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AN ECONOMETRIC ANAYLSIS OF THE EFFECTS OF
MONETARY POLICY ON NIGERIAN ECONOMY
BY
MBAMALU KINGSLEY KENECHUKWU
EC/2006/238
DEPARTMENT OF ECONOMICS
FACULTY OF SOCIAL SCIENCES
CARITAS UNIVERSITY AMORJI NIKE ENUGU
AUGUST 2010
TITTLE PAGE
AN ECONOMETRIC ANALYSIS OF THE EFFECTS OF
MONETARY POLICY IN NIGERIAN ECONOMY
A PROJECT SUBMITTED IN PARTIAL
FULLFILLMENT OF THE REQUIREMENT FOR
THE AWARD OF BACHELOR OF SCIENCE (B.SC)
DEGREE IN ECONOMICS
BY
MBAMALU KINGSLEY KENECHUKWU
EC/2006/238
DEPARTMENT OF ECONOMICS
FACULTY OF SOCIAL SCIENCES
CARITAS UNIVERSITY AMORJI NIKE ENUGU
AUGUST 2010
APPROVAL PAGE
This is to certify that this research work was carried out
by KinsleyMadumalu Kenechukwu with the registration
number EC/2008/238 on the effects of monetary policy on
Nigerian Economy and has been supervised and found
worthy of acceptance in partial fulfillment of the requirement
for the award of Bachelor of Science (B.Sc) degree in
Economics department caritas University Amorji Nike Enugu.
……………......
Dr. F.O. Asogwa
............................
Date
Supervisor
……..................
Barr. P.C. Onwudinjo
HOD Economics Department
….………….........
Date
…………………..
Prof. Umeh
Dean of Faculty
……………………
Date
…………………
External Examiner
………………………
Date
DEDICATION
This work is dedicated to the sacred heart of Jesus ever merciful
and unbeatable for super abundant prosperity, protection and
provision on the pursuit of my programme, also to my loving
parents, relations, friends and well-wishers.
ACKNOWLEDGEMENT
I hereby pronounce my gratitude to all who on their own
effort contributed to the success of this work. Indeed I lack words
to appreciate my supervisor Dr. Asogwa who deductively gave me
an appreciable supervision without grudges. Mr Ojike’s contribution
towards this work is ever significant and appreciated.
My propound gratitude goes to my parents Mr and Mrs Moses
Mbamalu for their immeasurable assistance both financially and
otherwise. To my sisters I say thank you.
I will not fail to thank friends like Elizabeth Nwando Mokwe for
contributing to this research work. To my well wishers i say thank
you all.
Mbamalu Kingsley Kenechukwu
Economics Department
ABSTRACT
This study aimed at analyzing through econometric methodology the
effects of monetary policy in Nigeria economy. To meet the above
objective, output growth was chosen as the dependent variable
while real exchange rate, real interest rate and inflation was chosen
as the independent variable. The ordinary least square was used in
the regression estimation. From the empirical result, we realized
that the entire explanatory variables are insignificant in the t-test,
but in f-test we rejected the null hypothesis and conclude that the
slope coefficient are not simultaneously equal to zero. We realizes
from the battery test that there is a co integration between the
explanatory band the dependent variables since its level of
stationarity are the same.
The policy implication of the result is that if monetary and banking
policies are effectively applied, it will be consistent with determining
the level of output growth in the economy
CHAPTER ONE
1.0
INTRODUCTION
One of the ways taken by all economy to make the
banking sector effective is the use of the monetary policy
introduced by the federal government and carried out by the
apex bank of the country. Apparently, the existence of
an
effective banking industry is vital to every economy and it
encourages economic growth and development via its role in
financial interdiction of funds supplies to deficit economic units
.This stimulates international trade, investment economic
growth as well employment growth as well as employment.
Monetary policy is one of the steps taken by every economy to
make the banking sector effective. Monetary and banking
policies are the sole responsibilities of monetary authority,
which comprises of The CBN for the initiation, implementation
and articulation of monetary system. The CBN carried out these
duties on behalf of the federal government according to CBN
decree 21 of 1991 and the banks and other financial institution
BOFIA A4, of 1991 as amended. The banks proposal on
monetary policy is subjective to the federal government.
The policies to be pursued is usually out in form of ‘’Audience’’
to all banks and other financial institutions. The guideline are
general in operation within a fiscal year but could be amended
on the course of the year. The CBN is equally empowered to
direct the activities of the financial institutions in other to carry
out certain duties in pursuit of approved monetary policy of
which penalties are prescribed for non-compliance with specific
provision of the guidelines.
1.1
BACKGROUND OF THE STUDY
Monetary policy affects financial and economic activities
over the year. In other to appreciate the effects of monetary
policy on the banking industry, it would be wise to move a
review of changing views of monetary influence. Usually when
the quantity of money changes in relation to financial activities
as viewed by FISHER (1932). Fisher, take other neoclassical
writer who held the view that in short run, money influences
real cash balances. According to him, when the money stock
increases, example;
An increase commodity prices since output and velocity
were fixes initially. He assumed that a rise in commodity prices
would exceed the increase in interest rate which was regarded
as a component of a firms operating cost. In the whole
analysis, rise in commodity prices will lead to an increase in a
firms profit, demand, money stock and deposit which will
eventually lead to a further rise in investment and commodity
price. The excess reserved for lending will decline with interest
rate, which was stocky earlier.
In the analysis of long-term transmission of monetary
influence, Fisher replaced ‘’Interest-Investment’’ channel with
‘’Real Cash Balance’’. He noted that when wealth rises due to
rise in money stock, people tend to reduce their cash balances
by purchasing goods and service. Since the velocity (v) and
output (y) in Fishers equation of exchange (MVPT) is fixed, the
risen money stock (M) cannot lead to increased holding of
goods and services but will lead to decline in prices level (P).
Keynes (1936) accepted the change in money supply relative
has both substitution and effect and considered investment to
be quite responsive to interest rates.
Keynes recommended price induce wealth effects, (i.e.
change in wealth due to change in yields). There are ranging
accounts by his interpreters about the extent he integrate them
in his general theory. Hence subsequent write to Keynes (i.e.
Keynesian or post Keynesian regards the cost of capital
(interest rate) as the main process by which changes in money
stock influence the economy. Thus the change in volume of
money alters the rate of interest. Usually approximated by the
long-term government bound rate, which affects investment
and consumption. Thus the link between wealth of private
sector and real sectors and consumption was analyzed by Piguo
(1974) and Patikin (1951) in form of ‘’real cash balance effect’’
According to them changes in quantities of money would affect
aggregate demand even if they did not alter interest rate. On
the other hand, credit rationing channel of monetary influence
explained how financial interdiction, would be controlled by the
market forces so as to ration the supply of credit by non-price
mechanism.
