixed assets provided that it has
been operating at full capacity (clark, 1917; Manne, 1945; Timbergen, 1938). The
assumption of full capacity and instantaneous adjustment underlying the naive accelerator
principal were modified and a more realistic model termed the flexible accelerator model
or capacity utilization model was developed (Godwin, 1948, Chanery, 1952, Koyck,
1954). The concept of flexible accelerator says that, the adjustment of the capital stock to
the desired level is not instantaneous because of delivery lags and delayed response to
changes in the level of demand. As argued by Eisner (1963), the relationship between
current investment and current income or output is an oversimplification because the
current changes in the demand, output or Sales is not enough to sustain an increase in
investment. Thus the firms will opt for other ways of meeting the demand like running
down the inventories in fixing their investment.
9
The neoclassical theory of investment-founded by Jorgenson (1963)-provided another
explanation for investment expenditure in addition to changes in output. Inducement to
invest may also be simulated by favorable changes in relative prices where downward
shifts in the real user cost of capital services imply that the firm has to restore equilibrium
by cutting down the marginal productivity of capital stock (Jorgensen, 1963). Jorgensen
model is based on theory of optimal capital allocation. The theory of profit maximization
firm, subject to a production function through which a technical relationship between
inputs and outputs get defined is central in neoclassical model. Jorgenson’s basic
assumptions for a firm to maximize its present value are the rate of changes of the input
of capital services is equal to the rate of net investment; the relationship between level of
output and inputs of labour and capital services is constrained by a production function.
The production function also connects the capital stock to the relative price between
capital and output. The model assumes flexible accelerator princes and perfect capital and
other markets. It implies that, there are no liquidity constraints to adjust capital stock and
a general equilibrium situation with full employment. Empirical evidence is consistent
with this accelerator effect and shows that high output growth is associated with high
investment rates (Greene and Villanueva, 1991; wai and Wong, 1982). The decision by
the firm to invest is too complex to be determined only by output and relative prices as
the accelerator-- neoclassical framework suggest (Badawi, 2004). The cash theories of
investment built on the assumption that external funds are more expansive than internal
funds-argued that financial conditions internal to the firm in the form of liquidity
constraints and profit availability determine investment outlay in a given firm (Eisner,
1963; Grunfeld, 1960; Meyer and Glauber, 1964). This theory hinges on total profits or
profit rates earned by business unit and industries instead of output. This analysis has
several variants. The profit theory states that “greater the gross profits, greater will be the
level of internally generated funds and in turn greater will the rate of investment” Meyer
and Kuh (1958) observed that the recognition of the institutional changes led the theory
of investment to changes from profit maximization to utility maximization’ Firms
decision is not only internally determined, external factors responsive to the firm’s assets
relative to replacement cost. In response to this, Tobin introduced the Tobin’s q, which
10
transmits the impact of fluctuations in capital and financial market on private sector
investment. The theory is the addition to the market value of the firm resulting from a
unit increase in fixed capital, or the capital valuation of the extra unit of the firms fixed
assets (Tobin, 1969;Brainard and Tobin, 1968).
In a volatile, uncertain world the firm may not be interested in expected or actual values
of the rate of returns, output, relative prices, or internally generated funds. It may rather
make investment decisions with a view to the degree of variability of investment
determinants from perceived expected value (Badawi, 2004). Much of the theoretical
work on uncertainty and investment has been developed in the framework of riskneutrality. However, unlike the neoclassical framework with certainty, the firm
maximizes expected utility or profit function, resulting in a marginal condition for
optional capital where the expected marginal revenue product of capital is a function of
random distribution of factor and prices. It is the variance of the density function of
probability distribution of each factor that determines the degree of uncertainty about that
factor. These degrees of uncertainty about different factors may be assumed independent
from each other by assuming an independent distribution of factors affecting expected
marginal revenue function or assumed correlated by assuming joint distribution and
analyzing uncertainty in a multivariate context (Hartman, 1972; Nickell, 1977; Serven,
1998). In support of this proposition, Abel (1983) states that price shocks causes firm to
alter the optional capital/labour mix, thus making marginal revenue product of capital rise
more (or fall less) than relative output prices. Consequently, marginal profitability is a
convex function of output prices, and Jensen’s inequality then implies that price
uncertainty raises the expected profitability of capital, hereby increasing investment. In
literature, focus has been shifted to the adjustment costs which is implied by the
acquisition and installation of capital, emphasizing the irreversibility nature of most fixed
investment projects (Dixi and Pindyck, 1994).
The above models reflect uncertainty about the appropriate form of the private
investment model for developing countries. Though the empirical test of the various
models including the most widely accepted neoclassical flexible accelerator model, have
11
been quite successful, its application in the developing countries context is rather difficult
due to the inherent assumptions of the model and non availability or inadequacy of data
for certain variables. In recognition of the above limitations, developing countries moved
from traditional theories to the role of economic policies in determining private
investment and try to identity and quantify the relevant policies for private investment as
well as bridge the gap between pure, investment theory and unique structural and
institutional characteristics of developing economies (Mckinnon, 1973; Fry, 1988;
Badawi, 2004). The theories synthesized a framework, which feature a new set of factors
that seems to be left out in conventional investment theories.
Based on this fact, Bhattacharaya et al (2004), and Badawi (2004) observed that banking
sector credit and depth or size of financial intermediation came out as an important
factors in investment equation: The relationship between the banking sector institutions
and private sector capital expansion remains one of the most complicated issues in the
policy making process and design in developing countries. This due to the fact that
expanding banking sector loanable funds and their potential effect on domestic credit are
at the heart of the concern of monetary policy designed and implemented in developing
country. Nair, (2005) observed that real bank credit to the private sector act as an
explicator to capture the credit constraints in the economy. He further observed that
asymmetric information and incomplete contracts implies that availability of finance
especially bank credit may constraint investment decisions of private firms. Since the
fundamental market problems centered on asymmetric information between buyers and
sellers, this will frustrate the efficient exchanges that would occur in equilibrium if all
agents were fully informed. Consequently, the assumption of the neo-liberal view that
individuals and firms can costlessly write and enforce richly detailed financial contracts
can be questioned since the completeness of financial contract is not possible if
information or ability to enforce contract is not possible (Gertler and Rose, 1994).
Until the early 1970s, it was generally believed that low interest rates on bank loans and
deposits would promote private investment spending – a notion consistent with the
Keynessian and neo-classical analyses. But McKinnon and Shaw (1973) challenged this
12
conventional wisdom. They argued that raising interest rates increase the amount people
are willing to hold as financial assets by decreasing the holdings of foreign assets and
non-financial assets. Thereby, the mostic financial system is able to extend more loans to
the investors. They argued further that the existence of very low or negative real interest
rate would result in the support and expansion of unproductive non-viable projects and
the channeling of funds into consumption rather than investment, which would be
detrimental to private capital formation. They advanced the hypothesis that private
investment in developing countries is positively related to the accumulation of real
money balances. In another perspective, the “new-structuralize” economist argued that
high bank interest rates lead to high bank deposits simply due to transfer of funds away
from alternative asset holdings (Taylor, 1983), such as the informal credit markets
(Edward, 1988). As a result of the above,stiglitz and Uyo (1996) argued against unbridled
