In order to examine
properly, the effect of commercial bank credit on industrial growth in Nigeria from
1980-2009, the researcher put in place some macro economic variable that
assumed to determine the relationship above. Such variables are credit to
industrial sector, exchange rate, inflation rate (independent) variables while
manufacturing sector output MASO (dependent) variable.
Having stated the
objectives, hypothesis and model of this study in the previous chapter, thus,
below are the empirical results presentation.
TABLE1: PRESENTATION OF EMPIRICAL RESULTS BY (OLS)
|
VARIABLES
|
CO-EFFICIENT
|
STD. ERROR
|
T- VALUE
|
PRO
|
|
C
|
9113.5
|
1631.5
|
5.586
|
0.000
|
|
CRIS
|
0.0012341
|
0.0050664
|
0.244
|
0.8097
|
|
INTR
|
172.30
|
92.237
|
1.868
|
0.0746
|
|
INIFR
|
83.785
|
30.752
|
2.723
|
0.0121
|
|
EXR
|
-30.617
|
26.475
|
-1.156
|
0.2594
|
|
R2=
|
0.67701
|
|
|
|
|
F-statistic=
|
(5,24)=12.052
|
|
|
|
|
D.W st= 1.22
|
|
|
|
|
However, the table above represents the relationship
between commercial bank credits as a function of credit to industrial sector
(CRIS), interest rate (INTR), and exchange rate (EXR). Thus, viewing the
results, it is clear that the constant variable (i.e the manufacturing sector
output) shows positive and stood at (9113.5) percent. This simple implies that
if all the independent variable is being hold constant, then the Dependent
variable (ie MASO) will be held at 9113.5 percent although, the statement above
is not our interest, our concerned here is to examine a-priori and statistical
influence of each of the independent variables to the dependent variable which
follows below.
The co-efficient of credit to industrial sector (CRIS) shows
that there exist a positive relationship between CRIS and the dependent
variable (MASO). The implication is that, a unit increase in (CRIS), will
equally increase the growth of industrial sector in Nigerian, while a decrease
in value and volume in credit to industrial sector will in the same proportion
and credit o industrial sector will in the same proportion and in the same
direction decrease the industrial growth rate in Nigeria by (0.12%) percent.
Thus this, series is in line with the a–priori assumption, but shows
statistical significant to the study.
The co-efficient of interest rate (INTR) has a positive
relationship with the manufacture sector output (MASO the dependent variable).
In other words, an increase in interest rate in the economy will increase also
the growth rate of industrial sector by
(172.30) percent while on the other way round, a decrease in niters rate
will also being about decrease in the industrial sector by the same percent (172.30). But thus, however is not in line
with a priori theory in economy because, it is expected that any units of drop
in interest rate will reduce the rate at which commercial bank loans money to
investor’s and if this happens, then money for expansions which in the long-run
will yield to employment, industrial growth and finally industry to Gross Domestic Product (GDP) meanwhile in as
much the interest rate was not confirm
to the theoretical a priori, the statistically criterion show that interest rate, is
significant to the study within the period under review.
The co-efficient of inflation rate (INFR) shows a positive
linear relationship with the Dependent variable (MASO). This means that as
inflation rate increase and decrease, so the industrial sector growth rate
increase and decrease in the same direction but in the same proportion.
In other words, an increase inflation, will increase
industrial sector by (83.725) percent during the period under review
(1980-2009). Meanwhile, viewing this from the a-priori assumption, we can agree
that this series is in confirm with the theoretical a-priori and also
statistically significant to the study.
The co-efficient of exchange rate (EXR) shows that there
exist a negative linear relationship with the dependent variable (MASO). The
negative relationship implies that an increase in the value of naira to other
currency, will decrease the industrial growth rate in Nigerian by (-30.617)an
decrease in the exchange rate (i.e the
value of naira to foreign currency, will increase the Nigerian industrial
growth from 1980-2009 period of observation. This is in line with the a-priori
assumption because the economy industrial growth and development theory stated
that for a country industrial growth to be realized that country currency
(exchange rate) to other foreign currency must be devaluated. So base on that, we agree that
exchange rate negative relationship to this study is current.
However, all along, we have been examining the theoretical
relationship (a-priori) of the independent variable up on the dependent
variable. Now we will view the statistical criteria of those variable in this
study.
The R-square (i.e the co-efficient of determination)
stood at 0.67701 percent, this show statistical significant. Implying that 67
percent variation in industrial growth of Nigeria is explained by the whole
independent variable or by (Commercial Bank credit, CRIS, INTR, INFR and EXR).
While35% out 100% were as a results of other factor’s that were not included in
the model but were captured by the Error term of the model. Thus, the
f-statistic also shows significant as it stands at 12.052 greater than the f –tabulated
value. Meanwhile the Durbin Watson statistics show that, there is no presence
of auto correlation in the model as it value stood at (1.22%) percent.
Table 2: TESTING
THE HYPOTHESIS USING THE T-STATISTIC
|
VARIABLES
|
T-cal
|
T-tab
|
OBSERVATION
|
DECISION RULE
|
|
CRIS
|
0.244
|
1.318
|
T-cal< T-tab
|
Accept the null hypothesis
|
|
INTR
|
1.868
|
1.318
|
T-cal> T-tab
|
Reject the null hypothesis
|
|
INFR
|
2.723
|
1.318
|
T-cal > T-tab
|
Reject the null
hypothesis
|
|
EXR
|
-1.156
|
1.318
|
T-cal< T-tab
|
Accept the null hypothesis
|
The above table is use to
test the significant of each variable to the hypothesis stated in chapter one
of this study base on the statistical decision rule. The Decision rule stated
that Null hypothesis should be rejected once the T-calculated is greater than
the T-tabulated, while the Null hypothesis should be accepted if otherwise;
with the chosen level of significance. The level of significance chosen in this
study is 10% level. Therefore, base on the above statement and table we examine
those hypothesis below for decision taking.
HYPOTHESIS
Null: there is no significant relationship between commercial
bank credit and industrial sector growth in Nigeria.
Base on the observation from
table 4.2 above we reject the Null hypothesis and accept the alternative
hypothesis that say’s that there exist a significant relationship between
commercial bank credit and industrial sector growth in Nigeria and the
ingratitude is very high ranking 67% percent as given by the R2 .