Thus an expansionary monetary policy would raise the force
of equity (i.e. reduce the yield on equities). The margin
between the market evaluation and cost of reproducing the
existing capital goods will stimulate new investment over those
goods. The non-monetarist argued that monetary policy is as
effective as fiscal policy as to determine total spending in the
economy in spite of their differences. It holds the following
views:
1. Movement in quantity of money is the most reliable
measure of monetary value.
2. Monetary authority can detect the movement in the stock
of money over time and business cycle.
3. Changes in stock of money are the primary determination
of total spending as emphasized on owen’s
economic
stabilization program.
4. Monetary impulse are transmitted to real economy
through an active price process or profit adjustment
process which affect many financial and real antes.
1.2
STATEMENT OF PROBLEM
Despite the establishment of Central Bank of Nigeria
(CBN) in 1958, banking industry remained both poor,
inadequate in terms of number, quality and variety of service
rendered. The establishment of CBN paved way for adoption
of monetary management by the banking industry. Just
incase any analyst is waiting in the wings to strike CBN for
its poor monetary policy performance. Ogwuma (1994:362)
offers a defense which says “A less than objective appraisal
of the CBN role in the Nigerian economy could interpret the
adverse macro-economic trend as evidence of failure on the
part of CBN. The key constraint are as follows:
1.3 AIMS AND OBJECTIVES OF THE STUDY
The following issues are the main aims and objectives of
carrying out this study;
a.
To identify the basic effects of monetary policy in order to
Achieve a sound financial system.
b.
To examine CBN monetary policy strategies
c.
To identify the best policy measure for economic stability.
1.4
SIGNIFICANT OF THE STUDY
The important of this study cannot be over emphasizes. It will
serve as a useful material to the monetary authority, bank
management and staff, customers, depositors, students and
indeed the entire economy. Never the less, it will add to the
volume of studies on the regards. The report shall be useful in
ensuring both monetary stability and a sound, safe and
profitable banking environment which will facilitate the pace for
the economic growth and development in Nigeria.
1.4
HYPOTHESIS / RESEARCH QUESTION
The following hypothesis has been formulated as a guide to the
conduct of the study. They should be tested based on the result
obtained from the regression coordinated. The hypotheses are;
b.
Ho: Variation in monetary policy does not significantly
affect output growth.
c.
H1: Variation in monetary policy significantly affect output
growth
i.e. Ho= Null Hypothesis
Hi= Alternative Hypothesis
1.5
SCOPE OF THE STUDY
Although there exist many factors affecting the operation of or
the performance of the banking industry, this study focuses on
the impacts of monetary policy on the performance of the
banking industry.
1.6
LIMITATION OF THE STUDY
It is quite believed that the study of nature needs sufficient
time, finance and materials. The inadequacy of those factors
poses enough limitations to this study. The limitations in
general include;
a.
Financial and monetary constraint
b.
Material constraint
c.
Time constraint
d.
Physical and Geographical constraint
1.8 DEFINITION OF TERMS
1.8.1 BANKING INDUSTRY
These refers to the total number of banks and other
financial institution who performs banking function such as
acceptance of deposits,. Issuing of credits/loan and keeping of
valuables.
Such
banks
include;
Merchant
Banks
and
Development Banks etc. The banking industry also consists of
the monetary authorities such as Central Bank of Nigeria and
other federal bodies whose duty includes the regulation of the
economy.
1.8.2 INSURANCE BANK
This implies those banks whose risk are insured with
Nigeria Deposit Insurance Commission ( NDIC)
1.8.3 BANK DISTRESS
This is the period in the banking industry when they
cannot be able to meet up its target such as; objectives,
dividends, staff remuneration in the economy as a whole. In
this period, a bank is said to be in the period of solvency, i.e. a
period when its debt ratio are high.
CHAPTER TWO
2.0
LITERATURE REVIEW
2.1 CONCEPTUAL FRAMEWORK
The concept and definition of monetary policy in the
previous year has no universal acceptability but however, the
term monetary policy according to CBN release on monetary
policy concept (2006) was defined as “Any policy measure
designed by the Federal Government through the CBN to
control cost availability and supply of credit. It also referred to
as the regulation of monetary supply and interest rate by the
CBN in order to control inflation and to stabilize the currency
flow in an economy.
However, in the CBN Briefs (Series No 97/03 June
1997).Monetary policy was defined as follows; The combination
of measures designed to regulate the value, supply and cost of
money on an economy in consonance with the expected levels
of the economic activities These imply that the excess supply of
money would result in excess demand for goods and services,
which would in turn cause a rise in price and determination of
balance of payment position. Monetary policy is one of the
available tools of macroeconomic objectives. The primary goals
of macroeconomic policy are price stability, external stability
and a satisfactory rate of output growth.
2.2
THEORITICAL LITERATURE
The effect of monetary policy is a central issue and has
attracted a lot of comments both in and out of the country. The
theories of monetary policy became success during 1930’s and
1940’s. It was believed that the well being of monetary policy in
stimulating recovery from depression was severely limited than
in controlling a boom and inflation. These views emerged from
the experience of Keynes in his theory. Keynes general view
holds that during depression, the CBN can increase the reserve
of commercial banks through a cheap monetary policy. They
can do so by buying securities and reducing the interest rate.
As a result of these, the ability of extending credit facilities to
borrowers increases. But the great depression tells us that in a
serious depression when there is pessimism among economic
actors, the success of such a policy is practically zero. In this
situation economic actors have no incentives to borrow even at
a reduced interest rate. In this case, the question of borrowing
for long-term capital needs does not arise in a depression when
the business activities are already at a low level.
The classical view of monetary policy is based on the
quantity theory of money. According to this theory, an increase
in the quantity of money leads to a proportional increase in
price level. The quantity theory of money is usually discussed in
terms of ‘’Equation Of Exchange’’ which is given by the
expression. P, denotes price level and Y denotes the level of
current real GDP. Hence, PY represents current;
’’NORMINAL GDP’’ M denotes the supply of money over
which the fed has some control and v denotes the “Velocity
Circulation’’ which is the average number of time a naira is
spent on final goods and services over the cause of the year.
The equation of exchange is an identity which states that the
current market value of all final goods and services… nominal
GDP must equal the supply of money multiplied by the average
number.