financial liberalization and instead, supported, “Mild financial repression. In support of
this statement is the work by (King and Levine, 1997).
Ndikumana (2005) observed that the effect of the exchange rate on private investment is
theoretically ambiguous. He argued that real exchange rate depreciation increases
profitability in export-oriented sectors and therefore promotes investment in these
sectors. Conversely, depreciation of the exchange rate increases the cost of imported
capital goods, and thus decreases investment in import dependent sectors. Badawi (2004)
also observed that real exchange rate appears to have a significant positive short-run
impact on private fixed investment, while it reports a negative long-run impact on private
sector investment in fixed assets. He further observed that the deleterious impact of
depreciation in the domestic currency on private sector investment has contributed to the
debate on the appropriateness and relevance of devaluation policy, a debate he contended
can be widened by adding a neoclassical dimension (as far as investment literature is
concerned), considering the potential impacts of devaluation on the real user cost of
capital, and thereby on investment and growth. This dimension may stand in conflict with
the conventional view that devaluation has a favorable effect on growth, and
development through correcting distortions and generating incentives for the private
sector (particularly in the tradable goods sector)
13
The theoretical literature on the relationship between fiscal policy and growth has
grown substantially since the mid-1980s, when the endogenous growth models emerged.
According to these models, the process of economic growth is endogenously determined.
A crucial difference with neo-classical growth models is that these new growth models
do not assume diminishing marginal productivity of capital. Consequently, (changes in)
the capital stock can affect the long run per capital growth rate, either via a quantity (i.e.
more investment) or a quality (i.e. more efficient investment) effect. These new growth
models, therefore, conclude that economic policy-among which is also fiscal policy-can
increase the steady-state economic growth rate, if policies are aim at influencing the
quantity and/or quality of the capital stock. Among the endogenous growth models
incorporating the role of fiscal policy are Barro (1990,) king and Rebelo (1990), Rebelo
(1991) and Barro and Sala-i-Martin (1992).
The exact nature of the impact of fiscal policy on economic growth according to these
models depends on the type of fiscal policy instruments used. In particular, the growth
effects of fiscal policy can be divided into productive and non-productive
expenditures,(distortionary and non-distortionary) taxes (Kneller, et al. 1999; Gemmell,
2000; Hermes and Lensink, 2001). When government expenditures create positive
production externalities, focus on enhancing innovation and research and development
and/or stimulate the accumulation of private capital, these expenditures are seen as
productive. Aschauer (1999), Kneller el. at (1999) posit that public investment in
infrastructure, education and health belong to productive expenditure and is said to
crowd-in private investment. However if financial recourses are scarce, public investment
may reduce the possibilities of the private sector to obtain credit to finance investment.
Moreover, if public investment is financed through monetary financing, private
investment may be seriously discouraged (Ramirez, 1996). In this case public investment
is said to crowd-out private investment opportunities (Buiter, 2004)
Locking at fiscal policy instruments, budget deficit are assumed to have a negative
impact on economic growth (Hermes and Lensink, 2001). First, high deficits may signal a
14
high tax burden in the future. This may discourage current aggregate expenditures, and
thus also private investment. Other works in support of the above include :( Bertola and
Drazen, 1993; Giavazzi and Pagano, 1990; 1996, Sutherland 1997; Guimaraes and Olaf
2000; Ndikumana 2005). It was further observed by Alesing and Perotti (1997) that high
budget deficit may lead to higher interest rates in financial markets, which may reduce
investment and growth. Moreover, high budget deficits may increase risk premiums on
interest rates, in particular raising inflation risk and the default risk premium. High
interest rate risk premium may discourage private investment finally when high deficits
are financed with financial market loan; this may decrease the opportunities of the private
sector to borrowing (Hermes and Lensink, 2001).
In addition to testing the impact of fiscal policy on private investment, the impact of
capital and trade flows have been reported to have had a positive effect on private capital
formation by increasing exchange base and private sectors access to imported capital
goods and foreign markets (FitzGerald et al, 1994).
2.2 Empirical Literature
Blejer and Khan (1984b) using a framework, which is an extension of flexible accelerator
type, associated with Jorgenson (1967, 1971) and Hall (1977) tested an explicit functional
relationship between principal policy instruments and private capital formation in
developing countries.
Their findings were a challenge of the traditional view that
standard investment theory is not relevant for developing countries. They were also able
to establish a direct empirical link between government policy variables and private
capital formation.
Asante (1993) estimated a private investment equation for Ghana. In estimating the
determinants of private investment, the independent variables employed include
incremental capital output ratio, the lending rate, the exchange rate, credit to the private
sector and public investment. His preliminary result showed among other things a
“crowding out” effect of public investment.
15
Ariyo and Raheem’s (1991) estimated the effect of fiscal deficit on macroeconomic
aggregate in Nigeria. Employing the following independent variables: public investment,
rate of growth of GDP, domestic credit to the private sector and interest rate. Their
results show that all the variables were statistically significant and evidence of “crowding
in” was arrived at.
Moshi and Kilindo (1999) estimated the impact of government policy on macroeconomic
variables in Tanzani using ordinary least square (OLS).
The work which was an
extension of Khan and Blejer (1984) was able to establish a direct empirical link between
government policy and private capital formation. The result indicates that public
investment crowd out private investment, but the effect depends on the way in which
public investment is introduced into the model.
Elenoa and Jayaraman (2001) carried out a study on the determinants of private
investment in Fiji. Employing an econometric extension of the work of Goldsborough et
al. (1996) and Ndikumana (2000) tried to avoid simultaneity problems by lagging certain
variables, constraining the causality to run in one direction. Augmented Dickey fuller test
(ADF) and the Phillips Perron test were used to examine the stationarity properties of the
time series data. The empirical investigation show that changes in real private investment
in Fiji are best explained by changes in terms of trade and by a dummy variable
representing a coup and its effects. It was further observed that changes in other
economic variables examined have an insignificant effect on the variations of private
investment.
Nair (2005) analyze the determinants of fixed investment in India Private Corporate using
Annual Survey of Industries data.
In caring out this investigation, a reduced form
equation derived from the neoclassical investment theory was used for the empirical
analysis. Empirical results show that, the traditional determinants like output and profit
still plays a major role in determinant corporate investment rather than the policy
variables. It was also observed that the only index that shows strong positive association
with corporate investment is index of money market liberalization.
It was further
observed that there is significant negative association between index of capital account
16
liberalization and corporate investment.
Hermes and Lensink (2001) investigated the impact of fiscal policy on private investment
in less developed countries. This work main contribution is that it is the first attempt to
analyses the existence of a non-linear relationship between fiscal policy variables and
investment.
The researchers employed a panel estimate for a set of LDCS, using
observations of variable that have been averaged over three periods: 1970-1979, 19801989 and 1990-1998. The result of the investigation show that a reduction of budget
deficits as such is not a panacea and can be even harmful and that the combination of
specific expenditure and revenue reforms may be of crucial importance.
Badawi (2003) in an attempt to address the issue of complementarily and substitutability
of state capital to private sector investment in a neoclassical growth framework employed
a co-integrated vector autoregressive model to account for potential endogeniety and
nonstationarity problems. Results suggest that both private and public capital spending
have simulated economic growth in Sudan over the period 1970-98. It was observed that
the impact of private investment on real growth has been more pronounced than that of
public sector investment.
Iyoko (2006) tested the relationship between public and private investment in Nigeria.
Her result reinforced the findings by Ndikumana that public investment does not crowed
out private investment in Africa.
Lutfi (1999) estimated the effects of financial markets on private capital formation in
Turkey covering the period 1968-1998 periods. This study modified the neoclassical
investment model by including credit availability, GARCH process of interest rate. While
reinforcing the findings of previous studies that the quantity of credits significantly
affects private investment, the result go on to indicate that cost uncertainty, but not the
level, has an adverse impact on private investment in turkey
Badawi, (2005) using a blend of co integration, vector autoregressive and error correction
techniques to estimate long and short-run coefficients. The empirical result suggests that
17
public sector investment had a negative crowd out impact on private investment over the
period of study. Devaluation policy contributed to discouraging private sector capital
expansion. He observed further that monetary policy in the form of restrictive domestic
credit appears to have a significant impact on private investment, suggesting that a
restrictive monetary policy may lead to shrinking private capital formation by tightening
financial contract private firms.
Ahmet and Gaobo (2005) analyze the determinants of unsatisfying private investment
growth in the Middct le East and North African (MENA) throughout the 1980s and 1990.
The researcher employed a panel of 40 developing economies. Extending the neoclassical
accelerator model and taking account of the various constraints faced by the investors in
developing countries into account, the research came to the conclusion that insufficient
structural reforms, deficient trade openness, economic uncertainty and external debt
burden have been a crucial factor for the deficit in private capital formation in the
developing world and in MENA countries in particular.
Seven (1998) estimated the impact of uncertainty on investment using a large panel data
set of developing countries. The researcher draws a distinction between sample
variability and uncertainty, and constructed alternative measures of the volatility of five
key macroeconomic variables- inflation, growth, the terms of trade, the real exchange
rate and the price of capital goods and examined their association with, aggregate private
investment. The method the method employed allowed for simultaneity, country specific
effects and parameter heterogeneity, across country. The result abstain underscore the
robustness of the investment uncertainty.
Akpokodje (2000) explored the association between export earning fluctuations and
capital formation in Nigeria using a reduced form equation built around the flexible
accelerator model and adopting a cointegration technique. Result reveals that the current
level of export earnings fluctuations adversely impinges on investment (that is the change
in capital stock in the short-run.
18
2.3 Limitation of Studies
Although the importance of private capital formation has been widely developed in the
literature, title is known-both theoretically and empirically about what induces private
investment in developing country like Nigeria. It has been observed that developing
countries do not always operate in a competitive environment and also faces constraints
that are not accounted for in the neoclassical model. This partly explains why most
economists do not agree on the subject of the determinants of investment in the
developing countries (see Greene and Villanueva, 1991, Blejer and Khan, 1984, serven,
1998, Ahmet and Gaobo, 2005, Naira, 2005, Badawi, 2005). This phenomenon is also the
case with Nigeria, for which empirical literature is very deficient (See Ekpo, 1990)
Akpokoje, 2000, Ahmet and Gavbo 2005). Most of these studies are not country specific
but rather a cross-country analysis. The study by Akpokoje (2000) is based on the
relationship between export and gross capital formation and that of Ekpo (1999) is on
public expenditure and economic growth. No work known to us has carried out an
investigation on the impact of macroeconomic policies on private capital formation in
Nigeria.
The big question of can macroeconomic policy stimulates private capital
formation in Nigeria has remained unanswered. This work is a novelty in that it is the
first time this research question is to be answered in Nigeria. This question forms the
nucleus of this research work.
19
Chapter three
Methodology
3.1 The Model
In modeling the determinants of investment, five broad approaches are generally
considered. These major strands of investment behaviour include the accelerator model,
the liquidity theory, the expected profit theory, the Tobin’s Q theory, and the neoclassical
flexible accelerator theory. The flexible accelerator model appears to be the most popular
of these theories used in applied work. However, in the context of developing countries,
due to data limitations and structural constraints, a variant of the flexible accelerator
model has often been used in empirical literature, including the literature on the
determinants of private investment in these countries.
According to the neoclassical model originally developed by Jorgensen (1963), solving
the profit maximization problem of a representative firm yields the demand for capital as
a function of output and the cost of capital under certainty (Ram, 1993).
K*pt = F (GDPt, Ct) ……………………………………………………………………….. (1)
Where K*pt is optimum or desired capital stock by private sector in period t; GDPt is the
output, and Ct is the cost of capital proxied by interest rate.
In addition, in the light of the arguments that the quantity constraints coming from the
financial markets may be more binding than the cost of capital in a developing country
like Nigeria, the flow of credits to the private sector is added. It has also been observed
that the exchange rate plays a significant role in the growth of the private sector. Though
the theoretical prediction are ambiguous. The inclusion of exchange rate into the model
is indeed expedient. Also, the role of public investment on private sector growth process
is still an ongoing debate in literature .Drawing a conclusion on its impact in the private
sector growth process is indeed difficult owing to the fact that empirical result conducted
in other developing countries reported divergent result on it impact on private sector
20
growth process.
While some report a crowding in relationship, others reported a
crowding out effect. The inclusion of this variable into the private investment equation
in is indeed important. Thus the equation becomes,
K*pt = H (GDPt, RIRt, DCRPt, REXCHt, PUINVt) ………………………………….... (2)
Because there is no data on capital stock available for Nigeria, one can use definition of
the gross private investment given by,
PIt = (Kpt - Kpt – 1) + Kpt – 1 …………………………………………………………. (3)
Where  is the depreciation rate of the private capital stock and P1t is gross private
investment. In the steady state, this equation becomes,
PI*t =  K* pt …………………………………………………………………………... (4)
Inserting (3) into (2), obtain
PI*t =  H (GDPt, RIRt, DCRPt, REXCHt, PUINVt) ………………………………….. (5)
The actual stock of private capital may not adjust completely to reach the desired level
due to technical constraints, and the time it takes to plan, decide, build and install new
capital. Such dynamic structure in private capital behaviour can be introduce through a
practical adjustment mechanism like the following,
Kpt – Kpt – 1 = B (K*pt –Kpt-1) O ≤  ≤ 1 …………………………………………….. (6)
Where  is the coefficient of adjustment. In this difference between desired private
capital in the time t and actual private capital in the previous period. For practical
purposes, on can express equation (6) in terms of gross private investment as
21
IPt-Pt –1 =  (IP*t – IPt –1) ……………………………………. …………………… (7)
Rearranging equation (7), obtain.
IPt =  IP*t – (1 - ) IPt – 1……………………………………………………..……. (8)
Extending the above theoretical model and previous studies like Badawi (2003 and
2004), Aschauer’s (1989), Monadjemi’s (1996), Ndikumana (2005), Ouattara, (2005) and
based on economic theory, Private Investment model can be specified as follows:
It  0  1 It 1  2 RGDPt  3 PUINVt  4 RIRt  5 EXRCHt  6 DCRPt   t …………………. .(3.9)
All variables in natural logarithm except real interest rate
The unrestricted VAR model of equation (3.9) may be written as
Vt = GoDt + G1Vt-1 + G2Vt-2 + ………. + GKVt-k +  t………………………….. ..(3.10)
Where Vt is (6 x 1) vector containing the endogenous variables, D is the vector of
intercept term and trend,  t is a (6x1) vector of white noise errors that are uncorrelated
with all the right hand side variables and their own lagged values but may be
contemporaneously correlated with own lagged value.
The corresponding vector error correction model (VECM) of equation (3.10) may be
specified as
Vt  Go Dt  1Vt 1  2 Vt 2  ...  k 1Vt k 1  Vt k ...(3.11)
Where  is a (6 x 6) matrix and  t is a (6 x 1) vector of error term. The matrix 
contains information on the long run adjustment, while
i
contains information on the
22
short run adjustment to changes in Vt. The matrix  is decomposed into  =   ; where
 is the adjustment matrix, representing the speed of adjustment to equilibrium, while 
contains long run coefficients or elasticities. The above equation can be transformed into
a matrix form as follow:
 ln I t 
 ln RGDP 
t 