Monetarist view of monetary policy dates back in
1950’s, a new view of monetary policy called monetarism, has
emerged that disputes the Keynesian view that monetary policy
is relatively ineffective. Adherent of monetary argue that the
demand for money is stable and not sensible to change the
interest rates.
2.2.1 TYPES OF MONETARY POLICY
There are basically two kinds of monetary policy, they are:
a.
EXPANSIONARY MONETARY POLICY
An expansionary monetary policy is used to overcome
depression, recession and deflationary gap. When there is fall
in consumer goods and services, and in business investment
goods, a deflationary gap emerges. The Central Banks starts an
expansionary policy that eases the credit market conditions and
leads to an upward shift in aggregate demand. For this the CBN
purchases the government securities in the open market,
lowers the reserve requirements of member banks, lowers the
discount rate and encourages consumer and business credit
through selective credit measures.
b.
RESTRICTIVE MONETARY POLICY
This is the kind of monetary policy designed to reduce
aggregate demand (AD) and inflationary gap. Inflationary
pressure takes place as a result of risen consumer demand for
goods and services and there is also boom in business
investment. The CBN introduces the restrictive policy in order to
lower aggregate consumption and investment by increasing the
cost availability of bank credit.
2.2.2
AIMS AND OBJECTIVES OF MONETARY POLICY
There appear to be a general consensus that the single
most important objectives of monetary policy are the pursuit of
price stability. These recognition is perhaps derived from the
increasing rate at which many central banks around the world
are been given the exclusive power to control inflation and
stabilize domestic prices. The perspective which recognizes a
focus on inflation as the right approach to macroeconomic
stability receives a strong support from the analytical research
summarized in Fisher (1996) The study concludes that the
fundamental task of the currency and the following;
a.
Achievement of domestic price and exchange rate stability
b.
To control inflation
c.
Maintenance of healthy balance of payment position
d.
Promotion of rapid and
sustainable rate of economic
growth and development
e.
f.
Maintenance of macroeconomic stability
Development of a sound financial system
g.
To stabilize the naira exchange rate
h.
To maintain a high level of employment
2.2.3 INSTRUMENTS OF MONETARY POLICY
The policy instruments are of two kinds, they are;
i. Indirect Quantitative or General
ii. Direct Quantitative or Selective
These affect the levels of aggregate demand and through the
supply of money cost and availability of credit. The first
category includes the bank rate variations, open market
operation and changing reserve requirement. They are meant
to regulate the overall level of credit in the economy through
commercial banks. The selective credit control aims at
controlling specific kinds of credit.
They are discussed under the following;
a. BANK RATE POLICY:
The bank rate is the minimum lending rate of the Central
Bank at which it rediscounts first class bill of exchange and
government securities held by the commercial bank. When they
notice an inflationary pressure in the economy, it raises the
bank rate. In this period, borrowing from the CBN becomes
difficult and the commercial banks borrow less from it. Also the
commercial banks borrowers such as the individual and
industries borrow less from it due to an increase in its lending
rate.
On the contrary when prices are depressed, the central
bank lowers their bank rate making it cheaper to borrow from
them. The commercial banks also lower its lending rate making
it easy for businessmen to borrow money. In this case,
investment, output, employment, income and demand starts
rising.
b.
CHANGES IN RESERVE RATIO:
This system was first adopted in USA as suggestion by
the Keynes ‘’Treatise on Money’’ as a monetary devise. In every
organized financial economy, certain percentage of its total
deposit is kept in form of reserve fund its vaults and also a
certain percentage with the central bank. When prices are
rising, the central bank raises the reserve ratio. Bank is
required by law to keep more to the central bank. They lend
less when their reserve is reduced and they lend less. The
volume of investment, output and employment are adversely
affected.
On the contrary when the reserve ratio is lowered, the
commercial banks reserves rises, thereby lending more and the
economic activities are favored.
C.
OPEN MARKET OPERATION:
This refers to the sell and purchase of securities by the
central bank in the money market. When prices are rising and
there is a need of controlling them, the central banks sell
securities. The reserves of commercial banks are reduced and
they are not in a position to lend money to individual and
corporations. Further investments discouraged and the rise in
price are checked. On the contrary, when recessionary forces
starts in an economy, the central bank by securities from
business
communities
and
commercial
banks,
their
by
increasing their reserve. Investment, output, income and
aggregate demand rises.
D.
CREDIT CONTROLS:
Credit control are used to control specific types of credit
for particular Purposes. They usually take the form of changing
margin to control speculative activities in the economy or in
particular sectors in certain commodities and prices will start
rising. The central bank raises the margin requirement on
them. The result is that the borrowers are given less money is
loans against specified securities.
2.2.4 FISCAL POLICY
Fiscal policy which is national in scope, is a government
policy related to taxation and policy, which is concerned with
money supply, are the two most important components of a
government overall economic growth.
Keynesians considered fiscal policy the steeling wheel for
aggregate economy. They said classical economists with their
Laissez-Faire policy were trying to drive an economy without
any steering wheel. Fiscal policy can be either expansionary,
concretionary. It is expansionary or loose when taxation is
reduced or public spending is increased with the aim of
stimulating total spending in the economy known as aggregate
demand. On the other hand, fiscal policy is contraction or tight
when taxation is increased or public spending is reduced in
order to restrict demand and slow down the economy.
In Nigeria, the major fiscal policy instrument includes
changes in tax rate (on personal income, company income,
petroleum profits, capital gain, import duties as well as mining
rents, royalties etc) and government expenditure (recurrent
and capital).
2.2.5 DIFFERENCES BETWEEN MONETARY AND FISCAL POLICY
Monetary
and
fiscal
policy
is
both
instrument
of
macroeconomic stability but they have the following difference;
a. Monetary policy is typically implemented by a central bank,
while fiscal policy decision are set by the national
government
b. Both monetary and fiscal policy may be used to influence
the performance of the economy in the short run
c. Monetary policy uses instruments such as open market
Operation, Reserve ratio and moral Suasion etc for economic
stability while Fiscal policy uses taxation as the instrument of
economic stability.
d. Fiscal policy decisions undergo stages before a [approval in
the house while monetary policy decisions are approved by
the decisions of the CBN.
2.3
EMPIRICAL LITERATURE
The effects of monetary policy is a central issue in
macroeconomics, it has attracted comments from different
scholars both in developed and developing countries.
Ojo (1999) regards monetary policy during much of the 90’s as
generally restrictive, yet money supply (in this case M2)
increased persistently and well beyond the established growth
rate target.
Sanusi (2001) goes further back to a period (1959-1969) when
Nigeria’s monetary policy was deliberately expansionary during
this period. As the Treasury bill rate was reduced from 5% in
1960 to 3, 5% in 1964, M2 rose at an annual rate of 44%
between 1960 1994 and to 84% during 1968-1970.
2.3.1
MONETARY POLICY STRATEGY IN NIGERIA
Monetary policy strategy refers to how the central bank
carries out monetary policy actions (Mish kin, 2001). A central
feature of the difference forms of monetary policy strategy is
the choice of the numerical anchor. Thus each of the three
basic types of monetary policy strategy uses a different nominal
anchor. Monetary targeting involves the use of information
conveyed by the monetary aggregate to conduct monetary
policy. Monetary targeting occurs in at least two forms, first is
the rigid Friedman-type in which the chosen monetary
aggregate is kept on a constant growth rate path as the forces
of monetary policy. Second is the flexibility variety, which may
involve a set of monetary aggregate, each of which is allowed
to grow at different rate.
According to ‘’Odozi’’ the conduct of monetary policy goes
on three inter-related stages, namely:
a. Policy Formulation Stage
b. Implementation Stage
c. Review Stage
The frame work of this exercise is usually provided by law as
follows;
1.
The relationship between the central bank and the federal
Government
2.
Which arm of the government has the financial authority
on the policies initiated by the central bank?
CHAPTER THREE
3.1
THE MODEL
The information used in this economic phenomenon
empirically can be analyze in functional relationship between
output growth as the dependent variable while the
independent variable such as ;real interest rate, inflation and
real exchange rate.
Yg = F (RIR, INF, RER)…………………….(1.0)
Equation
1.0
shows
a
functional
relationship
between output growth and other independent variables
such as; interest rate, inflation rate and real exchange rate.
3.2. BATTERY TEST:
This
involves
Augmented
Dickey
Fuller
test
and
cointegrated test of error correction. Co-integration is an
econometric property of time series variables. If two or more
series are individual integrated in the time series sense but
some linear combination of them has a lower order of
integration then the series are first order integrated. If residuals
are random walk, we say that the two variables are not
cointegrated. Static regression of Xt or Yt, the test for cointegration is a test of null hypothesis that p=1 in the residual
and may be tested using Dickey-fuller statics. Regression using
the error correction form of the system, followed by a test of
the null hypothesis.
3.3 MODEL SPECIFICATION
The specification of econometric model is based on
economic theory and on any valuable information relating to
the phenomenon being studied. In doing this, there are three
specific steps involved.
i
Determination of dependent and independent variables
ii
Theoretical a prior expectation about the size and signs of
parameters of the function and;
iii
The determination of the mathematical form of model.
The model to be adopted will specifically be based on the
following functional relationship.
Yg = F(INT, INF, RER)……………………(3.0)
Equation 3.0 reads that output growth is a function of interest
rate, inflation rate and exchange rate. However, to hold firm
the influence of random variable, the equation is explicitly
transformed in to the following:
Yg=Bo+B1INT+B2INF+B3RER+Ui……………………. (3.1)
Where;
RIR: Real Interest Rate
INF: Inflation Rate
RER: Exchange Rate
BO: parameter Constant
Ui :Error Term
B1, B2, B3= Parameter Estimates
In equation 3.1 output growth is the dependent variable while
interest rate, inflation and exchange rate are the independent
variable.
3.4 METHOD OF ESTIMATION:
We estimate the parameters of the model after obtaining
the data. We use the statistical techniques of regression
analysis to obtain the parameter estimates. The techniques to
be used in analysis are; co-efficient of multiple determinations,
F-test, T-test and Durbin-Watson etc.
3.4.1 CO-EFFICIENCE OF MULTIPLE DETERMINATION (R2)
The R2 is used to test for the goodness of fit of the model
in the economy that is to say that the percentage of total
variation in dependent variable explained by the regression
plane. The R2 is expressed mathematically as
R2= B1∑1Y+B2∑2Y+B3∑3Y
3.4.2 T-TEST
The t-test is used to test for the significance or
reliability of the estimates regression co-efficient. If the
probability at which t-cal is significant in our regression result
for any independent variable is less or equal to our chosen level
of significant (0.05), we reject null hypothesis (Ho) which states
that the independent variable is not singular. This means
accepting the alternative hypothesis (Hi)
3.4.3 F-TEST
This is a test of the overall significance of the entire
regression plane. It will be used to find out whether the joint
impact of the explanatory variable actually has a significance
influence on the dependent variable.
3.4.4 STANDARD ERROR TEST
This is used to test for the presence of auto-correlation
that is the serial dependent of successive error term in
regression. Auto-correlation usually indicates that an important
part of the variation of the dependent variable has not been
explained, the problem of auto-correlation are usually detected
by Durbin-Watson (DW) statistics.
It is mathematically giving as:
DW=∑ (et (et-1)2)
(et)2
Where:
DW= Durbin-Watson
∑= Summation
et= present period error
et-1= Previous period error
3.4.5 TEST FOR MULTICOLLINEARITY
It is used to check for multicollinearity among the
explanatory variable the basis for the test being the correlation
matrix result using the correlation co-efficiencies between bases
of regression.
3.4.6 HETEROSKEDASTICITY
It is conducted to ascertain whether the error term Ui,
in the model of regression has a common or constant variance
while the heteroskedesticity test will be adopted.
3.5 SOURCES OF DATA
The sets of data used in this research where the time
series data obtained from the annual abstract of statistics of the
Nigeria Bureau of Statistics. Secondly, the sources of data
involved the empirical exploration of the study which is made
from the secondary data obtained from relevant government
institutional publication such as: Central Bank of Nigeria
Bulletin.
CHAPTER FOUR
4.1
BATTERY TEST
4.1.1
UNIT ROOT TEST
Variable
ADF*
1%
5%
10%
Yg
2.4432
-3.4758
-2.8811
-2.5771
Yg(D)
-5-4350
-3.4761
-2.8812
-2.5772
RIP
-2.4346
-3.4758
-2.8811
-2.5771
RIP (D)
-4.6402
-3.4761
-2.8812
-2.5772
RER
-1.9357
-3.4758
-2.8811
-2.5771
RER (D)
-3.9119
-3.4761
-2.8812
-2.5772
-2.8%
-3.4758
-2.8811
-2.5771
-4.1585
-3.4761
-2.8812
-2.5772
INF
WF(D)
FOR OUTPUT GROWTH (YG)
Hence ADF* is less than the critical value at 1%, 5% and
10%, therefore Yg is not stationary but ADF* first difference
(YgD) is stationary because it is greater than the critical value
at 1%, 5% and 10% at first difference of Yg.
i.e
ADF* < 1%, 5% and 10% at level form
ADF* > 1%, 5% and 10% at first difference.