ln PUINVt 
k 1

   i 1
 RIRt 
 ln EXCH 
t


 ln DCRPt 
 i11

 i 21
i 31

i 41

 i 51
i 61
i12
i 22
i 32
i 42
i 52
i 62
i13
i 23
i 33
i 43
i 53
i 63
i14
i 24
i 34
i 44
i 54
i 64
i15
i 25
i 35
i 45
i 55
i 65
i16   (ln I )t i  1 
 ln I t  k   1i 





 ln RGDP   
i 26   (ln RGDP)t  i   2 
t  k   2i 

ln PUINVt  k   3i 
i 36   (ln PUINV )t i   3 

           
 
i 46   ( RIR)t i   4  1 2 3 4 5 6  RIRt  k   4i 
 ln EXCH   
i 56   (ln EXCH )t i   5 
t k
 
  

  5i 
i 66   (ln DCRP)t i   6 
 ln DCRPt  k   6i 
Where
It=Private Investment
RGDP=Real GDP
PUINV=Public Investment
PIR=Real interest rate
REEXC=Real exchange rate
DCRP=Domestic Credit to the private sector
3.2 Model Justification
In assessing the relationship between macroeconomic policies and private capital
formation in Nigeria, we opted to use a VAR approach. The choice of a VAR model will
help us obtain quality economic properties, strong statistical inference and sound
economic postulates of the specified model. In developing countries in general, it has
proved difficult to estimator robust structural models of private investment (see Agenor,
2004). VAR models offer a way of analyzing the dynamic relationship between two main
variables without having to specify a structural model of private capital formation. The
model allow us take into account-delayed responses with a parsimonious lag structure.
VAR model obviates a decision as to what contemporaneous variables are exogenous
with only lagged variables on the right hand side, and all variables are endogenous
23
(Green, 2000). The model takes all variables as dependent to avoid lead back effects of
two variables.
The central feature characterizing the VAR technique is that it poses strong restrictive
structural modeling, as it imposes no a priori end-exogenous divisions of variables.
Furthermore, no zero restrictions are imposed on individual variables to attain
identification, which is the case under simultaneous equation modeling. VAR model
when supplemented with co integration account for problems of non-stationarity and
exogeneity in order to estimate relevant parameters that describe both short and long run
equilibrium or stationary relationship, VAR models provide a convenient common
framework for examining private investment behavior in a country of this nature. Using a
uniform single regression model would amount to imposing strong restrictions on
specification and the direction of causality among the variables, thus the need for VAR
model,The use of VAR models to study the impact of macroeconomic variables on
private capital formation is by no means new. For instance, Mittnik and Neumanna
(2001) in a study of six industrial countries and Ghali (1998) used a VAR model in
investigating public investment and private investment; Belloc and Vertova (2002) in
HIPC used VAR to test complementary relationship. voss (2002) for united state and
Canada, Badawi (2003 and 2004) for Sudan and Ndikumana (2005) for South Africa used
VAR to test macroeconomic policies and private capital performance.
3.3 Estimation Procedure
Investigating the time series properties of data is a precondition to establishing the VAR
mode. To test the order of integration of variables, standard tests for unit root such as the
Augmented Dickey – Fuller (ADF).Johanson (1991) cointegration test based on the maxeigenvalue test or trace test is used to establish the existence of a long term relationship
between macroeconomic policies and private capital formation in Nigeria. Because all the
right-hand- side variables in the VAR contain lagged variables, the simultaneity bias is
not a concern, and the OLS estimates are as good as GLS estimate. Based on the AIC and
SIC (Akaike, 1981) we shall chose the optimal lag length for the VAR estimation. A
vector error correction model (VECM) is applied to estimate short run dynamic
24
relationships. VECM is a restricted VAR designed for nonstationary time series that are
cointegrated. The VECM has cointegrated facilities built into the model so that it restrict
the long term behaviuor of the endogenous variables to converge to their cointegrating
relationships while allowing for short term dynamic adjustments.
3.4 Method of Results Evaluation
To achieve the first objective of this study, the short-run dynamic VAR result will be
used to determine the impact of macroeconomic policies on private capital formation in
Nigeria. Effort will be made to interpret the estimated coefficients for the short run
dynamic VAR model.
For the second objective, the impulse response functions and variance decompositions of
the system will be used to draw implications about a VAR. Based on Sim (1980), the
impulse response depicts how an endogenous variable responds over time to a single
surprise change in itself or in another variable, thereby suggesting evolutionary effects
for each variable. If the error terms are uncorrelated, then each depicts the surprise
movement (or innovation) in the corresponding dependent variable. But since they are
correlated to some degree we shall use the Choleski decomposition, in which the errors
are orthogonalzed so that the covariance matrix of the resulting surprise movements is
lower triangular, to attribute common effects. This implies a recursive chain of causality
among the surprise movements in any given year, so that effects flow only downward,
from variables earlier in the causal chain to those later (Todd, 1990).Also, the impulse
response function test shall be complimented by the variance decomposition test. The test
suggests that forces associated with one variable are major influences on the evolution of
another variable. .This test will be used to give vent to the impulse response test
The third objective will be accomplished by conducting the granger causality test. The
granger causality test sets to determine the causal ordaining of the mediating variables
connecting private investment and macroeconomic policies. Granger (1969) starts from
the premise that the future cannot cause the present or the past. Note that the direction of
25
causality may depend critically on the number of lagged terms included in the regression.
The test is very sensitive to the number of lags used in the analysis.
3.5 The Data
The sample consists of annual data from 1970 – 2004 extracted from the central bank of
Nigeria statistical bulletin various years, AERC 2005, CBN Annual Reports and
Statement of Account for various years.
26
Chapter Four
Presentation and Interpretation of Empirical Results
4.1 Result Presentation
Most time series data tend to contain infinite variances that are not mean- reverting and
lie on the unit circle. Equation estimated from such series result in spurious regression
that makes little economic sense. Indeed the loading of the endogenous variable is
minuscule when in fact a long -run relationship exists between it and the economic
fundamentals driving it. Thus each of the variables would be examined for unit root and
co integration. Consequently, the Augmented Dickey – Fuller (ADF), defines the
equations for these tests.
4.2 Unit Root Analysis
The test for unit root using the Augmented Dickey – Fuller (ADF) indicated that real
gross domestic product, private investment, public investment and real exchange rate are
non-stationary with one as the order of integration. Domestic credit to the private sector
and real interest rate were shown to be stationary series. All tests were significant at both
5% and 1%. The lag length criteria (AIC) did not improve with further increases in the
lag length. See table 4.1 below
Table 4.1: Unit Root Statistics
Variable
Adf
Critical
McKinnon Lag
statistic
Order
integration
RGDP
-4.928986**
-3.639407
0
1
PRIV
-9.645069**
-3639407
0
1
PUINV
-5.798530**
-3639407
0
1
DCRP
-5.127062*
-3.711457
0
0
REXCH
-5.395782**
-3.63907
0
1
RIR
-3.901355*
-3.63907
0
0
1** Adf stationary at first difference 1*Adf stationary at level
27
of
4.3 Co-integration Analysis
The unit root results conducted above have significant implications for the co integration
analysis. The standard Johanson approach, which requires the variables to be integrated
of order one, can be implemented. This involves testing whether the  matrix has
reduced rank. That is to find whether r = (n-1) co integration vectors exist in
Here Johansen maximum eigenvalue and trace test is used to determine the number of co
integrating vectors for the specification suggested by the selection criteria. The null
hypothesis that there is no co integrating vector in the system (Ho: r = 0) is rejected, but
the alternative that there exists at most one co integrating vector (Ho: r = 1) is not. From
the table below, the estimated eigenvalue and trace test indicated that there are three co
integrating vector.
There are, therefore three long –run relationships between the
variables. See table 4.2 below.
Table 4.2: Johanson Co- integration Test Statistics
HO:rank = r
Maximum
Trace
5%
critical 5% critical No. of CE(s)
Eigenvalue
statistic
value for max value
for
eigenvalue
trace status
HO: r = 0
115.9645
230.19
40.08
95.75
None*
HO: r = 1
60.695
114.22
33.877
69.81
At most 1*
HO: r = 2
30.71
53.52
27.58
47.856
At most 2*
HO: r = 3
15.528
22.81
21.13
29.797
At most 3
HO: r = 4
5.857594
7.288
14.26
15.49
At most 4
HO: r = 5
1.430
1.430
3.84
3.84
At most 5
An asterisk indicates rejection of the null hypothesis at 5% level.
28
Model Results and Discussion
4.4.1
Short-Run Dynamic VAR Result