FOR REAL INTEREST RATE (RIR)
Since ADF* is less than the critical value at 1%, 5% and
1% therefore ADF* (RIR) is not stationary at level form of but
ADF* (RIRD) is stationary because it is greater than the critical
value at 1%, 5% and 10% at first difference i.e
ADF* < 1%, 5% and 10% at level form
ADF* > 1%, 5% and 10% at first difference.
FOR REAL EXCHANGE RATE (RER)
Since ADF* is less than the critical value at 1%, 5% and
10% therefore (RER) ADF* is not stationary but ADF* (RERD)
is stationary because, it is greater than the critical value at 1%,
5% and 10%
i.e
ADF* < 1%, 5% and 10% at level form
ADF* > 1%, 5% and 10% at first difference.
FOR INFLATION (INF)
Since ADF* is less than the critical value at 1%, 5% and
10% therefore (INF) ADF* is not stationary but in first
difference of inflation, the (INF) is stationary because ADF* is
greater than the critical value.
i.e
ADF* < 1%, 5% and 10% at level form
ADF* > 1%, 5% and 10% at first difference.
IN SUMMARY:
Since the co-efficient of dependent variable (Yg) conforms
with the explanatory variable (RIP, RER and INF), we assume
that there is a co-integration between them. (Dependent and
Independent Variable).
4.1.2
JOHAMSON CO-INTEGRATION
Because the dependent variable and explanatory variable are of
the same level of stationality, by rule thumb, we suspect and
assumed that there is a co-integration between the explanatory
and dependent variable. For the reason above, the error
correction model (ECM-1) lag 1 is added as one of the
explanatory variable.
4.2
PRESENTATION OF REGRESSION RESULT
Dependent Variable :
Dyg
Method
:
Ordinary least square
Sample
:
3-152
Included Observation
Variable
:
150
Co-efficient
Std Error
t-Statistics
Prob
C
- 1.8164
2.4640
-0.737
0.4622
DRIR
- 0.94313
0.57882
-1.629
0.1054
DEF
- 0.47543
0.55997
-0.849
0.3973
DRER
0.0022846
0.057581
-0.040
0.9684
ECM
0.33128
0.053734
6.165
0.0000
R- Squared
=
0.233869
F- Statistics
=
6.1924
DW
2.71
=
RSS
=
127820.7022
for
8
variables
and
150
observations.
4.2.1
EVALUATION OF RESULT
Evaluation Based on Economic criteria
1.
Real Interest Rate (RIR): The coefficient of the
variable is -0.94313. This shows that a unit change in real
interest rate will bring about a 94% decrease in output
growth.
2.
Inflation (INF): The Coefficient of the variable is 0.47543. This shows that a unit change in inflation rate
will bring about a 47.5% decrease in output growth.
3.
Real Exchange Rate (RER): The coefficient of the
variable is -0.0022848 which shows that a unit change in
real exchange rate will bring about a 0% change in
output growth.
4.2.2
EXPECTED AND OBTAINED SIGN OF OUR
PARAMETER ESTIMATE
From the regression data the obtained result is expected to
follow and conform to economic aprior expectations of signs
and magnitude. Hence, the table is a summary of the outcome
of our parameters.
Variable
RIR
Expected
Obtained
Conclusion
Positive
Negative
Do
not
conform
INF
Positive
Negative
Do not
conform
RER
Positive
Negative
Do not
conform
4.3 EVALUATION OF STATISTICAL CRITERIA
Coefficient of determination R2: The R2 is 0.233869 on
approximately 23%. This shows that in the Longrun, the
Independent Variables were able to explain the variations in
output growth to the time of 23%. Therefore, the regression
line is poorly fitted.
4.3.1
TEST OF SIGNIFICANCE OF THE PARAMETER
A student t-test is used to determine the significance of the
individual parameter estimate in doing this, we compare the
calculated t-value in the regression result with the T-tabulated
at n-k degree of freedom (df) and at 5% level of significance.
The test will be carried out under the following hypothesis:
Ho: B = 0
not statistically significant
H1: B ≠ 0
statistically significant
Where B =
coefficient of the parameter
Ho = Null hypothesis
H1 =
Alternative hypothesis
Decision Rule: reject Ho if T-calculated > T – tabulated on
accept if otherwise.
n= 150, k = 8
n- k = 150 – 8 = 142 df, at 5% of significance.
Variable
T-
T-tabulated Decision
Conclusion
Calculated
RIR
- 1.629
- 1.960
Accept Ho Not significance
INF
- 0.849
- 1.960
Accept Ho Not significance
RER
- 0.040
- 1.960
Accept Ho Not significance
The result shows that real interest rate, inflation rate and real
exchange rate are statistically insignificant using the t-test.
4.3.2
F-test Statistics
This analysis shall be carried out under the following
hypothesis:
Ho: x1 = x2 : xk = 0 (all slope coefficient are zero)
Ho: x1 ≠ x2 ≠ xk ≠ 0 (all slope coefficient are not zero)
Decision Rule: Reject Ho if F-calculated is greater than Ftabulated, for the numeration degree of freedom is k-1 = 8 – 1 = 7
For the denomination:
Degree of freedom is n-k = 150 – 8 = 142 at 5% - level of
significance.
F- Calculated
F- Tabulated
6.1924
2.01
Decision
Reject Ho
From the result, we’ll observe that f- calculated exceed our ttabulated that is 6.1924 > 2.01. Thus, we reject the null
hypothesis and conclude that all slope coefficients are not
simultaneously equal to zero.
ECONOMETRIC TEST
Test for Autocorrelation
The underlying assumption is that the succession values of the
random variable (VI) are temporarily independent. The problem
is usually dictated with Durblin – Watson (DW) statistics.
Decision Rule 5
d* < dc reject Ho, presence of positive autocorrelation of first
order.
d* > (4-dl) reject Ho presence of negative autocorrelation of
first order
du < d* <du (4-du) < d* < (4-dl), test is inconclusive.
Where
dl = Lower limit
du = Upper limit
d* = durblin – Watson
dh = 1.637; 4-dl = 4 – 1.637 = 2.363
du = 1.832
d* = 2.71
2.71 > 2.63
That is d* > (4.dl) reject Ho, presence of negative
autocorrelation of first order.
CHAPTER FIVE
SUMMARY, CONCLUSION AND POLICY
RECOMMENDATION
5.1 SUMMARY
The empirical result shows that the real interest rate, real
exchange rate and inflation are not statistically significant using
the t-test which implies that it impacts in determining the rate
of economic growth to that monetary policy help in the growth
of total domestic output through varying the magnitude of
interest rate, real exchange rate and inflation.
The explanatory variables from the model is not
significant from the t-test. This means that it has minimal
impact in determining the output growth.
5.2
CONCLUSION
This study has been concerned with finding the effects of
monetary and banking policies on the economic growth. It is
necessitated by the fact that since the financial liberalization,
Nigeria has come to rely heavily on the use of monetary and
banking policy for stabilization of the economy.
5.3 POLICY RECOMMENDATION
The empirical result revealed that an effective monetary
policy is necessary for macro-economic stability for attainment
of economic growth and development. The following policy idea
is necessary:
*
Stabilizing the Naira Exchange Rate: Considering the
failure of various market oriented measure aimed at
stabilizing the naira exchange rate since the introduction
of SFEMFEM there is need for another approach as well as
modification of the easily manipulated method of foreign
exchange allocation.
*
Need for Effective Monetary Policy in order to take
adequate
measures
instability
and
in
order
streamlining
economic
macroeconomic
impediment
that
jeopardizes growth and development.
*
Need
for
restrictive
monetary
policy
to
overcome
inflationary gap. Restrictive monetary policy is one
designed to curtail aggregate demand: The economy
experiences inflationary presume due to rising consumer
demand for goods and services.
*
The government and institutions charged with economic
development
strategies
and
policy
function
should
evolvement to impact move on GDP by conceptuality on
the use of exchange rate, interest rate in order to raise
the level of investment.
BIBLIOGRAPHY
Akatu, O.(1963). Reflection on Macroeconomic: Otta: Papers
and Proceedings Press.
Anyanwakoro, M. (1999). Theory and Policies of Money and
Banking.
Uwani Enug:Hosanna Publication.
Attamah, N. (1999). Basic Principles of Economics. Coal Camp
Enugu: Marydan Publishers.
Campbel, (1982). Nigerian Economic Policy and Performance.
Oxford:
OxfordUniversity Press.
Ezeduji, F.O. (1994). Conduct of Monetary Management In
Nigeria.
Onitsha: Wema Publishers.
Friedman, (1963). The Role of Monetary Policy. Binmighan:
Wiglass
Publishers Inc.
Jhinghan, M.C. (1970). Advanced Economic Theory. Mayan
Vinan
Phase 1 Delhi: Vindu Publication.
Julius, A.A. (2004). Facing New Challenges In
Akume:
Jobies Press.
Banking.
Keynes, J.M. (1936).The General Theory of Employment
Interest and
Money. New York: Harcourt Brace Company.
Nwagbara, C.P. (2004). An Introduction Approach to Statistics.
Ogui
Road Enugu: J.F.C and Company Publication.
Ogikhonon H. and Dimowo F.A. (1997). The
Structure of the Nigerian Economy (1960-1997). Awka:
Joanne Educational Publishers Ltd.
Pandey, I.M. (1992). Monetary Policy Effects. London: MC
Graw Hill
Companies Inc.
Uchendu O.A. (1996). The Transmission of
Monetary Policy in Nigeria. Central Bank of Nigeria
Economic and Financial Review, Vol. 34. No 2, p. 608.
Udeabah, S.I. (2002). Economic Development and Planning
Ogui New
Layout Enugu: Lincon Press Nig.
JOURNALS
Ezeudoji, F.U. (1994). The effects Monetary Policy on the
Performance of Banking Industry In Nigeria. CBN
Economic and Financial Review. Vol. 32, Pp 3-10.
Million, F.C. (1971). A Monetary Theory of Income. Journal of
Political Economy. Vol. 2, PP3-8.
Odozi, V.A. (1997). The Management of Monetary and
Banking
Politics. CBN Billion. Vol. 21, PP 2-13.
Ojo,M.O. (1999). A review and Appraisal of the Monetary and
other
financials sector policy measures in the Federal
Government budget for 1999.CBN Bullion. Vol.24,pp2-8
Kingsley Mbamalu Pre-Estimation Tests
Yg in Level form
ADF Test Statistic
2.443255
1% Critical Value*
5% Critical Value
10% Critical Value
-3.4758
-2.8811
-2.5771
*MacKinnon critical values for rejection of hypothesis of a unit root.
Augmented Dickey-Fuller Test Equation
Dependent Variable: D(YG)
Method: Least Squares
Date: 07/02/08 Time: 05:32
Sample(adjusted): 1971:2 2007:4
Included observations: 147 after adjusting endpoints
Variable
Coefficient
Std. Error
t-Statistic
Prob.
YG(-1)
D(YG(-1))
D(YG(-2))
D(YG(-3))
D(YG(-4))
C
0.139647
-0.682706
-0.283627
0.107745
-0.209351
-5.799682
0.057156
0.105475
0.120342
0.114792
0.091720
2.445852
2.443255
-6.472677
-2.356831
0.938611
-2.282502
-2.371232
0.0158
0.0000
0.0198
0.3495
0.0240
0.0191
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
Durbin-Watson stat
0.438157
0.418233
25.76599
93607.96
-683.1322
2.046108
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
F-statistic
Prob(F-statistic)
-2.078707
33.78100
9.375948
9.498006
21.99196
0.000000
Yg first diff
ADF Test Statistic
-5.434964
1% Critical Value*
5% Critical Value
10% Critical Value
-3.4761
-2.8812
-2.5772
*MacKinnon critical values for rejection of hypothesis of a unit root.
Augmented Dickey-Fuller Test Equation
Dependent Variable: D(YG,2)
Method: Least Squares
Date: 07/02/08 Time: 05:06
Sample(adjusted): 1971:3 2007:4
Included observations: 146 after adjusting endpoints
Variable
Coefficient
Std. Error
t-Statistic
Prob.
D(YG(-1))
D(YG(-1),2)
-1.508504
-0.017261
0.277556
0.249365
-5.434964
-0.069220
0.0000
0.9449
D(YG(-2),2)
D(YG(-3),2)
D(YG(-4),2)
C
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
Durbin-Watson stat
-0.105450
0.162517
0.028634
-3.144329
0.805909
0.798978
26.36822
97339.63
-681.8369
1.986671
0.217713
0.160931
0.086912
2.225676
-0.484354
1.009855
0.329464
-1.412753
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
F-statistic
Prob(F-statistic)
0.6289
0.3143
0.7423
0.1599
-0.246164
58.81102
9.422424
9.545038
116.2626
0.000000
RIR in Level form
ADF Test Statistic
-2.436351
1% Critical Value*
5% Critical Value
10% Critical Value
-3.4758
-2.8811
-2.5771
*MacKinnon critical values for rejection of hypothesis of a unit root.