The estimated model (see appendix) shows that private investment at the one period and
two period lags were not significant at five percent level of significance. This means that
changes in the past does not always trail changes in the actual value of private
investment. Private investment is found to respond to gross domestic product at the past
period, as real gross domestic product at the one lag was significant at the 5 percent level.
This is an indication that past performance of real GDP in is fundamental in determining
the performance of private investment in Nigeria. Similarly, public investment at the one
lag period has significant influence on private capital formation in Nigeria.
Meanwhile, real interest rate at both one period and the second period lags were
statistically significant at 5 percent level of significance suggesting the short-run impact
of interest rate in desired long-run private capital formation in Nigeria. The estimated
real exchange rate and domestic credit to the private sector lagged by one is also
significant at the 5 percent level of significance. From the results therefore, if real GDP
rose in the previous period by 1 base point it would result in a net effect of 0.971 base
points in the current private investment in Nigeria.
The above magnitude is large
compared to related results found for developing countries. For example, real GDP
coefficient appears to be close to unity in Blejer and Khan (1984), equal to 0.46 in fry
(1980), between 0.01-0.08 in Ndikumana (2000), 0.002 in Sioum (2002) and nearly 0.9
for Badawi (2004). While a 1 percent rise in one lag period of public investment will
contemporaneously lead to approximately 0.63 base points rise in private investment.
This result reinforced the findings by Mlambo and Nell (2000) for South Africa that a 10
percent increase in government expenditure results in a 0.24 percent increase in private
investment. These results suggest that public investment crowd in private investment in
the two countries. Furthermore, Reinikka and Svensson (2002) finds out that a 1 percent
increase in public investment result in 0.43 percent increase in private investment in
Uganda.
29
Also, interest rate coefficient both for one and two lagged period reported a different
result. The result of one lag of interest rate is not consistent with a priori expectation but
the estimated coefficient for second lag period of interest produced result that is
consistent with conventional economic theory. From the estimated result, interest rate
differential would lead to 0.445 base point increases in contemporaneous private
investment if the interest rate lagged by one period changes by 1 unit. This result appears
to be interesting in light of the considerable theoretical and empirical evidence
advocating a positive relationship between investment and interest rate in LDCs. While
many researches made significant empirical contributions to establish such a positive
relationship there seems to be no lack of an opposite position. With a highly significant
negative long-run coefficient of nearly 0.45 for interest rate lagged by two, Nigeria seems
to exhibit an interest rate investment nexus similar to those at work in Sudan, Indonesia
and Chile. Badawi (2004) reported a long-run coefficient of – 0.10 for Sudan, Chhibber
and Shafik (1990) report a long-run coefficient of –2.3 for Indonesia, Solimano(1980)
also report a negative long-run coefficient for Chile.
Revealing another intriguing result is real exchange rate for Nigeria. The estimated
coefficient suggests that a unit increase in exchange rate brings about a contemporaneous
increase in private investment by 0.92 base points. The exchange rate and private
investment pass through in Nigeria is not in tandem with conventional theory of an
inverse relationship between the two. However, this result seems not to be consistent –
qualitatively as well as quantitatively – with that reported by Solimano (1980) for the
case of Chile over the 1980s. What the above result is implying is that the size of the
Nigerian traded goods sector has expanded and depended on imported capital goods.
Furthermore, domestic real credit to the private sector reports a positive long-run effect of
private investment. This long-run elasticity is highly significant at 5 percent level of
significance reporting a large t statistic of around 6.85. With a magnitude of 0.76, real
credit seems to have exerted a large impact on private investment in Nigeria than in other
developing countries suggesting that credit rationing right have been more severe in
Nigeria in comparison to other less developing country's average. Blejer and Khan
30
(1984), using various specifications for the investment equation for a panel of 61
developing countries, estimate a similar result in the range 0.197 – 0.257. Ndikuman
(2000), employing a sample of 30 Sub-Saharan. African countries got a result of 0.363,
while Badawi (2004) for Sudan came up with, elasticity of 7.14.
4.4.2 Impulse Response and Variance Decomposition
The second objective of this study is to determine the responses of private investment to
shocks on macroeconomic variables. We shall look at impulse response and variance
decomposition under the vector autoregressive model. This will enable us ascertain how
the variables under study respond to innovations and to determine the percentage of
forecast error decomposition of the dependent variable as accounted for by the lagged
endogenous variables. We restrict our interpretations to the impulse response for, and
variance decomposition of private investment and real GDP. These are presented in
tables’ 4.3, 4.4, 4.5and 4.6 below.
Table 4.3 Impulse Response for Private Investment
Period
PRINV
DCRP
GDP
PUINV
REXCH
RIR
1.
124146.3
0.0000
0.0000
0.0000
0.0000
0.0000
2.
-10243.40
18215.07
7651.54
16005.45
-14581.47
-24105.84
3.
9532.7
17193.64
17524.14
10476.93
-21518.28
-16996.16
4
22522.86
16306.68
22270.64
21758.09
-24458.54
13922.91
5
-1426928
16754.32
22647.32
26027.17
-26660.99
12819.85
6
-3880.72
7304.189
24791.77
31060.12
-19502.65
819.1022
7
15476.35
3051.36
25862.04
38213.43
-13217.32
-352.0971
8
10648.46
4267.09
27330.80
39780.12
-1237213
-1641.492
9
8551.419
4684.837
30496.54
39951.94
-12996.53
-4071.742
10
11874.46
6435.33
33551.37
41625.16
-14506.25
-3189.268
The results suggest that private investment, responds negatively to one standard
innovation to its own lagged values in the 2nd, 5th, and 6th year of innovation, but respond
31
positively to domestic credit to private sector, real GDP and public investment both in the
short and long run. The result further reveals that private investment responded
negatively to one standard innovation on real exchange rate from the 2nd year to the 10th
year, with real interest rate responding negatively in the long-run. The result shows thatl
real exchange rate and real interest rate does not reflect an effective macroeconomic
policy pass through on private investment in Nigeria. The implication of the above
analysis is that domestic credit to private sector, real GDP and public investment is an
effective medium of shock transmission to private investment in Nigeria. The result is
reinforced by the variance decomposition for private investment shown in table 4.4 below
32
Response to Cholesky One S.D. Innov ations ± 2 S.E.
Response of PRINV to PRINV
Response of PRINV to DCRP
Response of PRINV to GDP
Response of PRINV to PUINV
Response of PRINV to REXCH
Response of PRINV to RIR
160000
160000
160000
160000
160000
160000
120000
120000
120000
120000
120000
120000
80000
80000
80000
80000
80000
80000
40000
40000
40000
40000
40000
0
0
0
0
0
0
-40000
-40000
-40000
-40000
-40000
-40000
-80000
-80000
1
2
3
4
5
6
7
8
9
10
-80000
1
Response of DCRP to PRINV
2
3
4
5
6
7
8
9
10
-80000
1
Response of DCRP to DCRP
2
3
4
5
6
7
8
9
10
-80000
1
Response of DCRP to GDP
40000
2
3
4
5
6
7
8
9
10
-80000
1
Response of DCRP to PUINV
2
3
4
5
6
7
8
9
10
1
Response of DCRP to REXCH
300000
300000
300000
300000
300000
300000
200000
200000
200000
200000
200000
200000
100000
100000
100000
100000
100000
100000
0
0
0
0
0
0
-100000
-100000
-100000
-100000
-100000
-100000
-200000
-200000
1
2
3
4
5
6
7
8
9
10
-200000
1
Response of GDP to PRINV
2
3
4
5
6
7
8
9
10
-200000
1
Response of GDP to DCRP
2
3
4
5
6
7
8
9
10
-200000
1
Response of GDP to GDP
2
3
4
5
6
7
8
9
10
2
3
4
5
6
7
8
9
10
1
Response of GDP to REXCH
16000
16000
16000
16000
16000
12000
12000
12000
12000
12000
12000
8000
8000
8000
8000
8000
8000
4000
4000
4000
4000
4000
0
0
0
0
0
0
-4000
-4000
-4000
-4000
-4000
-4000
-8000
-8000
-8000
-8000
-8000
-8000
-12000
1
2
3
4
5
6
7
8
9
10
-12000
1
Response of PUINV to PRINV
2
3
4
5
6
7
8
9
10
-12000
1
Response of PUINV to DCRP
2
3
4
5
6
7
8
9
10
Response of PUINV to GDP
2
3
4
5
6
7
8
9
10
2
3
4
5
6
7
8
9
10
1
Response of PUINV to REXCH
6000
6000
6000
6000
6000
4000
4000
4000
4000
4000
4000
2000
2000
2000
2000
2000
2000
0
0
0
0
0
0
-2000
-2000
-2000
-2000
-2000
-2000
-4000
1
2
3
4
5
6
7
8
9
10
-4000
1
Response of REXCH to PRINV
2
3
4
5
6
7
8
9
10
-4000
1
Response of REXCH to DCRP
2
3
4
5
6
7
8
9
10
-4000
1
Response of REXCH to GDP
2
3
4
5
6
7
8
9
10
Response of REXCH to PUINV
2
3
4
5
6
7
8
9
10
1
Response of REXCH to REXCH
100
100
100
100
100
50
50
50
50
50
0
0
0
0
0
0
-50
-50
-50
-50
-50
-50
-100
2
3
4
5
6
7
8
9
10
-100
1
Response of RIR to PRINV
2
3
4
5
6
7
8
9
10
-100
1
Response of RIR to DCRP
2
3
4
5
6
7
8
9
10
-100
1
Response of RIR to GDP
2
3
4
5
6
7
8
9
10
Response of RIR to PUINV