Augmented Dickey-Fuller Test Equation
Dependent Variable: D(RIR)
Method: Least Squares
Date: 07/02/08 Time: 06:23
Sample(adjusted): 1971:2 2007:4
Included observations: 147 after adjusting endpoints
Variable
Coefficient
Std. Error
t-Statistic
Prob.
RIR(-1)
D(RIR(-1))
D(RIR(-2))
D(RIR(-3))
D(RIR(-4))
C
-0.131051
-0.427578
-0.095073
0.117919
0.202999
-0.846172
0.053790
0.090773
0.097613
0.095683
0.083064
0.838656
-2.436351
-4.710395
-0.973984
1.232399
2.443891
-1.008962
0.0161
0.0000
0.3317
0.2199
0.0158
0.3147
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
Durbin-Watson stat
0.275264
0.249564
8.666040
10589.14
-522.9546
2.074885
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
F-statistic
Prob(F-statistic)
0.146122
10.00378
7.196661
7.318719
10.71073
0.000000
RIR first Diff
ADF Test Statistic
-4.640216
1% Critical Value*
5% Critical Value
10% Critical Value
-3.4761
-2.8812
-2.5772
*MacKinnon critical values for rejection of hypothesis of a unit root.
Augmented Dickey-Fuller Test Equation
Dependent Variable: D(RIR,2)
Method: Least Squares
Date: 07/02/08 Time: 06:26
Sample(adjusted): 1971:3 2007:4
Included observations: 146 after adjusting endpoints
Variable
Coefficient
Std. Error
t-Statistic
Prob.
D(RIR(-1))
D(RIR(-1),2)
D(RIR(-2),2)
D(RIR(-3),2)
D(RIR(-4),2)
C
-1.274227
-0.275005
-0.457409
-0.378222
-0.140832
0.145146
0.274605
0.248422
0.207007
0.151740
0.083501
0.726718
-4.640216
-1.107007
-2.209628
-2.492566
-1.686597
0.199728
0.0000
0.2702
0.0288
0.0138
0.0939
0.8420
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
Durbin-Watson stat
0.744050
0.734909
8.769329
10766.16
-521.1056
2.014765
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
F-statistic
Prob(F-statistic)
-0.036507
17.03211
7.220625
7.343239
81.39623
0.000000
RER in level form
ADF Test Statistic
-1.935670
1% Critical Value*
5% Critical Value
10% Critical Value
-3.4758
-2.8811
-2.5771
*MacKinnon critical values for rejection of hypothesis of a unit root.
Augmented Dickey-Fuller Test Equation
Dependent Variable: D(RER)
Method: Least Squares
Date: 07/02/08 Time: 06:15
Sample(adjusted): 1971:2 2007:4
Included observations: 147 after adjusting endpoints
Variable
Coefficient
Std. Error
t-Statistic
Prob.
RER(-1)
D(RER(-1))
D(RER(-2))
D(RER(-3))
D(RER(-4))
C
-0.059402
-0.454578
-0.083051
0.124708
0.245808
11.18332
0.030688
0.083475
0.092002
0.091881
0.081823
7.124801
-1.935670
-5.445646
-0.902716
1.357269
3.004141
1.569633
0.0549
0.0000
0.3682
0.1769
0.0032
0.1187
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
Durbin-Watson stat
0.265850
0.239816
42.34452
252821.2
-756.1594
2.104725
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
F-statistic
Prob(F-statistic)
-0.713878
48.56663
10.36952
10.49157
10.21177
0.000000
RER first diff
ADF Test Statistic
-3.911900
1% Critical Value*
5% Critical Value
10% Critical Value
-3.4761
-2.8812
-2.5772
*MacKinnon critical values for rejection of hypothesis of a unit root.
Augmented Dickey-Fuller Test Equation
Dependent Variable: D(RER,2)
Method: Least Squares
Date: 07/02/08 Time: 06:20
Sample(adjusted): 1971:3 2007:4
Included observations: 146 after adjusting endpoints
Variable
Coefficient
Std. Error
t-Statistic
Prob.
D(RER(-1))
D(RER(-1),2)
D(RER(-2),2)
D(RER(-3),2)
D(RER(-4),2)
C
-1.013373
-0.523197
-0.651157
-0.523952
-0.194341
-0.478337
0.259049
0.237127
0.200730
0.150007
0.083647
3.509024
-3.911900
-2.206397
-3.243941
-3.492853
-2.323342
-0.136316
0.0001
0.0290
0.0015
0.0006
0.0216
0.8918
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
Durbin-Watson stat
0.746868
0.737827
42.24881
249894.7
-750.6638
2.026644
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
F-statistic
Prob(F-statistic)
0.133836
82.51272
10.36526
10.48787
82.61418
0.000000
INF in Level form
ADF Test Statistic
-2.889871
1% Critical Value*
5% Critical Value
10% Critical Value
-3.4758
-2.8811
-2.5771
*MacKinnon critical values for rejection of hypothesis of a unit root.
Augmented Dickey-Fuller Test Equation
Dependent Variable: D(INF)
Method: Least Squares
Date: 07/02/08 Time: 05:40
Sample(adjusted): 1971:2 2007:4
Included observations: 147 after adjusting endpoints
Variable
Coefficient
Std. Error
t-Statistic
Prob.
INF(-1)
D(INF(-1))
D(INF(-2))
D(INF(-3))
D(INF(-4))
C
-0.159010
-0.431646
-0.055416
0.178571
0.231637
3.206346
0.055023
0.089500
0.096661
0.095059
0.082139
1.278776
-2.889871
-4.822875
-0.573304
1.878531
2.820062
2.507355
0.0045
0.0000
0.5674
0.0624
0.0055
0.0133
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
Durbin-Watson stat
0.306057
0.281449
8.862487
11074.66
-526.2496
2.122901
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
F-statistic
Prob(F-statistic)
0.124014
10.45506
7.241492
7.363550
12.43732
0.000000
INF first Diff
ADF Test Statistic
-4.158461
1% Critical Value*
5% Critical Value
10% Critical Value
-3.4761
-2.8812
-2.5772
*MacKinnon critical values for rejection of hypothesis of a unit root.