2
3
4
5
6
7
8
9
10
1
Response of RIR to REXCH
15
15
15
15
15
10
10
10
10
10
5
5
5
5
5
0
0
0
0
0
0
-5
-5
-5
-5
-5
-5
-10
-10
-10
-10
-10
-10
-15
-15
-20
1
2
3
4
5
6
7
8
9
10
-15
-20
1
2
3
4
5
6
7
8
9
10
2
3
4
5
6
7
8
9
10
2
3
4
5
6
7
8
9
10
4
5
6
7
8
9
10
2
3
4
5
6
7
8
9
10
2
3
4
5
6
7
8
9
10
2
3
4
5
6
7
8
9
10
-15
-20
1
3
5
-15
-20
1
2
Response of RIR to RIR
10
-20
10
-100
1
15
-15
9
Response of REXCH to RIR
50
1
8
-4000
1
100
-100
7
Response of PUINV to RIR
6000
-4000
6
-12000
1
Response of PUINV to PUINV
5
4000
-12000
1
4
Response of GDP to RIR
16000
-12000
3
-200000
1
Response of GDP to PUINV
2
Response of DCRP to RIR
-20
1
2
3
4
5
6
7
8
9
10
1
2
3
4
5
6
Table 4.4 Variance Decomposition for Private Investment
Period
S.E
PRINV
DCRP
GDP
PUINV
REXCH
RIP
1.
124146.3
100.00
0.0000
0.0000
0.0000
0.0000
0.0000
2.
130220.7
91.5069
1.9565
0.3452
1.5107
1.2538
3.4268
3.
130220.7
84.31018
3.38907
1.97508
1.9767
3.6497
4.6993
4.
145077.1
96.56722
4.0937
4.0937
3.9879
6.05243
5.0544
5.
153613.6
63.74027
4.9752
5.8249
6.4277
8.4107
5.2047
6.
160081.1
63.74027
4.3887
9.4326
9.6835
9.229
4.7953
7.
16786.1
58.8159
4.3887
9.4326
13.9885
9.0129
4.3613
33
7
8
9
10
8.
1754865
54.1863
4.0749
11.0567
17.9384
8.7441
3.9994
9.
191999.0
45.8475
3.5760
14.8133
24.01564
8.3338
3.4137
Obviously, the variance decomposition shows that private investment explains 100
percent of its variance in the first period while other lagged endogenous variables explain
zero percent. But with the passage of time, the influence of private investment decreases
while that of domestic credit to private sector, real GDP, public investment, real
exchange rate and interest rate starts to increase. This suggests that domestic credit is
very effective in the medium term, but decreases in the 9th and 10th period. Real GDP
and public investment explains more of its variance in the long-run as the values
maintained an upward trend, while real exchange rate and interest rate becomes more
effective in the medium term as more of the variance is explained in 4th to 7th year for
both variables. The implication of the above result is that domestic credit; real GDP and
pubic investment do explain significant part of private investment in the long run with
exchange rate and interest rate showing no significant impact. This result still reinforces
our findings on the short run dynamic VAR estimate conducted above.
Going by the long run relationship established by the neoclassical flexible accelerator
model that there exist a significant long run relationship between output and investment;
we next examine the impulse response function and variance decomposition for real GDP
in tables 4.5 and 4.6
Table 4.5 Impulse Responses for GDP
Period
PRINV
DCRP
GDP
PUINV
REXCH
RIR
1.
-792.908
-2842.079
6558.862
0.0000
0.0000
0.0000
2.
-707.549
2796.014
5322.02
1165.934
-2094.895
-379.6621
3.
761.229
5212.156
3997.829
246.1080
-2898.851
-844.8999
4.
1327.150
4317.241
3227.683
2343.696
-3282.852
-373.7757
5.
594.6124
3040.100
3059.980
4253.373
-3736.149
465.7742
6.
594.7096
1643.302
3574.802
5607.642
-3556.694
954.8808
34
7.
810.822
729.4939
4223.745
6620.312
-2967.109
769.1336
8.
1313.666
423.4418
4803.117
7177.602
-2388.695
100.654
9.
1910.387
549.2653
5333.940
7491.106
-2116.413
-477.7156
10.
2192.062
972.3175
5848.947
7745.336
-2273.113
-695.2243
The response function shows that the response of real GDP to an innovation in private
investment is negative between the 1st and second period but became positive with an
increasing influence over the long run. The response of real GDP to innovation in
domestic credit to the private sector is negative in the first period but assumed a positive
value afterward. The positive influence was more in the long run.
The response to innovation in lagged GDP was positive all through the period with an
increasing influence over the long run. The first two periods impacted more on real
GDP. The result is in tandem with economic a priori expectation of a positive
relationship between real GDP and private investment. The response of real GDP to
innovation in public investment shows a positive impact both in the short and long run
with an increasing influence over the long run. That of GDP to innovation in real
exchange rate and real interest has a negative impact both in the short and long run.
These findings are supported the result of variance decomposition in table 4.7 below.
Table 4.6 Variance Decomposition for GDP
S.C
PRINV
DCRP
RGDP
PUINV
REXCH
RIR
1.
7191.994
1.215477
15.61614
83.1684
0.0000
0.0000
0.0000
2.
9708.716
1.198110
16.86320
75.68771
1.4422
4.6558
0.01529
3.
1213.18
1.161140
29.26069
59.3381
0.09648
8.6922
0.5830
4.
13942.50
1.785707
31.7399
50.2812
3.5561
12.1244
0.5132
5.
15672.25
1.556754
28.8831
43.6068
10.1800
15.2788
0.4945
6.
17502.95
1.328666
24.03856
39.1332
18.4264
1637910
0.69411
35
7.
19457.82
1.248748
19.59156
36.3770
26.4861
15.5786
0.7179
8.
21466.62
1.400465
16.13538
34.8938
32.9408
14.0376
0.5920
9.
23538.10
1.823534
13.47480
34.1575
37.5266
12.4840
0.5336
10.
25683.52
2.260052
11.46096
33.8754
40.6133
11.2688
0.5214
The result of variance decomposition in the table above shows that private investment
explains a significant proportion of real GDP. Domestic credit to the private sector also
explains a significant proportion of GDP both in the short and long run, while real
exchange rate do not explains any significant proportion of real GDP in the short run, but
reveal a significant long run impact on GDP. The result also reveals that domestic credit
to the private sector and lagged real GDP have a significant impact on private capital
formation
in
Nigeria.
36
Variance Decomposition
Percent PRINV variance due to PRINV Percent PRINV variance due to DCRP Percent PRINV variance due to GDP Percent PRINV variance due to PUINVPercent PRINV variance due to REXCH Percent PRINV variance due to RIR
100
100
100
100
100
100
80
80
80
80
80
80
60
60
60
60
60
60
40
40
40
40
40
40
20
20
20
20
20
0
0
1
2
3
4
5
6
7
8
9
10
0
1
2
3
4
5
6
7
8
9
10
0
1
2
3
4
5
6
7
8
9
10
20
0
1
2
3
4
5
6
7
8
9
10
0
1
2
3
4
5
6
7
8
9
10
1
2
3
4
5
6
7
8
9
10
Percent DCRP variance due to PRINV Percent DCRP variance due to DCRP Percent DCRP variance due to GDP Percent DCRP variance due to PUINVPercent DCRP variance due to REXCH Percent DCRP variance due to RIR
100
100
100
100
100
100
80
80
80
80
80
80
60
60
60
60
60
60
40
40
40
40
40
40
20
20
20
20
20
0
0
1
2
3
4
5
6
7
8
9
10
Percent GDP variance due to PRINV
0
1
2
3
4
5
6
7
8
9
10
Percent GDP variance due to DCRP
0
1
2
3
4
5
6
7
8
9
10
Percent GDP variance due to GDP
20
0
1
2
3
4
5
6
7
8
9
10
0
1
2
3
4
5
6
7
8
9
10
Percent GDP variance due to PUINV Percent GDP variance due to REXCH
1
90
90
90
90
90
90
80
80
80
80
80
80
70
70
70
70
70
70
60
60
60
60
60
60
50
50
50
50
50
50
40
40
40
40
40
40
30
30
30
30
30
30
20
20
20
20
20
20
10
10
10
10
10
0
0
0
0
0
1
2
3
4
5
6
7
8
9
10
1
2
3
4
5
6
7
8
9
10
1
2
3
4
5
6
7
8
9
10
1
2
3
4
5
6
7
8
9
10
2
3
4
5
6
7
8
9
10
Percent GDP variance due to RIR
10
0
1
2
3
4
5
6
7
8
9
10
1
2
3
4
5
6
7
8
9
10
Percent PUINV variance due to PRINV Percent PUINV variance due to DCRP Percent PUINV variance due to GDP Percent PUINV variance due to PUINVPercent PUINV variance due to REXCH Percent PUINV variance due to RIR
80
80
80
80
80
80
70
70
70
70
70
70
60
60
60
60
60
60
50
50
50
50
50
50
40
40
40
40
40
40
30
30
30
30
30
30
20
20
20
20
20
10
10
10
10
10
0
0
0
0
0
1
2
3
4
5
6
7
8
9
10
1
2
3
4
5
6
7
8
9
10
1
2
3
4
5
6
7
8
9
10
1
2
3
4
5
6
7
8
9
10
20
10
0
1
2
3
4
5
6
7
8
9
10
1
2
3
4
5
6
7
8
9
10
Percent REXCH variance due to PRINVPercent REXCH variance due to DCRP Percent REXCH variance due to GDPPercent REXCH variance due to PUINV
Percent REXCH variance due to REXCHPercent REXCH variance due to RIR
100
100
100
100
100
100
80
80
80
80
80
80
60
60
60
60
60
60
40
40
40
40
40
40
20
20
20
20
20
0
0
1
2
3
4
5
6
7
8
9
10
Percent RIR variance due to PRINV
0
1
2
3
4
5
6
7
8
9
10
Percent RIR variance due to DCRP
0
1
2
3
4
5
6
7
8
9
10
Percent RIR variance due to GDP
20
0
1
2
3
4
5
6
7
8
9
10
Percent RIR variance due to PUINV
0
1
2
3
4
5
6
7
8
9
10
Percent RIR variance due to REXCH
1
80
80
80
80
80
80
70
70
70
70
70
70
60
60
60
60
60
60
50
50
50
50
50
50
40
40
40
40
40
40
30
30
30
30
30
30
20
20
20
20
20
10
10
10
10
10
0
0
1
2
3
4
5
6
7
8
9
10
0
1
2
3
4
5
6
7
8
9
10
0
1
2
3
4
5
6
7
8
9
10
2
3
4
5
6
7
8
9
10
3
4
5
6
7
8
9
10
20
10
0
1
2
Percent RIR variance due to RIR
0
1
2
3
4
5
6
7
8
9
10
1
2
3
4
5
6
7
8
9
10
4.4.4 Granger Causality Test
The third objective of this study is to determine the causal ordaining of the mediating
variables connecting private investment and macroeconomic policies. To achieve the
above objective, Granger causality test is indeed expedient. Granger (1969) starts from
the premise that the future cannot cause the present or the past. Note that the direction of
causality may depend critically on the number of lagged terms included in the regression.
The test is very sensitive to the number of lags used in the analysis. The Grange causality
test is guided by the following decision rule:
37
Hypothesis
Ho: Bj =0
Against
Hi: Bj =o
Decision Rule
Reject the null if the computed F-value s greater than critical F-value at 5% level of
significance otherwise accept the null. Based on the above criteria, we present the result
of Granger causality test in table 4.7 below
Table 4.7: Result of Granger Causality Test
Direction of causality
Computed F Critical F value Decision
value
RGDP
PRINV