Augmented Dickey-Fuller Test Equation
Dependent Variable: D(INF,2)
Method: Least Squares
Date: 07/02/08 Time: 05:06
Sample(adjusted): 1971:3 2007:4
Included observations: 146 after adjusting endpoints
Variable
Coefficient
Std. Error
t-Statistic
Prob.
D(INF(-1))
D(INF(-1),2)
D(INF(-2),2)
D(INF(-3),2)
D(INF(-4),2)
C
-1.116252
-0.465840
-0.630752
-0.493846
-0.198782
0.199372
0.268429
0.244289
0.205992
0.152264
0.082994
0.742116
-4.158461
-1.906923
-3.062029
-3.243355
-2.395129
0.268653
0.0001
0.0586
0.0026
0.0015
0.0179
0.7886
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
Durbin-Watson stat
0.758801
0.750187
8.964538
11250.81
-524.3200
2.041916
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
F-statistic
Prob(F-statistic)
0.040068
17.93578
7.264658
7.387272
88.08672
0.000000
---- PcGive 8.00, copy for meuller
----
---- session started at 9:59:10 on 2nd July 2010 ---Data loaded from: kingsl~1.wks
DYg = diff(Yg, 1);
DRIR = diff(RIR, 1);
DINF = diff(INF, 1);
DRER = diff(RER, 1);
EQ( 1) Modelling Yg by OLS
The present sample is: 2 to 152
Variable
Coefficient
Std.Error
t-value
t-prob
75.298
14.297
5.267 0.0000
-4.1188
0.81245
-5.070 0.0000
-1.8433
0.87806
-2.099 0.0375
-3.4756
0.78810
-4.410 0.0000
PartRý
Constant
0.1615
RIR
0.1514
RIR_1
0.0297
INF
0.1190
INF_1
-1.3272
0.84293
-1.574 0.1176
-0.16278
0.083619
-1.947 0.0535
0.070684
0.084248
0.839 0.4029
0.0169
RER
0.0256
RER_1
0.0049
Rý = 0.420829
F(6, 144) = 17.439 [0.0000]
å =
47.2574 DW = 0.645
RSS
=
321589.6766
for
7
variables
and
151
observations
ECM added to database
ECM = Residual values of equation 1
EQ( 2) Modelling DYg by OLS
The present sample is: 3 to 152
Variable
Coefficient
Std.Error
-1.8164
2.4640
t-value
t-prob
PartRý
Constant
0.0038
-0.737 0.4622
DRIR
-0.94313
0.57882
-1.629 0.1054
-0.10830
0.58233
-0.186 0.8527
-0.47543
0.55997
-0.849 0.3973
-0.054925
0.56078
-0.098 0.9221
-0.0022848
0.057581
-0.040 0.9684
0.028962
0.058141
0.498 0.6192
0.33128
0.053734
6.165 0.0000
0.0184
DRIR_1
0.0002
DINF
0.0051
DINF_1
0.0001
DRER
0.0000
DRER_1
0.0017
ECM
0.2111
Rý = 0.233869
F(7, 142) = 6.1924 [0.0000]
å =
30.0024 DW = 2.71
RSS
=
127820.7022
for
8
variables
and
150
observations
Testing for Error Autocorrelation from lags 1 to 2
Chiý(2) = 22.091 [0.0000] ** and
12.089 [0.0000] **
F-Form(2, 140) =
Error Autocorrelation Coefficients:
Lag 1
Coeff.
Lag 2
-0.4394 -0.09951
Normality test for Residual
The present sample is: 3 to 152
Sample Size
150
Mean
0.000000
Std.Devn.
29.191403
Skewness
-1.201842
Excess Kurtosis
4.377773
Minimum
-139.326914
Maximum
83.302943
Normality Chiý(2)=
28.817 [0.0000] **
Testing for Heteroscedastic errors
Chiý(14) = 9.9004 [0.7694]
and F-Form(14, 127) =
0.64105 [0.8262]
V01=DRIR
V02=DRIR_1
V03=DINF
V04=DINF_1
V05=DRER
V06=DRER_1
V07=ECM
Heteroscedasticity Coefficients:
Constant
V05
V01
V02
V03
V04
Coeff.
602.4
-1.352
-39.1
-1.382
-54.72
0.6238
t-value
0.846
3.351
-0.02723
-0.619
-0.02764
-
0.1186
V06
V07
V01ý
V02ý
V03ý
V04ý
Coeff.
0.9564
-0.7571
1.493
-1.232
-
0.2156
0.897
-0.6802
-
0.4957
t-value
0.6409
0.9463
-0.122
0.3046
V05ý
Coeff.
V06ý
V07ý
0.04762 -0.004178
t-value
1.814
-0.1378
RSS = 6.48822e+008
0.0861
1.26
å = 2260.27
Test of Functional Form
Chiý(35) = 30.033 [0.7066]
and F-Form(35, 106) =
0.75817 [0.8238]
V01=DRIR
V02=DRIR_1
V04=DINF_1
V05=DRER
V06=DRER_1
V07=ECM
V03=DINF
Heteroscedasticity Coefficients:
Constant
V01
V02
V03
V04
607.3
118.7
-13.48
121.5
-29.26
V05
Coeff.
-3.054
t-value
0.2801
2.763
1.678
-0.1344
1.648
-
-0.436
V06
V07
V01ý
V02ý
V03ý
V04ý
Coeff.
11.12
-1.621
-9.83
-0.1758
-
0.2374
-0.3008
-1.333
-0.02697
-
-1.773
t-value
1.692
2.011
-0.2808
V05ý
V06ý
V07ý V02 * V01 V03 *
V01 V03 * V02
Coeff.
19.37
0.02008
0.1525
-14.79
-
0.7401
0.4523
1.717
-1.238
-
-9.02
t-value
1.631
0.07008
-0.6706
V04 * V01 V04 * V02 V04 * V03 V05 * V01
V05 * V02 V05 * V03
Coeff.
-14.03
-1.261
-10.75
1.39
1.498
1.53
t-value
0.2316
-0.8743
-0.1248
-0.9605
0.4243
0.4615
V05 * V04 V06 * V01 V06 * V02 V06 * V03
V06 * V04 V06 * V05
Coeff.
0.8547
4.616
-0.5509
5.417
-
0.1509
0.6532
-0.2152
0.7434
-
0.08071
t-value
0.3304
1.01
0.4705
V07 * V01 V07 * V02 V07 * V03 V07 * V04
V07 * V05 V07 * V06
Coeff.
0.2592
0.6311
3.536
0.9924
1.57
0.3617
2.497
0.5632
0.1139
t-value
1.876
2.165
0.4805
RSS = 5.55587e+008
å = 2289.41