at 5%
PRINV 1.32941
3.63
Do not reject the null hypothesis
072133
3.63
Do not reject the null hypothesis
1.12226
3.63
Do not reject the null hypothesis
RGDP
PUIN

PRINV

PUINV
1.20891
3.63
Do not reject the null hypothesis
REXCH

PRINV 0.78644
3.63
Do not reject the null hypothesis
PRINV

REXCH 0.63599
3.63
Do not reject the null hypothesis
PRINV
RIP

PRINV
2.74570
3.63
Do not reject the null hypothesis
PRINV

RIP
2.72907
3.63
Do not reject the null hypothesis
PRINV 1.35649
3.63
Do not reject the null hypothesis
DCRP

PRINV

DCRP
PUINV

PUINV 4.46975
9.07287
Reject the null hypothesis
3.63
Reject the null hypothesis
RGDP

PUINV
0.73414
REXCH

RGDP
0.29435
3.63
Do not reject the null hypothesis
RGDP

REXCH
1.73260
3.63
Do not reject the null hypothesis
Do not reject the null hypothesis
38
RIR

RGDP
0.35234
3.63
Do not reject the null hypothesis
RGDP

RIP
1.63784
3.63
Do not reject the null hypothesis
RGDP
6.8569
3.63
Reject the null hypotheses
DCRP
0.77867
3.63
Do not reject the null hypotheses
1.44289
3.63
Do not reject the null hypothesis
REXCH
0.203.5
3.63
Do not reject the null hypothesis
PUINV
3.99620
3.63
Reject the null hypothesis
RIR
1.21362
3.63
Do not reject the null hypothesis
PUINV
2.52475
3.63
Do not reject the null hypothesis
DCRP
16.7718
3.63
Reject the null hypothesis
REXCH
0.74274
3.63
Do not reject the null hypothesis
DCRP

RGDP

REXCH

PUINV


RIR

PUINV
DCRP


PUINV

RIR
PUINV
REXCH

DCRP
1.83286
3.63
Do not reject the null hypothesis
DCRP

REXCH
0.33069
3.63
Do not reject the null hypotheses
REXCH

DCRP
0.37299
3.63
Do not reject the null hypothesis
DCRP

RIR
0.70438
3.63
Do not reject the null hypotheses
RIR

DCRP
2.69912
3.63
Do not reject the null hypotheses
Granger causality test result conducted above indicates that there is a unidirectional
causality between private investment and domestic credit to private sector, public
investment and real GDP, real interest rate and public investment, public investment and
domestic credit to the private sector. The unidirectional causality among these variables
is based on the rejection of the null hypothesis that their exist no causality among the
variables. The result further reveled that the unidirectional causality between these
variables is an indication of mutual relationship between them. The result further shows
that the null hypotheses are not rejected at 5% level of significance for the other variables
indicating the absence of mutual relationship between them.
The implications of the causality test conducted above include that: (1) domestic credit to
private sector has been established to be the main linkage variable between private
investment and the other macroeconomic variables: (ii) that the channel of transmission
39
 DCRP 

is: PINV 

PUIN 

RGDP 
 REXCH
RIR 
The current study gives support to the arguing for credit expansion to the private sector.
Literature on private investment in the developing countries has also established that their
exist a positive relationship between domestic credit and private capital formation.
4.5
Evaluation of Hypothesis
Based on the estimated result, we now evaluate the hypothesis of this study.
Test of Hypothesis one
Ho: Macroeconomic policies have no impact on private capital formation in Nigeria
Hi: Macroeconomic policies have a significant impact on private capital formation in
Nigeria
CONCLUSION
Based on the result of short run dynamic model investigated above, we reject the null
hypothesis and conclude that macroeconomic policy variables have significant impact on
private capital formation in Nigeria
Test of Hypothesis Two
Ho: Private investment has no significant impulse from macroeconomic variables in
Nigeria
Hi: Private investment has a significant impulse response from macroeconomic variables
in Nigeria
CONCLUSION
Result of impulse responses conduct in table 4.4 shows that there is a significant impulse
response among three variables and private investment. These variables include Private
investment lag by one, domestic credit to the private sector and real GDP. The result
further reveals a partial response between real exchange rate and real interest rate. Base
on findings, we reject the null hypothesis and uphold the alternative hypothesis.
40
Test of hypothesis three
Ho: The mediating variables connecting private investment and macroeconomic policies
have no causal ordering in Nigeria.
CONCLUSION
The result of the pair wise Granger causality test conducted in table 4.7 above leads to the
rejection of the null hypothesis since there exist a significant causal ordering of
macroeconomic variables and private capital formation in Nigeria.
4.6 Policy Implications of Findings
The result of the various test conducted above revealed an interesting outcome for policy
prescription in Nigeria. Domestic credit to the private has proved to have a more
significant impact on private investment in Nigeria than the other macroeconomic policy
variables.
Based on the various test conduct, the variable plays an outstanding role in
influencing private investment in Nigeria. This brings us to the negative impact of credit
rationing on investment. Real GDP also play an important role in private capital
formation in Nigeria. Results showed that real GDP reports a significant direct long run
effect on private investment over the period of the study. This finding provides evidence
to the validity of the hypothesis that the accelerator principle does explain private
investment in Nigeria. Result of public investment on the various parameters of
assessment showed that public investment crowd in private investment in Nigeria. This
lends support for rapid growth of public investment for they play a significant role in the
private sector production process. Results based on exchange rate revealed that the
concept of devaluation does not bring about the much-expected growth in private
investment in Nigeria.
Findings from this study lend support to the debate on the
appropriateness and relevance of devaluation policy on investment growth.
These
findings are incongruous with the conventional view that devaluation helps in correcting
distortions and generate incentives for the growth of the private sector. Results on real
interest rate showed that the variable does not play a prominent role in private capital
formation in Nigeria but has been a disincentive to the growth of the private sector.
41
Chapter Five
Summary, Policy Recommendation and Conclusion
5.1 Summary of Findings
This work is an attempt to empirically investigate the impact of macroeconomic policies
on private fixed capital formation in Nigeria within a co integrated vector autoregressive
framework. As earlier stated, private investment has been established to be a key to
economic growth through sound macroeconomic policies. To achieve the target of
achieving economic growth of about 7-8 percent, a good understanding of the impact of
macroeconomic polices on the growth of private sector is very expedient owing to the
fact that Nigeria economy has been experiencing serious structural imbalance, low
growth trap, characterized by a low savings – investment equilibrium.
The result of short run dynamic model shows that some of the macroeconomic variables
like real GDP, domestic credit to the private sector, public investment, real interest rate
lagged by two years and real exchange rate were statistically significant at the 5 percent
level of significance. Real GDP is statistically significant and impact positively on
private capital formation in Nigeria over the study period. The result upholds the validity
of the accelerator principle that there exist a positive long run relationship between real
GDP and private investment in Nigeria. Domestic credit to the private sector also reports
a significant positive effect on private investment. Public investment reports a crowd in
effect on private investment in Nigeria. This finding is not in tandem with literature that
public investment crowd out private investments in LDC. Rather it bolsters the
performance of private sector in Nigeria. The real interest rate reported an interesting
result. The variable reported a significant negative impact on private capital formation in
Nigeria. This shows the deleterious impact of high user cost of capital on investment
growth in Nigeria. The real exchange rate also reports a negative long run impact on
private investment. Depreciation of Nigeria currency has impacted negatively the
formation of private capital over the study period by increasing the imported capital
requirements of private investors. The deleterious impact of depreciation in the domestic
currency on private sector investment contributes to the debate on the appropriateness
42
and relevance of devaluation policy a debate that may be widened by adding a
neoclassical dimension (as far as investment literature is concerned), considering the
potential impacts of devaluation on the real user cost of capital, and thereby on
investment and growth. This dimension may stand in conflict with the conventional view
that devaluation brings about the growth of private capital formation through correcting
distortions and generating incentives for the private sector (particularly in the tradable
goods sector).
To achieve the third objective of this study which is the determination of the causal
ordering of the mediating variables connecting private investment and macroeconomic
policies, the granger causality test was conducted. The result reveals a unidirectional
causality between private investment and domestic credit to the private sector, between
public investment and real GDP, between real interest rate and public investment and
between public investment and domestic credit to the private sector. The unidirectional
causality among these variables is an indication of significant mutual relationship
between the variables and private capital formation. The result of the finding reveals
further that domestic credit to the private is a more effective policy variable than the
other variables on private capital formation in Nigeria.
5.2 Policy Recommendations
The empirical results and the analysis conducted revealed the best approach to improving
the performance of private investment in Nigeria.
Domestic credit to the private sector has been reported to play a prominent role in the
growth of the private sector in Nigeria. This provides the platform for arguing for credit
expansion to the private sector. The expansion of the banking sector loanable fund to the
private sector should be at the heart of the monetary policy design in Nigeria. The idea of
exercising tight measures in the process of constraining domestic credit should be given
attention and the conflict of curbing inflation and credit expansion to the domestic
economy can be resolved by introducing varieties of monetary tools and instruments.
Furthermore, the ratio of credit to GDP should be reviewed upwards to boost economic
growth.
43
The growth of the public investment has been reported to play a complimentary role on
the growth of the private sector in Nigeria. In light of these findings, effort should be
made to boost the development of public sector especially in the sectors that act as
catalyst to the growth of the private sector.
Policy prescription could be widened to include, in addition to targeting the volume of
credit to private sector the terms on which banking sector advances are extended to
private investors. This is directly related to the cost of funds dilemma in the sense that
governments in developing countries pursue policies with a view to make loans
expensive in the process of restricting domestic credit. The negative impact of real
interest rate on private investment poses very important qualitative implications for
financial sector efficiency. The monetary authority needs to be proactive in the
management of interest rate since user cost of capital has been established to be on the
high side in Nigeria in comparison to other developing countries. Efforts should be made
to see that interest rate do not derail the target of increasing investment to about 30
percent of GDP required to unleash a poverty reduction of at least 7 – 8 percent by 2015.
The stability of exchange rate is very expedient if the expected growth of the economy
through the private sector is to be achieved. To achieve exchange rate stability, efforts
should be intensified to wipe off all unofficial parallel markets or the so-called black
market since they facilitate not only faster depreciation of the Naira through round
tripping but also facilitate huge capital flight and illegal transfer of funds.
5.3 Conclusion
Empirical investigation reveals that macroeconomic policies like, interest rate policy,
exchange rate policy, the size of the public sector, domestic credit policy and the real
GDP growth plays a prominent role in the performance of private capital formation in
Nigeria. The results of both the dynamic short run model, impulse response and pair
wise Granger causality test revealed that domestic credit to the private sector plays a
more prominent role in influencing the growth of the private sector in Nigeria. This
study revealed that Nigeria’s private sector is still inertia and below the average for sub-
44
Saharan Africa and also below the 30 percent GDP growth ratio needed to reduce poverty
by half in Nigeria by 2015. Base on our findings, we agree that studies on private
investment in Nigeria still remain open for future researcher. One major limitation of this
work is its inability to incorporate investment under conditions of uncertainty. It is
recommended that further researchers in this area should look at this area. In addition,
carrying out the study under a structural vector autoregressive framework would
necessitate long run restrictions that would completely reflect the systemic behaviour of
the data generating process. So alternative model should be considered
45
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